Article

T.R.I.C.K.‐Tire/Road Interaction Characterization & Knowledge - A tool for the evaluation of tire and vehicle performances in outdoor test sessions

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Abstract

The most powerful engine, the most sophisticated aerodynamic devices or the most complex control systems will not improve vehicle performances if the forces exchanged with the road are not optimized by proper employment and knowledge of tires. The vehicle interface with the ground is constituted by the sum of small surfaces, wide about as one of our palms, in which tire/road interaction forces are exchanged. From this it is clear to see how the optimization of tire behavior represents a key-factor in the definition of the best setup of the whole vehicle.Nowadays, people and companies playing a role in automotive sector are looking for the optimal solution to model and understand tire's behavior both in experimental and simulation environments. The studies carried out and the tool developed herein demonstrate a new approach in tire characterization and in vehicle simulation procedures. This enables the reproduction of the dynamic response of a tire through the use of specific track sessions, carried out with the aim to employ the vehicle as a moving lab.The final product, named TRICK tool (Tire/Road Interaction Characterization and Knowledge), comprises of a vehicle model which processes experimental signals acquired from vehicle CAN bus and from sideslip angle estimation additional instrumentation. The output of the tool is several extra "virtual telemetry" channels, based on the time history of the acquired signals and containing force and slip estimations, useful to provide tire interaction characteristics. TRICK results can be integrated with the physical models developed by the Vehicle Dynamics UniNa research group, providing a multitude of working solutions and constituting an ideal instrument for the prediction and the simulation of the real tire dynamics.

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... 1 process of generation of tyre forces and moment. This pragmatic approach leads to a very straightforward model, which generally shows a good agreement with experimental evidence and -combined with MF, which is currently able to take into account physical phenomena connected to tyre inflation pressure, temperature and wear [43][44][45][46] -can also handle the presence of large camber angles and steering speeds. On the same lines, the two-regime [33] formulation consists of a relatively novel description that mimics the dual nature of the tyre by a series system behaving as a spring at low rolling speed and as a damper at high speeds [4,33,34]. ...
... This should be ascribed to the presence of the dissipative term in Eqs. (44), which acts as an additional damping effect. As a result, the contribution of the initial conditions to the total deflection of the bristles decreases exponentially in time (or over travelled distance), determining a different rate of convergence to the steady-state behaviour. ...
... In any case, input-to-state stability estimates in the form of Eqs. (24) may be derived directly from the closed-form expressions in (44), since the dissipative curvatures ϕ x (s), ϕ y (s) are, by definition, always nonnegative. ...
... The described comparison is shown in Figures 7-9. To replicate experimental operating conditions, where tyre dynamic behaviour is usually unknown, tyre parameters initially set in the EKF estimator were not the same ones adopted in simulation, whose parameters in their turn were identified with the already cited procedure that is available in experimental context [39,42]. The above-mentioned methodology is able to guarantee that the differences between the estimation accuracy achieved in simulation and in experimental scenarios are minimum. ...
... Cornering stiffnesses K 1 and K 2 decrease over time due to tyres heating, particularly relevant for rear stiffness K 2 . This behaviour is coherent with expectations and with the offline analyses performed with [39,42], and will result on a slight increase of side-slip angle lap over lap. In the test shown, there are no observability issues, since the tyre is excited on all its working range, and the vehicle is never on steady state for long periods. ...
... If a simplified elasto-kinematics formulation has to be employed, the estimator will have a slight loss of accuracy. The Magic Formula parameters have been obtained from the vehicle acquisitions through the methodology shown in [39,42]. The estimator is designed to work on the widest range of vehicle operating conditions: tyres working over their adhesion peak, with high combined interaction, on sloped and banked road, with tyre characteristics changing over time due to the thermodynamics variations and wear. ...
Article
This work describes the development of a vehicle state estimator, designed to be employed onboard in real-time, based on the data acquisitions already available within the vehicle CAN bus infrastructure. The proposed estimation algorithm, taking into account the suspension elasto-kinematics, the longitudinal, lateral and combined dynamics of the tyres as well as the aligning interaction torques at the ground, represents at the current stage a significantly complete tool, since it also provides an estimation of road slope and banking angles, generalising the adoption of the presented vehicle model even on highly inclined roads. A further advantage of the presented estimator consists of its capability to identify in real-time and with a good level of accuracy the tyre/road interaction physical characteristics in terms of grip and cornering stiffness.
... Models' parameterization global aim is to reproduce the experimental data as faithfully as possible, trying to bridge the gap between the simulation outputs and the sensors' measurements. For this specific case study, an average performance sport vehicle with open differential has been used to carry out a track test session, with specific instrumentation including: [14] with transmitter fitted to a wheel rim, sending pressure and temperature data samples over an RF link, pressure accuracy < |10 mBar| and temperature accuracy < |3 • C| Signals such as velocities and accelerations represent the input for TRICK tool [15], developed with the aim to increase the amount of information that track sessions can provide and to collect data useful to identify the parameters of tire interaction models used in simulations. The tool is based on a quadricycle model which, starting from a reliable vehicle description (including geometric and inertial parameters) processes experimental signals acquired from the vehicle CAN bus and, in this specific case, from the additional instrumentation mentioned before (S-Motion, IMU, encoders). ...
... The tool is based on a quadricycle model which, starting from a reliable vehicle description (including geometric and inertial parameters) processes experimental signals acquired from the vehicle CAN bus and, in this specific case, from the additional instrumentation mentioned before (S-Motion, IMU, encoders). The output provided is a sort of ''virtual telemetry'', constituted by the acquired signals and by further channels, including wheel slip indices (slip ratio and slip angle, evaluated on the basis of kinematic congruence equations), tire interaction forces (evaluated basing on dynamic equilibrium equations), tire inclination angles and rotation frequencies [15][16][17]. Once tire-road interaction characteristics have been properly evaluated, these have been used as input for tire models calibration process, which can be summarized in three fundamental steps: the first one is related to the pre-processing of the experimental data (which allows to discern useful information contained in the acquired data and to eliminate the outliers); the second one concerns the identification of the standard MF micro-coefficients in a specific range of temperature, pressure and wear; the third step aims at the calibration of the additional multiphysical analytical formulations, taking into account of the entire dataset and thus extending the tire model towards thermal and degradation phenomena. To do this, an advanced tire thermal model has been calibrated by means of experimental data and used to evaluate in real time circumferential and lateral temperature distribution of the different layers in which the tire is discretized along the radial direction. ...
... A thinner tire does not imply, for this type of tires and vehicle, a significant variation of temperature and pressure in a so short maneuver. What has been stated for temperature and pressure cannot be said for tire dynamics, since, as shown in 15 To sum-up, tread's thinning typically has a double influence on tire system; the first one is linked to thermodynamics, since a lower volume of viscoelastic material deforming generates different temperature and pressure evolution, the second one is directly linked with tire dynamics, since forces and slips are influenced by friction and stiffness variation towards tread thickness. For the analyzed short maneuver, the most marked effect is undoubtedly the second one, while the first one is quite negligible. ...
Article
The handling behavior of a vehicle is one of its most important properties because of its relation to performance and safety and to its deep link with concepts such as “over-steer” or “under-steer”. Tire-road interaction models play a fundamental role in the vehicle system modelling, since tires are responsible for the generation of forces arising within contact patches, fundamental for both handling and ride/comfort. Among the models used to reproduce such forces, Pacejka’s Magic Formula (MF) is undoubtedly one of the most used ones in real-time automotive simulation environments because of its ability to fit quite easily a large amount of experimental data, but its original formulation did not take into account of the tire thermodynamics and wear conditions, which clearly affect tire and vehicle dynamics and are not negligible, especially for high level applications, such as motorsport competitions. Exploiting a multiphysical tire model, which consists in an evolved version of the standard MF model (MF-evo), and a vehicle model properly validated throughout experimental data acquired in outdoor testing sessions carried out with an industrial partner, the current work presents a study on vehicle behavior variation induced by thermodynamic and wear parameters, defining a series of metrics to analyze and show results. One of the elements of interest on which the focus is placed is the possibility to highlight how under-over-steering behavior of a car changes according to different thermodynamic states of tires; to do this, a commercial software VI CarRealTime has been used to perform a series of objective steady-state maneuvers and long runs, exploiting the logic of a lap time optimizer.
... To solve the above open issues, in this paper, the authors propose a control architecture responsible for the longitudinal dynamics of the vehicle chassis, composed of two ADAS functionalities-namely Adaptive Cruice Control (ACC) and Autonomous Emergency Braking (AEB)-in addition to the blueAntilock Braking System (ABS), which is road-grip aware in the sense that it is able to properly regulate the vehicle motion on the base of the on-line estimation of the road friction coefficient per single tire, based on the T.R.I.C.K. (Tire Road Interaction Characterization & Knowledge) methodology [23]. In particular, the in-vehicle friction estimation module, starting from the acceleration, angular speed and steering angle data acquirable from widely-adopted sensors, allows us to calculate in runtime the kinematics and the dynamics of all the tires, in terms of interaction slips and forces, respectively. ...
... Furthermore, starting from the global quantities referring to the vehicle total behavior, it is currently possible to evaluate even the kinematic and dynamic states of its sub-components, as tires. The developed algorithm, based on the T.R.I.C.K. methodology described in [23], allows us to evaluate in a specifically dedicated on-board module the fundamental kinematic and dynamic quantities for the tire characterization in real time, starting from the experimental signals available within the vehicle CAN bus (Controller Area Network) and s-motion measurement or, as the case in exam, employing a specific set of sensors pre-configured on the vehicle. Such methodology also allows us to evaluate the potential of an estimation process in terms of tire interaction curves, such as in [48]. ...
... The originally designed model, described in [23], referred to a quadricycle vehicle fully described from the dynamic point of view. Since the study under analysis aims at simulating the emergency braking manoeuvres et similia, involving only the vehicle longitudinal dynamics, the model can be simplified considering its plane of symmetry xz (ISO reference system). ...
Article
Full-text available
In recent years, autonomous vehicles and advanced driver assistance systems have drawn a great deal of attention from both research and industry, because of their demonstrated benefit in reducing the rate of accidents or, at least, their severity. The main flaw of this system is related to the poor performances in adverse environmental conditions, due to the reduction of friction, which is mainly related to the state of the road. In this paper, a new model-based technique is proposed for real-time road friction estimation in different environmental conditions. The proposed technique is based on both bicycle model to evaluate the state of the vehicle and a tire Magic Formula model based on a slip-slope approach to evaluate the potential friction. The results, in terms of the maximum achievable grip value, have been involved in autonomous driving vehicle-following maneuvers, as well as the operating condition of the vehicle at which such grip value can be reached. The effectiveness of the proposed approach is disclosed via an extensive numerical analysis covering a wide range of environmental, traffic, and vehicle kinematic conditions. Results confirm the ability of the approach to properly automatically adapting the inter-vehicle space gap and to avoiding collisions also in adverse road conditions (e.g., ice, heavy rain).
... Based on the TRICK tool, [8] which calculates the tire forces and slips starting from the data acquired in the car and from the vehicle parameters, with the aim of characterizing the behavior of the tire from data acquired on the road, avoiding the use of laboratory instruments with the advantage of reducing costs and obtaining data that are truly sensitive to road conditions. The system uses dynamic equilibria for the calculation of forces and kinematic relations for the calculation of slips. ...
... The system requires the following parameters: -vehicle mass and geometry; -elasto-kinematic parameters of vehicle suspensions; -correction values of the sensors obtained with appropriate procedures [8] ; -Pacejka parameters of the equipped tire. ...
... The described procedure calculates the axle forces from the bicycle model, these are then split between the sides, proportionally to the vertical load. This equation set has proven to be robust and accurate in most of cases [8], but specific situations where the estimated forces are less close to those of the validation model have been identified. ...
Chapter
Real-time knowledge of the tire dynamic behaviour is a fundamental prerequisite for using electronic controls in vehicle dynamics, which are rapidly increasing their complexity and, consequently, the required accuracy of the measurement systems. Some examples of new advances from the automotive industry are driver assistance (ADAS) and roadside units (RSU), receivers installed on the road infrastructure capable of collecting vehicle data, with the purpose of monitoring the status of the road. Moreover, thanks to the low connection latency offered by the 5G network, interconnected vehicles will be able to passively communicate and apply autonomous driving strategies with the aim of avoiding road accidents [1]. Typically, the tire characterization is performed offline using the data acquired thanks to expensive test benches and instrumentation, subsequently, the parameters of specific models, analytic Pacejka [2] or Dugoff [3], formulations, multibody [4, 5] or FEA-based [6, 7] are identified. For the identification of tire models’ parameters directly using the signals acquired by means of on-board measurements, additional sensors not usually available in standard vehicles, such as the dynamometer hubs, are required. The UniNa vehicle dynamics research group has developed a tool called TRICK [8], able to estimate the physical quantities necessary to fully understand and characterize the tire dynamic behaviour from the CAN channels normally available in telemetry. The forces developed by the tires are derived from the equilibrium equations, while the tire slips are obtained from the kinematics equations [9]. The present paper describes the development stages which have been necessary to permit the TRICK tool working in real time, thus providing useful data regarding the vehicle and tire states to both the driver and the control systems. Issues related to the on-board instrument calibration procedure, noise filtering and interface development are specifically described.
... Other ap-proaches adopt Kalman filters to calculate tire-road interaction forces [6][7][8]. In [9] the T.R.I.C.K. tool is presented, which uses a 8 degrees-of-freedom (DOF) rear-wheeldrive vehicle model to obtain a fairly good estimation of the tire-road interaction forces. However, only the global mass of the vehicle is considered, without looking in detail at sprung mass and unsprung mass. ...
... The availability of such information is not a difficult task especially in motorsport environments, and it allows to introduce a significantly improved accuracy in the estimation of the tire-road longitudinal forces. Also, a different approach is used when compared to [9], i.e. individual free body diagrams are studied and exploited in the present formulation, which leads to different results than [9] even when only the global mass of the vehicle is considered. Additionally, in most road vehicles a further distinction can be made between the unsprung mass of the front wheels and the rear wheels, e.g. for a rear-wheel drive architecture, the rear wheel assembly includes additional components for housing the axle shafts. ...
... The availability of such information is not a difficult task especially in motorsport environments, and it allows to introduce a significantly improved accuracy in the estimation of the tire-road longitudinal forces. Also, a different approach is used when compared to [9], i.e. individual free body diagrams are studied and exploited in the present formulation, which leads to different results than [9] even when only the global mass of the vehicle is considered. Additionally, in most road vehicles a further distinction can be made between the unsprung mass of the front wheels and the rear wheels, e.g. for a rear-wheel drive architecture, the rear wheel assembly includes additional components for housing the axle shafts. ...
Chapter
Full-text available
In vehicle dynamics, the determination of the tire-road interaction forces plays a fundamental role in the analysis of vehicle behavior. This paper proposes a simple yet effective approach to estimate longitudinal forces. The proposed approach: i) is based on equilibrium equations; ii) analyses the peculiarities of driving and braking phases; iii) takes into account the interactions between vehicle sprung mass and unsprung mass. The unsprung mass is often neglected but that might lead to significant approximations, which are deemed unacceptable in performance or motorsport environments. The effectiveness of the proposed approach is assessed using experimental data obtained from a high performance racing car. Results show that the proposed approach estimates tire longitudinal forces with differences up to 10% when compared against a simpler formulation which uses only the overall mass of the vehicle. Therefore the distinction among vehicle sprung and unsprung masses, which is likely to be an easily obtainable piece of information in motorsport environments, is exploited in this approach to provide significant benefits in terms of longitudinal force estimation, ultimately aimed at maximizing vehicle performance.
... To enhance the accuracy of the tire models obtained from such indoor testing, this work devises an experimental setup and analysis procedure for characterizing the steady state tire behavior using racetrack data acquired from an instrumented race vehicle. Similar works are available in existing literature, in [2] a methodology is proposed to evaluate the tire performances by adopting a vehicle model for the estimation of the wheel forces. However, the proposed procedure strongly depends on different vehicle properties such as the aerodynamic coefficients and the tire rolling resistance, and the reported equations are valid only under steady state conditions. ...
... The wheel forces measured by the [GM] method at the front suspension were expressed in the tire axis system by adopting a rotation matrix around the zv-axis, as reported in [2]. The rotation matrix was evaluated for each observation from the wheel steering angle at the ground (δ w ) which, in turn, was calculated from the measured suspension travel (lSD) and steering pinion angle (δsp) as reported in the next paragraph. ...
... Moreover, thanks to EU-standardized labels [7] that help compare performances in areas such as wet grip, fuel efficiency, and noise, informed users can easily choose the safest and most economical and comfortable tires. The intensification of the development of electric cars, which is related to decisions made by the European Parliament The idea itself is not new; until now, artificial neural networks and decision trees have mainly been used to identify the parameters of a tire model [14]and the influence that the conditions of pressure, load, and speed have on tire uniformity measurements [15]. These techniques have also already been used for the estimation of tire-road interactions [16] and to model tires for vehicle system dynamics and control prediction [17] or to analyze the forces acting on the tire [18,19]. ...
... The obtained dependencies and data collected in real time make it possible to react quickly in a production environment, e.g., by immediately withdrawing from using the material causing defects or by introducing corrections to the process, which has a significant impact on reducing production costs by eliminating time loss, minimizing material losses, and reducing the amount of scrap. The use of the described The idea itself is not new; until now, artificial neural networks and decision trees have mainly been used to identify the parameters of a tire model [14] and the influence that the conditions of pressure, load, and speed have on tire uniformity measurements [15]. These techniques have also already been used for the estimation of tire-road interactions [16] and to model tires for vehicle system dynamics and control prediction [17] or to analyze the forces acting on the tire [18,19]. ...
Article
Full-text available
This article presents the current state and development directions of the tire industry. One of the main requirements that a tire must meet before it can leave the factory is achieving values of quantities describing uniformity at a defined level. Of particular importance areconicity and the components of the tire with the greatest impact on its value. This research is based on the possibility of using an ANN to meet contemporary challenges faced by tire manufacturers. In order to achieve a satisfactory level of prediction, we compared the use of a multi-layer perceptron and decision trees XGBoost, LightGbmRegression, and FastTreeRegression. Based on data analysis and similar examples from the literature, metrics were selected to evaluate the models’ ability to solve regression problems in relation to the described problem. We selected the best possible solution, standing at the top of the features covered by the criterion analysis. The proposed solutions can be the basis for acquiring new knowledge and contributions in the field of the computational analysis of industrial data in tire production. These solutions are characterized by the required accuracy and efficiency for online work, and they also contribute to the creation of the best fit elements of complex systems (including computational models). The results of this study will contribute to reducing the volume of waste in the tire industry by eliminating defective tire parts in the early stages of the production process.
... First, a tool called T.R.I.C.K. (Tire-Road Interaction Characterization & Knowledge) [10] is presented. This tool had been developed with the aim to process data acquired from experimental test sessions, estimating tires interaction forces, slip indices and inclination angle; the output of this tool is a sort of "virtual telemetry" which can be used to feed the thermoRIDE, a thermodynamic model [11][12][13] which provides in output the lateral and circumferential temperature distributions, in all the different tire layers: tread at three different depths, carcass and inner liner. ...
... T.R.I.C.K. Tool T.R.I.C.K. [10] is a tool developed with the idea of using the vehicle as a moving laboratory; indeed, it can be employed during experimental outdoor activities in order to increase the amount of information that track test sessions can provide and to evaluate data useful to identify the parameters of the most common tire interaction models [15] deeply used in simulations. The main advantages deriving from the use of this methodology are: ▪ Tire characterization without test benches; ▪ Analysis on data collected in real operative working conditions; ▪ Objective analysis of track session results and performance evaluation; ▪ Tire models' parameter identification. ...
... The Industry 4.0 paradigm is based on an assumption that technical inspections be performed at every stage of the production process as well as several times throughout the product life cycle. For the same reason, the use of computational analysis methods is on an upward trend [13][14][15][16][17][18]. Until now, artificial neural networks have been applied to identify tire model parameters [13] and identify tire parameters [14,15,16], or to analyze the forces acting on the tire [17,18]. ...
... For the same reason, the use of computational analysis methods is on an upward trend [13][14][15][16][17][18]. Until now, artificial neural networks have been applied to identify tire model parameters [13] and identify tire parameters [14,15,16], or to analyze the forces acting on the tire [17,18]. ...
Chapter
The article presents actual challenges faced by tire manufacturers and contemporary industry. Directions of development of methods for detecting and eliminating defects generated in the tire production process were discussed, with particular emphasis on methods using artificial intelligence. An exemplary classification of tire defects is presented. It was noted that a solution to reduce the amount of tire waste due to exceeding the uniformity limits is needed. Quantities describing tire uniformity were characterized. In the frame of the main purpose of the research, it was checked whether the model based on a traditional artificial neural network (with one hidden layer) can predict the value of conicity (output variable) based on five input variables. To solve this problem, the authors used the Multi-Layer Perceptron (MLP) - machine learning method, due to its ability to train non-linear models in “almost real time”. The parameters of the network structure were determined to guarantee the achievement of root-mean-square error (RMSE) for the training set data at a very low, satisfactory level. The authors see the high potential of using the built model in the mass production of tires. Application of mentioned model will minimize the waste of time and tire components scraps, and also will actually improve the quality of the final product.
... In this way, the dual nature of the tyre is mimicked by a series system that behaves as a spring at low rolling speed and as a damper at high speeds. This pragmatic approach leads to a very straightforward model, which generally shows a good agreement with experimental evidence and -combined with MF, which is currently able to take into account physical phenomena connected to tyre inflation pressure, temperature and wear [45][46][47] -can also handle the presence of large camber angles and steering speeds. However, two major disadvantages of the single contact point models consist in that they neglect nonstationary phenomena connected to the tread rubber flow inside the contact patch, i.e. the transient of the bristles, and do not come with important dynamical properties, like, e.g., asymptotic and input-to-state stability, that are appetible for control applications. ...
... The validation of the model should also be conducted to assess its ability to correctly replicate the steady-state tyre characteristics at large spin slips. This will require ad-hoc experiments or procedures [46], as well as a more detailed model for the contact patch shape as a function of the camber angle. In this context, it would be also interesting to perform a comparison against the forces and moment predicted using a full-version of Pacejka's MF. ...
Article
Full-text available
This paper presents a novel tyre model which combines the LuGre formulation with the exact brush theory recently developed by the authors, and which accounts for large camber angles and turning speeds. Closed-form solutions for the frictional state at the tyre-road interface are provided for the case of constant slip inputs, considering rectangular and elliptical contact patches. The steady-state tyre characteristics resulting from the proposed approach are compared to those obtained by employing the standard formulation of the LuGre-brush tyre models and the exact brush theory for large camber angles. Then, to cope with the general situation of time-varying slips and spins, two approximated lumped models are developed that describe the aggregate dynamics of the tyre forces and moment. In particular, it is found that the transient evolution of the tangential forces may be approximated by a system of two coupled ordinary differential equations (ODEs), whilst the dynamics of the self-aligning moment may described by combining two systems of two coupled ODEs. Given its stability properties and ease of implementation, the lumped one may be effectively employed for vehicle state estimation and control purposes.
... Due to the intrinsic empirical formulation and the amount of additional multiphysical quantities to be accounted for, the accuracy and the robustness of the model's output is directly linked to the degree of completeness and quality of the acquired data. The tyre-road interaction data could present different levels of accuracy, so that the measured or estimated quantities would need an additional step necessary to remove the physical inconsistencies and the evident data outliers, before being employed for the model calibration purposes [40]. ...
... The vehicle has been equipped with a significant amount of instrumentation to evaluate the kinematics and the dynamics at each corner, as well as the thermodynamics of each tyre: The kinematic and dynamic quantities concerning a single corner can be reliably acquired and estimated [26,28,40]. Compound and carcass temperatures, inner air pressure and wear level are among the additional inputs of the MF-evo model, and they can be provided by means of both additional sensors and physical predictive models. ...
Article
To cite this article: Aleksandr Sakhnevych (2021): Multiphysical MF-based tyre modelling and parametrisation for vehicle setup and control strategies optimisation, Vehicle System Dynamics, ABSTRACT Starting from the earliest phases of design of the vehicle and its control systems, the understanding of tyres is of fundamental importance to govern the overall vehicle dynamics. A properly charac-terised tyre-road interaction model is essential to achieve a reliable vehicle dynamics model on which more design variations can be studied directly in simulation environment optimising both cost and time. The possibility to count on computationally efficient and reliable formulations represents nowadays a great advantage, and the multiphysical Pacejka's Magic Formula (MF-evo) tyre model presented is one of the best trade-off solutions to meet the strict real-time requirements and to reproduce multiphysical variations of the tyre dynamic behaviour towards temperature, pressure and wear effects. A specific methodology has been developed to characterise and to identify the MF-evo parameters with a high grade of accuracy and reliability directly from experimental data. The proposed technique is based on a pre-processing procedure to remove non-physical outliers and to cluster the data, which allows to optimise the multidimensional parameterisation process. To the purpose of validation of the parametrisation routine, data from a motorsport case, exceptionally difficult to reproduce in simulation due particularly significant variations of the tyre dynamics during a single test, have been employed demonstrating the MF-evo model potential and robustness. ARTICLE HISTORY
... The parameters c 1 and c 2 were obtained via fitting equation (4) by using the Matlab function ''lsqnonlin'' on an extensive amount of experimental data, with the assumption µ = 1. For the purposes of fitting, the values of lateral and vertical forces for front and rear axles were obtained through the TRICK tool [31], [32]. Fig. 3 shows the results of the fitting, and Table 1 reports the obtained parameters. ...
... +ĉ 1R,k (µ + 1) + F zR µa Rĉ2R,k (µ + 1) β k −r k u a R 2F zF µc 1F c 2F (µ + 1) −δ k +β k +r k u a F F zF,0 Mu −δ k +β k +r k u a F + c 1F (µ + 1)+ F zF µc 1F c 2F (µ + 1) F zF,0 Mu −δ k +β k +r k u a F + c 1F (µ + 1) B 41 = − 2F z1 µa F c 1F c 2F (µ + 1) −δ k +β k +r k u a F F zF,0 J −δ k +β k +r k u a F + c 1F (µ + 1) + F zF µa F c 1F c 2F (µ + 1) F zF,0 J −δ k +β k +r k u a F + c 1F (µ + 1)The terms in equation (60) include the expressions given above for B31 andB 32 , usingĉ 1F,k ,ĉ 2F,k ,ĉ 1Rk ,ĉ 2R,k instead of, respectively, c 1F , c 2F , c 1R , c 2R . DIBIASE received the bachelor's degree in mechanical engineering from the Second University of Naples, Italy, in 2016, and the M.Sc. ...
Article
Full-text available
Vehicle sideslip angle is a key state for lateral vehicle dynamics, but measuring it is expensive and unpractical. Still, knowledge of this state would be really valuable for vehicle safety systems aimed at enhancing vehicle safety, to help to reduce worldwide fatal car accidents. This has motivated the research community to investigate techniques to estimate vehicle sideslip angle, which is still a challenging problem. One of the major issues is the need for accurate tyre model parameters, which are difficult to characterise and subject to change during vehicle operation. This paper proposes a new method for estimating vehicle sideslip angle using an Extended Kalman Filter. The main novelties are: i) the tyre behaviour is described using a Rational tyre model whose parameters are estimated and updated online to account for their variation due to e.g. tyre wear and environmental conditions affecting the tyre behaviour; ii) the proposed technique is compared with two other methods available in the literature by means of experimental tests on a heavy-duty vehicle. Results show that: i) the proposed method effectively estimates vehicle sideslip angle with an error limited to 0.5 deg in standard driving conditions, and less than 1 deg for a high-speed run; ii) the tyre parameters are successfully updated online, contributing to outclassing estimation methods based on tyre models that are either excessively simple or with non-varying parameters.
... The channels provided by TRICK tool [4], a model-based procedure developed by UniNa for tire characterization from vehicle data, work as an input for the identification. The big amount of available data needs to be classified with the aim to separate the effects linked with the different events that occurred during the acquired track session, making to the single coefficient possible to vary inside a limited range, assuming the numerical value that enables the optimal reproduction of the effects to which they are destined inside Pacejka's formulation. ...
... In the following plots the results of pure interaction coefficients identification are presented and discussed; the lines are Pacejka Magic Formula output and they have been compared with the experimental points obtained by TRICK procedure [4]. ...
Chapter
One of the most diffused tire/road interaction models, widely employed in simulation applications, is the Pacejka’s Magic Formula (MF) [1, 2]. It is a semi-empirical model able to fit full scale test data, characterized by a large number of coefficients, often called micro-parameters, grouped basing on physical considerations in order to create specific functions, called macro-parameters. MF model coefficients provided by tire manufacturers are generally not fully representative of the behaviour of tires in contact with road. This is due to the testing conditions employed to identify model coefficients: tests are usually performed on a specific rolling bench or on a flat-trac (Tire testing system, commercialised by MTS Systems Corporation. It applies forces and motions to a tire running on a continuous flat belt.), that keep the tire in contact with a steel or an abrasive paper covered belt. The impossibility to test the tires under real working conditions causes unavoidable approximation errors, mainly due to differences in thermal exchanges and wear phenomena [3] between tire/belt and real tire/road contact. Therefore it is commonly necessary to modify the MF coefficients in order to improve the bench data correlation and to be able to validate vehicle models with data coming from experimental tests. The aim of the developed tool, called TRIP-ID (Tire/Road Interaction Parameters IDentification), is to provide an innovative procedure to identify the Pacejka coefficients basing on the experimental tests carried out measuring global vehicle data during outdoor track sessions. In the presented application, the procedure collects and processes the data provided by TRICK tool [4], allowing to eliminate the outlier points, to discriminate wear and thermal phenomena, taking into account the combined slip condition and the effects of vertical load and camber angle on the global grip. The innovative approach proposed can be useful to reproduce in real time simulation applications the feedback that high performances tires give to sport vehicle drivers, whose interest and skills are focused on keeping them in the optimal thermal range. The coupling of a properly modified MF model with a thermal and with a friction model can provide a reliable simulation and analysis instrument for drivers, carmakers and tire producers.
... The experimental tests have been conducted on a high performance sport vehicle which has been fully parametrized as concerns its physical and geometrical parameters in order to apply procedures useful to completely characterize its dynamical behavior [25]. For this purpose a set of pure lateral and combined longitudinal and lateral manoeuvres have been performed before starting the test campaign. ...
... The described methodologies can find a very useful and wide application in the field concerning the estimation of tire/road interaction forces, and in particular of tire cornering stiffness [40]- [42], based on the processing of vehicle data instead of the expensive, uncomfortable and often not fully reliable tire test benches [25,43]. The tire forces evaluation procedure requires, among the input channels, the measurement of the vehicle sideslip angle, performed by means of a specific instrumentation, quite bulky and not equipped onboard as a standard vehicle sensor. ...
... Measured data need to be post-processed to define tyres kinematic state and the forces in the contact patch. Specific algorithms have been developed with such aim, based on vehicle models [26], advanced filters [27] or confidential procedures. ...
... Plot a complex and multi-dimensional function as Pacejka's one in a wide range of multi-graphs, able to highlight the interactions among tyre working variables, often hard to be determined at a glance, comparing curves with track and bench tyre data [26]. Identify MF micro-, macro-coefficients and scaling factors defining their research range, convergence criteria, error minimization algorithms and eliminating outliers and physical incongruences from track and bench tyre data. ...
Article
Tyres play a key role in ground vehicles' dynamics because they are responsible for traction, braking and cornering. A proper tyre-road interaction model is essential for a useful and reliable vehicle dynamics model. In the last two decades Pacejka's Magic Formula (MF) has become a standard in simulation field. This paper presents a Tool, called TRIP-ID (Tyre Road Interaction Parameters IDentification), developed to characterize and to identify with a high grade of accuracy and reliability MF micro-parameters from experimental data deriving from telemetry or from test rig. The tool guides interactively the user through the identification process on the basis of strong diagnostic considerations about the experimental data made evident by the tool itself. A motorsport application of the tool is shown as a case study.
... Such complex structure is necessary for supporting the interaction forces with the road. In literature there are different models able to describe tyre behavior both based on an physical approach [1][2][3][4][5][6][7][8][9][10][11][12] and based on an empirical one [13][14][15][16] . In order to parametrize physical based models [1][2][3][4][5][6][7][8][9][10][11][12] , it is very significant the knowledge about the thickness of the different tyre layers. ...
... In literature there are different models able to describe tyre behavior both based on an physical approach [1][2][3][4][5][6][7][8][9][10][11][12] and based on an empirical one [13][14][15][16] . In order to parametrize physical based models [1][2][3][4][5][6][7][8][9][10][11][12] , it is very significant the knowledge about the thickness of the different tyre layers. This aspect is particularly important as it concerns the physical models describing the tyre thermal behavior [8][9][10] , the tyre grip behavior [1,2,6,7] and the tyre wear [11] . ...
Article
In this work is exploited the possibility to use two optical techniques and combining their measurements for the 3D characterization of different tyres with particular attention to the tyre's section. Electronic Speckle Pattern Interferometry (ESPI) and Laser Scanner (LS) based on principle of triangulation have been employed for investigating and studying the tyre's section and 3D shape respectively. As case studies two different racing tyres, Michelin S9H and Pirelli Diablo respectively, have been considered. The investigation has been focused at the aim to evaluate and measure the section's components in order to add to the 3D model obtained by Laser Scanning accurate information about the different layers along through the tyres sections. It is important to note that the assessment about the different layers along the section is a very difficult task to obtain by visual inspection or classical microscopy and even with the LS. Here we demonstrate that the different layers can be easily highlighted and identified by mean of the ESPI.
... As underlined by [17], the thermal real effects on tyres are often underestimated; nevertheless, the Hc impact can be very meaningful on modern thermodynamic models implementing it. Thus, its determination is an important open research question, which cannot be neglected in the complex evaluation of tyre behaviour. ...
Article
Full-text available
Featured Application: Advanced thermo-mechanical tyre models, real time vehicle dynamic simulation , heat transfer calcualtion. Abstract: Tyres are one of the most important elements of a vehicle because they are the link to the road and have a huge impact on traffic-related pollution. Knowing their behaviour, thus being able to use them at their best and reducing their wear rate, is one of the means of improving their lifetime, which means decreasing traffic environmental impact. In order to understand how tyres behave and to predict the real-time tyre-road coefficient of friction, which is strongly influenced by the temperature, in the last few years several complex thermo-mechanical models of heat transfer inside the tyre have been developed. However, in the current state of the art of the literature and practice, there is still an important parameter regarding such models that is not deeply studied. This parameter is the heat transfer coefficient between the tyre and the road at the contact patch, which usually is considered as a constant. The current research paper allows understanding that such an approximation is not always valid for all of the speeds and tyre loads of city and race cars; instead, it is developed an equation that, for the first time, calculates the real-time, dynamic tyre-road heat transfer coefficient, taking into account the tyre's travelling speed and the footprint length. The equation results are in good agreement with the empirical values coming from the literature and permit understanding how much such a parameter can vary, depending on the tyre use range. The formulation is simple enough to be easily implemented in existing thermodynamic tyre models without requiring meaningful computational time.
... The forces and moments necessary to accelerate, brake and handle an automobile pass through this component; therefore, an accurate model of tire behavior is key to achieve a reasonably precise vehicle dynamics model. From the widespread magic formula of Pacejka [12] or simpler models, such as the Brush Model [13], to the most recent integrated methodologies [14][15][16], the study of tire dynamics is a fertile source of research and advancements. Most of the results are based on the detailed modelling of material mechanics or direct experimental extrapolation. ...
Article
Full-text available
The automotive industry is experiencing increasing competition, and vehicle development is becoming increasingly complex. Manufacturers must therefore be able to rapidly compare the outcomes of experimental tests carried out under different conditions. Robust simulation tools that can adjust for external factors have the potential to save a significant amount of time. In this regard, the purpose of this paper is to propose a method for evaluating the effect of asphalt temperature on tire and vehicle lateral dynamic performance, based on empirical data. Because rubber is a viscoelastic material, its properties are heavily influenced by the operating conditions. Therefore, a corrective algorithm must be created to enable the transfer of results obtained from tests carried out under different asphalt temperature conditions to a reference temperature of 25 °C. This article presents an analytical model that accurately describes this phenomenon, as well as the methods employed to generalize and optimize the model. Generalizability represents a crucial aspect of this research, as the model must be widely applicable across several vehicle categories while requiring minimal data to perform the corrections effectively. Finally, the analytical compensatory tool was incorporated into a MATLAB bicycle model to update the numerical transfer function measurements that describe the vehicle’s dynamic behavior during experimental maneuvers. These results indicate that modest data is needed to achieve good levels of accuracy, making the model and vehicle dynamics implementation promising.
... Concerning the analytical model approach, Lenzo et al. [6] successfully estimate the SAT from a Brush tire model. First, their method uses the TRICK tool (Tyre/Road Interaction Characterization & Knowledge) [7] to estimate the lateral forces. Then, the parameters of the Brush model are optimized to fit the estimation and are used to compute the SAT. ...
Conference Paper
Full-text available
Virtual sensing has attracted the interest of car makers and automotive service providers, owing to its cost-effective advantages, capacity to extract valuable insights from car data and its significance in enhancing the reliability of Advanced Driving Assistance Systems (ADAS). For instance, accurate virtual sensing of tire forces and torques can help adapt and improve the control strategies embedded in the vehicle's active safety systems. This paper deals with tire Self-Aligning Torque (SAT) estimation, an inherent parameter for identifying the limits of the vehicle at an early stage to prevent skidding. We present a data-driven approach to estimate the right and left front SATs, using a Neural Network (NN) model. The estimator takes directly existing in-vehicle signals and does not rely on expensive and unpractical sensors, which makes it cost-efficient and fast. Simulation results based on a high-fidelity vehicle model show a good performance of the chosen NN to estimate the SATs while considering the combined slip and road friction change.
... As explained before, the correct longitudinal velocity estimation is a fundamental goal of vehicle dynamics for different practical applications. For example, in the motorsport field, the knowledge of vehicle longitudinal velocity is essential to understanding the behavior dynamics because, thanks to this quantity, it is possible to estimate the tire slip and, therefore, to combine it with interaction forces [55], to explore and to understand the thermal state of the tire as well; however, in several championship rules, equipping the vehicle with sensors, such as the optical sensor s-motion, to measure such quantity is forbidden, so the estimation is the only way to reach this aim. Moreover, real-time knowledge of the correct vehicle state is needed not only to properly feed the low-level control systems commonly used in commercial cars, such as ABS, ESP and traction control, but also to allow for the development of more accurate advanced driver assistance systems (ADAS) up to fully autonomous driving scenarios. ...
Article
Full-text available
Vehicle dynamics control systems have a fundamental role in smart and autonomous mobility, where one of the most crucial aspects is the vehicle body velocity estimation. In this paper, the problem of a correct evaluation of the vehicle longitudinal velocity for dynamic control applications is approached using a neural networks technique employing a set of measured samples referring to signals usually available on-board, such as longitudinal and lateral acceleration, steering angle, yaw rate and linear wheel speed. Experiments were run on four professional driving circuits with very different characteristics, and the vehicle longitudinal velocity was estimated with different neural network training policies and validated through comparison with the measurements of the one acquired at the vehicle’s center of gravity, provided by an optical Correvit sensor, which serves as the reference (and, therefore, exact) velocity values. The results obtained with the proposed methodology are in good agreement with the reference values in almost all tested conditions, covering both the linear and the nonlinear behavior of the car, proving that artificial neural networks can be efficiently employed onboard, thereby enriching the standard set of control and safety-related electronics.
... More in detail, indirect approaches employ sensor signals, such as the vehicle accelerations, the longitudinal velocity, and the steering wheel angle, to provide an estimation of the wheel forces. To do this, a vehicle dynamics model [43][44][45][46][47] must be defined and dedicated measurements are performed to properly derive some vehicle properties such as inertia and aerodynamic coefficients, so as to guarantee the accuracy of force estimations. However, indirect approaches based on multibody models can hardly be implemented on vehicles' on-board computers for real-time wheel contact force estimation. ...
Article
The wheel loads of a race car have been estimated in view of structural durability assessments. First, the front left double‐wishbone suspension of a rear‐wheel‐drive race vehicle has been instrumented; then, wheel loads have been estimated by means of four approaches: (i) a geometric matrix (GM) method, (ii) a feedforward neural network (FNN) approach applied to the fully instrumented suspension (FIS), (iii) a FNN approach involving a reduced number of sensors (the partially instrumented suspension (PIS)) and an inertial measurement unit (IMU), and (iv) a linear modeling approach (LM). After having trained the FNNs by using suspension signals acquired in a racetrack as inputs and related tire forces measured with the GM method as targets, the FNN‐based methods have been validated on three different racetracks by comparing the estimated loads with those estimated by means of the GM method. According to the results achieved, the FNN approaches are effective for the estimation of the wheel forces. A double‐wishbone suspension was instrumented to measure the wheel fatigue loads. A geometric matrix method was formulated to measure the loads simply from equilibrium. Two NNs were formulated, with fully and partially instrumented suspension, respectively. Both NNs were trained and successfully estimated the wheel loads in track driving.
... To increase the amount of information and to estimate the data useful for identifying the parameters of tyre interaction models used in simulations, the velocities and accelerations signal were used as input for TRICK [30]. The output provided was a sort of 'virtual telemetry', constituting further channels with wheel slip ratio, slip angle, and tyre interaction forces. ...
Article
Full-text available
Vehicle dynamics can be deeply affected by various tyre operating conditions, including thermodynamic and wear effects. Indeed, tyre temperature plays a fundamental role in high performance applications due to the dependencies of the cornering stiffness and potential grip in such conditions. This work is focused on the evaluation of a potentially improved control strategy’s performance when the control model is fed by instantaneously varying tyre parameters, taking into account the continuously evolving external surface temperature and the vehicle boundary conditions. To this end, a simplified tyre thermal model has been integrated into a model predictive control strategy in order to exploit the thermal dynamics’ dependents within a proposed advanced ABS control system. We evaluate its performance in terms of the resulting braking distance. In particular, a non-linear model predictive control (NMPC) based ABS controller with tyre thermal knowledge has been integrated. The chosen topic can possibly lay a foundation for future research into autonomous control where the detailing of decision-making of the controllers will reach the level of multi-physical phenomena concerning the tyre–road interaction.
... To accurately identify the tire capacity regions in any driving scenarios, a large number of tire data under variety of road conditions, normal loads, velocities, tire pressures, slip ratios and slip angles are needed. Measurement for testing tire characteristics can be divided into two categories: indoor test including typical low-speed flat plank [34], high-speed flat track [35] and inner/outer drum test [36], and outdoor test by using the Tire Test Trailer [37] or on-vehicle test with six-component force/torque transducer directly [38]. For our current application, outdoor test seems to be a better way since the test trailer or vehicle can be driven on different real roads, however, the Tire Test Trailer is scarce and not easily available, and on-vehicle test is hardly to obtain high quality tire characteristics from linear region to high-nonlinear region. ...
Article
Full-text available
Tire states and capacity monitoring is critical for vehicle and wheel stabilization controls in automated driving and active safety systems. Tire capacity, which represents the performance margin of tire forces from its limits, determines the operational range for vehicle control systems and their actuation through steering or torques at each tire to maintain stability while performing trajectory following. This paper presents a generic tire capacity identification framework that can handle different normal loads, road surface friction, and combined-slip driving scenarios, which are challenging for stabilization and tracking control programs in automated driving systems. A novel measuring method for generating force-training data is designed by combining the indoor tire test procedure and tread rubber friction test rig, in order to obtain adequate and high-quality benchmark datasets. The results from large data sets from road experimenting and indoor tire test facilities, including pure- and combined-slip conditions, confirm effectiveness of the developed learning-based tire capacity estimation which utilizes notions from the model description with bounded uncertainty. More importantly, the proposed method can provide reliable tire properties ranging from the linear to the sliding regions. Further validation is performed on a real test car with on-board sensory measurements, and the results confirm accuracy of the proposed method for various free rolling and hard launch/brake scenarios.
... The track session has consisted of handling tests in the widest possible range of tyre operating conditions in terms of temperature, pressure, and wear level. Following the vehicle model parametrization and the tyre parameters' estimation procedures described in [36,37], the vehicle non-linear system has been completely characterized in all the conditions of interest, being able to faithfully reproduce the experimental data in the virtual environment. ...
Article
Full-text available
In recent years the increasing needs of reducing the costs of car development expressed by the automotive market have determined a rapid development of virtual driver prototyping tools that aims at reproducing vehicle behaviors. Nevertheless, these advanced tools are still not designed to exploit the entire vehicle dynamics potential, preferring to assure the minimum requirements in the worst possible operating conditions instead. Furthermore, their calibration is typically performed in a pre-defined strict range of operating conditions, established by specific regulations or OEM routines. For this reason, their performance can considerably decrease in particularly crucial safetycritical situations, where the environmental conditions (rain, snow, ice), the road singularities (oil stains, puddles, holes), and the tyre thermal and ageing phenomena can deeply affect the adherence potential. The objective of the work is to investigate the possibility of the physical model-based control to take into account the variations in terms of the dynamic behavior of the systems and of the boundary conditions. Different scenarios with specific tyre thermal and wear conditions have been tested on diverse road surfaces validating the designed model predictive control algorithm in a hardware-in-the-loop real-time environment and demonstrating the augmented reliability of an advanced virtual driver aware of available information concerning the tyre dynamic limits. The multidisciplinary proposal will provide a paradigm shift in the development of strategies and a solid breakthrough towards enhanced development of the driving automatization systems, unleashing the potential of physical modeling to the next level of vehicle control, able to exploit and to take into account the multi-physical tyre variations.
... With this approach the model can correct for sensors inaccuracies and unwanted measurements, but information on tyre parameter and road condition is needed for the tyre model. Many observers have been developed based on this approach [4] [5] [6] [7] [8], where different tyre models have been used. This paper proposes a new method for estimating the fundamental variables of vehicle dynamics and, at the same time, thanks to the use of a simple Magic formula characterized by four parameters obtained from extensive offline testing [9][10], the estimation of the lateral friction coefficient, through the use of an extended Kalman filter. ...
Article
Full-text available
The performance of the vehicle’s active safety systems depends on accurate knowledge of the vehicle state, and the frictional forces resulting from tyre contact and the road surface. This paper aims to estimate the vehicle states and tyre-road coefficient of friction through and Extended Kalman Filter (EKF), integrated with the Double-Track model and the Pacejka Magic Formula that allows knowledge of the lateral force of the tyre. Besides, this approach can estimate the overall coefficient of lateral friction on each side of the vehicle, left and right respectively. Simulations based on a reference vehicle model are performed on different road surfaces and driving manoeuvres to verify the effectiveness of the proposed estimation method, in order to obtain good performance from different vehicle control systems.
... A model capable of faithfully reproduce the axle characteristics at varying frequencies will also coincide with the real on all the other transfer functions, because all the single track model dynamics is determined from axle characteristics and other few macro-parameters that given as known in this work: vehicle mass, rotational inertia, wheelbase, center of gravity longitudinal position and steering ratio [Milliken]. The gain values of 1 ( ) and 2 ( ) are determined by the known parameters: tire cornering stiffness pre-identified with laboratory procedures or onboard identification methodologies like [13] [14] [15], while the delay values are determined by both the known and unknown parameters: the tire carcass lateral stiffnesses 1 and 2 . By varying the tire carcass stiffnesses, the delays of 1 ( ) and 2 ( ) vary uniformly over the entire frequency range, therefore determining the appropriate values is a simple task even without using an optimization algorithm. ...
Chapter
Measuring and modeling vehicle response delays is a fundamental prerequisite for dynamic simulations, both in real-time driving platforms and in offline systems. With a human driver the delays have a heavy influence on the driving feeling and for the achievement of the optimal lap times. If artificial intelligence is driving, lap times can be improved by using algorithms able to calculate vehicle states, whose reliable reproduction is deeply linked to the delay’s evaluation.
... For this reason, at the current stage, a tire characterization suite including both the characterization procedures and the software set of tools have been developed to overcome the difficulties linked to the deeper understanding of the tire behaviour and to the identification of the physical quantities necessary to properly parameterise all the physical models. The developed set of tools comprises an interaction forces estimator based on vehicle outdoor acquisitions, called TRICK [10], a "smart" parameters identifier developed for Pacejka formulations, called TRIP-ID [4], a real-time physical thermal model, called TRT [3][6] and a physical grip model, called GrETA [7]. ...
Chapter
The characterization and reproduction of tire behaviour for vehicle modelling is a topic of particular interest both for real-time driving simulations and for offline performance optimization algorithms. In such contexts, the Pacejka’s Magic Formula (MF) tire model [1] represents a standard that gained in the last 25 years a role of high relevance due to its low computational request and attitude to allow an efficient parameterization for a wide range of tires working conditions. Nevertheless, the original MF formulation was conceived with the aim to provide tire/road interaction forces and moments as a function of vertical load, longitudinal and lateral slip, and inclination (or camber) angle; such variables are fundamental but not totally satisfying in the description of the complex multi-physical phenomena occurring at tire/road interface [2]. In particular, the relationship between interaction forces and the cited input variables is highly influenced by further effects, linked to tire temperature, tread wear, compound viscoelastic characteristics and road roughness. Among these, the influence that the thermal conditions of the different layers constituting the global thickness of tires have on the friction and on their stiffness characteristics, is highly significant and definitely not negligible in case a full reliability of the vehicle dynamics simulations is required, especially in motorsport applications [4]. The paper illustrates the basic concepts linked to the development of a novel version of a MF-based formulation, able to take into account uncommon factors affecting tire/road interaction. Once described the structure and the parameters identification process [4], some results obtained with the MF-evo employed in a simulative loop with a thermal model are reported.
... The definition of a standard testing activity able to estimate tire forces and slip indices is a crucial task for many, and it is one of the pillars (together with thermodynamics and adherence studies) needed to reach the final goal: a tool to characterize tire behavior. TRICK tool [6] has resulted to be an efficient way to predict tire's and vehicle's performance basing on acquired data from standard sensors, and it has proved to be a valid alternative to expensive and very often long indoor test sessions. ...
Chapter
The tire behavior optimization is crucial for the definition of the best setup of the whole vehicle; in fact, its interface with the ground is constituted by the sum of small surfaces in which tire-road interaction forces are exchanged. The fundamental role that in the last years tires have played in automotive industry and the growing need to reproduce with a high level of detail the phenomena concerning with vehicle dynamics have given a strong impulse to the research in the field of vehicle systems and modelling.
... This paper refers to the T.R.I.C.K. tool [7] developed by UniNa vehicle dynamics research group that comes from the idea of using the car as a moving laboratory to characterize tires without test bench and in their real operating conditions. The T.R.I.C.K. uses an 8 degrees-offreedom (DOF) rear-wheel-drive vehicle model and is able to process experimental signals acquired from sensors mounted on the car providing a sort of virtual telemetry. ...
Chapter
In the last years, the tire technological development has played a fundamental role in motorsport and in automotive industry. The tire contact patch forces have a great influence on the vehicle behavior, so their correct estimation is a crucial task to understand how to improve the car performance. In order to identify the tire interaction characteristic, it is also necessary to use a procedure that allows the correct evaluation of the slip angles in the different operating conditions. This paper presents an evolution of the T.R.I.C.K. tool developed by the UniNa vehicle dynamics research group. In the first version of this tool an 8 degree of freedom vehicle model has been implemented and, starting from the experimental data acquired, the T.R.I.C.K. calculates the interaction forces and the tire slips using the equilibrium equations. Using more car parameters and further data obtained from track sessions and dedicated tests, in the presented release of the tool, new formulations have been developed for a more accurate calculation of the tire-road forces. The effectiveness of the treatments is assessed using experimental data and the simulator outputs. The new formulations introduced in this paper allows, depending on the availability of additional vehicle data and acquisition sensors, to estimate the interaction forces with different and more accurate methodologies than the equilibrium equations, while retaining very reduced simulation times. In this way it is possible to carry out a more precise study of vehicle dynamics with the possibility of investigating and significantly improving performance.
... This paper refers to the T.R.I.C.K. tool [7] developed by UniNa vehicle dynamics research group that comes from the idea of using the car as a moving laboratory to characterize tires without test bench and in their real operating conditions. The T.R.I.C.K. uses an 8 degrees-offreedom (DOF) rear-wheel-drive vehicle model and is able to process experimental signals acquired from sensors mounted on the car providing a sort of virtual telemetry. ...
Conference Paper
In the last years, the tire technological development has played a fundamental role in motorsport and in automotive industry. The tire contact patch forces have a great influence on the vehicle behavior, so their correct estimation is a crucial task to understand how to improve the car performance. In order to identify the tire interaction characteristic, it is also necessary to use a procedure that allows the correct evaluation of the slip angles in the different operating conditions. This paper presents an evolution of the T.R.I.C.K. tool developed by the UniNa vehicle dynamics research group. In the first version of this tool an 8 degree of freedom vehicle model has been implemented and, starting from the experimental data acquired, the T.R.I.C.K. calculates the interaction forces and the tire slips using the equilibrium equations. Using more car parameters and further data obtained from track sessions and dedicated tests, in the presented release of the tool, new formulations have been developed for a more accurate calculation of the tire-road forces. The effectiveness of the treatments is assessed using experimental data and the simulator outputs. The new formulations introduced in this paper allows, depending on the availability of additional vehicle data and acquisition sensors, to estimate the interaction forces with different and more accurate methodologies than the equilibrium equations, while retaining very reduced simulation times. In this way it is possible to carry out a more precise study of vehicle dynamics with the possibility of investigating and significantly improving performance.
... All the above-mentioned approaches are discussed by Besdo et al. (2010). Farroni (2016) describes the interaction between tyre and road and also elaborates on the effect of factors such as temperature field. Every time numerical models applications are discussed, their parameters should be identified through the comparison to the experiments on real object. ...
Article
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Tyre-to-road adhesion plays an important role when taking into account transmission of forces between tyres and road surface. It consequently influences vehicle safety. Moreover, it plays a significant role for modelling vehicle motion, which is often applied in the development of automotive active safety systems and in traffic accidents reconstruction. Furthermore, tyre-to-road adhesion properties are dependent on many factors. One of the factors is the type of tyre – summer or winter. This is the reason why it is justified to study the anti-slip properties of summer and winter tyres. This paper shows the method of measuring tyre-to-road adhesion coefficient. It is based on a skid resistance tester SRT-4 that consists of a special dynamometer trailer, towing vehicle and test-measuring equipment. It was designed to be applied in civil/road engineering and further developed. As a result, the SRT-4 system automatically obtains adhesion characteristics, such as the graph of tyre-to-road adhesion coefficient as a function of wheel slip ratio and velocity characteristics of peak adhesion coefficient. Results of the study present the above mentioned characteristics for different types of tyres (summer, winter) in different exploitation conditions. Differences between presented characteristics caused by tyre type and conditions of exploitation are shown. For example, for winter tyres we noticed that the peak value of adhesion coefficient was attained for higher values of slip ratio as compared with summer tyres.
Article
This paper describes a programme of tyre tests using a purpose built tyre test rig designed specifically to investigate the behaviour of tyres that are used with Road-Rail Vehicles (RRVs). These vehicles are used extensively by the rail industry to support the maintenance of existing rail lines and new construction works. In many cases, using a vehicle that can only operate on the road, or a rail engine that can only operate on tracks will not provide a suitable or effective solution for the task in hand. RRVs are able to operate on both roads and rail, and as such provide a very flexible solution to the rail industry. When operating on the road, RRVs use pneumatic tyres to control their motion and act to all intent and purpose as a normal road vehicle. When operating on rail lines RRVs use a combination of the pneumatic tyres and standard steel rail wheels to control their motion. The rail wheels maintain the directional stability on the track and the pneumatic tyres provide the tractive force to drive and brake the vehicle. Unlike standard road or rail vehicles, there is to date no predictive engineering practice that allows the use of computer simulation to design and optimise the performance of RRVs when they are operating on rails. Computer tools, such as multi-body systems (MBS) analysis are used extensively to design both road and rail vehicles. For road vehicles a tyre model is needed to represent the behaviour in the contact patch between the tyre and the road. For rail vehicles a model is needed to represent the contact force between the train wheel and the track. In both these applications the behaviour is well understood and over the last half century mathematical models have been developed that allow accurate and useful simulation to support the design of new vehicles and trains. In contrast, RRVs have evolved essentially as modifications to standard road vehicles. While the base vehicle may be very well designed to perform on the road, the performance on rail is based on experience and some testing. There is no up-front science involved in designing a RRV to perform effectively during this very important phase of its operation. In order to develop an accurate model to predict RRV performance on rails it is clear that a model of the behaviour of the tyre when in contact with the rail is needed. To date, no such model exists and additionally the testing needed to generate data that could be used to develop a model has never been carried out. The work described here addresses this with the design and build of a unique test rig that can be used to test tyres on rails for a range of operating conditions, and produce a set of initial results that provide a framework for a future tyre/rail model. The paper concludes with a review of the behaviour measured and provides new insights into how well tyres perform on rails and also where the behaviour differs from the well understood behaviour of tyres operating on roads. The important behaviours that would provide the main parameters for a new empirical tyre model are also identified and discussed.
Article
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The forces generated by the tyres of a vehicle are responsible for the maximum achievable performance for a race car. In this work, a geometric matrix method combined with a sensitivity matrix method has been applied to a rear multi-link suspension of a rear-wheel-drive race car to estimate the tyre forces from the measurement of the loads acting on the suspension arms. The geometric matrix method calculates the wheel forces from the equilibrium of the wheel assembly, thus involving all reaction forces exchanged with the suspension arms. The reaction forces have been measured through the application of axial strain gauge bridges on the link arms; however, the lower arm has a complex geometry and exchanges multi-axial forces with the upright, therefore a sensitivity matrix method has been implemented. The strain gauges positions have been identified with FE analyses and after installing the sensors, the calibration of the entire suspension assembly has been performed in a dedicated test rig where known forces at the ideal contact point between the wheel and the ground can be applied. After the calibration and validation in the laboratory, the instrumented suspension has been installed in a race vehicle and multiple racetrack acquisitions have been successfully performed.
Article
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Nowadays, the active safety systems that control the dynamics of passenger cars usually rely on real-time monitoring of vehicle side-slip angle (VSA). The VSA can’t be measured directly on the production vehicles since it requires the employment of high-end and expensive instrumentation. To realiably overcome the VSA estimation problem, different model-based techniques can be adopted. The aim of this work is to compare the performance of different model-based state estimators, evaluating both the estimation accuracy and the computational cost, required by each algorithm. To this purpose Extended Kalman Filters, Unscented Kalman Filters and Particle Filters have been implemented for the vehicle system under analysis. The physical representation of the process is represented by a single-track vehicle model adopting a simplified Pacejka tyre model. The results numerical results are then compared to the experimental data acquired within a specifically designed testing campaign, able to explore the entire vehicle dynamic range. To this aim an electric go-kart has been employed as a vehicle, equipped with steering wheel encoder, wheels angular speed encoder and IMU, while an S-motion has been adopted for the measurement of the experimental VSA quantity.
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The existing energy management strategies for four-wheel-drive electric vehicles only take into account the vehicle energy consumption under static adhesion constraints. However, the front and rear axle loads transfer under dynamic conditions lead to the variations of vehicle adhesion characteristics, which results in the changes of vehicle energy consumptions. In this paper, a multi-objective optimal torque distribution strategy is proposed, taking into account the front and rear axle load transfer and the variations of adhesion characteristics. The advantages of the proposed strategy are verified through simulation studies in terms of vehicle energy consumption and wheel slip ratio, in comparison with the average torque distribution strategy and the optimal torque distribution strategy based on Sequential Quadratic Programming Algorithm. The simulation results show that the economy performance of the proposed strategy is superior to those of the competing methods. Furthermore, the proposed strategy provides good power performance and eliminates excessive wheel slip, which in turn ensures vehicle longitudinal stability and avoids energy loss resulting from frequent ASR interventions.
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Accurate modeling of tire characteristics is one of the most challenging tasks. Many mathematical models can be used to fit measured data. Identification of the parameters of these models usually relies on least squares optimization techniques. Different researchers have shown that the proper selection of an initial set of parameters is key to obtain a successful fitting. Besides, the mathematical process to identify the right parameters is, in some cases, quite time-consuming and not adequate for fast computing. This paper investigates the possibility of using Artificial Neural Networks (ANN) to reliably identify tire model parameters. In this case, the Pacejka's "Magic Formula" has been chosen for the identification due to its complex mathematical form which, in principle, could result in a more difficult learning than other formulations. The proposed methodology is based on the creation of a sufficiently large training dataset, without errors, by randomly choosing the MF parameters within a range compatible with reality. The results obtained in this paper suggest that the use of ANN to directly identify parameters in tire models for real test data is possible without the need of complicated cost functions, iterative fitting or initial iteration point definition. The errors in the identification are normally very low for every parameter and the fitting problem time is reduced to a few milliseconds for any new given data set, which makes this methodology very appropriate to be used in applications where the computing time needs to be reduced to a minimum.
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In this paper, we discuss three improved brush models. The first one deals with the coupling between the slip and spin parameters and is valid for relatively high steering speed and small camber angles; the second one is more complex and considers the presence of a two-dimensional velocity field inside the contact patch due to large camber angles; the third one is more general and combines both the previous formulations. For the last two models, the investigation is conducted with respect to a rectangular contact patch, for which we show that three different regions can be identified, each of them corresponding to a different steady-state solution for the deflection of the bristle. Furthermore, from the transient analysis it emerges that each region can be in turn separated into an area in which steady-state conditions reign and another one in which the transient solution takes place. An asymptotic analysis is carried out for the three models and it is shown that the solutions are equivalent to the ones predicted by the standard brush theory for small values of the spin ratio and camber angle. Finally, a comparison is performed amongst the models to highlight the differences in the predicted tyre characteristics.
Chapter
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Soft robots have been extensively studied for their ability to provide both good performance and safe human-robot interaction. In this paper, we present and compare the performance of two model-based control techniques with the common aim to independently and simultaneously control position and stiffness of a pneumatic soft robot’s joint. The dynamic system of a robot arm with flexible joints actuated by a pneumatic antagonistic pair of actuators, so-called McKibben artificial muscles, will be regarded, while its dynamic parameters will be considered imprecise. Simulation results are provided to verify the performance of the algorithms.
Chapter
The understanding and control of tire wear, preventing tread degradation and irregular wear has been a challenge to tire product engineers, and an important issue for fleet management. There is not a simple equation to analyze and predict it. The optimal wear, and consequent mileage performance, depends not only on the tire, but also on its interaction with the vehicle and the road. It varies with operational conditions and, furthermore, with vehicle and tire maintenance. This paper aims to show the preliminary analysis useful for the development of a tool able to predict tire wear performances in the truck & bus environment, anticipating the results coming from a standard field evaluation. A predictive tool is important for both tire manufacturer and final customers: the advantage for tire manufacturer is the possibility to drastically reduce time-to-market and to have reliable and controlled results; for OEMs, the possibility to receive tire models based on outdoor tests using their own vehicle as a moving lab; for final customer, the advantage of having smart-tire able to predict wear performances, generating valuable advices for maintenance and fleet control. Such aspects will be explained in this paper covering the first results obtained during an outdoor session where a reference vehicle has been instrumented in order to evaluate longitudinal behavior.
Conference Paper
The evaluation of the tire tread viscoelastic characteristics, especially by means of non-destructive procedures, is a particularly interesting topic for motorsport teams and companies, used to work with unknown and confidential compounds. The availability of such information would define new scenarios in vehicle analysis field, as the possibility to provide physical inputs to tire grip models or the study of the suspensions setup able to make tires work inside their optimal thermal working range. The employment of commercial devices allows to select by means of specific indices the optimal combination of tires to be installed on a vehicle, but it does not provide any information physically correlated with the tread polymers characteristics. The aim of the presented activity is the modelling of one of the cited devices, a dynamic dial indicator, interacting with a viscoelastic half-space. The obtained results allow, analyzing the signals acquired by the device, to identify the tread equivalent stiffness and damping as a function of tire working temperature, providing the basic guidelines for the development of an innovative procedure for a full non-destructive viscoelastic characterization of the tire compounds. Index Terms-Material non-destructive characterization, temperature effect, tire tread compound behavior, TSD, viscoelastic characteristics.
Article
Purpose Existing three-dimensional (3D) road-surface models use approximation methods such as a set of discrete triangular patches and cannot accurately describe changes in the geometrically designed elements along the road. This paper aims to construct a 3D road-surface model with combinations of geometric design invariants and apply the proposed model to analyse the state of motion of a wheel’s centre. Design/methodology/approach In this paper, the 3D road surface is modelled as a continuous function with combinations of geometric design invariants. By introducing the theories of differential geometries and rigid body dynamics, a wheel-road model wherein a wheel fixed to a Darboux frame moves along a curved road surface is constructed, and the wheel time-dependent properties of the velocity, angular velocity and acceleration at an arbitrary point of the surface are described using road geometry design invariants. Findings This paper adopts the Darboux frame to study the instantaneous spin-rolling motion of a wheel. It is found that the magnitudes of the spin-rolling velocity, the acceleration and the geometric invariants of the road surface, including the geodesic curvature, the normal curvature and the geodesic torsion, determine the instantaneous states of motion of a wheel. Originality/value This work provides a theoretical foundation for future studies of wheel motion states, such as the relationship between road geometry design invariants and driving safety, vehicle lane changing and other vehicle microbehaviours. New insights are gained in the areas of road safety and vehicles incorporating artificial intelligence.
Article
This paper proposes an extensive overview of the tire-road interaction estimation issue as it relates to automated driving from the prospectives of sensor configuration, tire modeling, and estimation approaches. The tire-road interactions needed for estimation are first determined and classified. Then, the sensor configuration schemes of different types of tire-road interactions are presented and analyzed. The following introduces various types of tire models and provides the limitations and advantages of different estimation approaches based on categorizing and summarizing those techniques. Moreover, some interesting perspectives for future research are listed based on the extensive experience of the authors.
Conference Paper
A relatively new technology for the electric vehicles considers the use of brushless permanent magnet motors directly connected to the car wheels (in-wheel motors or hub motors). In order to evaluate the performance that can be obtained, a complete dynamic model of a four-wheel drive (4WD) electric vehicle equipped with four in-wheel motors is developed and a correspondent parametric simulator is implemented in Matlab/SimulinkTM. The simulator is also employed for designing, testing and comparing various control logics which reproduce the handling behavior of a real vehicle.
Conference Paper
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Accurate measurement of the vehicle sideslip angle is fundamental to improve reliability of the vehicle dynamics control systems focused on stability and developed both for safety and performance optimization. Many experimental procedures to estimate the vehicle sideslip angle have been proposed in the last years, mainly based on GPS, INS and physical models. The aim of this paper is to compare different methods to estimate sideslip angle employing an instrumented vehicle, equipped with a system for data acquisition and time-synchronized storage capabilities, a stand-alone GPS, a GPS aided MEMS-based Attitude and Heading Reference System (AHRS) and specific sensors to collect data on the steering wheel angle and on the position of brake, throttle and clutch pedals. Further information is collected by capturing the available data at the OBD port of the vehicle. Data acquisitions (from all sensors) are synchronized by means of an external triggering signal. After driving sessions performed with specific manoeuvres in order to highlight the main phenomena concerned with the dynamic behaviour of the vehicle, the different estimation procedures have been applied, discussing on the advantages and the degree of reliability of each one of them.
Conference Paper
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The paper presents considerations about the utility, suitability and limits of the coast-down experimental test in the automotive research. That test consists in launching of a motor vehicle from a certain speed with the engine disengaged and ascertaining of the current speed and distance covered during the free rolling, till vehicle stops. First it is indicated a modality to determine by computation the vehicle kinematics. There are presented the vehicle resistances, the assumptions and the values influencing the analyzed process. Then, there are established the mathematical equations necessary to ascertain the speed and distance during cost-down. By the analysis of the different factors influences it can be determined the necessary precision of measurements, so that the results of the test might be conclusive. Reciprocally, when experimental data exists, mathematical methods based on regression are presented to estimate the vehicle movement resistances. In the paper are presented data obtained using coast-down method with different test vehicles and in various road conditions. The results include estimated values for the rolling resistance coefficient and aerodynamic drag coefficient. New ideas for additional valorisation of the method are also indicated.
Book
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Book available at HALF PRICE (50% off), shipping included worldwide till MARCH 31, 2016 here http://www.springer.com/en/book/9789401785327 (Springer website) THE MORE YOU KNOW VEHICLE DYNAMICS, THE MORE YOU'LL BE SURPRISED Vehicle dynamics is often perceived as a quite intuitive subject. As a matter of fact, lots of people are able to drive a car. Nevertheless, without a rigorous mathematical formulation it is very difficult to truly understand the physical phenomena involved in the motion of a road vehicle. In this book, mathematical models of vehicles are developed, always paying attention to state the relevant assumptions and to provide explanations for each step. This approach allows for a deep, yet simple, analysis of the dynamics of vehicles, without having to resort to foggy concepts. The reader will soon achieve a clear understanding of the subject, which will be of great help both in dealing with the challenges of designing and testing new vehicles and in tackling new research topics. However, there is much more than that. Quite surprisingly, it is shown that several classical concepts, such as the understeer gradient or the roll axis, are either wrong or inadequate and need to be replaced. The book covers handling and performance of both road and race cars. A new approach, called MAP (Map of Achievable Performance), is presented and thoroughly discussed. It provides a global and intuitive picture of the handling features of a vehicle. Moreover, the book also deals with several relevant topics in vehicle dynamics that have never been discussed before. Even very experienced people should find the book interesting and stimulating. This new book is not a translation of the Italian Dinamica del Veicolo; by the same author. Actually, in some sense, this new book is totally different, with new topics and with new points of view for the topics covered in the Italian book as well.
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In the paper a new physical tyre thermal model is presented. The model, called Thermo Racing Tyre (TRT) was developed in collaboration between the Department of Industrial Engineering of the University of Naples Federico II and a top ranking motorsport team. The model is three-dimensional and takes into account all the heat flows and the generative terms occurring in a tyre. The cooling to the track and to external air and the heat flows inside the system are modelled. Regarding the generative terms, in addition to the friction energy developed in the contact patch, the strain energy loss is evaluated. The model inputs come out from telemetry data, while its thermodynamic parameters come either from literature or from dedicated experimental tests. The model gives in output the temperature circumferential distribution in the different tyre layers (surface, bulk, inner liner), as well as all the heat flows. These information have been used also in interaction models in order to estimate local grip value.
Conference Paper
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In this paper the results of an experimental activity carried out with the aim to investigate on the frictional behaviour of visco-elastic materials in sliding contact with road asperities is presented. Experiments are carried out using a prototype of pin on disk machine whose pin is constituted by a specimen of rubber coming from a commercial tyre while the disk may be in glass, marble or abrasive paper. Tests are performed both in dry and wet conditions. Roughness of the disk materials is evaluated by a tester and by a laser scan device. Temperature in proximity of the contact patch is measured by pyrometer pointed on the disk surface in the pin trailing edge, while room temperature is measured by a thermocouple. Sliding velocity is imposed by an inverter controlled motor driving the disk and measured by an incremental encoder. Vertical load is imposed applying calibrated weights on the pin and friction coefficients are measured acquiring the longitudinal forces signal by means of a load cell. As regards to the road roughness, the experimental results show a marked dependence with road Ra index. Dry and wet tests performed on different micro-roughness profiles (i.e. glass and marble) highlighted that friction coefficient in dry conditions is greater on smoother surfaces, while an opposite tendency is shown in wet conditions. Although affected by uncertainties the results confirm the dependence of friction on temperature, vertical load and track conditions.
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In this paper an experimental test rig aimed to characterize mechanical properties of a pneumatic tyre, together with some results, is presented. The objective is to determine tyre mechanical characteristics useful to physically model its behaviour; in particular: the normal interaction characteristic, the radial stiffness, the total stiffness and the longitudinal hysteretic cycles. To this aim two different kind of tests have been executed: radial and longitudinal. In the radial test the load is statically applied to the tyre, along the vertical direction, by means of an hydraulic press and it is measured together with the consequent radial deformation, so allowing the estimation of the tyre normal interaction characteristic and of its radial stiffness. Different radial tests can be conducted for an assigned tyre varying the inflation pressure. The longitudinal tests are conducted applying, under an assigned constant vertical load, a variable horizontal strain to the tyre by means of a linear actuator, two profile rail guides and a system to transfer the horizontal motion to the contact patch of the tyre, opportunely placed on a moving steel plate placed on the two linear guide rails. During the tests the horizontal load and the resulting deformations are measured and acquired so allowing the estimation of tyre total stiffness and of its longitudinal hysteretic cycles. Longitudinal tests can be conducted varying the assigned vertical load, the horizontal displacement law in terms of frequency and amplitude, the tyre inflation pressure. All the different types of rim can be mounted on the test rig thanks to a universal quick flange.
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A flat track tire testing machine developed by the IMMa group is described. It permits the simulation and study of the dynamic behavior of a great variety of tires under controllable and repetitive highly dynamic realistic working conditions in the laboratory for a diversity of vehicles, from motorcycles to light trucks. The machine incorporates: – a hydraulically operated tire support and loading system with wide operating ranges; – a computer controlled brake system to simulate braking maneuvers with ABS systems; – a complete sensorial system; – a data acquisition and control system continually monitoring and acting on the experimental variables, i.e., tire and belt speed, longitudinal slip, slip and camber angles, tire pressure, tire normal force, etc. As an application example, results are presented that adjust the parameter of the magic formula for a standard 175/70 R14 passenger vehicle tire. Accurate mathematical tire models are recognized as essential for the prediction of vehicle dynamic performances using simulation tools.
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A new technique for the determination of the thermal diffusivity of a tyre compound is proposed. The diffusivity is defined as the ratio between the thermal conductivity and the product of the specific heat and density. This technique is based on infrared measurement and successive analysis of the tyre cooling. Tyre samples were heated up by a laser at constant power rate and the heating and the next cooling of the tyres were registered versus time by mean of thermocouples and infrared cameras. Determination of the thermal diffusivity was thus estimated by mean of home-made model. The research activity was carried out in the laboratories of the department of Mechanics and Energetics of the University of Naples Federico II, in cooperation with the Combustion Institute of the CNR in Naples.
Article
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A new analytical–physical tyre model for which the paternity has to be ascribed to Professor Giuseppe Capone was developed at the Department of Mechanical Engineering for Energetics at Naples University ‘Federico II’ with the support of the Bridgestone Technical Centre Europe. The whole model allows to obtain the road–tyre interactions so it can be used in vehicle dynamic simulations. The model has been named Ph.An.Ty.M.H.A., acronym of ‘PHysical ANalytical TYre Model for Handling Analysis’ and it includes the normal, longitudinal and lateral tyre–road interaction. Considering that Ph.An.Ty.M.H.A. is an analytical ‘deductive’ model, it is necessary to develop it starting just from the normal interaction, described in this paper, and then the other ones will be described in future papers. In fact, the normal interaction, i.e. the relationship between the normal load and the normal deflection, influences the tangential (longitudinal plus lateral) one, which determines the vehicle handling behaviour. The parameters used in this model are physical and geometrical so they can be measured on the real tyre. This property allows to better understand the tyre–road interaction mechanism. The tyre behaviour is modelled by analytical expressions based on equilibrium conditions and geometrical relations. To reproduce the experimental normal interaction and the pressure distribution, once the tyre geometrical quantities are known, it is necessary to identify some parameters, related to the tyre structure, by a comparison with the experimental data. Moreover, the predictive ability of the whole model, combined with a vehicle model, is very careful in analysing the vehicle handling [J.C. Dixon, Tyres, Suspensions and Handling, Cambridge University Press, Cambridge, 1991].
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Race car performance depends on elements such as the engine, tires, suspension, road, aerodynamics, and of course the driver. In recent years, however, vehicle aero-dynamics gained increased attention, mainly due to the utilization of the negative lift (downforce) principle, yielding several important performance improvements. This review briefly explains the significance of the aerodynamic downforce and how it improves race car performance. After this short introduction various methods to generate downforce such as inverted wings, diffusers, and vortex generators are dis-cussed. Due to the complex geometry of these vehicles, the aerodynamic interaction between the various body components is significant, resulting in vortex flows and lifting surface shapes unlike traditional airplane wings. Typical design tools such as wind tunnel testing, computational fluid dynamics, and track testing, and their rel-evance to race car development, are discussed as well. In spite of the tremendous progress of these design tools (due to better instrumentation, communication, and computational power), the fluid dynamic phenomenon is still highly nonlinear, and predicting the effect of a particular modification is not always trouble free. Several examples covering a wide range of vehicle shapes (e.g., from stock cars to open-wheel race cars) are presented to demonstrate this nonlinear nature of the flow field.
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This study deals with two vehicle-dynamic observers constructed for use in a two-block estimation process. Block 1 mainly estimates tire-forces (without an explicit tire-force model), while block 2 calculates sideslip angle and corrects cornering stiffnesses (with an adaptive tire-force model). The first observer O1,4w (block 1), an extended Kalman Filter, is constructed with a random walk force model. The experimental evaluations of O1,4w are satisfactory, showing excellent estimations close to the measurements and good convergence properties. The second observer O2,LAM (block 2), developed with an adaptive tire-force model, was evaluated for different cornering stiffness settings and was compared with an observer constructed with a fixed tire-force model (Orl). Results show that Orl is not robust when cornering stiffness parameters change, whereas O2,LAM gives excellent estimations of the sideslip angle. This result justifies the use of an adaptive tire-force model to take into account road friction changes. The different results show the potential of the two-block estimation process. The first block has the advantage of providing satisfactory force estimations without a tire-force model, whereas the second block provides robust sideslip angle estimations with respect to cornering stiffness changes (or tire-road friction variations). Future studies will improve vehicle-road models, notably for the calculation of the front/rear sideslip angles, in order to widen validity domains for observers. Subsequent vehicle-road models will take into account roll, vertical dynamics and vehicle-tire elastokinematics. Moreover, experimental tests will be performed, notably on different road surfaces and in critical driving situations (strong understeering and oversteering).
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A bewilderingly large number of statistical quantities have been proposed to study outliers and influence of individual observations in regression analysis. In this article we describe the inter-relationships which exist among the proposed measures. An examination of these relationships leads us to conclude that only three of these measures along with some graphical displays can provide an analyst a complete picture of outliers (major discrepant points) and points which excessively influence the fitted regression equation. Illustrative examples based on real data are presented.
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This publication describes a process to develop and calibrate a physics-based model for vehicle stability control. The approach consists of two phases. In the first phase, a baseline vehicle dynamics model was established using the commercially available simulation tool CarSim. The model was calibrated and validated for a variety of steady state, transient state and brake intervention handling manoeuvres using experimental test data. In the second phase, a simplified stability control model was developed in Matlab/Simulink based on representative control strategies. Subsequently, the vehicle dynamics model and stability control model developed were coupled using co-simulation and calibrated such that the closed-loop system behaviour approximated the real world test behaviour as best as possible. Finally, two case studies were developed to showcase the application of the closed-loop mathematical model in simulation-based studies addressing aftermarket vehicle modifications and their implication on vehicle stability control behaviour.
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Filling the gaps between subjective vehicle assessment, classical vehicle dynamics and computer-based multibody approaches, The Multibody Systems Approach to Vehicle Dynamics offers unique coverage of both the virtual and practical aspects of vehicle dynamics from concept design to system analysis and handling development. The book provides valuable foundation knowledge of vehicle dynamics as well as drawing on laboratory studies, test-track work, and finished vehicle applications to gel theory with practical examples and observations. Combined with insights into the capabilities and limitations of multibody simulation, this comprehensive mix provides the background understanding, practical reality and simulation know-how needed to make and interpret useful models. New to this edition you will find coverage of the latest tire models, changes to the modeling of light commercial vehicles, developments in active safety systems, torque vectoring, and examples in AView, as well as updates to theory, simulation, and modeling techniques throughout. © 2015 Michael Blundell and Damian Harty. Published by Elsevier Ltd. All rights reserved.
Article
A new 3D mathematical-physical tire model is presented. This model considers not only the handling behavior of the tire but also its comfort characteristics, i.e., the dynamic properties in the lateral and the vertical planes. This model can be divided into two parts, the structural model and the contact area model. The structural parameters are identified by comparison with frequency responses of a 3D finite element model of the tire, whereas the contact parameters are directly calculated with a finite element model of the tread pattern. The 3D physical model allows predicting both steady state and transient behavior of the tire without the need of any experimental tests on the tire. The steady state analysis allows obtaining the friction circle diagram, i.e., the plot of the lateral force against the longitudinal force for different slip angles and for longitudinal slip, and the Gough plot, i.e., the diagram of the self-aligning torque versus the lateral force. The transient analysis allows obtaining the dynamic behavior of the tire for any maneuver given to the wheel. Among its outputs there are the relaxation length and the dynamic forces and torque transmitted to the suspension of the vehicle. Combining the tire model with the vehicle model it is possible to perform any kind of maneuver such as overtaking, changing of lane and steering pad at growing speed with or without braking, or accelerating. Therefore the 3D tire model can be seen as a powerful tool to optimize the tire characteristics through a sensitivity analysis performed with tire and vehicle models linked to each other without the need of building prototypes. Some preliminary comparisons with experimental data have been carried out.
Article
This paper deals with the frictional behaviour of a tyre tread elementary volume in sliding contact with road asperities. Friction is supposed as composed by two main components: adhesion and deforming hysteresis. The target, fixed in collaboration with a motorsport racing team and with a tyre manufacturing company, is to provide an estimation of local grip for on-line analyses and real time simulations and to evaluate and predict adhesive and hysteretic frictional contributions arising at the interface between tyre tread and road. A way to approximate asperities, based on rugosimetric analyses on macro and micro scale, has been introduced. The adhesive component of friction has been estimated by means of a new approach based on two different models found in literature, whose parameters have been identified thanks to a wide experimental campaign previously carried out. The hysteretic component of friction has been estimated by means of an energy balance taking into account rubber viscoelastic behaviour, characterized by means of proper DMA tests, and internal stress / strain distribution due to indentation with road. Model results are finally shown and discussed and the validation experimental procedure is described. The correct reproduction of friction phenomenology and the model prediction capabilities are highlighted making particular reference to grip variability due to changes in working conditions.
Article
Knowledge of "out of plane" modes is very important when defining the dynamic behavior of a motorcycle and its stability and handling in particular. Several mathematical models are available in the literature to study and preview frequency, damping and stability of these modes but, in order to verify these values, road tests must be performed which are sometimes dangerous for the tester. A test rig to evaluate the possibility of performing a dynamic characterization of the out of plane modes instead of road tests, was developed. The use of a test rig is certainly limited compared with road tests since the physical phenomena are not completely reproduced but allows tests to be extended to low and very high speeds and assures test repeatability. This paper presents the test rig and the results of an experimental investigation conducted on a scooter; the tests were conducted in steer free control condition with different inertia and tire characteristics.
Article
A Numerical–physical tyre model was developed . The whole model allows to obtain the road–tyre interactions so it can be used in vehicle dynamic simulations. In this article are presented its capabilities in normal interaction analysis. The normal interaction, i.e. the relationship between the normal load and the normal deflection, influences the tangential (longitudinal plus lateral) one, which determines the vehicle handling behaviour. The parameters used in this model depend on the structure of the tyre and they can be measured on the real tyre. The tyre has been schematized as composed by a flexible belt , the sidewalls and a rigid ring (Rim). The flexible belt is composed by a number of lumped masses linked by extensional and bending stiffnesses and dampers. The tyre model has been developed using the finite segment method. Using these method could be possible to include in the tyre simulations various non-linear structural effects due to large displacements and rotations. The model allows to simulate both steady state and transient conditions.
Article
The first version of the tire simulation software Flexible ring Tire model (FTire) had been released in December 1998. Being subject to permanent improvement and several far-reaching model extensions since then, today it is one of the most widely used and generally accepted tire models for ride comfort, handling, and road load prediction.Strength of FTire is the strictly physical background, which perfectly fits both to Multi-Body Systems (MBS) and Finite Element Method (FEM) environments. Even though certain simplifications are unavoidable, this clean mechanical, thermo-dynamical, and tribological structure of the model guarantees a consistent and plausible model behavior even in situations that are not covered by respective measurements.The modelization takes into account most of the relevant excitation sources and non-linear transfer mechanisms, up to very high frequencies and extremely short wavelengths. The model's high level of detail is accompanied by a very comfortable program interface and a numerically robust and efficient solver. This allows the simulation of even extreme manoeuvres with moderate computation time. FTire can be used together with most of the important MBS packages and specialized vehicle dynamics programs.This contribution gives an overview on history, application, modelization, road models, parameterization, interfacing, availability, and future perspectives of FTire.
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This book attempts to find a middle ground by balancing engineering principles and equations of use to every automotive engineer with practical explanations of the mechanics involved, so that those without a formal engineering degree can still comprehend and use most of the principles discussed. Either as an introductory text or a practical professional overview, this book is an ideal reference.
Article
This paper investigates the use of GPS to estimate vehicle sideslip and tire information. Both a one antenna GPS antenna/receiver and dual GPS antenna method are studied. Analysis of the accuracy that can be achieved using the two different GPS solutions is provided. The algorithms are then validated on a fully instrumented Infiniti G35 sedan. Experimental data is given showing the performance of the GPS based sideslip estimates compared against a simple bicycle model and a DatronTM velocity sensor. NOMENCLATURE r Vehicle yaw rate
Article
This paper presents a design methodology for the mechanical systems entitled First Design. It is based on a hierarchical organisation of the design, taking into account the notion of robustness at an early phase of the project. The aim is to improve the quality of the system in order to make it robust, less sensitive to the variability of the external parameters and design parameters. We distinguish two main stages of the design cycle: one concerning functional parameters and another concerning physical parameters. The methodology is based on simplified models, on sensitivity analysis and on robust multi-objective optimisation. As an example, the methodology will be applied to the optimisation of vehicle suspension system design parameters. For each stage of the hierarchical design, adapted simplified models, sensitivity analyses and optimisation processes will be studied and applied to our vehicle suspension system.
Conference Paper
The vehicle sideslip angle is one of the most important variable to evaluate vehicle stability during dynamic manoeuvres. In this paper a nonlinear estimator is proposed, which use measurements of lateral accleration, steering angle, yaw rate and longitudinal velocity as input signals and provide the sideslip angle estimate as output. The design of such an estimator is based on a recently proposed direct approach to the design of virtual sensor. The obtained estimator has been experimentally tested on a huge number of different manoeuvres showing quite good results in a large range of operation covering both the linear and the nonlinear behaviour of the car.
An Introduction to Modern Design Vehicle
  • J Happian-Smith
J. Happian-Smith, An Introduction to Modern Design Vehicle, Butterworth-Heinemann, Oxford UK, 2002.
  • P Wright
P. Wright, Formula 1 Technology, SAE, 2001.
Tire testing machine and tire testing method
  • Y Sumimoto
  • K Honke
  • M Murakami
  • T Yoshikawa
  • T Nonaka
Sumimoto Y., Honke K., Murakami M., Yoshikawa T., Nonaka T., Tire testing machine and tire testing method, Patent US 8342020 B2, 2013.
Race Car Aerodynamics [6] J. Happian-Smith, An Introduction to Modern Design Vehicle
  • J Katz
J. Katz, Race Car Aerodynamics, BentleyPublishers, USA, 1995. [6] J. Happian-Smith, An Introduction to Modern Design Vehicle, Butterworth-Heinemann, Oxford UK, 2002. [7] V.V. AA., Vehicle Dynamics Stability and Control, SAE International, 2011.
Road vehicles–vehicle dynamics and road-holding ability-vocabulary
ISO8855:2011, Road vehicles–vehicle dynamics and road-holding ability-vocabulary, 1992.
Fx vs slip ratio-pure interaction-rear tire
  • Plot G
PLOT G: Fx vs slip ratio-pure interaction-rear tire