Recent publications
Stabilizing a 6DOF underactuated mechanical system ( ) without a cascade structure while utilizing a full-state feedback controller presents a significant challenge. Furthermore, due to the complexities of its dynamics and the degree of underactuation, designing an energy-shaping controller for such a system has not been done until now. This paper introduces a solution to the potential energy shaping problem for 6DOF underactuated mechanical systems by employing the Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) approach. We extend the solution of partial differential equations (PDEs) from a 2D framework to a comprehensive 3D scenario. Simulation results using a quadrotor as a benchmark example demonstrate its effectiveness.
This chapter delves into the philosophical and sociological foundations of the principle of responsibility and explores how this concept has been applied to understand businesses’ agency and responsibility. The chapter further examines responsibility as a principle for motivating and justifying business action towards the circular economy, proposing the concept of circular business responsibility. To illustrate how the principle of responsibility operates within the circular economy, the chapter examines the role of Extended Producer Responsibility in global supply chains, showcasing successful voluntary initiatives that exemplify proactive producer responsibility.
This book comprises a collection of contributions on circular economy in sustainable supply chains. The chapters offer a global perspective on challenges, concepts and implementation cases. The distinguished authors of the chapters, hailing from different locations across the world, bring diverse perspectives and research methods to clarify specific issues related to the integration of circular economy in supply chains across various industries. The contributions are organised into three parts. “Part I: The R-Principles of Circular Economy” features microchapters exploring the foundational principles of the circular economy, encapsulated by the R-principles. “Part II: Theoretical Perspectives of Circular Economy in Global Supply Chains” includes contributions that discuss theoretical issues, providing a robust analytical framework. Finally, “Part III: Practical Implementations of Circular Economy in Global Supply Chains” highlights case studies from various industries and regions, illustrating real-world applications and successes.
The circular economy relies on several principles oriented to guide and refine decision-making processes across individual, organisational and systemic levels. Integral to the circular economy is the principle of regeneration. This chapter aims to fulfil a dual objective. Firstly, it seeks to provide a clear and comprehensive definition of regeneration as a principle of circular economy. Secondly, it endeavours to provide a practical illustration of how the companies can effectively operationalise the regeneration principle within their global supply chains. By scrutinising and clarifying the conceptual underpinnings of regeneration, this chapter aims to contribute to a deeper understanding of its significance in advancing circular economy practices. Furthermore, a case study analysis of GreenWave elucidates the purpose, practical strategies and business model features through which businesses can integrate regenerative principles into their operations, thereby fostering sustainability, resilience and ecological stewardship on a global scale.
This chapter examines the principle of respect within the circular economy context. It begins with a brief overview of the nature of respect, followed by an exploration of four distinct types of respect. The discussion then shifts to the respect for the rights of future generations and the respect for planetary and social boundaries. The challenges of integrating the principle of respect for planetary and social boundaries within global supply chains are also addressed. Finally, the chapter concisely describes how Unilever implements this integration through a specialised planetary boundaries life cycle assessment.
Small-scale biogas systems hold promise as reliable renewable energy sources in developing nations; however, adequate and consistent supply of feedstock remains a challenge. Agricultural residue, due to their lack of competition with food crops for resources, is touted as a dependable feedstock choice. This article therefore examines agricultural residues as potential biogas plant feedstocks in the Fès-Meknès region of Morocco, using a structured farm survey to evaluate livestock types, crop varieties, and residue utilization. Additionally, the study explores the challenges and drivers influencing biogas technology adoption in Morocco. Findings indicate a predominance of small-scale farms with livestock (averaging 11 cattle, 45 sheep, and 20 chicken) and mainly subsistence crop production, making these farms suitable candidates for small-scale biogas plants. Key barriers to adoption include a lack of awareness about the technology, along with technical and financial constraints. However, raising awareness, establishing demonstration plants, and offering financial and non-financial incentives are identified as potential drivers of adoption. This research provides a foundation for implementing biogas technologies in the case study area and other developing nations, guiding researchers and governmental and non-governmental organizations in disseminating small-scale biogas systems as a reliable energy source and a method for converting agricultural residues into sustainable energy (biogas) and fertilizer.
Graphical Abstract
The impact of Automated Vehicles (AVs) on road traffic safety has become the focus of discussions among governmental organizations, academia, stakeholders, and OEMs. Questions about how safe the automated driving features should be and how the road infrastructure should be improved for the arrival of this new technology must be clarified to enable full acceptance by the customers and society and prepare the mobility of future cities. The fundamental architecture of automated vehicles comprises perception, planning, decision, and actuation. The operation of the perception system, which is responsible for understanding the environment in which the vehicle is inserted, relies mainly on the onboard sensors. However, the available ranging and vision sensors, e.g., LiDAR, radar, and camera, have several limitations. Scenarios with occlusion present a real challenge for state-of-the-art perception systems. The occlusion, caused by obstructing the sensors’ detection field, limits the vehicle’s perception ability and inhibits the detection of other road users in the surroundings, especially Vulnerable Road Users (VRUs). Infrastructure composed of Roadside Units (RSUs) equipped with infrastructure-based sensors can overcome the perception limitations of a system based solely on onboard sensors by monitoring the road environment with a larger field of view and reduced sensitivity to occlusion. This paper presents a collaborative approach for smart infrastructures and automated vehicles for vulnerable road users’ collision avoidance. The proposed extended perception system comprises four main modules: traffic monitoring, long-term motion prediction, collision risk assessment, and trajectory planning. In the event of a safety-critical scenario, the infrastructure generates a safe and comfortable evasive maneuver to avoid a possible collision. Hence, the proposed approach provides a complete solution to overcome scenarios with occluded VRUs. It allows AVs to react to a critical situation with a longer time-to-collision than other systems relying only on onboard sensors, increasing the chance of successful avoidance even when implementing smoother maneuvers. This contributes considerably to the safe and comfortable operation of automated vehicles.
The perception of the vehicle’s environment is crucial for automated vehicles. Therefore, environmental sensors’ reliability and correct functioning are becoming increasingly important. Current vehicle inspections and self-diagnostics must be adapted to ensure the correct functioning of environmental sensors throughout the vehicle’s lifetime. There are several promising approaches for developing new test methods for vehicle environmental sensors, one of which has already been developed in our previous work. A method for testing vehicle front cameras was developed. In this work, the method is improved and applied again. Various test vehicles, including the Tesla Model 3, Volkswagen ID.3, and Volkswagen T-Cross, are stimulated by simulating driving scenarios. The stimulation is carried out via a tablet positioned before the camera. The high beam assist is used to evaluate the vehicle’s reaction. It was observed whether the vehicle switched from high to low beam as expected in response to the stimulation. Although no general statement can be made, the principle of stimulation works. A vehicle reaction can be successfully induced using this method. In further test series, the influence of display brightness is examined for the first time in this work. The results show that the display brightness significantly influences the test procedure. In addition, the method is validated by stimulation with colored images. It is shown that no complex traffic simulation is necessary to trigger a vehicle reaction. In the following validation approach, the CAN data of the Tesla Model 3 is analyzed during the tests. Here, too, the assumption that the vehicle reaction is based solely on the detected brightness instead of identifying road users is confirmed. The final validation approach examines the method’s applicability to other vehicles and high beam assist technologies. Although the method could not be used on the Volkswagen T-Cross due to a fault detected by the vehicle’s self-diagnosis, it worked well on the Volkswagen ID.3. This vehicle has a dynamic light assist in which individual segments of the high beam are dimmed during stimulation. Although the method developed to stimulate vehicle front cameras is promising, the specific factors that trigger the vehicle responses remain to be seen. This uncertainty suggests that further research is needed better to understand the interaction of stimulation and sensor detection.
The construction industry is currently facing challenges such as skilled labor shortages, limited automation, and inadequate digitalization, particularly for small and medium-sized enterprises (SME), amidst rising interest rates and decreasing subsidies for builders. To address these challenges, a simulation model library for construction is being established. The Plant Simulation System is used to map construction site systems with various model components, enabling digital simulation of the environment and supply chains. Customized simulation parameters are used to simulate specific construction requirements. This paper describes the use of masonry robots and transportation in wall and floor construction and their impact on site performance. The simulation model library REMUS is important for digitalizing construction sites, allowing for the assessment of innovative systems before construction and estimation of investment returns. Simulations can be used to evaluate investments and future concepts.
In this study, the effect of temperature changes on the voltage decay and current behavior of lithium‐ion cells is investigated, focusing on a comparison between open‐circuit voltage (OCV) measurements and float current IFloat measurements. Using our self‐developed advanced Floater system, the voltage decay rates dUdtOCV from OCV and float current measurements for three different cell types are assessed. Temperature ramps and steps, ranging from 5 °C to 50 °C, are applied to capture the impact of entropic effects and aging mechanisms. Both methods effectively capture aging dynamics, showing strong agreement between ramp and step measurements. Deviations arise only in cases of strong entropy effects due to differences in measurement strategies. The findings confirm that float currents do not introduce additional aging beyond that captured by OCV measurements. The relationship between OCV and float current is governed by differential capacity dUdQ , which varies with cell voltage and temperature. Furthermore, strong deviations from classical differential voltage analysis but high agreement with local pulse measurements are observed, especially at low depths of discharge. This can be explained by the hysteresis effect of graphite. These findings highlight the benefits of high‐precision float current measurements in aging studies, particularly in contrast to simpler OCV methods.
Cooperative intelligent transportation systems continuously send self-referenced data about their current status in the Cooperative Awareness Message (CAM). Each CAM contains the current position of the vehicle based on GPS accuracy, which can have inaccuracies in the meter range. However, a high accuracy of the position data is crucial for many applications, such as electronic toll collection or the reconstruction of traffic accidents. Kalman filters are already frequently used today to increase the accuracy of position data. The problem with applying the Kalman filter to the position data within the Cooperative Awareness Message is the low temporal resolution (max. 10 Hz) and the non-equidistant time steps between the messages. In addition, the filter can only be applied to the data retrospectively. To solve these problems, an Extended Kalman Filter and an Unscented Kalman Filter were designed and investigated in this work. The Kalman filters were implemented with two kinematic models. Subsequently, driving tests were conducted with two V2X vehicles to investigate and compare the influence on the accuracy of the position data. To address the problem of non-equidistant time steps, an iterative adjustment of the Process Noise Covariance Matrix Q and the introduction of additional interpolation points to equidistance the received messages were investigated. The results show that without one of these approaches, it is impossible to design a generally valid filter to improve the position accuracy of the CAM position data retrospectively. The introduction of interpolation points did not lead to a significant improvement in the results. With the Q matrix adaptation, an Unscented Kalman Filter could be created that improves the longitudinal position accuracy of the two vehicles under investigation by up to 80% (0.54 m) and the lateral position accuracy by up to 72% (0.18 m). The work thus contributes to improving the positioning accuracy of CAM data for applications that receive only these data retrospectively.
Human-machine ethics has emerged as a rapidly growing research field in recent years. However, it seems that Generative Artificial Intelligence (AI) leads to a paradigm shift from human-machine interaction to co-action. The ethical assessment of such relationships is still in the making and needs further scrutiny. First, studies about the influence of technology in human-system interactions and manipulation are reviewed. Second, the “mutual theory of mind” approach is critically examined to identify its shortcomings. Third, creating user models is reconstruced to demonstrate the strategies of systems. Finally, use cases are discussed and assessed to outline ethical implications.
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