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This paper presents an improved and easy-to-use battery dynamic model. The charge and the discharge dynamics of the battery model are validated experimentally with four batteries types. An interesting feature of this model is the simplicity to extract the dynamic model parameters from batteries datasheets. Only three points on the manufacturer’s di...
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... particularity of this model is the use of a filtered current ( i ∗ ) flowing through the polarisation resistance. In fact, experimental results show a voltage slow dynamic behaviour for a current step response. This filtered current solve also the algebraic loop problem due to the simulation of electrical systems in Simulink. Finally, the OCV varies non-linearly with the SOC. This phenomenon is modelled by the polarisation voltage term. The exponential zone of equation (1) is valid for the Li-Ion battery. For the other batteries (Lead-Acid, NiMH and NiCD), there is a hysteresis phenomenon between the charge and the discharge, no matter the SOC of the battery [6], [7]. This behaviour occurs only in the exponential area, as shown in Fig. 2. This phenomenon can be represented by a non-linear dynamic ...
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Citations
... The present paper proposes equations using proper physical units, which include the SoC-dependent behavior of internal resistance. Tremblay et al. stated for [20], as well as their extended version from 2009 [23], that the sets of equations would not model the so-called Peukert effect, which means the discharge current would not change the predicted available capacity under constant current discharge [12]. Nevertheless, the present paper will demonstrate that this kind of equation can well describe the main reasons for the Peukert-effect of lithium-ion cells. ...
... In 2018, Song et al. [14] Tremblay et al. stated for [20], as well as their extended version from 2009 [23], that the sets of equations would not model the so-called Peukert effect, which means the discharge current would not change the predicted available capacity under constant current discharge [12]. Nevertheless, the present paper will demonstrate that this kind of equation can well describe the main reasons for the Peukert-effect of lithium-ion cells. ...
... The classic Peukert equation (1) leads to a straight-line representation (negative linear slope −k) when plotting the employed constant current I versus the reached discharge time t end , and both axes are scaled in a logarithmic order. The experiments and application of the proposed equations using (20)- (22) with the exemplary specimen showed its validity for reflecting the Peukert behavior up to discharge C-rates of approximately 5 C n (see Figures 4 and 5), in which the Peukert exponent can be derived from (23). ...
The design and operation of performant and safe electric vehicles depend on precise knowledge of the behavior of their electrochemical energy storage systems. The performance of the battery management systems often relies on the discrete-time battery models, which can correctly emulate the battery characteristics. Among the available methods, electric circuit-based equations have shown to be especially useful in describing the electrical characteristics of batteries. To overcome the existing drawbacks, such as discrete-time simulations for parameter estimation and the usage of look-up tables, a set of equations has been developed in this study that solely relies on the open-circuit voltage and the internal resistance of a battery. The parameters can be obtained from typical cell datasheets or can be easily extracted via standard measurements. The proposed equations allow for the direct analytical determination of available discharge capacity and the available energy content depending on the discharge current, as well as the Peukert exponent. The fidelity of the proposed system was validated experimentally using 18650 NMC and LFP lithium-ion cells, and the results are in close agreement with the datasheet.
... Similarly, another research uses modelica methodologies to model EV pickup attributes to study the dynamic response of an electric vehicle [3]. Other such models for battery dynamics and solar hybrid vehicles have been given in [4] and [5] respectively. In conclusion, there is enough research material that can be found for developing a model to study the vehicle dynamics of an electric vehicle. ...
While the global electric vehicle (EV) adoption is on rise, developing countries like Pakistan have been facing many obstacles in the face of EV adoption such as shortfall of electricity, high EV prices, low average income and absence of commercial and residential charging infrastructure. In this paper, we propose a design of a micro solar electric vehicle, which would help overcome all of these problems and provide an economical yet feasible solution. The design and system sizing of the micro solar EV was done in HOMER Pro. A dynamic model of the micro solar EV was created in MATLAB/Simulink, which
implemented PV generation, maximum power point tracking, battery charging and discharging, DC-motor operation and speed control of the electric vehicle, while taking into consideration environmental factors like irradiance and temperature.
... Alat penelitian terdiri dari perangkat keras dan perangkat lunak. Perangkat keras yang digunakan dalam penelitian ini terangkum pada Tabel 1. Persamaan 4 dan 5 merupakan model baterai [18]. Nilai dan secara berturut-turut adalah resistansi internal baterai dan tegangan baterai. ...
... Tabel 4. Spesifikasi baterai [18] Parameter Nilai ...
Management of battery at direct current (DC) microgrids is the essential factor to maintain the balance of power and the bus voltage's stability in the grids. To ensure the quality of battery management is necessary to simulate the operation of the battery management system. This paper presents the simulations in various battery management algorithms. The simulations were designed to determine the effect of these variations on the balance of the power balance, bus voltage stability, and battery consumption level. The configurations of one, two, and three battery groups could maintain a balance of power balance. The three arrangements could ensure the bus voltage stability at a value of 24 Volts. The variations in the battery group configurations cause different battery consumption levels. The three-battery group configuration has a lower power consumption rate of 0.1% than other battery group configurations. Variations in the battery management algorithms affect power balance, bus voltage stability, and battery electricity consumption. The result showed the best power balance achieved by an algorithm without counting a value-based state of charge (SoC). The algorithm also committed that the difference between the supply and demand equal to 0 Watts. For the voltage stability, the algorithms that were counting a value-based SoC can maintain bus voltage stability at a value of 24 Volts. Nevertheless, other algorithms that rely on less than one SoC value-based and have the lowest mean value of SoC reduction are equal to 0.19%.
... Alat penelitian terdiri dari perangkat keras dan perangkat lunak. Perangkat keras yang digunakan dalam penelitian ini terangkum pada Tabel 1. Persamaan 4 dan 5 merupakan model baterai [18]. Nilai dan secara berturut-turut adalah resistansi internal baterai dan tegangan baterai. ...
... Tabel 4. Spesifikasi baterai [18] Parameter Nilai ...
Management of battery at direct current (DC) microgrids is the essential factor to maintain the balance of power and the bus voltage's stability in the grids. To ensure the quality of battery management is necessary to simulate the operation of the battery management system. This paper presents the simulations in various battery management algorithms. The simulations were designed to determine the effect of these variations on the balance of the power balance, bus voltage stability, and battery consumption level. The configurations of one, two, and three battery groups could maintain a balance of power balance. The three arrangements could ensure the bus voltage stability at a value of 24 Volts. The variations in the battery group configurations cause different battery consumption levels. The three-battery group configuration has a lower power consumption rate of 0.1% than other battery group configurations. Variations in the battery management algorithms affect power balance, bus voltage stability, and battery electricity consumption. The result showed the best power balance achieved by an algorithm without counting a value-based state of charge (SoC). The algorithm also committed that the difference between the supply and demand equal to 0 Watts. For the voltage stability, the algorithms that were counting a value-based SoC can maintain bus voltage stability at a value of 24 Volts. Nevertheless, other algorithms that rely on less than one SoC value-based and have the lowest mean value of SoC reduction are equal to 0.19%. Keywords: Direct current microgrid, energy storage system, and battery management. I. PENDAHULUAN Masyarakat seringkali menggunakan peralatan listrik seperti komputer jinjing, telepon, televisi, dan perangkat rumah tangga lainnya yang membutuhkan suplai listrik arus searah menggunakan jaringan listrik skala mikro arus searah [1]. Jaringan listrik skala mikro tersebut adalah jaringan energi lokal yang melibatkan sumber energi terdistribusi dan sistem penyimpanan energi [2]. Konsep jaringan listrik ini dapat menjadi solusi optimal karena efisiensi, biaya, dan keandalannya [3]. Jaringan listrik skala mikro dapat dijalankan dalam dua mode yakni mode terhubung jaringan listrik atau mode mandiri (tidak terhubung jaringan listrik). Keseimbangan neraca daya adalah isu penting pada mode mandiri karena sifat intermiten yang dimiliki oleh sumber energi terbarukan [4]. Baterai menjadi komponen yang berperan penting untuk menjaga kestabilan operasional sistem yang bersifat intermiten [5]. Sumber energi terbarukan seperti panel surya dan baterai terhubung ke bus DC melalui converter DC/DC [6]. Manajemen baterai pada jaringan listrik arus searah skala mikro mode mandiri diperlukan untuk menjaga kestabilan tegangan bus dan keseimbangan daya listrik antara sumber energi dengan beban listrik. Oleh karena itu, algoritma dari manajemen baterai menjadi mempunyai peranan yang cukup penting pada jaringan listrik skala mikro arus searah. Banyak penelitian yang mencoba untuk mengembangkan algoritma-algoritma manajemen baterai. Jayasena [7] dan Sahoo [8] telah mengembangkan algoritma manajemen baterai berbasis state of charge (SoC) dan tegangan bus pada sistem penyimpanan baterai yang terdiri dari satu baterai. Jing [9] meneliti algoritma manajemen baterai berbasis tegangan bus dan tegangan baterai pada sistem penyimpanan energi yang terdiri dari satu baterai dan satu kapasitor ultra. Das [10] mengembangkan algoritma manajemen baterai berbasis SoC pada sistem penyimpanan energi yang terdiri dari sejumlah baterai. Algoritma manajemen baterai berbasis SoC menjadi tren penelitian dalam rentang tahun 2018-2020 dan umumnya sistem penyimpanan energi yang diteliti terdiri dari 1 baterai. Algoritma manajemen baterai pada sejumlah baterai masih perlu diselidiki lebih lanjut. Makalah ini mempresentasikan penelitian yang bertujuan menganalisis algoritma manajemen baterai berbasis state of charge (SoC) pada sistem penyimpan energi yang terdiri dari sejumlah baterai. Variasi konfigurasi baterai dan algoritma manajemen baterai akan disimulasikan pada studi kasus. Pengaruh konfigurasi baterai dan algoritma manajemen baterai dianalisis untuk mengetahui kemampuannya dalam menjaga keseimbangan neraca daya, kestabilan tegangan bus, dan tingkat konsumsi baterai. Untuk pengujian penelitian dibatasi pada obyek penelitian dan metode pengujian algoritma. Obyek penelitian terbatas pada jaringan listrik arus searah skala mikro mode mandiri yang terdiri dari panel surya, sistem penyimpan energi yang terdiri dari tiga baterai, konverter tipe arus searah, dan beban listrik arus searah. Algoritma manajemen baterai dievaluasi menggunakan metode simulasi jaringan listrik arus searah skala mikro [11]. II. METODOLOGI Pada penelitian ini, simulasi jaringan listrik arus searah skala mikro dilakukan untuk mengevaluasi
... The battery terminal voltage has a nonlinear dependency on the battery capacity. Here, the mathematical model of the battery dynamics, as discussed in [32], [33] has been adopted. ...
A battery energy storage system (BESS) can play a critical role in regulating system frequency and voltage in an islanded microgrid. A
$\mu$
-synthesis-based robust control has been proposed for dc link voltage regulation of BESS for achieving frequency regulation and voltage quality enhancement of islanded microgrid. Variation in the operating condition of ac microgrid affects the operating condition of the BESS converter. This controller synthesis accounts for such uncertain variations as parametric uncertainty. The stability and performance of the proposed controller can be guaranteed for bounded parametric variations. The bounds on parameters are selected based on practical limitations of BESS. The proposed controller's performance is tested on an islanded CIGRE TF C6:04:02 benchmark low voltage ac microgrid system. The importance of dc link voltage regulation is analyzed based on performance comparison with a benchmark controller. The controller performance is also validated using a real-time Typhoon HIL emulator.
... The circuit is based off the work of Zhu et al. [37]. and Tremblay et al. [36] (see Fig. 10). The internal resistance is assumed to be constant during the charge and discharge cycles and does not vary with the amplitude of the current. ...
... Input/output given to the fuel cell model from Njoya[34].Fig. 10e Equivalent circuit of the battery included in the model[36]. ...
This paper presents a simulation tool for marine hybrid power-plants equipped with polymer exchange membrane fuel cells and batteries. The virtual model, through the combination of operational data and dynamically modelled subsystems, can simulate power-plants of different sizes and configurations, in order to analyze the response of different energy management strategies. The model aims to replicate the realistic behavior of the components included in the vessel's grid, to asses if the hardware selected by the user is capable of delivering the power set-point requested by the energy management system. The model can then be used to optimize key factors such as hydrogen consumption. The case study presented in the paper demonstrates how the model can be used for the evaluation of a retrofitting operation, replacing a diesel electric power-plant with fuel cells and batteries. The vessel taken into consideration is a domestic ferry, operating car and passenger transport in Denmark. The vessel is outfitted with a diesel electric plant and an alternative hybrid power-plant is proposed. The hybrid configuration is tested using the model in a discrete time-domain.
... Given this, it is advisable to use the Shepherd's parametric model [8,9], which describes the chargedischarge characteristic of SB. This system of equations, is implemented in the Simscape Simulink model and has the form (2) ...
This article determines a methodology to maximize a specific power of the electrical power system of a geostationary spacecraft, using the EPS simulation model. A typical (for GEO spacecraft) fully-regulated EPS structure is considered. The advantages of using the full bridge quasi-resonant converters with galvanic isolation are considered. The results of the energy efficiency estimation of power converters at various ranges of input voltages, as well as the criteria and conditions for calculating the positive energy budget of a GEO spacecraft are presented. The application of the EPS simulation model is shown and the results of optimization of the proposed EPS energy and mass characteristics for 6 and 13 kW payloads are described
... Given this, it is advisable to use the Shepherd's parametric model [8,9], which describes the chargedischarge characteristic of SB. This system of equations, is implemented in the Simscape Simulink model and has the form (2) ...
... The discharging process is therefore divided into exponential zone, nominal zone, B Q and fast-discharging zone to reflect this dynamic feature. 16 Fig. 2 Typical discharging curve of lithium ion battery 15 Currently, there are a variety of models describing the dynamic characteristic of the battery, e.g., Equivalent Circuit Model (ECM), [16][17][18] electrochemical model, 19 and intelligent mathematical model. 20 With the high fidelity and complexity, the electrochemical model is mainly utilized in the battery design and manufacturing. ...
... The discharging process is therefore divided into exponential zone, nominal zone, B Q and fast-discharging zone to reflect this dynamic feature. 16 Fig. 2 Typical discharging curve of lithium ion battery 15 Currently, there are a variety of models describing the dynamic characteristic of the battery, e.g., Equivalent Circuit Model (ECM), [16][17][18] electrochemical model, 19 and intelligent mathematical model. 20 With the high fidelity and complexity, the electrochemical model is mainly utilized in the battery design and manufacturing. ...
... is the internal resistance, is the filtered current, is the nominal capacity, K is B R F I N Q the polarization resistance, A is the exponential zone voltage amplitude, and B is the exponential zone time constant inverse. Oliver and Louis 16 derived the equations to determine the coefficients K, A and B 16 (6) ...
The increasing gross weight of electric Unmanned Aerial Vehicle (UAV) poses a challenge in practical applications. The range and endurance of the electric UAV are limited by the fixed mass of the battery package. In this work, a design optimization method for the battery package topology of small electric UAV is proposed to enhance the performance. To improve the accuracy of the method, the dynamic battery model and simplified electric component models are presented. These models are utilized by the trajectory optimization method, which takes the dynamic characteristic into consideration to calculate the aircraft performance. The direct optimal control method is used for solving the trajectory optimization problem, and this method is tested on a small blended-wing-body electric aircraft. The test result shows that the range and energy-consumption are mainly influenced by the parallel topology of the battery package, while the flight time in climb phase is more sensitive to the series topology. It is deduced that the range- and energy-optimal design points can be considered concurrently in design optimization. The work proves the feasibility of integrating the trajectory optimization and battery package design.
... Batteries are modelled based on their charging and discharging cycles. The number of lifecycles reduces with the Depth of Discharge (DOD) [46]. Also, a few models use the currentvoltage characteristics of a battery as a function of State of Charge (SOC) [47]. ...
Photovoltaic systems (PV) are one of the most promising renewable energy technologies for on-site generation. Most of the techno-economic studies consider distributed standalone photovoltaic generation with little consideration of community-based standalone photovoltaic systems. Location-based case studies are required to provide economic and reliable photovoltaic systems to meet the peak loads of residential neighbourhoods in an optimized manner. This paper devises an integrated evaluation methodology; a combination of white-box energy modelling and black box photovoltaic design optimization. This research uses optimization methods to develop a quantitative optimized model for analysing the opportunities of centralized systems to adequately meet the demands of a residential neighbourhood and support the grid. This analysis includes three metrics including the level of the energy production, reliability of system for peak power and finally the capital cost of implementation in residential districts. Results indicate that the size of a centralized photovoltaic installation is less when compared to distributed installations to support a similar single peak load. The required converter size is reduced for the centralized system owing to the reduced system size. Centralized installations require fewer batteries to store surplus energy produced due to increased interaction of energy flows. Centralized installations are economically more viable than distributed ones.
