Characterization and modeling of a hybrid electric vehicle lithium-ion battery pack at low temperatures

Although lithium-ion batteries have penetrated hybrid electric vehicles (HEVs) and pure electric vehicles (EVs), they suffer from significant power capability losses and reduced energy at low temperatures. To evaluate those losses and to make an efficient design, good models are required for system simulation. Subzero battery operation involves nonclassical thermal behavior. Consequently, simple electrical models are not sufficient to predict bad performance or damage to systems involving batteries at subzero temperatures. This paper presents the development of an electrical and thermal model of an HEV lithium-ion battery pack. This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries over the selected operating range of currents and battery capacities. In addition, a thermal modeling method has been developed for this model so that it can predict the battery core and crust temperature by including the effect of internal resistance. First, various discharge tests on one cell are carried out, and then, cell's parameters and thermal characteristics are obtained. The single-cell model proposed is shown to be accurate by analyzing the simulation data and test results. Next, real working conditions tests are performed, and simulation calculations on one cell are presented. In the end, the simulation results of a battery pack under HEV driving cycle conditions show that the characteristics of the proposed model allow a good comparison with data from an actual lithium-ion battery pack used in an HEV. © 2015 IEEE

Low temperature performance of Lithium-ion batteries for different drive cycles

Lithium-ion batteries, suitable for Battery-electric vehicles (BEVs) due to their high energy and power densities, and lifetime demonstrate deterioration in energy and power available at lower temperatures. It is attributed to reduction in capacity and increase in internal resistance. Investigations are carried out to determine energy, and power decline for four drive-cycles: FTP, NEDC, UDDS and US06. The minimum temperatures where the battery meets the drive-cycles’ energy and power requirements are determined. The impact of regenerativebraking and self-heating on battery performance is discussed. The minimum temperature where any drive-cycle is met by the battery is directly proportional to its aggressiveness

Exploring the effects of below-freezing temperatures on smartphone usage

While the use of smartphones in extreme temperatures does not necessarily occur every day nor in all parts of the world, numerous use cases can be highlighted where the use of smartphones in cold temperatures is mandatory. Modern smartphones are designed to function in a wide range of temperatures, but when exposed to extreme cold temperatures the performance and reliability can significantly suffer. This paper presents a controlled laboratory experiment, using a clinical cold chamber to expose seven smartphone models to both medium cold (0 degrees C to -20 degrees C) and extreme cold (-30 degrees C) environments. The results showcase the smartphones' sensing software's lack of awareness of the cold environment, as well as reliability issues in the form of device crashes across the whole range of tested devices. We present a strategy for implementing monitoring application designs to both appropriately sense the effect of cold environments, as well as predicting device shutdowns in extreme cold. (C) 2021 The Authors. Published by Elsevier B.V.Peer reviewe

A new consideration for validating battery performance at low ambient temperatures

Existing validation methods for equivalent circuit models (ECMs) do not capture the effects of operating lithium-ion cells over legislative drive cycles at low ambient temperatures. Unrealistic validation of an ECM may often lead to reduced accuracy in electric vehicle range estimation. In this study, current and power are used to illustrate the different approaches for validating ECMs when operating at low ambient temperatures (−15 °C to 25 °C). It was found that employing a current-based approach leads to under-testing of the performance of lithium-ion cells for various legislative drive cycles (NEDC; FTP75; US06; WLTP-3) compared to the actual vehicle. In terms of energy demands, this can be as much as ~21% for more aggressive drive cycles but even ~15% for more conservative drive cycles. In terms of peak power demands, this can range from ~27% for more conservative drive cycles to ~35% for more aggressive drive cycles. The research findings reported in this paper suggest that it is better to use a power-based approach (with dynamic voltage) rather than a current-based approach (with fixed voltage) to characterise and model the performance of lithium-ion cells for automotive applications, especially at low ambient temperatures. This evidence should help rationalize the approaches in a model-based design process leading to potential improvements in real-world applications for lithium-ion cell

Comparative analysis of battery electric vehicle thermal management systems under long-range drive cycles

Due to increasing regulation on emissions and shifting consumer preferences, the wide adoption of battery electric vehicles (BEV) hinges on research and development of technologies that can extend system range. This can be accomplished either by increasing the battery size or via more efficient operation of the electrical and thermal systems. This study endeavours to accomplish the latter through comparative investigation of BEV integrated thermal management system (ITMS) performance across a range of ambient conditions (-20 °C to 40 °C), cabin setpoints (18 °C to 24 °C), and six different ITMS architectures. A dynamic ITMS modelling framework for a long-range electric vehicle is established with comprehensive sub models for the operation of the drive train, power electronics, battery, vapor compression cycle components, and cabin conditioning in a comprehensive transient thermal system modelling environment. A baseline thermal management system is studied using this modelling framework, as well as four common thermal management systems found in literature. This study is novel for its combination of comprehensive BEV characterization, broad parametric analysis, and the long range BEV that is studied. Additionally, a novel low-temperature waste heat recovery (LT WHR) system is proposed and has shown achieve up to a 15% range increase at low temperatures compared to the baseline system, through the reduction of the necessary cabin ventilation loading. While this system shows performance improvements, the regular WHR system offers the greatest benefit, a 13.5% increase in cold climate range, for long-range BEV drive cycles in terms of system range and transient response without the need for additional thermal system equipment

Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging

Electro-mobility is increasing significantly in the urban public transport and continues to face important challenges. Electric bus fleets require high performance and extended longevity of lithium-ion battery at highly variable temperature and in different operating conditions. On the other hand, bus operators are more concerned about reducing operation and maintenance costs, which affects the battery aging cost and represents a significant economic parameter for the deployment of electric bus fleets. This paper introduces a methodological approach to manage overnight charging of an electric bus fleet. This approach identifies an optimal charging strategy that minimizes the battery aging cost (the cost of replacing the battery spread over the battery lifetime). The optimization constraints are related to the bus operating conditions, the electric vehicle supply equipment, and the power grid. The optimization evaluates the fitness function through the coupled modeling of electro-thermal and aging properties of lithium-ion batteries. Simulation results indicate a significant reduction in the battery capacity loss over 10 years of operation for the optimal charging strategy compared to three typical charging strategies

Prolongamento da Vida Útil de um Transformador através do Agendamento do Carregamento de Veículos Eléctricos numa Unidade Industrial Insular com Microgeração Fotovoltaica

A mobilidade eléctrica tem vindo a apresentar uma evolução considerável nos últimos anos, tanto na União Europeia como nos restantes países da OCDE. Para o efeito contribuíram inúmeras decisões estratégicas e desenvolvimento de legislação, o que permite que esta aposta pudesse ser ganha gradualmente e de um modo sustentável. Os construtores mundiais de veículos têm desenvolvido vários modelos de veículos eléctricos (VEs), apresentando soluções inovadoras para vários elementos dos VEs o que permite que sejam uma alternativa viável em relação aos veículos de combustão interna, tanto em autonomia, como em gastos de manutenção e alimentação dos motores, sobretudo de uma forma menos poluente. O propósito deste trabalho é analisar o impacte que poderá ter uma elevada concentração de VEs a carregar simultaneamente numa unidade industrial com microgeração fotovoltaica na deterioração da vida útil de um posto de transformação através da degradação térmica do óleo dieléctrico do transformador na ilha de São Miguel, Açores. Neste trabalho, o modelo térmico do transformador irá ser usado para estimar a temperatura de hot-spot (θh) dado o diagrama de carga diário da unidade industrial alimentada pelo posto de transformação em questão. Dados reais irão ser utilizados para as entradas principais do modelo a ser desenvolvido, tal como os parâmetros do transformador, a radiação solar, a temperatura ambiente e as características de vários VEs. Seguidamente, uma optimização do agendamento dos VEs terá que ser efectuada com o objectivo de mitigar os impactos negativos que uma elevada concentração de VEs a carregar simultaneamente na unidade industrial insular com microgeração fotovoltaica poderá ter no posto de transformação. Para a execução deste trabalho ser concluída com sucesso, certas habilidades com software serão necessárias. Uma dessas habilidades é a utilização do software/ferramenta MathWorks Matlab. Por conseguinte, vários cenários do carregamento dos VEs perante vários níveis de penetração no mercado serão modelados. O propósito da simulação de tais cenários justifica-se através da avaliação da validade, robustez e eficácia do modelo proposto e identificação dos seus limites. Uma apresentação detalhada de resultados só irá fortalecer a qualidade académica do trabalho proposto e cimentar os pontos fortes das conclusões deduzidos a partir dos resultados

Hybrid Electric Vehicle Energy Management Strategy with Consideration of Battery Aging

The equivalent consumption minimization strategy (ECMS) is a well-known energy management strategy for Hybrid Electric Vehicles (HEV). ECMS is very computationally efficient since it yields an instantaneous optimal control. ECMS has been shown to minimize fuel consumption under certain conditions. But, minimizing the fuel consumption often leads to excessive battery damage. The objective of this dissertation is to develop a real-time implementable optimal energy management strategy which improves both the fuel economy and battery aging for Hybrid Electric Vehicles by using ECMS. This work introduces a new optimal control problem where the cost function includes terms for both fuel consumption and battery aging. The Ah-throughput method is used to quantify battery aging. ECMS (with the appropriate equivalence factor) is shown to also minimize the cost function that incorporates battery aging. Finding the appropriate equivalence factor often required prior knowledge of the entire drive cycle. While using the appropriate equivalence factor might miss the opportunities for fuel savings under certain conditions. Therefore, an adaptive control law of equivalence factor called Catch Energy Saving Opportunity (CESO) has been introduced in this work to make the proposed aging ECMS real-time implementable. In order to better understand the impact of the developed optimal strategies on battery aging in HEVs, systematic analysis has been performed to find relations between fuel economy, battery aging and the optimization decisions when using ECMS. Therefore, the varies equivalence factors, state of charge constraints and battery temperatures are observed and analyzed under different Combined Drive-cycles (CDs). The CDs are formulated to test the energy management strategy and battery aging with weights on city and highway drive. In addition, rule-based control in charge-depletion mode aimed to improve battery aging has been simulated in a HEV truck. The simulation results show that, the fuel consumed and battery aging degradation during varied operation could be significantly improved by using a simple control rule in charge-depletion mode. This further indicates the benefits of implementing a battery aging term which impacts the control decision in charge-sustaining ECMS. Based on the analysis results, an aging ECMS has been developed by adding a battery aging term as a cost to the battery. The simulation results showed that this optimal energy management strategy improves battery aging significantly with little or no penalty in fuel economy. In addition, aging CESO ECMS, a real-time optimal strategy, has been developed based on the proposed aging ECMS. The simulation results show that aging CESO ECMS improvs upon the basic aging ECMS performance