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Lithium‐ion cell chemistries are favored in the automotive sector, as they enable electric vehicles (EVs) to compete with traditional gasoline‐powered vehicles in terms of performance, range, and cost. The life and performance of these packs depend upon the Battery management system which monitors and controls the pack. The modeling, simulation, and analysis of a lithium‐ion battery pack that closely resembles an actual automobile battery are the focus of this paper. Real cells that are commercially available and specifically developed for automotive applications are modeled in the simulation environment. The cell characterization and formation of pack topology with heat exchange are addressed. A commercial electric car's power train model and EV dynamics are used in the simulation environment to test the modeled battery pack over various drive cycles. The performance analysis is upscaled by considering different aspects like resistive forces while driving, ambient temperature, initial conditions while the vehicle starts, etc. The battery manufacturer can verify the battery's performance under different load conditions, with a high degree of similarity to real‐world scenarios. The simulations are conducted on MATLAB/Simulink 2021b software. [ABSTRACT FROM AUTHOR]

Batteries are essential to mobilization and electrification as they are used in a wide range of applications, from electric vehicles to small mobile devices. All these devices are powered with AC or DC inside their systems, so they require different battery systems depending on their technical requirements. Batteries show unique characteristics depending on their types, and their needs vary based on their performance, ambient conditions, and so forth. One of the main demands for them is thermal stability. For batteries, thermal stability is not just about safety; it's also about economics, the environment, performance, and system stability. This paper has evaluated over 200 papers and harvested their data to build a collective understanding of battery thermal management systems (BTMSs). These studies are specifically designed to solve different problems. This paper has been prepared to show what these systems are, how they work, what they have been designed for, and under what conditions they should be applied. The BTMSs have been evaluated based on their method, method tools, discharge rate, maximum temperature, temperature difference values, and ambient and inlet temperatures. After evaluating over 200 studies, the results indicate that the passive BTMSs are not useful the cases where the temperature reaches higher values suddenly, especially for system systems that require higher discharge rates. On the other hand, active cooling methods do not manage the temperature difference in the battery cells. However, hybrid cooling methods address both cases admirably by compensating for both of their weaknesses and bringing out their advantages. The general optimum temperature for lithium battery batteries is 55°C. Even though there are many other parameters that need to be considered before making a decision for a BTMS design, the best performance for an optimum system seems to be methods 34, 38, and 22 as they are able to provide lower maximum temperature and temperature difference in the cells. [ABSTRACT FROM AUTHOR]

The heat dissipation around battery cells should be thoroughly examined to keep the battery pack running properly. This article mainly focuses on the 3D analysis of thermal distribution in lithium‐ion battery (LIB; 14650, 18650 and 26650) with varied geometry sizes and the thermal distribution of LIB packs (6s and 12s series) at different charge/discharge rate. It has been concluded that the capacity loss increases at higher SOC levels for the calendar aging as derived from the lumped model approach. Additionally, the rate of heat generation with the increase in battery size and its effect on the overall battery temperature has been observed. The proposed work has been simulated in COMSOL Multiphysics 5.6 for observing the temperature variations within the battery pack and the vital findings are stated from the conclusions. [ABSTRACT FROM AUTHOR]

This paper outlines a new simulation approach to study the effect of factors on the state of charge (SOC) consistency of Li‐ion battery packs. The proposed method is based on a system model and the Monte Carlo method. The system model includes 100 serial connected equivalent circuit models and their respective parameters. This paper divides the internal and external factors into two categories: independent factors such as internal resistance, capacity, Coulombic efficiency, leakage current, and comprehensive factors related to temperature. The Monte Carlo method simulates the differences and distribution of independent factors among cells. Temperature‐dependent factors are modeled with empirical formulas. Simulation results show that the main factors affecting SOC consistency are differences in battery temperature, leakage current, and Coulombic efficiency. Meanwhile, slight differences in capacity and internal resistance have little effect on SOC inconsistency. Furthermore, this paper demonstrates the effectiveness of the system model. [ABSTRACT FROM AUTHOR]

In this paper, the temperature response of a lithium‐ion type 18650 battery pack cooled by a thermoelectric air‐cooling module is presented. The effects of the airflow rate, on‐off cooling fan position, charging and discharging rate and cooling by the thermoelectric air‐cooling module are investigated. The charging and discharging procedures with different current rates of 2 A (0.06 C), 3 A (0.09 C), and 4 A (0.12 C) are investigated. The results showed that different test conditions of the thermoelectric air‐cooling module have a substantial effect on the temperature of the battery pack. It was demonstrated that a thermoelectric air‐cooling module has a decreased battery temperature of lower than 40°C. The operating conditions of the cooling fans have a substantial effect on battery temperature. The experiment in which all the cooling fans are turned on shows a higher cooling capacity than natural air cooling by approximately 16%–57%. However, when setting the on‐off position of the fans that are installed in different positions, the cooling capacity when the fans at the inlet and thermoelectric cooling heat sink are turned on and the fan at the outlet battery pack is turned off is slightly less than that when all the cooling fans are turned on by approximately 25%–57%. Therefore, it can be selected as an optimum for cooling the battery pack due to less power consumption and noise issues. The proposed research can be implemented as a guideline for the cooling system of energy storage, such as small electric vehicle platforms, ground batteries, and solar energy storage. [ABSTRACT FROM AUTHOR]

Academic research in the battery field frequently remains limited to small coin or pouch cells, especially for new materials that are still rather far from commercialization, which renders a meaningful evaluation at an early stage of development challenging. Here, the realization of large lab‐scale pouch cells comprising Sn0.9Mn0.1O2 (SMO), prepared via an easily scalable hydrothermal synthesis method, as an alternative active material for the negative electrode and LiNi0.6Mn0.2Co0.2O2 (NMC622) as a commercially available active material for the positive electrode is reported. Nine double‐layer pouch cells are connected in series and parallel, suitable for powering a remote‐controlled vehicle. Subsequently, these SMO‖NMC622 cells are critically evaluated by means of an early‐stage life cycle assessment and compared to graphite‖NMC622 cells, in order to get first insights into the potential advantages and challenges of such lithium‐ion chemistry. [ABSTRACT FROM AUTHOR]

The application of lithium‐ion batteries especially for electric vehicles has been limited by the factors of safety, lifetime, charging time, and cost. One of the principal limitations is that the performance of Li‐ion batteries drops intensely in a cold environment. Cold environment dramatically reduces the available capacity of the batteries and increases its internal impedance at the same time. Therefore, the estimation of state‐of‐health is of great importance in battery performance evaluation and lifetime prediction. Furthermore, the heating methods need to be developed to ensure that batteries work in abnormal temperature conditions. This paper conducts a comprehensive review specifically on the poor performance of lithium‐ion cells under severe conditions. The content contains three sections. First, a comprehensive study on the aging mechanisms of lithium‐ion batteries at cold temperatures is undertaken. Second, the estimation methods of the health state of the batteries are conducted, which is vital to understand the fundamentals and quantify the performance and aging effects for lithium‐ion batteries. Third, the heating methods are classified and studied in detail to reduce the degradation mechanism and promote the performance of lithium‐ion batteries under sub‐zero conditions. [ABSTRACT FROM AUTHOR]

This study proposes a novel hybrid energy storage system (HESS) composed of a battery pack and a superconducting magnetic energy storage (SMES) for electric vehicle. Typically, the SMES has a higher power density and lower energy density than other energy storage devices, while battery has higher energy density. Thus, the overall HESS performance can be increased in power and energy density by combining SMES and batteries. The proposed HESS is designed based on bidirectional Z‐source inverter (ZSI). Compared to other SMES/battery‐based HESS topologies that are two stage designs (including DC/DC and AC/DC converters), in this topology, SMES and battery can be incorporated into the Z‐source network which results in lower cost and improved HESS performance. Furthermore, the battery converter has been eliminated due to the buck/boost feature of the ZSI. The fuzzy control method and filters are used to distribute power between the SMES and battery. This study also describes the proposed HESS performance principles and its operation in different modes. [ABSTRACT FROM AUTHOR]

A battery pack is the main energy storage element, and directly affects the performance of an electric vehicle. Battery thermal management system research and its development for a modern electric vehicle is required. This paper selects the forced air cooling of battery pack as the research object, and uses simulation methods to research the heat dissipation performance with different structures of battery packs. The results indicate that according to the four types of transient state conditions, the rising temperature of both battery packs are significantly higher than the temperature difference, the maximum temperature rise and temperature difference of a horizontal battery pack are lower than a longitudinal battery pack. When an electric vehicle begins to decrease speed, the curves of temperature rising and temperature difference increase. This shows the internal heat is continuously rising, so even in a electric vehicle beginning to decrease speed, the fan must work. The reference basis for choosing battery pack type and an analysis of heat flow field characteristics, including fan run-time control, are offered. [ABSTRACT FROM AUTHOR]

There is not much research carried out on factors such as temperature differences in different regions of battery pack, which is highly important and poses a great challenge. Temperature changes across batteries affect the battery pack performance and its life span largely. Thus, the present work proposes the Integrated Finite Element‐Meta‐Optimization Framework for solving this problem. The integrated framework includes the formulation of Finite Element Model of a battery pack and Meta‐Optimization Framework for multi‐objective minimization of three objectives such as the inter‐cell temperature differences, temperature standard deviation and the total volume of the cell. In this framework, firstly Support Vector Regression (SVR) model is formulated based on the data and the SVR parameters are optimized using a genetic algorithm. It can conclude that the resulting model has a coefficient of correlation metric of 99%. The simulated annealing algorithm is then applied to find the optimal values of inter‐cell and cell‐enclosure distances for minimization of inter‐cell temperature differences and the total volume of the cell. Optimization analysis concluded that the volume of the battery pack was decreased by 29%, temperature difference (K) by 42% and SD of the temperature over the entire pack decreased by 55%. [ABSTRACT FROM AUTHOR]