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首页> 外文期刊>IEEE Transactions on Energy Conversion >Mathematical Modeling of Li-Ion Battery Using Genetic Algorithm Approach for V2G Applications
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Mathematical Modeling of Li-Ion Battery Using Genetic Algorithm Approach for V2G Applications

机译：V2G应用中基于遗传算法的锂离子电池数学建模

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摘要

This paper presents an electric circuit-based battery and a capacity fade model suitable for electric vehicles (EVs) in vehicle-to-grid applications. The circuit parameters of the battery model (BM) are extracted using genetic algorithm-based optimization method. A control algorithm has been developed for the battery, which calculates the processed energy, charge or discharge rate, and state of charge limits of the battery in order to satisfy the future requirements of EVs. A complete capacity fade analysis has been carried out to quantify the capacity loss with respect to processed energy and cycling. The BM is tested by simulation and its characteristics such as charge and discharge voltage, available and stored energy, battery power, and its capacity loss are extracted. The propriety of the proposed model is validated by superimposing the results with four typical manufacturers’ data. The battery profiles of different manufacturers’ like EIG, Sony, Panasonic, and Sanyo have been taken and their characteristics are compared with proposed models. The obtained battery characteristics are in close agreement with the measured (manufacturers’ catalogue) characteristics.
机译：本文提出了一种基于电路的电池和容量衰减模型，该模型适用于车辆到电网应用中的电动汽车（EV）。使用基于遗传算法的优化方法提取电池模型（BM）的电路参数。已经为电池开发了一种控制算法，该算法可以计算处理后的能量，充电或放电速率以及电池的充电状态限制，以满足电动汽车的未来需求。已经进行了完整的容量衰减分析，以量化与处理后的能量和循环有关的容量损失。通过仿真测试BM，并提取其特性，例如充电和放电电压，可用和存储的能量，电池电量以及其容量损耗。通过将结果与四个典型制造商的数据相叠加，可以验证所提出模型的适当性。已获取了EIG，索尼，松下和三洋等不同制造商的电池配置文件，并将其特性与建议的型号进行了比较。获得的电池特性与测得的（制造商的产品目录）特性非常一致。

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