Optimization Tool for the Characterization of Electric Vehicle Battery Packs

Peter Wilson, C. Vagg
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Abstract

The use of vehicle scale data for the parameter characterization of electric vehicle battery packs is a challenging topic. This paper describes the implementation of a design tool that carries out both simulated annealing and genetic optimization of model parameters for a modified Nernst Open Circuit Voltage Battery model (K0, K1, K2, K3), concurrently with the dynamic transient model parameters (R0,R1,RP,C1,CP) and pack level parameters including the initial state of charge and capacity (SOCINIT and AH). This paper describes the model for the battery pack implemented in the Saber simulator and the optimization tool (written in TCL-TK) also integrated with the Saber simulator. Results were collected from rolling road tests of of a BMW i8 to validate the fidelity of the model.
电动汽车电池组特性优化工具
利用整车规模数据对电动汽车电池组进行参数表征是一个具有挑战性的课题。本文介绍了一种设计工具的实现,该设计工具对改进的能思特开路电压电池模型(K0, K1, K2, K3)进行模型参数的模拟退火和遗传优化,同时对动态瞬态模型参数(R0,R1,RP,C1,CP)和包括初始充电状态和容量(SOCINIT和AH)在内的电池组水平参数进行优化。本文描述了在Saber模拟器中实现的电池组模型以及与Saber模拟器集成的优化工具(用TCL-TK编写)。为验证该模型的保真度,收集了BMW i8的滚动道路试验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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