Extraction of battery parameters for optimal performance using the circuit model with a multi-objective genetic algorithm

Jonathan Brand, Zheming Zhang, Ramesh K. Agarwal

Research output: Contribution to journalConference articlepeer-review

Abstract

A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent-circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials. Several test cases demonstrate that the multi-objective genetic algorithm can serve as a robust and reliable tool for extracting the battery performance parameters.

Original languageEnglish
JournalSAE Technical Papers
Volume2
DOIs
StatePublished - 2013
EventSAE 2013 World Congress and Exhibition - Detroit, MI, United States
Duration: Apr 16 2013Apr 18 2013

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