Extraction of battery parameters of the equivalent circuit model using a multi-objective genetic algorithm

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...

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Bibliographic Details
Published in:Journal of power sources 2014-02, Vol.247, p.729-737
Main Authors: BRAND, Jonathan, ZHEMING ZHANG, AGARWAL, Ramesh K
Format: Article
Language:English
Subjects:
Applied sciences
Direct energy conversion and energy accumulation
Electric batteries
Electric potential
Electrical engineering. Electrical power engineering
Electrical power engineering
Electrochemical conversion: primary and secondary batteries, fuel cells
Equivalent circuits
Exact sciences and technology
Genetic algorithms
Mathematical models
Optimization
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Summary: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.
ISSN:0378-7753
1873-2755
DOI:10.1016/j.jpowsour.2013.09.011