A quick capacity estimation method for Li-ion battery combining equivalent circuit model and Bayesian network

Yifan Wang; Shiyu Liu; Pengfei Kou; Yifan Zhou

doi:10.1117/12.2611023

14 October 2021 A quick capacity estimation method for Li-ion battery combining equivalent circuit model and Bayesian network

Yifan Wang, Shiyu Liu, Pengfei Kou, Yifan Zhou

Author Affiliations +

Proceedings Volume 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation; 119303U (2021) https://doi.org/10.1117/12.2611023
Event: International Conference on Mechanical Engineering, Measurement Control, and Instrumentation (MEMCI 2021), 2021, Guangzhou, China

Abstract

State of health (SOH) estimation for power battery is critical for reliable and safe operation of electric vehicles (EVs). In this paper, we propose a novel SOH estimation method combing equivalent circuit model (ECM) and Bayesian network. Firstly, a Bayesian network for SOH estimation is constructed according to existing knowledge about battery degradation. Then variables in Bayesian network is estimated by applying recursive least square algorithm with forgetting factor on first-order RC ECM. Afterwards, the model is trained to obtain the conditional probability distribution for each variable in Bayesian network. Finally, the effectiveness and accuracy of the model is verified using battery aging data.

Citation Download Citation

Yifan Wang, Shiyu Liu, Pengfei Kou, and Yifan Zhou "A quick capacity estimation method for Li-ion battery combining equivalent circuit model and Bayesian network", Proc. SPIE 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation, 119303U (14 October 2021); https://doi.org/10.1117/12.2611023

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