Lithium-ion battery health estimation with real-world data for electric vehicles

Jiaqiang Tian, Xinghua Liu, Siqi Li, Zhongbao Wei, Xu Zhang, Gaoxi Xiao and Peng Wang

Energy, 2023, vol. 270, issue C

Abstract: Complex environments and variable working conditions lead to irreversible attenuation of battery pack capacity in electric vehicles (EVs). Online capacity estimation is of great significance for battery pack management and maintenance. This work proposes a state-of-health (SOH) attenuation model considering driving mileage and seasonal temperature for battery health estimation. Firstly, a variable forgetting factor recursive least square (VFFRLS) algorithm is proposed for battery model parameter identification. It adaptively adjusts the forgetting factor according to current fluctuations. Then, an extended Kalman-particle filter (EPF) algorithm is proposed for online capacity estimation. In addition, a battery pack SOH attenuation model is constructed considering seasonal temperature and driving mileage. Finally, the performance of the proposed model and algorithm is verified with nine months of actual vehicle data. The experimental results show that the proposed parameter identification and capacity estimation algorithm can accurately estimate the model parameters and capacity. The average capacity of the battery module decreases with the total mileage. The compensation of monthly driving mileage and ambient temperature factors effectively improves the accuracy of SOH model.

Keywords: Electric vehicles; Battery pack; Variable forgetting factor recursive least square; State-of-health; SOH attenuation model (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:270:y:2023:i:c:s0360544223002499

DOI: 10.1016/j.energy.2023.126855

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