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SOC estimation for LiFePO4 battery in EVs using recursive least-squares with multiple adaptive forgetting factors

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conference contribution
posted on 2024-11-14, 10:13 authored by Van Huan Duong, Hany Bastawrous, Kai Chin LimKai Chin Lim, Khay Wai SeeKhay Wai See, Peng Zhang, Shi DouShi Dou
This work presents a novel technique which is simple yet effective in estimating electric model parameters and state-of-charge (SOC) of the LiFePO4 battery. Unlike the well-known recursive least-squares-based algorithms with single constant forgetting factor, this technique employs multiple adaptive forgetting factors to provide the capability to capture the different dynamics of model parameters. The validity of the proposed method is verified through experiments using actual driving cycles.

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Citation

Duong, V. H., Bastawrous, H. A., Lim, K. C., See, K. W., Zhang, P. & Dou, S. X. (2014). SOC estimation for LiFePO4 battery in EVs using recursive least-squares with multiple adaptive forgetting factors. Connected Vehicles and Expo (ICCVE), 2014 International Conference on (pp. 520-521). United States: Institute of Electrical and Electronics Engineers.

Parent title

2014 International Conference on Connected Vehicles and Expo, ICCVE 2014 - Proceedings

Pagination

520-521

Language

English

RIS ID

105835

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