Simulation of adaptive voltage compensation charging model for lithium iron phosphate battery

Yingpeng Xiong; Yi Deng; Chongkai Liu

doi:10.1117/12.3007078

25 October 2023 Simulation of adaptive voltage compensation charging model for lithium iron phosphate battery

Yingpeng Xiong, Yi Deng, Chongkai Liu

Proceedings Volume 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023); 128015B (2023) https://doi.org/10.1117/12.3007078
Event: Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 2023, Dalian, China

Abstract

In order to reflect the real situation of lithium battery charging model under high rate charging current. Based on the study of charging data of lithium iron phosphate battery and Shepherd's empirical model, an adaptive voltage compensation charging model is proposed in this paper. The model combines the adaptive algorithm and the voltage compensation algorithm to compensate the initial voltage of Shepherd's empirical model, making the simulation data of the battery charging model more close to the real data. The results show that, compared with those before voltage compensation, when the charging current is 1 C, the absolute error of battery charging capacity is reduced by 0.01 Ah, and the relative error is reduced by 0.055%. When the charging current is 2 C, the absolute error of battery charging capacity is reduced by 0.81 Ah, and the relative error is reduced by 5.88%. When the charging current is 3 C, the absolute error of battery charging capacity is reduced by 8.88 Ah, and the relative error is reduced by 807.3%.

Citation Download Citation

Yingpeng Xiong, Yi Deng, and Chongkai Liu "Simulation of adaptive voltage compensation charging model for lithium iron phosphate battery", Proc. SPIE 12801, Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023), 128015B (25 October 2023); https://doi.org/10.1117/12.3007078

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KEYWORDS

Batteries

Data modeling

Lithium

Iron

Phosphates

Detection and tracking algorithms

Reflection

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