Core Temperature-Aware Optimal Preheating Strategy for Lithium-ion Battery

Lithium-ion batteries are the crucial energy source for electric vehicles. However, they experience capacity degeneration when used in low-temperature environments. It is necessary to preheat them before using. In this paper, a core temperature-aware optimal preheating strategy, featuring a multi-stage constant-current discharge heating method, is proposed to heat lithium-ion batteries in low-temperature environments. Firstly, this paper builds an internal battery temperature distribution model based on Fourier’s law of heat conduction. Secondly, the temperature distribution model is coupled within the battery model to display the comprehensive performance of the battery. Thirdly, decreasing heating time and reducing capacity loss jointly formulate a multi-objective optimization problem solved by dynamic programming(DP) algorithm. Judging by simulation results, heating time is downsized and the capacity loss is reduced at the same time, proving the progressiveness of the proposed strategy.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/hpcc64274.2024.00224
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Core Temperature-Aware Optimal Preheating Strategy for Lithium-ion Battery

Kaifu Guan, Yongjie Liu, Zhiwu Huang, Lisen Yan et al.
Advanced Battery Technologies Research
article

Core Temperature-Aware Optimal Preheating Strategy for Lithium-ion Battery

Kaifu Guan, Yongjie Liu, Zhiwu Huang, Lisen Yan, Xi Yan, Fei Li
article en

Abstract

Lithium-ion batteries are the crucial energy source for electric vehicles. However, they experience capacity degeneration when used in low-temperature environments. It is necessary to preheat them before using. In this paper, a core temperature-aware optimal preheating strategy, featuring a multi-stage constant-current discharge heating method, is proposed to heat lithium-ion batteries in low-temperature environments. Firstly, this paper builds an internal battery temperature distribution model based on Fourier’s law of heat conduction. Secondly, the temperature distribution model is coupled within the battery model to display the comprehensive performance of the battery. Thirdly, decreasing heating time and reducing capacity loss jointly formulate a multi-objective optimization problem solved by dynamic programming(DP) algorithm. Judging by simulation results, heating time is downsized and the capacity loss is reduced at the same time, proving the progressiveness of the proposed strategy.

Central South University (CN)
Natural Science Foundation of Hunan Province
Openalex Percentile: Top 67%
Advanced Battery Technologies Research
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