基于物理的电池SOC评估方法:最新进展和未来展望

IF 14 1区 化学 Q1 CHEMISTRY, APPLIED
Longxing Wu , Zhiqiang Lyu , Zebo Huang , Chao Zhang , Changyin Wei
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引用次数: 2

摘要

电池荷电状态(SOC)的可靠预测是先进电池管理系统(BMS)的重要功能之一,对电动汽车的安全运行具有重要意义。到目前为止,各种文献已经对基于经验模型和数据驱动的锂离子电池荷电状态估计方法进行了全面的讨论和综述。然而,电化学机制对有机荷电性的影响是目前国内外研究的热点。电化学机制是有机荷电性的物理解释,是高级BMS最有吸引力的候选机制。为此,本文全面综述了基于物理的SOC算法在高级BMS中的应用。首先,深入讨论了锂离子电池物理荷电状态评估方法的研究进展,并详细阐述了相应的评估标准。其次,展望了当前基于物理的电池荷电状态估计研究的未来前景。本文提出的见解有望促进基于物理的高级BMS算法的发展和应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Physics-based battery SOC estimation methods: Recent advances and future perspectives

Physics-based battery SOC estimation methods: Recent advances and future perspectives

The reliable prediction of state of charge (SOC) is one of the vital functions of advanced battery management system (BMS), which has great significance towards safe operation of electric vehicles. By far, the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures. However, few reviews involving SOC estimation focused on electrochemical mechanism, which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS. For this reason, this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS. First, the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated. Second, future perspectives of the current researches on physics-based battery SOC estimation are presented. The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.

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CiteScore
23.60
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