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Fast charging optimization for lithium-ion batteries based on dynamic programming algorithm and electrochemical-thermal-capacity fade coupled model

机译:基于动态规划算法和电化学-热容量衰减耦合模型的锂离子电池快速充电优化

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摘要

Enabling fast charging of lithium-ion batteries may accelerate the commercial application of electric vehicles (EVs). The fast charging, however, could lead to capacity fade, lithium plating, and thermal runaway. This paper develops an optimal multi-stage charging protocol for lithium-ion batteries to minimize capacity fade due to the solid-electrolyte interphase (SEI) increase, to maximize the SEI potential to decrease the lithium plating, and to reduce the temperature rise to avoid a thermal runaway situation. An electrochemical-thermal-capacity fade coupled model is developed to monitor the battery internal state. The dynamic programming (DP) optimization algorithm is employed to search for the suboptimal charging current profiles. The optimization results illustrate that the optimized charging current profile varies with the state of charge (SOC) and the cycle number. As compared to the constant current charging protocol, each optimized charging strategy can reduce the capacity fade ratio by 4.6%, increase the SEI potential by 57%, and reduce the temperature rise by 16.3% for over 3300 charging-discharging cycles, respectively.
机译:实现锂离子电池的快速充电可以加速电动汽车(EV)的商业应用。但是,快速充电可能会导致容量衰减,锂电镀和热失控。本文针对锂离子电池开发了一种最佳的多阶段充电协议,以最大程度地减少由于固体电解质中间相(SEI)的增加而引起的容量衰减,最大程度地提高SEI电位以减少锂镀层,并减少温升以避免热失控的情况。建立了电化学-热容量衰减耦合模型来监控电池内部状态。动态编程(DP)优化算法用于搜索次优充电电流曲线。优化结果表明,优化的充电电流曲线随充电状态(SOC)和循环次数而变化。与恒定电流充电协议相比,每种优化的充电策略分别可以在3300多个充电-放电循环中将容量衰减率降低4.6%,将SEI电位提高57%,并将温度升高降低16.3%。

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