Abstract: As the penetration rate of China's new energy vehicle market rises significantly in 2025, the demand for fast-charging technology surges, yet insufficient charging simulation accuracy becomes a core bottleneck restricting thermal management optimization and charging strategy design. This study proposes a parameter coordination optimization strategy that dynamically calibrates the entropy heat coefficient and the temperature dependence of variable-temperature specific heat capacity based on open-circuit voltage (OCV) parameters, aiming to solve the error accumulation problem in lithium-ion battery fast-charging simulation under high and low temperature environments. Through experimental testing and calculation, the modified model after parameter optimization shows high consistency between its temperature rise variation and the temperature rise in vehicle testing; the simulation error of lithium-ion battery fast-charging duration decreases from 5.32% to 1.95% under high temperature, and from 4.32% to 0.25% under low temperature.

Key words: lithium battery charging performance; parameter coordination; specific heat capacity at a variable temperature; entropy heat

摘要： 随着 2025 年中国新能源汽车市场渗透率大幅提高，快充技术需求激增，充电仿真精度 不足却成为制约热管理优化与充电策略设计的核心瓶颈。该研究提出一种基于开路电压 （OCV）参数动态标定熵热系数与变温比热容温度依赖性的参数协同优化策略，以解决高低 温环境下锂电池快充仿真的误差累积问题。经实验测试与计算，参数优化后的修正模型，其 温升变化与整车测试温升跟随性较高，高温下锂电池快充时长仿真误差从 5.32%降低至 1.95%，低温下则从 4.32%降至 0.25%。

关键词: 锂电池充电性能；参数协同；变温比热容；熵热