基于SOC自适应分阶的动力锂电池两步优化快速充电策略

快速高效的充电方式对于推动汽车电动化,加快以石油为主导的传统交通能源向绿色低碳能源转型,实现中国"双碳战略"的目标具有重要意义。针对充电时间和充电损失的平衡优化问题,提出了一种基于SOC自适应分阶的两步优化多阶恒流充电策略。为实现充电过程的优化分阶,利用改进的二分K-means算法对基于内阻曲线的采样点集进行聚类,实现了充电区间关于内阻变化和分布特征的自适应划分。基于分阶优化结果,采用改进的非支配排序哈里斯鹰优化算法(INSHHO)求解优化电流对应帕累托前沿。利用Logistic混沌初始化及自适应t分布突变算子对哈里斯鹰模型(HHO)进行改进,进一步提升算法的全局寻优能力。最后通过充电对比试验,将优化多阶恒流充电策略与恒流恒压策略(CC-CV)和均分多阶恒流充电策略在不同充电时间条件下进行充电性能对比。结果表明:在充电时间保持一致的条件下,提出的优化多阶恒流充电策略较恒流恒压策略和均分多阶恒流充电策略的充电欧姆损失最大分别减少1.03%和0.3%;在温升表现上,优化多阶恒流充电策略较均分多阶恒流充电策略的充电温升最多降低了0.82℃。

A Two-step Optimization of Fast Charging Strategy for Lithium-ion Battery Based on Adaptive SOC Segmentation

The fast and efficient charging method is important for promoting the electrification of automobiles,the transformation of petroleum-dominated transportation energy to green low-carbon energy,and the realization of 'carbon peaking and carbon neutrality'.Aimed at the balance optimization problem of charging time and charging loss,this study proposed a two-step optimization multistage constant current charging strategy based on SOC adaptive segmentation.To realize the optimal division of the charging process,the improved bisecting K-means algorithm was used to cluster the sampling point set based on the internal resistance curve to realize adaptive segmentation according to the change and distribution of the internal resistance.Based on the result of the segmentation optimization,the improved non-dominated sorting Harris hawks optimization algorithm (INSHHO) was used to solve the Pareto frontier corresponding to the optimized current.The Harris hawks optimization (HHO) model was improved by using Logistic chaotic mapping initialization and adaptive t-distribution mutation operator to further improve the global optimization capability of the algorithm.Finally,the charging performances under different charging time conditions of the optimized multistage constant current,constant current-constant voltage (CC-CV) and evenly divided multistage constant current charging strategies were compared by experiments.Compared with the CC-CV strategy and evenly divided multistage constant current strategy,under the condition of the same charging time,the proposed optimized multistage constant current charging strategy reduces the charging ohmic loss by 1.03% and 0.3%,respectively.In terms of the temperature rise performances,the optimized multistage constant current charging strategy reduces the maximum temperature rise by 0.82℃ compared with the evenly divided multistage constant current charging strategy.