基于电-热-老化耦合模型的自适应多段恒流充电研究

基于一阶RC等效电路模型、热网络法以及老化模型建立了锂离子电池的电-热-老化耦合的多状态联合估计模型，采用粒子群优化算法建立阶数自适应的多段恒流充电策略.通过构建充电时间-电池寿命的帕累托边界曲线，得到了电池最短充电时间(β=1)、最小老化(β=0)及平衡(β=0.02)充电三种充电策略，并与CC-CV充电策略进行了对比.结果表明，最短时间充电与2C CC-CV具有很高的一致性.最小老化充电与0.1C CC-CV充电的老化损失都很小，但前者缩短了61.7%的充电时间.平衡充电策略相比于最小老化策略，仅牺牲0.06%SOH，缩短71.19%的充电时间.相比于0.5C CC-CV充电策略，平衡充电策略的充电时间减少了44.9%.

Study on Self-Adaptive Multistage Constant Current Charging Based on Electro-Thermal-Aging Coupling Model

An electro-thermal-aging coupling multi-state joint-estimation model of lithium-ion batteries was built based on the first-order RC equivalent circuit model， the thermal network method and the aging model. Particle swarm optimization(PSO) algorithm was adopted to establish a self-adaptive multistage constant current(SMCC)charging strategy whose stages were adaptive to the objective function. By constructing the Pareto frontier of charging time and battery life， three charging strategies， including the minimum-time charge， the minimum-aging charge and the balanced charge， were obtained. Then they were compared with the CC-CV charges. The results show that the minimum-time charge is highly consistent with the 2C CC-CV. The aging losses of the minimum-aging charge and the 0.1C CC-CV are very small， but the former reduces charging time by 61.7%. Compared with the minimum-aging charge， the charging time of the balanced charge is reduced by 71.19% at the expense of 0.06%SOH. Compared with the 0.5C CC-CV charge， the charging time of the balanced charge is reduced by 44.9%.