动力电池环境适应性,尤其是低温性能受限严重制约新能源汽车在高寒地区的安全、耐久、高效和长里程运行。为解决动力电池低温预热难题,提出一种基于短时大电流自放电的电触发极速自加热方法,以18650类锂离子动力电池为研究对象,分析加热过程中的动力电池产热及温升特性,进而设计基于动力电池温度预测的极速加热控制策略;结合COMSOL仿真系统模拟动力电池加热效果,进而开发带有极速加热样机的测试平台,测试结果表明,该方法可以实现快达0.65℃/s的瞬时加热速率,在87 s内将动力电池从环境温度-20℃加热到20℃,目标温度的控制误差仅0.4%,且该加热方法对动力电池寿命的影响很小,对动力电池模组加热时温升标准差小于2.7℃。最后对该加热方法的应用前景、所需进一步解决的科学问题及研究路线进行探讨。

锂离子动力电池在低温环境下性能急剧衰退,制约了电动汽车在全气候范围内的推广应用.针对电触发极速加热系统:首先进行电热特性建模方法研究,开展电特性表征,建立考虑材料各向异性的电池产热及热扩散有限元模型,试验验证表明电流误差低于98.2 mA,温升误差小于4.09％;仿真研究不同占空比、电池初始SOC情况的加热特性,进而对电池组在加热过程中的加热行为一致性进行研究,结果表明可在270 s内从-20℃加热到20℃,最大温差低于3.94℃;分析电池单体不一致性与加热系统控制参数对加热行为一致性的影响特性,结果表明电池组温升不一致性与单体电池内阻标准差呈正线性相关,且受控制频率与占空比影响显著,其中占空比对温升影响幅度高达15％.

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency of the vehicle since the engine has to participate more. Therefore, the energy management strategy is required to be adjusted during the entire lifespan of lithium-ion batteries to maintain the optimality of energy economy. In this study, tests of the battery performances under thirteen different aging stages are involved and a parameters-varying battery model that represents the battery degradation is established. The influences of battery aging on energy consumption of a given plug-in hybrid electric vehicle (PHEV) are analyzed quantitatively. The results indicate that the variations of capacity and internal resistance are the main factors while the polarization and open circuit voltage (OCV) have a minor effect on the energy consumption. Based on the above efforts, the optimal energy management strategy is proposed for optimizing the energy efficiency concerning both the fresh and aging batteries in PHEV. The presented strategy is evaluated by a simulation study with different driving cycles, illustrating that it can balance out some of the harmful effects that battery aging can have on energy efficiency. The energy consumption is reduced by up to 2.24% compared with that under the optimal strategy without considering the battery aging.