Battery management for plug-in electric vehicles (PEVs) has attracted extensive research attention, with most existing studies focusing on PEV operating conditions. However, battery maintenance during idling remains largely unexplored, under which electrochemical side reactions can cause battery degradation. The degradation rate depends on battery states, e.g., state of charge (SOC) and temperature. Considering that PEV idling accounts for the majority of the time, the accumulated degradation could have a major impact on battery and vehicle lifetime. In this article, battery maintenance during extended idling periods is investigated by utilizing a commonly available infrastructure, i.e., the charging unit. An optimal charging profile is designed to maintain the battery states under desirable conditions to minimize degradation over the idling period while still satisfying the charging energy requirement. Optimal charging profiles are obtained under different ambient temperatures and stages of battery life, showing different features due to respective dominating degradation mechanisms. Compared with the optimal charging profile, constant-current (CC) charging could result in up to 51.6% higher capacity loss, and that of (fast) CC-constant-voltage charging could be up to 12.3 times higher under circumstances over a 12-h overnight idling period. Integration/accommodation of user and grid demand is also addressed by augmenting the optimization framework.

中文翻译：

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优化电动汽车充电用于电池维护和退化管理

插电式电动汽车 (PEV) 的电池管理引起了广泛的研究关注，现有的大多数研究都集中在 PEV 运行条件上。然而，闲置期间的电池维护在很大程度上仍未得到探索，在这种情况下，电化学副反应会导致电池退化。退化率取决于电池状态，例如荷电状态（SOC）和温度。考虑到 PEV 怠速占大部分时间，累积的退化可能对电池和车辆寿命产生重大影响。在本文中，通过使用常用的基础设施（即充电单元）来研究长时间闲置期间的电池维护。最佳充电曲线旨在将电池状态保持在理想条件下，以最大限度地减少闲置期间的退化，同时仍满足充电能量要求。最佳充电曲线是在不同环境温度和电池寿命阶段下获得的，由于各自的主要退化机制而表现出不同的特征。与最佳充电曲线相比，恒流 (CC) 充电可导致高达 51.6% 的容量损失，而（快速）CC 恒压充电在 12-12 倍的情况下可高达 12.3 倍。 h 过夜空转期。用户和电网需求的集成/适应也通过增强优化框架来解决。最佳充电曲线是在不同环境温度和电池寿命阶段下获得的，由于各自的主要退化机制而表现出不同的特征。与最佳充电曲线相比，恒流 (CC) 充电可导致高达 51.6% 的容量损失，而（快速）CC 恒压充电在 12-12 倍的情况下可高达 12.3 倍。 h 过夜空转期。用户和电网需求的集成/适应也通过增强优化框架来解决。最佳充电曲线是在不同环境温度和电池寿命阶段下获得的，由于各自的主要退化机制而表现出不同的特征。与最佳充电曲线相比，恒流 (CC) 充电可导致高达 51.6% 的容量损失，而（快速）CC 恒压充电在 12-12 倍的情况下可高达 12.3 倍。 h 过夜空转期。用户和电网需求的集成/适应也通过增强优化框架来解决。在 12 小时的夜间空转期间，（快速）CC 恒压充电的充电效率最高可达 12.3 倍。用户和电网需求的集成/适应也通过增强优化框架来解决。在 12 小时的夜间空转期间，（快速）CC 恒压充电的充电效率最高可达 12.3 倍。用户和电网需求的集成/适应也通过增强优化框架来解决。