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首页> 外文期刊>IEEE transactions on industrial informatics >Optimal Charging Control for Lithium-Ion Battery Packs: A Distributed Average Tracking Approach
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Optimal Charging Control for Lithium-Ion Battery Packs: A Distributed Average Tracking Approach

机译:锂离子电池组最佳充电控制:分布式平均跟踪方法

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摘要

Effective lithium-ion battery pack charging is of extreme importance for accelerating electric vehicle development. This article derives an optimal charging control strategy with a leader-followers framework for battery packs. Specifically, an optimal average state-of-charge (SOC) trajectory based on cells' nominal model is first generated through a multiobjective optimization with consideration of both user demand and battery pack's energy loss. Then, a distributed charging strategy is proposed to make the cells' SOCs follow the prescheduled trajectory, which can effectively suppress the violation of the safety-related charging constraints through online battery model bias compensation. This article highlights the superiorities of the proposed leader-followers-based charging framework that combines the offline scheduling and online closed-loop regulation for battery pack charging, which brings benefits to significantly reduce the computational burden for the charger controller as well as improve the robustness to suppress the negative impact caused by the cell's model bias. Extensive illustrative results demonstrate the effectiveness of the proposed optimal charging control strategy.
机译:有效的锂离子电池组充电对于加速电动汽车开发来说是极端重要的。本文源于具有电池组的领导者追随者框架的最佳充电控制策略。具体地,首先通过考虑用户需求和电池组的能量损失,首先通过多目标优化来产生基于细胞标称模型的最佳平均电荷状态(SOC)轨迹。然后,提出了一种分布式充电策略来使细胞的SOC遵循预定的轨迹,这可以通过在线电池模型偏置补偿有效地抑制与安全相关的充电约束的违反。本文突出了拟议的领导者 - 追随者的计费框架的优势,这些充电框架结合了电池组充电的离线调度和在线闭环调节,这为充电器控制器的计算负担显着降低了益处,提高了鲁棒性抑制由细胞模型偏置引起的负面影响。广泛的说明性结果证明了所提出的最佳充电控制策略的有效性。

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