Charge unbalancing in series-connected cells can lead to lower storage capacity and shorter battery life. Model-based optimization strategies have proven to be very effective in addressing this problem. In this article, we propose a general nonlinear model predictive control (NMPC) scheme for obtaining a balancing-aware optimal charging. The presented method relies on an electrochemical model, tailored for control purposes. In view of the possibility of practical implementation, the concepts are subsequently specialized for an easily implementable power supply scheme. Finally, the NMPC approach is validated on commercial cells using a detailed battery simulator, with sound evidence of its effectiveness both under the assumption of full state availability and in the presence of an observer scheme.

中文翻译：

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串联锂离子电池的平衡感知充电策略：非线性模型预测控制方法

串联连接的电池中的电荷不平衡会导致较低的存储容量和较短的电池寿命。基于模型的优化策略已被证明在解决该问题方面非常有效。在本文中，我们提出了一种通用的非线性模型预测控制（NMPC）方案，以获得平衡感知的最佳充电。提出的方法依赖于为控制目的而定制的电化学模型。考虑到实际实施的可能性，这些概念随后专门用于易于实施的电源方案。最后，使用详细的电池模拟器在商用电池上对NMPC方法进行了验证，并在充分状态可用性的假设下和存在观察员方案的情况下均具有其有效性的可靠证据。