In this part of the paper, a control strategy for optimal charging is discussed. This work seeks to develop a capacity fade minimizing model predictive control (MPC) framework, which can help in identification and realization of optimum charge-discharge cycles in Lithium-ion (Li-ion) batteries. Although the model developed in the first part is a good representation for a battery, it has limitations for on-line applications due to its complexity. For on-line applications, it is important that the model is computationally fast, but at the same time incorporate the effects of various capacity fade mechanisms. Development of a simple lumped model to meet these requirements is also a part of this work.

在本文的这一部分中，讨论了最佳充电的控制策略。这项工作旨在开发一种容量衰减最小化模型预测控制（MPC）框架，该框架可帮助识别和实现锂离子（Li-ion）电池的最佳充放电循环。尽管在第一部分中开发的模型可以很好地表示电池，但是由于其复杂性，它在在线应用方面存在局限性。对于在线应用，重要的是模型的计算速度要快，但同时要考虑各种容量衰减机制的影响。满足这些要求的简单集总模型的开发也是这项工作的一部分。