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Optimal Health-aware Charging Protocol for Lithium-ion Batteries: A Fast Model Predictive Control Approach

机译:锂离子电池最佳健康意识充电协议:一种快速的模型预测控制方法

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Lithium-ion batteries are widely used in industry to supply different portable applications. Their management is handled by Battery Management Systems (BMSs), which are intended to ensure good performance (such as minimum charging time) while simultaneously minimizing safety risks. The use of accurate mathematical models can help in achieving such goals. The first-principles pseudo-two dimensional (P2D) model is one of the mostly used models for simulation but rarely used in design of BMSs. This model, together with a description of the capacity fade mechanisms occurring during battery operations, is used to design health-aware BMS strategies. A Model Predictive Control (MPC) scheme based on a linearized version of the P2D model is proposed in order to track a reference value of the State of Charge (SOC), while taking into account the aging dynamics of the system as well as temperature and voltage constraints. Simulations show the effectiveness of the approach: the tuning of the control parameters allows controlled operation with different tradeoffs between charging time and battery lifetime enhancement.
机译:锂离子电池在工业中被广泛用于提供各种便携式应用。它们的管理由电池管理系统(BMS)处理,旨在确保良好的性能(例如最短的充电时间),同时最大程度地降低安全风险。使用准确的数学模型可以帮助实现这些目标。第一性原理伪二维(P2D)模型是最常用于仿真的模型之一,但很少用于BMS的设计中。该模型与电池运行期间发生的容量衰减机制的描述一起,用于设计具有健康意识的BMS策略。为了跟踪荷电状态(SOC)的参考值,同时考虑了系统的老化动态以及温度和温度,提出了一种基于P2D模型线性化模型的模型预测控制(MPC)方案。电压限制。仿真显示了该方法的有效性:控制参数的调整允许在充电时间和电池寿命提高之间以不同的权衡取舍进行受控操作。

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