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Nonlinear model predictive control for cell balancing in Li-ion battery packs

机译:锂离子电池组电池平衡的非线性模型预测控制

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A major issue with Li-ion batteries hindering their widespread application in transportation industry is safety related concerns that should be effectively addressed within the battery management system design. Over-charge/discharge of the cells within a battery pack is one undesirable outcome that can affect the battery's health. Differences between the cells within a battery pack can lead to cell over-charge/discharge that is not detectable from battery pack's voltage. Thus, a cell balancing circuit is usually employed in battery packs in order to keep all the cells in balance. The control of cell-balancing circuits is mostly addressed by logical-based algorithms where the dynamical model of the system is not taken into account. This work considers the control problem of a cell-balancing circuit in a model-based framework by proposing a nonlinear model predictive control (NMPC). The NMPC problem is solved using a genetic algorithm and simulation studies show the effectiveness of the proposed algorithm.
机译:阻碍锂离子电池在运输行业中广泛应用的主要问题是与安全相关的问题,应在电池管理系统设计中有效解决这些问题。电池组中的电池单元过度充电/放电是一种不希望的结果,可能会影响电池的健康。电池组中电池之间的差异会导致电池过充/放电,这无法从电池组的电压中检测到。因此,通常在电池组中采用电池平衡电路,以保持所有电池平衡。电池平衡电路的控制主要由基于逻辑的算法解决,其中不考虑系统的动力学模型。这项工作通过提出非线性模型预测控制(NMPC),在基于模型的框架中考虑了单元平衡电路的控制问题。使用遗传算法解决了NMPC问题,仿真研究表明了该算法的有效性。

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