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