Nonlinear Model Predictive Control Design for Active Cell Balancing and Thermal Management

Active cell balancing and thermal management are essential for optimizing the performance and extending the lifespan of a battery pack. The battery pack consists of two adjacent LiFePO
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cells connected in series with a bidirectional buck-boost converter. The cell model integrates the electrical and thermal dynamics to form a coupled electro-thermal model. A high-fidelity model is employed to calculate the mean balancing currents and the power losses of an active cell balancing network (ACBN). A nonlinear model predictive controller (NMPC) is designed to minimize SoC imbalances, thermal deviations, and power losses within the ACBN. The CasADi toolbox and the interior point optimizer (Ipopt) algorithm are used to solve the control scheme. The NMPC maintains the SoC difference within a 2% threshold despite the modeling uncertainties and a generic current profile. The inclusion of thermal constraints within the NMPC’s cost function ensures that cell temperatures remain within safe operational limits, thereby accommodating temperature variation among cells. The simulations demonstrate the critical role of incorporating thermal dynamics into the NMPC formulation, highlighting the trade-offs between balancing speed, power losses, and thermal management.