Integrated Optimal Fast Charging and Active Thermal Management of Lithium-Ion Batteries in Extreme Ambient Temperatures

This article presents an integrated control strategy for optimal fast charging and active thermal management of lithium-ion batteries (LiBs) in extreme ambient temperatures, striking a balance between charging speed and battery health. A control-oriented thermal-nonlinear double-capacitor (NDC) battery model is proposed to describe the electrical and thermal dynamics, incorporating the effects of both an active thermal source and ambient temperature. A state-feedback model predictive control (MPC) algorithm is then developed for optimal fast charging and active thermal management. Numerical experiments validate the algorithm under extreme temperatures, showing that the proposed algorithm can energy-efficiently adjust the battery temperature, thereby balancing charging speed and battery health. In addition, an output-feedback MPC algorithm with an extended Kalman filter (EKF) is proposed for battery charging when states are partially measurable. Numerical experiments validate the effectiveness under extreme temperatures.