Optimization of Lithium-Ion Battery Charging Strategies From a Thermal Safety Perspective

The charging rate of lithium-ion batteries (LIBs) constitutes an essential metric for quantifying the competency of electric vehicles (EVs) and energy storage systems (ESSs) in restoring power expeditiously. Nevertheless, unrestricted escalation of the charging current may trigger hazardous thermal runaways in battery packs. Hence, this work is concerned with optimizing the battery charging strategy from a thermal safety perspective. Instead of relying on the conventional thermal-coupling equivalent circuit models, a numerical approach based on a thermal-coupling simplified electrochemical model (TC-SEM) is proposed to predict the battery voltage and temperature via recursion. The potential error accumulation in the recursive process is suppressed by a multistep-ahead Kalman filter, which operates in concert with measurable terminal voltage and temperature. Subsequently, the aforementioned prediction algorithm is integrated into a model predictive control (MPC) framework. Central to the MPC framework is a liquid cooling system that seeks to regulate the battery temperature, and thus the efficacy of the prediction algorithm should be, and in fact is, verified in terms of the temperature control ability of an actual cooling system. Experimental result shows that, during the battery charging process, the maximum temperature only overshoots the prescribed temperature by 0.1 °C, whereas the average error is just −0.08 °C, which empirically validates the proposal.