A Multi-objective Optimized Self-heating Strategy for All-Climate Batteries at Low Temperatures

Efficient and uniform battery preheating is vitally important to improve the poor performance and safety hazards of lithium-ion batteries (LIB) at low temperatures. All-climate battery (ACB) is a novel battery structure that enables rapid self-heating of LIB without requiring additional power sources, but it also leads to an extremely non-uniform distribution of internal temperature and thus capacity degradation. In this study, a variable duty cycle control strategy for heating of ACBs at low temperatures is proposed to make an optimal trade-off among heating time, capacity consumption and temperature gradient during heating based on a nondominated sorting-based multi-objective evolutionary algorithm, called nondominated sorting genetic algorithm II (NSGA-II). Results show that this heating strategy can heat LIB from −20 ℃ to 25 ℃ within 424.93 s and with small temperature gradient. Under the same maximum temperature gradient limit, the proposed method shortens the heating time by 14.20% compared with the traditional constant duty cycle heating strategy, and by 8.65% compared with the constant duty cycle optimal heating control strategy optimized by the NSGA-II algorithm.