An optimized internal heating strategy based on bidirectional pulsed current for lithium-ion battery at low temperature

The low-temperature characteristics of lithium-ion batteries limit the performance of electric vehicles in cold weather, and the internal heating of lithium-ion batteries is a promising method. Unlike the existing constant-amplitude AC heating method, this paper proposes an optimized two-way pulse battery internal heating method based on a genetic algorithm. First, perform an EIS test on the battery based on the Thevenin model, and use Zview software to fit the test results to obtain impedance spectra at different temperatures and frequencies. Based on the Bernardi formula, describe the heat generated during the heating process of the battery. Then the thermos-electric coupling model of the battery is established to reflect the electric heating characteristics of the battery heating process. Through the analysis of the thermoelectric coupling model, the factors affecting the heating of the battery during the self-heating process are obtained. The heating current is limited according to the battery voltage's upper and lower safety thresholds. The genetic algorithm optimization process takes the current frequency as the solution set and the heat generation as the target. The method can achieve the maximum heat generation rate during the heating process at -20°C to 10°C and reduce battery loss, which greatly increases the battery's cycle life.