基于3D模型的电池电化学-热耦合数值模拟与预测分析OA

Energy shortage and environmental pollution have driven the widespread adoption of lithium-ion batteries,however,effective temperature control during charging and discharging needs to be overcome,so it is of great significance to investigate the electrothermal characteristics of lithium-ion batteries.A 3D electrochemical-thermal coupled model of a 150 Ah lithium iron phosphate battery was established using simulation technology to simulate thermal behavior under different charging rates The synergistic effects of multiple electrochemical variables and temperature variables were investigated by the structure vector autoregressive model(SVAR),and an integrated learning regression prediction system was developed to improve the research efficiency.The results indicate that the increase of charging rate will increase the temperature and temperature difference of the battery,and the temperature difference exceeds 5℃when charging at high rate(1.3C,1.5C),the heat generation rate accelerates significantly,with the most pronounced increase in reversible heat.The relationship between battery electrochemistry and heat is complex.At a charging rate of 0.5C,voltage,current density,battery capacity and maximum temperature difference are significantly positively correlated with p<0.001.During 1.0C discharge,the voltage is significantly positively correlated with most of the thermal characteristic variables,with correlation coefficients ranging from-0.973 to 0.949 under different conditions.The integrated learning regression prediction system shows high prediction accuracy and strong generalization and trend analysis capabilities,which can provide support for battery thermal management.