A numerical and statistical implementation of a thermal model for a lithium-ion battery

Abstract

Lithium-ion batteries are substantial technologies to improve energy storage. If a detailed understanding of thermal behavior for a range of operating conditions is achieved, lithium-ion batteries can be used more effectively in various applications. This study focuses on the effect of ambient temperature, discharge rate, depth-of-discharge, and convective heat transfer coefficient on the maximum battery temperature and maximum battery temperature difference of a commercially available LiMn2O4 prismatic battery. The statistical evaluation showed that the ambient temperature with the delta value of 0.55 was the most influential discharge parameter while the effect of the depth-of-discharge on the maximum battery temperature can be neglected. The maximum battery temperature difference is dominated by the C-rate with the delta value of 15.5399 and the convective heat transfer coefficient with the delta value of 4.2624. More attention is paid to both the C-rate and the convective heat transfer coefficient to simultaneously control and improve the maximum battery temperature and maximum battery temperature difference due to they fulfilled the requirement for a significance level of 95%. The statistical results provide unique insights into the difficult-to-determine effect of the discharge parameters that are closely monitored and controlled to improve the battery thermal management systems.