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

Highlights: • Effect of discharge parameters on maximum battery temperature is statistically investigated. • Ambient temperature is the most influential discharge parameter on the maximum battery temperature. • C-rate is the main discharge parameter for the maximum temperature gradient. • C-rate and convective heat transfer coefficient play a vital role in the control of T_max and ΔT_max. 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.