Temperature characterization based state-of-charge estimation for pouch lithium-ion battery

Pouch lithium-ion batteries have aroused widespread attention in the field of electric vehicles because of the high energy density and low internal resistance. The available capacity of the battery varies greatly under different temperatures, resulting significant error in state-of-charge (SOC) estimation. An effective approach to relieve this issue is to make full use of the battery surface temperature. This article presents an enhanced Coulomb counting method based on surface temperature characterization to improve SOC estimation accuracy. Theoretical analysis and visualization tests using infrared thermal imager are conducted to identify surface temperature features during battery operation. The feature regions of the pouch lithium-ion battery are initially determined by temperature distribution function and further screened by dynamic time warping (DTW) algorithm. Finally, the screened temperature features are applied to battery available capacity modeling. The experimental results prove that the proposed method can effectively improve the SOC estimation accuracy under various temperature conditions.