Lithium-ion battery expansion mechanism and Gaussian process regression based state of charge estimation with expansion characteristics

Lithium-ion battery (LIB) thickness variation due to its expansion behaviors during cycling significantly affects battery performance, lifespan, and safety. This study establishes a three-dimensional electrochemical-thermal-mechanical coupling model to investigate the impacts of thermal expansion and particle intercalation on LIB thickness variation, respectively. Results indicate that thickness variation induced by particle intercalation predominantly determines LIB expansion behavior, contributing to 92 % of the observed thickness variation. Moreover, the expansion behavior of LIBs across the entire state of charge (SOC) ranges can be categorized into four stages based on the expansion rate, with turning points closely correlating with the positions of peaks in the Incremental Capacity (IC) curve. This phenomenon underscores the nuanced relationship between LIB thickness variation characteristics and SOC. Consequently, this study proposes a novel SOC estimation approach based on Gaussian regression processes utilizing expansion behavior and voltage characteristics. The experimental results indicate that the maximum error does not exceed 0.0076, and the root mean square error (RMSE) remains within 0.0018 for the constant charging/discharging conditions under different current rates. This research provides guidance for expansion mechanism investigation and SOC estimation optimization.