Xincheng Han1, Hongyan Ma1,2,3,*, Shuo Meng1, Chengzhi Ren1
Energy Engineering, DOI:10.32604/ee.2025.072906
Abstract Lithium-ion (Li-ion) batteries stand as the dominant energy storage solution, despite their widespread adoption, precisely determining the state of charge (SOC) continues to pose significant difficulties, with direct implications for battery safety, operational reliability, and overall performance. Current SOC estimation techniques often demonstrate limited accuracy, particularly when confronted with complex operational scenarios and wide temperature variations, where their generalization capacity and dynamic adaptation prove insufficient. To address these shortcomings, this work presents a PSO-TCN-Transformer network model for SOC estimation. This research uses the Particle Swarm Optimization (PSO) method to automatically configure the architectural parameters of… More >