A Novel Method of SOC Estimation for Electric Vehicle Based on Adaptive Particle Filter

Abstract

Aimed at improving SOC estimation accuracy, speed and robust of battery on electric vehicle, SOC estimation method based on adaptive particle filter is proposed. 1-order RC and lag model, 2-order RC and lag model, 3-order RC and lag model are built. Particle Swarm algorithm is used to search optimal parameters. Considering calculation and model accuracy, 1-order lag model is chosen. Traditional particle filter principle is analyzed. State estimation is a substitute to observation equation, and observation estimation is gotten. Observation noise variance is adjusted adaptively through observation error. Verification by simulation, convergence speed and robust of adaptive particle filter are superior to traditional algorithm when SOC original error is large. Besides, SOC estimation accuracy and stability is superior to traditional algorithm obviously.