State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization

• Main Authors: Ismail, Nur Hazima Faezaa, Toha, Siti Fauziah
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: T175 Industrial research. Research and development
• Online Access: http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf; http://irep.iium.edu.my/34110/

Lithium-ion battery plays important roles in electric drive vehicles. It has several advantages among other battery technologies such as high energy density and specific energy. The primary concerns of Lithium-ion batteries are to maintain optimum battery performance and extend the battery’s life. An accurate state of charge (SOC) estimation can improve the performance of Lithium-ion battery. In this paper, a method for SOC estimation for LiFePO4 using the particle swarm optimization (PSO) algorithm is presented. The results indicate the SOC estimation using PSO optimized algorithm has good performance. The simulation result has also been validated and complies within specific confidence level.