Unscented Kalman Filter-Based Battery SOC Estimation and Peak Power Prediction Method for Power Distribution of Hybrid Electric Vehicles

• Published in: IEEE access Vol. 6; pp. 35957 - 35965
• Main Authors: Wang, Weida, Wang, Xiantao, Xiang, Changle, Wei, Chao, Zhao, Yulong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Batteries; Computational modeling; Electric power distribution; Electric vehicles; Energy management; Estimation; Extended Kalman filter; Hybrid electric vehicles; Integrated circuit modeling; Lithium; Lithium-ion batteries; Lithium-ion battery; Mathematical model; Noise; noise suppression; peak power prediction; Power management; Prediction algorithms; Rechargeable batteries; Sampling; SOC estimation; State of charge; unscented Kalman filter; Vehicles

State of Charge (SOC) is a key parameter for battery management and vehicle energy management. Recently used SOC estimation methods for lithium-ion battery for vehicles have problems of too simple a base model for the battery and large sampling noise in both the voltage and current signals. To impro...