Battery state of charge estimation using adaptive extended kalman filter for electric vehicle application

• Main Authors: Shrivastava, Prashant, Soon, Tey Kok, Bin Idris, Mohd Yamani Idna, Mekhilef, Saad
• Format: Conference or Workshop Item
• Published: IEEE 2020
• Subjects: QA75 Electronic computers. Computer science; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/37178/; https://ieeexplore.ieee.org/document/9367743
• Institution: Universiti Malaya

To build up a proficient battery management system, it is required to accurately estimate the state of charge (SOC) of the electric vehicle (EV) battery. Generally, the accuracy of the conventional extended Kalman Filter (CEKF) algorithm is exceptionally affected by the method used to update the noi...