TY - GEN
T1 - Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries
AU - Hu, Jian
AU - Wei, Zhongbao
AU - He, Hongwen
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/24
Y1 - 2021/5/24
N2 - Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.
AB - Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.
KW - lithium-ion battery
KW - moving horizon estimation
KW - state of charge
KW - unknown input observer
UR - http://www.scopus.com/inward/record.url?scp=85114208886&partnerID=8YFLogxK
U2 - 10.1109/ECCE-Asia49820.2021.9479173
DO - 10.1109/ECCE-Asia49820.2021.9479173
M3 - Conference contribution
AN - SCOPUS:85114208886
T3 - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
SP - 959
EP - 962
BT - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Y2 - 24 May 2021 through 27 May 2021
ER -
