TY - JOUR
T1 - Electrochemical Estimation and Control for Lithium-Ion Battery Health-Aware Fast Charging
AU - Zou, Changfu
AU - Hu, Xiaosong
AU - Wei, Zhongbao
AU - Wik, Torsten
AU - Egardt, Bo
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical-thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. A moving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.
AB - Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical-thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. A moving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.
KW - Electrochemical model
KW - fast charging
KW - lithium-ion (Li-ion) battery
KW - model predictive control (MPC)
KW - moving horizon estimation (MHE)
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85034233352&partnerID=8YFLogxK
U2 - 10.1109/TIE.2017.2772154
DO - 10.1109/TIE.2017.2772154
M3 - Article
AN - SCOPUS:85034233352
SN - 0278-0046
VL - 65
SP - 6635
EP - 6645
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 8
ER -