DocumentCode :
2850049
Title :
Hybrid electric vehicle supervisory control design reflecting estimated lithium-ion battery electrochemical dynamics
Author :
Tae-Kyung Lee ; Youngki Kim ; Stefanopoulou, A. ; Filipi, Z.S.
Author_Institution :
Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
388
Lastpage :
395
Abstract :
Accurate prediction of the battery electrochemical dynamics is important to avoid undesired battery operation under aggressive driving. This paper proposes a battery power management strategy considering Li-ion concentration in the electrodes to prevent excessive battery charging and discharging. The proposed approach adjusts the allowable battery power limits through the feedback of the estimated electrode-averaged Li-ion concentration information. An advanced hybrid electric vehicle (HEV) power split strategy is constructed implementing a Li-ion battery model with electrochemical diffusion dynamics to capture the battery dynamic behavior under transients. A novel contribution arises from the implementation of an extended Kalman filter (EKF) using uneven discretization of the particle radius for fast and accurate prediction of the Lithium intercalation dynamics. The control design modifies the allowable battery power limit used in the supervisory controller, thus, maintaining low complexity of the control structure.
Keywords :
Kalman filters; SCADA systems; battery management systems; battery powered vehicles; control system synthesis; electrochemical electrodes; hybrid electric vehicles; lithium compounds; secondary cells; Li-ion concentration; aggressive driving; battery charging; battery discharging; battery power management; electrochemical diffusion dynamics; electrodes; extended Kalman filter; hybrid electric vehicle; lithium intercalation dynamics; lithium-ion battery; supervisory control design; Batteries; Electrodes; Hybrid electric vehicles; Mathematical model; Solid modeling; Solids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5990985
Filename :
5990985
Link To Document :
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