Title :
Estimation of Real-Time Peak Power Capability of a Traction Battery Pack Used in an HEV
Author :
Zhang Cai-ping ; Zhang Cheng-ning ; Sharkh, S.M.
Author_Institution :
Nat. Eng. Lab. for Electr. Vehicle, Beijing Inst. of Technol., Beijing, China
Abstract :
Battery peak power capability estimation has an important theoretical significance and utility value for proper use of a battery and to help extend its lifetime. It is an important part of a battery management system. The paper presents an algorithm for estimating the dynamic peak power capability of a battery pack. The algorithm is based on a dynamic battery model taking into consideration constraints of rated, current, voltage and state of charge. The suitability of alternative equivalent circuit models for lithium-ion batteries was also analyzed. It is shown that using Thevenin´s model, the estimation algorithm could compute the dynamic battery peak power in real-time and could provide real-time estimates of the charged and discharged power in an electric vehicle so that the battery may be used within its safe operating limits.
Keywords :
battery management systems; battery powered vehicles; hybrid electric vehicles; lithium; secondary cells; traction power supplies; HEV; Thevenin model; battery management system; dynamic battery model; dynamic peak power capability; electric vehicle; equivalent circuit models; lithium-ion batteries; real-time battery peak power capability estimation; traction battery pack; Automotive engineering; Batteries; Hybrid electric vehicles; Laboratories; Life estimation; Lifetime estimation; Power engineering and energy; Power system modeling; Vehicle dynamics; Voltage;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
DOI :
10.1109/APPEEC.2010.5448755