DocumentCode :
1937310
Title :
A new SOH prediction concept for the power lithium-ion battery used on HEVs
Author :
Haifeng, Dai ; Xuezhe, Wei ; Zechang, Sun
Author_Institution :
Sch. of Automotive Studies, Tongji Univ., Shanghai, China
fYear :
2009
fDate :
7-10 Sept. 2009
Firstpage :
1649
Lastpage :
1653
Abstract :
One of the most important tasks of the battery management system (BMS) is to estimate the battery states which mainly include the State of Charge (SOC) and State of Health (SOH). Compared with the SOC estimation technology, which progresses a lot currently, the study of SOH prediction method is in its junior state. In this paper, a SOH prediction concept was proposed. Main points of this concept include the aging process of the battery, the definition of the SOH, and prediction of the battery´s healthy state etc. Aiming at the application mode of the battery packs on hybrid electric vehicles (HEVs), ageing processes of the battery were discussed and several accelerated life test results were listed. Then according to the ageing process studies, a power-reflecting SOH definition was proposed. Based on these, a parameter system identification based SOH prediction method was designed. To validate the SOH prediction concept we presented, a simulation test was designed, and test result show that the concept is feasible to predict SOH online.
Keywords :
ageing; battery management systems; hybrid electric vehicles; life testing; parameter estimation; secondary cells; HEV; ageing process studies; battery management system; hybrid electric vehicles; lithium-ion-battery; power-reflecting SOH; state of charge prediction; state of health prediction; Accelerated aging; Battery management systems; Design methodology; Hybrid electric vehicles; Life estimation; Life testing; Prediction methods; Predictive models; State estimation; System identification; Ageing process; Lithium-ion battery; Parameter identification; SOH prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicle Power and Propulsion Conference, 2009. VPPC '09. IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
978-1-4244-2600-3
Electronic_ISBN :
978-1-4244-2601-0
Type :
conf
DOI :
10.1109/VPPC.2009.5289654
Filename :
5289654
Link To Document :
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