DocumentCode
2949296
Title
State and Parameter Estimation of a HEV Li-ion Battery Pack Using Adaptive Kalman Filter with a New SOC-OCV Concept
Author
Dai Haifeng ; Wei Xuezhe ; Sun Zechang
Author_Institution
Sch. of Automotive Studies, Tongji Univ., Shanghai, China
Volume
2
fYear
2009
fDate
11-12 April 2009
Firstpage
375
Lastpage
380
Abstract
A new methodology of defining the relationship between SOC (state of charge) and OCV (open circuit voltage) relationship of the Li-ion battery pack used on HEVs (hybrid electric vehicles) which is independent of the battery condition was proposed. This methodology could avoid the problems resulting from the defects that the conventional SOC-OCV relationship differs between batteries and different working conditions. Based on the new definition, a state and parameter estimator of the Li-ion battery pack based on the Sage-Husa adaptive Kalman filter was proposed. This estimator recruited an equivalent circuit model to describe the dynamic characteristics of the battery pack. The estimator could estimate the SOC, the battery actual capacity and the inner resistance on-board. The implementation of the estimator on a FPGA platform was also introduced. Testing results show that the new definition and the estimator work very well in any specific working condition.
Keywords
adaptive Kalman filters; hybrid electric vehicles; lithium; parameter estimation; power filters; secondary cells; state estimation; FPGA platform; Li; Sage-Husa adaptive Kalman filter; hybrid electric vehicles; inner resistance on-board; open circuit voltage; parameter estimation; secondary cells; state estimation; state of charge; Batteries; Employee welfare; Equivalent circuits; Field programmable gate arrays; Hybrid electric vehicles; Parameter estimation; Recruitment; State estimation; Vehicle dynamics; Voltage; HEV Li-ion battery; State and parameter estimation; adaptive Kalman filter; model; new SOC-OCV concept;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-0-7695-3583-8
Type
conf
DOI
10.1109/ICMTMA.2009.333
Filename
5203451
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