DocumentCode :
1543437
Title :
Multiphysical Lithium-Based Battery Model for Use in State-of-Charge Determination
Author :
Watrin, N. ; Roche, R. ; Ostermann, H. ; Blunier, B. ; Miraoui, A.
Author_Institution :
Segula Technol. Automotive, Villeneuve-d´Ascq, France
Volume :
61
Issue :
8
fYear :
2012
Firstpage :
3420
Lastpage :
3429
Abstract :
This paper presents a multiphysical battery pack model, along with a procedure to identify its parameters and its application to state-of-charge (SOC) determination using an extended Kalman filter (EKF). The model enables the reproduction of the electric and thermal behaviors of batteries with high accuracy. A methodology is proposed to identify the parameters of the model and optimize them. The model is experimentally validated with measurements run on high-energy-density ThunderSky cells. A comparison of measurements and model results shows that the electrical model error is below 1.6% and that the error of the thermal model is below 2.5%. The model is used as an EKF basis to reliably estimate the battery SOC. The results are also experimentally verified through measurements showing that the proposed model performs better than other simpler models and determination methods.
Keywords :
Kalman filters; battery management systems; optimisation; power system parameter estimation; secondary cells; EKF; SOC; ThunderSky cell; electrical model error; energy density; extended Kalman filter; multiphysical lithium-based battery model; optimization; parameter identification; state-of-charge determination; thermal model; Batteries; Battery charge measurement; Current measurement; Discharges; Mathematical model; System-on-a-chip; Voltage measurement; Kalman filter; lithium-ion battery; multiphysical modeling; parameter identification; state-of-charge (SOC) determination;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2012.2205169
Filename :
6220281
Link To Document :
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