Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery
Joint Authors
Zheng, Jun
Zhang, Liqiang
Ma, Kehua
Wang, Lixin
Luo, Weilin
Lyu, Chao
Source
Advances in Mechanical Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-26
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery.
This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification.
Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters.
Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model.
For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB.
The performance of two parallelized methods, namely Single Program Multiple Data (SPMD) and parallel FOR loop (PARFOR), is investigated and then the parallelized GA identification is proposed.
With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA.
This conclusion is validated by model parameter identification of a real LiFePO4 battery.
American Psychological Association (APA)
Zhang, Liqiang& Lyu, Chao& Wang, Lixin& Zheng, Jun& Luo, Weilin& Ma, Kehua. 2013. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-496174
Modern Language Association (MLA)
Zhang, Liqiang…[et al.]. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery. Advances in Mechanical Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-496174
American Medical Association (AMA)
Zhang, Liqiang& Lyu, Chao& Wang, Lixin& Zheng, Jun& Luo, Weilin& Ma, Kehua. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-496174
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496174