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Extraction of Battery Parameters for Optimal Performance Using the Circuit Model with a Multi-Objective Genetic Algorithm
Technical Paper
2013-01-1540
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent-circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials. Several test cases demonstrate that the multi-objective genetic algorithm can serve as a robust and reliable tool for extracting the battery performance parameters.
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Authors
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Citation
Brand, J., Zhang, Z., and Agarwal, R., "Extraction of Battery Parameters for Optimal Performance Using the Circuit Model with a Multi-Objective Genetic Algorithm," SAE Technical Paper 2013-01-1540, 2013, https://doi.org/10.4271/2013-01-1540.Also In
References
- Larmine , J. and Lowry , J. Electric Vehicle Technology Explained John Wiley 2003
- North American Reliability Corporation Accommodating High Levels of Variable Power Generation April 2009
- Makarov , Y.V. , Yang , J.G. , DeSteese , S. , Lu , S. , Miller , C.H. , Nyeng , P. , Ma , J. , Hammerstorm , D.J. , and Viswanathan , V.V. Wide Area Energy Storage and Management System to Balance Intermittent Resources in the Bonneville Power Administration in California ISO Control Areas June 2008
- Tremblay , O. , Dessaint , L.A. , and Dekkich , A.I. A Generic Battery Model for the Dynamic Simulation of Hybrid Electric Vehicles Applied Power Electronics Conference and Exposition 603 607 2009
- Bor , Y. , Liaw , G. , Nagasubramanian , R. , Jungst , G. , and Doughty , D.H. Modeling of Lithium-ion Cells - A Simple Equivalent Circuit Model Approach J. of Solid State Ionics 835 839 2004
- Kumar , P. and Bauer , P. Parameter Extraction of Battery Models Using Multi-objective Optimization Genetic Algorithms International Power Electronics and Motion Control Conference 106 110 2010 10.1109/EPEPEMC.2010.5606653
- Deb , K. , Pratap et al. A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II IEEE Transactions on Evolutionary Computation 6 2 April 2002
- www.eigbattery.com
- ANR26650 product catalog, A123 Systems http://www.a123systems.com/lithium-ion-cells-26650-cylindrical-cell.htm Sept. 2012
- MS614SE project catalog, Seiko Instruments Inc. http://www.sii.co.jp/components/battery/productSpecBatEN.jsp?recordID=74 Sept. 2012
- Peng , Z. , Freunberger , S.A. , Chen , Y. , and Bruce , P.G. A Reversible and Higher-Rate Li-O 2 Battery Science Express 337 6094 563 566 2012 10.1126/science.1223985
- Manohar , A.K. , Malkhandi , S. , Yang , B. , Yang , C. , Surya Prakash , G.K. , and Narayanan , S.R. A High-Performance Rechargeable Iron Electrode for Large-Scale Battery-Based Energy Storage Journal of Electrochemical Society 159 8 A1209 A1214 2012 10.1149/2.034208jes
- Verbrugge , M.W. and Conell , R.S. Electrochemical and Thermal Characterization of Battery Modules Commensurate with Electric Vehicle Integration Journal of the Electrochemical Society 149 A45 A53 2002 10.1149/1.1426395
- Bader , J.M. Hyper-volume Based Search for Multi-objective Optimization: Theory and Methods CreateSpace Independent Publishing Platform 2010
- A Framework for Multi-Objective Optimization http://jmetal.sourceforge.net Sept. 2012
- Durillo , J.J. , Nebro , A.J. , Coello , C.A. , Garcia-Nieto , J. , Luna , F. , and Alba , E. A Study of Multi-Objective Metaheuristics when Solving Parameter Scalable Problems IEEE Transactions on Evolutionary Computation 14 4 618 635 2010 10.1109/TEVC.2009.2034647
- Whitley Darrell A Genetic Algorithm Tutorial Colorado State University http://reference.kfupm.edu.sa/content/g/e/a_genetic_algor ithm_tutorial_80073.pdf Sept. 2012
- Miller , B.L. and Goldberg , D.E. Genetic Algorithms, Tournament Selection, and the Effects of Noise University of Illinois Urbana-Champaign 1995 10.1.1.30.6625