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Large-scale battery system modeling and analysis for emerging electric-drive vehicles

Published: 18 August 2010 Publication History

Abstract

Emerging electric-drive vehicles demonstrate the potential for significant reduction of petroleum consumption and greenhouse gas emissions. Existing electric-drive vehicles typi- cally include a battery system consisting of thousands of Lithium-ion battery cells. Therefore, large-scale battery-system modeling and analysis is essential for battery system performance analysis, next-generation battery system design, and transportation electrification.
This paper presents a modeling and analysis framework for large-scale Lithium-ion battery systems. The proposed solution models major run-time and long-term battery effects, and uses fast frequency-domain analysis techniques. It enables efficient and accurate characterization of large- scale battery system run-time charge-cycle energy efficiency and long-term cycle life. Our solution is validated against physical measurements using real-world user driving studies.

References

[1]
EEtrex. http://www.eetrex.com/.
[2]
Ismail and I. Yehea. Efficient model order reduction via multi-node moment matching. In ICCAD '02, 2002.
[3]
V. H. Johnson. Battery performance models in ADVISOR. Journal of Power Sources, pages 321--329, 2002.
[4]
O. Kazuo, K. Hisashi, H. Takeshi, and I. Kohei. Study on heat generation behavior of small lithium-ion secondary battery. Journal of the Electrochemical Society, 150(3):A285 -- A291, 2003.
[5]
S. A. Khateeb, M. M. Farid, J. R. Selman, and S. Al-Hallaj. Mechanical-electrochemical modeling of Li-ion battery designed for an electric scooter. Journal of Power Sources, 158(1):673 -- 678, 2006.
[6]
K. J. Laidler. The World of Physical Chemistry. Oxford University Press., 1995.
[7]
T. Markel and A. Simpson. Cost-benefit analysis of plug-in hybrid electric vehicle technology. In 22nd International Electric Vehicle Symposium, Oct. 2006.
[8]
T. L. Martin. Balancing batteries, power, and performance:system issues in cpu speed-setting for mobile computing. 1999.
[9]
J. M. Miller. Energy storage system technology challenges facing strong hybrid, plug-in and battery electric vehicles. In IEEE Vehicle Power Propuls. Conf., pages 4--10, 2009.
[10]
Nelson and K. Amine. Advanced lithium-ion batteries for plug-in hybrid-electric vehicles. In EVS23, Argonne National Laboratory, US, 2007.
[11]
D. Panigrahi, C. Chiasserini, S. Dey, R. Rao, A. Raghunathan, and K. Lahiri. Battery life estimation of mobile embedded systems. In Proc. of the 14th IEEE/ACM Intl. Conf. on VLSI Design, San Diego, CA, USA, 2001.
[12]
E. Peled, D. Golodnitsky, G. Ardel, and V. Eshkenazy. The sei model-application to lithium-polymer electrolyte batteries. International Symposium on Polymer Electrolytes, 40:2197--2204, 1995.
[13]
D. Rakhmatov, S. Vrudhula, and D. Wallach. Model for battery lifetime analysis for organizing applications on a pocket computer. IEEE Trans. VLSI Systems, 11(6), 2003.
[14]
P. Ramadass, B. Haran, R. White, and B. N. Popov. Capacity fade of sony 18650 cells cycled at elevated temperatures: Part i. cycling performance. Journal of Power Sources, 112(2):606--613, 2002.
[15]
P. Rong and M. Pedram. An analytical model for predicting the remaining battery capacity of lithium-ion batteries. IEEE Transactions on Very Large Scale Integration VLSI systems, 14(5), 2006.
[16]
S. Santhanagopalan, Q. Guo, P. Ramadass, and R. E. White. Review of models for predicting the cycling performance of lithium ion batteries. Journal of Power Sources, pages 620--628, 2005.
[17]
J. Vetter, P. Novak, M. R. Wagner, C. Veit, K.-C. Moller, J. O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, and C. Vogler. Ageing mechanisms in lithium-ion batteries. Journal of Power Sources, pages 269--281, 2005.

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  • (2013)Real-time prediction of battery power requirements for electric vehiclesProceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems10.1145/2502524.2502527(11-20)Online publication date: 8-Apr-2013
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    cover image ACM Conferences
    ISLPED '10: Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
    August 2010
    458 pages
    ISBN:9781450301466
    DOI:10.1145/1840845
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 18 August 2010

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    Author Tags

    1. analysis
    2. battery system model
    3. electric-drive vehicles

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    View all
    • (2016)Future strategic plan analysis for integrating distributed renewable generation to smart grid through wireless sensor network: Malaysia prospectRenewable and Sustainable Energy Reviews10.1016/j.rser.2015.09.02053(978-992)Online publication date: Jan-2016
    • (2014)Electric vehicles charging control in a smart grid: A model predictive control approachControl Engineering Practice10.1016/j.conengprac.2013.10.00522(147-162)Online publication date: Jan-2014
    • (2013)Real-time prediction of battery power requirements for electric vehiclesProceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems10.1145/2502524.2502527(11-20)Online publication date: 8-Apr-2013
    • (2013)Large-Scale Energy Storage System Design and Optimization for Emerging Electric-Drive VehiclesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2012.222826832:3(325-338)Online publication date: 1-Mar-2013
    • (2013)Energy Storage System Design for Green-Energy Cyber Physical SystemsDesign Technologies for Green and Sustainable Computing Systems10.1007/978-1-4614-4975-1_7(179-203)Online publication date: 11-Jun-2013
    • (2012)Personalized Mobile Sensing System Development for Emerging Electric-Drive VehiclesAdvanced Materials Research10.4028/www.scientific.net/AMR.466-467.1310466-467(1310-1314)Online publication date: Feb-2012
    • (2012)Personalized driving behavior monitoring and analysis for emerging hybrid vehiclesProceedings of the 10th international conference on Pervasive Computing10.1007/978-3-642-31205-2_1(1-19)Online publication date: 18-Jun-2012
    • (2011)Large-Scale Battery System Development and User-Specific Driving Behavior Analysis for Emerging Electric-Drive VehiclesEnergies10.3390/en40507584:5(758-779)Online publication date: 29-Apr-2011
    • (2010)Hybrid energy storage system integration for vehiclesProceedings of the 16th ACM/IEEE international symposium on Low power electronics and design10.1145/1840845.1840925(369-374)Online publication date: 18-Aug-2010

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