EV and PHEV Battery Technologies

Chapter

Abstract

It is well-known today that batteries are indeed the main stumbling block to driving electric vehicles. In fact, the common issues related to lithium rechargeable cells can be summed up by one simple topic: cell equalization. Typically, a battery of a HEV consists of a long string of cells (typically 100 cells, providing a total of about 360 V), where each cell is not exactly equal to the others, in terms of capacity and internal resistance, because of normal dispersion during manufacturing. However, the most viable solution for this problem might not originate from mere changes in battery properties. The aim of this chapter is, first, to explain the role of power electronics based battery cell voltage equalizers and their role in improving cycle life, calendar life, power, and overall safety of EV/HEV battery energy storage systems.

Keywords

Nickel Europe Lithium Cobalt Cadmium 

References:

  1. 1.
    AA Portable Power Corp., Li-ion 18650, quantities of 50,000, Jan. 2009Google Scholar
  2. 2.
    T. Markel, A. Simpson, Energy storage systems considerations for grid-charged hybrid electric vehicles, in Proceedings of IEEE Vehicle Power and Propulsion Conference, Chicago, 2005, pp. 344–349Google Scholar
  3. 3.
    M. Anderman, F. Kalhammer, D. MacArthur, Advanced batteries for electric vehicles: an assessment of performance, cost, and availability, Technical Report for the State of California Air Resources Board, June 2000Google Scholar
  4. 4.
    U.S. DOE, Retail Gasoline Historical Prices. June 2009Google Scholar
  5. 5.
    A123 systems, Inc.; see company website: http://www.a123systems.com
  6. 6.
    LiFeBATT, Inc.; see company website: http://www.lifebatt.com
  7. 7.
    T.R.Crompton, Battery Reference Book, 3rd edn (Newnes, Oxford, 2000) Google Scholar
  8. 8.
    I. Buchmann, Batteries in a Portable World: A Handbook on Rechargeable Batteries for Non-Engineers, 2nd edn (Cadex Electronics Inc, Richmond, 2001)Google Scholar
  9. 9.
    S. Park, A. Savvides, M.B. Srivastava, in ISLPED01 Proceedings of the 2001 International Symposium on Low Power Electronics and Design. Battery capacity measurement and analysis using lithium coin cell battery, California, USA, 2001Google Scholar
  10. 10.
    J.F. Manwell, J.G. McGowan, Lead acid battery storage model for hybrid energy systems. Elsevier J. Sol. Energy 50(5), 399–405 (1993)Google Scholar
  11. 11.
    D. Rakhmatov, S. Vrudhula, D.A. Wallach, A model for battery lifetime analysis for organizing applications on a pocket computer. IEEE Trans. VLSI Syst. 11(6), 1019–1030 (2003)CrossRefGoogle Scholar
  12. 12.
    M.R. Jongerden, B.R. Haverkort, Which battery model to use? IET Softw. 3(6), 445–457 (2009)CrossRefGoogle Scholar
  13. 13.
    M. Chen, G.A. Rincon-Mora, Accurate electrical battery model capable of predicting runtime and I-V performance. IEEE Trans. Energy Convers. 21(2) 504– 511 (2006)Google Scholar
  14. 14.
    Gamry instruments. Application note: basics of electrochemical impedance spectroscopy (2007), www.gamry.com
  15. 15.
    A. Ramamurthy, S. Notani, S. Bhattacharya, Advanced lithium ion battery modeling and power stage integration technique, in 2010 IEEE Energy Conversion Congress and Exposition (ECCE), pp. 1485–1492, 12–16 September 2010Google Scholar
  16. 16.
    E. Barsoukov, J.H. Kim, C.O. Yoon, H. Lee, Universal battery parameterization to yield a nonlinear equivalent circuit valid for battery simulation at arbitrary load. J. Power Sour. 83(1–2), 61–70 (1999)CrossRefGoogle Scholar
  17. 17.
    J. Lee, J. Lee, O. Nam, J. Kim, B.H. Cho, H-S. Yun; S-S. Choi, K. Kim, J.H.Kim, S. Jun, Modeling and real time estimation of lumped equivalent circuit model of a lithium ion battery, in 12th International Power Electronics and Motion Control Conference, 2006. EPE-PEMC 2006, pp. 1536–1540, 2006Google Scholar
  18. 18.
    X. Wei, B. Zhu, W. Xu, Internal resistance identification in vehicle power lithium-ion battery and application in lifetime evaluation. International conference on measuring technology and mechatronics automation, icmtma, vol. 3, pp. 388–392, 2009Google Scholar
  19. 19.
    L.W. Yao, J.A. Aziz, Modeling of lithium ion battery with nonlinear transfer resistance. IEEE applied power electronics colloquium (Iapec), pp. 104–109, 18–19 April 2011Google Scholar
  20. 20.
    A. Shafiei, S.S. Williamson, Plug-in hybrid electric vehicle charging: current issues and future challenges. IEEE vehicle power and propulsion conference (VPPC), pp.1–8, 1–3 September 2010Google Scholar
  21. 21.
    A. Pesaran, V. Johnson, Battery thermal models for hybrid vehicle simulations. J. Power Sour. 110, 377–382 (2002)CrossRefGoogle Scholar
  22. 22.
    D. Bharathan, A. Pesaran, A. Vlahinos, G.-H. Kim, Improving battery design with electro-thermal modeling. IEEE conference on vehicle power and propulsion, p. 8, 7–9 September 2005Google Scholar
  23. 23.
    X. Hu, S. Lin, S. Stanton, W. Lian, A foster network thermal model for HEV/EV battery modeling. IEEE Trans. Ind. Appl. 47(4) 1692–1699 (2011)Google Scholar
  24. 24.
    V.H. Johnson, Battery performance models in advisor. Elsevier J. Pow. Sour. 110(2), 321–329 (2002)Google Scholar
  25. 25.
    Lahiri, K.; Raghunathan, A.; Dey, S.; Panigrahi, D, Battery-driven system design: a new frontier in low power design, in Design Automation Conference Proceedings of ASP-DAC 2002. 7th Asia and South Pacific and the 15th International Conference on VLSI Design, pp. 261–267, 2002Google Scholar
  26. 26.
    M. Knauff, C. Dafis, D. Niebur, A new battery model for use with an extended kalman filter state of charge estimator. American control conference (ACC), pp. 1991–1996, 2010Google Scholar
  27. 27.
    B.O. Anderson, J.B. Moore, Optimal Filtering (Prentice-Hall, Englewood Cliffs, 1979)MATHGoogle Scholar
  28. 28.
    H. Zhang, M-Y. Chow, Comprehensive dynamic battery modeling for PHEV applications. IEEE power and energy society general meeting, pp. 1–6, 25–29 July 2010Google Scholar
  29. 29.
    P. Kumar, P. Bauer, Parameter extraction of battery models using multi objective optimization genetic algorithms. 14th international conference on power electronics and motion control (EPE/PEMC), pp. T9-106-T9-110, 6–8 September 2010Google Scholar
  30. 30.
    W. Banzhaf, P. Nordin, R. Keller, F. Francone, Genetic Programming, an Introduction (Morgan Kaufmann Publishers, San Francisco, 1998)CrossRefMATHGoogle Scholar
  31. 31.
    D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. (Addison-Wesley, Reading, l989)Google Scholar
  32. 32.
    O. Tremblay, L.-A. Dessaint, Experimental validation of a battery dynamic model for ev applications. World Electr. Veh. J. 3. ISSN 2032-6653 - © 2009 AVERE, EVS24 Stavanger, Norway, 13–16 May 2009Google Scholar
  33. 33.
    H. Abea, T. Muraia, K. Zaghibb. Vapor-grown carbon fiber anode for cylindrical lithium ion rechargeable batteries. J. Power Sour. 77(2), 110–115 (1999)Google Scholar
  34. 34.
    H. Webster, Flammability assessment of bulk-packed, rechargeable lithium-ion cells in transport category aircraft. Office of aviation research and development, September 2006Google Scholar
  35. 35.
    P. Ramadass, B. Haran, R. White, B. Popov, Performance study of commercial LiCoO2 and spinel-based Li-ion cells. J. Power Sour. 111(2), 210–220 (2002)CrossRefGoogle Scholar
  36. 36.
    H. Maleki, J. Howard, Effects of overdischarge on performance and thermal stability of a Li-ion cell. J. Power Sour. 160(2), 1395–1402 (2006)CrossRefGoogle Scholar
  37. 37.
    J.W. Lee, Y.K. Anguchamy, B.N. Popov, Simulation of charge-discharge cycling of lithium-ion batteries under low-earth-orbit conditions. J. Power Sour. 162(2), 1395–1400 (2006)CrossRefGoogle Scholar
  38. 38.
    G. Ning, B. Haran, R. White, B. Popov, Cycle life evaluation of pouch lithium-ion battery, in Proceedings 204th Meeting of the Electrochemical Society, Orlando. Abstract No. 414, October 2003Google Scholar
  39. 39.
    P. Liu, K. Kirby, E. Sherman, Failure Mechanism Diagnosis of Lithium-Ion Batteries, in Proceedings of 206th Meeting of the Electrochemical Society, Honolulu, Hawaii, Abstract No. 387, October 2004Google Scholar
  40. 40.
    K.A. Striebel, J. Shim, R. Kostecki, T.J. Richardson, P.N. Ross, X. Song, G.V. Zhuang, Characterization of High-Power Lithium-Ion Cells—Performance and Diagnostic Analysis. (Lawrence Berkeley National Laboratory, Berkeley, 2003). Paper LBNL-54097Google Scholar
  41. 41.
    H. Croft, B. Staniewicz, M.C. Smart, B.V. Ratnakumar, Cycling and Low Temperature Performance of Lithium-Ion Cells, in Proceedings of IEEE 35th Intersociety Energy Conversion Engineering Conference and Exhibit, vol. 1 (Las Vegas, Nevada, 2000), pp. 646–650Google Scholar
  42. 42.
    M.C. Smart, B.V. Ratnakumar, L. Whitcanack, S. Surampudi, J. Byers, R. Marsh, Performance characteristics of lithium-ion cells for NASA’s Mars 2001 Lander application. IEEE Aerosp. Electron. Syst. Mag. 14(11), 36–42 (1999)CrossRefGoogle Scholar
  43. 43.
    Texas Instruments, Bq27500-System Side Impedance Track Fuel Gauge, September 2007Google Scholar
  44. 44.
    U.S. DOE, Annual Energy Review 2008. June 2009, p. 34Google Scholar
  45. 45.
    U.S. DOE, International Petroleum Monthly, World Oil Balance 2004–2008. June 2009Google Scholar
  46. 46.
    U.S. DOE, Annual Energy Review 2008. June 2009, p. 24Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringConcordia UniversityMontrealCanada

Personalised recommendations