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Future Trends in Vehicle Power Management

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Vehicle Power Management

Part of the book series: Power Systems ((POWSYS))

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Abstract

With an eye to the future development and potential problems of vehicle power management, this chapter first introduces some state-of-the-art technologies in alternative fuel vehicles and accordingly powertrain components, and then delineates several thoughts including appropriate combinations of existing strategies, more considerations of safety factors from new components, precision improvement of battery SOC, better prediction of driving patterns using advanced communication technologies, etc. Magnificent prospects of vehicle power management are painted for readers in this chapter.

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References

  1. Gonder J, Markel T (2007) Energy management strategies for plug in hybrid electric vehicles. SAE world congress 2007-01-0290

    Google Scholar 

  2. Sciarretta A, Back M, Guzzella L (2004) Optimal control of parallel hybrid electric vehicles. IEEE Trans Control Syst Technol 12:352–363

    Article  Google Scholar 

  3. Arsie I, Graziosi M, Pianese C et al (2004) Optimization of supervisory control strategy for parallel hybrid vehicle with provisional load estimate. AVEC 2004, pp 483–488

    Google Scholar 

  4. Tomoyuki O, Hiroaki Y, Shinji W, Keiichiro K, Minoru K (2008) Design estimation of the hybrid power source railwa y vehicle based on the multi objective optimization by the dynamic programming. IEEE Trans Electr Electron Eng 3:48–55

    Article  Google Scholar 

  5. Augusto FA, Antenor PJ, Giorgio S et al (2008) Energy management fuzzy logic supervisory for electric vehicle power supplies system. IEEE Trans Power Electron 23:107–115

    Article  Google Scholar 

  6. Schouten NJ, Salman MA, Kheir NA (2002) Fuzzy logic control for parallel hybrid vehicles. IEEE Trans Control Syst Technol 10:460–468

    Article  Google Scholar 

  7. Lelitha V, Laurence R (2004) A comparison of the performance of artificial neural networks and support vector machines for the prediction of traffic speed. IEEE Intelligent Vehicles Symposium 2004, pp 194–199

    Google Scholar 

  8. McFadden J, Yang WT, Durrans SR (2001) Application of artificial neural networks to predict speeds on two lane rural highways. Transp Res Rec 1751:9–17

    Article  Google Scholar 

  9. Hydrogen use in internal combustion engines. http://www1.eere.energy.gov/hydrogen andfuelcellsandfuelcells/tech_validation/pdfs/fcm03r0.pdf. Accessed 5 April 2010

  10. BMW hydrogen 7. http://www.hydrogencarsnow.com/bmw-hydrogen7.htm. Accessed 3 Mar 2010

  11. Hydrogen engine. http://www.ca.sandia.gov/crf/research/combustionEngines/PFI.php. Accessed 3 Mar 2010

  12. Introducing the IRIS engine A breakthrough in energy efficiency. http://www.irisengine.com/index2.html. Accessed 13 Mar 2010

  13. Chun WH, Yi SC, Tswen SD et al (2006) Enhanced high temperature cycle life of LiFePO4 based Li ion batteries by vinylene carbonate as electrolyte additive. Electrochem Solid State Lett 9:537–541

    Article  Google Scholar 

  14. China’s BYD to dell electric cars and plug in hybrids in Israel in 2009 http://www.iconocast.com/00006/R1/News2.htm. Accessed 9 Mar 2010

  15. Nanotechnology companies and products. http://www.understandingnano.com/nanotechnology-companies.html. Accessed 3 Mar 2010

  16. Products. http://www.a123systems.com/products. Accessed 3 Mar 2011

  17. Company brochure. http://b2icontent.irpass.cc/546%2F93807.pdf?AWSAccessKeyId = 1Y51NDPSZK99KT3F8VG2&Expires = 1244490241&Signature = sOeaA%2BmbTjhD1QO6B2BPTFe%2BlK8%3D. Accessed 3 April 2010

  18. Technology nanomaterial synthesis. http://www.nanoexa.com/nanomaterial.html. Accessed 4 April 2010

  19. Plug in hybrid. http://en.wikipedia.org/wiki/Plug-in_hybrid. Accessed 3 Mar 2010

  20. Langari R, Won JS (2005) Intelligent energy management agent for a parallel hybrid vehicle part I system architecture and design of the driving situation identification process. IEEE Trans Veh Technol 54:925–934

    Article  Google Scholar 

  21. Sierra Research (2003) SCF Improvement-cycle development. SR2003-06-02

    Google Scholar 

  22. Raj M, Craig S (2005) The effect of process models on short term prediction of moving objects for autonomous driving. Int J Control Autom Syst 3:509–523

    Google Scholar 

  23. Murphey YL (2008) Intelligent vehicle power management an overview. Stud Comput Intell 132:223–251

    Google Scholar 

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Correspondence to Chris Mi .

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© 2011 Springer-Verlag London Limited

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Zhang, X., Mi, C. (2011). Future Trends in Vehicle Power Management. In: Vehicle Power Management. Power Systems. Springer, London. https://doi.org/10.1007/978-0-85729-736-5_11

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  • DOI: https://doi.org/10.1007/978-0-85729-736-5_11

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  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-735-8

  • Online ISBN: 978-0-85729-736-5

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