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Control Strategy for Hybrid Electric Vehicle Based on Online Driving Pattern Classification

Journal Article
08-08-02-0006
ISSN: 2167-4191, e-ISSN: 2167-4205
Published December 04, 2019 by SAE International in United States
Control Strategy for Hybrid Electric Vehicle Based on Online Driving Pattern Classification
Sector:
Citation: Yao, Z. and Yoon, H., "Control Strategy for Hybrid Electric Vehicle Based on Online Driving Pattern Classification," SAE Int. J. Alt. Power. 8(2):91-102, 2019, https://doi.org/10.4271/08-08-02-0006.
Language: English

References

  1. Wei , Z. , Xu , J. , and Halim , D. HEV Power Management Control Strategy for Urban Driving Applied Energy 194 705 714 2017
  2. Enang , W. and Bannister , C. Modelling and Control of Hybrid Electric Vehicles (A Comprehensive Review) Renewable and Sustainable Energy Reviews 74 1210 1239 2017
  3. Ehsani , M. , Gao , Y. , and Miller , J.M. Hybrid Electric Vehicles: Architecture and Motor Drives Proceedings of the IEEE 95 4 719 728 2007
  4. Becerra , G. , Alvarez-Icaza , L. , and Pantoja-Vázquez , A. Power Flow Control Strategies in Parallel Hybrid Electric Vehicles Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 230 14 1925 1941 2016
  5. Tate , E.D. and Boyd , S.P. Finding Ultimate Limits of Performance for Hybrid Electric Vehicles SAE Technical Paper 2000-01-3099 2000 https://doi.org/10.4271/2000-01-3099
  6. Chen , H. , Kessels , J. , and Weiland , S. Adaptive ECMS: A Causal Set-Theoretic Method for Equivalence Factor Estimation IFAC-PapersOnLine 48 15 78 85 2015
  7. Pisu , P. and Rizzoni , G. A Comparative Study of Supervisory Control Strategies for Hybrid Electric Vehicles IEEE Transactions on Control Systems Technology 15 3 506 518 2007
  8. Wirasingha , S.G. and Emadi , A. Classification and Review of Control Strategies for Plug-In Hybrid Electric Vehicles IEEE Transactions on Vehicular Technology 60 1 111 122 2010
  9. Jalil , N. , Kheir , N.A. , and Salman , M. A Rule-Based Energy Management Strategy for a Series Hybrid Vehicle Proceedings of the 1997 American Control Conference Albuquerque, NM 1997
  10. Lin , C.-C. et al. Power Management Strategy for a Parallel Hybrid Electric Truck IEEE Transactions on Control Systems Technology 11 6 839 849 2003
  11. Wang , R. and Lukic , S.M. Review of Driving Conditions Prediction and Driving Style Recognition Based Control Algorithms for Hybrid Electric Vehicles 2011 IEEE Vehicle Power and Propulsion Conference Chicago, IL 2011
  12. Feng , L. , Liu , W. , and Chen , B. Driving Pattern Recognition for Adaptive Hybrid Vehicle Control SAE International Journal of Alternative Powertrains 1 1 169 179 2012 https://doi.org/10.4271/2012-01-0742
  13. Lei , Z. et al. Dynamic Energy Management for a Novel Hybrid Electric System Based on Driving Pattern Recognition Applied Mathematical Modelling 45 940 954 2017
  14. Gu , B. and Rizzoni , G. An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management Based on Driving Pattern Recognition ASME 2006 International Mechanical Engineering Congress and Exposition Chicago, IL 2006
  15. Lin , C.-C. et al. Control of a Hybrid Electric Truck Based on Driving Pattern Recognition Proceedings of the 2002 Advanced Vehicle Control Conference 2002 Hiroshima, Japan
  16. Zhang , S. and Xiong , R. Adaptive Energy Management of a Plug-In Hybrid Electric Vehicle Based on Driving Pattern Recognition and Dynamic Programming Applied Energy 155 68 78 2015
  17. Higuchi , N. , Sunaga , Y. , Tanaka , M. , and Shimada , H. , Development of a New Two-Motor Plug-In Hybrid System SAE Int. J. Alt. Power. 2 1 135 145 2013 https://doi.org/10.4271/2013-01-1476
  18. Mathworks https://www.mathworks.com/help/releases/R2017a/pdf_doc/autoblks/autoblks_ref.pdf 2019
  19. Wang , H. , Zhang , X. , and Ouyang , M. Energy Consumption of Electric Vehicles Based on Real-World Driving Patterns: A Case Study of Beijing Applied Energy 157 710 719 2015
  20. US Environmental Protection Agency 2011
  21. United States Census Bureau 2017
  22. Alpaydin , E. Introduction to Machine Learning Cambridge, MA MIT Press 2014

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