• DocumentCode
    2752485
  • Title

    Multi-objective adaptive cruise control based on nonlinear model predictive algorithm

  • Author

    Chen, Tao ; Luo, Yugong ; Li, Keqiang

  • Author_Institution
    State Key Lab. of Automotive Safety & Energy, Tsinghua Univ., Beijing, China
  • fYear
    2011
  • fDate
    10-12 July 2011
  • Firstpage
    274
  • Lastpage
    279
  • Abstract
    A multi-objective Adaptive Cruise Controller of Hybrid Electric Vehicle (so called i-HEV-ACC) is proposed in this paper. It integrates both advantages of Intelligent Transportation Systems (ITS) and HEV, and it reaches comprehensive performances on traffic safety, fuel efficiency and ride comfort. According to the analysis of i-HEV-ACC, a hierarchical control structure with steady-state optimization and dynamic coordination is presented. Furthermore, on the basis of global longitudinal dynamics model, the control strategy of i-HEV-ACC which incorporates comprehensive performances has been developed by employing nonlinear model predictive control algorithm. Finally, the i-HEV-ACC forward simulation platform is established. Through system simulation and analysis, the results demonstrate that i-HEV-ACC can realize coordinated performances of traffic safety, fuel efficiency and ride comfort.
  • Keywords
    adaptive control; hybrid electric vehicles; nonlinear control systems; predictive control; dynamic coordination; fuel efficiency; global longitudinal dynamics model; hierarchical control structure; hybrid electric vehicle; i-HEV-ACC forward simulation platform; intelligent transportation systems; multiobjective adaptive cruise control; nonlinear model predictive control algorithm; ride comfort; steady-state optimization; traffic safety; Engines; Fuels; Optimization; Safety; System-on-a-chip; Vehicle dynamics; Vehicles; i-HEV-ACC; multi-objective coordination; nonlinear model predictive control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety (ICVES), 2011 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4577-0576-2
  • Type

    conf

  • DOI
    10.1109/ICVES.2011.5983828
  • Filename
    5983828