• DocumentCode
    181637
  • Title

    Legendre pseudospectral computation of optimal speed profiles for vehicle eco-driving system

  • Author

    Shaobing Xu ; Kun Deng ; Li, Shengbo Eben ; Sisi Li ; Bo Cheng

  • Author_Institution
    State Key Lab. of Automotive Safety & Energy, Tsinghua Univ., Beijing, China
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    1103
  • Lastpage
    1108
  • Abstract
    This paper presents a computational framework to solve optimal control problems (OCPs) using Legendre Pseudospectral (PS) method and its application to obtain eco-driving strategies for ground vehicles. Both control and state variables of OCPs are approximated by Lagrange interpolating polynomials at the Legendre-Gauss-Lobatto (LGL) collocation points. The OCP is converted into a nonlinear programming (NLP) problem, and numerically solved by matured optimization algorithms. To implement the PS method, we developed a computational package, called Pseudospectral Optimal control Problem Solver (POPS) in Matlab environment. Further, the POPS is applied to obtain fuel-optimized driving strategies for automated vehicles in hilly road conditions.
  • Keywords
    nonlinear programming; optimal control; road vehicles; LGL collocation points; Lagrange interpolating polynomials; Legendre pseudospectral computation; Legendre-Gauss-Lobatto collocation; Matlab environment; NLP problem; OCPs; POPS; PS method; automated vehicles; computational framework; computational package; eco-driving strategies; fuel-optimized driving strategies; ground vehicles; hilly road conditions; nonlinear programming problem; optimal control problems; optimal speed profiles; optimization algorithms; pseudospectral optimal control problem solver; vehicle eco-driving system; Engines; Fuels; Optimal control; Optimization; Polynomials; Roads; Vehicles; Legendre Pseudospectral method; Optimal control; eco-driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856437
  • Filename
    6856437