• DocumentCode
    1730280
  • Title

    Approximate dynamic programming solutions for lean burn engine aftertreatment

  • Author

    Kang, Jun-Mo ; Kolmanovsky, Ilya ; Grizzle, J.W.

  • Author_Institution
    Electr. Eng. & Comput. Sci. Dept., Michigan Univ., MI, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    1703
  • Abstract
    The competition to deliver fuel efficient and environmentally friendly vehicles is driving the automotive industry to consider ever more complex powertrain systems. Adequate performance of these new highly interactive systems can no longer be obtained through traditional approaches, which are intensive in hardware use and final control software calibration. The paper explores the use of dynamic programming to make model-based design decisions for a lean burn, direct injection spark ignition engine, in combination with a three way catalyst and lean NOx trap aftertreatment system. The primary contribution is the development of a very rapid method to evaluate the tradeoffs in fuel economy and emissions for this novel powertrain system, as a function of design parameters and controller structure, over a standard emission test cycle
  • Keywords
    air pollution control; computational complexity; dynamic programming; internal combustion engines; interpolation; state-space methods; approximate dynamic programming solutions; direct injection spark ignition engine; fuel economy; lean burn engine aftertreatment; model-based design decisions; Automotive engineering; Control systems; Dynamic programming; Electrical equipment industry; Engines; Fuels; Hardware; Interactive systems; Mechanical power transmission; Vehicle driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
  • Conference_Location
    Phoenix, AZ
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-5250-5
  • Type

    conf

  • DOI
    10.1109/CDC.1999.830269
  • Filename
    830269