• DocumentCode
    2822980
  • Title

    Feedforward Method of Engine Torque Estimiation

  • Author

    Kaisheng, Huang ; Shuaiyu, Wang ; Zhenhua, Jin ; Dinan, Jiang

  • fYear
    2006
  • fDate
    13-15 Dec. 2006
  • Firstpage
    246
  • Lastpage
    249
  • Abstract
    Engine effective torque is a very important performance parameter as well as control parameter. In this paper, a feedforward method of engine torque estimation is presented. After the engine control parameters such as injection pulse width and engine effective torque are gained through engine steady-state experiment, three one-stage statistical models that expresses the relationship between the inputs of engine control parameters and the output of effective torque are built with linear polynomial and artificial neural network algorithm respectively, using MATLAB Model-Based Calibration Toolbox. Tested with the data from engine dynamic experiment, artificial neural network model can obtain a good precision in real time engine torque estimation.
  • Keywords
    engines; feedforward; neurocontrollers; parameter estimation; statistical analysis; torque control; MATLAB model-based calibration toolbox; artificial neural network algorithm; control parameter; engine dynamic experiment; engine effective torque; engine steady-state experiment; engine torque estimation; feedforward method; injection pulse width; linear polynomial algorithm; parameter estimation; statistical model; Artificial neural networks; Calibration; Engines; MATLAB; Mathematical model; Polynomials; Space vector pulse width modulation; Steady-state; Testing; Torque control; engine; estimation; neural network; torque;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-0759-1
  • Electronic_ISBN
    1-4244-0759-1
  • Type

    conf

  • DOI
    10.1109/ICVES.2006.371592
  • Filename
    4234028