Estimation of Gasoline-Engine Parameters Using Higher Order Sliding Mode

Abstract

Automotive-engine control and fault diagnostics largely depend upon the accuracy of the nonlinear models used. The structure of these nonlinear models is generally agreed upon. However, the model parameters are mostly difficult to obtain. This paper presents the development of second-order sliding-mode technique with real twisting algorithm for estimation of more than one parameter from a single dynamical equation of the nonlinear model. The system under study is a mean-value engine model of a naturally breathing gasoline engine. The parameters estimated are throttle body's discharge coefficient, load torque, and indicated torque as a function of inlet manifold pressure. The estimated variables are used to compensate for the unmodeled dynamics, modeling inaccuracies, and approximations which arise from the assumptions made for the development of mathematical model of a real-world system. The resulting model is a better description of the actual engine dynamics and gives good agreement to real engine data. The data are acquired from a production model vehicle equipped with an electronic control unit compliant to OBD-II standard. The observer designed is simple enough for implementation, and estimated parameters can also be used for engine-controller design and fault-diagnosis work.