摘要：AbstractThe engine control and estimation problem is an important area of research in the automotive industry. Researchers have been working to make the vehicles more efficient and economically friendly while producing lesser pollutants. To reduce emissions, the air-fuel ratio must be controlled to a specific value. The requirement of air-fuel ratio improvement has increased the need for the investigation of engine dynamical models and their parameter estimation. Some of the main parameters affecting the air-fuel ratio are the throttle discharge coefficient, thermal efficiency and volumetric efficiency. The precise values of these parameters are essential for accurate control of the air-fuel ratio of the engine. Under steady state, these parameters are constant but in the long run due to wear and tear of the engine and various uncertainties, their value may change. The main challenges are how to obtain the information of parameters and that of the states under the influence of process noise, measurement noise and parameter uncertainty, which are essential elements to develop an effective control strategy. In this work, the problem of physical parameter estimation of the nonlinear system comprising a throttle, intake manifold, engine speed dynamics and fuel system altogether with unknown states have been considered. A novel method with a unique combination of Unscented Kalman Filter and Recursive Least Squares with forgetting factor for estimation of parameters and states of spark ignition engines has been developed. Simulation results are provided for state and parameter estimation for spark ignition engine model.
关键词：KeywordsSpark Ignition engineRecursive Least Squares methodUnscented Kalman Filtercoefficient of discharge in throttle bodyvolumetric efficiencythermal efficiency
