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Idle Control of Internal Combustion Engines (ICEs) is an important mode of Engine Management Systems (EMS) due to its effects on Fuel Consumption (FC) and pollutions produced in urban traffics. In this paper an optimal controller is used to control the idle speed with respect to minimization of FC in transient situations. In order to design an optimal controller a state space representation of engine in demanded. Subspace identification method is used to derive a proper state space model of engine around idle speed state. The required input/output data is generated using a mean value model. A finite time optimal controller is designed with the aim of minimizing both fuel consumption and speed fluctuations. The influence of finite time value on gross fuel consumption is then studied under various weighting factors. It is shown that the fuel consumption is sensitive to the controlling time duration for finite time LQR.

In this paper a state space representation of a turbocharged diesel engine is provided based on off-line least square method. Internal combustion engines show high nonlinear behavior due to complicated combustion phenomena and air flow dynamics inside the engine. In development phase of modern control methods like LQR controller, an accurate state space model with meaningful and measurable states is required. Identification is the method of deriving a mathematical model for dynamic systems based on input-output data. In this paper a mean value model of a turbocharged diesel engine is employed to generate demanded input-output data for identification purposes. This nonlinear mean value model predicts engine speed as a function mass of fuel injected per cycle, injection timing (ξ), ambient pressure and temperature and external loads. In the next step the simulation data is used to develop a state space model around idle mode operation state.