Design of a Model-Based Fuzzy-PID Controller with Self-Tuning Scaling Factor for Idle Speed Control of Automotive Engine

Automotive engines spend a considerable portion of their life in idle state, where their characteristics are highly nonlinear and time varying. Efficient control of the engine in idle state significantly improves fuel economy, emission level and drivability. In this work, we proposed a combined fuzzy-PID idle speed controller which improves stability, fuel consumption and emission level, during normal operation as well as transient loads. In order to study the performance of control algorithm, XU7-1761cc gasoline port fuel injection engine has been modeled in idle state. This model calculates engine speed as a function of idle air valve position and ignition angle. This model demonstrated maximum of 8% error during parallel model in the loop and engine in the loop operation. After tuning the membership functions, performance of fuzzy-PID controller has been compared with baseline PID controller of engine control unit. Model in the loop simulation demonstrated that fuzzy-PID controller is more accurate than baseline PID controller, unconditionally stable and is able to reduce fuel consumption in the order of 14% compared to baseline controller. Finally, an experimental setup for real-time control of idle air valve based on proposed controller has also been developed.