Air-to-fuel ratio control of gasoline engines using smooth sliding mode algorithm

An application of Smooth Super-Twisting Algorithm (SSTA) for air-to-fuel ratio (AFR) control of a gasoline engine is presented. Air-to-fuel ratio control has remained important problem to minimize calibration effort and meeting performance requirements. Operating gasoline engine at a desired air-to-fuel ratio is critical as optimal conversion efficiency of a three-way catalytic converter exists around the stoichiometric value of air-to-fuel ratio of an engine. Primarily, deviation of air-to-fuel ratio from ideal stoichiometric value occur due to difference in actual fuel mass flow rate from desired fuel mass rate. For this reason, a self converging and robust Smooth Super-Twisting Algorithm based controller is proposed. Mean Value Engine Model (MVEM) of Spark Ignition (SI) has been utilized to control its air-to-fuel ratio. Controller performance has been analyzed by parameters variation of fuel delivery subsystem and proposed controller. Simulation results showed that chattering effect has been substantially reduced while maintaining robustness to model errors.