Cyclic model based generalized predictive control of air-fuel ratio for gasoline engines

In four stroke internal combustion engines, optimization of engine performance with air-fuel ratio close to stoichiometric condition is still a challenging task specially in transient operation due to cycle-to-cycle coupling of combustion phenomena and gas dynamics in cylinder. In this paper, the cycle-to-cycle in-cylinder gas dynamics coupling model based air-fuel ratio control using the generalized predictive control law has been discussed and validated in which the input parameters of the discrete time model are updated on cyclic event based. With the discrete time model, a Kalman filter-based state variables such as total fuel mass, unreacted air and residual burnt gas are estimated and used to calculated the in-cylinder air-fuel ratio which reflect the cycle-to-cycle coupling effects of residual gas mass. Then based on model, a controller is designed to achieve the air-fuel control. Apart from this, the control performances of generalized predictive controller and PI controller have been compared. Finally, experimental validation results are demonstrated to show the effectiveness of proposed control scheme that is conducted on a full-scaled gasoline engine test bench.