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

Abstract

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.

Digital fuzzy sliding-mode control for a linear parameter-varying air–fuel ratio system

“…In this article, the sampling interval is chosen as 0.01 s. In addition, a set of delays with an increment of 10 time intervals was conducted for 0. First, the proposed DFSMC (equation (8)) was applied to the LPV sampled-data AFR system with external periodic disturbances modeled in equation (3). Figure 5 displays the output tracking and its corresponding control input.…”

“…6 A linear quadratic (LQ) tracking controller was designed by Pace and Zhu 7 to optimally track the desired AFR by minimizing the error between the trapped in-cylinder air mass and the product of the desired AFR and fuel mass. Recently, a generalized predictive control (GPC) was proposed by Kumar and Shen 8 to achieve AFR control based on the cycle-tocycle in-cylinder gas dynamic coupling model. Furthermore, total fuel mass, unreacted air, and residual burnt gas were estimated using the Kalman filter technique to calculate the in-cylinder AFR.…”

Improved scheme of membership function optimisation for fuzzy air‐fuel ratio control of GDI engines

“…Here, the integral of the absolute magnitude of error (ITAE) index is introduced that takes advantages of producing smaller overshoots and oscillations [35]. The ITAE criterion is defined as = ∑ | | ∞ 0 (13) Performance comparisons of the AFR regulation for GDI engines by using the PI-like FKBC with existing MFs and conventional PI lookup table are summarised in Table 5 with overshooting, convergence time and ITAE.…”

“…Relatively, to construct two control laws need to spend huge workload on identifying engine model. In 2016, Madan K. pointed out that a cyclic model based generalized predictive control of AFR for V6 GDI engines [13], which shows reflect the cycle-to-cycle coupling effects of residual gas mass.…”

“…Relatively, to construct two control laws it is needed to spend huge workload on identifying engine model. In 2016, Madan pointed out a cyclic model based generalised predictive control of AFR for V6 GDI engines [13], which shows the reflection of cycle‐to‐cycle coupling effects of residual gas mass. Actually, it is hard to predict the non‐linear relation of the model‐based controller and the transient response performance is not optimistic as results.…”