Air-Fuel Ratio Control of Lean-Burn SI Engines Using Fuzzy Sliding-Model Technique

Author(s):  
Hsiu-Ming Wu ◽  
Reza Tafreshi

Minimization of the carbon dioxide and harmful pollutants emissions and maximization of fuel economy for the lean-burn spark ignition (SI) engines significantly rely on precise air-fuel ratio (AFR) control. However, the main challenge of AFR control is the large time-varying delay which exists in lean-burn engines. Since the system is usually subject to external disturbances and uncertainties, a high level of robustness in the AFR control design has to be considered. Herein, a fuzzy sliding-mode control (FSMC) technique is proposed to track the desired AFR in the presence of periodic disturbances. The proposed method is model free and does not need any system characteristics. Based on the fuzzy system input-output data, two scaling factors are first employed to normalize the sliding surface and its derivative. According to the concept of the if-then rule, an appropriate rule table for the logic system is designed. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated under various operating conditions.

Author(s):  
Javier Espinoza-Jurado ◽  
Jorge Rivera ◽  
Alexander Loukianov

Author(s):  
P F Puleston ◽  
G Monsees ◽  
S K Spurgeon

This paper deals with the combined air-fuel ratio (AFR) and speed control of automotive engines. The robust controller is developed using dynamic sliding mode (SM) control design methods. The proposed controller set-up is tested under realistic operating conditions by means of computer simulation using a comprehensive non-linear model of a four-stroke engine, specifically provided by the automotive industry for these purposes. This accurate industrial model comprises extensive dynamics description and numerous look-up tables representing parameter characteristics obtained from experimental data. The SM controller set-up proves to be robust to model uncertainties and unknown disturbances, regulating effectively the engine speed for a wide range of set-points while maintaining the AFR at the stoichiometric value.


2012 ◽  
Vol 45 (30) ◽  
pp. 296-301 ◽  
Author(s):  
B. Ebrahimi ◽  
R. Tafreshi ◽  
H. Masudi ◽  
M.A. Franchek ◽  
J. Mohammadpour ◽  
...  

2019 ◽  
Vol 11 (1) ◽  
pp. 168781401882210
Author(s):  
Hsiu-Ming Wu ◽  
Reza Tafreshi

Air–fuel ratio is a key factor for the minimization of the harmful pollutant emissions and maximization of fuel economy. However, a big challenge for air–fuel ratio control is a large time-varying delay existing in spark ignition engines. In this article, a digital fuzzy sliding-mode controller is proposed to control a linear parameter-varying sampled-data air–fuel ratio system. First, the Pade first-order technique is utilized to approximate the time-varying delay. The resultant system—a linear parameter-varying continuous-time air–fuel ratio system with unstable internal dynamics—is then discretized to a linear parameter-varying sampled-data air–fuel ratio system appropriate for a discrete-time control approach. Based on the linear parameter-varying sampled-data air–fuel ratio system, a stable sliding surface with a desired tracking error dynamics is presented. Two input scaling factors and one output scaling factor are determined for the proposed digital fuzzy sliding-mode controller. Then, the fuzzy inference is executed through a look-up table to stabilize the sliding surface into a convex set, and then make the tracking error possess uniformly ultimately bounded performance. The overall system stability is verified by Lyapunov’s stability criteria. Finally, the simulation results demonstrate the feasibility, effectiveness, and robustness of the proposed control scheme under different operating conditions and show the superiority of the proposed approach performance compared to the baseline controller.


2000 ◽  
Author(s):  
J. R. Wagner ◽  
D. M. Dawson ◽  
Z. Liu

Abstract The wide-range of operating conditions, inherent induction process nonlinearities, and gradual component degradations due to aging, have prompted research into model-based engine control algorithms. Consequentially, a variety of nonlinear and intelligent algorithms have been proposed and experimentally studied. Recent attention has focused on the simultaneous regulation of the air-to-fuel ratio and engine speed using a sliding mode control strategy. In this paper, a nonlinear model-based backstepping control strategy will be proposed for simultaneous air-to-fuel ratio control and speed tracking in passenger/light-duty automobile engines. For comparison purposes, a multi-surface sliding mode controller and an integrated speed-density air-to-fuel controller with attached engine speed regulation will be implemented. Representative numerical results will be presented and discussed.


Energy ◽  
2017 ◽  
Vol 120 ◽  
pp. 106-116 ◽  
Author(s):  
Madan Kumar ◽  
Tielong Shen

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