Fuzzy Sliding-mode Strategy for Air-fuel Ratio Control of Lean-burn Spark Ignition Engines

2017 ◽  
Vol 20 (1) ◽  
pp. 149-158 ◽  
Author(s):  
Hsiu-Ming Wu ◽  
Reza Tafreshi
Keyword(s):  
Sliding Mode ◽  
Spark Ignition ◽  
Spark Ignition Engines ◽  
Lean Burn ◽  
Fuel Ratio ◽  
Fuzzy Sliding Mode

A Dynamic Sliding Manifold for Air-fuel Ratio Control in Lean-Burn Spark Ignition Engines

2012 ◽  
Author(s):  
Behrouz Ebrahimi ◽  
Reza Tafreshi ◽  
Javad Mohammadpour ◽  
Houshang Masudi ◽  
Matthew A. Franchek ◽  
...  
Keyword(s):  
Spark Ignition ◽  
Spark Ignition Engines ◽  
Lean Burn ◽  
Fuel Ratio ◽  
Sliding Manifold

scholarly journals NONLINEAR TORQUE AND AIR-TO-FUEL RATIO CONTROL OF SPARK IGNITION ENGINES USING NEURO-SLIDING MODE TECHNIQUES

2011 ◽  
Vol 21 (03) ◽  
pp. 213-224 ◽  
Author(s):  
TING HUANG ◽  
HOSSEIN JAVAHERIAN ◽  
DERONG LIU
Keyword(s):  
Neural Networks ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Spark Ignition ◽  
Spark Ignition Engines ◽  
New Approach ◽  
Fuel Ratio ◽  
Mode Control ◽  
Equivalent Control ◽  
Corrective Control

This paper presents a new approach for the calibration and control of spark ignition engines using a combination of neural networks and sliding mode control technique. Two parallel neural networks are utilized to realize a neuro-sliding mode control (NSLMC) for self-learning control of automotive engines. The equivalent control and the corrective control terms are the outputs of the neural networks. Instead of using error backpropagation algorithm, the network weights of equivalent control are updated using the Levenberg-Marquardt algorithm. Moreover, a new approach is utilized to update the gain of corrective control. Both modifications of the NSLMC are aimed at improving the transient performance and speed of convergence. Using the data from a test vehicle with a V8 engine, we built neural network models for the engine torque (TRQ) and the air-to-fuel ratio (AFR) dynamics and developed NSLMC controllers to achieve tracking control. The goal of TRQ control and AFR control is to track the commanded values under various operating conditions. From simulation studies, the feasibility and efficiency of the approach are illustrated. For both control problems, excellent tracking performance has been achieved.

scholarly journals Robust Control of the Air to Fuel Ratio in Spark Ignition Engines with Delayed Measurements from a UEGO Sensor

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Javier Espinoza-Jurado ◽  
Emmanuel Dávila ◽  
Jorge Rivera ◽  
Juan José Raygoza-Panduro ◽  
Susana Ortega
Keyword(s):  
Oxygen Sensor ◽  
Sliding Mode ◽  
Time Derivative ◽  
Spark Ignition ◽  
Mean Value ◽  
Control Input ◽  
Spark Ignition Engines ◽  
Precise Control ◽  
Engine Model ◽  
Fuel Ratio

A precise control of the normalized air to fuel ratio in spark ignition engines is an essential task. To achieve this goal, in this work we take into consideration the time delay measurement presented by the universal exhaust gas oxygen sensor along with uncertainties in the volumetric efficiency. For that purpose, observers are designed by means of a super-twisting sliding mode estimation scheme. Also two control schemes based on a general nonlinear model and a similar nonlinear affine representation for the dynamics of the normalized air to fuel ratio were designed in this work by using the super-twisting sliding mode methodology. Such dynamics depends on the control input, that is, the injected fuel mass flow, its time derivative, and its reciprocal. The two latter terms are estimated by means of a robust sliding mode differentiator. The observers and controllers are designed based on an isothermal mean value engine model. Numeric and hardware in the loop simulations were carried out with such model, where parameters were taken from a real engine. The obtained results show a good output tracking and rejection of disturbances when the engine is closed loop with proposed control methods.

In-Cylinder Air Fuel Ratio and Combustion Control for Spark Ignition Engines

1995 ◽  
Author(s):  
Minoru Ohsuga ◽  
Jun'ichi Yamaguchi ◽  
Ryuhei Kawabe ◽  
Masakichi Momono
Keyword(s):  
Spark Ignition ◽  
Spark Ignition Engines ◽  
Combustion Control ◽  
Fuel Ratio

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

2017 ◽  
Author(s):  
Hsiu-Ming Wu ◽  
Reza Tafreshi
Keyword(s):  
Sliding Mode ◽  
Operating Conditions ◽  
Lean Burn ◽  
Time Varying Delay ◽  
Fuel Ratio ◽  
Model Free ◽  
Main Challenge ◽  
System Input ◽  
Si Engines ◽  
High Level

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.

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