Sliding Mode Control of Both Air-to-Fuel and Fuel Ratios for a Dual-Fuel Internal Combustion Engine

Author(s):  
Stephen Pace ◽  
Guoming G. Zhu

A multi-input-multi-output (MIMO) sliding mode control scheme was developed with guaranteed stability to simultaneously control air-to-fuel ratio (AFR) and fuel ratios to desired levels under various air flow disturbances by regulating the mass flow rates of engine port-fuel-injection (PFI) and direct injection (DI) systems. The sliding mode control performance was compared with a baseline multiloop proportional integral differential (PID) controller through simulations and showed improvements. A four cylinder mean value engine model and the proposed sliding mode controller were implemented into a hardware-in-the-loop (HIL) simulator and a target engine control module, and HIL simulations were conducted to validate the developed controller for potential implementation in an automotive engine.

Author(s):  
Stephen Pace ◽  
Guoming G. Zhu

Air-to-fuel (A/F) ratio is the mass ratio of air-to-fuel mixture trapped inside a cylinder before combustion begins, and it affects engine emissions, fuel economy, and other performances. Using an A/F ratio and dual-fuel ratio control oriented engine model, a multi-input-multi-output (MIMO) sliding mode control scheme is used to simultaneously control the mass flow rate of both port fuel injection (PFI) and direct injection (DI) systems. The control target is to regulate the A/F ratio at a desired level (e.g., at stoichiometric) and fuel ratio (ratio of PFI fueling vs. total fueling) to a given desired level between zero and one. A MIMO sliding mode controller was designed with guaranteed stability to drive the system A/F and fuel ratios to the desired target under various air flow disturbances. The performance of the sliding mode controller was compared with a baseline multi-loop PID (Proportional-Integral-Derivative) controller through simulations and showed improvements over the baseline controller.


Author(s):  
Marco Meza-Aguilar ◽  
Juan Diego Sanchez-Torres ◽  
Antonio Navarrete-Guzman ◽  
Jorge Rivera ◽  
Alexander G. Loukianov

Author(s):  
Raheel Anjum ◽  
Ahmed Yar ◽  
Ghulam Murtaza ◽  
Qadeer Ahmed ◽  
Aamer Bhatti

Abstract The torque produced by the internal combustion engine is desired to be of similar value for consecutive combustion cycles; nevertheless, the difference occurs in the cyclic torque due to disturbances in its generation. The variation between output work of successive combustion cycles is considered as the main cause of imbalance in the cyclic torque. Such variations are displayed in engine output torque and affect its fuel efficiency as well as exhaust emissions. In this paper, a model based unified framework is proposed for the detection and mitigation of cyclic toque imbalance in gasoline engines. First Principle Based Engine Model (FPEM) is employed to develop the proposed novel framework. Fault in fuel injection subsystem is induced to generate an imbalance in the cyclic torque. Uniform Second Order Sliding Mode (USOSM) observer is applied for the estimation of the unknown input i.e. net piston force from engine speed dynamics to detect the imbalance in cyclic torque. Estimated net piston force is employed to design the control law for Certainty Equivalence Super Twisting Algorithm (CESTA) based Fault Tolerant Control (FTC) technique to mitigate the torque imbalance. First Principle Based Engine Model is transformed to get a direct relation between engine speed and fuel input. Results of numerical simulation demonstrated that the desired objective is achieved by the proposed unified framework.


2014 ◽  
Vol 493 ◽  
pp. 321-326
Author(s):  
Agoes Priyanto ◽  
Mohammad Javad Nekooei ◽  
Jaswar

This paper presents an online Artificial Fuzzy sliding Gain Scheduling Sliding Mode Control (AFSGSMC) design and its application to internal combustion (IC) engine high performance nonlinear controller in the presence of uncertainties and external disturbance. The fuzzy online tune sliding function in fuzzy sliding mode controller is based on Mamdanis fuzzy inference system (FIS) and it has multi input and multi output. The input represents the function between sliding function, error and the rate of error. The output represents the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The performance of the AFSGSMC was compared with the IC engine controller based on sliding mode control theory (SMC). Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance


Author(s):  
Sangmin Kang ◽  
Maru Yoon ◽  
Myoungho Sunwoo

The purpose of an engine-controlled traction control system (TCS) is to regulate engine torque in order to keep the driven wheel slip in a desired range. Engine torque can be regulated by a throttle valve. In this paper, the engine-controlled TCS based on an engine model and estimated load torque by a Luenberger observer is proposed. For this control scheme, the engine model is required for a model-based controller design using sliding mode control. The engine torque controller determines the throttle angle for maintaining the desired manifold pressure to generate engine torque corresponding to the desired wheel torque. Since the load torque is composed of multiple external sources such as friction force, drag force, mechanical losses, and others, load torque estimation is required. The simulation results to various manoeuvres during slippery and split road conditions have showed better acceleration performance and stability of the vehicle with TCS. In addition, the load torque observer has estimated real load torque with little error.


Sign in / Sign up

Export Citation Format

Share Document