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Research on Air-Fuel Ratio Control Method for Gasoline Engine Base on MATLAB

Author: HuangJian
Tutor: SongGuiQiu
School: Northeastern University
Course: Mechanical and Electronic Engineering
Keywords: Air-fuel ratio Automotive engine Control strategy Neural Networks
CLC: TK412
Type: Master's thesis
Year: 2008
Downloads: 226
Quote: 1
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Abstract


The automotive air-fuel ratio control and ignition advance angle control are two important issues in the engine control system. To make the car to meet emissions requirements, but also has good driveability of the engine's air-fuel ratio and ignition advance angle control. This is the highest stoichiometric combustible mixture, so it is necessary to control the air-fuel ratio of the engine to reduce emissions in the vicinity of the value of this theory, because the conversion efficiency of the three-way catalytic converter. For effective control of the rotational speed of the engine is also an important problem in the engine control system, not only can be a flexible embodied engine power performance, but also to save fuel so as to improve the economic performance of the engine. Firstly, using Matlab / simulink to establish engine system model and control system model. The engine control system is a multi-input multi-output nonlinear system with parameter uncertainty and time-varying nonlinear model of the air-fuel ratio control system, the traditional model identification method is difficult to apply. To this end, we consider the running characteristics of the engine under different conditions, respectively, using different control algorithms. Based on neural network control algorithm is simple, highly robust, and suitable for the engine in transient operating conditions such pure delay nonlinear object This selection of more adaptive ability to learn faster, more efficient BP neural network control algorithm; based on fuzzy parameter self-tuning PID control algorithm with dynamic tracking of good quality and high steady-state accuracy and less sensitive to the control system parameters adjustment, this article this algorithm applied to the heat engine idling condition; steady-state control conditions, this article uses a MAP of control method is widely used, and the difference between the past, the MAP control method is that the method is more accurate after neural network algorithm to optimize control control method. Furthermore, this article established a the engine simulation calibration model, and the use of the simulation calibration substitute part of the real machine test initial MAP data. The introduction of artificial neural network forecasting method in the optimization of the initial MAP data. From the process point of view this method seems a little cumbersome, but using MATLAB neural network toolbox, making the design and training of the neural network are relatively simple process, more importantly, the neural network is able to use the data. And then consider the the engine strongly nonlinear factors, so from that point in terms of the traditional linear interpolation is certainly inaccurate. Neural network nonlinear mapping is precisely its advantage, so in theory, neural network forecasting method to be processed initial injector MAP data is more reliable Finally, this paper based on the MATLAB / GUIDE GUI development environment homemade open-loop control for the engine, closed-loop control and simulation calibration graphical user interface, the interface makes the running of the engine control system, data entry easy and intuitive. The interface by calling the controls, as well as the design of the control callback function, engine modeling and simulation system interactive interface design can be achieved. Fast simulation calibration of the control system and to obtain initial MAP.

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CLC: > Industrial Technology > Energy and Power Engineering > Internal combustion engine > Gasoline > Design, calculation
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