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Research On EFI Control Strategy For Single-cylinder Engine Of Motorcycle

Posted on:2015-07-23Degree:MasterType:Thesis
Country:ChinaCandidate:X Y TuFull Text:PDF
GTID:2272330431456118Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
Electronic control technology is an important technology to reduce the engineemissions and fuel consumption.But the most existing motorcycle engine still usecarburetor engine, it`s fuel economy and emission performances are difficult to meetthe needs of modern society. In this paper, the typical working conditions ofmotorcycle engine are studied, and the corresponding control strategy is developedvia simulation.Comparing the control effect of different controller, we candemonstrate the superiority of the proposed controller.This paper has dealt with the following respects:(1) establishing the enginemean value model, and improving the traditional EMVM based on the characteristicof the motorcycle engine: increasing intake wave module, delay module, enginetemperature model and the idle intake model, and then verifing the accuracy of themodel.(2) studing for the idle speed control strategy. The traditional PID controlalgorithm can not very well stable idle speed. In this paper,we use neural networkmodel predictive control algorithm to control the engine idle speed, and compare thecontrol effect of neural network with the conventional PID control.(3) studing for thefuel injection control strategy of steady condition.We put forward the overall controlscheme combining open loop with closed loop, and use a new controller to realizeclosed loop, making up for the shortcomings of traditional PID algorithm effectivelly.(4) studing for fuel injection control strategy of transient conditions.Aimed at thephenomena of the wet wall effect will cause the air fuel ratio deviation, through themethod of mathematical reasoning, we design the fuel compensator, and then comparethe control effect of existing and without fuel compensator.The simulation prove thatfuel compensator is effective.
Keywords/Search Tags:mean value model, neural network model predictive control, time delaycompensation, fuzzy PID, fuel compensation
PDF Full Text Request
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