{"title":"The injection petrol control system about CMAC neural networks","authors":"Yaming Han, H. Tack","doi":"10.6109/JKIICE.2017.21.2.395","DOIUrl":null,"url":null,"abstract":"The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved. 키워드 : CMAC 신경회로망, 연료분사 제어, 산소제어, 공연비 Key word : CMAC neural network, automobile engine, injection petrol control, ideal mixing ratio Received 10 November 2016, Revised 19 December 2016, Accepted 04 January 2017 * Corresponding Author Han-Ho Tack(E-mail:fmtack@gntech.ac.kr, Tel:+82-55-751-3332) Department of Electronic Engineering, Gyeongnam National University of Science and Technology, Gyeongnam 52725, Korea Open Access http://doi.org/10.6109/jkiice.2017.21.2.395 print ISSN: 2234-4772 online ISSN: 2288-4165 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/li-censes/ by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright C The Korea Institute of Information and Communication Engineering. Journal of the Korea Institute of Information and Communication Engineering 한국정보통신학회논문지(J. Korea Inst. Inf. Commun. Eng.) Vol. 21, No. 2 : 395~400 Feb. 2017","PeriodicalId":136663,"journal":{"name":"The Journal of the Korean Institute of Information and Communication Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of the Korean Institute of Information and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6109/JKIICE.2017.21.2.395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved. 키워드 : CMAC 신경회로망, 연료분사 제어, 산소제어, 공연비 Key word : CMAC neural network, automobile engine, injection petrol control, ideal mixing ratio Received 10 November 2016, Revised 19 December 2016, Accepted 04 January 2017 * Corresponding Author Han-Ho Tack(E-mail:fmtack@gntech.ac.kr, Tel:+82-55-751-3332) Department of Electronic Engineering, Gyeongnam National University of Science and Technology, Gyeongnam 52725, Korea Open Access http://doi.org/10.6109/jkiice.2017.21.2.395 print ISSN: 2234-4772 online ISSN: 2288-4165 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/li-censes/ by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright C The Korea Institute of Information and Communication Engineering. Journal of the Korea Institute of Information and Communication Engineering 한국정보통신학회논문지(J. Korea Inst. Inf. Commun. Eng.) Vol. 21, No. 2 : 395~400 Feb. 2017