{"title":"Electric vehicle braking by fuzzy logic control","authors":"J. Paterson, M. Ramsay","doi":"10.1109/IAS.1993.299173","DOIUrl":null,"url":null,"abstract":"It is shown that, by exploiting the inherent tolerances in the braking system, a fuzzy controller can be used to achieve a more comfortable ride for the electric vehicle operator. Tolerances in energy recovery were exploited to gain a more acceptable performance. The fuzzy controller model reduces the velocity error but does not eliminate it completely. The magnitude of the errors has been reduced and separated to the two conditions where only one of the models is operating and the other either has not initiated deceleration or has turned off before the controller expected. These errors are due to the time variables of temperature, brake pad wear, brake pad temperature, and the mechanical frictions in the system. By using the tolerances available in both the energy recovery system and the operating conditions, smoother operation of the vehicle is possible.<<ETX>>","PeriodicalId":345027,"journal":{"name":"Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting","volume":" 14","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.1993.299173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37
Abstract
It is shown that, by exploiting the inherent tolerances in the braking system, a fuzzy controller can be used to achieve a more comfortable ride for the electric vehicle operator. Tolerances in energy recovery were exploited to gain a more acceptable performance. The fuzzy controller model reduces the velocity error but does not eliminate it completely. The magnitude of the errors has been reduced and separated to the two conditions where only one of the models is operating and the other either has not initiated deceleration or has turned off before the controller expected. These errors are due to the time variables of temperature, brake pad wear, brake pad temperature, and the mechanical frictions in the system. By using the tolerances available in both the energy recovery system and the operating conditions, smoother operation of the vehicle is possible.<>
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