{"title":"一种基于速度识别的车辆载荷识别系统","authors":"Su Wenchao","doi":"10.1109/ICUEMS50872.2020.00093","DOIUrl":null,"url":null,"abstract":"This paper introduces a vehicle speed recognition system and a fuzzy inference system based on driving conditions. This system can use the vehicle dynamics principle to non-contactly measure vehicle load. And based on the vehicle speed-time series, the optimal estimation method is adopted, and the vehicle weight is estimated according to some unusual operating points or operating intervals. The analysis results show that the system has certain reliability and convergence for vehicle load measurement, and has definite practical value.","PeriodicalId":285594,"journal":{"name":"2020 International Conference on Urban Engineering and Management Science (ICUEMS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A vehicle load identification system based on speed identification\",\"authors\":\"Su Wenchao\",\"doi\":\"10.1109/ICUEMS50872.2020.00093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a vehicle speed recognition system and a fuzzy inference system based on driving conditions. This system can use the vehicle dynamics principle to non-contactly measure vehicle load. And based on the vehicle speed-time series, the optimal estimation method is adopted, and the vehicle weight is estimated according to some unusual operating points or operating intervals. The analysis results show that the system has certain reliability and convergence for vehicle load measurement, and has definite practical value.\",\"PeriodicalId\":285594,\"journal\":{\"name\":\"2020 International Conference on Urban Engineering and Management Science (ICUEMS)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Urban Engineering and Management Science (ICUEMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUEMS50872.2020.00093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Urban Engineering and Management Science (ICUEMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUEMS50872.2020.00093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A vehicle load identification system based on speed identification
This paper introduces a vehicle speed recognition system and a fuzzy inference system based on driving conditions. This system can use the vehicle dynamics principle to non-contactly measure vehicle load. And based on the vehicle speed-time series, the optimal estimation method is adopted, and the vehicle weight is estimated according to some unusual operating points or operating intervals. The analysis results show that the system has certain reliability and convergence for vehicle load measurement, and has definite practical value.