{"title":"Realization and simulation of full hardware vehicle speed estimator on FPGA","authors":"Faner Meng, Xiao-hua Xie, Ke-tian Cai, Gui-jun Qin","doi":"10.1109/CYBER.2013.6705446","DOIUrl":null,"url":null,"abstract":"When a vehicle is running, its measured speed can reflect the operation status of the vehicle sufficiently. In practice, therefore, it is very important to estimate the speed. In this paper, FPGA is used to realize full hardware vehicle speed estimator. The longitudinal velocity of the vehicle can be achieved by a Kalman estimator, which is described by Verilog language. The output data from the eight degrees of freedom vehicle model are regarded as input data of the function simulation in ModelSim. The single precision floating-point binary number is adopted to expand the data range and improve data accuracy. The curves related to the actual speed and estimated speed are analyzed in Matlab, and various performance indicators of the estimator can be checked.","PeriodicalId":146993,"journal":{"name":"2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBER.2013.6705446","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
When a vehicle is running, its measured speed can reflect the operation status of the vehicle sufficiently. In practice, therefore, it is very important to estimate the speed. In this paper, FPGA is used to realize full hardware vehicle speed estimator. The longitudinal velocity of the vehicle can be achieved by a Kalman estimator, which is described by Verilog language. The output data from the eight degrees of freedom vehicle model are regarded as input data of the function simulation in ModelSim. The single precision floating-point binary number is adopted to expand the data range and improve data accuracy. The curves related to the actual speed and estimated speed are analyzed in Matlab, and various performance indicators of the estimator can be checked.