{"title":"基于多传感器的电动汽车ESP关键状态参数估计研究","authors":"Wang Cheng, Song Chuan-xue, L. Jianhua","doi":"10.1109/IMCCC.2015.13","DOIUrl":null,"url":null,"abstract":"In order to enhance the estimation accuracy and improve the response time of the estimator for the key state parameters estimation of electric vehicle ESP system. A vehicle state estimator was built based on multi-sensor and the improved estimation algorithm. The estimator was used to estimate vehicle speed. A speed estimation model was introduced. The model was made up of three degree of freedom vehicle model, tire force calculation model and road adhesion coefficient calculation model. The mathematical equations of those models were introduced. The improved estimation algorithm was based on two times sigma points sampling of improved UKF. The estimation process was introduced including initialization, forecast and update. The state space equations of electric vehicle were established in accordance with the requirements of speed estimation. A simulation model was built based on Carsim and Simulink software. Combined simulation experiments were made including the speed of 55 kilometers and 95 kilometers per hour simulation experiment. The experimental results shown that the estimated speed could follow the actual speed timely and accurately. The improved estimation method was fit for ESP of electric vehicle.","PeriodicalId":438549,"journal":{"name":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on Key State Parameters Estimation of Electric Vehicle ESP Based on Multi-sensor\",\"authors\":\"Wang Cheng, Song Chuan-xue, L. Jianhua\",\"doi\":\"10.1109/IMCCC.2015.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to enhance the estimation accuracy and improve the response time of the estimator for the key state parameters estimation of electric vehicle ESP system. A vehicle state estimator was built based on multi-sensor and the improved estimation algorithm. The estimator was used to estimate vehicle speed. A speed estimation model was introduced. The model was made up of three degree of freedom vehicle model, tire force calculation model and road adhesion coefficient calculation model. The mathematical equations of those models were introduced. The improved estimation algorithm was based on two times sigma points sampling of improved UKF. The estimation process was introduced including initialization, forecast and update. The state space equations of electric vehicle were established in accordance with the requirements of speed estimation. A simulation model was built based on Carsim and Simulink software. Combined simulation experiments were made including the speed of 55 kilometers and 95 kilometers per hour simulation experiment. The experimental results shown that the estimated speed could follow the actual speed timely and accurately. The improved estimation method was fit for ESP of electric vehicle.\",\"PeriodicalId\":438549,\"journal\":{\"name\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCCC.2015.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCCC.2015.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Key State Parameters Estimation of Electric Vehicle ESP Based on Multi-sensor
In order to enhance the estimation accuracy and improve the response time of the estimator for the key state parameters estimation of electric vehicle ESP system. A vehicle state estimator was built based on multi-sensor and the improved estimation algorithm. The estimator was used to estimate vehicle speed. A speed estimation model was introduced. The model was made up of three degree of freedom vehicle model, tire force calculation model and road adhesion coefficient calculation model. The mathematical equations of those models were introduced. The improved estimation algorithm was based on two times sigma points sampling of improved UKF. The estimation process was introduced including initialization, forecast and update. The state space equations of electric vehicle were established in accordance with the requirements of speed estimation. A simulation model was built based on Carsim and Simulink software. Combined simulation experiments were made including the speed of 55 kilometers and 95 kilometers per hour simulation experiment. The experimental results shown that the estimated speed could follow the actual speed timely and accurately. The improved estimation method was fit for ESP of electric vehicle.