{"title":"基于参数估计的电动客车数学模型速度和横摆角速度响应优化","authors":"Mohammad Aditya Rafi Pratama, Aries Subiantoro","doi":"10.1109/AIMS52415.2021.9466080","DOIUrl":null,"url":null,"abstract":"The mathematical model of the vehicle is an important component of vehicle stability control research. Therefore, the right model is required to model an actual vehicle. In designing a vehicle model, the right parameter values are also needed to produce an optimal output response from the model. However, optimal response cannot be obtained when there is parameter value that are either unknown or cannot be measured directly. This paper proposed a parameter estimation approach using the Quasi–Newton and least squares methods to estimate the value of the unknown parameter. The output responses from the model with the estimated parameters will be compared with the output responses from the simulator used, and the level of accuracy and error of the estimation method will be analyzed. From the test results, it was found that the model with the estimated parameter values produces high accuracy of more than 85%. It is shown that the proposed estimation method can be used in estimating the parameters of a vehicle model and can produce an optimal output response.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Speed and Yaw Rate Response Optimization based on Parameter Estimation for Electrical Bus Mathematical Model\",\"authors\":\"Mohammad Aditya Rafi Pratama, Aries Subiantoro\",\"doi\":\"10.1109/AIMS52415.2021.9466080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The mathematical model of the vehicle is an important component of vehicle stability control research. Therefore, the right model is required to model an actual vehicle. In designing a vehicle model, the right parameter values are also needed to produce an optimal output response from the model. However, optimal response cannot be obtained when there is parameter value that are either unknown or cannot be measured directly. This paper proposed a parameter estimation approach using the Quasi–Newton and least squares methods to estimate the value of the unknown parameter. The output responses from the model with the estimated parameters will be compared with the output responses from the simulator used, and the level of accuracy and error of the estimation method will be analyzed. From the test results, it was found that the model with the estimated parameter values produces high accuracy of more than 85%. It is shown that the proposed estimation method can be used in estimating the parameters of a vehicle model and can produce an optimal output response.\",\"PeriodicalId\":299121,\"journal\":{\"name\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIMS52415.2021.9466080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIMS52415.2021.9466080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speed and Yaw Rate Response Optimization based on Parameter Estimation for Electrical Bus Mathematical Model
The mathematical model of the vehicle is an important component of vehicle stability control research. Therefore, the right model is required to model an actual vehicle. In designing a vehicle model, the right parameter values are also needed to produce an optimal output response from the model. However, optimal response cannot be obtained when there is parameter value that are either unknown or cannot be measured directly. This paper proposed a parameter estimation approach using the Quasi–Newton and least squares methods to estimate the value of the unknown parameter. The output responses from the model with the estimated parameters will be compared with the output responses from the simulator used, and the level of accuracy and error of the estimation method will be analyzed. From the test results, it was found that the model with the estimated parameter values produces high accuracy of more than 85%. It is shown that the proposed estimation method can be used in estimating the parameters of a vehicle model and can produce an optimal output response.