Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer
When the alternating current (AC) chassis dynamometer system measures the motion parameters of a test vehicle, it is subject to interference from measurement noise, leading to an increase in testing errors. An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is prop...
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MDPI AG
2025-04-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/4/239 |
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| _version_ | 1850179964251406336 |
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| author | Xiaorui Zhang Xingyuan Xu Hengliang Shi |
| author_facet | Xiaorui Zhang Xingyuan Xu Hengliang Shi |
| author_sort | Xiaorui Zhang |
| collection | DOAJ |
| description | When the alternating current (AC) chassis dynamometer system measures the motion parameters of a test vehicle, it is subject to interference from measurement noise, leading to an increase in testing errors. An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is proposed. This algorithm facilitates the optimal estimation of vehicle motion parameters without necessitating prior error statistics. The loading model of the measurement and control system is optimized, enabling the precise loading of the dynamometer. The test results indicate that the testing error of the optimized algorithm for the loading model decreases from 6.4% to 1.8%. This improvement establishes a foundation for achieving accurate control of the chassis dynamometer and minimizing testing errors. |
| format | Article |
| id | doaj-art-25f68f04f70041cc9ab046577e9ceafd |
| institution | OA Journals |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-25f68f04f70041cc9ab046577e9ceafd2025-08-20T02:18:21ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-04-0116423910.3390/wevj16040239Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis DynamometerXiaorui Zhang0Xingyuan Xu1Hengliang Shi2School of Automobile and Rail Transit, Luoyang Polytechnic, Luoyang 471000, ChinaSchool of Automobile and Rail Transit, Luoyang Polytechnic, Luoyang 471000, ChinaSchool of Automobile and Rail Transit, Luoyang Polytechnic, Luoyang 471000, ChinaWhen the alternating current (AC) chassis dynamometer system measures the motion parameters of a test vehicle, it is subject to interference from measurement noise, leading to an increase in testing errors. An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is proposed. This algorithm facilitates the optimal estimation of vehicle motion parameters without necessitating prior error statistics. The loading model of the measurement and control system is optimized, enabling the precise loading of the dynamometer. The test results indicate that the testing error of the optimized algorithm for the loading model decreases from 6.4% to 1.8%. This improvement establishes a foundation for achieving accurate control of the chassis dynamometer and minimizing testing errors.https://www.mdpi.com/2032-6653/16/4/239vehiclechassis dynamometerestimation algorithmmotion parametersadaptive Kalman filteringinnovation covariance |
| spellingShingle | Xiaorui Zhang Xingyuan Xu Hengliang Shi Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer World Electric Vehicle Journal vehicle chassis dynamometer estimation algorithm motion parameters adaptive Kalman filtering innovation covariance |
| title | Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer |
| title_full | Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer |
| title_fullStr | Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer |
| title_full_unstemmed | Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer |
| title_short | Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer |
| title_sort | estimation algorithm for vehicle motion parameters based on innovation covariance in ac chassis dynamometer |
| topic | vehicle chassis dynamometer estimation algorithm motion parameters adaptive Kalman filtering innovation covariance |
| url | https://www.mdpi.com/2032-6653/16/4/239 |
| work_keys_str_mv | AT xiaoruizhang estimationalgorithmforvehiclemotionparametersbasedoninnovationcovarianceinacchassisdynamometer AT xingyuanxu estimationalgorithmforvehiclemotionparametersbasedoninnovationcovarianceinacchassisdynamometer AT hengliangshi estimationalgorithmforvehiclemotionparametersbasedoninnovationcovarianceinacchassisdynamometer |