Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables
This paper presents an extended Kalman filtering (EKF) algorithm for estimating immeasurable state variables of a vehicle stability control system. Initially, the steering angle and vertical forces on the tires were considered inputs of the estimator. The measured process outputs were the sensor sig...
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| Format: | Article |
| Language: | English |
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Ton Duc Thang University
2017-05-01
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| Series: | Journal of Advanced Engineering and Computation |
| Online Access: | http://jaec.vn/index.php/JAEC/article/view/45 |
| _version_ | 1818032803101540352 |
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| author | Tuan Le Anh |
| author_facet | Tuan Le Anh |
| author_sort | Tuan Le Anh |
| collection | DOAJ |
| description | This paper presents an extended Kalman filtering (EKF) algorithm for estimating immeasurable state variables of a vehicle stability control system. Initially, the steering angle and vertical forces on the tires were considered inputs of the estimator. The measured process outputs were the sensor signals egarding longitudinal and lateral accelerations, steering angle, yaw rate, and wheel speed. Subsequently, by using Euler discretization for a seven-degree-of-freedom nonlinear vehicle model, difficult-to-measure state variables such as lateral velocity, vehicle side-slip angle, and lateral tire forces were identified separately by using the EKF algorithm. The estimation results of the proposed control system evidenced high performance.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| first_indexed | 2024-12-10T06:13:10Z |
| format | Article |
| id | doaj.art-093b0d15dde84762b95abc50d3c5a868 |
| institution | Directory Open Access Journal |
| issn | 1859-2244 2588-123X |
| language | English |
| last_indexed | 2024-12-10T06:13:10Z |
| publishDate | 2017-05-01 |
| publisher | Ton Duc Thang University |
| record_format | Article |
| series | Journal of Advanced Engineering and Computation |
| spelling | doaj.art-093b0d15dde84762b95abc50d3c5a8682022-12-22T01:59:30ZengTon Duc Thang UniversityJournal of Advanced Engineering and Computation1859-22442588-123X2017-05-0111182810.25073/jaec.201711.4518Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State VariablesTuan Le Anh0Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, VietnamThis paper presents an extended Kalman filtering (EKF) algorithm for estimating immeasurable state variables of a vehicle stability control system. Initially, the steering angle and vertical forces on the tires were considered inputs of the estimator. The measured process outputs were the sensor signals egarding longitudinal and lateral accelerations, steering angle, yaw rate, and wheel speed. Subsequently, by using Euler discretization for a seven-degree-of-freedom nonlinear vehicle model, difficult-to-measure state variables such as lateral velocity, vehicle side-slip angle, and lateral tire forces were identified separately by using the EKF algorithm. The estimation results of the proposed control system evidenced high performance. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.http://jaec.vn/index.php/JAEC/article/view/45 |
| spellingShingle | Tuan Le Anh Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables Journal of Advanced Engineering and Computation |
| title | Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables |
| title_full | Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables |
| title_fullStr | Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables |
| title_full_unstemmed | Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables |
| title_short | Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables |
| title_sort | application of extended kalman filtering for estimating immeasurable vehicle state variables |
| url | http://jaec.vn/index.php/JAEC/article/view/45 |
| work_keys_str_mv | AT tuanleanh applicationofextendedkalmanfilteringforestimatingimmeasurablevehiclestatevariables |