Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle
Skid-steered wheeled vehicles can be applied in military, agricultural, and other fields because of their flexible layout structure and strong passability. The research and application of vehicles are developing towards the direction of “intelligent” and “unmanned”. As essential parts of unmanned ve...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/10/11/1015 |
| _version_ | 1797467492013047808 |
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| author | Yuzheng Zhu Xueyuan Li Xing Zhang Songhao Li Qi Liu Shihua Yuan |
| author_facet | Yuzheng Zhu Xueyuan Li Xing Zhang Songhao Li Qi Liu Shihua Yuan |
| author_sort | Yuzheng Zhu |
| collection | DOAJ |
| description | Skid-steered wheeled vehicles can be applied in military, agricultural, and other fields because of their flexible layout structure and strong passability. The research and application of vehicles are developing towards the direction of “intelligent” and “unmanned”. As essential parts of unmanned vehicles, the motion planning and control systems are increasingly demanding for model and road parameters. In this paper, an estimation method for tire and road parameters is proposed by combining offline and online identification. Firstly, a 3-DOF nonlinear dynamic model is established, and the interaction between tire and road is described by the Brush nonlinear tire model. Then, the horizontal and longitudinal stiffness of the tire is identified offline using the particle swarm optimization (PSO) algorithm with adaptive inertia weight. Referring to the Burckhardt adhesion coefficient formula, the extended forgetting factor recursive least-squares (EFRLS) method is applied to identify the road adhesion coefficient online. Finally, the validity of the proposed identification algorithm is verified by TruckSim simulation and real vehicle tests. Results show that the relative error of the proposed algorithm can be well controlled within 5%. |
| first_indexed | 2024-03-09T18:54:25Z |
| format | Article |
| id | doaj.art-06d54f4533de49d5a8be9cb6e8340e17 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-09T18:54:25Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-06d54f4533de49d5a8be9cb6e8340e172023-11-24T05:32:58ZengMDPI AGMachines2075-17022022-11-011011101510.3390/machines10111015Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground VehicleYuzheng Zhu0Xueyuan Li1Xing Zhang2Songhao Li3Qi Liu4Shihua Yuan5National Key Laboratory of Vehicular Transmission, Beijing Institute of Technology, Beijing 100081, ChinaNational Key Laboratory of Vehicular Transmission, Beijing Institute of Technology, Beijing 100081, ChinaNo. 208 Research Institute of China Ordnance Industies, Beijing 102202, ChinaNational Key Laboratory of Vehicular Transmission, Beijing Institute of Technology, Beijing 100081, ChinaNational Key Laboratory of Vehicular Transmission, Beijing Institute of Technology, Beijing 100081, ChinaNational Key Laboratory of Vehicular Transmission, Beijing Institute of Technology, Beijing 100081, ChinaSkid-steered wheeled vehicles can be applied in military, agricultural, and other fields because of their flexible layout structure and strong passability. The research and application of vehicles are developing towards the direction of “intelligent” and “unmanned”. As essential parts of unmanned vehicles, the motion planning and control systems are increasingly demanding for model and road parameters. In this paper, an estimation method for tire and road parameters is proposed by combining offline and online identification. Firstly, a 3-DOF nonlinear dynamic model is established, and the interaction between tire and road is described by the Brush nonlinear tire model. Then, the horizontal and longitudinal stiffness of the tire is identified offline using the particle swarm optimization (PSO) algorithm with adaptive inertia weight. Referring to the Burckhardt adhesion coefficient formula, the extended forgetting factor recursive least-squares (EFRLS) method is applied to identify the road adhesion coefficient online. Finally, the validity of the proposed identification algorithm is verified by TruckSim simulation and real vehicle tests. Results show that the relative error of the proposed algorithm can be well controlled within 5%.https://www.mdpi.com/2075-1702/10/11/1015skid-steered wheeled vehiclePSOEFRLStire parameters identificationroad adhesion coefficient |
| spellingShingle | Yuzheng Zhu Xueyuan Li Xing Zhang Songhao Li Qi Liu Shihua Yuan Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle Machines skid-steered wheeled vehicle PSO EFRLS tire parameters identification road adhesion coefficient |
| title | Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle |
| title_full | Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle |
| title_fullStr | Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle |
| title_full_unstemmed | Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle |
| title_short | Research on Tire–Road Parameters Estimation Algorithm for Skid-Steered Wheeled Unmanned Ground Vehicle |
| title_sort | research on tire road parameters estimation algorithm for skid steered wheeled unmanned ground vehicle |
| topic | skid-steered wheeled vehicle PSO EFRLS tire parameters identification road adhesion coefficient |
| url | https://www.mdpi.com/2075-1702/10/11/1015 |
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