Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation
In this paper, the least squares method is used to determine the vertical height of the road space domain. Based on the road estimation method, the active suspension control mode switching model is constructed, and the dynamic characteristics of the vehicle in comfort, safety, and integrated modes a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/6/3310 |
| _version_ | 1797609015582130176 |
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| author | Jianze Liu Jiang Liu Yang Li Guangzheng Wang Fazhan Yang |
| author_facet | Jianze Liu Jiang Liu Yang Li Guangzheng Wang Fazhan Yang |
| author_sort | Jianze Liu |
| collection | DOAJ |
| description | In this paper, the least squares method is used to determine the vertical height of the road space domain. Based on the road estimation method, the active suspension control mode switching model is constructed, and the dynamic characteristics of the vehicle in comfort, safety, and integrated modes are analyzed. The vibration signal is collected by the sensor, and the parameters such as vehicle driving conditions are solved for in reverse. A control strategy for multiple mode switching under different road surfaces and speeds is constructed. At the same time, the particle swarm optimization algorithm (PSO) is used to optimize the weight coefficients of LQR control under different modes, and the dynamic performance of vehicle driving is comprehensively analyzed. The test and simulation results show that the road estimation results under different speeds in the same road section are very close to the results obtained by the detection ruler method, and the overall error is less than 2%. Compared with the active suspension controlled by passive and traditional LQR, the multi-mode switching strategy can achieve a better balance between driving comfort and handling safety and stability, and also improve the driving experience more intelligently and comprehensively. |
| first_indexed | 2024-03-11T05:55:39Z |
| format | Article |
| id | doaj.art-bcf2fe6bf8ff40f59849067149a5cde3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:55:39Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-bcf2fe6bf8ff40f59849067149a5cde32023-11-17T13:48:54ZengMDPI AGSensors1424-82202023-03-01236331010.3390/s23063310Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road EstimationJianze Liu0Jiang Liu1Yang Li2Guangzheng Wang3Fazhan Yang4Institute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, ChinaInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, ChinaInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, ChinaInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, ChinaInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, ChinaIn this paper, the least squares method is used to determine the vertical height of the road space domain. Based on the road estimation method, the active suspension control mode switching model is constructed, and the dynamic characteristics of the vehicle in comfort, safety, and integrated modes are analyzed. The vibration signal is collected by the sensor, and the parameters such as vehicle driving conditions are solved for in reverse. A control strategy for multiple mode switching under different road surfaces and speeds is constructed. At the same time, the particle swarm optimization algorithm (PSO) is used to optimize the weight coefficients of LQR control under different modes, and the dynamic performance of vehicle driving is comprehensively analyzed. The test and simulation results show that the road estimation results under different speeds in the same road section are very close to the results obtained by the detection ruler method, and the overall error is less than 2%. Compared with the active suspension controlled by passive and traditional LQR, the multi-mode switching strategy can achieve a better balance between driving comfort and handling safety and stability, and also improve the driving experience more intelligently and comprehensively.https://www.mdpi.com/1424-8220/23/6/3310vehicle engineeringroad estimationmode switchingPSO_LQG controlvibration test |
| spellingShingle | Jianze Liu Jiang Liu Yang Li Guangzheng Wang Fazhan Yang Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation Sensors vehicle engineering road estimation mode switching PSO_LQG control vibration test |
| title | Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
| title_full | Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
| title_fullStr | Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
| title_full_unstemmed | Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
| title_short | Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
| title_sort | study on multi mode switching control strategy of active suspension based on road estimation |
| topic | vehicle engineering road estimation mode switching PSO_LQG control vibration test |
| url | https://www.mdpi.com/1424-8220/23/6/3310 |
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