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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10059842/ https://www.ncbi.nlm.nih.gov/pubmed/36992021 http://dx.doi.org/10.3390/s23063310 |
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author | Liu, Jianze Liu, Jiang Li, Yang Wang, Guangzheng Yang, Fazhan |
author_facet | Liu, Jianze Liu, Jiang Li, Yang Wang, Guangzheng Yang, Fazhan |
author_sort | Liu, Jianze |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-10059842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100598422023-03-30 Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation Liu, Jianze Liu, Jiang Li, Yang Wang, Guangzheng Yang, Fazhan Sensors (Basel) Article 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. MDPI 2023-03-21 /pmc/articles/PMC10059842/ /pubmed/36992021 http://dx.doi.org/10.3390/s23063310 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Jianze Liu, Jiang Li, Yang Wang, Guangzheng Yang, Fazhan Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation |
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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10059842/ https://www.ncbi.nlm.nih.gov/pubmed/36992021 http://dx.doi.org/10.3390/s23063310 |
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