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Research on control strategy of vehicle stability based on dynamic stable region regression analysis

The intervention time of stability control system is determined by stability judgment, which is the basis of vehicle stability control. According to the different working conditions of the vehicle, we construct the phase plane of the vehicle's sideslip angle and sideslip angular velocity, and e...

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Autores principales: Liu, Zhaoyong, Li, Yihang, Li, Weijun, Li, Zefan, Zhang, Haosen, Tan, Xiaoqiang, Wu, Guangqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042292/
https://www.ncbi.nlm.nih.gov/pubmed/36994073
http://dx.doi.org/10.3389/fnbot.2023.1149201
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author Liu, Zhaoyong
Li, Yihang
Li, Weijun
Li, Zefan
Zhang, Haosen
Tan, Xiaoqiang
Wu, Guangqiang
author_facet Liu, Zhaoyong
Li, Yihang
Li, Weijun
Li, Zefan
Zhang, Haosen
Tan, Xiaoqiang
Wu, Guangqiang
author_sort Liu, Zhaoyong
collection PubMed
description The intervention time of stability control system is determined by stability judgment, which is the basis of vehicle stability control. According to the different working conditions of the vehicle, we construct the phase plane of the vehicle's sideslip angle and sideslip angular velocity, and establish the sample dataset of the stable region of the different phase planes. To reduce the complexity of phase plane stable region division and avoid large amount of data, we established the support vector regression (SVR) model, and realized the automatic regression of dynamic stable region. The testing of the test set shows that the model established in this paper has strong generalization ability. We designed a direct yaw-moment control (DYC) stability controller based on linear time-varying model predictive control (LTV-MPC). The influence of key factors such as centroid position and road adhesion coefficient on the stable region is analyzed through phase diagram. The effectiveness of the stability judgment and control algorithm is verified by simulation tests.
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spelling pubmed-100422922023-03-28 Research on control strategy of vehicle stability based on dynamic stable region regression analysis Liu, Zhaoyong Li, Yihang Li, Weijun Li, Zefan Zhang, Haosen Tan, Xiaoqiang Wu, Guangqiang Front Neurorobot Neuroscience The intervention time of stability control system is determined by stability judgment, which is the basis of vehicle stability control. According to the different working conditions of the vehicle, we construct the phase plane of the vehicle's sideslip angle and sideslip angular velocity, and establish the sample dataset of the stable region of the different phase planes. To reduce the complexity of phase plane stable region division and avoid large amount of data, we established the support vector regression (SVR) model, and realized the automatic regression of dynamic stable region. The testing of the test set shows that the model established in this paper has strong generalization ability. We designed a direct yaw-moment control (DYC) stability controller based on linear time-varying model predictive control (LTV-MPC). The influence of key factors such as centroid position and road adhesion coefficient on the stable region is analyzed through phase diagram. The effectiveness of the stability judgment and control algorithm is verified by simulation tests. Frontiers Media S.A. 2023-03-13 /pmc/articles/PMC10042292/ /pubmed/36994073 http://dx.doi.org/10.3389/fnbot.2023.1149201 Text en Copyright © 2023 Liu, Li, Li, Li, Zhang, Tan and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Liu, Zhaoyong
Li, Yihang
Li, Weijun
Li, Zefan
Zhang, Haosen
Tan, Xiaoqiang
Wu, Guangqiang
Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title_full Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title_fullStr Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title_full_unstemmed Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title_short Research on control strategy of vehicle stability based on dynamic stable region regression analysis
title_sort research on control strategy of vehicle stability based on dynamic stable region regression analysis
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042292/
https://www.ncbi.nlm.nih.gov/pubmed/36994073
http://dx.doi.org/10.3389/fnbot.2023.1149201
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