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Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method

Vehicle dynamic parameters are of vital importance to establish feasible vehicle models which are used to provide active controls and automated driving control. However, most vehicle dynamics parameters are difficult to obtain directly. In this paper, a new method, which requires only conventional s...

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Detalles Bibliográficos
Autores principales: Li, Wenfei, Li, Huiyun, Xu, Kun, Huang, Zhejun, Li, Ke, Du, Haiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198488/
https://www.ncbi.nlm.nih.gov/pubmed/34073574
http://dx.doi.org/10.3390/s21113711
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author Li, Wenfei
Li, Huiyun
Xu, Kun
Huang, Zhejun
Li, Ke
Du, Haiping
author_facet Li, Wenfei
Li, Huiyun
Xu, Kun
Huang, Zhejun
Li, Ke
Du, Haiping
author_sort Li, Wenfei
collection PubMed
description Vehicle dynamic parameters are of vital importance to establish feasible vehicle models which are used to provide active controls and automated driving control. However, most vehicle dynamics parameters are difficult to obtain directly. In this paper, a new method, which requires only conventional sensors, is proposed to estimate vehicle dynamic parameters. The influence of vehicle dynamic parameters on vehicle dynamics often involves coupling. To solve the problem of coupling, a two-stage estimation method, consisting of multiple-models and the Unscented Kalman Filter, is proposed in this paper. During the first stage, the longitudinal vehicle dynamics model is used. Through vehicle acceleration/deceleration, this model can be used to estimate the distance between the vehicle centroid and vehicle front, the height of vehicle centroid and tire longitudinal stiffness. The estimated parameter can be used in the second stage. During the second stage, a single-track with roll dynamics vehicle model is adopted. By making vehicle continuous steering, this vehicle model can be used to estimate tire cornering stiffness, the vehicle moment of inertia around the yaw axis and the moment of inertia around the longitudinal axis. The simulation results show that the proposed method is effective and vehicle dynamic parameters can be well estimated.
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spelling pubmed-81984882021-06-14 Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method Li, Wenfei Li, Huiyun Xu, Kun Huang, Zhejun Li, Ke Du, Haiping Sensors (Basel) Article Vehicle dynamic parameters are of vital importance to establish feasible vehicle models which are used to provide active controls and automated driving control. However, most vehicle dynamics parameters are difficult to obtain directly. In this paper, a new method, which requires only conventional sensors, is proposed to estimate vehicle dynamic parameters. The influence of vehicle dynamic parameters on vehicle dynamics often involves coupling. To solve the problem of coupling, a two-stage estimation method, consisting of multiple-models and the Unscented Kalman Filter, is proposed in this paper. During the first stage, the longitudinal vehicle dynamics model is used. Through vehicle acceleration/deceleration, this model can be used to estimate the distance between the vehicle centroid and vehicle front, the height of vehicle centroid and tire longitudinal stiffness. The estimated parameter can be used in the second stage. During the second stage, a single-track with roll dynamics vehicle model is adopted. By making vehicle continuous steering, this vehicle model can be used to estimate tire cornering stiffness, the vehicle moment of inertia around the yaw axis and the moment of inertia around the longitudinal axis. The simulation results show that the proposed method is effective and vehicle dynamic parameters can be well estimated. MDPI 2021-05-26 /pmc/articles/PMC8198488/ /pubmed/34073574 http://dx.doi.org/10.3390/s21113711 Text en © 2021 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
Li, Wenfei
Li, Huiyun
Xu, Kun
Huang, Zhejun
Li, Ke
Du, Haiping
Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title_full Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title_fullStr Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title_full_unstemmed Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title_short Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
title_sort estimation of vehicle dynamic parameters based on the two-stage estimation method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198488/
https://www.ncbi.nlm.nih.gov/pubmed/34073574
http://dx.doi.org/10.3390/s21113711
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