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Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions
This paper presents an innovative electronically controlled suspension system installed on a real car and used as a test bench. The proposed setup relies on a sensor network that acquires a large real-time dataset collecting the car vibrations and the car trim and, through a new controller based on...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679211/ https://www.ncbi.nlm.nih.gov/pubmed/31336758 http://dx.doi.org/10.3390/s19143062 |
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author | Pepe, Gianluca Roveri, Nicola Carcaterra, Antonio |
author_facet | Pepe, Gianluca Roveri, Nicola Carcaterra, Antonio |
author_sort | Pepe, Gianluca |
collection | PubMed |
description | This paper presents an innovative electronically controlled suspension system installed on a real car and used as a test bench. The proposed setup relies on a sensor network that acquires a large real-time dataset collecting the car vibrations and the car trim and, through a new controller based on a recently proposed theory developed by the authors, makes use of adjustable semi-active magneto-rheological dampers. A BMW series 1 is equipped with such an integrated sensors-controller-actuators device and an extensive test campaign, in real driving conditions, is carried out to evaluate its performance. Thanks to its strategy, the new plant enhances, at once, both comfort and drivability of the car, as field experiments show. A benchmark analysis is performed, comparing the performance of the new control system with the ones of traditional semi-active suspensions, such as skyhook devices: the comparison shows very good results for the proposed solution. |
format | Online Article Text |
id | pubmed-6679211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66792112019-08-19 Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions Pepe, Gianluca Roveri, Nicola Carcaterra, Antonio Sensors (Basel) Article This paper presents an innovative electronically controlled suspension system installed on a real car and used as a test bench. The proposed setup relies on a sensor network that acquires a large real-time dataset collecting the car vibrations and the car trim and, through a new controller based on a recently proposed theory developed by the authors, makes use of adjustable semi-active magneto-rheological dampers. A BMW series 1 is equipped with such an integrated sensors-controller-actuators device and an extensive test campaign, in real driving conditions, is carried out to evaluate its performance. Thanks to its strategy, the new plant enhances, at once, both comfort and drivability of the car, as field experiments show. A benchmark analysis is performed, comparing the performance of the new control system with the ones of traditional semi-active suspensions, such as skyhook devices: the comparison shows very good results for the proposed solution. MDPI 2019-07-11 /pmc/articles/PMC6679211/ /pubmed/31336758 http://dx.doi.org/10.3390/s19143062 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pepe, Gianluca Roveri, Nicola Carcaterra, Antonio Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title | Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title_full | Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title_fullStr | Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title_full_unstemmed | Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title_short | Experimenting Sensors Network for Innovative Optimal Control of Car Suspensions |
title_sort | experimenting sensors network for innovative optimal control of car suspensions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679211/ https://www.ncbi.nlm.nih.gov/pubmed/31336758 http://dx.doi.org/10.3390/s19143062 |
work_keys_str_mv | AT pepegianluca experimentingsensorsnetworkforinnovativeoptimalcontrolofcarsuspensions AT roverinicola experimentingsensorsnetworkforinnovativeoptimalcontrolofcarsuspensions AT carcaterraantonio experimentingsensorsnetworkforinnovativeoptimalcontrolofcarsuspensions |