Speed effect to a Quarter car ARX model based on system identification

This paper presents the effect of car speeds on a quarter car passive suspension system model dynamics. The model is identified using system identification technique, in which the input-output data are collected by running a test car on an artificial road surface with two different speeds i.e., 10 k...

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Main Authors: Hanafi, D., Suid, M. S., Ribuan, M. N., Omar, R., Than, M. N. M., Rahmat, M. F.
Format: Article
Language:English
Published: Insight Society 2017
Online Access:http://eprints.utm.my/id/eprint/80580/1/DirmanHanafi2017_SpeedEffecttoaQuarterCarARX.pdf
http://eprints.utm.my/id/eprint/80580/
http://dx.doi.org/10.18517/ijaseit.7.2.1500
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spelling my.utm.805802019-06-27T06:08:33Z http://eprints.utm.my/id/eprint/80580/ Speed effect to a Quarter car ARX model based on system identification Hanafi, D. Suid, M. S. Ribuan, M. N. Omar, R. Than, M. N. M. Rahmat, M. F. This paper presents the effect of car speeds on a quarter car passive suspension system model dynamics. The model is identified using system identification technique, in which the input-output data are collected by running a test car on an artificial road surface with two different speeds i.e., 10 km/h and 20 km/h. The quarter car passive suspension system dynamics is assumed to have an ARX model structure and identified using linear least-square estimation algorithm. The car vertical body acceleration, which is the output variable, is measured by installing an accelerometer sensor on the car body, above the suspension. On the other hand, the car shaft acceleration, which is the input variable, is measured by installing an accelerometer sensor at the lower arm of the car suspension. The best model for the 10 km/h car speed gives the output order (na) = 4, the input order (nb) = 2, delay (d) = 1, the best fit = 90.65%, and the Akaike's Final Prediction Error (FPE) = 5.315e-06. In contrast, the 20 km/h speed results in 4th output order (na), 1st the input order (nb), 1st delay (d), the best fit of 91.05%, and 7.503e-05 Akaike's FPE. These results show that the higher speed reduces the effect of the road surface to car dynamics, which is indicated by the order of the model. Insight Society 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/80580/1/DirmanHanafi2017_SpeedEffecttoaQuarterCarARX.pdf Hanafi, D. and Suid, M. S. and Ribuan, M. N. and Omar, R. and Than, M. N. M. and Rahmat, M. F. (2017) Speed effect to a Quarter car ARX model based on system identification. International Journal on Advanced Science, Engineering and Information Technology, 7 (2). pp. 468-474. ISSN 2088-5334 http://dx.doi.org/10.18517/ijaseit.7.2.1500 DOI:10.18517/ijaseit.7.2.1500
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
description This paper presents the effect of car speeds on a quarter car passive suspension system model dynamics. The model is identified using system identification technique, in which the input-output data are collected by running a test car on an artificial road surface with two different speeds i.e., 10 km/h and 20 km/h. The quarter car passive suspension system dynamics is assumed to have an ARX model structure and identified using linear least-square estimation algorithm. The car vertical body acceleration, which is the output variable, is measured by installing an accelerometer sensor on the car body, above the suspension. On the other hand, the car shaft acceleration, which is the input variable, is measured by installing an accelerometer sensor at the lower arm of the car suspension. The best model for the 10 km/h car speed gives the output order (na) = 4, the input order (nb) = 2, delay (d) = 1, the best fit = 90.65%, and the Akaike's Final Prediction Error (FPE) = 5.315e-06. In contrast, the 20 km/h speed results in 4th output order (na), 1st the input order (nb), 1st delay (d), the best fit of 91.05%, and 7.503e-05 Akaike's FPE. These results show that the higher speed reduces the effect of the road surface to car dynamics, which is indicated by the order of the model.
format Article
author Hanafi, D.
Suid, M. S.
Ribuan, M. N.
Omar, R.
Than, M. N. M.
Rahmat, M. F.
spellingShingle Hanafi, D.
Suid, M. S.
Ribuan, M. N.
Omar, R.
Than, M. N. M.
Rahmat, M. F.
Speed effect to a Quarter car ARX model based on system identification
author_facet Hanafi, D.
Suid, M. S.
Ribuan, M. N.
Omar, R.
Than, M. N. M.
Rahmat, M. F.
author_sort Hanafi, D.
title Speed effect to a Quarter car ARX model based on system identification
title_short Speed effect to a Quarter car ARX model based on system identification
title_full Speed effect to a Quarter car ARX model based on system identification
title_fullStr Speed effect to a Quarter car ARX model based on system identification
title_full_unstemmed Speed effect to a Quarter car ARX model based on system identification
title_sort speed effect to a quarter car arx model based on system identification
publisher Insight Society
publishDate 2017
url http://eprints.utm.my/id/eprint/80580/1/DirmanHanafi2017_SpeedEffecttoaQuarterCarARX.pdf
http://eprints.utm.my/id/eprint/80580/
http://dx.doi.org/10.18517/ijaseit.7.2.1500
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score 13.160551