A novel nonlinear road profile classification approach for controllable suspension system: Simulation and experimental validation

Qin, Y; Wei, C; Tang, X; Zhang, N; Dong, M; Hu, C

A novel nonlinear road profile classification approach for controllable suspension system: Simulation and experimental validation

Qin, Y Wei, C Tang, X Zhang, N

Dong, M Hu, C

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Publication Type:: Journal Article
Citation:: Mechanical Systems and Signal Processing, 2019, 125 pp. 79 - 98
Issue Date:: 2019-06-15

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Field	Value	Language
dc.contributor.author	Qin, Y	en_US
dc.contributor.author	Wei, C	en_US
dc.contributor.author	Tang, X	en_US
dc.contributor.author	Zhang, N https://orcid.org/0000-0001-6408-0044	en_US
dc.contributor.author	Dong, M	en_US
dc.contributor.author	Hu, C	en_US
dc.date.issued	2019-06-15	en_US
dc.identifier.citation	Mechanical Systems and Signal Processing, 2019, 125 pp. 79 - 98	en_US
dc.identifier.issn	0888-3270	en_US
dc.identifier.uri	http://hdl.handle.net/10453/134799
dc.description.abstract	© 2018 Elsevier Ltd Driven by the increasing requirement for road conditions in the field of the controllable suspension system, this paper presents a novel nonlinear road-excitation classification procedure for arbitrary suspension control strategy. The proposed procedure includes four steps: the definition of controller parameters, selection of insensitive frequency ranges, calculation of superior features, and generation of the classifier. To better illustrate the proposed procedure, the clipped optimal control strategy is taken as an example in the simulation part. Simulation results reveal that the proposed method can accurately estimate road excitation level for various controller parameters, vehicle speeds, and vehicle models. Three contributions have been made in this paper: (1) A road classification procedure that can be used for road adaptive suspension control with any control algorithm is developed; (2) In order to improve classification accuracy, the concept of insensitive index which is based on the time-frequency analysis is proposed; (3) Experimental validation with a quarter vehicle test rig is performed, which has verified the effectiveness of the proposed method for the adaptive controllable suspension system.	en_US
dc.relation.ispartof	Mechanical Systems and Signal Processing	en_US
dc.relation.isbasedon	10.1016/j.ymssp.2018.07.015	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Acoustics	en_US
dc.title	A novel nonlinear road profile classification approach for controllable suspension system: Simulation and experimental validation	en_US
dc.type	Journal Article
utslib.citation.volume	125	en_US
utslib.for	0905 Civil Engineering	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0915 Interdisciplinary Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	125	en_US

Abstract:

© 2018 Elsevier Ltd Driven by the increasing requirement for road conditions in the field of the controllable suspension system, this paper presents a novel nonlinear road-excitation classification procedure for arbitrary suspension control strategy. The proposed procedure includes four steps: the definition of controller parameters, selection of insensitive frequency ranges, calculation of superior features, and generation of the classifier. To better illustrate the proposed procedure, the clipped optimal control strategy is taken as an example in the simulation part. Simulation results reveal that the proposed method can accurately estimate road excitation level for various controller parameters, vehicle speeds, and vehicle models. Three contributions have been made in this paper: (1) A road classification procedure that can be used for road adaptive suspension control with any control algorithm is developed; (2) In order to improve classification accuracy, the concept of insensitive index which is based on the time-frequency analysis is proposed; (3) Experimental validation with a quarter vehicle test rig is performed, which has verified the effectiveness of the proposed method for the adaptive controllable suspension system.

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http://hdl.handle.net/10453/134799