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

Yechen Qin, Chongfeng Wei, Xiaolin Tang, Nong Zhang, Mingming Dong, Chuan Hu

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)79-98
Number of pages20
JournalMechanical Systems and Signal Processing
Early online date21 Jul 2018
Publication statusPublished - 15 Jun 2019
Externally publishedYes

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