Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

Yechen Qin; Mingming Dong; Reza Langari; Liang Gu; Jifu Guan

doi:10.1155/2015/636739

Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

Yechen Qin, Mingming Dong, Reza Langari, Liang Gu^*, Jifu Guan

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

50 Citations (Scopus)

Abstract

A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem) and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II). A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System) and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.

Original language	English
Article number	636739
Journal	Shock and Vibration
Volume	2015
DOIs	https://doi.org/10.1155/2015/636739
Publication status	Published - 2015

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title = "Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation",

abstract = "A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem) and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II). A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System) and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.",

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T1 - Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

AU - Qin, Yechen

AU - Dong, Mingming

AU - Langari, Reza

AU - Gu, Liang

AU - Guan, Jifu

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AB - A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem) and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II). A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System) and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.

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Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

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