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Article

Road Roughness Estimation Based on the Vehicle Frequency Response Function

1
Department of Civil Engineering, Dalian Minzu University, Dalian 116600, China
2
Department of Civil Engineering, Dalian University of Technology, Dalian 116023, China
3
Department of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China
4
Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
5
China Merchants Roadway Information Technology (Chongqing) CO. LTD, Chongqing 400067, China
*
Author to whom correspondence should be addressed.
Actuators 2021, 10(5), 89; https://doi.org/10.3390/act10050089
Submission received: 25 February 2021 / Revised: 2 April 2021 / Accepted: 21 April 2021 / Published: 26 April 2021
(This article belongs to the Special Issue Vibration Control and Structure Health Monitoring)

Abstract

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.
Keywords: structural health monitoring; road roughness; vehicle response; frequency response function; Fourier transform structural health monitoring; road roughness; vehicle response; frequency response function; Fourier transform

Share and Cite

MDPI and ACS Style

Zhang, Q.; Hou, J.; Duan, Z.; Jankowski, Ł.; Hu, X. Road Roughness Estimation Based on the Vehicle Frequency Response Function. Actuators 2021, 10, 89. https://doi.org/10.3390/act10050089

AMA Style

Zhang Q, Hou J, Duan Z, Jankowski Ł, Hu X. Road Roughness Estimation Based on the Vehicle Frequency Response Function. Actuators. 2021; 10(5):89. https://doi.org/10.3390/act10050089

Chicago/Turabian Style

Zhang, Qingxia, Jilin Hou, Zhongdong Duan, Łukasz Jankowski, and Xiaoyang Hu. 2021. "Road Roughness Estimation Based on the Vehicle Frequency Response Function" Actuators 10, no. 5: 89. https://doi.org/10.3390/act10050089

APA Style

Zhang, Q., Hou, J., Duan, Z., Jankowski, Ł., & Hu, X. (2021). Road Roughness Estimation Based on the Vehicle Frequency Response Function. Actuators, 10(5), 89. https://doi.org/10.3390/act10050089

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