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Volume 14
Issue 11
10.3390/su14116698
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Article

Prediction of Clearance Vibration for Intelligent Vehicles Motion Control

by
Yunhe Zhang
1,
Faping Zhang
1,*,
Wuhong Wang
1,
Fanjun Meng
2,
Dashun Zhang
3 and
Haixun Wang
3
1
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
2
School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130013, China
3
The 55 Research Institute of China North Industries Group Corporation Limited, Changchun 130012, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(11), 6698; https://doi.org/10.3390/su14116698
Submission received: 20 April 2022 / Revised: 27 May 2022 / Accepted: 27 May 2022 / Published: 30 May 2022
(This article belongs to the Special Issue Smart Transportation and Intelligent and Connected Driving)
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Abstract

Motion control analysis should consider the system’s uncertainty to ensure the intelligent vehicle’s autonomy. The clearance structure of the transmission shaft is modeled as a cantilever beam with double clearance to predict the clearance vibration for mitigating the nonlinearity. Based on the Kelvin–Voigt collision model, a clearance model was developed using time-varying parameters identified by the wavelet transform. Comparing the frequency response functions (FRF) of the initial model with constant parameters and the updated model with time-varying parameters, the experimental results from the updated model indicate that the modal assurance criterion (MAC) is increased by 42.92%, 31.08%, 38.97%, and 50.74% in the first-four order. Cross-signature assurance criteria (CSAC) and cross-signature scale factor (CSF) have been increased by 6.55% and 12.37%. The control method based on the clearance model has been verified. In the case of 120 km/h, compared with model-predictive control (MPC) and sliding mode control (SMC), the peak of the lateral position error was reduced by 35.7% and 14.3%, and the peak of the heading error was reduced by 50% and 15.6%.
Keywords: intelligent vehicle; motion control; clearance nonlinearity; parameter identification; frequency response function intelligent vehicle; motion control; clearance nonlinearity; parameter identification; frequency response function

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MDPI and ACS Style

Zhang, Y.; Zhang, F.; Wang, W.; Meng, F.; Zhang, D.; Wang, H. Prediction of Clearance Vibration for Intelligent Vehicles Motion Control. Sustainability 2022, 14, 6698. https://doi.org/10.3390/su14116698

AMA Style

Zhang Y, Zhang F, Wang W, Meng F, Zhang D, Wang H. Prediction of Clearance Vibration for Intelligent Vehicles Motion Control. Sustainability. 2022; 14(11):6698. https://doi.org/10.3390/su14116698

Chicago/Turabian Style

Zhang, Yunhe, Faping Zhang, Wuhong Wang, Fanjun Meng, Dashun Zhang, and Haixun Wang. 2022. "Prediction of Clearance Vibration for Intelligent Vehicles Motion Control" Sustainability 14, no. 11: 6698. https://doi.org/10.3390/su14116698

APA Style

Zhang, Y., Zhang, F., Wang, W., Meng, F., Zhang, D., & Wang, H. (2022). Prediction of Clearance Vibration for Intelligent Vehicles Motion Control. Sustainability, 14(11), 6698. https://doi.org/10.3390/su14116698

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