Title: Research on construction method of the prediction model for semi-trailer on-board weighing system

Authors: Yu Zhang; Hongxun Fu; Qiang Zhao; Huanbo Qiao; Xianyue Gang

Addresses: School of Transportation and Vehicle Engineering, Shandong University of Technology, 12 Zhangzhou Road, Zhangdian, Zibo, 255049, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, 12 Zhangzhou Road, Zhangdian, Zibo, 255049, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, 12 Zhangzhou Road, Zhangdian, Zibo, 255049, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, 12 Zhangzhou Road, Zhangdian, Zibo, 255049, China ' School of Transportation and Vehicle Engineering, Shandong University of Technology, 12 Zhangzhou Road, Zhangdian, Zibo, 255049, China

Abstract: Aiming at the problems of overloading and inconvenient weighing of semi-trailer, this paper designed a semi-trailer on-board weighing system based on the strain measurement of the frame, and built the weighing prediction model of the system. The three-dimensional model of the semi-trailer frame was established, and the strain sensitive area of the frame was determined by using the finite element analysis method, and the suitable position was selected as the strain sensitive point. According to the load distribution of the semi-trailer frame, the strain and load of the traction pin and suspension components are fitted respectively, and the weighing prediction model of the system is established. Finally, by comparing the test load with the predicted load, it is found that the error of the predicted load is less than 1%, and the accuracy of the model meets the engineering requirements.

Keywords: semi-trailer; on-board weighing system; finite element; strain; prediction model.

DOI: 10.1504/IJHVS.2022.123240

International Journal of Heavy Vehicle Systems, 2022 Vol.29 No.1, pp.1 - 12

Received: 02 Apr 2021
Accepted: 19 Jun 2021

Published online: 06 Jun 2022 *

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