Title: Research on on-board dynamic weighing algorithm based on two-degree-of-freedom 1/4 vehicle model

Authors: Hongxun Fu; Yu Zhang; Xianyue Gang; Huanbo Qiao; Yan Wang; Laiyun Ku

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

Abstract: The moving vehicle will be disturbed in many aspects, resulting in the dynamic weighing accuracy of the airborne weighing system being significantly lower than the static accuracy. In order to improve the dynamic weighing accuracy of the system, this paper designs a dynamic weighing algorithm based on wavelet threshold denoising and BP neural network. Firstly, a two-degree-of-freedom 1/4 vehicle model was built to obtain the vehicle dynamic distance data. Then, the wavelet threshold denoising algorithm was used to denoise the dynamic distance data. Finally, the BP neural network was constructed with the signal of vehicle speed, acceleration signal and denoised weight signal as the input layer to reduce the impact of the speed and acceleration on the weight signal. The results show that after the processing of dynamic weighing algorithm, the dynamic weighing error of vehicle is less than 2%, and the algorithm meets the accuracy requirements, and has high universality.

Keywords: on-board weighing system; two-degree-of-freedom 1/4 vehicle model; dynamic weighing algorithm; wavelet threshold denoising algorithm; BP neural network.

DOI: 10.1504/IJHVS.2021.121940

International Journal of Heavy Vehicle Systems, 2021 Vol.28 No.6, pp.792 - 807

Received: 13 Sep 2021
Accepted: 05 Oct 2021
Published online: 07 Apr 2022 *

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