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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Zhao, Xuana; * | Wang, Shua | Yu, Mana; c | Yu, Qianga | Zhou, Chenyua; b
Affiliations: [a] School of Automobile, Chang’an University, Xi’an, China | [b] Department of Mechanical Engineering, University of Maryland, College Park, MD, USA | [c] Xi’an Auto Repair Industry Management Department, Xi’an, China
Correspondence: [*] Corresponding author. Xuan Zhao, School of Automobile, Chang’an University, Xi’an 710064, China. E-mail: [email protected].
Abstract: Speed bump set before truck scale is to prevent the error of weighing measurement caused by truck driver non-standard operation through the weighing platform. However, the vehicle vibration produced by the speed bump will affect the weighing result if the speed bump is closer to truck scale, and can’t play a role in restricting driver’s operation if the speed bump is farther to truck scale. This paper researches the reasonable position of speed bump based on triaxial truck vibration characteristics. Simulation model of vibration in the process of triaxial truck passing the speed bump is built based on the speed hump model and dynamics model of 5DOF 1/2 triaxial truck. Then vehicle vibration characteristics are researched at the speed of 1.8 km/h, 3.6 km/h, 5.4 km/h, 7.0 km/h, and obtains the vibration decay time with different speed, which determine the minimum distance between speed bump and truck scale. The accuracy of the model is tested on the commercial vehicles safety test platform. The results of simulation and experiment indicate that model of vibration in the process of triaxial truck passing the speed bump can accurately calculate the minimum distance between speed bump and truck scale with different speed, which maximum error is 5.81%.
Keywords: Vehicle dynamics, speed bump position, truck scale, three-axle truck
DOI: 10.3233/JIFS-169402
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 1083-1095, 2018
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