Title: Study on super-wheelbase preview controller/algorithm for internet of vehicles suspension system used in a heavy vehicle fleet

Authors: Ce Yuan; Jiang Liu; Xilong Zhang; Bilong Liu; Yushun Wang

Addresses: Department of Shandong, Qingdao University of Technology, Qingdao, Shandong, 266520, China ' Department of Shandong, Qingdao University of Technology, Qingdao, Shandong, 266520, China ' Department of Shandong, Qingdao University of Technology, Qingdao, Shandong, 266520, China ' Department of Shandong, Qingdao University of Technology, Qingdao, Shandong, 266520, China ' Department of Shandong, Qingdao University of Technology, Qingdao, Shandong, 266520, China

Abstract: Most truck fleet transportation shows typical repetitive features in vehicle models, routes and cargos. So the internet of vehicles (IoV) theory could be easily introduced into the active control for truck suspensions. We establish a communication network structure in which paired vehicles are basic elements, and the geographic information systems are treated as a detection auxiliary. The new design reduces the overall communication demand for suspension control data. Based on this simplified IoV system, a new super-wheelbase preview control method is proposed. The optimal vehicle distance between paired trucks is calculated by the particle swarm optimisation (PSO). The traditional wheelbase preview algorithm is improved by using two equivalent parameters. The rear truck shows better comprehensive suspension performances than the front one. Finally, we perform a simple objective optimisation in the truck pairs sequence. The convergence results show that with the help of the IoV suspension system, the 6th and after trucks can get the minimised body acceleration in the fleet's first loop.

Keywords: suspension; IoV; internet of vehicles; super-wheelbase preview; PSO; particle swarm optimisation.

DOI: 10.1504/IJHVS.2023.131977

International Journal of Heavy Vehicle Systems, 2023 Vol.30 No.1, pp.71 - 89

Received: 17 Feb 2020
Accepted: 24 Oct 2020
Published online: 06 Jul 2023 *