Multipurpose Longitudinal Distance-Based Driver for On-Road and Off-Road Vehicles

Authors Abstract
Content
Driving skills and, more in general, driver’s behavior may have a major impact on vehicle performances. They can affect not only the fuel consumption of the machine but, at the same time, also its productivity and the durability of many mechanical, electronic, and hydraulic components equipped on the vehicle. In this article, a model, able to reproduce different driver’s approaches to the machine, is shown. The longitudinal driver model has been developed in Matlab/Simulink and, firstly, employed on buses and trucks applications; then it has been also exported into a wheel loader plant model designed in Simcenter AMESim. The article is focused on how the driver model, integrated into the wheel loader plant model, can simulate custom cycles with a different driving style (high/low aggressiveness). It allows, on one hand, to emulate a real driver behavior and, on the other hand, to increase simulation repeatability and reproducibility.
The designed model has also an auto-tune feature to set a suitable parametrization according to the characteristics of the selected vehicle (mass, acceleration, on-road/off-road, etc.) for a first simulation attempt; eventually, it can also be manually tuned to increase its accuracy.
Meta TagsDetails
DOI
https://doi.org/10.4271/02-14-03-0025
Pages
8
Citation
Bonavolontà, G., Pintore, F., and Monacelli, G., "Multipurpose Longitudinal Distance-Based Driver for On-Road and Off-Road Vehicles," Commercial Vehicles 14(3):311-318, 2021, https://doi.org/10.4271/02-14-03-0025.
Additional Details
Publisher
Published
Sep 7, 2021
Product Code
02-14-03-0025
Content Type
Journal Article
Language
English