Application of Servo-Assisted Technology in Commercial Vehicle Steering Systems for Autonomous Mobility in Off-Road Trucks. Case Study: Application on 8x2/8x4 Sugarcane Trucks

2024-36-0033

12/20/2024

Features
Event
SAE Brasil 2024 Congress
Authors Abstract
Content
The exponential growth of the agribusiness market in Brazil combined with the high receptivity among farmers of new technological solutions has driven the study and implementation of high technology in the field. This work aimed to apply servo-assisted driving technology to enable autonomous mobility in an off-road sugarcane truck responsible for harvesting sugarcane. The technology consists of a conventional hydraulic steering with a motor, ECU and torque and angle sensors responsible for reading input data converted from GPS signals and previously recorded tracking lines. The motor responsible for replacing 100% of the physical force generated by the driver acts in accordance with the required torque demand, and the sensors combined with the ECU correct the course to meet the follow-up line through external communication ports. The accuracy of the system depends exclusively on the accuracy of the GPS signal, in this case reaching 2,5 cm, which is considered extremely high accuracy when comparing available technologies. The proposal was assembled on a national vehicle with a capacity of 31t in an 8x4 configuration, duly modified to meet the effort demands on typical national grounds and validated in the field through special test circuits. The use of the technology proved to be highly satisfactory and allowed an increase in efficiency of up to 7,5% compared to the use of conventional technology.
Meta TagsDetails
DOI
https://doi.org/10.4271/2024-36-0033
Pages
6
Citation
Oliveira Santos Neto, A., Lara, V., Silva, E., Destro, D. et al., "Application of Servo-Assisted Technology in Commercial Vehicle Steering Systems for Autonomous Mobility in Off-Road Trucks. Case Study: Application on 8x2/8x4 Sugarcane Trucks," SAE Technical Paper 2024-36-0033, 2024, https://doi.org/10.4271/2024-36-0033.
Additional Details
Publisher
Published
Dec 20
Product Code
2024-36-0033
Content Type
Technical Paper
Language
English