Virtual Driveline Concept-Based Maneuverability Control of a Skid-Steering UGV with Individually Driven Wheels 2022-01-0366
In the absence of a physical driveline between the wheels powered by individual electric motors, in this paper, a concept of the virtual driveline system was applied to a small skid-steering unmanned ground vehicle (UGV) for the purpose of controlling its maneuverability, i.e., for fulfilling desired maneuvers in terrain zones constrained by natural and man-made objects.
The virtual driveline concept supposes that the UGV driving wheels are connected via a virtual driveline that is a computational code to manage the power split among the wheels by using characteristics of a mechanical driveline system. The kinematic discrepancy factor (KDF) as a mechanical driveline characteristic is utilized to mathematically link the angular velocities and the drive torques of the electrically driven wheels.
The UGV maneuverability is considered as a vehicle complex operational property, which characterization and assessment is limited in this study to an analysis of two simple operational properties, i.e., vehicle turnability and lateral stability. The turnability is defined as an ability of UGV to change the curvature of its trajectory path under variations of the wheel angular velocities and torques. The lateral stability is understood as an ability of UGV to withstand lateral and yaw loads while continuing its lateral movement characteristics within desired boundaries.
A model predictive control algorithm designed in this study to improve the maneuverability of the UGV non-linear model manages KDFs and, thus, ensures the torques at the wheels that are needed for UGV desired maneuvers. The paper presents computational results and analysis of UGV maneuverability in various terrain conditions.
Citation: Zhang, S., Vantsevich, V., Gorsich, D., and Letherwood, M., "Virtual Driveline Concept-Based Maneuverability Control of a Skid-Steering UGV with Individually Driven Wheels," SAE Technical Paper 2022-01-0366, 2022, https://doi.org/10.4271/2022-01-0366. Download Citation
Author(s):
Siyuan Zhang, Vladimir Vantsevich, David Gorsich, Michael Letherwood
Affiliated:
University of Alabama at Birmingham, U.S. Army Ground Vehicle Systems Center, Alion Science & Technology
Pages: 12
Event:
WCX SAE World Congress Experience
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Electric motors
Unmanned ground vehicles
Wheels
Mathematical models
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