Publication

Modeling & Simulation, Testing & Validation (MSTV)
2011

EXPERIMENTAL VALIDATION OF A MULTIBODY DYNAMICS MODEL OF THE SUSPENSION SYSTEM OF A TRACKED VEHICLE

by Tamer M. Wasfy; James O’Kins; David Ryan

Abstract

A time-accurate multibody dynamics model of the suspension system of a tracked vehicle is experimentally validated using a full-scale tracked-vehicle on an N-post motion simulator. The experiments consist of harmonic excitations at various amplitudes and frequencies and ramp excitations of the vehicle road-wheels (without the track), with each road wheel under one linear actuator of the N-post motion simulator. A high-fidelity multibody dynamics model of the vehicle along with the N-post motion simulator is constructed. The multibody dynamics model consists of rigid bodies, joints, rotational springs (that include non-linear rotational stiffness, damping and friction), actuators and contact surfaces. The rigid bodies rotational equations of motion are written in a body-fixed frame with the total rigid-body rotation matrix updated each time step using incremental rotations. Connection points on the rigid bodies are used to define joints between the bodies including revolute, cylindrical, prismatic and bracket joints. A penalty model is used to impose the joint and normal contact constraints. The contact model detects contact between discrete points on the surface of each wheel (master contact surfaces) and a polygonal surface representation of the linear actuators dishpans (slave contact surfaces). A recursive bounding box/bounding sphere contact search algorithm is used to allow fast contact detection. An asperity friction model is used for the contact friction forces. The governing equations of motion are solved along with joint/constraint equations using a time-accurate explicit solution procedure. The time-histories of the suspension system rotational deflections are experimentally measured for the various input motion excitations. The experimental measurements are compared with the results predicted using the computational model. The comparison shows that the model can predict with reasonably good accuracy the test tracked-vehicle’s dynamic response.