Simulating the Longitudinal Dynamics of a Tracked Vehicle

Abstract

The simulation procedure has always been considered as a giant leap forward, especially in the field of basic designing of a product. There is nothing new underneath the basic concept, but the scientific and technical progress always brings up new techniques that improve simulation in its whole. When we talk about a vehicle, especially about a military one, we consider that it is much cheaper to simulate a process involving the weapon system than performing countless tests that are rather expensive. In this respect, we tried to develop a simulation mathematical model, check its accuracy with a set of extensive tests, prove it reliability and further extrapolate the behavior of the simulated model to a larger number of military vehicles of the same kind. It could help in various fields, such as diagnose (by comparing the simulated results with the real ones got from a faulty vehicle) or automatically regulating some functions (an intelligent vehicle, having an implemented, simulated model, that is able to feel the status of a subsystem in real time and regulate its behavior, accordingly). Hence, the paper presents a model that simulates the longitudinal dynamics of a tracked vehicle. It has been issued using Simulink module of Matlab programming environment. It aims at pointing out the performances of the vehicle. The models interface is friendly and its structure is modular. The main modules of the model are the engine, the torque converter, the transmission and the track. The engine and the torque converter are modeled using the experimental maps obtained by the tests that have been previously developed by the manufacturer. The main principle of the equations that describe the system is to set a balance among the forces (both active and resistive) that load the vehicle. The inputs of the model are the technical and dimensional features, provided by the manufacturer or experimentally determined. The output of the model is a dynamic behavior. Comparing the results with the experimental data eventually validates or invalidates the model. But the results were excellent, so the model was validated. Also, the results proved that the developed model is able to predict the performances of the take-off stage of the tracked vehicle.