Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Michelin develops and manufactures tires. To check their tire, different tires tests are used.
During the testing process of agricultural tires, some endurance tests are performed on a
circular test track where a convoy, made of a truck pulling two single-axle trailers without
suspension system, is driven at a constant speed. Depending on the tested tires, it has been
observed that the convoy may become severely instable. This instability is a large problem
for the test team since the tires undertake too much overload which makes test results
unexploitable. This is time consuming and expensive for the company.
The aim of this thesis is two-folded. The first aim is to identify the phenomenon causing the
instability from experimental data and also the parameters which influence the
phenomenon. The second aim is to model the phenomenon from technical data in order to
predict instability behaviors in advance.
Models have been developed and the behavior have been analyzed and compared with
experiments. The main result of this work is that the instable behavior is due to the
excitation of natural modes of the convoy by the tires frequencies. Natural modes are
identified as the natural bouncing mode of the trailers. The bouncing natural mode of a
trailer depends on tires stiffnesses and the load on the trailer. Tires excitation frequencies
are related to the test speed, the trailer track width and the rolling circumference of the
tires. To get a good prediction tires stiffness and tires rolling circumference under operation
require to be better characterized.
Thanks to this work the test teams have a better understanding of the phenomenon and a
tool which can be used to give a rough indication about problematic configurations. This tool
cannot totally predict instable behaviors with the technical data at our disposal since some
more parameters, which are not quantified for now, might influence the phenomenon.
Nevertheless, these parameters have been highlighted by this study and if explored by the
test team, a working predicting tool could be achieved.
2013. , 51 p.