The tire is an essential element for the handling, comfort and safety of a vehicle. However, an under-inflation increases the risk of burst, causes rapid tire wear and increases fuel consumption. It is therefore important to develop tire pressure monitoring systems (TPMS). A first approach, reffered to as "direct" method, consisting on using pressure sensors is expensive and unreliable (possible sensors faults). The new generation of TPMS promotes "indirect" methods, without pressure sensors. Monitoring is performed from the physical quantities related to the pressure. The tire pressure drop results in increasing the wheel angular velocity, shifting the vehicle vibratory modes, reducing the wheel effective radius and increasing its rolling resistance. The approach based on a comparative analysis of the wheels angular velocities does not meet the requirements regarding the minimum pressure drop that must be detected and the number of detectable deflated tires. Adding a spectral analysis of each wheel angular velocity signal enhances the robustness of such an approach. However, it shows significant convergence time. The first aim of the thesis work is therefore to optimize such algorithms and reduce the computational time. An alternative approach requiring low maintenance costs is the implementation of observers for quantities related to the pressure. The second objective of this thesis is to propose observers able to estimate both the effective radius and the rolling resistance of the wheels without using additional sensors. The work in this thesis deals with methodological and experimental aspects through the implementation of the methods and their application to real data.
