Connected Tyres : Real-time Tyre Monitoring System for Fleet& Autonomous Vehicles with Tyre WearEstimation through Sensor Fusion

Abstract: Tyres are one crucial part for vehicles, as they are the only contact pointbetween the vehicle and the road. Intelligent tyres are a trending new subjectin the tyre industry. They are designed to monitor various tyre states and sendthis information to both drivers and remote servers. The master thesis focuseson the proposal of a real-time tyre monitoring system for fleet and autonomousvehicles. It includes developing a tyre wear model and analysis of the currenttyre pressure monitoring functionality by leveraging the connectivity of fleetvehicles equipped with a Volvo web cloud service. The tyre wear model indirectlymonitors the tread depth of the vehicles all four tyres by identifyingcharacteristics between worn and fresh tyres. The two characteristics are identifiedby monitoring and analyzing vehicle speed and braking signals. The twocharacteristics is input to a voting scheme which decides when a worn tyre isdetected. The test vehicle was a Volvo XC40 with three types of tyres: wintertyres, summer tyres and worn summer tyres. The wear model gives 90 %accuracy to 10 set of test data, randomly selected from all dataset at HälleredProving Ground (Sweden). The connectivity realizes the data transmissionfrom the raw data of onCAN and FlexRay signals stored in a Volvo web cloudservice to the tyre monitoring fleet system. The signals are filtered and resampled,leaving the required signals of the tyre pressure monitor system andthe tyre wear model. Two signals, Calibration Status and iTPMS Status, areused to perform a statistical analysis on tyre pressure by categorizing the calibrationstatus and the tyre pressure conditions.The project outcome is an interfacebuilt on MATLAB GUI for demonstration of vehicle identification andtyre health conditions, with the embedded tyre wear model and connectivity.