Toe misalignment of tyres is a common phenomenon in trucks. They pose a safety risk as they cause the truck to drift to one side, forcing the driver to make constant course corrections, which may lead to driver fatigue. Continuous monitoring of the truck can detect misalignment and help in mitigating potential safety issues by alerting the driver and the fleet owner. In this paper, the effectiveness of using a model-based approach to detect toe and thrust angle misalignment in a single-unit twin-axle truck is explored. For this purpose, an analytical model that can accurately predict the dynamic response of a truck with proper alignment was first developed. Secondly, data were synthesised from TruckMaker® for a truck with the same vehicle parameters as the model but with toe and thrust misalignment. Subsequently, the data from TruckMaker® were compared with the output of the analytical model for the same manoeuvres to flag a misalignment. The model-based approach showed good effectiveness in detecting toe misalignment, with approximately 30% and 5% of random misalignment cases going undetected in the static and dynamic slip ratio modes.
Model-Based Toe Misalignment Detection in Single-Unit Twin-Axle Trucks
2022-10-08
673247 byte
Conference paper
Electronic Resource
English
Data-Driven Toe Misalignment Detection in Single-Unit Twin-Axle Trucks
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