Diagnosis and Prognosis of Chassis Systems in Autonomous Driving Conditions
Expanding various future motilities such as PBV(Purpose Built Vehicle), UAM(Urban Air Mobility), and Robo-taxi, the application of autonomous driving system (ADS) technology is also spreading. In order to prepare for the disruption of autonomous vehicle operation or the occurrence of an accident, and to secure customer safety, important is monitoring the anomaly of a vehicle. In this study, the process to diagnose the anomaly and to evaluate the remaining useful life of chassis system of the vehicle under autonomous driving conditions is established. Once an autonomous driving simulation model of the vehicle with Modelica is constructed, a lane keeping assistant (LKA) system with Matlab is combined with the model to perform the driving simulations. Applying the degrading data of three kinds of chassis systems (a shock absorber damper, a suspension bush, and a tire), the deteriorated LKA behavior is monitored with K-NN (K-nearest neighbor) and GMM (Gaussian Mixture Model).