Abstract
Driving safety of a vehicle is largely influenced by the damper and the tire. Developed in this research is an algorithm of fault diagnosis for the damper and the tire so that the driver can be promptly informed when a fault occurs in one or both of the components. To this end, the damper and the tire were modeled using the neural network from their experimental data, and the fault diagnosis was made using frequency responses of the damping force and the dynamic wheel force. The algorithm was tested via experiments, and showed successful diagnostic performance under various driving conditions.