FNT-Based Road Profile Classification in Vehicle Semi-Active Suspension System

Combining the computational intelligence with dynamic responses of vehicle suspension for estimating the road profiles provides effective tool for designing various control strategies. In this paper, a FNT-based road profile classification method is proposed based on the dynamic responses of a quarter semi-active suspension under PID controller and road disturbances generated from power spectral density under the ISO 8608 standard. More specially, a data preprocessing method is designed to reduce the impact of vehicle velocity on dynamic response and determine the appropriate size of the spatial domain for data collection. After that, FNT is employed as the basic model to screen these extracted features for road profile classification with low computational consumption of road evaluation. From the numerical simulation results, the classification accuracy is 98.41% under the proposed road profile classification with six input variables.