Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort

Abstract

Abstract A suspension system plays an active role in balancing the conflicting requirements of stability and ride comfort in an automobile. The health of the driver is an important aspect since continuous exposure to vehicle vibrations may lead to severe health hazards in long run. In this study, full car with driver model of 13 Degrees of Freedom (DOF) is considered. The vehicle is tested under bump, pulse, half-sine and different classes of random road profiles (ISO 8608) for analysis in Matlab/Simulink environment. Initially the vehicle suspension is tested for a Proportional Integral and Derivative (PID) controller. To deal with higher complexity of the vehicle design, intelligent controllers are implemented. Fuzzy Logic Controller (FLC) is designed for the vehicle which plays a role in vibration suppression and ride comfort (ISO 2631-1 standard) improvement. This design is further enhanced by Adaptive Neuro-Fuzzy Inference System (ANFIS) controller which incorporates the advantages of both fuzzy and neural control system. The time domain analysis and ride comfort analysis show that ANFIS controller gives better control over linear PID controller, FLC and Passive Suspension System (PSS). To evaluate the effectiveness of the controller, it is tested for various classes of random road profile for varying speed condition. Simulation results show that ANFIS controller fed system gives better ride comfort and passenger safety by reducing the Root Mean Square (RMS) values of Head Acceleration (HA), Frequency Weighted RMS (FWRMS) values of HA, Vibration Dose Value (VDV) at the driver head and Power Spectrum Density (PSD) analysis of HA. Also, the proposed ANFIS controller is experimentally verified on laboratory Quarter car setup. It is tested on two road inputs namely pulse input and half-sine input. This analysis also proves that the ANFIS controller performs better than FLC and PSS.