Enhancement of Suspension Performance of the Vehicle Model Using Sliding Mode Controllers

1. Introduction

In a real time, scenario application of controller design requires a driver for riding the car. Even though driverless cars have been invented but they are still not available for commercial use. The ride comfort analysis is very useful to analyse the vertical vibration of the Full Car Model (FCM) but it does not include the dynamics of seat suspension for a driver. Therefore, it is necessary to include the seat suspension for a driver model for the analysis of the complete dynamics of FCM. Passive seat suspension, Semi-active seat suspension and Active seat suspension are the three types of seat suspension. In Passive seat Suspension System (PSS) the constant spring stiffness and damping coefficient of the vehicle model has a very low attenuating power. Similarly in semi-active seat suspension system, the damping force of the shock absorber is controlled by using variable damper. Whereas in active seat suspension the force is generated using actuator with respect to the road conditions.

The issues of nonlinearities of 8 DOF vehicle with driver model due to friction in the dampers are addressed in (Güçlü, 2003). The objective of this proposed PID control scheme is to arrest the vibration in the seat section and body of the vehicle. The PID control technique decreases vibration and linearizes the nonlinear model, improving ride comfort for the passenger. An optimal control technique for 8 DOF Active Seat Suspension (ASS) has been developed (Sadati et al., 2008). The road handling and ride comfort is considered as the performance index to show the effectiveness of the proposed method. To validate the proposed method, the stochastic inputs are simulated and the result confirms that the optimal kalman observer provides better performance index.

The Neural Network (NN) controller for nonlinear 8 DOF full vehicle with driver model to obtain desirable output has been designed (Guclu & Gulez, 2008). The time and frequency responses of the vehicle are plotted for with and without controllers. The proposed NN control technique provides zero steady state error and better travelling comfort to the passenger. The simulation results show that NN outperforms than uncontrolled system. An illustrated static and dynamic comfort of the human with seat model is shown in (Siefert et al., 2008). The virtual realisation of the human model is adopted to analyse the static and dynamic loading effects. The vibration analysis is successfully carried out in human seat model. The ride comfort analysis for tractors cabin through experimental measurements and finite element modelling is demonstrated in (Zehsaz et al., 2011). According to ISO standards two different road profiles are chosen and accelerometer sensor is attached in the vehicle for measurement. Due to vertical acceleration, tractors operator experiences the discomfort. (Pazooki et al., 2012) depicts the off road dynamics of the vehicle model and three dimensional tyre model. An ASS and PSS results are evaluated for driver’s seat location in terms of PSD analysis. The suspension design increases human health and ride comfort of the passenger in the off road vehicle.