Active Suspension Control of Full Car Model Using Bat Optimized PID Controller

1. Introduction

The reduction of vibrations is a challenging task in the Full Car Model (FCM) of the vehicle. The researchers are focused on different types of control strategies in the FCM Active Suspension System (ASS) to analyse the vehicle dynamics and increase the ride comfort of the passengers. Active suspensions offer the potential of being adaptable to the quality of the road surface, vehicle speed and comfort requirements. The suspension system reduces the transmission of oscillations to the vehicle body from road surface disturbances.

Rajagopal, K., & Ponnusamy, L. (2014) discussed PSO and Biogeography-Based Optimization (BBO) to obtain optimal PID controller parameters for Quarter Car Model (QCM). The time domain and frequency domain analysis are considered to examine the effectiveness of the Genetic Algorithm (GA) based Fuzzy Logic Controller (FLC). The ride comfort and stability of the nonlinear model is enhanced by GA based FLC when compared to PID controller and PSS. Nagarkar, M P et al. (2018) introduced multi objective optimization for nonlinear quarter car model to detach the vehicle body from external disturbances. The trajectory optimization of FCM (Soh, M et al. 2018) and the damper structure optimization using Particle Swarm Optimization (PSO) (Wang, M & Xie, N 2018) have been discussed in earlier studies. Wang, W. et al. (2015) took into account the cultural algorithm to optimise the Fuzzy PID controller to lower the BA, which increases the passenger's comfort throughout the ride. Jahromi, AF & Zabi hollah, A (2010) designed Linear Quadratic Regulator (LQR) and FLC to reduce the vibration level of passenger car. The overshoot and steady state error are decreased to minimum value with LQR in comparison to FLC. Prabakar, RS et al. (2013) considered magneto-rheological damper as a semi active device to replace actuator. The performances of body acceleration and road handling are utilised to evaluate the potency of LQR. To examine the passenger's comfort during the ride, additional frequency responses of sprung mass acceleration are illustrated. The simulation (Yuvapriya T and Lakshmi, P 2020) and experimental QCM is investigated with sliding mode controllers (Yuvapriya T et al. 2020). The requirements are simultaneously fulfilled and the controller's parameters are adjusted via evolutionary multi-objective optimization. (Reynoso-Meza et al. 2014). The ride quality of the vehicle is improved by Zhao, J et al. (2019) using semi- ASS. The quarter car model utilises air spring and hydraulic damper. The cuckoo search algorithm optimises PID parameters which improves the passenger comfort using semi-ASS. The simulation and experimental analysis illustrate that the optimised PID controller outperforms the conventional PID controller for different driving conditions.