GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Background The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. Methods This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions’ range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. Results The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Conclusion Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system

Theoretical and experimental investigation of magneto-rheological damper based semi-active suspension systems

Semi-active vehicle suspension systems with Magneto-Rheological (MR) dampers have recently received an increasing attention. Satisfactory performance of these systems is highly dependent on the adopted control method. This paper offers theoretical and experimental investigation of the control of vehicle suspension systems using a quarter car suspension equipped with a MR damper. To achieve the best performance, a control method made of two nested controllers is used. Fuzzy logic, skyhook and On-Off control techniques are studied as system controllers in conjunction with a Heaviside step function as the damper controller. For the theoretical study, the modified Bouc-Wen model of MR dampers is used to calculate the damping force and a mathematical model of the semi-active quarter car suspension is derived and used in the simulation. To prove the applicability of the proposed fuzzy logic controller in a real suspension system, a two degrees of freedom quarter car test rig is designed and used. To quantify the effectiveness of the system under bump and random road disturbance, various performance criteria are evaluated based on the dynamic response of the quarter car suspension system in time and frequency domains,. Simulation and experimental results from the system with the fuzzy logic controllers are compared to the results from the system with skyhook controller, On-Off controller, a passive MR damper and a conventional passive damper