Automotive Magneto-Rheological Dampers:Modelling and Parameter Identification using contrast-based Fruit Fly Optimisation

The present study discusses the mechanical behaviour and modelling of a prototype automotive magneto-rheological (MR) damper, which presents different viscous damping coefficients in jounce and rebound. The force generated by the MR damper is measured at different velocities and electrical currents, and a modified damper model is proposed to improve fitting of the experimental data. The model is calibrated by means of parameter identification and for this purpose a new swarm intelligence algorithm is proposed, that we call the contrast-based Fruit Fly Optimisation Algorithm (c-FOA). The performance of c-FOA is compared with that of Genetic Algorithms, Particle Swarm Optimisation, Differential Evolution and Artificial Bee Colony. The comparison is made on the basis of no a-priori knowledge of the damper model parameters range. The results confirm the good performance of c-FOA under parametric range uncertainty. A sensitivity analysis discusses c-FOA’s performance with respect to its tuning parameters. Finally, a ride comfort simulation study quantifies the discrepancies in the results, for different identified damper model sets. The discrepancies underline the importance of accurately describing MR damper nonlinear behaviour, considering that virtual sign-off processes are increasingly gaining momentum in the automotive industry.<br/

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

Vibration Control of a Seat Suspension System Using Magnetorheological Damper

Seat suspension system is critical to the ride comfort experience of a vehicle’s driver and passengers. The use of a magnetorheological (MR) damper in a seat suspension system has been shown to offer significant benefits in this regard. Most research on seat MR dampers has applied active control strategies to command the MR damper, which is an inherently semi-active device. This paper introduces a more suitable semi-active control strategy for an MR damper used in a seat suspension, enabling more effective control. The proposed control system comprises a system controller that computes the desired damping force using a sliding mode control algorithm, and a neural-based damper controller that provides a direct estimation of the command voltage that is required to track the desired damping force. The seat suspension system is approximated by base-excited single degree of freedom system. The proposed semi-active seat suspension is compared to a passive seat suspension for prescribed base displacements. These inputs are representative of the vibration of the sprung mass of a passive or semi-active quarter-vehicle suspension under bump or random-profile road disturbance. Control performance criteria such as seat travel distance and seat acceleration are evaluated in time and frequency domains, in order to quantify the effectiveness of proposed semi-active control system. The simulated results reveal that the use of semi-active control in the seat suspension provides a significant improvement in ride comfort.</jats:p

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