Abstract
BackgroundThe 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.MethodsThis 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.ResultsThe 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.ConclusionSimulation 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.
Highlights
The primary function of a suspension system is to isolate the vehicle body from road irregularities providing the ride comfort and to support the vehicle and provide stability
The stationary road roughness is effectively described by power spectral density (PSD)
In the fuzzy logic control system, RMS acceleration is reduced by 46% as compared to the passive system and by 18% as compared to genetic algorithm (GA)-based PID controller
Summary
The primary function of a suspension system is to isolate the vehicle body from road irregularities providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; 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 improves the performance of suspension system. The main function of an automotive suspension system is to support the vehicle weight, to isolate the occupants against the excitations caused by road unevenness and providing the ride comfort and better handling, and to keep the contact between tyre and ground. The primary objective of the active suspension system is to replace the passive suspension system by a controlled system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between the body and the wheel. One of the main objectives was to minimize body acceleration to improve ride comfort
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