Adaptive Soft Computing Strategies for ABS Equipped Full-Car Active Suspension System with Seated-Passengers Biodynamic Virbrations Damping Control

Abstract

Intheexistinghighlymechanizedandtechnologicallyadvancedsociety,thevehicleprovides a key means of communication. Vehicle ride is influenced by road surface roughness. Somedoseofunpleasantwholebodyvibration(WBV)transmittedintothehuman organs causes fatigue and discomfort. Low frequency WBV is injurious and prolonged exposures result in multiple health problems. Increase in vibration creates more health hazards thus reduces human performance. A score of experimental and analytical studiesonseated-driversexposuretolow-frequencyWBVhavedemonstratedintheexisting literature. However,thepublishedliteraturelacksintegratedbiodynamicmodeling. Verification of the models against various external road excitation profiles. And the use of advanced intelligent control strategies for vibration damping and the biodynamic response analysis. Today,theautomobilemanufacturersareconfrontedwithconflictingchallenges,atradeoff between ride quality, vehicle safety, stability, rattle space and wheels deflection limits. WBVdamping,therefore,hasattractedalotofinterestintherecentyears. Anumber of suspension models and control techniques are developed and implemented and few are still under consideration. The work presented in this thesis includes mathematical modeling of the nonlinear fullcar active suspension system with driver and passenger lumped seat model along with anti-lockbrakingsystem(ABS).Themodelingisextendedtovehicle-driverbiodynamic, vehicle-pregnant subject biodynamic and vehicle-driver-pregnant subject biodynamic with ABS and cornering models. These models incorporate all forms of the system motions and nonlinearities. An advanced adaptive NeuroFuzzy control is proposed and developed for vibrations damping and ride comfort improvement. An adaptive recurrent Fuzzy wavelet neural network(ARFWNN)controlalgorithmisalsoproposedtofurtherenhancetheridecomfort of the vehicle occupants.