Active control of vibrations transmitted through a car suspension

Abstract

A the sis submitted to McGill University in partial fulfilment of the requirements for the degree of Master of Engineering © Jean-Gabriel Roumy, MMHI L'auteur conserve la propriété du droit d'auteur et des droits moraux qui protège cette thèse. Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation. 1+1Conformément à la loi canadienne sur la protection de la vie privée, quelques formulaires secondaires ont été enlevés de cette thèse.Bien que ces formulaires aient inclus dans la pagination, il n'y aura aucun contenu manquant.• ABSTRACT The vibrations caused by road imperfections, which are transmitted to a car frame through the suspension, are one of the major sources of ambient noise inside the passenger compartment of an automobile.A solution to this problem is the addition of feedback-controlled actuators between the suspension attachment points and the car frame. These actuators can be driven to provide an active control of the vibrations, thus reducing greatly the magnitude of the forces exerted on the car frame at the suspension attachment points. In order to implement a robust yet effective controller, a model of a 1,4 car suspension (suspension associated to a single wheel) is derived from experimentally acquired data. The structure's modal parameters are extracted from Frequency Response data, and are used to obtain a state-space realization. The performance of controller design techniques such as LQR and Hoo is assessed through simulation using the model of the suspension .

Analysis and Simulation of Active Suspension System for Full Vehicle Model Subjected To Random Road Profile

“…Different design criteria are defined either in frequency or time domain for controllers and large variety are devised. The commonly approaches are proportional-integral-derivative (PID) [3][4][5][6], model-predictive control (MPC) [7,8], load dependent controller [9], fuzzy logic [10][11][12][13], neural network [10,14], H∞ [15][16][17], LQR [10,[18][19][20][21], Skyhook controller [10,22], preview controller [23,24] etc. More details about this methods can be found on [25].…”