AbstractThis thesis details the development of an experimental test rig to measure the performance of semi-active and active vehicle suspensions. Due to the variety of suspension components, configurations and vehicle types that might adopt active suspensions a hybrid numerical-experimental test rig were developed using simulation and a range of mechanical and microprocessor hardware. Using Model-in-the-Loop and Hardware-in-the-Loop systems representing the suspension allows for flexibility in the testing of various suspension components. Similarly a model-in-the-loop system representing the vehicle structure was developed to investigate flexible systems such as those found in an aircraft. This allows the dynamic interaction between the structural flexible vibration modes and the suspension to be established.Actuator tracking errors are crucial to the accuracy and stability of model-in-the-loop systems. Friction was shown to be a major source of tracking error for the suspension model-in-the-loop actuator and this led to the development of a novel force controlled friction compensator which resulted in a 37% improvement of the test rig accuracy and a reduction of peak force error by approximately 50%. Another source of tracking error which directly effects system stability is system delays caused by actuator, sensor, computational and filter lags. The effect of these delays upon the accuracy and stability of the test rig is analysed and discussed. Finally, passive, semi-active and active skyhook quarter car experiments were conducted and verified using the hybrid test rig. The results show that characteristics of passive, semi-active and active suspensions, and their dynamic interaction with a flexible vehicle structure can be successfully replicated using the test rig.
|Date of Award||24 Jun 2015|
|Supervisor||Andrew Hillis (Supervisor) & Jos Darling (Supervisor)|
Hybrid Numerical-Experimental Testing of Active and Semi-Active Suspensions
Eamcharoenying, P. (Author). 24 Jun 2015
Student thesis: Doctoral Thesis › PhD