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Adaptive control of an active seat for occupant vibration reduction

Vehicle occupants are typically exposed to unpleasant whole-body vibration (WBV) for extended period of time. It is well known that the transmission of unwanted vibration to the human body can lead to fatigue and discomfort. Moreover, the unwanted vibration normally distributed in the low-frequency range has been found as the main risk factor for lower back pain and lumbago, which seriously affect the health and working performance of occupants. Thus vibration cancellation on seats has attracted considerable interest in recent years. So far, for most vehicle seats, vibration isolation is achieved passively by using seat cushions and conventional energy absorbers, which have very limited performance in the low-frequency range. The work presented in this thesis forms a successful development and experimental study of an active seat and control algorithm for occupants’ WBV reduction under low frequency excitations. Firstly, a modelling study of the seat human subjects (SHS) and an extensive experimental measurement of the vibration transmissibility of a test dummy and vehicle seat are carried out. The biodynamic responses of SHS exposed to uncoupled vertical and fore-and-aft WBV is modelled. A comparison with the existing models is made and the results show that an improved fit with the aggregated experimental data is achieved. Secondly, an active seat is developed based upon the observations and understanding of the SHS and seat system. The characteristics of the active seat dynamics are identified through experimental tests found suitable for the development of an active seat to attenuate the vibration experienced by vehicle occupants. The vibration cancellation performance of the active seat is initially examined by feedforward plus proportional-integral (PI) control tests. Through these tests, the effectiveness of the actuators control authority is verified, but the limitations are also revealed. Because the active seat system is subject to non-linear and time-varying behaviour, a self-tuning fully adaptive algorithm is a prime requirement. The Filtered-x Least-Mean-Square (FXLMS) algorithm with the Fast-block LMS (FBLMS) system identification technique is found suitable for this application and is investigated through experimental tests. Substantial vibration reductions are achieved for a variety of input vibration profiles. An excellent capability of the active seat and control system for efficiently reducing the vibration level of seated occupants under low-frequency WBV is demonstrated.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:665426
Date January 2015
CreatorsGan, Zengkang
ContributorsHillis, Andrew ; Darling, Jocelyn
PublisherUniversity of Bath
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

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