Paul, Gunther, and Ulbrich, Heinz (2019) Active seat suspension enhancing driver comfort. In: [Presented at the International Scientific Conference on Hardwood Processing]. From: ISCHP 2019: International Scientific Conference on Hardwood Processing, 28–30 August 2019, Delft, The Netherlands.

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Abstract

One or two mass models (Fig.1) have been suggested to represent vehicle seat-occupant vibration behaviour, which contributes significantly to vehicle occupant comfort. Moreover it has been experimentally determined that vehicle seat vibration comfort mainly depends on vibration in a frequency range from f = 0-30 Hz. Subjective vibration comfort perception coincides with the two-mass models and finds resonance frequencies at around 4.5 Hz and 14-15 Hz.To avoid adverse occupant effects in autonomous driving, seat vibration must be controlled (Fig.2).This can be achieved through four actors mounted between the seat and seat rails, effectively isolating the seat from vehicle vibration. The isolation performance for such an active vibration damper is shown in Fig.3 for a constant damping factor and three stiffnesses. Moreover, isolation performance depends on the operating displacement capacity (Fig.4).Small actor displacement drives high stiffness; vice–versa the higher the stiffness, the smaller the actor displacement. The higher the stiffness, the higher is also the required actor power, and the stiffer the system, the worse the vibration isolation. The larger the actor displacement, the smaller the resonance frequency, which is desirable. The higher the damping, the higher is also the required actor power, and the smaller the resonance amplitude. On the other hand, the smaller the damping and the higher the actor displacement, the better the vibration isolation above 4 Hz. Vibration isolation below 1 Hz is not possible. Hence to optimize the system large actor displacement, small stiffness and medium to high damping must be achieved (Fig.5).

Item ID:	60656
Item Type:	Conference Item (Presentation)
Related URLs:	https://www.unisa.it/centri_e_vari/icc20...
Date Deposited:	10 Sep 2020 00:53
FoR Codes:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling @ 50% 09 ENGINEERING > 0902 Automotive Engineering > 090204 Automotive Safety Engineering @ 50%
SEO Codes:	88 TRANSPORT > 8801 Ground Transport > 880109 Road Safety @ 50% 97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 50%
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