Numerical and Experimental Dynamics of a Monotube Shock Absorber

Paper #:
  • 2016-01-1557

Published:
  • 2016-04-05
DOI:
  • 10.4271/2016-01-1557
Citation:
Castellani, F., Bartolini, N., Scappaticci, L., Astolfi, D. et al., "Numerical and Experimental Dynamics of a Monotube Shock Absorber," SAE Technical Paper 2016-01-1557, 2016, doi:10.4271/2016-01-1557.
Pages:
10
Abstract:
Shock absorber is one of the most relevant sub-systems of the suspension system for a wide range of vehicles. Although a high level of development and tuning has been reached, in order to ensure high safety standards in almost every situation, some dynamic phenomena affecting vehicle handling or NHV (Noise Vibration Harshness) can appear. The aim of present work is to improve a mathematical model using experimental data from a prototype of monotube shock absorber developed for research purposes. The model takes into account all the main features affecting the global performance of the device, such as non-linear behaviour and the presence of hysteresis loops. Actually, the most important parameters are analyzed, such as flow and orifice coefficients of the valves, coefficients of mechanical compliance of the chambers and oil compressibility, dry and viscous friction coefficients. The identification of these parameters is carried out through experimental tests on the prototype, which is a totally adjustable device equipped with pressure and temperature transducers for every chamber. Experimental tests are performed on a test rig, collecting data about piston rod displacement, velocity, pressure and force. Finally, the model is validated through comparison against experimental results. An optical access is included in the prototype in order to allow data correlation with the images from a high speed camera. This approach is valuable for analyzing the occurrence and the time development of dynamic phenomena such as the cavitation of the flow or the motion of the main valve blades. Finally, the correlation of the processed optical images, coupled with evidences from experimental data, allows to characterize the dynamic events, supporting the reliability of the model.
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