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Dynamic analysis of a tracked snowplowing vehicle and assessment of ride quality


Dynamic analysis of a tracked snowplowing vehicle and assessment of ride quality

Wang, Kun (1998) Dynamic analysis of a tracked snowplowing vehicle and assessment of ride quality. Masters thesis, Concordia University.

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Tracked snowplow vehicles, designed for removing snow from the sidewalks, pose severe ride environment for the drivers, primarily arising from road wheel-track-terrain interactions. The drivers of such vehicles are thus exposed to a comprehensive magnitude of low frequency whole-body vibrations. Exposure to such large amplitude low frequency vibration limits the performance abilities of the driver and thus the vehicle mobility. The ride dynamics of a modern snowplowing vehicle is analyzed through systematic considerations of the track dynamics, track-terrain interaction, road wheel suspension, snowplowing forces, road wheel-track interactions, secondary suspension and biodynamic behavior of the driver. An in-plane twelve-degrees-of-freedom ride dynamic model of the vehicle is developed. The ride dynamic response of the model is analyzed under deterministic and random road excitations, during transit and plowing operations. The validity of the analytical model is demonstrated by comparing the response characteristics with the measured data. The ride quality of the vehicle is assessed in relation to the proposed guidelines upon applying the recommended frequency-weighting filters. The influence of variations in design and operating variables on the ride performance of the vehicle is investigated through a comprehensive parametric study. The variations in operating conditions include the speed, road roughness, the nature of task, and snow parameters. The parametric study on design variables includes the variations in secondary and primary suspension, geometry, track tension and elasticity, and road wheel parameters. The results of the study are discussed to highlight the contributions of these parameters the ride quality and to identify most desirable design and operating conditions

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Wang, Kun
Pagination:xxii, 188 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Dept. of Mechanical Engineering
Thesis Supervisor(s):Rakheja, Subhash
ID Code:592
Deposited By: Concordia University Library
Deposited On:27 Aug 2009 17:12
Last Modified:18 Jan 2018 17:14
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