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Technical Paper

Damage Identification of Rear Axle Under Experimental Condition from Curvature Mode Change

2010-04-12
2010-01-0930
In this paper the approach of using modal parameters to detect and locate damage of automobile rear axle under experimental condition is explained. This method uses the changes in the curvature mode of the structure as the damage identification indicator to detect and locate damage. The curvature mode and the damage identification indicator are explained, the process of the identification is introduced. The method is demonstrated with a FEM (Finite Element Method) analysis on a plate under different damage conditions. And the indicator is improved with a weighting function. Then EMA (Experimental Modal Analysis) is conducted on a damaged and an undamaged rear axle of a vehicle to get the modal parameters for the damage identification indicator which later identifies and locates the damages, thus validating the introduced method.
Technical Paper

Torsional Vibration Modeling of Driveline System for EV Low-Frequency Flutter

2015-06-15
2015-01-2191
In view of the problem of low-frequency (less than 10Hz, such as 0.5Hz, 1.15Hz, 8Hz in this paper) longitudinal vibration exists in a pure electric vehicle, modeling methods of drive-line torsion vibration system are conducted. Firstly, dynamometer test is performed, signals of motor speed and seat rail acceleration are obtained, the frequency characteristics of flutter is determined using the order analysis and time frequency analysis. Then four types of modeling and analysis are investigated facing the drive-line torsion vibration problem, including single model without electromagnetic stiffness, branch model without electromagnetic stiffness, single model considering electromagnetic stiffness and branch model considering electromagnetic stiffness. The results show that, modeling taking into account the electromagnetic stiffness and branches can reflect more low-frequency characteristics helps to reveal the low-frequency longitudinal flutter of the researched electric vehicle.
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