Application of Multibody Simulation for Fatigue Life Estimation
In automobile design, the safety of passengers is of prime concern to the manufacturers. Suspension is one of the safety-related automotive systems which is responsible for maintaining traction between the road and tires, and offers a comfortable ride experience to the passengers by absorbing distu...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Universiti Malaysia Pahang
2013
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/11001/ http://umpir.ump.edu.my/id/eprint/11001/ http://umpir.ump.edu.my/id/eprint/11001/ http://umpir.ump.edu.my/id/eprint/11001/1/9_Kamal%20et%20al.pdf |
Summary: | In automobile design, the safety of passengers is of prime concern to the manufacturers. Suspension is one of the safety-related automotive systems which is responsible for
maintaining traction between the road and tires, and offers a comfortable ride experience to the passengers by absorbing disturbances. One of the critical components
of the suspension system is the knuckle, which constantly faces cyclic loads subjecting it to fatigue failure. This paper presents an evaluation of the fatigue characteristics of a knuckle using a gravel road profile acquired using a data acquisition system and standard SAE profiles for the suspension (SAESUS), bracket (SAEBRAKT) and
transmission (SAETRN). The gravel road profile was applied as the input to a multi body simulation (MBS), and the load history for various mounting points of the knuckle
is extracted. Fatigue life is predicted using the strain-life method. The instantaneous stress distributions and maximum principal stress are used for fatigue life predictions. From the results, the strut connection is found to be the critical region for fatigue failure. The fatigue life from loading extracted from gravel road MBS agreed well with the life prediction when standard SAE profiles were used. This close agreement shows the effectiveness of the load extraction technique from MBS. This method can also be effectively used for more complex loading conditions that occur during real driving
environments. |
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