Loads Simplification on Multi Input Axle Systems

Event
WCX SAE World Congress Experience
Authors Abstract
Content
The time domain is currently the most widely chosen option in fatigue testing to fully represent random events occurring in multiple simultaneous input channels. In vehicles for example, time domain tests can represent the same conditions of the road, by applying the same loads at the hard points of the vehicle along a time history. The main drawback of this methodology is the extensive testing duration and hardware cost. Time domain based fatigue tests are composed of a complex hardware, which requires servo motors to work, in order to induce the specific amount of load at a specific time window. These tests are time consuming, since they require the same length duration of the event they are reproducing, times the required repetitions. The frequency domain method for fatigue testing, on the other hand, requires simpler hardware, since there are no need for servomotors and the test length is reduced, since there is no need to run the full event times the required repetitions. The drawback in this case is the ability to represent random events with multiple simultaneous input channels. For this reason, frequency domain tests are mainly applied for simple round-robin tests, unable to represent random events like a road condition. In this work, we will present a new methodology that uses the fatigue result as input, reversing it in order to find the loads that would be required to originate it in frequency domain. This new methodology can help future developments in fatigue test, replacing time domain tests without losing accuracy and the ability to represent random events occurring in multiple simultaneous input channels.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-1056
Pages
7
Citation
Goncalves, R., Bishop, N., Kerr, S., and Vinturini, C., "Loads Simplification on Multi Input Axle Systems," SAE Int. J. Adv. & Curr. Prac. in Mobility 2(5):2809-2815, 2020, https://doi.org/10.4271/2020-01-1056.
Additional Details
Publisher
Published
Apr 14, 2020
Product Code
2020-01-1056
Content Type
Journal Article
Language
English