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International Journal of Automotive Technology > Volume 23(4); 2022 > Article
International Journal of Automotive Technology 2022;23(4): 1109-1115.
doi: https://doi.org/10.1007/s12239-022-0097-8
EQUIVALENT LOAD GENERATION FROM VEHICLE RLDA DATA USING TIME-CORRELATED DAMAGE EDITING AND REPRESENTATIVE FREQUENCY BAND COMPONENTS METHODS
Hweekwon Jung 1, Kwonhee Suh 2
1Intelligent Photonic IoT Research Center, KOPTI
2Special Vehicle R&D Center, KIA
PDF Links Corresponding Author.  Kwonhee Suh  , Email. lastadam@kia.com
ABSTRACT
This paper aims for generating an equivalent load signal for the durability analysis of a heavy-duty vehicle using a signal processing technique. Durability analysis is an essential part in the early stages of development. For a reliable durability assessment, an equivalent load signal representing load events that a real vehicle will experience should be clearly identified. In addition, due to the limited computational resources, the equivalent load signal must be of much shorter time duration and should satisfy statistical properties and fatigue damage with respect to the measured load data. The proposed method consists of data conversion from the original responses, data refinement and representative segment selection based on damage and statistical properties, and equivalent load generation based on a time-correlated damage editing method and a representative frequency band components method. By incorporating these steps into one framework, the equivalent load data could be generated automatically with minimum user interaction. The fatigue lives according to TCDE and RFBC signals show an average difference of 14.2 % and 43.6 % compared to the test life, respectively. The effectiveness and accuracy of the proposed techniques are demonstrated by comparing analytic fatigue lives with those of the durability test.
Key Words: Road load, Signal processing, Pseudo-damage, Equivalent load, Durability analysis
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