Study and Comparison of Road Profile for Representative Patch Extraction and Duty Cycle Generation in Durability Analysis

2017-26-0309

01/10/2017

Event
Symposium on International Automotive Technology 2017
Authors Abstract
Content
Automotive vehicles are subjected to a variety of loads caused by road undulations. The load history data measured from the roads are one of the vital input parameters for physical test as well as virtual durability simulation of vehicles. In general, the automotive vehicles are instrumented and subjected to a variety of driving conditions in diverse roads to obtain representative road load time histories. Acquired road load time history signals from various roads are exhaustive and repetitive in terms of both time length and data size. This results in more computation and virtual simulation processing. Hence it is imperative to reduce the input time signals without compromising on the representation of the actual operating conditions.
Signal reduction of measured road load histories for virtual simulation assumes greater significance for durability prediction. This work intends on selecting representative patches from input signals by categorizing it in terms of ISO class of roads and extracting only the high damage patches for each class. To perform this selection, road profile information is essential. Inertial profiler methodology is selected and validated for the same. The measured road profile information with road load data implies objective classification of acquired data based on ISO class of roads. This eliminates the re-selection of signals for virtual analysis from similar class of roads. It helps in reducing the product lead-time and costs of new vehicle development.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-26-0309
Pages
7
Citation
Prasad, S., Prakaash, J., and Dayalan, P., "Study and Comparison of Road Profile for Representative Patch Extraction and Duty Cycle Generation in Durability Analysis," SAE Technical Paper 2017-26-0309, 2017, https://doi.org/10.4271/2017-26-0309.
Additional Details
Publisher
Published
Jan 10, 2017
Product Code
2017-26-0309
Content Type
Technical Paper
Language
English