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Intelligent prediction of wear life of automobile brake pad based on braking conditions

Intelligent prediction of wear life of automobile brake pad based on braking conditions To avoid braking accidents caused by excessive wear of brake pad, this study aims to achieve online prediction of brake pad wear life (BPWL).Design/methodology/approachA simulated braking test bench for automobile disc brake was used. The correlation and mechanism between the three braking condition parameters of initial braking speed, braking pressure and initial braking temperature and the tribological performance were analyzed. The different artificial neural network (ANN) models of wear loss were discussed. Genetic algorithm was used to optimize the ANN model. The structure scheme of the online prediction system of BPWL was discussed and completed.FindingsThe results showed that the braking conditions were positively correlated with the wear loss, but negatively correlated with the friction coefficient. The prediction accuracy of back propagation (BP) ANN model was higher. The model was optimized by genetic algorithm, and the average deviation of prediction results was 4.67%. By constructing the online monitoring system of automobile braking conditions, the online prediction of BPWL based on the ANN model could be realized.Originality/valueThe research results not only have important theoretical significance for the study of BPWL but also have practical value for guiding the maintenance and replacement of automobile brake pads and avoiding the occurrence of braking accidents. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Lubrication and Tribology Emerald Publishing

Intelligent prediction of wear life of automobile brake pad based on braking conditions

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References (19)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0036-8792
eISSN
0036-8792
DOI
10.1108/ilt-04-2022-0132
Publisher site
See Article on Publisher Site

Abstract

To avoid braking accidents caused by excessive wear of brake pad, this study aims to achieve online prediction of brake pad wear life (BPWL).Design/methodology/approachA simulated braking test bench for automobile disc brake was used. The correlation and mechanism between the three braking condition parameters of initial braking speed, braking pressure and initial braking temperature and the tribological performance were analyzed. The different artificial neural network (ANN) models of wear loss were discussed. Genetic algorithm was used to optimize the ANN model. The structure scheme of the online prediction system of BPWL was discussed and completed.FindingsThe results showed that the braking conditions were positively correlated with the wear loss, but negatively correlated with the friction coefficient. The prediction accuracy of back propagation (BP) ANN model was higher. The model was optimized by genetic algorithm, and the average deviation of prediction results was 4.67%. By constructing the online monitoring system of automobile braking conditions, the online prediction of BPWL based on the ANN model could be realized.Originality/valueThe research results not only have important theoretical significance for the study of BPWL but also have practical value for guiding the maintenance and replacement of automobile brake pads and avoiding the occurrence of braking accidents.

Journal

Industrial Lubrication and TribologyEmerald Publishing

Published: Feb 15, 2023

Keywords: Wear loss; Temperature; Life prediction; Brake pad; Braking pressure; Initial braking speed

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