Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters
The paper presents an experimentally validated regression model for dry clutch friction lining wear, accounting for the influence of clutch temperature, initial slip speed, torque, and closing time. The experimental data have been collected by using a custom-designed disk-on-disk computer-controlled...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/15/8150 |
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| author | Krunoslav Haramina Branimir Škugor Matija Hoić Nenad Kranjčević Joško Deur Andreas Tissot |
| author_facet | Krunoslav Haramina Branimir Škugor Matija Hoić Nenad Kranjčević Joško Deur Andreas Tissot |
| author_sort | Krunoslav Haramina |
| collection | DOAJ |
| description | The paper presents an experimentally validated regression model for dry clutch friction lining wear, accounting for the influence of clutch temperature, initial slip speed, torque, and closing time. The experimental data have been collected by using a custom-designed disk-on-disk computer-controlled tribometer and conducting repetitive real operation-like clutch closing cycles for different levels of the above operating parameters. The model is designed to be cycle-wise, predicting cumulative worn volume expectation and standard deviation after each closing cycle. It is organized around three distinctive submodels, which provide predictions of: (i) wear rate expectation, (ii) wear rate variance, and (iii) elevated wear rate during run-in operation. Finally, the wear rate expectation and variance submodels and the overall, cumulative worn volume model are validated on independent experimental datasets. The main novelty of the presented research lies in the development of stochastic multi-input cycle-wise dry cutch wear model for clutch design and monitoring applications. |
| format | Article |
| id | doaj-art-b2cdbad465ff4a79b5d39137d952e9eb |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-b2cdbad465ff4a79b5d39137d952e9eb2025-08-20T03:36:30ZengMDPI AGApplied Sciences2076-34172025-07-011515815010.3390/app15158150Modeling of Dry Clutch Wear for a Wide Range of Operating ParametersKrunoslav Haramina0Branimir Škugor1Matija Hoić2Nenad Kranjčević3Joško Deur4Andreas Tissot5Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFord-Werke GmbH, 50769 Cologne, GermanyThe paper presents an experimentally validated regression model for dry clutch friction lining wear, accounting for the influence of clutch temperature, initial slip speed, torque, and closing time. The experimental data have been collected by using a custom-designed disk-on-disk computer-controlled tribometer and conducting repetitive real operation-like clutch closing cycles for different levels of the above operating parameters. The model is designed to be cycle-wise, predicting cumulative worn volume expectation and standard deviation after each closing cycle. It is organized around three distinctive submodels, which provide predictions of: (i) wear rate expectation, (ii) wear rate variance, and (iii) elevated wear rate during run-in operation. Finally, the wear rate expectation and variance submodels and the overall, cumulative worn volume model are validated on independent experimental datasets. The main novelty of the presented research lies in the development of stochastic multi-input cycle-wise dry cutch wear model for clutch design and monitoring applications.https://www.mdpi.com/2076-3417/15/15/8150weardry friction clutchmodelingregressionvariabilityrun-in effect |
| spellingShingle | Krunoslav Haramina Branimir Škugor Matija Hoić Nenad Kranjčević Joško Deur Andreas Tissot Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters Applied Sciences wear dry friction clutch modeling regression variability run-in effect |
| title | Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters |
| title_full | Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters |
| title_fullStr | Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters |
| title_full_unstemmed | Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters |
| title_short | Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters |
| title_sort | modeling of dry clutch wear for a wide range of operating parameters |
| topic | wear dry friction clutch modeling regression variability run-in effect |
| url | https://www.mdpi.com/2076-3417/15/15/8150 |
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