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Durability Test Suite Optimization Based on Physics of Failure
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches.
A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented. When comparing to an exclusively historically based test suite, the Load Matrix approach provides a 20% reduction in dyno test hours while increasing the number of failure modes covered to the engine durability target by nearly a factor of two.
CitationVelten, C., Hammer, M., Wohlfart, J., Holland, B. et al., "Durability Test Suite Optimization Based on Physics of Failure," SAE Technical Paper 2018-01-0792, 2018, https://doi.org/10.4271/2018-01-0792.
Data Sets - Support Documents
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- Stanton , D. Systematic Development of Highly Efficient and Clean Engines to Meet Future Commercial Vehicle Greenhouse Gas Regulations SAE Int. J. Eng. 6 3 1395 1480 2013 10.4271/2013-01-2421
- Kopin , A. and Musselman , S. Complete Vehicle Standards for Heavy-Duty Trucking: Optimizing Freight Efficiency Benefits to Meet U.S. Greenhouse Gas Emission Standards SAE Int. J. Commer. Veh. 8 2 400 418 2015 10.4271/2015-01-2772
- Schilke , W. Analysis of Transmission and Vehicle Field Test Data SAE Technical Paper 1964 10.4271/640466SAE 640466
- Berns , H. Field Service History Analysis for Ground Vehicles SAE Technical Paper 1975 10.4271/750553.
- Smith , K. and Stornant , R. Cumulative Damage Approach to Durability Route Design SAE Technical Paper 1979 10.4271/791033 SAE 920660
- Hu , J. and Garfinkel , G. Correlation of Thermal Cycle Tests to Field Usage Profiles for Solder Joints in Automotive Electronics SAE Technical Paper 1998 10.4271/980344
- Holland , B. , McKinley , T. , and Storkman , B. Modeling Approach to Estimate EGR Cooler Thermal Fatigue Life SAE Int. J. Eng. 8 4 1724 1732 2015 10.4271/2015-01-1654
- Sever , C. , Brewer , T. , Eeley , S. , Chen , X. et al. Cylinder Head Thermo-Mechanical Fatigue Risk Assessment Under Customer Usage SAE Technical Paper 2017 10.4271/2017-01-1086
- Grewal , H. , D'Amato , A. , and Rossie , K. A Method for Rapid Durability Test Development SAE Technical Paper 2017 10.4271/2017-01-0199
- Hick , H. , Denkmayr , K. , and Aschaber , M. Optimizing Validation Programs with the Load Matrix Method SAE Technical Paper 2004 10.4271/2004-01-2668
- Gosain , G. , Holland , B. , and McKinley , T. Customer Usage Space Classification and Representative Duty Cycle Development Using K-Means Clustering SAE Int. J. Commer. Veh. 10 2 2017 10.4271/2017-01-0204
- Damji , N. , Dresser , D. , Bellavoine , J. , and Swaminathan , M. Automated Model-Based Calibration for Drivability Using a Virtual Engine Test Cell SAE Technical Paper 2015 10.4271/2015-01-1628