This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Transmission Shifting Analysis and Model Validation for Medium Duty Vehicles
Technical Paper
2023-01-0196
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie.
Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data. In addition to importing measured test signals into the Autonomie environment, the process also calculated some of the critical missing signals, such as each component effort or flow signal. Numerous analysis functions have been developed to quickly analyze the shifting map, using the integrated test data in Autonomie to generate model parameters. In addition, a set of calibrations for the generic shifting algorithm was developed to match the test data. Finally, we demonstrated the validation of Autonomie transmission component models and shifting control strategy by using medium duty vehicle test data over different driving records.
Authors
Topic
Citation
Kim, N., Islam, E., Vijayagopal, R., and Pamminger, M., "Transmission Shifting Analysis and Model Validation for Medium Duty Vehicles," SAE Technical Paper 2023-01-0196, 2023, https://doi.org/10.4271/2023-01-0196.Also In
References
- https://tedb.ornl.gov/wp-content/uploads/2021/02/TEDB_Ed_39.pdf
- Lee , C.T. , Ames , D. , Caldwell , B. , Knoth , M. et al. Development of GM Allison 10-Speed Heavy Duty Transmission SAE Technical Paper 2020-01-0438 2020 https://doi.org/10.4271/2020-01-0438
- Raser , B. Modular Transmission Family for Fuel Consumption Reduction Tailored for Indian Market Needs SAE Technical Paper 2021-26-0049 2021 https://doi.org/10.4271/2021-26-0049
- Morozov , A. , Humphries , K. , Rahman , T. , Zou , T. et al. Drivetrain Analysis and Optimization of a Two-Speed Class-4 Electric Delivery Truck SAE Technical Paper 2019-01-5001 2019 https://doi.org/10.4271/2019-01-5001
- Pettersson , P. , Jacobson , B. , Bruzelius , F. , Johannesson , P. et al. Intrinsic Differences between Backward and Forward Vehicle Simulation Models The 21st IFAC World Congress 53 2 2020 14292 14299 10.1016/j.if acol.2020.12.1368
- https://vms.taps.anl.gov/tools/autonomie/
- Vijayagopal , R. , Nieto Prada , D. , and Rousseau , A. December 2019
- https://www.energy.gov/eere/vehicles/21st-century-truck-partnership
- Islam , E. , Moawad , A. , Kim , N. , and Rousseau , A. A Detailed Vehicle Simulation Process to Support CAFE and CO2 Standards for the MY 2021–2026 Final Rule Analysis — Section 5: Vehicle and Component Assumptions Energy Systems Division, Argonne National Laboratory ANL/ESD-19/9 2020 124 216
- https://www.regulations.gov/document/NHTSA-2021-0053-0003
- Stutenberg , K. , Lohse-Busch , H. , Duoba , M. , Iliev , S. , et al. https://anl.box.com/v/AMTL-testing-reference
- Jeong , J. , Vijayagopal , R. , and Rousseau , A. Automated Model Initialization Using Test Data SAE International Journal of Engines 10 4 2017 2015 2020 https://doi.org/10.4271/2017-01-1144
- Meng , Y. , Jennings , M. , Tsou , P. , Brigham , D. et al. Test Correlation Framework for Hybrid Electric Vehicle System Model SAE Int. J. Engines 4 1 2011 1046 1057 https://doi.org/10.4271/2011-01-0881