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Optimal Mission-Specific Dynamic Powertrain Calibration from Cloud for Class 8 Linehaul Truck Cruise Operation
Technical Paper
2020-01-5006
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Calibration of control software including engine and transmission is a major step in the integration of the powertrain system in heavy-duty vehicles. This calibration is done through a series of tests performed on the powertrain system in test cell or on the vehicle in the field to meet fuel economy, emissions, drivability and other customer performance requirements. Currently, since the knowledge of the future driving conditions of the vehicle is limited, the calibration is done to meet the requirements under different vehicle operating conditions leading to robust but sub-optimal performance operation of the system under some real-world driving conditions. In this paper, a mission-specific vehicle calibration optimization is presented, in which connectivity to cloud-computing platforms is utilized to run more complex optimization algorithms on a high fidelity digital twin model of the system and dynamically optimize selected calibration parameters of the control software for fuel economy and trip time. The route information including speed limit and elevation, or grade, is available over the entire trip mission, or route. This leads to a framework in which calibration parameters are dynamically updated to optimize fuel (energy) consumption subject to drivability, emissions and other customer requirements. The impact over 49,000 miles (78,900 km) of U.S. highways is further analyzed in simulation. The results indicate that nationwide implementation of the proposed concept to utilize connected and automated vehicle technologies for powertrain efficiency re-calibration has the potential of significant reduction in CO2 emissions and fuel cost spent in line-haul fleet operation.
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Sandoval, J., Tulpule, P., Hodzen, E., and Borhan, H., "Optimal Mission-Specific Dynamic Powertrain Calibration from Cloud for Class 8 Linehaul Truck Cruise Operation," SAE Technical Paper 2020-01-5006, 2020, https://doi.org/10.4271/2020-01-5006.Data Sets - Support Documents
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References
- Alternative Fuels Data Center, U.S. Department of Energy https://afdc.energy.gov/data 2018
- ARPA-E, U.S. Department of Energy https://arpa-e.energy.gov/?q=arpa-e-programs/nextcar 2018
- Pla , B. , Waschl , H. , del Re , L. , and Guardiola , C. Fuel and Immission Potential of Context Aware Engine Control SAE Technical Paper 2013-01-0306 2013 https://doi.org/10.4271/2013-01-0306
- Guardiola , C. , Pla , B. , Bares , P. , and Waschl , H. Adaptive Calibration for Reduced Fuel Consumption and Emissions Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 230 14 2002 2014 2016 https://doi.org/10.1177/0954407016636977
- Polterauer , P. and Waschl , H. An Implementable Multi-Calibration Strategy to Address Real Driving Emissions of CI Engines 2017 American Control Conference (ACC) 2017 297 302 https://doi.org/10.23919/ACC.2017.7962969
- Liu , J. , Pattel , B. , Desai , A. , Hodzen , E. et al. Fuel Efficient Control Algorithms for Connected and Automated Line-Haul Trucks 2019 IEEE Conference on Control Technology and Applications (CCTA) 2019
- Belludi , N. , Raymond , J. , Receveur , J. , and Hosagrahara , A. Cummins Vehicle Mission Simulation Tool: Software Architecture and Applications SAE Technical Paper 2010-01-1997 2010 https://doi.org/10.4271/2010-01-1997
- https://faf.ornl.gov/fafweb/ 2019
- https://developer.here.com/develop/rest-apis 2019
- O’Keefe , M. , Simpson , A. , Kelly , J. , and Pedersen , D. Duty Cycle Characterization and Evaluation Towards Heavy Hybrid Vehicle Applications SAE Technical Paper 2007-01-0302 2007 https://doi.org/10.4271/2007-01-0302
- http://smartadvantagepowertrain.com 2019
- http://www.powerspec.cummins.com 2019
- Asamer , J. , Graser , A. , Heilmann , P. , and Ruthmair , M. Sensitivity Analysis for Energy Demand Estimation of Electric Vehicles Transportation Research Part D: Transport and Environment 46 182 199 2016 https://doi.org/10.1016/j.trd.2016.03.017
- https://www.esteco.com/modefrontier 2019
- Wood , E. , Duran , A. , Burton , E. , Gonder , J. et al. 2015 https://www.nrel.gov/docs/fy15osti/63853.pdf
- U.S. Department of Transportation - Federal Highway Administration 2000 https://www.fhwa.dot.gov/reports/tswstudy/Vol2-Chapter3.pdf
- https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=pet&s=emd_epd2d_pte_nus_dpg&f=a 2019