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2020 | OriginalPaper | Chapter

Leveraging Connectivity and Automation to Improve Propulsion System Energy Sufficiency

Authors : Darrell Robinette, Bo Chen, Pradeep Bhat, Joe Oncken, Josh Orlando, Neeraj Rama

Published in: CTI SYMPOSIUM 2018

Publisher: Springer Berlin Heidelberg

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Abstract

The use of connectivity and automation in mobility applications is rapidly increasing and being introduced into propulsion system controls to reduce energy consumption. With support from the US Department of Energy’s, ARPA-E agency and in partnership with General Motors, the Chevrolet Volt, generation II, is studied and tested for the benefits of Connected and Automated Vehicle (CAV) control applied to Vehicle Dynamics and Powertrain (VD&PT) to reduce energy consumption by 20% in real world driving scenarios. This investigation looks at application of model predictive control, energy utilization forecasting and external data regarding traffic and infrastructure to develop a mission profile for propulsion system and vehicle dynamics. Both a long and short prediction time horizon are created for propulsion system operation, determining blending of charge depleting and charge sustaining, with the objective of reducing the total energy utilized for the trip by upwards of 20%. The presentation/paper will present the VD&PT model predictive control methodology being developed as a supervisory controller and/or driver assistant. Measured data from a test fleet of generation 2 Chevrolet Volts will also be presented illustrating the benefits of CAV on a single vehicle on real world driving cycle. The experimental results cover a range of driving conditions, from rural to heavy urban; representing the potential reduction in energy consumption CAV control can provide a plugin hybrid electric propulsion system architecture.

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Literature
5.
go back to reference Wang H, Sacheva K, Tripp J, Chen B, Robinette D, Shahbakhti M (2018) Optimal map-based mode selection and powertrain control for a multi-mode plug-in hybrid electric vehicle. In: IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA2018). Oulu, Finland, July 2–4 Wang H, Sacheva K, Tripp J, Chen B, Robinette D, Shahbakhti M (2018) Optimal map-based mode selection and powertrain control for a multi-mode plug-in hybrid electric vehicle. In: IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA2018). Oulu, Finland, July 2–4
Metadata
Title
Leveraging Connectivity and Automation to Improve Propulsion System Energy Sufficiency
Authors
Darrell Robinette
Bo Chen
Pradeep Bhat
Joe Oncken
Josh Orlando
Neeraj Rama
Copyright Year
2020
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-58866-6_25

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