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Mission-based Design Space Exploration for Powertrain Electrification of Series Plugin Hybrid Electric Delivery Truck Ohio State University

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Jung, Jung, author.
Contributor:
Ahmed, Qadeer
Rizzoni, Giorgio
Zhang, Xieyuan
Conference Name:
WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2018
Summary:
AbstractHybrid electric vehicles (HEV) are essential for reducing fuel consumption and emissions. However, when analyzing different segments of the transportation industry, for example, public transportation or different sizes of delivery trucks and how the HEV are used, it is clear that one powertrain may not be optimal in all situations. Choosing a hybrid powertrain architecture and proper component sizes for different applications is an important task to find the optimal trade-off between fuel economy, drivability, and vehicle cost. However, exploring and evaluating all possible architectures and component sizes is a time-consuming task. A search algorithm, using Gaussian Processes, is proposed that simultaneously explores multiple architecture options, to identify the Pareto-optimal solutions. The search algorithm is designed to carefully select the candidate in each iteration which is most likely to be Pareto-optimal, based on the results from previous candidates, to reduce computational time. The powertrain of a medium-sized series plugin hybrid electric delivery truck with a range extender is optimized for different driving missions. Three different powertrain architectures are included in the design space exploration and the fuel economy is evaluated using a simulation model of the powertrain and Dynamic Programming. Results from the analysis show which ranges of powertrain component sizes are recommended for the different types of driving scenarios
Notes:
Vendor supplied data
Publisher Number:
2018-01-1027
Access Restriction:
Restricted for use by site license

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