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Accelerated Sizing of a Power Split Electrified Powertrain
- Pier Giuseppe Anselma - Politecnico di Torino / McMaster University ,
- Atriya Biswas - McMaster University ,
- Lucas Bruck - McMaster University ,
- Saeed Amirfarhangi Bonab - McMaster University ,
- Adam Lempert - McMaster University ,
- Joel Roeleveld - McMaster University ,
- Krishna Madireddy - FCA US LLC ,
- Omkar Rane - FCA US LLC ,
- Bryon Wasacz - FCA US LLC ,
- Giovanni Belingardi - Politecnico di Torino ,
- Ali Emadi - McMaster University
ISSN: 2641-9637, e-ISSN: 2641-9645
Published April 14, 2020 by SAE International in United States
Citation: Anselma, P., Biswas, A., Bruck, L., Amirfarhangi Bonab, S. et al., "Accelerated Sizing of a Power Split Electrified Powertrain," SAE Int. J. Adv. & Curr. Prac. in Mobility 2(5):2701-2711, 2020, https://doi.org/10.4271/2020-01-0843.
Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin’s minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude. In this paper, sizing parameters for a power split electrified powertrain are considered that include the internal combustion engine size, the two electric motor/generator sizes, the transmission ratios, and the final drive ratio. The SERCA approach is adopted to rapidly evaluate the fuel economy capabilities of each sizing option in various driving missions considering both type-approval drive cycles and real-world driving profiles. While screening out for optimal sizing options, the implemented methodology includes drivability criteria along with fuel economy potential. Obtained results will demonstrate the agility of the developed sizing tool in identifying optimal sizing options compared to state-of-the-art sizing tools for electrified powertrains.