Design-space exploration of series plug-in hybrid electric vehicles for medium-duty truck applications in a total cost-of-ownership framework. (15th September 2017)

• Record Type: Journal Article
• Authors: Vora, Ashish P.; Jin, Xing; Hoshing, Vaidehi; Saha, Tridib; Shaver, Gregory; Varigonda, Subbarao; Wasynczuk, Oleg; Tyner, Wallace E.
• Is Part Of: Applied energy. Volume 202(2017)
• Page Start: 662
• Page End: 672
• Publication Date: 2017-09-15
• Subjects: Economic analysis -- Plug-in hybrid electric vehicles -- Energy storage system -- Component sizing -- Battery life -- Payback period; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2017.05.090
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A model-based framework for parametric design of hybrid electric vehicles is shown. Powertrain efficiency and Li-ion battery degradation are both simulated. The framework enables design from a total cost-of-ownership perspective. Results are shown for the series architecture over medium-duty truck applications. Significant impact of payback period and battery replacement limitations. Abstract: The light-duty vehicle market has seen some adoption of hybrid electric vehicles that is not reflected in the heavy-duty market. The major challenges associated with the heavy-duty segment are: (i) greater emphasis on economic viability, (ii) reluctance to take on risk associated with new technologies, and (iii) numerous diverse applications that preclude a one-size-fits-all approach to hybrid-electric powertrain design. To overcome these challenges, a model-based framework is required that enables the exploration and optimal design of powertrain architectures for diverse applications while capturing the impact of hybridization on the economics of ownership under different economic scenarios. This paper demonstrates such a framework that incorporates powertrain simulation and battery degradation models to predict fuel consumption, electrical energy consumption, and battery replacements. These results are combined with economic assumptions to enable the exploration of a large design space (which spans powertrain design & control variables, noise variables, and economic scenarios) from a total cost-of-ownership perspective to provide better insights to vehicle integrators, component manufacturers, and buyers of heavy-duty hybrid electric vehicles. The methodology is applied to series plug-in hybrid electric and extended-range electric powertrain architectures for medium duty truck applications. The results show that under the assumptions made, economically favorable solutions for series plug-in hybrid electric medium-duty trucks exist in the 2020 time-frame for the NY Composite Truck drive cycle, while for the HTUF Refuse Truck and HTUF Class 6 P&D Truck drive cycles, feasible solutions are not obtained until 2025 and 2030 time-frames respectively.