Augmented Framework for Economic Viability-Based Powertrain Design and Emissions Analysis of Medium/Heavy-Duty Plug-in Hybrid Electric Vehicles

Vaidehi Y Hoshing, Purdue University

Abstract

Plug-in hybrid electric vehicles (PHEVs) are being considered as an alternative to conventional medium-duty (MD) and heavy-duty (HD) commercial vehicles to reduce fuel consumption and tailpipe emissions. Lithium ion batteries, which are used in PHEVs due to their high energy density, are expensive. The battery contributes significantly towards the life-cycle cost of MD/HD PHEVs, as these vehicles, due to high mass and aggressive battery usage, require multiple battery replacements over their lifetime. Smaller batteries increase the fuel consumption and need more replacements, while bigger batteries increase the initial system cost. Powertrain design from a life-cycle cost perspective is required to explore this trade-off and maximize the economic gains obtained from PHEVs. Powertrain design entails component sizing, control strategy selection as well as architecture selection. Different powertrain designs yield different lifetime economic gains. A variety of applications exist for MD/HD vehicles, which differ in their ways of powertrain usage, due to variations in required acceleration, available braking, and average and maximum speeds. Therefore, different powertrain designs are needed depending on the application and usage scenario. The powertrain design space needs to be explored, and solutions that maximize the economic gains within the specified constraints need to be chosen. This dissertation compares the economic viability of two PHEV applications (MD Truck and HD Transit Bus), with options of series and parallel hybrid architectures, over multiple drivecycles, for four economic scenarios (years 2015, 2020, 2025 and 2030). It is shown that hybridizing the transit bus achieves payback sooner than hybridizing the truck. Further, the results for the transit bus application, over the Manhattan drivecycle, show that implementation of the parallel architecture is economically viable in the 2015(present) scenario, while the series architecture becomes viable in 2020, due to significantly lower initial costs involved in the parallel architecture. A methodology to select a solution out of the explored design space that maximizes the economic gains is demonstrated. Variations in the economic and vehicle usage conditions for which this solution is designed, can be expected. It is therefore necessary to check the robustness of this solution to change in external factors such as vehicle mass, annual vehicle miles travelled (AVMT), component and fuel costs. It is shown that the economic gains are affected by the battery cost, fuel cost, AVMT and vehicle mass, while the number of battery replacements are affected by AVMT and vehicle mass. A probability-based approach is demonstrated to obtain confidence in the economic and battery life predictions. Specifically, probability-based variations are provided to variables such as miles traveled between recharge, recharge C-rate and battery temperature. It is shown that battery life is affected the most by battery temperature. A battery heating/cooling system is required to maintain constant battery temperature of operation during all seasons, but these systems incur additional fuel costs. A framework that utilizes just the Coefficient of Performance (COP) of the heating/cooling system to calculate the excess fuel cost is proposed and demonstrated. An increase of 0.9-1.8\% in fuel consumption is shown, depending on the drivecycle and ambient temperature.

Degree

Ph.D.

Advisors

Shaver, Purdue University.

Subject Area

Climate Change|Energy|Finance|Transportation

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