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Moniot, Matthew
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Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

National Renewable Energy Laboratory-Matthew Moniot, Yanbo Ge, Nicholas Reinicke, Alex Schroeder
  • Technical Paper
  • 2020-01-0941
To be published on 2020-04-14 by SAE International in United States
The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in…
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Feasibility Analysis of Taxi Fleet Electrification using 4.9 Million Miles of Real-World Driving Data

National Renewable Energy Laboratory-Matthew Moniot, Clement Rames, Erin Burrell
Published 2019-04-02 by SAE International in United States
Ride hailing activity is rapidly increasing, largely due to the growth of transportation network companies such as Uber and Lyft. However, traditional taxi companies continue to represent an important mobility option for travelers. Columbus Yellow Cab, a taxi company in Columbus, Ohio, offers traditional line-of-sight hailing as well as digital hailing through a mobile app. Data from Columbus Yellow Cab was provided to the National Renewable Energy Laboratory to analyze the potential for taxi electrification. Columbus Yellow Cab data contained information describing both global positioning system trajectories and taxi meter information. The data spanned a period of 13 months, containing approximately 70 million global system positioning system points, 840 thousand trips, and 170 unique vehicles. A variety of scenarios were evaluated using Columbus Yellow Cab data and the Electric Vehicle Infrastructure Projection Tool (EVI-Pro) to understand challenges and opportunities associated with operating an electrified taxi fleet. Two main factors-access to home charging and vehicle specifications-are shown to be major variables affecting successful electric fleet operation. The analysis indicates that 95.7% of taxi travel days can…
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EcoRouting Strategy Using Variable Acceleration Rate Synthesis Methodology

Virginia Tech-Hrusheekesh Warpe, Matthew Moniot, Douglas Nelson, William Baumann
Published 2018-04-16 by SAE International in United States
This paper focuses on the analysis of an EcoRouting system with minimum and maximum number of conditional stops. The effect on energy consumption with the presence and absence of road-grade information along a route is also studied. An EcoRouting system has been developed that takes in map information and converts it to a graph of nodes containing route information such as speed limits, stop lights, stop signs and road grade. A variable acceleration rate synthesis methodology is also introduced in this paper that takes into consideration distance, acceleration, cruise speed and jerk rate as inputs to simulate driver behavior on a given route. A simulation study is conducted in the town of Blacksburg, Virginia, USA to analyze the effects of EcoRouting in different driving conditions and to examine the effects of road grade and stop lights on energy consumption. The results show that the synthesis with a piecewise jerk model simulates better driver behavior over a route and removes the hurdles associated with a piecewise acceleration model. The EcoRoute solution is found to vary with…
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Determining Off-cycle Fuel Economy Benefits of 2-Layer HVAC Technology

Argonne National Laboratory-Forrest Jehlik
DENSO International America Inc-Yuanpei Song, Masahiro Nomura
Published 2018-04-03 by SAE International in United States
This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation and heat rejection losses of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology in use versus the technology being disabled (disabled equals fresh air-considered as the standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state. These vehicle models were integrated into a database of measured on road testing and coupled with U.S. typical meteorological data to simulate vehicle efficiency across seasonal thermal and operational conditions for hundreds of thousands of drive cycles. Fuel economy benefits utilizing the 2-Layer HVAC technology are presented in addition…
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