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Eco-Driving Strategies for Different Powertrain Types and Scenarios

Argonne National Laboratory-Simeon Iliev, Eric Rask, Kevin Stutenberg, Michael Duoba
  • Technical Paper
  • 2019-01-2608
To be published on 2019-10-28 by SAE International in United States
Connected automated vehicles (CAVs) are quickly becoming a reality, and their potential ability to communicate with each other and the infrastructure around them has big potential impacts on future mobility systems. Perhaps one of the most important impacts could be on network wide energy consumption. A lot of research has already been performed on the topic of eco-driving and the potential fuel and energy consumption benefits for CAVs. However, most of the efforts to date have been based on simulation studies only, and have only considered conventional vehicle powertrains. In this study, experimental data is presented for the potential eco-driving benefits of two specific intersection approach scenarios and four different powertrain types. The two intersection approach scenarios considered in this study include an approach to a red light where coming to a complete stop is avoidable and one where a complete stop is determined necessary thanks to advance information from vehicle to infrastructure communication (V2I). The four powertrain types tested in this study include an advanced conventional vehicle, a conventional vehicle with idle stop-start capability,…
 

On-Track Measurement of Road Load Changes in Two Close-Following Vehicles: Methods and Results

Argonne National Laboratory-Michael Duoba, Alejandro Fernandez Canosa
Published 2019-04-02 by SAE International in United States
As emerging automated vehicle technology is making advances in safety and reliability, engineers are also exploring improvements in energy efficiency with this new paradigm. Powertrain efficiency receives due attention, but also impactful is finding ways to reduce driving losses in coordinated-driving scenarios. Efforts focused on simulation to quantify road load improvements require a sufficient amount of background validation work to support them. This study uses a practical approach to directly quantify road load changes by testing the coordinated driving of two vehicles on a test track at various speeds (64, 88, 113 km/h) and vehicle time gaps (0.3 to 1.3 s). Axle torque sensors were used to directly measure the load required to maintain steady-state speeds while following a lead vehicle at various gap distances. Through trial and error, test methods were developed that appear to provide satisfactory results, considering the challenges of track testing under real-world conditions (wind, weather, temperature changes, etc.). We found that total road load was reduced by about 10-12% at an optimum gap time of 0.25 to 0.4 s. Challenges…
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Investigating Steady-State Road Load Determination Methods for Electrified Vehicles and Coordinated Driving (Platooning)

Argonne National Laboratory-Michael Duoba, Forrest Jehlik
Published 2018-04-03 by SAE International in United States
Reductions in vehicle drive losses are as important to improving fuel economy as increases in powertrain efficiencies. In order to measure vehicle fuel economy, chassis dynamometer testing relies on accurate road load determinations. Road load is currently determined (with some exceptions) using established test track coastdown testing procedures. Because new vehicle technologies and usage cases challenge the accuracy and applicability of these procedures, on-road experiments were conducted using axle torque sensors to address the suitability of the test procedures in determining vehicle road loads in specific cases. Whereas coastdown testing can use vehicle deceleration to determine load, steady-state testing can offer advantages in validating road load coefficients for vehicles with no mechanical neutral gear (such as plug-in hybrid and electric vehicles). Steady-state testing may also be the only way to directly evaluate vehicle loads during coordinated driving (platooning or automated cruise control). Several electrified test vehicles with axle torque sensors were tested on a flat, level stretch of pavement to (1) validate/compare to conventional coastdown testing loads, and (2) investigate road load reductions from two-car…
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Real-World Thermal Effects on Wheel Assembly Efficiency of Conventional and Electric Vehicles

SAE International Journal of Passenger Cars - Mechanical Systems

Argonne National Laboratory-Forrest Jehlik, Eric Rask, Michael Duoba
  • Journal Article
  • 2016-01-0236
Published 2016-04-05 by SAE International in United States
It is widely understood that cold ambient temperatures negatively impact vehicle system efficiency. This is due to a combination of factors: increased friction (engine oil, transmission, and driveline viscous effects), cold start enrichment, heat transfer, and air density variations. Although the science of quantifying steady-state vehicle component efficiency is mature, transient component efficiencies over dynamic ambient real-world conditions is less understood and quantified.This work characterizes wheel assembly efficiencies of a conventional and electric vehicle over a wide range of ambient conditions. For this work, the wheel assembly is defined as the tire side axle spline, spline housing, bearings, brakes, and tires. Dynamometer testing over hot and cold ambient temperatures was conducted with a conventional and electric vehicle instrumented to determine the output energy losses of the wheel assembly in proportion to the input energy of the half-shafts. Additionally, response surface methodology (RSM) techniques were applied to the conventional vehicle serving as predictive models of the wheel assembly efficiency as a function of its thermal state. For the conventional vehicle, data showed that under -17°C ambient…
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Performance and Efficiency Assessment of a Production CNG Vehicle Compared to Its Gasoline Counterpart

Argonne National Laboratory-Thomas Wallner, Kevin Stutenberg, Henning Lohse-Busch, Michael Duoba
Michigan Technological Univ.-Jay Anderson, Scott Miers
Published 2014-10-13 by SAE International in United States
Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations.Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model.The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied. When the indicated thermal efficiency at each point was calculated, it was found that the CNG vehicle typically exhibited lower thermal efficiency.Several operating points were chosen for further characterization of engine efficiency and combustion behavior, including an analysis of losses. Though the CNG engine had better…
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Validating Volt PHEV Model with Dynamometer Test Data Using Autonomie

SAE International Journal of Passenger Cars - Mechanical Systems

Argonne National Laboratory-Namdoo Kim, Michael Duoba, Namwook Kim, Aymeric Rousseau
  • Journal Article
  • 2013-01-1458
Published 2013-04-08 by SAE International in United States
The first commercially available Plug-In Hybrid Electric Vehicle (PHEV), the General Motors (GM) Volt, was introduced into the market in December 2010. The Volt's powertrain architecture provides four modes of operation, including two that are unique and maximize the Volt's efficiency and performance. The electric transaxle has been specially designed to enable patented operating modes both to improve the electric driving range when operating as a battery electric vehicle and to reduce fuel consumption when extending the range by operating with an internal combustion engine (ICE). However, details on the vehicle control strategy are not widely available because the supervisory control algorithm is proprietary. Since it is not possible to analyze the control without vehicle test data obtained from a well-designed Design-of-Experiment (DoE), a highly instrumented GM Volt, including thermal sensors, was tested at Argonne National Laboratory's Advanced Powertrain Research Facility (APRF). In this paper, we first describe the vehicle instrumentation and the test results. The vehicle control algorithm is analyzed from the test data and designed in Simulink. Finally, the Autonomie Volt component models…
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Ambient Temperature (20°F, 72°F and 95°F) Impact on Fuel and Energy Consumption for Several Conventional Vehicles, Hybrid and Plug-In Hybrid Electric Vehicles and Battery Electric Vehicle

Argonne National Laboratory-Henning Lohse-Busch, Michael Duoba, Eric Rask, Kevin Stutenberg
US Dept of Energy-Lee Slezak, David Anderson
Published 2013-04-08 by SAE International in United States
This paper determines the impact of ambient temperature on energy consumption of a variety of vehicles in the laboratory. Several conventional vehicles, several hybrid electric vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle were tested for fuel and energy consumption under test cell conditions of 20°F, 72°F and 95°F with 850 W/m₂ of emulated radiant solar energy on the UDDS, HWFET and US06 drive cycles.At 20°F, the energy consumption increase compared to 72°F ranges from 2% to 100%. The largest increases in energy consumption occur during a cold start, when the powertrain losses are highest, but once the powertrains reach their operating temperatures, the energy consumption increases are decreased. At 95°F, the energy consumption increase ranges from 2% to 70%, and these increases are due to the extra energy required to run the air-conditioning system to maintain 72°F cabin temperatures. These increases in energy consumption depend on the air-conditioning system type, powertrain architecture, powertrain capabilities and drive patterns. The more efficient the powertrain, the larger the impact of climate control (heating or…
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Developing a Utility Factor for Battery Electric Vehicles

SAE International Journal of Alternative Powertrains

Argonne National Laboratory-Michael Duoba
  • Journal Article
  • 2013-01-1474
Published 2013-04-08 by SAE International in United States
As new advanced-technology vehicles are becoming more mainstream, analysts are studying their potential impact on petroleum use, carbon emissions, and smog emissions. Determining the potential impacts of widespread adoption requires testing and careful analysis. PHEVs possess unique operational characteristics that require evaluation in terms of actual in-use driving habits. SAE J2841, “Utility Factor Definitions for Plug-In Hybrid Electric Vehicles Using 2001 U.S. DOT National Household Travel Survey Data,” published by SAE in 2009 with a revision in 2010, is a guide to using DOT's National Household Travel Survey (NHTS) data to estimate the relative split between driving in charge-depleting (CD) mode and charge-sustaining (CS) mode for a particular PHEV with a given CD range. Without this method, direct comparisons of the merits of various vehicle designs (e.g., efficiency and battery size) cannot be made among PHEVs, or between PHEVs and other technologies.The dedicated battery electric vehicle (BEV) is now becoming a viable alternative to conventional vehicles and other advanced vehicles (like HEVs and PHEVs). However, a shortcoming persists in current comparisons between BEVs and other…
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Design of an On-Road PHEV Fuel Economy Testing Methodology with Built-In Utility Factor Distance Weighting

SAE International Journal of Alternative Powertrains

Argonne National Laboratory-Michael Duoba
  • Journal Article
  • 2012-01-1194
Published 2012-04-16 by SAE International in United States
As vehicle technology progresses to new levels of sophistication, so too, vehicle test methods must evolve. This is true for analytical testing in a laboratory and for on-road vehicle testing. Every year since 1993, the U.S. Department of Energy (DOE) and original equipment manufacturer (OEM) sponsors have organized a series of competitions featuring advanced hybrid electric vehicle (HEV) technology to develop and promote DOE goals in fuel savings and alternative fuel usage. The competition has evolved over many years and has included many alternative fuels feeding the prime mover (including hydrogen fuel cells). EcoCAR turned its focus to plug-in hybrid electric vehicles (PHEVs) and it was quickly realized that to keep using on-road testing methods to evaluate fuel and electricity consumption, a new method needed to be developed that would properly weight depleting operation with the sustaining operation, using the established Utility Factor (UF) method. A new approach using three separate trips was devised for the on-road emissions and energy consumption event that matches the Fleet UF found in SAE J2841. This paper explains the…
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Calculating Results and Performance Parameters for PHEVs

Argonne National Laboratory-Michael Duoba, Richard “Barney” Carlson, Daniel Bocci
Published 2009-04-20 by SAE International in United States
As one of the U.S Department of Energy's (DOE's) vehicle systems benchmarking partners, Argonne National Laboratory (Argonne) has tested many plug-in hybrid electric vehicle (PHEV) conversions and purpose-built prototype vehicles. The procedures for testing follow draft SAE J1711 and California Air Resources Board (CARB) test concepts and calculation methods. This paper explains the testing procedures and calculates important parameters. It describes some parameters, such as cycle charge-depleting range, actual charge-depleting range, electric range fraction, equivalent all-electric range, and utility factor-weighted fuel economy.
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