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The potential peaking of world conventional oil production and the possible imperative to reduce carbon emissions will put great pressure on vehicle manufacturers to produce more efficient vehicles, on vehicle buyers to seek them out in the marketplace, and on energy suppliers to develop new fuels and delivery systems. Four cases for stabilizing or reducing light vehicle fuel use, oil use, and/or carbon emissions over the next 50 years are presented. Case 1 - Improve mpg so that the fuel use in 2020 is stabilized for the next 30 years. Case 2 - Improve mpg so that by 2030 the fuel use is reduced to the 2000 level and is reduced further in subsequent years. Case 3 - Case 1 plus 50% ethanol use and 50% low-carbon fuel cell vehicles by 2050. Case 4 - Case 2 plus 50% ethanol use and 50% low-carbon fuel cell vehicles by 2050. The mpg targets for new cars and light trucks require that significant advances be made in developing cost-effective and very efficient vehicle technologies.

Fuel cell vehicles are currently undergoing extensive research and development because of their potential for high efficiency and low emissions. A complete well-to-wheels evaluation is helpful when considering the introduction of advanced vehicles that could use a new fuel, such as hydrogen. Several modeling tools developed by Argonne National Laboratory were used to evaluate the impact of several new vehicle configurations. A transient vehicle simulation software code, PSAT (Powertrain System Analysis Toolkit), was used with a transient fuel cell model derived from GCTool (General Computational Toolkit); and GREET (Greenhouse gases, Regulated Emissions and Energy use in Transportation) was employed in estimating well-to-tank performances. This paper compares the well-to-wheels impacts of several advanced SUVs, including conventional, parallel and series hybrid-electric and fuel cell vehicles.

This paper introduces a new systematic workflow for the rapid evaluation of energy-efficient automated driving controls in real vehicles in controlled laboratory conditions. This vehicle-in-the-loop (VIL) workflow, largely standardized and automated, is reusable and customizable, saves time and minimizes costly dynamometer time. In the first case study run with the VIL workflow, an automated car driven by an energy-efficient driving control previously developed at Argonne used up to 22 % less energy than a conventional control. In a VIL experiment, the real vehicle, positioned on a chassis dynamometer, has a digital twin that drives in a virtual world that replicates real-life situations, such as approaching a traffic signal or following other vehicles.

The National Highway Traffic Safety Administration (NHTSA) plays a crucial role in guiding the formulation of Corporate Average Fuel Economy (CAFE) standards, and at the forefront of this regulatory process stands Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy (DOE) research institution, has developed Autonomie—an advanced and comprehensive full-vehicle simulation tool that has solidified its status as an industry standard for evaluating vehicle performance, energy consumption, and the effectiveness of various technologies. Under the purview of an Inter-Agency Agreement (IAA), the DOE Argonne Site Office (ASO) and Argonne have assumed the responsibility of conducting full-vehicle simulations to support NHTSA's CAFE rulemaking initiatives. This paper introduces an innovative approach that hinges on a large-scale simulation process, encompassing standard regulatory driving cycles tailored to various vehicle classes and spanning diverse timeframes.

The U.S. Environmental Protection Agency instrumented and tested a line-haul Class 8 tractor trailer on a 4-wheel-drive heavy-duty chassis dynamometer. A vehicle model was then developed in the Powertrain Systems Analysis Toolkit (PSAT), Argonne National Laboratory's vehicle simulation tool, using the truck technical specifications and the recorded data, which included the Portable Emissions Measurement System (PEMS) and Controller Area Network (CAN) signals. In this paper, we describe the test scenarios and the analysis performed on the data. We then present the vehicle model and assumptions. Finally, we compare the test and simulation data, including fuel consumption and component signals, as well as the main challenges specific to heavy-duty vehicle testing and simulation.

Hybrid electric vehicles (HEVs) combine two sources of energy and offer a wide variety of component and drivetrain configurations. However, optimizing the blending of these two energy sources is complex. Argonne National Laboratory (ANL) working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT allows users to choose the best configuration and to optimize the control strategy in simulations. The importance of component models and the complexity involved in setting up optimized control laws require validation of the models and control strategies developed in PSAT. In this paper, we first describe our capability to validate each component model with an actual component test, using test stand facilities. Once each component model has been validated, ANL can perform tests on a whole HEV by using a chassis dynamometer.

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).

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. Aerodynamic drag can also be reduced by close-gap platooning using information from vehicle-to-vehicle communications. In order to achieve these goals, the designers of control strategies need to simulate a wide range of driving situations in which vehicles interact with other vehicles and the infrastructure in a closed-loop fashion. RoadRunner is a new model-based system engineering platform based on Autonomie software, which can collectively provide the necessary tools to predict energy consumption for various driving decisions and scenarios such as car-following, free-flow, or eco-approach driving, and thereby can help in developing control algorithms.

The successful commercialization of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) can provide significant benefits by reducing the United States' growing dependence on petroleum fuels for transportation; decreasing polluting and greenhouse gas emissions; and facilitating a long-term transition to sustainable renewable energy sources. Recognizing these benefits, the U.S. Department of Energy (DOE) supports an active program of long-range R&D to develop electric vehicle (EV) and hybrid electric vehicle (HEV) technologies and to accelerate their commercialization. The DOE Office of Advanced Automotive Technologies (OAAT) supports several innovative R&D programs, conducted in partnership with DOE's national laboratories, industry, other government agencies, universities, and small businesses. The Office has two key R&D cooperative agreements with the U.S. Advanced Battery Consortium (USABC) to develop high-energy batteries for EVs and high-power batteries for HEVs.

Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie. Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data.

This paper reports our efforts to develop an instrument, TG-1, to measure particulate emissions from diesel engines in real-time. TG-1 while based on laser-induced incandescence allows measurements at 10 Hz on typical engine exhausts. Using such an instrument, measurements were performed in the exhaust of a 1.7L Mercedes Benz engine coupled to a low-inertia dynamometer. Comparative measurements performed under engine steady state conditions showed the instrument to agree within ±12% of measurements performed with an SMPS. Moreover, the instrument had far better time response and time resolution than a TEOM® 1105. Also, TG-1 appears to surpass the shortcomings of the TEOM instrument, i.e., of yielding negative values under certain engine conditions and, being sensitive to external vibration.

Hydrogen is considered one of the most promising future energy carriers. There are several challenges that must be overcome in order to establishing a “hydrogen economy”, including the development of a practical, efficient, and cost-effective power conversion device. Using hydrogen as a fuel for internal combustion engines is a huge step toward developing a large-scale hydrogen infrastructure. This paper summarizes the testing of a hydrogen powered pick-up truck on a chassis dynamometer. The vehicle is powered by a port-injected 8-cylinder engine with an integrated supercharger and intercooler. The 4-wheel drive chassis dynamometer is equipped with a hydrogen delivery, metering and safety system as well as hydrogen specific instrumentation. This instrumentation includes numerous sensors, includes a wide-band lambda sensor and an exhaust gas hydrogen analyzer. This analyzer quantifies the amount of unburned hydrogen in the exhaust indicating the completeness of the combustion.

Hybrid electric vehicles (HEVs) have seen tremendous improvements in performance, fuel economy and cost over the last two decades. As battery and motor prices decrease, HEVs are likely to be even more attractive to consumers. This study considers how HEVs can improve and whether advancements in engines and other components will play a large role in the HEV segment. Past studies have relied on a rule-based component sizing approach for hybrids to meet certain performance criteria. By going beyond this approach, we can explore the design space by varying engine power and electric drivetrain power. This can provide more insights into the fuel-saving potential of HEVs, and the trade-offs required on performance or cost characteristics to achieve those savings. In this study, we examine the fuel-saving potential of three main hybrid powertrain architectures (parallel, series, and power-split) with varying degrees of hybridization (DOH) and using various engine technologies.

An increase in spark-ignition engine efficiency can be gained by increasing the engine compression ratio, which requires fuels with higher knock resistance. Oxygenated fuel components, such as methanol, ethanol, isopropanol, or iso-butanol, all have a Research Octane Number (RON) higher than 100. The octane numbers (ON) of fuels are rated on the CFR F1/F2 engine by comparing the knock intensity of a sample fuel relative to that of bracketing primary reference fuels (PRF). The PRFs are a binary blend of iso-octane, which is defined to an ON of 100, and n-heptane, which represents an ON of 0. Above 100 ON, the PRF scale continues by adding diluted tetraethyl lead (TEL) to iso-octane. However, TEL is banned from use in commercial gasoline because of its toxicity. The ASTM octane number test methods have a “Fit for Use” test that validate the CFR engine’s compliance with the octane testing method by verifying the defined ON of toluene standardization fuels (TSF).

Recent advances in fuel-cell technology and low-emission, direct-injection spark-ignition and diesel engines for vehicles could significantly change the transportation vehicle power plant landscape in the next decade or so. This paper is a scoping study that compares total fuel cycle options for providing power to personal transport vehicles. The key question asked is, “How much of the energy from the fuel feedstock is available for motive power?” Emissions of selected criteria pollutants and greenhouse gases are qualitatively discussed. This analysis illustrates the differences among options; it is not intended to be exhaustive. Cases considered are hydrogen fuel from methane and from iso-octane in generic proton-exchange membrane (PEM) fuel-cell vehicles, methane and iso-octane in spark-ignition (SI) engine vehicles, and diesel fuel (from methane or petroleum) in direct-injection (DI) diesel engine vehicles.

This paper introduces control strategy analysis and performance degradation for the 2010 Toyota Prius under different thermal conditions. The goal was to understand, in as much detail as possible, the impact of thermal conditions on component and vehicle performances by analyzing a number of test data obtained under different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory. A previous study analyzed the control behavior and performance under a normal ambient temperature; thus the first step in this study was to focus on the impact when the ambient temperature is cold or hot. Based on the analyzed results, thermal component models were developed in which the vehicle controller in the simulation was designed to mimic the control behavior when temperatures of the components are cold or hot. Further, the performance degradation of the components was applied to the mathematical models based on analysis of the test data.

A detailed description of a numerical method for computing unsteady flows in engine intake and exhaust systems is given. The calculations include the effects of heat transfer and friction. The inclusion of such calculations in a mathematically simulated engine cycle is discussed and results shown for several systems. In particular, the effects of bell-mouth versus plain pipe terminations and the effects of a finite surge tank are calculated. Experimental data on the effect of heat transfer from the back of the intake valve on wave damping are given and show the effect to be negligible. Experimental data on wave damping during the valve closed period and on the temperature rise of the air near the valve are also given.

The ratio of two temperature gradients across the combustion-chamber wall in a diesel engine is used to provide a heat flow ratio showing the radiant heat transfer as a per cent of local total heat transfer. The temperature gradients were obtained with a thermocouple junction on each side of the combustion-chamber wall. The first temperature gradient was obtained by covering the thermocouple at the cylinder gas-wall interface with a thin sapphire window, while the second was obtained without the window. Results show that the time-average radiant heat transfer is of significant magnitude in a diesel engine, and is probably even more significant in heat transfer during combustion and expansion.

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among U.S. automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future “top-selling” HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, with methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020.

A two-stage Delphi study was conducted to collect information that would enable a technical and economic assessment of electric (EV) and hybrid electric (HEV) vehicles. The first-stage worldwide survey was completed in fall 1994 while the second-stage was completed by summer 1995. The paper reports results from the second round of the survey and the major differences between the two rounds. This second-stage international survey obtained information from 93 expert respondents from the automotive technology field. The second stage response provided the following key results. EVs will penetrate the market first followed by internal combustion engine powered HEVs while gas turbine and fuel cell powered HEVs will not have any significant penetration until after 2020. By 2020 EVs and internal combustion engine powered HEVs are projected to have approximately a 15% share of the new vehicle market.