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The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.

A methodology for evaluating life cycle cost of electric vehicles (EVs) to their buyers is presented. The methodology is based on an analysis of conventional vehicle costs, costs of drivetrain and auxiliary components unique to EVs, and battery costs. The conventional vehicle's costs are allocated to such subsystems as body, chassis, and powertrain. In electric vehicles, an electric drive is substituted for the conventional powertrain. The current status of the electric drive components and battery costs is evaluated. Battery costs are estimated by evaluating the material requirements and production costs at different production levels; battery costs are also collected from other sources. Costs of auxiliary components, such as those for heating and cooling the passenger compartment, are also estimated. Here, the methodology is applied to two vehicle types: subcompact car and minivan.

Use of ethanol as gasoline replacement can contribute to the reduction of nitrogen oxide (NOx) and carbon oxide (CO) emissions. Depending on ethanol production, significant reduction of greenhouse-gas emissions is possible. Concentration of certain species, such as unburned ethanol and acetaldehyde in the engine-out emissions are known to rise when ratio of ethanol to gasoline increases in the fuel. This research explores on hydrous ethanol fueled port-fuel injection (PFI) spark ignition (SI) engine emissions that contribute to photochemical formation of ozone, or so-called ozone precursors and the precursor of peroxyacetyl nitrates (PANs). The results are compared to engine operation on gasoline. Concentration obtained by FTIR gas analyzer, and mass-specific emissions of formaldehyde (HCHO), acetaldehyde (MeCHO) and methane (CH4) under two engine speed, four load and two spark advance settings are analyzed and presented.

The 2001 FutureTruck competition involved 15 universities from across North America that were invited to apply a wide range of advanced technologies to improve energy efficiency and reduce greenhouse gas impact while producing near-zero regulated exhaust emissions in a 2000 Chevrolet Suburban. The modified vehicles designated as FutureTrucks demonstrated improvements in greenhouse gas emissions, tailpipe emissions, and over-the-road fuel economy compared with the stock vehicle on which they were based. The technologies represented in the vehicles included ICE-engines and fuel cell hybrid electric vehicle propulsion systems, a range of conventional and alternative fuels, advanced exhaust emissions controls, and light weighting technologies.

In June of 2002, 15 universities participated in the third year of FutureTruck, an advanced vehicle competition sponsored by the U.S. Department of Energy and Ford Motor Company. Using advanced technologies, teams strived to improve vehicle energy efficiency by at least 25%, reduce tailpipe emissions to ULEV levels, and lower greenhouse gas impact of a 2002 Ford Explorer. The competition vehicles were tested for dynamic performance and emissions and were judged in static events to evaluate the design and features of the vehicle. The dynamic events include braking, acceleration, handling, and fuel economy, while the dynamometer testing provided data for both the emissions event and the greenhouse gas event. The vehicles were scored for their performance in each event relative to each other; those scores were summed to determine the winner of the competition. The competition structure included different available fuels and encouraged the use of hybrid electric drivetrains.

The Battery Performance and Cost Model (BatPaC), developed by Argonne National Laboratory, is a versatile tool designed for lithium-ion battery (LIB) pack engineering. It accommodates user-defined specifications, generating detailed bill-of-materials calculations and insights into cell dimensions and pack characteristics. Pre-loaded with default data sets, BatPaC aids in estimating production costs for battery packs produced at scale (5 to 50 GWh annually). Acknowledging inherent uncertainties in parameters, the tool remains accessible and valuable for designers and engineers. BatPaC plays a crucial role in National Highway Transportation Traffic Safety Administration (NHTSA) regulatory assessments, providing estimated battery pack manufacturing costs and weight metrics for electric vehicles. Integrated with Argonne's Autonomie simulations, BatPaC streamlines large-scale processes, replacing traditional models with lookup tables.

This paper analyzes four recent major studies carried out by MIT, a GM-led team, Directed Technologies, Inc., and A. D. Little, Inc. to assess advanced technology vehicles. These analyses appear to differ greatly concerning their perception of the energy benefits of advanced technology vehicles, leading to great uncertainties in estimating full-fuel-cycle (or “well-to-wheel”) greenhouse gas (GHG) emission reduction potentials and/or fuel feedstock requirements per mile of service. Advanced vehicles include, but are not limited to, advanced gasoline and diesel internal combustion engine (ICE) vehicles, hybrid electric vehicles (HEVs) with gasoline, diesel, and compressed natural gas (CNG) ICEs, and various kinds of fuel-cell based vehicles (FCVs), such as direct hydrogen FCVs and gasoline or methanol fuel-based FCVs.

This paper analyzes fuel economy benefits of direct hydrogen and gasoline reformer fuel cell vehicles, with special focus on cold-start impacts on these fuel cell based vehicles. Comparing several existing influential studies reveals that the most probable estimates from these studies differ greatly on the implied benefits of both types of fuel cell vehicles at the tank-to-wheel level (vehicle-powertrain efficiency and/or specific power), leading to great uncertainties in estimating well-to-wheel fuel energy and/or greenhouse gas (GHG) emission reduction potentials. This paper first addresses methodological issues to influence the outcome of these analyses. With one exception, we find that these studies consistently ignore cold-start and warm-up issues, which play important roles in determining both energy penalties and start-up time of fuel cell vehicles. To better understand cold-start and warm-up behavior, this paper examines approaches and results based on two available U.S.

To reduce development time and introduce technologies faster to the market, many companies have been turning more and more to Model Based Design. In Model Based Design, the development process centers around a system model, from requirements capture and design to implementation and test. Engineers can skip over a generation of system design processes on the basis of hand coding and use graphical models to design, analyze, and implement the software that determines machine performance and behavior. This paper describes the process implemented in Autonomie, a Plug-and-Play Software Environment, to design and evaluate component hardware in an emulated environment. We will discuss best practices and provide an example through evaluation of advanced high-energy battery pack within an emulated Plug-in Hybrid Electric Vehicle.

The U.S. Renewable Fuel Standard (RFS2) requires an increase in the use of advanced biofuels up to 36 billion gallons by 2022. Longer chain alcohols, in addition to cellulosic ethanol and synthetic biofuels, could be used to meet this demand while adhering to the RFS2 corn-based ethanol limitation. Higher carbon number alcohols can be utilized to improve the energy content, knock resistance, and/or petroleum displacement of gasoline-alcohol blends compared to traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part I of this paper focuses on the development of scenarios by which to compare higher alcohol fuel blends to traditional ethanol blends. It also details the implementation of fuel property prediction methods adapted from literature. Possible combinations of eight alcohols mixed with a gasoline blendstock were calculated and the properties of the theoretical fuel blends were predicted.

Higher carbon number alcohols offer an opportunity to meet the Renewable Fuel Standard (RFS2) and improve the energy content, petroleum displacement, and/or knock resistance of gasoline-alcohol blends from traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part II of this paper builds upon the alcohol selection, fuel implementation scenarios, criteria target values, and property prediction methodologies detailed in Part I. For each scenario, optimization schemes include maximizing energy content, knock resistance, or petroleum displacement. Optimum blend composition is very sensitive to energy content, knock resistance, vapor pressure, and oxygen content criteria target values. Iso-propanol is favored in both scenarios' suitable blends because of its high RON value.

The CFR F1 engine is the standard testing apparatus used for rating the research octane number (RON) of gasoline fuels. Unlike the motor octane number (MON) method, where the intake port temperature after the carburetor is controlled by an electric heater, the mixture temperature can vary during the RON test due to the heat of vaporization (HoV) of the fuel. Ethanol is receiving increasing attention as a high octane and high HoV fuel component. This work presents an analysis of the combustion characteristics during the RON rating of ethanol fuel blends according to the standard ASTM D2699 method, highlighting the effects of ethanol concentration and base fuel composition. All fuels were blended to a constant RON of 98. Ethanol levels varied from 0 to 50 vol% and the base fuels were surrogate blends composed of primary reference fuels (PRF), toluene standardization fuels (TSF), and a four component gasoline surrogate.

Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. When considering the introduction of advanced vehicles, a complete well-to-wheel evaluation must be performed to determine the potential impact of a technology on carbon dioxide and Green House Gases (GHGs) emissions. Several modeling tools developed by Argonne National Laboratory (ANL) were used to evaluate the impact of advanced powertrain configurations. The Powertrain System Analysis Toolkit (PSAT) transient vehicle simulation software was used with a variety of fuel cell system models derived from the General Computational Toolkit (GCtool) for pump-to-wheel (PTW) analysis, and GREET (Green house gases, Regulated Emissions and Energy use in Transportation) was used for well-to-pump (WTP) analysis. This paper compares advanced propulsion technologies on a well-to-wheel energy basis by using current technology for conventional, hybrid and fuel cell technologies.

To properly compare and contrast the environmental performance of one vehicle technology against another, it is necessary to consider their production, operation, and end-of-life fates. Since 1995, Argonne’s GREET® life cycle analysis model (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) has been annually updated to model and refine the latest developments in fuels and materials production, as well as vehicle operational and composition characteristics. Updated cradle-to-grave life cycle analysis results from the model’s latest release are described for a wide variety of fuel and powertrain options for U.S. light-duty and medium/heavy-duty vehicles. Light-duty vehicles include a passenger car, sports utility vehicle (SUV), and pick-up truck, while medium/heavy-duty vehicles include a Class 6 pickup-and-delivery truck, Class 8 day-cab (regional) truck, and Class 8 sleeper-cab (long-haul) truck.

The correlations between the physical properties and autoignition parameters of several alternate fuels have been examined. The fuels are DF-2 and its blends with petroleum derived fuels, coal derived fuels, shale derived fuels, high aromatic naphtha sun-flower oils, methanol and ethanol. A total of eighteen existing correlations are discussed. An emphasis is made on the suitability of each of the correlations for the development of electronic controls for diesel engines when run on alternate fuels. A new correlation has been developed between the cetane number of the fuels and its kinematic viscosity and specific gravity.

A heavy-duty vehicle (HDV) module of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREETTM) model has been developed at Argonne National Laboratory. The fuel-cycle GREET model has been published extensively and contains data on fuel-cycles and vehicle operation of light-duty vehicles. The addition of the HDV module to the GREET model allows for well-to-wheel (WTW) analyses of heavy-duty advanced technology and alternative fuel vehicles (AFVs), which has been lacking in the literature. WTW analyses of HDVs becomes increasingly important to understand the fuel consumption and greenhouse gas (GHG) emissions impacts of newly enacted and future HDV regulations from the Environmental Protection Agency and the Department of Transportation’s National Highway Traffic Safety Administration.

Detailed properties of particulate matter (PM) emissions from a gasoline direct injection (GDI) engine were analyzed in terms of size, morphology, and nanostructures, as gasoline and its ethanol blend E20 were used as a fuel. PM emissions were sampled from a 0.55L single-cylinder GDI engine by means of a scanning mobility particle sizer (SMPS) for size measurements and a self-designed thermophoretic sampling device for the subsequent analyses of size, morphology and nanostructures using a transmission electron microscope (TEM). The particle sizes were evaluated with variations of air-fuel equivalence ratio and fuel injection timing. The most important result from the SMPS measurements was that the number of nucleation-mode nanoparticles (particularly those smaller than 10 - 15 nm) increased significantly as the fuel injection timing was advanced to the end-of-injection angle of 310° bTDC.

This paper presents the vehicle model development and validation process for the Ford Focus battery electric vehicles (BEVs) using Autonomie and test results from Advanced Powertrain Research Facility in Argonne National Laboratory. The parameters or characteristic values for the important components such as the electric machine and battery pack system are estimated through analyzing the test data of the multi cycle test (MCT) procedure under the standard ambient condition. A novel process was used to import vehicle test data into Autonomie. Through this process, a complete vehicle model of the Ford Focus BEV is developed and validated under ambient temperature for different drive cycles (UDDS, HWFET, US06 and Steady-State). The simulation results of the developed vehicle model show coincident results with the test data within 0.5% ∼ 4% discrepancies for electrical consumption.

Low temperature combustion through in-cylinder blending of fuels with different reactivity offers the potential to improve engine efficiency while yielding low engine-out NOx and soot emissions. A Navistar MaxxForce 13 heavy-duty compression ignition engine was modified to run with two separate fuel systems, aiming to utilize fuel reactivity to demonstrate a technical path towards high engine efficiency. The dual-fuel engine has a geometric compression ratio of 14 and uses sequential, multi-port-injection of a low reactivity fuel in combination with in-cylinder direct injection of diesel. Through control of in-cylinder charge reactivity and reactivity stratification, the engine combustion process can be tailored towards high efficiency and low engine-out emissions. Engine testing was conducted at 1200 rpm over a load sweep.