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As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a 2018 Toyota Camry front wheel drive eight-speed automatic transmission was benchmarked. The benchmarking data were used as inputs to EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model to estimate GHG emissions from light-duty vehicles. ALPHA requires both detailed engine fuel consumption maps and transmission torque loss maps. EPA’s National Vehicle and Fuels Emissions Laboratory has developed a streamlined, cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to characterize transmissions within ALPHA. This testing methodology targets the range of transmission operation observed during vehicle testing over EPA’s city and highway drive cycles.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to estimate greenhouse gas (GHG) emissions from light-duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. In order to model the behavior of current and future vehicles, an algorithm was developed to dynamically generate transmission shift logic from a set of user-defined parameters, a cost function (e.g., engine fuel consumption) and vehicle performance during simulation. This paper presents ALPHA's shift logic algorithm and compares its predicted shift points to actual shift points from a mid-size light-duty vehicle and to the shift points predicted using a static table-based shift logic as calibrated to the same vehicle during benchmark testing.

The U.S. Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been refined and revalidated using newly acquired data from model year 2013-2016 engines and vehicles. The robustness of EPA’s vehicle and engine testing for the MTE coupled with further validation of the ALPHA model has highlighted some areas where additional data can be used to add fidelity to the engine model within ALPHA.

Motor vehicle emission testing during on-road driving is important to assess a vehicle’s exhaust emission control design, its compliance with Federal regulations and its impact on air quality. The U.S. Environmental Protection Agency (EPA) has been developing new approaches to screen the characteristics of vehicle dynamic emission control behaviors (its operating signature) while driving both on-road and on-dynamometer. The so-called “signature device” used for this testing is equipped with an O2/NOx sensor, thermocouple and GPS to record dynamic exhaust NOx concentration, air fuel ratio-controlled tailpipe lambda (λ), tailpipe temperature and vehicle speed (acceleration). In the early EPA research, signature screening was used to characterize a vehicle’s PCM control behaviors (cause/effect bijectivity), which help distinguish operation in normal control state-space and abnormal state-space.

The increasing numbers of hybrid electric and full electric vehicle models currently in the market or in the pipeline of automotive OEMs require creative testing mechanisms to drive down development costs and optimize the efficiency of these vehicles. In this paper, such a testing mechanism that has been successfully implemented at the US Environmental Protection Agency National Vehicle and Fuel Emissions Laboratory (EPA NVFEL) is described. In this testing scheme, the units-under-test consist of a battery pack and its associated battery management system (BMS). The remaining subsystems, components, and environment of the vehicle are virtual and modeled in high fidelity.

This paper summarizes the Heavy-Duty In-Use Testing (HDUIT) measurement allowance program for Particulate Matter Portable Emissions Measurement Systems (PM-PEMS). The measurement allowance program was designed to determine the incremental error between PM measurements using the laboratory constant volume sampler (CVS) filter method and in-use testing with a PEMS. Two independent PM-PEMS that included the Sensors Portable Particulate Measuring Device (PPMD) and the Horiba Transient Particulate Matter (TRPM) were used in this program. An additional instrument that included the AVL Micro Soot Sensor (MSS) was used in conjunction with the Sensors PPMD to be considered a PM-PEMS. A series of steady state and transient tests were performed in a 40 CFR Part 1065 compliant engine dynamometer test cell using a 2007 on-highway heavy-duty diesel engine to quantify the accuracy and precision of the PEMS in comparison with the CVS filter-based method.

As part of an ongoing assessment of the potential for reducing greenhouse gas (GHG) emissions of light-duty vehicles, the U.S. Environmental Protection Agency (EPA) has implemented an updated methodology for applying the results of full vehicle simulations to the range of vehicles across the entire fleet. The key elements of the updated methodology explored for this article, responsive to stakeholder input on the EPA’s fleet compliance modeling, include (1) greater transparency in the process used to determine technology effectiveness and (2) a more direct incorporation of full vehicle simulation results. This article begins with a summary of the methodology for representing existing technology implementations in the baseline fleet using EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation. To characterize future technologies, a full factorial ALPHA simulation of every conventional technology combination to be considered was conducted.

With increasingly stringent light duty particulate emissions regulations, it is of great interest to better understand particulate matter formation. Helping to build the knowledge base for a thorough understanding of particulate matter formation will be an essential step in developing effective control strategies. It is especially important to do this in such a way as to emulate real driving behaviors, including cold starts and transients. To this end, this study examined particulate emissions during transient operation in a recent model year vehicle equipped with a GDI engine. Three of the major federal test cycles were selected as evaluation schemes: the FTP, the HWFET, and the US06. These cycles capture much of the driving behaviors likely to be observed in typical driving scenarios. Measurements included particle size distributions from a TSI EEPS fast-response particle spectrometer, as well as real-time soot emissions from an AVL MSS soot sensor.

As part of its technology assessment for the upcoming midterm evaluation (MTE) of the 2022-2025 Light-Duty Vehicle Greenhouse Gas (LD GHG) emissions standards, EPA has been benchmarking engines and transmissions to generate inputs for use in its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) model, a physics-based, forward-looking, full vehicle computer simulation tool. One of the most efficient engines today, a 2.0L Mazda SkyActiv engine, is of particular interest due to its high geometric compression ratio and use of an Atkinson cycle. EPA benchmarked the 2.0L SkyActiv at its National Vehicle and Fuel Emissions laboratory. EPA then incorporated ALPHA into an engine dynamometer control system so that vehicle chassis testing could be simulated with a hardware-in-the-loop (HIL) approach.

The Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles[1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all internal energy flows in the model. The software tool is a MATLAB/Simulink based desktop application. In preparation for the midterm evaluation of the light-duty GHG emission standards for model years 2022-2025, EPA is refining and revalidating ALPHA using newly acquired data from model year 2013-2015 engines and vehicles.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data.

As part of the Midterm Evaluation of the 2017-2025 Light-duty Vehicle Greenhouse Gas Standards, the U.S. Environmental Protection Agency (EPA) developed simulation models for studying the effectiveness of stop-start technology for reducing CO2 emissions from light-duty vehicles. Stop-start technology is widespread in Europe due to high fuel prices and due to stringent EU CO2 emissions standards beginning in 2012. Stop-start has recently appeared as a standard equipment option on high-volume vehicles like the Chevrolet Malibu, Ford Fusion, Chrysler 200, Jeep Cherokee, and Ram 1500 truck. EPA has included stop-start technology in its assessment of CO2-reducing technologies available for compliance with the standards. Simulation and modeling of this technology requires a suitable model of the battery. The introduction of stop-start has stimulated development of 12-volt battery systems capable of providing the enhanced performance and cycle life durability that it requires.

The U.S. Environmental Protection Agency, U.S. Department of Transportation's National Highway and Traffic Safety Administration, and the California Air Resources Board have recently released proposed new regulations for greenhouse gas emissions and fuel economy for light-duty vehicles and trucks in model years 2017-2025. These proposed regulations intend to significantly reduce greenhouse gas emissions and increase fleet fuel economy from current levels. At the fleet level, these rules the proposed regulations represent a 50% reduction in greenhouse gas emissions by new vehicles in 2025 compared to current fleet levels. At the same time, global growth, especially in developing economies, should continue to drive demand for crude oil and may lead to further fuel price increases. Both of these trends will therefore require light duty vehicles (LDV) to significantly improve their greenhouse gas emissions over the next 5-15 years to meet regulatory requirements and customer demand.

This study is the second in a series of three EPA studies to investigate the effect of fuel reformulations and modifications on exhaust emissions. Both the first and second study in this series of studies were used to support the development of EPA's complex model for the certification of reformulated gasolines. Phase I of the study tested eight fuels on forty vehicles. This study, termed Phase II, tested twelve fuels on a separate fleet of 39 light-duty vehicles. The Phase II fuel parameters studied included Reid Vapor Pressure (RVP), the 50% and 90% evaporated distillation temperatures (T50 and T90), sulfur content, aromatics content, olefin content, oxygenate type and oxygen content. Measured exhaust emissions included total hydrocarbons (THC), oxides of nitrogen (NOx), carbon monoxide (CO), carbon dioxide (CO2), benzene, 1,3-butadiene, acetaldehyde and formaldehyde.

This study was the first of three EPA studies to investigate the effect of gasoline fuel parameters on hydrocarbon, nonmethane hydrocarbon, nitrogen oxides, benzene, formaldehyde, and acetaldehyde exhaust emissions of 1990 model year or equivalent vehicles. The fuel parameters tested in this program were oxygen concentration, Reid Vapor Pressure (RVP), ninety percent evaporative distillation temperature (T90), and sulfur concentration. Sulfur concentration was found to have the greatest effect on hydrocarbon and nitrogen oxide emissions. Increasing oxygen concentration and RVP reduction was found to reduce hydrocarbon emission more for high-emitting than normal-emitting vehicles. Oxygenate concentration was found to have a significant effect on aldehyde emissions.

By almost any definition, technology has penetrated the U.S. light-duty vehicle fleet significantly in conjunction with the increased stringency of fuel economy and GHG emissions regulations. The physical presence of advanced technology components provides one indication of the efforts taken to reduce emissions, but that alone does not provide a complete measure of the benefits of a particular technology application. Differences in the design of components, the materials used, the presence of other technologies, and the calibration of controls can impact the performance of technologies in any particular implementation. The effectiveness of a technology for reducing emissions will also be influenced by the extent to which the technologies are applied towards changes in vehicle operating characteristics such as improved acceleration, or customer features that may offset mass reduction from the use of lightweight materials.

The Environmental Protection Agency (EPA) has collected a variety of engine and vehicle test data to assess the effectiveness of new automotive technologies in meeting greenhouse gas (GHG) and criteria emission standards and to monitor their behavior in real world operation. EPA’s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate GHG emissions from vehicles using various combinations of advanced technologies and has been refined using data from testing conducted at EPA’s National Vehicle and Fuel Emissions Laboratory. This paper describes a process for constructing complete engine maps using engine dynamometer and in-vehicle test data for use in ALPHA or any other full vehicle simulation which performs similar analyses. The paper reviews how to use available steady state and transient test data to characterize different operating conditions, and then combine the data to construct a complete engine map suitable for ALPHA model simulation.

Portable Emission Measurement Systems (PEMS) are used by the U.S. Environmental Protection Agency (EPA) to measure gaseous and particulate mass emissions from vehicles in normal, in-use, on-the-road operation to support many of its programs, including assessing mobile source emissions compliance, emissions factor assessment for in-use fleet modeling, and collection of in-use vehicle operational data to support vehicle simulation modeling programs. This paper discusses EPA’s use of Global Positioning System (GPS) measured altitude data and electronically logged vehicle speed data to provide real-world road grade data for use as an input into the Gamma Technologies GT-DRIVE+ vehicle model. The GPS measured altitudes and the CAN vehicle speed data were filtered and smoothed to calculate the road grades by using open-source Python code and associated packages.

Light-duty vehicle greenhouse gas (GHG) and fuel economy (FE) standards for MYs 2012-2025 are requiring vehicle powertrains to become much more efficient. One key technology strategy that vehicle manufacturers are using to help comply with GHG and FE standards is to replace naturally aspirated engines with smaller displacement “downsized” boosted engines. In order to understand and measure the effects of this technology, the Environmental Protection Agency (EPA) benchmarked a 2013 Ford Escape with an EcoBoost® 1.6L engine. This paper describes a “tethered” engine dyno benchmarking method used to develop a fuel efficiency map for the 1.6L EcoBoost® engine. The engine was mounted in a dyno test cell and tethered with a lengthened engine wire harness to a complete 2013 Ford Escape vehicle outside the test cell. This method allowed engine mapping with the stock ECU and calibrations.

In light-duty vehicles, there is a fundamental trade-off between fuel consumption and acceleration performance, if other vehicle attributes are held fixed. Earlier econometric studies have estimated the magnitude of this trade-off - the elasticity of fuel consumption with respect to performance - based on historical vehicle data. The majority of these studies assume, a priori, that elasticity is constant across the model year, vehicle power, and technology content. However, there is evidence that the content in the underlying powertrain technology packages is shifting in a way that reduces the value of the elasticity of fuel consumption with respect to performance, such that historical trends would not predict future behavior. This paper presents an alternative strategy for studying vehicle fuel consumption versus performance trade-off.