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The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission.

Chassis dynamometer tests were conducted on three Class III on-highway motorcycles produced for the North American market and equipped with advanced emission control technologies in order to inform emissions inventories and compare the impacts of existing Tier 2 (E0) fuel with more market representative Tier 3 and LEV III certification fuels with 10% ethanol. For this study, the motorcycles were tested over the US Federal Test Procedure (FTP) and the World Motorcycle Test Cycle (WMTC) certification test cycles as well as a sample of real-world motorcycle driving informally referred to as the Real World Driving Cycle (RWDC). The primary interest was to understand the emissions changes of the selected motorcycles with the use of certification fuels containing 10% ethanol compared to 0% ethanol over the three test cycles.

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.

This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

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.

Chassis dynamometer testing was conducted with three on-highway motorcycles produced for the North American market with engine displacements of 296 cc, 749 cc and 1198 cc to better inform criteria pollutant emissions inventories. The motorcycles were tested using US Tier 2 certification fuel over the Federal Test Procedure (FTP), World Motorcycle Test Cycle (WMTC) and a cycle based on a sample of real-world motorcycle driving, informally referred to as the ‘Real World Driving Cycle’ (RWDC). Emissions characterization includes composite, individual test phase and 1Hz cumulative results for various criteria pollutants for each test cycle. Overall, it was found that the higher peak speed rates and peak torque levels observed during the RWDC are more fully represented in the WMTC than the FTP. The use of the WMTC and RWDC cycles generally translated into higher emissions rates compared to the FTP and in particular for nitrogen oxides and carbon monoxide.

In-use, light-duty vehicles were recruited in Cary, North Carolina for emissions testing on a transportable dynamometer in 1999. Two hundred forty-eight vehicles were tested in as received condition using the IM240 driving cycle. The study was conducted in two phases, a summer and winter phase, with half of the vehicles recruited during each phase. Regulated emissions, PM10, carbonaceous PM, aldehydes and ketones were measured for every test. PM2.5, individual volatile hydrocarbons, polycyclic aromatic hydrocarbons, sterane and hopane emissions were measured from a subset of the vehicles. Average light-duty gasoline PM10 emission rates increased from 6.5 mg/mi for 1993-97 vehicles to 53.8 mg/mi for the pre-1985 vehicles. The recruited fleet average, hot-stabilized IM240 PM10 emission rate for gasoline vehicles was 19.0 mg/mi.

To investigate the feasibility of various test procedures to determine aerodynamic performance for the Phase 2 Greenhouse Gas (GHG) Regulations for Heavy-Duty Vehicles in the United States, the US Environmental Protection Agency commissioned, through Southwest Research Institute, constant-speed torque tests of several heavy-duty tractors matched to a conventional 53-foot dry-van trailer. Torque was measured at the transmission output shaft and, for most tests, also on each of the drive wheels. Air speed was measured onboard the vehicle, and wind conditions were measured using a weather station placed along the road side. Tests were performed on a rural road in Texas. Measuring wind-averaged drag from on-road tests has historically been a challenge. By collecting data in various wind conditions at multiple speeds over multiple days, a regression-based method was developed to estimate wind-averaged drag with a low precision error for multiple tractor-trailer combinations.

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.

To make an HCCI engine as a useful commercial product, the engine has to be capable of performing quick transients in a large operating range, especially in vehicle applications. HCCI combustion is kinetically controlled and has to be operated properly between two limits: misfire and knock. To achieve the correct state, the right amount of fuel/air/EGR has to be inducted into the cylinder. The amounts and ratios of the three components are highly dependent on other variables as operating conditions change. It is unrealistic and unreliable to predict the right combination of these variables without principal component analysis. Thus, the optimal response control path has to be based on the quality of the previous combustion event as well as the direction and the rate of transition.

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.