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With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

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.

Energy security and climate change challenges provide a strong impetus for investigating Electric Vehicle (EV) concepts. EVs link two major infrastructures, the transportation and the electric power grid. This provides a chance to bring other sources of energy into transportation, displace petroleum and, with the right mix of power generation sources, reduce CO₂ emissions. The main obstacles for introducing a large numbers of EVs are cost, battery weight, and vehicle range. Battery health is also a factor, both directly and indirectly, by introducing limits on depth of discharge. This paper considers a low-cost path for extending the range of a small urban EV by integrating a parallel hydraulic system for harvesting and reusing braking energy. The idea behind the concept is to avoid replacement of lead-acid or small Li-Ion batteries with a very expensive Li-Ion pack, and instead use a low-cost hydraulic system to achieve comparable range improvements.

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by Environmental Protection Agency to evaluate the greenhouse gas emissions and fuel efficiency of light-duty vehicles. It is a physics-based, forward-looking, full vehicle computer simulator that is capable of analyzing various vehicle types equipped with different powertrain technologies. The software is built on MATLAB/Simulink. This first version release of the simulation tool models conventional vehicles and is capable of evaluating effects of off-cycle technologies on greenhouse gas emissions, such as air conditioning, electrical load reduction, road load reduction by active aerodynamics, and engine start-stop. This paper introduces the simulation tool by describing its basic model architecture and presenting its underlying physics as well as model formulations. It describes the simulation capability along with its graphical user interface of the tool, designed for off-cycle technology analysis purposes.

While equivalent circuit modeling is an effective way to model the performance of automotive Li-ion batteries, in some applications it is more convenient to refer to round-trip energy efficiency. Energy efficiency of either cells or full packs is seldom documented by manufacturers in enough detail to provide an accurate impression of this metric over a range of operating conditions. The energy efficiency of a full battery pack may also be subject to more variables than would be represented by extrapolating results obtained from a single cell, and can be more demanding to measure in an accurate and consistent manner. Roundtrip energy efficiency of a 22.8-kWh A123 Li-ion (Lithium Iron Phosphate, LiFePO4) battery pack was measured by applying a fixed quantity of charge and discharge current between 0.2C and 2C rates and at SOCs between 10% and 90% at an average temperature of 23°C.

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.

To investigate the feasibility of various aerodynamic test procedures for the Phase 2 Greenhouse Gas (GHG) Regulations for heavy-duty vehicles in the United States, the US Environmental Protection Agency conducted, through Southwest Research Institute (SwRI), coastdown testing of several heavy-duty tractors matched to a conventional 53-foot dry-van trailer. Three vehicle configurations were tested, two of which included common trailer drag-reduction technologies. 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. One vehicle configuration was tested over several days to evaluate day-to-day repeatability and the influence of changing wind conditions. Data on external sources of road forces, such as grade and speed dependence of tire rolling resistance, were collected separately and incorporated into the analysis.

In June of 2015, the Environmental Protection Agency and the National Highway Traffic Safety Administration issued a Notice of Proposed Rulemaking to further reduce greenhouse gas emissions and improve the fuel efficiency of medium- and heavy-duty vehicles. The agencies proposed that vehicle manufacturers would certify vehicles to the standards by using the agencies’ Greenhouse Gas Emission Model (GEM). The agencies also proposed a steady-state engine test procedure for generating GEM inputs to represent the vehicle’s engine performance. In the proposal the agencies also requested comment on an alternative engine test procedure, the details of which were published in two separate 2015 SAE Technical Papers [1, 2]. As an alternative to the proposed steady-state engine test procedure, these papers presented a cycle-average test procedure.

The Environmental Protection Agency (EPA), in partnership with Research Triangle Institute (RTI International) and Auto Research Center (ARC-Indy), have created digital geometries of commercially available heavy-duty tractor-trailers. The goal of this effort was to improve the agency’s understanding of aerodynamic modeling of modern trucks and to provide opportunities for more consistent engagement on computational fluid dynamics (CFD) analyses. Sleeper and day cab tractors with aerodynamic features and a 53-foot box trailer with aerodynamic technology options were scanned to create high-resolution geometries. The scanning process consisted of a combination of physical scanning with a handheld device, along with digital post-processing. The completed truck geometries are compatible with most commercial CFD software and are publicly available for modeling and analyses.