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The National Renewable Energy Laboratory (NREL) has conducted a series of chassis dynamometer and road tests on the 2000 model-year Honda Insight. This paper will focus on results from the testing, how the results have been applied to NREL's Advanced Vehicle Simulator (ADVISOR), and how test results compare to the model predictions and published data. The chassis dynamometer testing included the FTP-75 emissions certification test procedure, highway fuel economy test, US06 aggressive driving cycle conducted at 0°C, 20°C, and 40°C, and the SC03 test performed at 35°C with the air conditioning on and with the air conditioning off. Data collection included bag and continuously sampled emissions (for the chassis tests), engine and vehicle operating parameters, battery cell temperatures and voltages, motor and auxiliary currents, and cabin temperatures.

Electrifying transportation can reduce or eliminate dependence on foreign fuels, emission of green house gases, and emission of pollutants. One challenge is finding a pathway for vehicles that gains wide market acceptance to achieve a meaningful benefit. This paper evaluates several approaches aimed at making plug-in electric vehicles (EV) and plug-in hybrid electric vehicles (PHEVs) cost-effective including opportunity charging, replacing the battery over the vehicle life, improving battery life, reducing battery cost, and providing electric power directly to the vehicle during a portion of its travel. Many combinations of PHEV electric range and battery power are included. For each case, the model accounts for battery cycle life and the national distribution of driving distances to size the battery optimally. Using the current estimates of battery life and cost, only the dynamically plugged-in pathway was cost-effective to the consumer.

A study was performed in the spring of 2001 to chemically characterize exhaust emissions from trucks and buses fueled by various test fuels and operated with and without diesel particle filters. This study was part of a multi-year technology validation program designed to evaluate the emissions impact of ultra-low sulfur diesel fuels and passive diesel particle filters (DPF) in several different heavy-duty vehicle fleets operating in Southern California. The overall study of exhaust chemical composition included organic compounds, inorganic ions, individual elements, and particulate matter in various size-cuts. Detailed descriptions of the overall technology validation program and chemical speciation methodology have been provided in previous SAE publications (2002-01-0432 and 2002-01-0433).

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy's National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, their effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads.

We describe a study to identify potential biofuels that enable advanced spark ignition (SI) engine efficiency strategies to be pursued more aggressively. A list of potential biomass-derived blendstocks was developed. An online database of properties and characteristics of these bioblendstocks was created and populated. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a bioblendstock met the requirements for advanced SI engines. Criteria included melting point (or cloud point) < -10°C and boiling point (or T90) <165°C. Compounds insoluble or poorly soluble in hydrocarbon were eliminated from consideration, as were those known to cause corrosion (carboxylic acids or high acid number mixtures) and those with hazard classification as known or suspected carcinogens or reproductive toxins.

Mixing controlled compression ignition, i.e., diesel engines are efficient and are likely to continue to be the primary means for movement of goods for many years. Low-net-carbon biofuels have the potential to significantly reduce the carbon footprint of diesel combustion and could have advantageous properties for combustion, such as high cetane number and reduced engine-out particle and NOx emissions. We developed a list of over 400 potential biomass-derived diesel blendstocks and populated a database with the properties and characteristics of these materials. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a blendstock met the basic requirements for handling in the diesel distribution system and use as a blend with conventional diesel. Criteria included cetane number ≥40, flashpoint ≥52°C, and boiling point or T90 ≤338°C.

This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage.

In previous SAE papers, the initial development and testing of a vacuum-insulated catalytic converter was presented. This paper provides an update of the converter development and an analysis of potential off-cycle emissions savings. Hot vibration, cool-down, and 1975 Federal Test Procedure (FTP-75) emissions test results are provided to demonstrate the effectiveness of design improvements in greatly increasing durability while retaining performance. Using standard drive cycles and “real-world” driving statistics with a vehicle simulator (ADVISOR©), catalyst temperature and vehicle exhaust emissions of a sport utility vehicle (SUV) were predicted for 16 days of driving (107 trips, 770 total miles). Compared to the baseline vehicle with a conventional catalytic converter, the SUV with a vacuum-insulated converter produced 66% less non-methane hydrocarbon (NMHC), 65% less carbon monoxide (CO), and 60% less oxides of nitrogen (NOx).

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts.

Today's hybrid electric vehicle (HEV) controls do not necessarily provide maximum fuel savings over all drive cycles. An approach that employs route-based control could improve HEV efficiency at potentially minimal additional cost. This paper evaluates a range of route-based control approaches and identifies look-ahead strategies (using input from “on-the-fly” route predictions) as an area meriting further analysis. A novel implementation approach is developed and discussed, and a comparison with simulation results using an optimized general control setting indicates that fuel savings of approximately 2% to 4% can be obtained with route-based control. Given the increasing prevalence of GPS systems in vehicles, this advance has the potential to provide considerable aggregate fuel savings if applied across the entire national fleet. For instance, a 3% across-the-board reduction in HEV fuel use would save nearly 6.5 million gallons of fuel annually in the United States.

Spark-ignition engine fuel standards have been put in place to ensure acceptable hot and cold weather driveability (HWD and CWD). Vehicle manufacturers and fuel suppliers have developed systems that meet our driveability requirements so effectively that drivers overwhelmingly find that their vehicles reliably start up and operate smoothly and consistently throughout the year. For HWD, fuels that are too volatile perform more poorly than those that are less volatile. Vapor lock is the apparent cause of poor HWD, but there is conflicting evidence in the literature as to where in the fuel system it occurs. Most studies have found a correlation between degraded driveability and higher dry vapor pressure equivalent or lower TV/L = 20, and less consistently with a minimum T50. For CWD, fuels with inadequate volatility can cause difficulty in starting and rough operation during engine warmup.

Both hydrogen and plug-in electric vehicles offer significant social and environmental benefits to enhance energy security and reduce criteria and greenhouse gas emissions from the transportation sector. However, the rollout of electric vehicle supply equipment (EVSE) and hydrogen retail stations (HRS) requires substantial investments with high risks due to many uncertainties. We compare retail infrastructure costs on a common basis - cost per mile, assuming fueling service to 10% of all light-duty vehicles in a typical 1.5 million person city in 2025. Our analysis considers three HRS sizes, four distinct types of EVSE and two distinct EVSE scenarios. EVSE station costs, including equipment and installation, are assumed to be 15% less than today's costs. We find that levelized retail capital costs per mile are essentially indistinguishable given the uncertainty and variability around input assumptions.

Regulated and unregulated emissions (individual hydrocarbons, ethanol, aldehydes and ketones, polynuclear aromatic hydrocarbons (PAH), nitro-PAH, and soluble organic fraction of particulate matter) were characterized in engines utilizing duplicate ISO 8178-C1 eight-mode tests and FTP smoke tests. Certification No. 2 diesel (400 ppm sulfur) and three ethanol/diesel blends, containing 7.7 percent, 10 percent, and 15 percent ethanol, respectively, were used. The three, Tier II, off-road engines were 6.8-L, 8.1-L, and 12.5-L in displacement and each had differing fuel injection system designs. It was found that smoke and particulate matter emissions decreased with increasing ethanol content. Changes to the emissions of carbon monoxide and oxides of nitrogen varied with engine design, with some increases and some decreases. As expected, increasing ethanol concentration led to higher emissions of acetaldehyde (increases ranging from 27 to 139 percent).

A new type of solar-reflective glass that improves reflection of the near-infrared (NIR) portion of the solar spectrum has been developed. Also developed was a prototype solar-reflective paint that increases the NIR reflection of opaque vehicle surfaces while maintaining desired colors in the visible portion of the spectrum. Both of these technologies, as well as solar-powered parked car ventilation, were tested on a Cadillac STS as part of the Improved Mobile Air Conditioning Cooperative Research Program (I-MAC). Significant reductions in interior and vehicle skin temperatures were measured. The National Renewable Energy Laboratory (NREL) performed an analysis to determine the impact of reducing the thermal load on the vehicle. A simplified cabin thermal/fluid model was run to predict the potential reduction in A/C system capacity. The potential reduction in fuel use was calculated using a vehicle simulation tool developed by the U.S. Department of Energy (DOE).

National concerns over energy consumption and emissions from the transportation sector have prompted regulatory agencies to implement aggressive fuel economy targets for light-duty vehicles through the U.S. National Highway Traffic Safety Administration/Environmental Protection Agency (EPA) Corporate Average Fuel Economy (CAFE) program. Automotive manufacturers have responded by bringing competitive technologies to market that maximize efficiency while meeting or exceeding consumer performance and comfort expectations. In a collaborative effort among Toyota Motor Corporation, Argonne National Laboratory (ANL), and the National Renewable Energy Laboratory (NREL), the real-world savings of one such technology is evaluated. A commercially available Toyota Highlander equipped with two-phase cold storage technology was tested at ANL’s chassis dynamometer testing facility.

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver.

The Kia Soul battery electric vehicle (BEV) is available with either a positive temperature coefficient (PTC) heater or an R134a heat pump (HP) with PTC heater combination [1]. The HP uses both ambient air and waste heat from the motor, inverter, and on-board-charger (OBC) for its heat source. Hanon Systems, Hyundai America Technical Center, Inc. (HATCI) and the National Renewable Energy Laboratory jointly, with financial support from the U.S. Department of Energy, developed and proved-out technologies that extend the driving range of a Kia Soul BEV while maintaining thermal comfort in cold climates. Improved system configuration concepts that use thermal storage and waste heat more effectively were developed and evaluated. Range extensions of 5%-22% at ambient temperatures ranging from 5 °C to −18 °C were demonstrated. This paper reviews the three-year effort, including test data of the baseline and modified vehicles, resulting range extension, and recommendations for future actions.

The National Renewable Energy Laboratory's (NREL's) Fleet Test and Evaluations team recently conducted chassis dynamometer tests of a class 8 conventional regional delivery truck over the Heavy Heavy-Duty Diesel Truck (HHDDT), West Virginia University City (WVU City), and Composite International Truck Local and Commuter Cycle (CILCC) drive cycles. A quantitative study analyzed the impacts of various factors on fuel consumption (FC) and fuel economy (FE) by modeling and simulating the truck using NREL's Future Automotive Systems Technology Simulator (FASTSim). Factors included vehicle weight and the coefficients of rolling resistance and aerodynamic drag. Simulation results from a single parametric study revealed that FC was approximately a linear function of the weight, coefficient of aerodynamic drag, and rolling resistance over various drive cycles.

The disparate characteristics between conventional (CVs) and battery electric vehicles (BEVs) in terms of driving range, refill/recharge time, and availability of refuel/recharge infrastructure inherently limit the relative utility of BEVs when benchmarked against traditional driver travel patterns. However, given a high penetration of high-power public charging combined with driver tolerance for rerouting travel to facilitate charging on long-distance trips, the difference in utility between CVs and BEVs could be marginalized. We quantify the relationships between BEV utility, the deployment of fast chargers, and driver tolerance for rerouting travel and extending travel durations by simulating BEVs operated over real-world travel patterns using the National Renewable Energy Laboratory's Battery Lifetime Analysis and Simulation Tool for Vehicles (BLAST-V). With support from the U.S.

The air-conditioning (A/C) compressor load significantly impacts the fuel economy of conventional vehicles and the fuel use/range of plug-in hybrid electric vehicles (PHEV). A National Renewable Energy Laboratory (NREL) vehicle performance analysis shows the operation of the air conditioner reduces the charge depletion range of a 40-mile range PHEV from 18% to 30% in a worst case hot environment. Designing for air conditioning electrical loads impacts PHEV and electric vehicle (EV) energy storage system size and cost. While automobile manufacturers have climate control procedures to assess A/C performance, and the U.S. EPA has the SCO3 drive cycle to measure indirect A/C emissions, there is no automotive industry consensus on a vehicle level A/C fuel use test procedure. With increasing attention on A/C fuel use due to increased regulatory activities and the development of PHEVs and EVs, a test procedure is needed to accurately assess the impact of climate control loads.