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Biodiesel (i.e., mono-alkyl esters of long chain fatty acids derived from vegetable oils and animal fats) is a renewable diesel fuel providing life-cycle greenhouse gas emission reductions relative to petroleum-derived diesel. With the expectation that there would be widespread use of biodiesel as a substitute for ultra-low sulfur diesel (ULSD), there have been many studies looking into the effects of biodiesel on engine and aftertreatment, particularly its compatibility to the current aftertreatment technologies. The objective of this study was to generate experimental data to measure the effectiveness of a current technology diesel oxidation catalysts (DOC) to oxidize soy-based biodiesel at various blend levels with ULSD. Biodiesel blends from 0 to 100% were evaluated on an engine using a conventional DOC.

The quality of neat biodiesel (B100) is critical for ensuring biodiesel blends used in diesel-powered vehicles do not adversely impact engine performance. In the United States, B100 is required to meet ASTM International’s purity and fuel property requirements in D6751, “Standard Specification for Biodiesel Fuel Blend Stock (B100) for Middle Distillate Fuels.” Here we review the development of this standard for the different grades of B100. The BQ-9000 program, which currently covers over 90% of U.S. and Canadian production volumes, is also described. Engine and original equipment manufacturers have expressed a desire for credible, third-party data on values of various ASTM B100 properties in the commercial market to inform their efforts to address future emissions and durability requirements.

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles.

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory’s Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation.

This project’s objective was to generate experimental data to evaluate the impact of metals doped B20 on diesel particle filter (DPF) ash loading and performance compared to that of conventional petrodiesel. The effect of metals doped B20 vs. conventional diesel on a DPF was quantified in a laboratory controlled accelerated ash loading study. The ash loading was conducted on two DPFs – one using ULSD fuel and the other on B20 containing metals dopants equivalent to 4 ppm B100 total metals. Engine oil consumption and B20 metals levels were accelerated by a factor of 5, with DPFs loaded to 30 g/L of ash. Details of the ash loading experiment and on-engine DPF performance evaluations are presented in the companion paper (Part I). The DPFs were cleaned, and ash samples were taken from the cleaned material. X-ray Fluorescence (XRF), X-Ray Photoelectron Spectroscopy (XPS) and X-Ray Diffraction (XRD) were conducted on the ash samples.

The project objective was to generate experimental data to evaluate the impact of metals doped B20 on DPF ash loading and performance compared to that of conventional petrodiesel. Accelerated ash loading was conducted on two DPFs – one exposed to regular diesel fuel and the other to B20 containing metal dopants equivalent to 4 ppm B100 total metals (currently total metals are limited to 10 ppm in ASTM D6751, the standard for B100). Periodic performance evaluations were conducted on the DPFs at 10 g/L ash loading intervals. After the evaluations at 30 g/L, the DPF was cleaned with a commercial DPF cleaning machine and another round of DPF evaluations were conducted. A comparison of the effect of ash loading with the two fuels and DPF cleaning is presented. The metals doped B20 fuel resulted in ash that was similar to that deposited when exposed to ULSD (lube oil ash) and exhibited similar ash cleaning removal efficiency.

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.

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process.

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the thermal control/heat rejection system sensitivity to intentional lateral offsets over a range of intervehicle spacings. Previous studies have shown the following vehicle can experience elevated temperatures and reduced airflow through the cooling package as a result of close-formation platooning. Four anemometers positioned across the grille of the following trucks as well as aligned and multiple offset positions are used to evaluate the sensitivity of the impact. Straight sections of the track are isolated for the most accurate airflow impact measurements and to be most representative of on-highway driving. An intentional lateral offset in truck platooning is considered as a controls approach to mitigate reduced cooling efficacy at close following scenarios where the highest platoon savings are achieved.

Currently, connected and autonomous vehicle (CAV) technology is being developed for Class 8 tractor trucks aimed at improved safety and fuel economy and reduced CO2 emissions. Despite extensive efforts conducted across the world, the reported efficiency gains were varied from different research groups, raising concerns about the fidelity of models, the performance of control, and the effectiveness of the experimental validation. One root cause for this variation stems from the fact that the efficiency gain obtained from the CAV is sensitive to real-world conditions, including surrounding traffic and road grade. This study presents an approach aimed at identifying representative public road sections and facilitating CAV research from this perspective. By employing the decision tree regression (DTR) method to the Fleet DNA database, the most representative road sections can be identified.

Conventional diesel engines will continue to hold a vital role in the heavy- and medium-duty markets for the transportation of goods along with many other uses. The ability to offset traditional diesel fuels with low-net-carbon biofuels could have a significant impact on reducing the carbon footprint of these vehicles. A prior study screened several hundred candidate biofuel blendstocks based on required diesel blendstock properties and identified 12 as the most promising. Eight representative biofuel blendstocks were blended at a 30% volumetric concentration with EPA certification ultra-low-sulfur diesel (ULSD) and were investigated for emissions and fuel efficiency performance. This study used a single cylinder engine (based on the Ford 6.7L engine) using Conventional Diesel Combustion (CDC), also known as Mixing Control Compression Ignition (MCCI). The density, cetane number, distillation curve and sooting tendency (using the yield sooting index method) of the fuels were measured.

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL.

Range-extended hybrids are an attractive option for medium- and heavy-duty commercial vehicle fleets because they offer the efficiency of an electrified powertrain with the driving range of a conventional diesel powertrain. The vehicle essentially operates as if it was purely electric for most trips, while ensuring that all commercial routes can be completed in any weather conditions or geographic terrain. Fuel use and point-source emissions can be significantly reduced, and in some cases eliminated, as many shorter routes can be fully electrified with this architecture. Under a U.S. Department of Energy (DOE)-funded project for Medium- and Heavy-Duty Vehicle Powertrain Electrification, Cummins has developed a plug-in hybrid electric Class 6 truck with a range-extending engine designed for pickup and delivery application.

Ride hailing activity is rapidly increasing, largely due to the growth of transportation network companies such as Uber and Lyft. However, traditional taxi companies continue to represent an important mobility option for travelers. Columbus Yellow Cab, a taxi company in Columbus, Ohio, offers traditional line-of-sight hailing as well as digital hailing through a mobile app. Data from Columbus Yellow Cab was provided to the National Renewable Energy Laboratory to analyze the potential for taxi electrification. Columbus Yellow Cab data contained information describing both global positioning system trajectories and taxi meter information. The data spanned a period of 13 months, containing approximately 70 million global system positioning system points, 840 thousand trips, and 170 unique vehicles.

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.

Evaporative cooling of the fuel-air charge by fuel evaporation is an important feature of direct-injection spark-ignition engines that improves fuel knock resistance and reduces pumping losses at intermediate load, but in some cases, may increase fine particle emissions. We have reported on experimental approaches for measuring both total heat of vaporization and examination of the evaporative heat effect as a function of fraction evaporated for gasolines and ethanol blends. In this paper, we extend this work to include other low-molecular-weight alcohols and present results on species evolution during fuel evaporation by coupling a mass spectrometer to our differential scanning calorimetry/thermogravimetric analysis instrument. The alcohols examined were methanol, ethanol, 1-propanol, isopropanol, 2-butanol, and isobutanol at 10 volume percent, 20 volume percent, and 30 volume percent.

The key hurdles to achieving wide consumer acceptance of battery electric vehicles (BEVs) are weather-dependent drive range, higher cost, and limited battery life. These translate into a strong need to reduce a significant energy drain and resulting drive range loss due to auxiliary electrical loads the predominant of which is the cabin thermal management load. Studies have shown that thermal sub-system loads can reduce the drive range by as much as 45% under ambient temperatures below −10 °C. Often, cabin heating relies purely on positive temperature coefficient (PTC) resistive heating, contributing to a significant range loss. Reducing this range loss may improve consumer acceptance of BEVs. The authors present a unified thermal management system (UTEMPRA) that satisfies diverse thermal and design needs of the auxiliary loads in BEVs.

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.

Knock-limited loads for a set of surrogate gasolines all having nominal 100 research octane number (RON), approximately 11 octane sensitivity (S), and a heat of vaporization (HOV) range of 390 to 595 kJ/kg at 25°C were investigated. A single-cylinder spark-ignition engine derived from a General Motors Ecotec direct injection (DI) engine was used to perform load sweeps at a fixed intake air temperature (IAT) of 50 °C, as well as knock-limited load measurements across a range of IATs up to 90 °C. Both DI and pre-vaporized fuel (supplied by a fuel injector mounted far upstream of the intake valves and heated intake runner walls) experiments were performed to separate the chemical and thermal effects of the fuels’ knock resistance. The DI load sweeps at 50°C intake air temperature showed no effect of HOV on the knock-limited performance. The data suggest that HOV acts as a thermal contributor to S under the conditions studied.

A relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from direct injection spark ignition (DISI) vehicles. The fundamental cause of this observation is not well understood. One potential explanation is that increased evaporative cooling as a result of ethanol’s high HOV may slow evaporation and prevent sufficient reactant mixing resulting in the combustion of localized fuel rich regions within the cylinder. In addition, it is well known that ethanol when blended in gasoline forms positive azeotropes which can alter the liquid/vapor composition during the vaporization process. In fact, it was shown recently through a numerical study that these interactions can retain the aromatic species within the liquid phase impeding the in-cylinder mixing of these compounds, which would accentuate PM formation upon combustion.