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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.

Heavy-duty commercial vehicles consume a significant amount of energy due to their large size and mass, directly leading to vehicle operators prioritizing energy efficiency to reduce operational costs and comply with environmental regulations. One tool that can be used for the evaluation of energy efficiency in heavy-duty vehicles is the evaluation of energy efficiency using vehicle modeling and simulation. Simulation provides a path for energy efficiency improvement by allowing rapid experimentation of different vehicle characteristics on fuel consumption without the need for costly physical prototyping. The research presented in this paper focuses on using real-world, sparsely sampled telematics data from a large fleet of heavy-duty vehicles to create high-fidelity models for simulation. Samples in the telematics dataset are collected sporadically, resulting in sparse data with an infrequent and irregular sampling rate.

The authors present transient wind velocity measurements from two successive, well-documented truck platooning track-test campaigns to assess the wake-shedding behavior experienced by trucks in various platoon formations. Utilizing advanced analytics of data from fast-response (100-200-Hz) multi-hole pressure probes, this analysis examines aerodynamic flow features and their relationship to energy savings during close-following platoon formations. Applying Spectral analysis to the wind velocity signals, we identify the frequency content and vortex-shedding behavior from a forward truck trailer, which dominates the flow field encountered by the downstream trucks. The changes in dominant wake-shedding frequencies correlate with changes to the lead and follower truck fuel savings at short separation distances.

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.

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.

When developing and designing new technology for integrated vehicle systems deployment, standard cycles have long existed for chassis dynamometer testing and tuning of the powertrain. However, to this day with recent developments and advancements in plug-in hybrid and battery electric vehicle technology, no true “work day” cycles exist with which to tune and measure energy storage control and thermal management systems. To address these issues and in support of development of a range-extended pickup and delivery Class 6 commercial vehicle, researchers at the National Renewable Energy Laboratory in collaboration with Cummins analyzed 78,000 days of operational data captured from more than 260 vehicles operating across the United States to characterize the typical daily performance requirements associated with Class 6 commercial pickup and delivery operation.

For renewable fuels to displace petroleum, they must be compatible with emissions control devices. Pure biodiesel contains up to 5 ppm Na + K and 5 ppm Ca + Mg metals, which have the potential to degrade diesel emissions control systems. This study aims to address these concerns, identify deactivation mechanisms, and determine if a lower limit is needed. Accelerated aging of a production exhaust system was conducted on an engine test stand over 1001 h using 20% biodiesel blended into ultra-low sulfur diesel (B20) doped with 14 ppm Na. This Na level is equivalent to exposure to Na at the uppermost expected B100 value in a B20 blend for the system full-useful life. During the study, NOx emissions exceeded the engine certification limit of 0.33 g/bhp-hr before the 435,000-mile requirement.

This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method.

Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no road grade requirements. Additionally, the existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

This research project compares laboratory-measured fuel economy of a medium-duty diesel powered hydraulic hybrid vehicle drivetrain to both a conventional diesel drivetrain and a conventional gasoline drivetrain in a typical commercial parcel delivery application. Vehicles in this study included a model year 2012 Freightliner P10HH hybrid compared to a 2012 conventional gasoline P100 and a 2012 conventional diesel parcel delivery van of similar specifications. Drive cycle analysis of 484 days of hybrid parcel delivery van commercial operation from multiple vehicles was used to select three standard laboratory drive cycles as well as to create a custom representative cycle. These four cycles encompass and bracket the range of real world in-use data observed in Baltimore United Parcel Service operations.

Small impurities in the fuel can have a significant impact on the emissions control system performance over the lifetime of the vehicle. Of particular interest in recent studies has been the impact of sodium, potassium, and calcium that can be introduced either through fuel constituents, such as biodiesel, or as lubricant additives. In a collaboration between the National Renewable Energy Laboratory and the Oak Ridge National Laboratory, a series of accelerated aging studies have been performed to understand the potential impact of these metals on the emissions control system. This paper explores the effect of the rate of accelerated aging on the capture of fuel-borne metal impurities in the emission control devices and the subsequent impact on performance. Aging was accelerated by doping the fuel with high levels of the metals of interest. Three separate evaluations were performed, each with a different rate of accelerated aging.

Alkali and alkaline earth metal impurities found in diesel fuels are potential poisons for diesel exhaust catalysts. Using an accelerated aging procedure, a set of production exhaust systems from a 2011 Ford F250 equipped with a 6.7L diesel engine have been aged to an equivalent of 150,000 miles of thermal aging and metal exposure. These exhaust systems included a diesel oxidation catalyst (DOC), selective catalytic reduction (SCR) catalyst, and diesel particulate filter (DPF). Four separate exhaust systems were aged, each with a different fuel: ULSD containing no measureable metals, B20 containing sodium, B20 containing potassium and B20 containing calcium. Metals levels were selected to simulate the maximum allowable levels in B100 according to the ASTM D6751 standard. Analysis of the aged catalysts included Federal Test Procedure emissions testing with the systems installed on a Ford F250 pickup, bench flow reactor testing of catalyst cores, and electron probe microanalysis (EPMA).

It is estimated that operating continuously on a B20 fuel containing the current allowable ASTM specification limits for metal impurities in biodiesel could result in a doubling of ash exposure relative to lube-oil-derived ash. The purpose of this study was to determine if a fuel containing metals at the ASTM limits could cause adverse impacts on the performance and durability of diesel emission control systems. An accelerated durability test method was developed to determine the potential impact of these biodiesel impurities. The test program included engine testing with multiple DPF substrate types as well as DOC and SCR catalysts. The results showed no significant degradation in the thermo-mechanical properties of cordierite, aluminum titanate, or silicon carbide DPFs after exposure to 150,000 mile equivalent biodiesel ash and thermal aging. However, exposure of a cordierite DPF to 435,000 mile equivalent aging resulted in a 69% decrease in the thermal shock resistance parameter.

In this work, the influences of ethanol and iso-butanol blended with gasoline on engine-out and post three-way catalyst (TWC) particle size distribution and number concentration were studied using a General Motors (GM) 2.0L turbocharged spark ignition direct injection (SIDI) engine. The engine was operated using the production engine control unit (ECU) with a dynamometer controlling the engine speed and the accelerator pedal position controlling the engine load. A TSI Fast Mobility Particle Sizer (FMPS) spectrometer was used to measure the particle size distribution in the range from 5.6 to 560 nm with a sampling rate of 1 Hz. U.S. federal certification gasoline (E0), two ethanol-blended fuels (E10 and E20), and 11.7% iso-butanol blended fuel (BU12) were tested. Measurements were conducted at 10 selected steady-state engine operation conditions. Bi-modal particle size distributions were observed for all operating conditions with peak values at particle sizes of 10 nm and 70 nm.

Engine and flow reactor experiments were conducted to determine the impact of biodiesel relative to ultra-low-sulfur diesel (ULSD) on inhibition of the selective catalytic reduction (SCR) reaction over an Fe-zeolite catalyst. Fe-zeolite SCR catalysts have the ability to adsorb and store unburned hydrocarbons (HC) at temperatures below 300°C. These stored HCs inhibit or block NOx-ammonia reaction sites at low temperatures. Although biodiesel is not a hydrocarbon, similar effects are anticipated for unburned biodiesel and its organic combustion products. Flow reactor experiments indicate that in the absence of exposure to HC or B100, NOx conversion begins at between 100° and 200°C. When exposure to unburned fuel occurs at higher temperatures (250°-400°C), the catalyst is able to adsorb a greater mass of biodiesel than of ULSD. Experiments show that when the catalyst is masked with ULSD, NOx conversion is inhibited until it is heated to 400°C.

A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

The objective of this research project was to compare B20 (20% biodiesel fuel) and ultra-low-sulfur (ULSD) diesel-fueled buses in terms of fuel economy, vehicle maintenance, engine performance, component wear, and lube oil performance. We examined 15 model year (MY) 2002 Gillig 40-foot transit buses equipped with MY 2002 Cummins ISM engines. The engines met 2004 U.S. emission standards and employed exhaust gas recirculation (EGR). For 18 months, eight of these buses operated exclusively on B20 and seven operated exclusively on ULSD. The B20 and ULSD study groups operated from different depots of the St. Louis (Missouri) Metro, with bus routes matched for duty cycle parity. The B20- and ULSD-fueled buses exhibited comparable fuel economy, reliability (as measured by miles between road calls), and total maintenance costs. Engine and fuel system maintenance costs were also the same for the two groups after correcting for the higher average mileage of the B20 group.

Increasing interest in biofuels—specifically, biodiesel as a pathway to energy diversity and security—have necessitated the need for research on the performance and utilization of these fuels and fuel blends in current and future vehicle fleets. One critical research area is related to achieving a full understanding of the impact of biodiesel fuel blends on advanced emission control systems. In addition, the use of biodiesel fuel blends can degrade diesel engine oil performance and impact the oil drain interval requirements. There is limited information related to the impact of biodiesel fuel blends on oil dilution. This paper assesses the oil dilution impacts on an engine operating in conjunction with a diesel particle filter (DPF), oxides of nitrogen (NOx) storage, a selective catalytic reduction (SCR) emission control system, and a 20% biodiesel (soy-derived) fuel blend.

Raising interest in Diesel powered passenger cars in the United States in combination with the government mandated policy to reduce dependency of foreign oil, leads to the desire of operating Diesel vehicles with Biodiesel fuel blends. There is only limited information related to the impact of Biodiesel fuels on the performance of advanced emission control systems. In this project the implementation of a NOx storage and a SCR emission control system and the development for optimal performance are evaluated. The main focus remains on the discussion of the differences between the fuels which is done for the development as well as useful life aged components. From emission control standpoint only marginal effects could be observed as a result of the Biodiesel operation. The NOx storage catalyst results showed lower tailpipe emissions which were attributed to the lower exhaust temperature profile during the test cycle. The SCR catalyst tailpipe results were fuel neutral.