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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.

Zinc-based electrogalvanized (EG) and hot-dip galvanized (HDGI) coatings have been widely used in automotive body-in-white components for corrosion protection. The formability of zinc coated sheet steels depends on the properties of the sheet and the interactions at the interface between the sheet and the tooling. The frictional behavior of zinc coated sheet steels is influenced by the interfacial conditions present during the forming operation. Friction behavior has also been found to deviate from test method to test method. In this study, various lubrication conditions were applied to both bending under tension (BUT) test and a draw bead simulator (DBS) test for friction evaluations. Two different zinc coated steels; electrogalvanized (EG) and hot-dip galvanized (HDGI) were included in the study. In addition to the coated steels, a non-coated cold roll steel was also included for comparison purpose.

Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory’s FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls.

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.

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.

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.

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.

Presently, a main mobility sector objective is to reduce its impact on the global greenhouse gas emissions. While there are many techniques being explored, a promising approach to improve fuel economy is to reduce the required energy by using slipstream effects. This study analyzes the demanded engine power and mechanical energy used by heavy-duty trucks during platooning and non-platooning operation to determine the aerodynamic benefits of the slipstream. A series of platooning tests utilizing class 8 semi-trucks platooning via Cooperative Adaptive Cruise Control (CACC) are performed. Comparing the demanded engine power and mechanical energy used reveals the benefits of platooning on the aerodynamic drag while disregarding any potential negative side effects on the engine. However, energy savings were lower than expected in some cases.

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 application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

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.

We investigate tradeoffs between the airflow strategies related to engine cooling and the aerodynamic-enabled fuel savings created by platooning. By analyzing air temperatures, engine temperatures and cooling air flow at different platoon distances, we show the thermal impact to the engine from truck platooning. Previously, we collected wind and thermal data for numerous heavy-duty truck platoon configurations (gaps ranging from 4 to 87 meters) and reported the significant fuel savings enabled by these configurations. The fuel consumption for all trucks in the platoon were measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate while travelling at 65 mph and loaded to a gross weight of 65,000 lb.

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances.

Third generation advanced high strength steels (3GAHSS) are increasingly used in automotive for light weighting and safety body structure components. However, high material strength usually introduces higher springback that affects the dimensional accuracy. The ability to accurately predict springback in simulations is very important to reduce time and cost in stamping tool and process design. In this work, tension and compression tests were performed and the results were implemented to generate Isotropic/Kinematic hardening (I/KH) material models on a 3GAHSS steel with 980 MPa minimum tensile strength. Systematic material model parametric studies and evaluations have been conducted. Case studies from full-scale industrial parts are provided and the predicted springback results are compared to the measured springback data. Key variables affecting the springback prediction accuracy are identified.

The thermal deflection associated with the conventional die heat treating procedure usually requires extra die grinding process to fine-tune the die surface. Due to the size of the production die, the grinding is time consuming and is not cost effective. The goal of the study is to develop a new die heat treating process utilizing the flexible laser heat treatment, which could serve the same purpose as the conventional die heat treating and avoid the thermal deflection. The unique look of the developed zebra pattern laser heat treating process is defined as the Zebra Line. The heat-treating parameters and processes were developed and calibrated to produce the laser heat treating on laboratory size dies, which were subjected to the die wear test in the laboratory condition. The USS HDGI 980 XG3TM steel was selected to be carried out on the developmental dies in the cyclic bend die wear test due to its high strength and coating characteristic.

Commercially available Third Generation Advanced High Strength Steels (GEN3 AHSS) are qualified by automakers worldwide. With an excellent combination of strength and ductility, GEN3 AHSS are cold-formable and have shown potential to replace press hardenable steels (PHS) in structural applications. With overall formability equivalent to 590DP, U. S. Steel 980 GEN3 AHSS (980 XG3™ AHSS) may achieve cold-formed component geometries similar to those achieved by hot-formed PHS. Furthermore 980 GEN3 AHSS demonstrates a substantial increase in post-forming yield strength due to the combined effects of work-hardening and bake-hardening-thereby contributing strongly toward crash energy management performance. The technical challenges and attributes of cold-formed 980 GEN3 AHSS are explored in this paper for an automotive rear rail application (currently PHS), including: formability analysis, wrinkling elimination and springback compensation.

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.

The simulation of a crash event in the design stage of a vehicle facilitates the optimization of crashworthiness and significantly reduces the design cost and time. The development of a fracture material card used in crash simulation is heavily dependent on laboratory testing data. In this paper, the experimental characterization process to generate fracture data for fracture model calibration is discussed. A third-generation advanced high strength steel (AHSS), namely the XG3TM steel, is selected as the example material. For fracture model calibration, fracture locus and load-displacement data are obtained using mechanical testing coupled with digital image correlation (DIC) technique. Test coupons with designed geometries are deformed under different deformation modes including shear, uniaxial tension, plane strain and biaxial stretch conditions. Mini-shear, sub-sized tensile, and Marciniak cup tests are employed to achieve these strain conditions.