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36 records · Page 2

Development of heavy-duty vehicle representative driving cycles via decision tree regression

Previously, researchers who developed representative driving cycles mainly focused on light-duty vehicles and only considered vehicle speed and related derivations. In this paper, we propose a novel approach to develop representative cycles for heavy-duty vehicles. By implementing decision tree regression (DTR) to the Fleet DNA on-road vehicle data, a broader set of metrics, such as engine power and fuel consumption, can be used for more robust cycle development. Additionally, the influence of each metric on the regression target is also accounted for by a weighted number derived through the DTR to enhance the representativenss of the developed cycle. As case studies, we applied the proposed method to five heavy-duty vocations (drayage, long haul, regional haul, local delivery, and transit bus) and derived the most representative cycle, as well as four extreme cycles (maximal energy consumption, maximal power-weighted work, maximal fraction of high speed, and minimal fuel economy) to advance the related alternative powertrain design.

33 ADVANCED PROPULSION SYSTEMS↗

Advancing Platooning with ADAS (Advanced Driver-Assistance Systems) Control Integration and Assessment

Application of Cooperative Adaptive Cruise Control (CACC) to heavy duty trucks known as truck platooning has shown fuel economy improvements on the test track under ideal driving conditions. However, limited test data is available to assess the truck platooning under real-world driving conditions. Under this Cummins-led project that was funded by the U.S. Department of Energy, truck platooning with CACC has been tested on a real-world interstate highway and the results of the project are reviewed in this report. At first, the real-world driving conditions were characterized using National Renewable Energy Laboratory (NREL) Fleet DNA database to define test factors, including route, terrain, and highway traffic. Afterward, both test track and on-highway testing guided by SAE J1321 procedures were conducted to assess truck platooning under controlled and real-world driving conditions. On-highway testing was done on a highway route in Indiana, consisting of low, medium, and high road grade segments. The highway test results of 2-truck and 3-truck platooning showed considerably reduced fuel savings compared to the controlled test track data, which mainly stems from the traffic or high-grade portions of the route. However, integration of Cummins powertrain and vehicle eco-driving features such as predictive cruise control and neutral coasting called ADEPT™ on the lead truck showed an improvement of fuel saving for the trucks in CACC operation. Furthermore, the importance of tire connectivity in efficient and safe operation of the trucks in platooning is characterized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluating the Impact of Road Grade on Simulated Commercial Vehicle Fuel Economy Using Real-World Drive Cycles

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 then 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 climb or descent requirements. Additionally, 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. Drive-cycles are matched with vocation-specific vehicle models and simulated with and without grade. Fuel use due to grade is presented, and variation in fuel consumption due to drive cycle and vehicle characteristics is explored through graphical and statistical comparison. The results of this study suggest that road grade accounts for 1%-9% of fuel use in commercial vehicles on average and up to 40% on select routes.

33 ADVANCED PROPULSION SYSTEMS↗

Decision Tree Regression to Identify Representative Road Sections for Evaluating Performance of Connected and Automated Class 8 Tractors

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. High-level metrics and detailed information of the derived road sections are also illustrated and discussed, which demonstrate their representativeness and the effectiveness of the approach. Meanwhile, the capability of this approach can be easily extended by integrating specific constraints into the DTR algorithm. As an example, a specific representative road section with an aggressive road grade profile was also provided via this approach.

27 ARPA - Advanced Research Projects Agency-Energy↗

Advancing Platooning with ADAS Control Integration and Assessment Test Results

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). Track and on-highway testing guided by SAE J1321 procedures were conducted to assess truck platooning operation under the characterized real-world driving conditions. On-highway testing is done on a route in Indiana representing operation of long-haul Class 8 trucks in the United States. The road includes low-, medium-, and high-grade segments. The highway test results of a two-truck platooning configuration indicate considerable fuel-saving reduction comparing to the test track data collected under ideal driving conditions. The test data indicate that platooning could lead to increases in fuel consumption during traffic or high-grade portions of the route, causing reduction of the overall fuel saving on the road comparing to test track results. However, integration of ADAS features on the lead truck during on-road tests leads to significant improvement of fuel saving for both trucks in CACC operation.

ADAS↗

Exploring Class 8 Long-Haul Truck Electrification: Key Technology Evaluation and Potential Challenges

The phenomena of global warming and climate change are encouraging more and more countries, local communities, and companies to establish carbon neutrality targets, which has very significant implications for the US trucking industry. Truck electrification helps fleets to achieve zero tailpipe emissions and macro-scale decarbonization while allowing continued business growth in response to the rapid expansion of e-commerce and shipping related to increased globalization. Here, this paper presents an analysis of Class 8 long-haul truck electrification using a commercial vehicle electrification evaluation tool and Fleet DNA drive data. The study provides new insight into the impacts of streamlined chassis, battery energy density, and superfast charging on battery capacity needs as well as implications for payload, energy consumption, and greenhouse gas emissions for electric long-haul trucks. The study also identifies a pathway for achieving optimal long-haul truck electrification. The results show that no single technology can simultaneously achieve significant improvements in all these key areas and that a cost-effective approach requires a deliberate combination of all of these technologies. Moreover, the analysis highlights the strong evolution of vehicle and battery technologies and the excellent potential for long-haul truck electrification to achieve 100% year-round service coverage with continued technology advancement.

33 ADVANCED PROPULSION SYSTEMS↗

Map Matching and Real World Integrated Sensor Data Warehousing (Presentation)

The inclusion of interlinked temporal and spatial elements within integrated sensor data enables a tremendous degree of flexibility when analyzing multi-component datasets. The presentation illustrates how to warehouse, process, and analyze high-resolution integrated sensor datasets to support complex system analysis at the entity and system levels. The example cases presented utilizes in-vehicle sensor system data to assess vehicle performance, while integrating a map matching algorithm to link vehicle data to roads to demonstrate the enhanced analysis possible via interlinking data elements. Furthermore, in addition to the flexibility provided, the examples presented illustrate concepts of maintaining proprietary operational information (Fleet DNA) and privacy of study participants (Transportation Secure Data Center) while producing widely distributed data products. Should real-time operational data be logged at high resolution across multiple infrastructure types, map matched to their associated infrastructure, and distributed employing a similar approach; dependencies between urban environment infrastructures components could be better understood. This understanding is especially crucial for the cities of the future where transportation will rely more on grid infrastructure to support its energy demands.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Emissions from Medium-Duty Conventional and Diesel-Electric Hybrid Vehicles; NREL (National Renewable Energy Laboratory)

This presentation discusses the results of emissions testing for medium-duty conventional and diesel-electric hybrid vehicles. Testing was based on a field evaluation approach that utilized the Fleet DNA drive cycle database and NREL’s Renewable Fuels and Lubricants (ReFUEL) Laboratory chassis dynamometer. Vehicles tested included parcel delivery (Class 6 step vans), beverage delivery (Class 8 tractors), and parcel delivery (Class 7 box trucks) vehicles, all with intended service class medium/heavy heavy-duty diesel (MHDD). Results for fuel economy and tailpipe NOx emissions included: diesel hybrid electric vehicles showed an average fuel economy advantage on identified test cycles: Class 6 Step Vans: 26%; Class 7 Box Trucks: 24.7%; Class 8 Tractors: 17.3%. Vehicle miles traveled is an important factor in determining total petroleum and CO2 displacement. Higher NOx emissions were observed over some test cycles: highly drive cycle dependent; engine-out differences may result from different engine operating point; and selective catalyst reduction temperature may play a role, but does not explain the whole story.

33 ADVANCED PROPULSION SYSTEMS↗

Fleet Tools; NREL (National Renewable Energy Laboratory)

From beverage distributors to shipping companies and federal agencies, industry leaders turn to the National Renewable Energy Laboratory (NREL) to help green their fleet operations. Cost, efficiency, and reliability are top priorities for fleets, and NREL partners know the lab’s portfolio of tools can pinpoint fuel efficiency and emissions-reduction strategies that also support operational the bottom line. NREL is one of the nation’s foremost leaders in medium- and heavy-duty vehicle research and development (R&D) and the go-to source for credible, validated transportation data. NREL developers have drawn on this expertise to create tools grounded in the real-world experiences of commercial and government fleets. Operators can use this comprehensive set of technology- and fuel-neutral tools to explore and analyze equipment and practices, energy-saving strategies, and other operational variables to ensure meaningful performance, financial, and environmental benefits.

33 ADVANCED PROPULSION SYSTEMS↗

Transportation Database Development Using Floating Car Data

In support of projects funded by the U.S. Department of Transportation and the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has received on average 4 million floating car data (FCD) points each day over a 3-year period. To handle data sets of this size, the Transportation & Hydrogen Systems Center at NREL has developed a series of transportation databases (Transportation Secure Data Center and Fleet DNA projects) to support real-world vehicle and transportation infrastructure analysis on a national scale. To ensure the quality of the FCD received by NREL and to ensure that data can be accessed and applied quickly and easily across transportation research disciplines, a customized data processing routine and database were required. 'Floating car data' is a general term for location data recorded by a vehicle or by a person traveling in a vehicle. FCD are used to support real-time traffic information systems and have proven to be beneficial in a large number of research applications. For large-scale traffic information systems, FCD are logged from smart phones using either the GPS included in the device, or if GPS is disabled, triangulation from the network. Additionally, in scientific applications FCD are oftentimes collected on a smaller scale using onboard GPS-enabled data logging systems. Through the fusion of real-time data and historically logged results, up-to-date and accurate vehicle operating information are provided in near real-time to support routing and operation decisions. The approach outlined within this paper builds upon methods developed for advanced traffic information systems to link FCD to the street of travel and further extends the link to data recorded by components within a vehicle. Linking vehicle component performance to the infrastructure a vehicle is operating within provides the path to assess vehicle and infrastructure interactions, going far beyond providing information on traffic flow alone.

33 ADVANCED PROPULSION SYSTEMS↗

Effect of extended strain fields on point defect phonon scattering in thermoelectric materials

The design of thermoelectric materials often involves the integration of point defects (alloying) as a route to reduce the lattice thermal conductivity. Classically, the point defect scattering strength follows from simple considerations such as mass contrast and the presence of induced strain fields (e.g. radius contrast, coordination changes). While the mass contrast can be easily calculated, the associated strain fields induced by defect chemistry are not readily predicted and are poorly understood. In this work, we use classical and first principles calculations to provide insight into the strain field component of phonon scattering from isoelectronic point defects. Our results also integrate experimental measurements on bulk samples of SnSe and associated alloys with S, Te, Ge, Sr and Ba. These efforts highlight that the strength and extent of the resulting strain field depends strongly on defect chemistry. Strain fields can have a profound impact on the local structure. For example, in alloys containing Ba, the strain fields have significant spatial extent (1 nm in diameter) and produce large shifts in the atomic equilibrium positions (up to 0.5 A). Such chemical complexity suggests that computational assessment of point defects for thermal conductivity depression should be hindered. However, in this work, we present and verify several computational descriptors that correlate well with the experimentally measured strain fields. Furthermore, these descriptors are conceptually transparent and computationally inexpensive, allowing computation to provide a pivotal role in the screening of effective alloys. The further development of point defect engineering could complement or replace nanostructuring when optimizing the thermal conductivity, offering the benefits of thermodynamic stability, and providing more clearly defined defect chemistry.

30 DIRECT ENERGY CONVERSION↗

Research, Development and Demonstration of Advanced Vehicle Technologies in Clean Motor Fuels (CRADA Final Report)

NREL/DOE has been funding research, development, and demonstration (RD&D) projects to facilitate the deployment of alternative fuels into the marketplace in order to achieve three objectives: 1) enhance the reduction of mobile source emissions in California and the U.S.; 2) increase U.S. competitiveness and economic prosperity; and 3) preserve the environment through the reduction of emissions and toxins from the motor vehicle population. The Lewis-Presley Air Quality Management Act requires the South Coast Air Quality Management District to establish a program to encourage participation in projects to increase the utilization of clean-burning fuels. The parties seek to collaborate on a joint RD&D project to perform a field test on a small vehicle fleet operating on Fischer-Tropsch synthetic diesel fuel. Recently the 106th U.S. Congress designated "gas-to-liquid" (GTL) transportation fuels that are produced from domestic products as alternative fuels under the Energy Policy Act of 1992 (EPACT). Niche markets could develop quickly for these fuel products, perhaps especially for the use of Fischer-Tropsch synthetic fuels in centrally fueled vehicle fleets in California. NREL and its project partners from the U.S. Department of Energy and West Virginia University have recently conducted what we believe to be the first-ever controlled tests of Fischer-Tropsch synthetic fuels in heavy vehicles. These tests have shown that Fischer-Tropsch fuels can be substituted in unmodified trucks and buses without any detectable loss in drivability and performance. Compared to a California diesel fuel baseline, neat Shell Fischer-Tropsch fuel emitted about 12% lower NOx and 24% lower particulate matter over a five-mile driving route while maintaining the same fuel economy on an energy equivalent basis. Whereas these exhaust emissions reductions from these previous studies have been impressive, far greater exhaust emissions reductions can be achieved if the vehicles are retrofitted with emissions control technologies that are enabled by Fischer-Tropsch fuels. For this program, a test fleet would be selected and retrofitted with continuously regenerating traps (CRT’s) or diesel particulate filters (DPF's). The University of West Virginia, under a separate subcontract to SCAQMD will have the responsibility to test and measure the emissions from the test fleet of vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Development of 80- and 100- Mile Work Day Cycles Representative of Commercial Pickup and Delivery Operation

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. In total, over 2.5 million miles of real-world vehicle operation were condensed into a pair of duty cycles, an 80-mile cycle and a 100-mile cycle representative of the daily operation of U.S. class 3-6 commercial pickup and delivery trucks. Using novel machine learning clustering methods combined with mileage-based weighting, these composite representative cycles correspond to 90th and 95th percentiles for daily vehicle miles traveled by the vehicles observed. In addition to including vehicle speed vs time drive cycles, in an effort to better represent the environmental factors encountered by pickup and delivery vehicles operating across the United States, a nationally representative grade profile and key status information were also appended to the speed vs. time profiles to produce a 'work day' cycle that captures the effects of vehicle dynamics, geography, and driver behavior which can be used for future design, development, and validation of technology.

100 mile↗

Statistical Characterization of Medium-Duty Electric Vehicle Drive Cycles; NREL (National Renewable Energy Laboratory)

With funding from the U.S. Department of Energy’s Vehicle Technologies Office, the National Renewable Energy Laboratory (NREL) conducts real-world performance evaluations of advanced medium- and heavy-duty fleet vehicles. Evaluation results can help vehicle manufacturers fine-tune their designs and assist fleet managers in selecting fuel-efficient, low-emission vehicles that meet their economic and operational goals. In 2011, NREL launched a large-scale performance evaluation of medium-duty electric vehicles. With support from vehicle manufacturers Smith and Navistar, NREL research focused on characterizing vehicle operation and drive cycles for electric delivery vehicles operating in commercial service across the nation.

33 ADVANCED PROPULSION SYSTEMS↗

Transport Energy Impact Analysis; NREL (National Renewable Energy Laboratory)

Presented at the Sustainable Transportation Energy Pathways Spring 2015 Symposium on May 13, 2015, this presentation by Jeff Gonder of the National Renewable Energy Laboratory (NREL) provides information about NREL's transportation energy impact analysis of connected and automated vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Transportation Deployment; NREL (National Renewable Energy Laboratory)

Automakers, commercial fleet operators, component manufacturers, and government agencies all turn to the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) to help put more green vehicles on the road. The lab’s independent analysis and evaluation pinpoint fuel-efficient and low-emission strategies to support economic and operational goals, while breaking down barriers to widespread adoption. Customized assessment of existing equipment and practices, energy-saving alternatives, operational considerations, and marketplace realities factor in the multitude of variables needed to ensure meaningful performance, financial, and environmental benefits. NREL provides integrated, unbiased, 360-degree sustainable transportation deployment expertise encompassing alternative fuels, advanced vehicles, and related infrastructure. Hands-on support comes from technical experts experienced in advanced vehicle technologies, fleet operations, and field data collection coupled with extensive modeling and analysis capabilities. The lab’s research team works closely with automakers and vehicle equipment manufacturers to test, analyze, develop, and evaluate high-performance fuel-efficient technologies that meet marketplace needs.

33 ADVANCED PROPULSION SYSTEMS↗

NREL/Industry Range-Extended Electric Vehicle for Package Delivery

Range-extended electric vehicle (EV) technology can be a viable option for reducing fuel consumption from medium-duty (MD) and heavy-duty (HD) engines by approximately 50 percent or more. Such engines have wide variations in use and duty cycles, however, and identifying the vocations/duty cycles most suitable for range-extended applications is vital for maximizing the potential benefits. This presentation provides information about NREL's research on range-extended EV technologies, with a focus on NREL's real-world data collection and analysis approach to identifying the vocations/duty cycles best suited for range-extender applications and to help guide related powertrain optimization and design requirements. The presentation also details NREL's drive cycle development process as it pertains to package delivery applications.

25 ENERGY STORAGE↗

Sustainable Port Operations: Powered by NREL

Seaports are vital economic hubs that allow the United States to compete on a global scale. But the heavy vehicles and cargo equipment that enable their operations also emit harmful air pollutants and greenhouse gas emissions. For nearly two decades, National Renewable Energy Laboratory (NREL) researchers have worked toward comprehensive seaport decarbonization. They fuse world-class analysis with deep vehicle and transportation systems knowledge to guide strategic deployment of low- and zero-emissions vehicles, charging and refueling infrastructure, and grid improvements. Together, these capabilities can enable sustainable port operations. This fact sheet outlines major seaport and airport decarbonization capabilities across the laboratory, including: fleet research, energy data, and insights for decarbonization; comprehensive hydrogen infrastructure deployment; optimized charging through grid integration; strategic blueprinting for clean, optimized technology deployment; and integrating diversity, equity, inclusion, and accessibility considerations into decarbonization efforts.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗