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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Feasibility of Operating a Heavy-Duty Battery Electric Truck Fleet for Drayage Applications

Vehicle fleet electrification is regarded as one major pathway toward achieving energy independence and reducing air pollution and greenhouse gas emissions. Compared to light-duty and medium-duty vehicles, electrification of heavy-duty vehicles, especially Class 8 trucks, is more challenging owing to the battery size required to attain the driving range necessary for their operating goals. As drayage trucks generally have a limited daily mileage, return to a home base every night, and spend a large amount of time creeping and idling, drayage operation has been the first targeted application for Class 8 electric trucks. The feasibility of operating battery electric drayage trucks at the individual vehicle level has recently been demonstrated. However, questions remain as to whether these trucks are capable of meeting the needs of typical drayage operation at the fleet level. Here we present a feasibility analysis of operating an electric truck fleet based on real-world operation data of a diesel drayage operator in Southern California. Second-by-second activity data collected from 20 trucks in the fleet were used to estimate the corresponding electric energy consumption and the state of charge of the battery using a microscopic electric energy consumption model. An algorithm for generating tours of drayage activity from the collected data was developed and implemented. Multiple scenarios with different battery charging and truck scheduling assumptions were analyzed. The results show that 85% of the tours could be served by electric trucks if there is opportunity for charging at the home base during the time gap between consecutive tours.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Plug-In Hybrid Urban Delivery Truck Technology Demonstration

The I-710 and CA-60 highways are key transportation corridors in the Southern California region that are heavily used on a daily basis by heavy duty drayage trucks that transport the cargo from the ports to the inland transportation terminals. These terminals, which include store/warehouses, inland-railways, are anywhere from 5 to 50 miles in distance from the ports. The concentrated operation of these drayage vehicles in these corridors has had and will continue to have a significant impact on the air quality in this region whereby significantly impacting the quality of life in the communities surrounding these corridors. To reduce these negative impacts it is critical that zero and near-zero emission technologies be developed and deployed in the region. A potential local market size of up to 46,000 trucks exists in the South Coast Air Basin, based on near- dock drayage trucks and trucks operating on the I-710 freeway. The South Coast Air Quality Management District (SCAQMD), California Air Resources Board (CARB) and Southern California Association of Governments (SCAG) — the agencies responsible for preparing the State Implementation Plan required under the federal Clean Air Act — have stated that to attain federal air quality standards the region will need to transition to broad use of zero and near zero emission energy sources in cars, trucks and other equipment (Southern California Association of Governments et al, 2011). SCAQMD partnered with Volvo Trucks to develop, build and demonstrate a prototype Class 8 heavy-duty plug-in hybrid drayage truck with significantly reduced emissions and fuel use. Volvo’s approach leveraged the group’s global knowledge and experience in designing and deploying electromobility products. The proprietary hybrid driveline selected for this proof of concept was integrated with multiple enhancements to the complete vehicle in order to maximize the emission and energy impact of electrification. A detailed review of all technologies included in the demonstrator is presented in this report. The project was completed in July 2015 with a final demonstration of the concept vehicle on a simulated drayage route around Volvo’s North American headquarters in Greensboro, NC. The route included all traffic conditions typical of drayage operation in Southern California as well as geofences defined to showcase the zero emission capabilities of the truck. The demonstrator successfully completed four consecutive trips with a gross combined vehicle weight of 44,000 lb., covering approximately 2 miles out of a total distance of 9 miles per trip in the Zero Emission (ZE) geofence. This vehicle is expected to use approximately 30% less fuel than a typical drayage truck in daily operation, and it is designed to allow full electric operation whenever operating in a marine terminal in the ports of Los Angeles / Long Beach. A paper study on the feasibility of expanding the capabilities of the plug-in hybrid concept developed as part of this project was also delivered as an addendum to the regular progress reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Charging Needs for Battery Electric Semi-Trucks

Battery-electric vehicles provide a pathway to decarbonize heavy-duty trucking, but the market for heavy-duty battery-electric semi-trailer trucks is nascent, and specific charging requirements remain uncertain. We leverage large-scale vehicle telematics data (>205 million miles of driving) to estimate the charging behaviors and infrastructure requirements for U.S. battery-electric semi-trailer trucks within three operating segments: local, regional, and long-haul. We model two types of charging; mid-shift (fast) and off-shift (slow), and show that off-shift charging at speeds compatible with current light-duty charging infrastructure (i.e., =350 kW) can supply 35 to 77% of total energy demand for local and regional trucks with =300-mile range. Megawatt-level speeds are required for mid-shift charging, which make up 44 to 57% of energy demand for long-haul trucks with =500-mile range. However, demand shifts from mid-shift to off-shift charging as the range for battery-electric trucks increases and when off-shift charging is widely available. Finally, we observe geographic trends in charging demand, finding that local trucks have greater demand within urban areas, whereas long-haul trucks have more demand along rural interstate corridors. As the range for battery-electric trucks increases, we show that charging demand shifts from rural to urban locations due to observed vehicle dwell tendencies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Impact of Lateral Alignment for Cooling Airflow during Heavy-Truck Platooning

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. The truck platooning system was tested at four gap distances from 9 to 23 meters and the following truck was either aligned with the lead or offset with a 25% width (0.65 m) or 50% width (1.3 m) lateral distance. The experimental results clearly show that offset driving is effective at bringing cooling airflow from 56% with an aligned platoon back up to 75%-80% with minimal impact to fuel savings. In addition, the offset driving can also reduce the trailing truck’s engine coolant temperature by 2°C and the corresponding underhood temperature rise by 10°C. The test outcomes indicate a plausible controls strategy to mitigate reduced cooling flow during hot-weather truck platooning while still enabling the highest-energy-saving, close-following scenarios.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2011

Medium Truck Duty Cycle Data from Real-World Driving Environments: Project Interim Report

Since the early part of the 20th century, the US trucking industry has provided a safe and economical means of moving commodities across the country. At the present time, nearly 80% of the US domestic freight movement involves the use of trucks. The US Department of Energy (DOE) is spearheading a number of research efforts to improve heavy vehicle fuel efficiencies. This includes research in engine technologies (including hybrid and fuel cell technologies), lightweight materials, advanced fuels, and parasitic loss reductions. In addition, DOE is developing advanced tools and models to support heavy vehicle truck research, and is leading the 21st Century Truck Partnership whose stretch goals involve a reduction by 50% of the fuel consumption of heavy vehicles on a ton-mile basis. This Medium Truck Duty Cycle (MTDC) Project is a critical element in DOE s vision for improved heavy vehicle energy efficiency and is unique in that there is no other national database of characteristic duty cycles for medium trucks. It involves the collection of real-world data for various situational characteristics (rural/urban, freeway/arterial, congested/free-flowing, good/bad weather, etc.) and looks at the unique nature of medium trucks drive cycles (stop-and-go delivery, power takeoff, idle time, short-radius trips), to provide a rich source of data that can contribute to the development of new tools for fuel efficiency and modeling, provide DOE a sound basis upon which to make technology investment decisions, and provide a national archive of real-world-based medium-truck operational data to support heavy vehicle energy efficiency research. The MTDC project involves a two-part field operational test (FOT). For the Part-1 FOT, three vehicles, each from two vocations (urban transit and dry-box delivery) were instrumented for one year of data collection. The Part-2 FOT will involve the towing/recovery and utility vocations. The vehicles participating in the MTDC project are doing so through gratis partnerships in return for early access to the results of this study. Partnerships such as these are critical to FOTs in which real-world data is being collected. In Part 1 of the project, Oak Ridge National Laboratory(ORNL) established partnerships with the H.T. Hackney Company, one of the largest wholesale distributors in the country, distributing products to 21 states; and with the Knoxville Area Transit (KAT), the City of Knoxville s transit system, operating services across the city of Knoxville and parts of Knox co. These partnerships and agreements provided ORNL access to three Class-7 2005/2007 International day-cab tractors, model 8600, which regularly haul 28 ft pup trailers (H.T. Hackney Co) and three Class-7 2005 Optima LF-34 buses (KAT), for collection of duty cycle data. In addition, ORNL has collaborated with the Federal Motor Carrier Safety Administration (FMCSA) to determine if there were possible synergies between this duty cycle data collection effort and FMCSA s need to learn more about the operation and duty cycles of the second-largest fuel consuming commercial vehicle category in the US. FMCSA s primary interest was in collecting safety data relative to the driver, carrier, and vehicle. In order to collect the duty cycle and safety-related data, ORNL developed a data acquisition and wireless communication system that was placed on each test vehicle. Each signal recorded in this FOT was collected by means of one of the instruments incorporated into each data acquisition system (DAS). Native signals were obtained directly from the vehicle s J1939 and J1708 data buses. A VBOX II Lite collected Global Positioning System related information including speed, acceleration, and spatial location information at a rate of 5 Hz, and communicated this data via the CAN (J1939) protocol. The Air-Weigh LoadMaxx, a self-weighing system which determines the vehicle s gross weight by means of pressure transducers and posts the weight to the vehicle s J1939 data bus, was used to collect vehicle payload information. A cellular modem, the Raven X EVDO V4221, facilitated the communication between the eDAQ-lite (the data collection engine of the system) and the user, via the internet. The modem functioned as a wireless gateway, allowing data retrievals and system checks to be performed remotely. Also, and in partnership with FMCSA, two additional safety sensors were installed on the combination vehicles: the MGM e-Stroke brake monitoring system and the Tire SafeGuard tire pressure monitoring system. Both of these systems posted data to the J1939 data bus, enabling these signals to be read without any additional DAS interface hardware. Seventy-three signals from the different deployed sensors and available vehicle systems were collected. Because of the differences in vehicle data buses (i.e., J1939 and J1708 data buses), not all desired signals were available for both types of vehicles.

duty cycles↗
DOE OSTI2012

Medium Truck Duty Cycle Data from Real-World Driving Environments (Project Final Report)

Since the early part of the 20th century, the US trucking industry has provided a safe and economical means of moving commodities across the country. At present, nearly 80% of US domestic freight movement involves the use of trucks. The US Department of Energy (DOE) is spearheading a number of research efforts to improve heavy vehicle fuel efficiencies. This includes research in engine technologies (including hybrid and fuel cell technologies), lightweight materials, advanced fuels, and parasitic loss reductions. In addition, DOE is developing advanced tools and models to support heavy vehicle research and is leading the 21st Century Truck Partnership and the SuperTruck development effort. Both of these efforts have the common goal of decreasing the fuel consumption of heavy vehicles. In the case of SuperTruck, a goal of improving the overall freight efficiency of a combination tractor-trailer has been established. This Medium Truck Duty Cycle (MTDC) project is a critical element in DOE’s vision for improved heavy vehicle energy efficiency; it is unique in that there is no other existing national database of characteristic duty cycles for medium trucks based on collecting data from Class 6 and 7 vehicles. It involves the collection of real-world data on medium trucks for various situational characteristics (e.g., rural/urban, freeway/arterial, congested/free-flowing, good/bad weather) and looks at the unique nature of medium trucks’ drive cycles (stop-and-go delivery, power takeoff, idle time, short-radius trips). This research provides a rich source of data that can contribute to the development of new tools for FE and modeling, provide DOE a sound basis upon which to make technology investment decisions, and provide a national archive of real-world-based medium-truck operational data to support energy efficiency research. The MTDC project involved a two-part field operational test (FOT). For the Part-1 FOT, three vehicles each from two vocations (urban transit and dry-box delivery) were instrumented for the collection of one year of operational data. The Part-2 FOT involved the towing and recovery and utility vocations for a second year of data collection.

CMV↗
DOE OSTI2015

Design and Validation Testing of TruckScan to Assay Large Sacks of Fukushima Radioactive Debris on a Truck

As a result of the March 2011 earthquake and resulting tsunami in Japan, there was a serious accident at the Fukushima Dai-ichi Nuclear Power Plant. This accident has contaminated soil and vegetation in a wide area around the plant. Decontamination projects over the last 4 years have resulted in large numbers of 1 cubic meter canvas bags of debris, commonly called Super Sacks [SS]. These are currently stored nearby where they were generated, but starting in 2015, they will be moved to various Interim Storage Facilities [ISF]. Trucks will typically carry 8-20 of these SSs. When the trucks arrive at the ISF they need to be rapidly sorted into groups according to radioactivity level, for efficient subsequent processing. Canberra Industries, Inc. [CI] has designed a new truck monitoring system 'TruckScan' for use at these ISFs. The TruckScan system must measure the entire truck loaded with multiple closely packed SSs, and generate a nuclide specific assay report showing the radioactivity in each individual SS. The Canberra-Japan office, along with Obayashi Corporation have performed validation testing to demonstrate to the regulatory authorities that the proposed technique was sufficiently accurate. These validation tests were conducted at a temporary storage area in Fukushima prefecture. Decontaminated waste of various representative types and of various levels of radioactivity was gathered and mixed to create homogeneous volumes. These volumes were sampled multiple times and assayed with laboratory HPGe detectors to determine the reference concentration of each pile. Multiple SSs were loaded from each pile. Some of the SSs were filled 50% full, others 75% full, and others 100% full, to represent the typical loading configuration of the existing SSs in the field. The content of the SSs are either sand, soil, or vegetation with densities ranging from 0.3 g/cc - 1.6 g/cc. These SSs with known concentrations of Cs-134 and Cs-137 were then loaded onto trucks in a variety of configurations, typical of how they might be on the real trucks. A partial system was installed at the site and used to assay these trucks with the various loading configurations. Whereas the full system will have 8 collimated 3 x 3'' NaI detectors, the test system only had two detectors; therefore the truck was moved and counted 4 times. The data were acquired and analyzed with the Canberra Genie software to determine the peak counts for both Cesium nuclides. That data was then analyzed with a prototype version of a Maximum Entropy algorithm, to determine the individual SS activity. The goal of the validation tests was to demonstrate that the system could detect 1000 Bq/kg in 15 seconds, and to determine how accurately it could quantify individual SSs. The validation tests demonstrated that the product would perform as predicted. The TruckScan results were consistent with the sample assay results [y = 1.0029 x, R{sup 2} = 0.914]. The Total Propagated Uncertainty, including both uncertainties from these tests and others that were estimated but not tested was 16.6% percent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗
DOE OSTI2020

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Platooning has the potential to reduce greenhouse gas missions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. For real world application and accurate return on investment for potential adopters, non-uniform platoons and the impacts of grade and disturbances on a platoon’s fuel economy must also be characterized. This study investigates the fuel economy of a heterogeneous four-truck platoon on a closed test track. Tests were run for one hour at a speed of 45 mph. The trucks used for this study are two 2015 Peterbilt 579’s with a Cummins ISX15 and a Paccar MX-13, and two 2009 Freightliner M915A5’s, one armored and the other unarmored. Many analysis methodologies were leveraged to describe and compare the fuel data, including lap-wise and track-segment analysis. The methodology for dividing the data into laps is described in detail. The influence of other factors beyond the aerodynamics of platooning is discussed. CAN fuel rate analysis showed excellent agreement with previous experimental trends for two and three-truck platoons. In general, the indicated fuel economy benefits in this study were 5-11% for following vehicles and 0-4% for the lead vehicle in platoon relative to their baseline fuel consumption. On a cumulative basis, all platoons saved fuel, ranging from 6% to 8% versus the sum of the standalone trucks’ fuel consumption. The practical implications of the fuel economy results are discussed, as well as avenues for future research. Introduction and Motivation platooning is controlled coordination of two or more vehicles in a convoy, sometimes called CACC (Coordinated or Cooperative Adaptive Cruise Control). The distance between vehicles in a platoon can be controlled tightly at no additional fatigue to the driver. Platooning vehicles can also respond quickly to braking events of the leader, much more quickly than the typical human driver’s reaction time of 1-1.5 s. Therefore, vehicles in a platoon can follow each other much more closely than would usually be considered a safe following distance under human operation. It is implied that under very close following conditions, platooning technology must be extremely robust before it is safe for wide-scale implementation. Platooning is under investigation as a fuel-saving technology. Close-following significantly reduces aerodynamic drag for both leading and trailing vehicles. According to the NRC in 2010, aerodynamic drag represents roughly half of a Class-8 truck’s on-highway fuel usage, meaning a 20% reduction in drag roughly equals a 10% reduction in fuel usage, if all other sources of energy loss remain equal (i.e. accessory, rolling resistance, drivetrain, braking). It is by aerodynamics that platooning saves fuel. At risk of oversimplifying the aerodynamics, following (or trailing) vehicles experience reduced wind velocity due to shielding, and the leading vehicles experience an increased aft pressure, especially at distances closer than 75’ (23 m).

greenhouse gas emissions, truck platoon, heavy-dut↗
DOE OSTI2018

Influences on Energy Savings of Heavy Trucks Using Cooperative Adaptive Cruise Control

An integrated adaptive cruise control (ACC) and cooperative ACC (CACC) was implemented and tested on three heavy-duty tractor-trailer trucks on a closed test track. The first truck was always in ACC mode, and the followers were in CACC mode using wireless vehicle-vehicle communication to augment their radar sensor data to enable safe and accurate vehicle following at short gaps. The fuel consumption for each truck in the CACC string was measured using the SAE J1321 procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb, demonstrating the effects of: inter-vehicle gaps (ranging from 3.0 s or 87 m to 0.14 s or 4 m, covering a much wider range than previously reported tests), cut-in and cut-out maneuvers by other vehicles, speed variations, the use of mismatched vehicles (standard trailers mixed with aerodynamic trailers with boat tails and side skirts), and the presence of a passenger vehicle ahead of the platoon. The results showed that energy savings generally increased in a non-linear fashion as the gap was reduced. The middle truck saved the most fuel at gaps shorter than 12 m and the trailing truck saved the most at longer gaps, while lead truck saved the least at all gaps. The cut-in and cut-out maneuvers had only a marginal effect on fuel consumption even when repeated every two miles. The presence of passenger-vehicle traffic had a measurable impact. The fuel-consumption savings on the curves was less than on the straight sections.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Comparative Study of Hybrid Powertrains on Fuel Saving, Emissions, and Component Energy Loss in HD Trucks

We compared parallel and series hybrid powertrains on fuel economy, component energy loss, and emissions control in Class 8 trucks over both city and highway driving. A comprehensive set of component models describing battery energy, engine fuel efficiency, emissions control, and power demand interactions for heavy duty (HD) hybrids has been integrated with parallel and series hybrid Class 8 trucks in order to identify the technical barriers of these hybrid powertrain technologies. The results show that series hybrid is absolutely negative for fuel economy benefit of long-haul trucks due to an efficiency penalty associated with the dual-step conversions of energy (i.e. mechanical to electric to mechanical). The current parallel hybrid technology combined with 50% auxiliary load reduction could elevate 5-7% fuel economy of long-haul trucks, but a profound improvement of long-haul truck fuel economy requires additional innovative technologies for reducing aerodynamic drag and rolling resistance losses. The simulated emissions control indicates that hybrid trucks reduce more CO and HC emissions than conventional trucks. The simulated results further indicate that the catalyzed DPF played an important role in CO oxidations. Limited NH 3 emissions could be slipped from the Urea SCR, but the average NH 3 emissions are below 20 ppm. Meanwhile our estimations show 1.5-1.9% of equivalent fuel-cost penalty due to urea consumption in the simulated SCR cases.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Charging Needs for Battery Electric Semi Trucks

Battery-electric vehicles provide a pathway to decarbonize heavy-duty trucking, but the market for electric trucks is nascent, and specific charging requirements remain uncertain. This paper summarizes methods and findings from Charging Needs for Electric Semi-Trailer Trucks [1] wherein we leverage large-scale vehicle telematics data (>205 million miles of driving) to estimate the charging behaviors and infrastructure requirements for U.S. battery-electric semi-trailer trucks within three operating segments: local, regional, and long-haul. We model two types of charging - mid-shift (fast en-route charging) and off-shift (slow depot charging) - and show that off-shift charging at speeds compatible with current light-duty charging infrastructure (i.e., =350 kW) can supply 35% to 77% of total energy demand for local and regional trucks with =300-mile range. Megawatt-level speeds are required for mid-shift charging, which make up 44% to 57% of energy demand for long-haul trucks with =500-mile range. However, the role of off-shift charging increases as the range for battery-electric trucks increases and when off-shift charging is widely available.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Fuel assembly shaker and truck test simulation

This study continues the modeling support of the SNL shaker table task from 2013 and includes analysis of the SNL 2014 truck test campaign. Detailed finite element models of the fuel assembly surrogate used by SNL during testing form the basis of the modeling effort. Additional analysis was performed to characterize and filter the accelerometer data collected during the SNL testing. The detailed fuel assembly finite element model was modified to improve the performance and accuracy of the original surrogate fuel assembly model in an attempt to achieve a closer agreement with the low strains measured during testing. The revised model was used to recalculate the shaker table load response from the 2013 test campaign. As it happened, the results remained comparable to the values calculated with the original fuel assembly model. From this it is concluded that the original model was suitable for the task and the improvements to the model were not able to bring the calculated strain values down to the extremely low level recorded during testing. The model needs more precision to calculate strains that are so close to zero. The truck test load case had an even lower magnitude than the shaker table case. Strain gage data from the test was compared directly to locations on the model. Truck test strains were lower than the shaker table case, but the model achieved a better relative agreement of 100-200 microstrains (or 0.0001-0.0002 mm/mm). The truck test data included a number of accelerometers at various locations on the truck bed, surrogate basket, and surrogate fuel assembly. This set of accelerometers allowed an evaluation of the dynamics of the conveyance system used in testing. It was discovered that the dynamic load transference through the conveyance has a strong frequency-range dependency. This suggests that different conveyance configurations could behave differently and transmit different magnitudes of loads to the fuel even when traveling down the same road at the same speed. It is recommended that the SNL conveyance system used in testing be characterized through modal analysis and frequency response analysis to provide context and assist in the interpretation of the strain data that was collected during the truck test campaign.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Application of Sleeper Cab Thermal Management Technologies to Reduce Idle Climate Control Loads in Long-Haul Trucks

Each intercity long-haul truck in the U.S. idles approximately 1,800 hrs per year, primarily for sleeper cab hotel loads. Including workday idling, over 2 billion gallons of fuel are used annually for truck idling. NREL's CoolCab project works closely with industry to design efficient thermal management systems for long-haul trucks that keep the cab comfortable with minimized engine idling andfuel use. The impact of thermal load reduction technologies on idle reduction systems were characterized by conducting thermal soak tests, overall heat transfer tests, and 10-hour rest period A/C tests. Technologies evaluated include advanced insulation packages, a solar reflective film applied to the vehicle's opaque exterior surfaces, a truck featuring both film and insulation, and abattery-powered A/C system. Opportunities were identified to reduce heating and cooling loads for long-haul truck idling by 36% and 34%, respectively, which yielded a 23% reduction in battery pack capacity of the idle-reduction system. Data were also collected for development and validation of a CoolCalc HVAC truck cab model. CoolCalc is an easy-to-use, simplified, physics-based HVAC loadestimation tool that requires no meshing, has flexible geometry, excludes unnecessary detail, and is less time-intensive than more detailed computer-aided engineering modeling approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each n close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces green- house gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.

vehicle platooning, sensor performance, semi-auton↗
DOE OSTI2022

Control Oriented Model of Cabin-HVAC System in a Long-Haul Trucks for Energy Management Applications

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output. Second, a two-node cabin model formulated to estimate the cabin temperature as a function of the Global Horizontal Irradiance (GHI), HVAC load and ambient temperature. The models are calibrated using experimental cabin-HVAC system data as for long-haul class 8 truck (e.g. ST-II). Here, the model simulations show that the overall Root Mean Square Error (RMSE) value of 0.4°C between the experimental and simulated cabin temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

National Energy Impacts of Heavy Electric Truck Adoption For Freight

Freight trucks are projected to account for nearly 30% of transportation sector energy use in 2050 in the United States. Potentially some of the freight energy use and associated emissions can be reduced by electrified vehicle technologies, smart technologies (e.g. platooning, driverless truck), and possible mode shifts. Several U.S. truck makers, new startups, and independent engine manufacturers made announcements of taking commericialized medium- and heavy-duty trucks into production for these emerging technologies. By analyzing the freight shipment by commodity and freight zones, the study objectives are 1) idenfiy long-haul freight miles that could be electrified without on-route charging infrastructure; and 2) quantify future energy consumption impacts. This paper utilized Argonne’s NEAT and VISION models to estimate the potential energy impacts of electric truck adoption by 2050 in the United States. Analysis results shows that either a Class 7 and 8 electric truck with 500-mile electric range could potentially reduce the petroleum consumption by 1.61 quad in 2050, while the electricity consumption increases by 0.99 quad.

Electric heavy duty truck, freight↗