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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

On High-Temperature Dynamometer Test Stand Development

RePED is a novel prototype alternator that has been designed and built to operate at 35 kW under 250 degrees C ambient temperature conditions. The operating efficiency will be measured using a 225-kW motor to drive the machine in a back-to-back configuration. The goal is to determine if the RePED alternator can deliver 35 kW at a rotational speed of 1,000 rpm while operating in 250 degrees C ambient temperature and have a minimum efficiency of 60%. Dynamometer testing of a high-temperature alternator for geothermal drilling presents several unique challenges, especially around maintaining and managing the various sources and types of energy passing through the system without impacting data quality. The objectives of this report are to (1) describe the test stand in detail, the relative orientation of each major component, and the data acquisition system and (2) discuss the behavior of the test stand components such that this report can serve as a reference document for future projects.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Assessing the National Off-Cycle Benefits of 2-Layer HVAC Technology Using Dynamometer Testing and a National Simulation Framework

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. Validation of component thermal models and engine efficiency ensured accurate thermal dynamics, fuel consumption, and two-layer benefit. The real-world benefit of the two-layer technology was calculated by simulating the validated powertrain model across a representative test matrix comparing performance with and without the two-layer system. Simulation across the test matrix revealed a real-world representative benefit of 0.0835%. Analysis of test matrix results at the regional level revealed the most benefit in cold climates and rural regions. Mean results across cycle length sensitivity simulations revealed a larger real-world benefit of 0.0872%. These benefit values can be considered a more accurate assessment of real-world technology performance. Future work is planned to explore the requisite number of drive cycles to ensure the full technology benefit is captured.

2-layer↗
DOE OSTI2023

Analysis of Uncertainty Impacts on Emissions and Fuel Economy Evaluation for Chassis Dynamometer Testing

This study illustrates a methodology for quantifying the uncertainties encountered in the measurement of tailpipe emissions and in the fuel consumption measurements for light-duty conventional vehicles tested on a four-wheel drive chassis dynamometer. The study leverages high-fidelity experimental data collected over three standard drive cycles, UDDS, HWY and US06, intended to simulate a wide range of operating conditions. Here, a method is developed to estimate the measurement uncertainties in fuel consumption for a test cycle, which occur due to the accumulation of measurement uncertainties propagated through the system. The uncertainty determination model uses statistical analysis and standard propagation techniques to evaluate and combine the uncertainties introduced from various sources (including the vehicle, chassis dynamometer, driver, and instrumentation). The analysis also examines three different experimental methods for determining the fuel consumption: 1) carbon mass balance, 2) volumetric fuel scale and 3) gravimetric fuel scale, and takes into consideration the properties of the instrumentation used. The results show that the most significant influence on the determination of the emissions comes from the concentration measurement, and similarly the biggest impact on the total fuel consumption uncertainty comes from the uncertainty in the determination of the carbon dioxide mass, due to the large presence of this pollutant in the overall emissions. It was found that the fuel consumption uncertainties are in the range of ±1-2% for all three methods analyzed, with the lowest values being obtained for measurements performed using the gravimetric method for all three drive cycles considered.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Polyalkylene Glycol (PAG) Based Lubricant for Light & Medium Duty Axles

The axle lubricant (SAE 75W-140) widely used in the market place over the last few years is primarily formulated from polyalpha olefin (PAO) basestock. This investigation focused on polyalkylene glycol (PAG) base stock which is significantly different chemically from PAO and because of their polar nature it is hypothesized that it can adsorb relatively easily on contacting surfaces resulting in significant friction reduction and improve fuel economy. Axle efficiency is generally quite high at high torque range but it could be quite low at low torque range representative of EPA drive cycles. Therefore, this project primarily focus on improving axle efficiency in the low torque range while maintaining all durability attributes. The objective of this project is to develop novel lubricant formulations that are expected to improve the fuel efficiency of light, medium, heavy-duty, and military vehicles by at least 2% over Society of Automotive Engineers (SAE) 75W-140 axle lubricants (improvement based on comparative results from engine dynamometer testing, chassis dynamometer testing or test track, e.g., SAE J1321) without adverse impacts on vehicle performance or durability. The proposed research project followed a structured approach beginning with lubricant formulations by varying base oil chemistry and additive components followed by physical property characterization. Lubricant performance evaluations started with simple laboratory friction, wear, oxidation, and corrosion tests which guided into identification of performance areas requiring improvements. This required an iterative lubricant reformulation. Once a few acceptable formulations were identified, they are evaluated in more complex component tests including ASTM tests (L-37 - load carrying capacity under low speed and high torque, L42 – load carrying properties under high speed and shock loading, L-60 - thermal and oxidative stability, and L-33-1 moisture corrosion resistance). Two issues were observed following L-42 tests; toxicological and foaming. This required reformulation and repeating all ASTM tests. During repeat tests it was observed that some of the additives precipitated out of solution. Since it was discovered quite late in the program, and the time it may need to find a solution to this issue, the team changed direction of the program to switch to use of an oil soluble PAG as a co-basestock (15-30%) with mineral oil used in a commercial formulation (SAE 75W-85). This formulation strategy helped passing all ASTM tests. This was followed by Ford proprietary axle efficiency, gear wear, and chassis roll dynamometer tests for fuel economy evaluations. Axle efficiency was improved up to 7% when a full PAG formulation was used but no such significant improvement was observed with PAG as co-basestock formulation. Chassis roll fuel economy improved by 1.9% with PAG co-basestock formulation (conforming to SAE 75W-85) compared to SAE 75W-140 baseline. However, it was observed that the improvement is mostly due to reduced viscosity of candidate formulation when compared to a full mineral oil based SAE 75W-85 formulation. PAG as co-basestock also exhibited unacceptable wear in proprietary gear wear test. This investigation highlighted challenges with PAG formulations including identification of additive components that stay in PAG solution for intended duration, and meeting component durability requirement.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Automotive fuel cell stack and system efficiency and fuel consumption based on vehicle testing on a chassis dynamometer at minus 18 °C to positive 35 °C temperatures

In this work we present an in-depth laboratory technology assessment of a 2016 Toyota Mirai Fuel Cell (FC) vehicle based on chassis dynamometer testing. The 114.6 kW FC stack has a high dynamic response, which makes this powertrain a FC-dominant hybrid electric vehicle. The measured peak efficiency is 66.0% FC stack and 63.7% FC system with an idle hydrogen flow rate of 4.39 g/hr. The high FC system efficiencies at low loads match typical vehicle power spectrums, resulting in a high average vehicle efficiency of 62% compared to 45% and 23% for a hybrid electric vehicle and a conventional vehicle, respectively. An energy breakdown accounts for the FC stack losses, FC system losses, air compressor loads, and heater loads for different drive cycles and different thermal conditions. The cold-start North American city drive cycle (UDDS) energy consumption values are, respectively, 758, 581, 226, and 321 Wh/km at ambient conditions of -18 degrees C, -7 degrees C, -25 degrees C and 35 degrees C with 850 W/m 2 of solar loading. The FC system shutdown and startup processes at temperatures below the freezing point contribute to the increased hydrogen consumption. Additionally, the raw test data files are available for download, thus providing the research community with a public reference data on a modern production automotive FC system.

08 HYDROGEN↗
DOE OSTI2021

Using Ionic Liquid Additive to Enhance Lubricating Performance for Low-Viscosity Engine Oil

Energy efficient lubricants are essential for sustainable transportation, and the trend is to develop and implement lower viscosity lubricants with more effective additives. Ionic liquids (ILs) have been reported as candidate additives with superior friction and wear reducing capabilities. Unlike most literature relying on bench-scale testing of simple oil–IL blends, this study produced low-viscosity (SAE 0W-12) fully formulated engine oils using a phosphonium-organophosphate IL as an antiwear additive and evaluated them in both bench-scale tribological testing and full-scale fired engine dynamometer testing. The experimental formulation containing a combination of ZDDP and IL outperformed the formulations using either ZDDP or IL alone, as well as a commercial SAE 0W-20 engine oil in terms of mitigating boundary friction, wear, and contact fatigue-induced micropitting. Furthermore, racing engine dynamometer tests demonstrated 3–4 °C lower oil temperature, 4–5 ft-lbs higher horsepower output, and up to 9.9% better fuel economy for the IL-containing SAE 0W-12 experimental oil compared with selected commercial SAE 5W-30 and 0W-20 engine oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Integrated Boosting and Hybridization for Extreme Fuel Economy and Downsizing

The objective of this project was to develop, demonstrate, and evaluate commercialization of a highly efficient downsized engine by electrification of the air delivery and waste heat recovery system and optimizing energy usage to achieve significant fuel economy improvement at a commercially viable cost. The system consists of an Electrically Assisted Variable speed Supercharger (EAVS), driven by an electric motor and the engine through a planetary gear train, that provides engine boost pressure and provides the mild hybrid functions of engine start/stop, torque assist, and brake energy recovery. In the exhaust path of the engine is the electric Waste Heat Recovery (eWHR) system, a roots-based expander driven by another electric motor, that enables exhaust gas energy recovery along with controlled back pressure on the engine. The two electric motors are powered by a 48V rechargeable lithium-ion battery. Further, the EAVS system coupled to an EGR valve enables very precise high exhaust recirculation rates to control the NOx emissions. Through two budget periods, the project team of Eaton, Isuzu, Southwest Research Institute and AVL designed and developed the EAVS and eWHR systems, integrated with an Isuzu diesel engine, and validated the target fuel economy performance and emissions by engine dynamometer testing and vehicle level simulations. GT Power model-based analyses results were used to size the EAVS and eWHR systems for the 1.9L Isuzu Spark engine. The two systems were built and the functional testing was carried out to verify the boosting performance of the superchargers. Following the baseline engine dynamometer testing, the two systems were integrated with the engine and the fuel economy performance and emissions were determined by combined steady state and transient testing over three drive cycles, namely, FTP75, NEDC and HWFET. The EAVS/eWHR system demonstrated 4% improvement in fuel economy for the NEDC cycle in engine dyno testing, correlating well with vehicle simulation results (5.3%). The simulation results indicated that the combination of hybrid functions and drivetrain optimization, fuel economy improvement of more than 20% was feasible with the system. The commercialization study to evaluate the cost of the system and the scalability for different engine/vehicle classes was planned for the final budget period but not completed as the project was closed at the end of budget period two.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

TEAMER: Performance mapping of Re Vision's Persistance PTO

Contains datasets from experimental measurements that were used to validate Re Vision's Persistence PTO's efficiency and performance. These measurements were obtained using a dynamometer test bench setup. The data includes open-circuit voltage and loss measurements to validate machine characteristics, efficiency mapping tests to determine the generator's performance mapping, and efficiency mapping tests to determine the converter's efficiency over the feasible operating range. This data was collected between June 2023 and September 2023. The data was collected at the National Renewable Energy Laboratory's Flatirons Campus, Colorado, United States. The data was collected using NREL's 5-kW dynamometer test bench, equipped with a torque sensor and various voltage and current sensors fed to a dedicated data acquisition system. Units for the data are included in the data file headers for each data series. A text editor or spreadsheet software such as Excel is required to view the *.csv data. The data are also provided in *.mat files. To view data plots, a Matlab script with *.mat files are provided.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

Optimal engine operation during a transient driving cycle is the key to achieving greater fuel economy, engine efficiency, and reduced emissions. In order to achieve continuously optimal engine operation, engine calibration methods use a combination of static correlations obtained from dynamometer tests for steady-state operating points and road and/or track performance data. As the parameter space of control variables, design variable constraints, and objective functions increases, the cost and duration for optimal calibration become prohibitively large. In order to reduce the number of dynamometer tests required for calibrating modern engines, a large-scale simulation-driven machine learning approach is presented in this work. A parallel, fast, robust, physics-based reduced-order engine simulator is used to obtain performance and emission characteristics of engines over a wide range of control parameters under various transient driving conditions (drive cycles). We scale the simulation up to 3,906 nodes of the Theta supercomputer at the Argonne Leadership Computing Facility to generate data required to train a machine learning model. The trained model is then used to predict various engine parameters of interest, and the results are compared with those predicted by the engine simulator. Our results show that a deepneural-network-based surrogate model achieves high accuracy: Pearson product-moment correlation values larger than 0.99 and mean absolute percentage error within 1.07% for various engine parameters such as exhaust temperature, exhaust pressure, nitric oxide, and engine torque. Once trained, the deep-neural-network-based surrogate model is fast for inference: it requires about 16 mu s for predicting the engine performance and emissions for a single design configuration compared with about 0.5 s per configuration with the engine simulator. Moreover, we demonstrate that transfer learning and retraining can be leveraged to incrementally retrain the surrogate model to cope with new configurations that fall outside the training data space.

deep learning↗
DOE OSTI2023

Demonstration of Ego Vehicle and System Level Benefits of Eco-Driving on Chassis Dynamometer

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (i.e., ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification. The large-scale simulation study consisted of doing approximately 96,000 powertrain simulations. A sophisticated clustering scheme was built and utilized to down select representative traces for each scenario from the simulation study for vehicle testing on a chassis dynamometer. Furthermore, this paper provides a summary of individual ego vehicle testing as well as a comprehensive overview of the method utilized for down selecting representative traces from large scale simulation studies that can be used to quantify corridor level benefits. Vehicle test results along with corresponding analyses are presented.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Oil miscible phosphonium-phosphate ionic liquid as novel antiwear and antipitting additive for low-viscosity rear axle lubricants

Here we explored the feasibility of using a phosphonium phosphate ionic liquid as a candidate anti-wear and anti-pitting additive for rear axle lubricant. This particular IL was first added to a VHVI8 base oil at 2–3% concentration and demonstrated effective surface protection for wear and micro-cracking under rolling-sliding contacts. The promising results directed to a step further to produce a series of IL-containing low-viscosity (about a half of SAE 75W-90) fully formulated gear oils. Selected IL-containing experimental oils showed superior mitigation of rolling contact fatigue to a commercial SAE 75W-90 gear oil in bench-scale rolling-sliding tests. Full-scale hub dynamometer tests were then conducted and demonstrated more than 3% power output and torque generation for an IL-containing low-viscosity gear oil benchmarked against commercial baselines.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real-World Evaluation of National Energy Efficiency Potential of Cold Storage Evaporator Technology in the Context of Engine Start-Stop Systems

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. The cold storage technology maintains the thermal state of air-conditioning evaporators to enable longer and more frequent engine-off operation in vehicles equipped with start-stop functionality. Test results were analyzed and provided to NREL where a novel simulation framework was developed and calibrated to the test data. The vehicle model was then exercised over a large set of real-world drive cycle and ambient condition data to estimate national-level fuel economy benefits. Results indicate that the cold storage evaporator provided national fuel consumption reductions of 0.113% relative to a conventional evaporator in the same vehicle. In addition, when the cold storage evaporator engine stop/start was enabled for any temperature and the baseline was limited to the EPA menu, Start and Stop credit assumption of 27°C, a national fuel savings of 0.497% was found. Fuel savings resulted from a combination of extended engine-off duration during idle events and increased frequency of deceleration fuel cutoff, both enabled by the ability of the cold storage evaporator to maintain thermal state in situations where air conditioning is active.

DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Electrical Validation Testing for ORPC MHK Generator, Modification 6: ORPC SBV for MHK Generator System (CRADA Final Report)

For the U.S. Department of Energy’s (DOE) 2016 Small Business Voucher for Marine and Hydrokinetic (MHK) System, Second Round 2016, ORPC intends to work with the National Renewable Energy Laboratory (NREL) to perform dynamometer testing of the MHK generator systems and its associated controls and inverters. ORPC will provide the generator, variable frequency drives (VFD), controls, and inverter for this testing. NREL will utilize the NREL Energy Systems Integration Facility (ESIF) and dynamometer facilities at the National Wind Technology Center (NWTC) for this work. Modification 6: Additionally, NREL will conduct a feasibility study for implementing passive DC rectification at the turbine.

17 WIND ENERGY↗
DOE OSTI2018

Opportunities and Challenges with Polyalkylene Glycol for Engine Oil Application

Base oil plays an important role in engine oil formulation in delivering overall performance attributes in addition to additives. Non-traditional base oil like polyalkylene glycol (PAG) did not get much attention in the past for formulating automotive engine oil. This investigation explored PAGs for enhancing engine oil performance primarily for fuel economy benefit over traditional mineral oil-based formulations. This paper highlights key findings from an extensive investigation, parts of which were published in detail elsewhere, and identifying opportunities and challenges. Several PAG chemistries were investigated depending on their feedstock material. Friction performance was evaluated by several methods starting with laboratory bench tests to engine components to chassis roll dynamometer tests. Durability was also evaluated from laboratory bench tests to engine components to ASTM sequence tests. The investigation revealed that significant friction reduction or fuel economy gain can be achieved with PAG oil but wear protection capability, piston deposit, and varnish require much improvement requiring identification/development of additive components. A few alternative routes for performance improvement are suggested.

Gangopadhyay, Arup↗
DOE OSTI2021

A Deterministic Multivariate Clustering Method for Drive Cycle Generation from In-Use Vehicle Data

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data. This paper explores the development and initial validation of a method of generating representative drive cycles from large collections of real-world vehicle data using a deterministic multivariate clustering approach. Starting with theory and diving into the methodology behind representative cycle generation, the paper aims to also present graphical and tabular results of initial validation via vehicle simulation and chassis dynamometer testing. Additional topics for further research and areas for ongoing development will also be presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2020

Integrated friction reduction technology to improve fuel economy without sacrificing durability

This project aims to develop fuel economy technologies to minimize parasitic losses within vehicle engines and drivetrains by improving fuel economy at least 2% for 2014 legacy vehicles and 2018 vehicles without adverse impacts on engine durability. The tools used are advanced low viscosity lubricants and surface material technologies, including surface textures, and coatings. Working with industrial partners, an experimental fuel efficient low viscosity lubricant was developed, verified by ASTM fuel economy engine test for 2014 vehicle population. An ultralow viscosity lubricant was also developed for 2018 engines, demonstrated by engine chassis dynamometer tests. Surface texturing of engine components was also conducted, and in engine testing, confirmed the textured engine developed more torque and power while the textures largely stayed intact after the test.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Gearbox high-speed-stage bearing slip induced by electric excitation in a test facility

The goal of this paper is to investigate the behaviour of the high-speed stage of a wind turbine gearbox during transient grid-loss events triggered at different power levels in a full-scale nacelle dynamometer test. The gear mesh behaviour and the bearing roller slip during these events are characterized by strain measurements placed in the gear teeth roots and embedded in the outer rings of the tapered roller bearing locating pair. From our experiments, we conclude that the high-speed stage experiences a multidimensional loading consisting of bending and torsional deformation during the transient event. This loading propagates throughout the gearbox and results in unfavourable loading conditions at the bearing that have the potential to go beyond the preload during the torque reversals that occur during the grid-loss event. During the torque reversal, roller slip can occur in the bearings. It is observed that the slip behaviour is directly linked to the initial power level of the generator. Electrically induced excitation that typically leads to dynamic torque events can therefore cause mechanical gearbox degradation.

17 WIND ENERGY↗