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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An OpenStreetMaps based tool to study the energy demand and emissions impact of electrification of medium and heavy-duty freight trucks

In this paper, we present the mathematical formulation of an OpenStreetMaps (OSM) based tool that compares the costs and emissions of long-haul medium and heavy-duty (M&HD) electric and diesel freight trucks, and determines the spatial distribution of added energy demand due to M&HD EVs. The optimization utilizes a combination of information on routes from OSM, utility rate design data across the United States, and freight volume data, to determine these values. In order to deal with the computational complexity of this problem, we formulate the problem as a convex optimization problem that is scalable to a large geographic area. In our analysis, we further evaluate various scenarios of utility rate design (energy charges) and EV penetration rate across different geographic regions and their impact on the operating cost and emissions of the freight trucks. Our approach determines the net emissions reduction benefits of freight electrification by considering the primary energy source in different regions. Such analysis will provide insights to policy makers in designing utility rates for electric vehicle supply equipment (EVSE) operators depending upon the specific geographic region and to electric utilities in deciding infrastructure upgrades based on the spatial distribution of the added energy demand of M&HD EVs. To showcase the results, a case study for the U.S. state of Texas is conducted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption (Research Performance Final Report)

This is the research performance final report for the project entitled: Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption This project was able to achieve the DOE’s goals of developing new modeling tools to understand MDHD vehicle operation and adoption. The first modeling tool is a fleet-level techno-economic analysis model capable of estimating energy use and associated environmental and cost impacts for electrified and conventional vehicles of any MDHD vocation, using real-world cost and operations data, including approaches to optimizing schedules for charging and/or vehicle dispatch. The second modeling tool is a system-level, bottom-up, agent-based adoption model capable of generating geographically-resolved estimates of market projections for MDHD vehicles and charging infrastructure. These tools will be developed and published to serve dual purposes as analysis tools for researchers, and decision-support tools for decision makers within the MDHD system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NOx emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1957

Comparison of the Combustion Performance of Shell UMF, Grade C, MIL-F-5624C, Grade JP-5, Fuels in a Heavy-Duty XRJ47-W-9 Ram-Jet Engine

Comparable combustion performance data for Shell UMF, grade C, and MIL-F-5624C, grade JP-5, fuels were obtained using a heavy-duty version of the XRJ47-W-9 ram-jet engine operated in a 2.75 Mach number free-jet facility. Data were obtained for the two fuels over a range of fuel-air ratios, engine airflows, and engine-inlet temperatures. The test conditions were selected to provide combustor-inlet temperatures. The test conditions were selected to provide combustor-inlet conditions approximately representative of those which would be encountered over a range of altitudes and flight Mach numbers. The variation of combustion efficiency with fuel-air ratio for the two fuels is compared at the several inlet conditions. The pilot-burner ignition and operating limits with both fuels are also included. In general, the combustion efficiency with Shell UMF, grade C, fuel was 1 to 4 points lower than with MIL-F-5624C, grade JP-5, fuel.

Ranscht, W. G.↗
DOE OSTI2020

Engine-in-the-Loop Study of a Hierarchical Predictive Online Controller for Connected and Automated Heavy-Duty Vehicles

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. This work is experimentally experimentally validated via a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve the closed-loop validation of the proposed control strategies, both individually and combined. These studies show that this hierarchy of algorithms is capable of running online, with the round-trip communication delay inherent in EIL simulation being one of the key factors affecting the EIL results. Moreover, the EIL studies are encouraging, both in terms of the successful hierarchical integration of the underlying algorithms and also in the resulting fuel savings seen in the EIL tests. In particular, the EIL results suggest that an aggressive overall goal of reducing vehicle fuel consumption by 15-20% or more is potentially achievable, especially in urban/suburban scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Optimizing liquid free ionomer binders for high-temperature polymer electrolyte membrane fuel cells for heavy duty vehicles

This report documents tech transfer from Penn State to Ionomer Solutions LLC for high-temperature polymer electrolyte membrane fuel cells. High-temperature polymer electrolyte membrane (HT-PEM) fuel cells are enticing power plants for heavy-duty vehicle (HDV) transportation because their elevated temperature operation fosters greater heat rejection through larger temperature differentials. In 2021, over 6 million battery electric light duty vehicles (LDVs) were sold. Conversely, only 19,000 LDVs using fuel cell power trains were sold in 2021. Given the meteoric rise of battery-based powertrains for LDVs and its projected growth, stakeholders for fuel cell technology for transportation have shifted their focus towards HDVs rather than LDVs given fuel cells specific and volumetric energy density advantage over batteries when the vehicle is large, heavy, and/or needs to move large distances before refueling.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Development and Optimization of a Multi-Functional SCR-DPF Aftertreatment System for Heavy-Duty NOX and Soot Emission Reduction

The objective of this project is to develop a strategy for the integration of catalytic NOX emission control and particulate matter emission control into a single device for the successful application to heavy-duty on-road diesel engine exhaust aftertreatment. The critical attributes of such a device, for successful application to PACCAR fleet, are as follows: 1. Must have sufficient filtration efficiency and successfully demonstrate soot management strategies (i.e., oxidation) to be economically attractive and regulatory compliant for particulate matter abatement. 2. In particular, the integrated device must retain sufficiently high soot oxidation capacity with NO2 (i.e., passive soot oxidation) across an applicable engine test cycle to be economically attractive. 3. Must exhibit sufficient catalytic NOX reduction activity in an economically-attractive fashion that is regulatory compliant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

I.1 Heavy-Duty Diesel Combustion (Sandia National Laboratories)

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of cleaner and more fuel-efficient engine operating strategies. Most current production heavy-duty diesel engines use a combination of both in-cylinder and exhaust emissions-control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes that can be influenced by using multiple fuel injections. Past work performed under this project showed that adding a second injection can reduce soot to levels below what would have been produced by an unchanged first injection, thereby increasing load while decreasing soot and potentially reducing brake specific fuel consumption. Information characterizing the important in-cylinder processes with multiple injections has been gleaned from ensemble-averaged planar laser-induced incandescence (PLII) imaging visualizing the soot cloud and planar induced fluorescence (PLIF) of OH characterizing the soot oxidation regions. PLII showed a consistent disruption of the first injection soot cloud by the second injection. In conjunction with OH-PLIF, differences in soot oxidation patterns for multiple injections compared to single injections were observed. This understanding was further enhanced in FY20, when high-speed imaging resolving the above-mentioned effects in a single cycle were combined with direct numerical simulations investigating the multiple-injection ignition process on the microscopic level of turbulence and chemistry interaction. In FY21, these findings in conjunction with findings from other researchers published in the scientific literature were composed into a preliminary multiple-injection conceptual model of fuel-mixing, injection and ignition processes. Remaining key research questions were also highlighted. In addition, wall heat flux was investigated experimentally and with numerical simulations to understand the potential of multiple injections to reduce the engine heat losses and further enhance the efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Performance and Durability of Heavy-Duty Fuel Cell Systems with an Advanced Ordered Intermetallic ORR Alloy Catalyst and Novel Support

Ordered PtCo intermetallic (OIM) catalyst (L1 0 -PtCo/C) is a promising candidate as the oxygen reduction reaction (ORR) catalyst in hybrid fuel cell systems (FCS) for class-8 heavy duty (HD) trucks. Compared to a baseline annealed Pt on high surface area carbon (a-Pt/HSC) catalyst, its mass activity (MA) is 71% higher initially and 144% higher after 90,000 potential cycles in an accelerated stress test (AST). Analysis of the AST data indicates that the ORR kinetic constants do not change with aging and the degradation in the OIM catalyst activity is linearly proportional to the loss in the electrochemically active surface area (ECSA). Several operational strategies are investigated to mitigate catalyst degradation and achieve 25,000-h electrode lifetime and 2.5 kW g −1 Pt utilization on a HD truck duty cycle including load sharing with the hybrid battery, regulating the radiator fan power to maintain the coolant temperature close to 60 °C, clipping the maximum cell voltage below 850 mV, limiting the ECSA loss to 55%, and oversizing the active area of the membrane electrode assemblies by 20%. Drive cycle simulations indicate that the lifetime average voltage degradation rate is about 1.8 μV h −1 and the integrated stack and FCS drive cycle efficiencies decrease by 3.5 to 3.9%.

25 ENERGY STORAGE↗
DOE OSTI2020

On-Road Heavy-Duty Low-NOx Technology Cost Study

The National Renewable Energy Laboratory (NREL) conducted a cost analysis for emission control technologies under contract to the California Air Resources Board (CARB). CARB sought incremental cost analysis for emission control technologies for on-road heavy-duty (HD) engines, used in vehicle greater than 14,000 pounds (lbs) gross vehicle weight rating (GVWR) to achieve oxides of nitrogen (NOx) emissions rates significantly lower than those required by current emissions standards. Specifically, incremental costs (without any retail price mark-up) were estimated for representative diesel, natural gas, and gasoline engine and emission aftertreatment systems that were selected to represent potential technology packages that could achieve 0.02 grams per brake horsepower hour (g/bhp-hr) NOx on certification test cycles, including a proposed updated certification test cycle that includes additional low load operating conditions. NREL surveyed stakeholders including industry association groups, Tier 1 suppliers, and engine original equipment manufacturers (OEMs) to estimate incremental direct and indirect costs. Incremental costs were considered for current engine full useful life (FUL) definitions, as well as with proposed increased FUL and warranty period. The incremental costs were subsequently incorporated in life-cycle cost analyses examining the incremental engine and aftertreatment costs along with life-cycle costs over the various engine FUL scenarios. Life-cycle costs analysis included the incremental upfront cost, fuel consumption changes (changes in fuel economy), diesel exhaust fluid (DEF) consumption changes, and the maximum FUL of the aftertreatment package (major overhaul intervals).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0

In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.

Wang, Bin↗
NASA NTRS1984

Computer simulation of the heavy-duty turbo-compounded diesel cycle for studies of engine efficiency and performance

Reductions in heat loss at appropriate points in the diesel engine which result in substantially increased exhaust enthalpy were shown. The concepts for this increased enthalpy are the turbocharged, turbocompounded diesel engine cycle. A computer simulation of the heavy duty turbocharged turbo-compounded diesel engine system was undertaken. This allows the definition of the tradeoffs which are associated with the introduction of ceramic materials in various parts of the total engine system, and the study of system optimization. The basic assumptions and the mathematical relationships used in the simulation of the model engine are described.

Assanis, D. N.↗
DOE OSTI2022

Protonated phosphonic acid electrodes for high power heavy-duty vehicle fuel cells

We report that state-of-the-art automotive fuel cells that operate at about 80 °C require large radiators and air intakes to avoid overheating. High-temperature fuel cells that operate above 100 °C under anhydrous conditions provide an ideal solution for heat rejection in heavy-duty vehicle applications. Here we report protonated phosphonic acid electrodes that remarkably improve the performance of high-temperature polymer electrolyte membrane fuel cells. The protonated phosphonic acids comprise tetrafluorostyrene-phosphonic acid and perfluorosulfonic acid polymers, where a perfluorosulfonic acid proton is transferred to the phosphonic acid to enhance the anhydrous proton conduction of fuel cell electrodes. By using this material in fuel cell electrodes, we obtained a fuel cell exhibiting a rated power density of 780 mW cm -2 at 160 °C, with minimal degradation during 2,500 h of operation and 700 thermal cycles from 40 to 160 °C under load.

25 ENERGY STORAGE↗
DOE OSTI2022

Mass Detection for Heavy-Duty Vehicles using Gaussian Belief Propagation

Predicting vehicle mass is critical to accurately estimate energy use and emissions of commercial trucks. However, data from vehicle telematics is often not at sufficient temporal resolution or accuracy for use in model-based detection methods. In this work, a new statistical mass prediction technique is described for heavy-duty vehicles that incorporates the use Gaussian Belief Propagation (GBP) for probabilistic inference. Similar to Bayesian inference models, the GBP model typically requires less labeled training data than other contemporary machine learning techniques. First, a factor graph is constructed, and a set of Gaussian belief nodes with associated means and variances are fitted to the training data. To better handle noisy input data, the GBP mass prediction model utilizes a k-nearest factors (kNF) algorithm for probabilistic inference on unseen testing data. The proposed method is compared with a classical weighted k-nearest neighbors (kNN) regressor. This statistical kNF-GBP model works even with low-quantity, low-quality initial training data, while being capable of realtime mass estimation. Unlike the kNN regressor, the GBP model produces a measure of uncertainty with its predictions. The proposed method is validated using curve-sampled driving data collected from multiple cloud-connected Class 8 regional haul diesel trucks. Both the kNN regressor and the kNF-GBP mass prediction model were able to predict payload mass with coefficients of determination above 0.97 with minimal data preprocessing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

R&D Insights for Extreme Fast Charging of Medium- and Heavy-Duty Vehicles: Insights from the NREL Commercial Vehicles and Extreme Fast Charging Research Needs Workshop, August 27-28, 2019

As battery costs have declined and battery performance has improved, the applicability of vehicle electrification has expanded beyond passenger cars to the commercial vehicle sector. However, due to the larger batteries that would be needed for the medium- and heavy-duty (MDHD) sector, the electric charging capabilities to serve these larger commercial vehicles will need to be substantially more powerful than light-duty chargers. More specifically, such 'extreme fast charging' (XFC) will likely need to reach the megawatt scale to provide a full charge in less than 30 minutes in some applications. In addition, the combined cost of electrified vehicles and charging must be competitive with the costs of petroleum-based technologies and other alternatives to encourage widespread adoption of battery electric vehicles (BEVs) among MDHD fleets. Most of these fleets have a commercial mission and demand low total cost of ownership (TCO) (which motivates minimal refueling times) and high performance from their vehicles.

25 ENERGY STORAGE↗
DOE OSTI2023

PR100: Estimated Medium- and Heavy-Duty Electric Vehicle Adoption and Load Estimation in Puerto Rico through 2050

The 2-year Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study analyzed stakeholder-driven pathways to Puerto Rico’s clean energy future. Outputs relating to electricity demand modeling were partially informed by estimates of electric vehicle adoption across all classes of medium- and heavy-duty vehicles (MHDVs), and the ensuing charging loads. To create these estimates, the team developed a transportation model for MHDVs in Puerto Rico to estimate the amount and geospatial distribution of energy used. Charging schedules for the different end uses of MHDVs were then used to construct electric load shapes assuming a portion of those vehicles would be replaced by battery electric counterparts. Study results showed that, by 2050, electric vehicles may constitute roughly 50% of the MHDV population in Puerto Rico. The resulting electrical demand curve attributable to MHDV charging showed that, for solar energy-based electrical systems with limited energy storage, this demand may create challenges unless appropriately managed either on the demand or supply side.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

High Efficiency Powertrain for Heavy Duty Trucks Using Silicon Carbide (SiC) Inverter

The objective of the High Efficiency Propulsion (HEP) project is to research, develop, and demonstrate life cycle cost-effective Class 8 battery electric vehicles utilizing an 800 V high efficiency and compact 250 kW continuous power SiC inverter designed to support the commercial operations of the high continuous loads and challenging shock/vibration environment of heavy-duty trucks with an electrified axle specifically designed for high performance and efficiency in battery-electric Class 8 trucks used in medium range (~250 miles) distribution, and compared to the baseline Peterbilt 579 electric truck fleet performance using an IGBT inverter. The project was split into 3 budget periods, with the first two being design and development focused, and the final one is an on-vehicle demonstration phase of the high efficiency SiC traction drive inverter with daily mileage accumulation.

33 ADVANCED PROPULSION SYSTEMS↗