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At least 55 records · Page 3

Medium and Heavy Duty Vehicle Powertrain Electrification and Fleet Demonstration

The Contract Award Grant # EE0007513 dated 2 June, 2016 is for the design, development and demonstration of medium duty package delivery vehicles that will result in a 100% increase in fuel economy as measured in miles per gallon. The project was proposed in 3 phases over two budget periods. The Phases were: 1. Modeling and Simulation – This phase was completed and formed the basis of the specifications for the design and build of the physical systems. The modeling and simulation was conducted by AVL and used real world package delivery routes that AVL mapped. The motors, battery pack, range extender and balance of plant support systems were modeled and iterated until a system with the desired fuel economy improvement was realized. Early design of the major subsystems using the actual vehicle space constraints was also completed. This phase was successfully completed in May of 2017. 2. 1st Build and FE Confirmation - This phase was completed and resulted in the final design, release, procurement and build of all major vehicle systems for commissioning into the first vehicle. The work was a partnered effort between McLaren and AVL. McLaren built the eAxle system while AVL built the range extender and integrated the range extender, battery and balance of plant sub-systems into the first vehicle with a control system to make it operate. Prior to the end of this phase a real world HIL system test gave evidence that the fuel economy improvement would be achieved in the real world. This phase was exited with a 7 month delay due mostly to procurement and supply base issues and ended in May, 2018. 3. Final Build and Demonstration - This phase included the final build and commissioning of the four program vehicles and the operation of a demonstration on a set of routes near San Diego California. During this phase, a multitude of issues arose in different systems in the vehicle. These issue resolution exercises were quite complex and caused repeated delays but were all successfully completed. It should also be noted that an early commercialization analysis resulted in the conclusion that the complexity of the system would not make it cost effective, leading to the start of a follow-on design that used newly available component technologies to specify a more cost effective system. This design will be repurposed and put into demonstration on a separately (non-DOE) funded program. It was decided and agreed with DOE that this phase should be considered completed. The knowledge and know-how gained on this program has been incorporated into and transferred to the new program. This phase and the entire program was considered closed on June 1, 2021.

33 ADVANCED PROPULSION SYSTEMS↗

Delivering Clean Air in Denver: Propane Trucks and Infrastructure in Mail Delivery Application

In 2021, Drive Clean Colorado, a Denver-based Clean Cities coalition, initiated the deployment of five Class 6 medium-duty propane autogas delivery trucks into a United States Postal Service (USPS) mail delivery contractor fleet with the goal of providing a proof-of-concept demonstration for mail delivery fleets nationwide. Funded by the U.S. Department of Energy's Office of Energy Efficiency & Renewable Energy, the project, titled "Delivering Clean Air in Denver: Propane Trucks and Infrastructure in Mail Delivery Application," enabled the purchase and deployment of the propane-powered trucks, refueling infrastructure, and supporting analysis by the National Renewable Energy Laboratory (NREL). Key objectives of the analysis included calculating the propane vehicles' emissions reductions, analyzing the costs and operational performance of the propane fleet compared to conventional diesel-powered vehicles, and evaluating the viability of propane as a clean and cost-effective alternative to conventional diesel trucks (AFDC 2023b, 2023c). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a clean and cost-effective alternative to conventional diesel trucks. This proof-of-concept demonstration is expected to lead to improved understanding of the performance attributes, costs, and operational issues to inform technology adoption decisions, helping to spur market transformation toward lower-emission truck fleets. By reducing the risk of first adoption, potential exists to transform the U.S. Postal Service (USPS) mail delivery system into a lower-carbon national fleet. This technical report details the vehicle duty cycle characterization and fleet cost and performance comparison performed by the National Renewable Energy Laboratory, in addition to estimated emissions reductions for delivery operations.

33 ADVANCED PROPULSION SYSTEMS↗

Depot-Based Vehicle Data for National Analysis of Medium- and Heavy-Duty Electric Vehicle Charging

Medium- and heavy-duty vehicles (MHDVs) are a major source of greenhouse gases and local criteria air pollutants. Electrifying MHDVs may reduce these harmful emissions, which disproportionately impact disadvantaged communities. Due to their relatively high per-vehicle energy needs, consistent fleet operations, and frequent colocation of multiple vehicles at depots, MHDVs may have more spatially and temporally concentrated charging demands than light-duty passenger electric vehicles. That charging concentration means their electrification may require careful advance planning and coordination to manage potential impacts to the electrical grid via charge management or infrastructure upgrades. However, MHDV duty cycles and parking schedules are highly variable across vocations of operation, and there is a shortage of nationally representative, vocationally diverse public data describing typical MHDV operations. This report summarizes the methodology - designed with national representativeness in mind - used to create a new set of data describing typical daily driving distances, dwell durations, and normalized electric vehicle depot charging load curves for MHDVs. The dataset reflects the subset of MHDV operating patterns that may originate from a consistent depot each day and rely on the same depot for charging. In addition to trucks with depot-centric vocational patterns, the data describes operations of transit buses and school buses, each with a depot-centric focus. The dataset is available to the public and suitable for national analysis. It can inform research, infrastructure planning, and policymaking regarding the electrification of MHDVs.

33 ADVANCED PROPULSION SYSTEMS↗

Identifying Electric Vehicles to Best Serve University Fleet Needs and Support Sustainability Goals

University fleets represent an enticing opportunity to explore the near-term feasibility of achieving net-zero-carbon emissions in transportation. In many instances, universities operate much like a small, self-contained ecosystem with all the same transportation needs as a larger municipality, but with a smaller geographic footprint. Their fleets often include a wide variety of vehicle types serving the campus, including low-speed vehicles (e.g., golf carts), light-duty sedans, SUVs, and pickups, as well as medium-duty trucks and delivery vehicles. The mix of vehicle and operational needs combined with broader activities related to net-zero campuses makes universities and colleges unique microcosms to determine the feasibility of and path to achieving net-zero fleets. As the availability of electric drivetrains expands beyond light-duty sedans, fleets need to understand when it will be operationally and financially appropriate to start adding electric drivetrains to their fleets. To better understand these opportunities, NREL contracted Sawatch Labs to analyze the role electric vehicles (EVs) can have in helping universities meet net-zero emissions and fleet sustainability goals they have instituted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Los Angeles Air Force Base Vehicle-to-Grid Demonstration (Final Project Report)

Electrification of non-tactical vehicle fleets represents a key efficiency and energy security objective for the United States Department of Defense. To achieve electrification, the department targeted vehicle-to-grid services as a way to decrease the overall cost of operating the vehicle fleet and achieve rough parity with traditional internal combustion engine vehicle fleets. This report describes efforts to aggregate a fleet of bi-directional electric vehicles and charging stations to provide regulation up and regulation down in the California Independent System Operator ancillary services market. A 29-vehicle electric vehicle demonstration fleet, consisting of mixed purpose and duty vehicles such as sedans, pickups, vans, and medium-duty trucks, was deployed at the Los Angeles Air Force base. The fleet provided frequency regulation to the California Independent System Operator’s wholesale electricity market to determine the capability of recouping some of the additional costs of procuring electric vehicles and their supporting infrastructure. Lawrence Berkeley National Laboratory, with its partner Kisensum, LLC, developed the fleet scheduling, optimization, and control software to allow the vehicle fleet at the air force base to participate in the ancillary services markets. This report focuses on the control software and market interactions, the significant challenges faced and solutions devised to address them, and examines the potential of using the electric vehicle fleet as an energy storage resource for the base buildings, an application known as vehicle-tobuilding, in providing demand response and emergency backup power. The report discusses key findings related to providing frequency regulation to the California Independent System Operator market, electric vehicle fleet performance, compatibility of varying resource parameters of vehicle fleet aggregation, the need for automated methods for communicating hour-ahead energy bidding, challenges related to battery capacity and charge/discharge rates, and monthly settlement revenue.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Innovating High Throughput Hydrogen Stations: Cooperative Research and Development Final Report, CRADA Number CRD-18-00773

Hydrogen stations today serve the emerging market of light duty fuel cell vehicles, primarily in California with over 30 public retail locations. There has been a steady increase in the number of stations open and hydrogen dispensed, especially in the last two years. From 2015 to 2016, the annual amount of hydrogen dispensed increased from 27,400 kg to 109,200 kg, a nearly fourfold increase in just one year. One station dispensed nearly 12,000 kg in the second quarter of 2017. Despite the significant progress, gaps exist between current infrastructure capabilities and future requirements. For example, fuel cell vehicle applications such as buses, medium-duty, and heavy-duty trucks will gain market share and this must be considered as future customers at hydrogen stations. The expected number of light duty fuel cell vehicles in California alone are expected to grow from approximately 4,000 to over 13,000 by 2020, and 37,000 by 2023. To serve the multiple mobile fuel cell technologies and increased demand, hydrogen stations will have to increase output, decrease cost, and improve reliability. To address these challenges, the project team will demonstrate a hydrogen-focused integrated renewable energy production, storage, and transportation fuel distribution/retailing system. The proposed R&D tasks address key challenges related to light duty station/component reliability and development and validation of high flow rate system models for new applications like medium and heavy-duty truck fueling.

08 HYDROGEN↗

Decarbonizing Medium & Heavy-Duty On-Road Vehicles

We analyze the decarbonization potential of medium and heavy-duty vehicles (MHDVs) across multiple vehicle classes and market segments. We evaluate the timeframe in which zero-emission vehicles (ZEVs) could achieve cost parity with conventional diesel vehicles and the implications for energy and emissions. Our results show that ZEVs can achieve cost parity with conventional vehicles by 2035 across the majority of vehicle classes and market segments. Emissions reductions range from 27% to 77% by 2050 relative to 2019 across multiple fuel cost and technology progress sensitivities. Multiple technology pathways are viable for decarbonization, including battery-electric vehicles and hydrogen fuel cell electric vehicles. This presentation is based on previous work published by NREL: Ledna, C., Muratori, M., Yip, A., Jadun, P., and Hoehne, C. 2022. Decarbonizing Medium & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost Analysis. National Renewable Energy Laboratory, https://www.nrel.gov/docs/fy22osti/82081.pdf.

ADVANCED PROPULSION SYSTEMS↗

Well-to-Wheels Analysis of Zero-Emission Plug-In Battery Electric Vehicle Technology for Medium- and Heavy-Duty Trucks

Conventional diesel medium- and heavy-duty vehicles (MHDVs) create large amount of air emissions. With the advancement in technology and reduction in the cost of batteries, plug-in battery electric vehicles (BEVs) are increasingly attractive options for improving energy efficiency and reducing air emissions of MHDVs. In this paper, we compared the well-to-wheels (WTW) greenhouse gases (GHGs) and criteria air pollutant emissions of MHD BEVs with their conventional diesel counterparts across weight classes and vocations. We expanded the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model to conduct the WTW analysis of MHDVs. The fuel economy for a wide range of MHDV weight classes and vocations, over various driving cycles, was evaluated using a high-fidelity vehicle dynamic simulation software (Autonomie). The environmental impacts of MHD BEVs are sensitive to the source of electricity used to recharge their batteries. The WTW results show that MHD BEVs significantly improve environmental sustainability of MHDVs by providing deep reductions in WTW GHGs, nitrogen oxides, volatile organic compounds, and carbon monoxide emissions, compared to conventional diesel counterparts. Increasing shares of renewable and natural gas technologies in future national and regional electricity generation are expected to reduce WTW particulate matters and sulfur oxide emissions for further improvement of the environmental performance of MHD BEVs.

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Effects of Hybridization on Selective Catalytic Reduction (SCR) Thermal Management of a Medium Heavy-Duty Hybrid Work Truck

The increased market penetration of hybrid electric powertrains in medium heavy-duty (MHD) applications has provided a novel platform for vehicle research. One example of such a platform is the MHD parallel hybrid truck developed by Odyne Systems, LLC. In collaboration with Odyne Systems, LLC and the Department of Energy (DOE), Oak Ridge National Laboratory (ORNL) developed a validated vehicle plant model for this truck and tested the Odyne powertrain in a hardware-in-the-loop (HIL) environment. While testing in the HIL environment, the effects of reduced engine load, and thus catalyst heating, on the selective catalytic reduction (SCR) catalyst produced diminished hybrid improvement as the level of energy storage usage increased. This article will discuss these results and the potentially unforeseen interactions with modern aftertreatment systems when hybridizing conventional powertrains.

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Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗

Total Cost of Ownership Reduction Using Passive Pre-Chamber Ignition in Natural Gas Engines

Spark plug durability is a factor affecting the total cost of ownership (TCO) of spark-ignited natural gas engines, with some heavy-duty platforms requiring plug replacement after only 750 hours of operation. The high ignition energy demand under lean or diluted conditions accelerates electrode wear, shortening plug life and increasing maintenance frequency. This work evaluates passive pre-chamber (PC) ignition operating at lowered spark energies as a strategy to reduce spark energy requirements and extend plug durability, thereby lowering TCO. Experiments were conducted on a medium-duty Cummins 6.7L ISB engine at 1600 RPM and 50% load under varying exhaust gas recirculation (EGR) dilution levels (0–40%). Two passive pre-chambers with 1.1 mm and 1.6 mm nozzle diameters were compared with conventional spark ignition (SI). SI was operated with a fixed coil dwell of 4 ms (~90 mJ), while the PC configuration was tested across 2–4 ms dwell times (~30–90 mJ). Cylinder pressure analysis revealed that PC ignition sustained stable combustion at significantly lower spark energies than SI, with improved combustion stability at ~30 mJ compared with SI at ~90 mJ. The PC system also extended the dilution tolerance beyond that achievable with SI, while delivering up to ~2% higher indicated thermal efficiency and reducing the COV by nearly 90% at 30% EGR. A TCO analysis was conducted to assess the economic benefit of adopting a passive PC system operating at reduced spark energies compared to SI. It was found that adopting a passive PC system could reduce TCO by approximately $11,000 per engine over a five-year operational period, primarily due to fuel savings, extended spark plug life, and reduced maintenance frequency. These projections were weighed against the additional hardware cost of the pre-chamber, yielding a rapid estimated return on investment of ~300 operating hours. Therefore, this work motivates continued research and development of passive PC technology and its commercial adoption in natural gas engines used in transportation applications.

Dhotre, Akash [University of Minnesota]↗

Analytic Framework for Optimal Sizing of Hydrogen Fueling Stations for Heavy Duty Vehicles at Ports (CRADA 512)

This CRADA presents the strategy that PNNL and Sandia National Laboratories (SNL) will take to support Seattle City Light (SCL) in properly sizing a hydrogen station for class 8 drayage trucks at the Port of Seattle (Port), as part of a coordinated plan of mixed uses for hydrogen. The proper sizing for the fueling station is unique from past experiences because it will be part of a coordinated plan for a multi-use scheme for the hydrogen, and not a stand-alone fueling station. The multiple use-streams, and their relative values, will impact all facets of station sizing and design, including fueling rates, storage technology and size, equipment selection, and safety considerations. The future deployment of this fueling station, and its proper sizing, is seen as a critical first step in the larger vision of utilizing hydrogen to address a range of issues for SCL and the Port. These include, but are not limited to, large scale fueling of medium duty (MD) and heavy duty (HD) vehicles to reduce emissions, support of adjacent light duty (LD) vehicles, support of critical port operation during extreme events (e.g. resiliency), mitigation of capital intensive electrical distribution system upgrades to support evolving port operations, a market resource that can be used by SCL to generate revenue, and support of planned future maritime operations that currently require heavy use of shipboard hydrogen. While the broader use of hydrogen by SCL and the Port is not the focus of this CRADA, how its use impacts the design of the initial vehicle fueling station, and the modular approach, are the central work. As such, this project will develop the framework and process for developing a modular station design that considers the broader range of coordinate uses of hydrogen as an energy resource.

08 HYDROGEN↗

Fundamental insights on ignition and combustion of natural gas in an active fueled pre-chamber spark-ignition system

Pre-chamber spark-ignition (PCSI), either fueled or non-fueled, is a leading concept with the potential to enable diesel-like efficiency in medium-duty (MD) and heavy-duty (HD) natural gas (NG) engines. However, the inadequate scientific base and simulation tools to describe/predict the underlying processes governing PCSI systems is one of the key barriers to market penetration of PCSI for MD/HD NG engines. To this end, experiments were performed in a heavy-duty, optical, single-cylinder engine fitted with an active fueled PCSI module. Furthermore, the spatial and temporal progress of ignition and subsequent combustion of lean-burn natural gas using PCSI system were studied using optical diagnostic imaging and heat release analysis based on main-chamber and pre-chamber pressure measurements.

42 ENGINEERING↗

Assessment of Turbulent Combustion Models for Simulating Prechamber Ignition in a Natural Gas Engine

Lean combustion is a promising strategy to increase thermal efficiency in an internal combustion engine, by exploiting a favorable specific heat ratio of the fresh mixture while simultaneously suppressing the heat losses to the cylinder wall. However, unstable ignition and slow flame propagation at fuel-lean conditions lead to large cycle-to-cycle variability and limit the high-efficiency engine operating range. Prechamber ignition is considered an effective concept to extend the lean operating limit, by providing spatially distributed ignition with multiple turbulent flame-jets and enabling a faster combustion rate compared to the conventional spark ignition approach. From a numerical modeling standpoint to date science base and available simulation tools are inadequate to properly understand and predict the combustion processes in prechamber ignited engines. In this paper, conceptually different Reynolds-averaged Navier–Stokes (RANS) combustion models widely adopted in the engine modeling community are used to simulate the ignition and combustion processes in a medium-duty natural gas engine with a prechamber spark-ignition system. Here, a flamelet-based turbulent combustion model, i.e., G-equation, and a multizone well-stirred reactor model are employed for this modeling study. Simulation results are compared with experimental data in terms of in-cylinder pressure and heat release rate. Finally, the analysis of the performance of the two models is carried out to highlight the strengths and limitations of the two evaluated approaches.

42 ENGINEERING↗

Neural Network-Based Electric Vehicle Range Prediction for Smart Charging Optimization

Range prediction is a standard feature in most modern road vehicles, allowing drivers to make informed decisions about when to refuel. Most vehicles make range predictions through data- or model-driven means, monitoring the average fuel consumption rate or using a tuned vehicle model to predict fuel consumption. The uncertainty of future driving conditions makes the range prediction problem challenging, particularly for less pervasive battery electric vehicles (BEV). Most contemporary machine learning-based methods attempt to forecast the battery SOC discharge profile to predict vehicle range. In this work, we propose a novel approach using two recurrent neural networks (RNNs) to predict the remaining range of BEVs and the minimum charge required to safely complete a trip. Each RNN has two outputs that can be used for statistical analysis to account for uncertainties; the first loss function leads to mean and variance estimation (MVE), while the second results in bounded interval estimation (BIE). These outputs of the proposed RNNs are then used to predict the probability of a vehicle completing a given trip without charging, or if charging is needed, the remaining range and minimum charging required to finish the trip with high probability. Training data was generated using a low-order physics model to estimate vehicle energy consumption from historical drive cycle data collected from medium-duty last-mile delivery vehicles. Here, the proposed method demonstrated high accuracy in the presence of day-to-day route variability, with the root-mean-square error (RMSE) below 6% for both RNN models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of turbulent combustion models for simulating pre-chamber ignition in a natural gas engine

Lean combustion in an internal combustion engine is a promising strategy to increase thermal efficiency by leveraging a more favorable specific heat ratio of the fresh mixture and simultaneously suppressing the heat losses to the cylinder wall. However, unstable ignition events and slow flame propagation at fuel-lean condition lead to high cycle-to-cycle variability and hence limit the high-efficiency engine operating range. Pre-chamber ignition is considered an effective concept to extend the lean operating limit, by providing spatially distributed ignition with multiple turbulent flame-jets and enabling faster combustion rate compared to the conventional spark ignition approach. From a numerical modeling perspective, to date, still the science base and available simulation tools are inadequate for understanding and predicting the combustion processes in pre-chamber ignited engines. In this paper, conceptually different RANS combustion models widely adopted in the engine modeling community were used to simulate the ignition and combustion processes in a medium-duty natural gas engine with a pre-chamber spark-ignition system. A flamelet-based turbulent combustion model, i.e., G-equation, and a multi-zone well-stirred reactor model were employed for the multi-dimensional study. Simulation results were compared with experimental data in terms of in-cylinder pressure and heat release rate. Finally, the analysis of the performance of the two models is carried out to highlight the strengths and limitations of the two formulations respectively.

combustion model evaluation↗

Numerical investigation of a fueled pre-chamber spark-ignition natural gas engine

Pre-chamber spark-ignition (PCSI) is a leading advanced ignition concept for internal combustion engines with the potential to enable diesel-like efficiency in medium-duty/heavy-duty (MD/HD) natural gas (NG) engines. By leveraging distributed ignition sources from multiple turbulent jets, the PCSI technology can deliver extremely short combustion duration in ultra-lean mixtures and significantly improve the engine thermal efficiency. However, in the automotive industry there is a lack of adequate science base and predictive simulation tools required for commercial development of PCSI engines. Here, in this study, Reynolds-Average Navier-Stokes simulations are carried out to describe the combustion process in lean-burn NG engines, focusing on the combustion modeling approach. Two combustion models, multi-zone well-stirred reactor (MZ-WSR) and G-equation, are used to simulate the combustion process in an MD NG engine equipped with a fueled-PCSI system for four operating conditions close to the lean operating limit. A skeletal chemical mechanism and a laminar flame speed tabulation are used to compute the combustion accurately. Simulation results are compared with experimental data regarding measured cylinder pressure, heat release rate, and combustion duration. By dividing the PCSI combustion process into four distinct phases, the difference between the two models’ results for each phase is analyzed in detail. The MZ-WSR model overestimates the combustion duration for early flame kernel growth in the pre-chamber due to the lack of a specific formulation to take turbulence-chemistry interaction into account. Despite the prolonged combustion duration and low pressure built-up inside the pre-chamber, the model matches the combustion rate in the main-chamber. In contrast, the G-equation model delivers good agreements for the pre-chamber combustion and turbulent jet-driven combustion processes. However, the model starts to underestimate the combustion rate in the main-chamber, especially under ultra-lean mixture conditions. Finally, improvements are needed for both models to simulate the later combustion stage that occurred in the near-wall regions.

33 ADVANCED PROPULSION SYSTEMS↗