SEARCH · Engineering Papers

Results for “Energy Management Information Systems”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Corral Summit Pumped Storage Hydropower Hybrid: Site Suitability Assessment

In 2024, Idaho National Laboratory (INL) and Pacific Northwest National Laboratory (PNNL) initiated a technical-assistance project to support Cat Creek Energy, LLC, (CCE) in evaluating site suitability for the proposed Corral Summit Pumped Storage Hydropower (PSH) project in south-central Idaho near Mackay Reservoir. The Corral Summit facility incorporates battery storage and photovoltaic (PV) solar arrays in a Trybrid configuration to deliver large-volume long-duration (LVLD) storage solutions for rural electric cooperatives in eastern Idaho. The evaluation process focused on determining the most-suitable location for the upper reservoir of the PSH system, guided by a comprehensive assessment framework spanning multiple categories, including physical characteristics, environmental constraints, building infrastructure, regulatory constraints, cultural resources and sensitivity, social factors, and power market and grid integration. Each site was analyzed based on a ranking scale (0–1), which scores ranging from “severely disfavored” to “highly favored,” allowing detailed comparisons of site-specific conditions. Categories such as hydraulic head, utilities corridor, land ownership, and transmission-grid limitations emerged as key contributors to the overall assessment. Site 2 (Idaho Trust) demonstrated a slight advantage over Site 1 (Bureau of Land Management) primarily due to favorable outcomes in regulatory constraints, building infrastructure, and power-market integration. However, Site 1 outperformed Site 2 in factors related to physical characteristics and social factors. The report emphasizes the need for further evaluation of both sites before clear determination of which site is preferred, due to the limited information available on either site at the time of this report. Key areas of evaluation to clearly define the preferred site are ecological impacts, cultural-resource surveys, and economic-feasibility assessments. For successful project execution, recommended follow-up actions include seismic and geotechnical surveys, groundwater and habitat monitoring, regulatory reviews of water rights and right-of-way agreements, cultural engagement with local tribal governments, and enhanced stakeholder strategies. These efforts will ensure the Corral Summit Trybrid facility meets local energy needs while balancing environmental, social, and regulatory responsibilities.

13 - HYDRO ENERGY↗

DOE OSTI2025

MiniMOD

SAND2025-03854O MiniMod is a user-friendly software tool designed to assess the performance of high-performance computing (HPC) systems. Researchers can use the program to test communication methods and computational tasks to understand how different setups can affect application efficiency. This software is particularly useful for optimizing network performance in scientific research, simulations, and data analysis. MiniMod‘s flexible design allows users to make informed decisions about their computing environments, which can enhance productivity and results in real-world applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dosanjh, Matthew [Sandia National Lab. (SNL-CA), L↗

DOE OSTI2023

Physics-informed Data-driven Degradation and Prognostic For Hydropower System

The hydropower system is a cyber-physical system, and the industry is experiencing high operation and maintenance (O&M) costs along with increasing unplanned outages, primarily due to aging equipment and new asset loading patterns. Current (O&M) practices in asset management are predominantly reactive rather than predictive and systematic. To address these challenges, a proposed physics-informed data-driven degradation model aims to simulate the health of components in various environments. Its purpose is to accurately characterize wear and fatigue in the pilot components of hydropower systems. Additionally, the model provides informed confidence in prognostic predictions concerning asset degradation and remaining life.

13 HYDRO ENERGY↗

DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗

DOE OSTI2026

Fast, Controllable, and Modular Solid-State Circuit Breaker Design for Battery Management Systems

Electric power grid is experiencing a growing number of distributed and inertia-free generation resources. To facilitate the growing generation and load demands, and ensure stable operation, energy storage systems, especially behind-themeter-storage (BTMS), have emerged as a potential candidate. BTMS plays a vital role in the grid storage sector and supports high power charging for EVs. However, the potential of thermal runaway and associated safety concerns in the batteries can hamper their widespread adoption. In this work, we provide a solution for a fast and controllable discharge of a cell that was identified as a stressful/faulty, in the battery pack, and fast circuit breaking leveraging the Solid-State Circuit Breaker (SSCB) technology which provides active control over the cell connection as opposed to conventional passive solutions. Testing on the simulation platform successfully validated the concept, demonstrating its efficacy. Controlled discharge testing with 20Ah LiFePO4 Lithium Iron Phosphate (LFP) cells from 1C-10C current rate on the hardware prototype corroborated simulation results, demonstrating design feasibility and providing essential data for its performance and thermal characteristics, while also revealing limitations that inform areas for further optimization.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO 2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and emissions reductions of 3–100 %, with strategic energy management achieving 3–5 % and renewable electricity paired with electrified heating achieving up to 100 %. Text mining revealed that energy, hardware, and process technologies account for 91 % of literature coverage. Water, building envelope, and CO 2 utilization remain underexplored, indicating priorities for future research. This integrative approach to technology assessment supports growers, developers, and policymakers in aligning CEA system design with local conditions, improving resource efficiency and addressing gaps in cross-domain technology coverage.

Controlled environment agriculture↗

DOE OSTI2021

OWL Change Control Process

The Online Waste Library (OWL) provides a consolidated source of information on Department of Energy-managed radioactive waste likely to require deep geologic disposal. With the release of OWL Version 1.0 in fiscal year 2019 (FY2019), much of the FY2020 work involved developing the OWL change control process and the OWL release process. These two processes (in draft form) were put into use for OWL Version 2.0, which was released in early FY2021. With the knowledge gained, the OWL team refined and documented the two processes in two separate reports. This report focuses on the change control process and discusses the following: (1) definitions and system components; (2) roles and responsibilities; (3) origin of changes; (4) the change control process including the Change List, Task List, activity categories, implementation examples, and checking and review; and (5) the role of the re lease process in ensuring changes in the Change List are incorporated into a public release.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Unleashing the Frequency: Multi-Megawatt Demonstration of 100% Renewable Power Systems with Decentralized Communication-Less Control Scheme

Power systems, which range in size from small microgrids to island systems to large regional grids, are typically managed by a central controller that requires complex communication methods and can be unreliable and pose cyber security risks in certain applications, especially when controlling a larger number of nodes. We propose an inherently robust, scalable method of integration using multiple energy storage systems and distributed energy resources, which does not require any means of dedicated communication. This method moves beyond the paradigm of controlling grid frequency at a fixed value (e.g., 60 Hz), instead allowing the frequency to fluctuate within certain limits (e.g., 59.6-60.4 Hz). With a greater operating range, the frequency can carry necessary information from energy storage systems to highly variable distributed energy resources like photovoltaics, wind, hydro, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Corral Summit Pumped Storage Hydropower Hybrid Site Suitability Assessment (Rev.1)

13 - HYDRO ENERGY↗

DOE OSTI2020

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Resilience Metrics and Framework for Distributed Wind Presentation

This presentation communicates information about the MIRACL project Resilience Metrics report and Resilience Framework report. It was created for the 2021 MIRACL advisory board meeting. We propose a three-tiered approach for the resilience framework. At the top level, we consider the time horizons on which resilience will be evaluated and executed. At the middle level, we consider the core functions of resilience, which span across the time horizons. At the lower level, we consider the process steps that correspond to implementing practices for resilience in each of the core functions. The framework considers three time horizons in order to enable organizations to assess and improve their system’s resilience throughout its lifecycle. We call these time horizons the planning, operational, and future stages. The planning stage uses organizational needs and current system evaluation to prepare for potential hazards. The operational stage seeks to execute responses to hazards as prudently and efficiently as possible to maintain system resilience. The future stage seeks to improve on current system resilience and feeds back into the planning stage to promote continuous improvement. While all three time horizons are important when considering a specific topic, the planning and evaluation phase (i.e., what is done in advance of the event) is critical in defining a system’s resilience characteristics and in outlining how a system responds to an event. This framework intentionally emphasizes the planning stage to highlight the overarching emphasis of this effort, not to imply that the other two time-related horizons (i.e., operational and change the future) are less important. The core functions in the framework are identify, prepare, detect, adapt, and recover. These five functions stem from a rigorous analysis of definitions used across the industry, and they represent the core capabilities that an organization must have to enable lifecycle resilience. Within each core function, process steps are described that help walk an organization through the information gathering, evaluation, decision-making, and implementation processes they will need to ensure their resilience goals are maintained throughout the system and the system lifecycle. Also highlighted in the figure is the concept that a resilience framework should be cyclical in nature. Because a system’s resilience is based on finite resources and time, it must continually evolve through this framework’s risk management and capital investment steps at an appropriate level of scope and pace.

17 WIND ENERGY↗

DOE OSTI2024

Community Microgrid Assistance Partnership (C-MAP) [Slides]

This informational webinar, held on Nov. 11, 2024, covered the structure, technical focus, and eligibility criteria for the first Request for Proposals (RFP) released by the Community Microgrid Assistance Partnership (C-MAP). Eligible communities are invited to propose a community-based microgrid development or improvement project for funding and/or technical assistance. C-MAP is a program led by the U.S. Department of Energy Office of Electricity with management and coordination by the National Renewable Energy Laboratory. C-MAP will bring together many of the organizations that are working to understand, improve, and implement advanced microgrid energy systems in underserved and Indigenous communities in remote areas, facilitating a new forum for engagement and collaboration. Wraparound services from regional organizations will support the participating communities in microgrid operations as it relates to advancing their energy goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Dynamic Decarbonization through Autonomous Physics-Centric Deep Learning and Optimization of Building Operations (Abstract only)

This project directly addresses the primary goal of Area of Interest 2 in the CRADA call: to advance optimization-based integrated energy management systems in commercial and residential buildings. Pacific Northwest National Laboratory (PNNL) and its industry partner PassiveLogic aim to accomplish this by reaching three key objectives. First, to ensure a broad impact in the building controls industry, PNNL will extend its open-source library for predictive control synthesis by augmenting its capabilities with data-driven self-learning of building models and auto-calibration of predictive controllers. The effort will focus on building use cases selected in collaboration with PassiveLogic. The team will specifically address the development of methods for data-driven adaptation of building models, investigation of model architectures that best address specific building types, and automated synthesis of differentiable predictive controllers that optimize diverse objectives. Second, PNNL will collaborate with PassiveLogic to integrate the aforementioned methods with PasiveLogic’s advanced controls platform. The collaborative integration effort will inform the developments under the first objective by providing specific data on the attainable performance of model learning on resource-constrained edge computing platforms. This software integration effort will increase the technical maturity of the developed libraries by exploring the use of software integration tools and methods. Third, PNNL and PassiveLogic will work to improve the technology readiness of the developed predictive controllers by testing their performance in relevant test environments, such as high-fidelity simulation, hardware in the loop, and actual test buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Towards a circular economy for PET bottle resin using a system dynamics inspired material flow model

Not Available

Ghosh, Tapajyoti (ORCID:0000000205220235)↗

DOE OSTI2022

Transforming Energy Through Sustainable Mobility: Expanding Low-Carbon Transportation R&D Solutions

As the nation's premier laboratory for cutting-edge transportation decarbonization research and development solutions, the National Renewable Energy Laboratory (NREL) pioneers the creation and deployment of sustainable mobility technologies and strategies, with a focus on slashing transportation sector greenhouse gas emissions and combatting climate change. Trucks, planes, cargo ships, and other difficult-to-decarbonize vehicles are part of this essential transition for the transportation sector, which is currently the nation's largest source of the greenhouse gas emissions. NREL provides the scientific building blocks needed to spur innovation through multifaceted analysis, research, and engineering. This work acts as a catalyst to help industry bring affordable, high-performance, energy-efficient, and low-emission modes of transport and related infrastructure to market sooner. Our researchers collaborate closely with academic, government, and industry partners to design better batteries, drivetrains, and engines. They develop technologies for high-power charging, thermal management, energy storage, and power electronics. They are also reimagining fuels and combustion while creating sustainable lightweight materials. Unbiased expert guidance - backed by credible data and analysis, tools, and scientific rigor - empowers partners to make informed decisions about sustainable transportation. NREL recognizes that communities with limited mobility options face reduced access to employment opportunities, health care, and education, lowering overall quality of life. Alongside partners, NREL experts are creating transportation solutions that meet community-identified needs and increase mobility equity in historically underserved and overburdened communities. Rather than providing a one-size-fits-all solution, we take an interdisciplinary approach to mobility equity that considers the needs and challenges of diverse groups, maximizing benefits at the individual, community, and societal levels.

ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2019

Regarding Pilot Usage of Display Technologies for Improving Awareness of Aircraft System States

ed systems and the procedures for ng in complexity. This interacting trend places a larger burden on pilots to manage increasing amounts of information and to understand system interactions. The result is an increase in the likelihood of loss of airplane state awareness (ASA). One way to gain more insight into this issue is through experimentation using objective measures of visual behavior. This study summarizes an analysis of oculometer data obtained during a high-fidelity flight simulation study that included a variety of complex pilot-system interactions that occur in current flight decks, as well as several planned for the next generation air transportation system. The study was comprised of various scenarios designed to induce low and high energy aircraft states coupled with other emulated causal factors in recent accidents. Three different display technologies were evaluated in this recent pilot-in-the-loop study conducted at NASA Langley Research Center. These technologies include a stall recovery guidance algorithm and display concept, an enhanced airspeed control indication of when the automation is no longer actively controlling airspeed, and enhanced synoptic diagrams with corresponding simplified electronic interactive checklists. Multiple data analyses were performed to understand how the 26 participating airline pilots were observing ASA-related information provided during different stag specific events within these stages.

Daniels, Taumi S.↗

DOE OSTI2025

ArcticShark Uncrewed Aerial System

Some studies of atmospheric processes benefit from specialized instrumented observation platforms, including towers, crewed aircraft, tethered balloon systems, and uncrewed aerial systems (UAS). The ArcticShark UAS, managed by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) User Facility, has emerged as a vital scientific platform, providing comprehensive measurements to expand the horizons of atmospheric research and ARM data. The ArcticShark focuses on small-scale, accurate, and repetitive flight patterns over areas of scientific interest, including ARM’s ground observatories in Alabama and Oklahoma. When used in concert with data from ground-based instruments and other aerial platforms, UAS observations help deliver a complete picture of atmospheric processes, helping scientists evaluate and improve the accuracy of earth system models needed to inform energy infrastructure planning.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Development and Demonstration of a Fuel-Efficient, Class 8 Tractor & Trailer Engine System (SuperTruck II)

Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.

Zukouski, Russ↗