Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “BATTERY PROGRAM”

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.

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

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of battery aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Low-Cost All-Temperature Zinc-Pulp Battery for Stationary Storage

WH-Power Final Technical Report — Low-Cost All-Temperature Zinc-Pulp Battery This is the final scientific/technical report for ARPA-E CREATE program award DE-AR0001796, covering work from September 2023 through September 2025. The WHP–UMD–Yale team set out to develop a safe, low-cost, wide-temperature zinc battery for grid-scale stationary storage. What was built: A zinc-pulp (Zn/CNF) battery system pairing an aqueous high-entropy electrolyte (HEE) with a cellulose-derived ion-conducting membrane.

25 ENERGY STORAGE↗
DOE OSTI2015

Effects of Electric Vehicle Fast Charging on Battery Life and Vehicle Performance

As part of the U.S. Department of Energy’s Advanced Vehicle Testing Activity, four new 2012 Nissan Leaf battery electric vehicles were instrumented with data loggers and operated over a fixed on-road test cycle. Each vehicle was operated over the test route, and charged twice daily. Two vehicles were charged exclusively by AC level 2 EVSE, while two were exclusively DC fast charged with a 50 kW charger. The vehicles were performance tested on a closed test track when new, and after accumulation of 50,000 miles. The traction battery packs were removed and laboratory tested when the vehicles were new, and at 10,000-mile intervals. Battery tests include constant-current discharge capacity, electric vehicle pulse power characterization test, and low peak power tests. The on-road testing was carried out through 70,000 miles, at which point the final battery tests were performed. The data collected over 70,000 miles of driving, charging, and rest are analyzed, including the resulting thermal conditions and power and cycle demands placed upon the battery. Battery performance metrics including capacity, internal resistance, and power capability obtained from laboratory testing throughout the test program are analyzed. Results are compared within and between the two groups of vehicles. Specifically, the impacts on battery performance, as measured by laboratory testing, are explored as they relate to battery usage and variations in conditions encountered, with a primary focus on effects due to the differences between AC level 2 and DC fast charging. The contrast between battery performance degradation and the effect on vehicle performance is also explored.

Electric Vehicle↗
DOE OSTI2016

Data-driven battery product development: Turn battery performance into a competitive advantage.

Poor battery performance is a primary source of user dissatisfaction across a broad range of applications, and is a key bottleneck hindering the growth of mobile technology, wearables, electric vehicles, and grid energy storage. Engineering battery systems is difficult, requiring extensive testing for vendor selection, BMS programming, and application-specific lifetime testing. This work also generates huge quantities of data. This presentation will explain how to leverage this data to help ship quality products faster using fewer resources while ensuring safety and reliability in the field, ultimately turning battery performance into a competitive advantage.

25 ENERGY STORAGE↗
DOE OSTI2012

Electrical Energy Storage for Renewable Energy Systems

This program focused on development of the fundamental understanding necessary to significantly improve advanced battery and ultra-capacitor materials and systems to achieve significantly higher power and energy density on the one hand, and significantly lower cost on the other. This program spanned all the way from atomic-level theory, to new nanomaterials syntheses and characterization, to system modeling and bench-scale technology demonstration. This program not only delivered significant advancements in fundamental understanding and new materials and technology, it also showcased the power of the cross-functional, multi-disciplinary teams at UT Dallas and UT Tyler for such work. These teams are continuing this work with other sources of funding from both industry and government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Testing Low-Energy, High-Power Energy Storage Alternatives in a Full-Hybrid Vehicle (Presentation)

Automakers have been mass producing hybrid electric vehicles (HEVs) for well over a decade, and the technology has proven to be very effective at reducing per-vehicle gasoline use. However, the battery cost in HEVs contribute to higher incremental cost of HEVs (a few thousand dollars) than the cost of comparable conventional vehicles, which has limited HEV market penetration. Significant cost reductions/performance improvements to the energy storage system (ESS) can improve the vehicle-level cost vs. benefit relationship for HEVs. Such an improvement could lead to larger HEV market penetration and greater aggregate gasoline savings. After significant analysis by the National Renewable Energy Laboratory (NREL), the United States Advanced Battery Consortium (USABC) and Department of Energy (DOE) Energy Storage program suggested a new set of requirements for ESS for power-assist HEVs for cost reduction without impacting performance and fuel economy significantly. With support from DOE, NREL has developed an HEV test platform for in-vehicle performance and fuel economy validation testing of the hybrid system using such LEESS devices. This poster will describe development of the LEESS HEV test platform, and LEESS laboratory as well as in-vehicle evaluation results. The first LEESS technology tested was lithium-ion capacitors (LICs) - i.e., asymmetric electrochemical energy storage devices possessing one electrode with battery-type characteristics (lithiated graphite) and one with ultracapacitor-type characteristics (carbon). We will discuss the performance and fuel saving results with LIC with comparison with original NiMH battery.

25 ENERGY STORAGE↗
DOE OSTI2018

Energy Dense Batteries Based on Highly Conductive Solid Electrolyte and Cathode Materials

Solid Power’s Phase II program builds on promising Phase I results to further develop, scale, and integrate Oakridge National Laboratory’s (ORNL) material technologies into prototype cells relevant to electric vehicle applications. These cells will provide excellent energy density, specific energy, safety, and low cost compared to conventional Li-ion. The optimal material system is targeted for integration into >10 Ah pouch cells to demonstrate the ability to reach the United State Advanced Battery Consortium (USABC) performance targets and the specific targets of Solid Power’s automotive OEM stakeholders.

25 ENERGY STORAGE↗
DOE OSTI2013

Development of Production-Intent Plug-In Hybrid Vehicle Using Advanced Lithium-Ion Battery Packs with Deployment to a Demonstration Fleet

The primary goal of this project was to speed the development of one of the first commercially available, OEM-produced plug-in hybrid electric vehicles (PHEV). The performance of the PHEV was expected to double the fuel economy of the conventional hybrid version. This vehicle program incorporated a number of advanced technologies, including advanced lithium-ion battery packs and an E85-capable flex-fuel engine. The project developed, fully integrated, and validated plug-in specific systems and controls by using GM’s Global Vehicle Development Process (GVDP) for production vehicles. Engineering Development related activities included the build of mule vehicles and integration vehicles for Phases I & II of the project. Performance data for these vehicles was shared with the U.S. Department of Energy (DOE). The deployment of many of these vehicles was restricted to internal use at GM sites or restricted to assigned GM drivers. Phase III of the project captured the first half or Alpha phase of the Engineering tasks for the development of a new thermal management design for a second generation battery module. The project spanned five years. It included six on-site technical reviews with representatives from the DOE. One unique aspect of the GM/DOE collaborative project was the involvement of the DOE throughout the OEM vehicle development process. The DOE gained an understanding of how an OEM develops vehicle efficiency and FE performance, while balancing many other vehicle performance attributes to provide customers well balanced and fuel efficient vehicles that are exciting to drive. Many vehicle content and performance trade-offs were encountered throughout the vehicle development process to achieve product cost and performance targets for both the OEM and end customer. The project team completed two sets of PHEV development vehicles with fully integrated PHEV systems. Over 50 development vehicles were built and operated for over 180,000 development miles. The team also completed four GM engineering development Buy-Off rides/milestones. The project included numerous engineering vehicle and systems development trips including extreme hot, cold and altitude exposure. The final fuel economy performance demonstrated met the objectives of the PHEV collaborative GM/DOE project. Charge depletion fuel economy of twice that of the non-PHEV model was demonstrated. The project team also designed, developed and tested a high voltage battery module concept that appears to be feasible from a manufacturability, cost and performance standpoint. The project provided important product development and knowledge as well as technological learnings and advancements that include multiple U.S. patent applications.

25 ENERGY STORAGE↗
DOE OSTI2016

Economic Analysis and Optimal Sizing for behind-the-meter Battery Storage

This paper proposes methods to estimate the potential benefits and determine the optimal energy and power capacity for behind-the-meter BSS. In the proposed method, a linear programming is first formulated only using typical load profiles, energy/demand charge rates, and a set of battery parameters to determine the maximum saving in electric energy cost. The optimization formulation is then adapted to include battery cost as a function of its power and energy capacity in order to capture the trade-off between benefits and cost, and therefore to determine the most economic battery size. Using the proposed methods, economic analysis and optimal sizing have been performed for a few commercial buildings and utility rate structures that are representative of those found in the various regions of the Continental United States. The key factors that affect the economic benefits and optimal size have been identified. The proposed methods and case study results cannot only help commercial and industrial customers or battery vendors to evaluate and size the storage system for behind-the-meter application, but can also assist utilities and policy makers to design electricity rate or subsidies to promote the development of energy storage.

Wu, Di↗
DOE OSTI2018

Bulk force in a battery pack and its application to state of charge estimation

There is disclosed an electrical device including a battery pack, a pressure sensor for measuring a volume change of the battery pack, a voltage sensor in electrical communication with a positive terminal and a negative terminal of the battery pack, a temperature sensor positioned in a cell of the battery pack, and a battery management system. The battery management system includes a controller in electrical communication with the pressure sensor, the voltage sensor, and the temperature sensor, the controller being configured to execute a program stored in the controller to determine a state of charge percentage of the battery pack based on a pressure reading from the pressure sensor, a terminal voltage reading from the voltage sensor, and a temperature reading from the temperature sensor.

Stefanopoulou, Anna G.↗
DOE OSTI2021

An economic assessment of behind-the-meter photovoltaics paired with batteries on the Hawaiian Islands.

Due to natural variability and uncertainty, the ever-increasing penetration of solar generation in Hawaii presents challenges to power grid operators to maintain reliable system operation. Demand response (DR) has the potential to be a cost-effective tool for Hawaii to reach its aggressive renewable energy goals while maintaining the reliability of power grids. The Hawaii Public Utilities Commission has approved the Hawaiian Electric Company's revised portfolio of DR programs. The companies have released a grid services purchase agreement and subscribed an initial tranche of load into their DR programs. This paper presents innovative analytical methods and comprehensive economic assessment for distributed photovoltaics (PV) paired with battery energy storage systems (BESSs) for two new DR programs, including fast frequency response and capacity grid service. Optimal dispatch and sizing methods are proposed for the paired system considering different tariff schedules and PV compensation programs across five islands. It was found that while the best resource configuration and potential economic benefits vary with tariff structure, a BESS paired with PV can be optimally dispatched to generate multiple value streams simultaneously. Compensation from DR programs is an important value stream to help increase the cost-effectiveness of the integrated system.

Battery energy storage system↗
DOE OSTI2019

Dispatch optimization of concentrating solar power with utility-scale photovoltaics

Concentrating solar power (CSP) tower technologies capture thermal radiation from the sun utilizing a field of solar-tracking heliostats. When paired with inexpensive thermal energy storage (TES), CSP technologies can dispatch electricity during peak-market-priced hours, day or night. The cost of utility-scale photovoltaic (PV) systems has dropped significantly in the last decade, resulting in inexpensive energy production during daylight hours. The hybridization of PV and CSP with TES systems has the potential to provide continuous and stable energy production at a lower cost than a PV or CSP system alone. Hybrid systems are gaining popularity in international markets as a means to increase renewable energy portfolios across the world. Typically, CSP-PV hybrid systems have been evaluated using either monthly averages of hourly PV production or scheduling algorithms that neglect the time-of-production value of electricity in the market. To more accurately evaluate a CSP-PV-battery hybrid design, we develop a profit-maximizing mixed-integer linear program ($\mathcal{H}$) that determines a dispatch schedule for the individual sub-systems with a sub-hourly time fidelity. We introduce the mathematical formulation of such a model and show that it is computationally expensive to solve. To improve model tractability and reduce solution times, we offer techniques that: (1) reduce the problem size, (2) tighten the linear programming relaxation of ($\mathcal{H}$) via reformulation and the introduction of cuts, and (3) implement an optimization-based heuristic (that can yield initial feasible solutions for (($\mathcal{H}$) and, at any rate, yields near-optimal solutions). Applying these solution techniques results in a 79% improvement in solve time, on average, for our 48-h instances of (($\mathcal{H}$); corresponding solution times for an annual model run decrease by as much as 93%, where such a run consists of solving 365 instances of (($\mathcal{H}$), retaining only the first 24 h' worth of the solution, and sliding the time window forward 24 h. We present annual system metrics for two locations and two markets that inform design practices for hybrid systems and lay the groundwork for a more exhaustive policy analysis. A comparison of alternative hybrid systems to the CSP-only system reflects that hybrid models can almost double capacity factors while resulting in a 30% improvement related to various economic metrics.

14 SOLAR ENERGY↗
DOE OSTI2012

Development of an Anode Stabilization Layer for High Energy Li-S Cells for Electric Vehicles

For lithium-Sulfur (Li-S) batteries to be practical, economic and safe for powering electric vehicles more than 300 miles between charges the energy and cycle life must be improved. Li- S’s theoretical specific energy and energy density are (2,550 Wh/kg, 2,860 Wh/l), compared to (~600 Wh/kg, 1,800 Wh/l) for Li-ion. At less than 25% of theoretical specific energy (~560 Wh/kg at the cell level), Li-S batteries could power a 1500 kg, 5 passenger vehicle, more than 300 miles between charges with a battery pack weighing less than 300 kg. For commercial viability these cells must be safe, low cost and exhibit more than 1,000 full depth of discharge cycles. By implementing unique new physical barrier technologies this work targets (500 Wh/kg, 500 cycles) at the cell level by late 2013. After this program, (600 Wh/kg, 1,000 cycles) cells are targeted in >40 kWh battery packs by 2018 at < $200/kWh. The present state-of-the-art Li-S cells developed at Sion Power, in current commercial format delivers (2.8 Ah, 5.8 Wh, 350 Wh/kg) and are limited to ~50 cycles. These cells deliver only 14% of theoretical specific energy. By retooling and optimizing cell design and packaging to rebalance materials, this chemistry can reach (350 Wh/kg, ~100 cycles) in commercial cells. Much more than 100 cycles, at >350 Wh/kg, is unlikely for the present chemistry-only Li-S cell paradigm. Cycle life is limited almost exclusively by reactions between the Li-metal anode and the solvents necessary to promote cathode function. To release the transformational energy of Li-S the anode must be decoupled from the cathode chemistry. Prospects to achieve this decoupling through chemistry alone are challenging, therefore this program is to accelerate efforts to decouple anode and cathode chemistries by separating the electrodes with ion selective, thin film multi-layer, physical barrier membranes stabilized by externally applied pressure. This report will focus on efforts of Battelle to develop an anode stabilization layer and method to measure the ionic conductivity of this thin vacuum deposited polymeric layer.

Gross, M. E.↗
DOE OSTI2018

Telematics and Data Science: Informing Energy-Efficient Mobility: October 25, 2016 - October 31, 2017

The University of Connecticut (UCONN) is exploring the possibility of adding electric vehicles (EVs) - including battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), or both-to its vehicle fleet. This report presents results of the UCONN fleet EV Suitability pilot program and offers recommendations for transitioning fleet vehicles to EVs as well as implementing adequate charging infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Impact of heating and cooling loads on battery energy storage system sizing in extreme cold climates

Efficient operation of battery energy storage systems requires that battery temperature remains within a specific range. Current techno-economic models neglect the parasitic loads heating and cooling operations have on these devices, assuming they operate at constant temperature. In this work, these effects are investigated considering the optimal sizing of battery energy storage systems when deployed in cold environments. Here, a peak shaving application is presented as a linear programming problem which is then formulated in the PYOMO optimization programming language. The building energy simulation software EnergyPlus is used to model the heating, ventilation, and air conditioning load of the battery energy storage system enclosure. Case studies are conducted for eight locations in the United States considering a nickel manganese cobalt oxide lithium ion battery type and whether the power conversion system is inside or outside the enclosure. The results show an increase of 42% to 300% in energy capacity size, 43% to 217% in power rating, and 43% to 296% increase in capital cost dependent on location. This analysis shows that the heating, ventilation, and air conditioning load can have a large impact on the optimal sizes and cost of a battery energy storage system and merit consideration in techno-economic studies.

25 ENERGY STORAGE↗
DOE OSTI2026

Discrete versus continuous: Enhancing battery optimization in capacity expansion models

This study compares two battery modeling approaches for capacity expansion models: discrete-duration and continuous-duration formulations. In the discrete approach, battery duration is fixed, and power capacity is optimized. In the continuous approach, both power and energy capacities are decision variables, allowing storage duration to be optimized endogenously. Although both discrete-duration and continuous-duration battery formulations are used in long-term power system planning models, the literature has provided limited direct, systematic comparisons of their implications within a common modeling framework. To address this gap, this study implements both approaches in the Regional Energy Deployment System (ReEDS TM ) capacity expansion model using two resource adequacy methods, across a range of future system conditions, and with varying battery cost projections. Results show continuous-duration and high-resolution discrete approaches produce similar capacity expansion outcomes. The continuous formulation achieves faster runtimes compared to discrete-duration runs with many discrete-duration options. However, the discrete-duration approach allows users to choose to have limited fidelity for storage duration options, which in some cases can outperform the continuous formulation. The continuous formulation has the lowest overall system costs, indicating its ability to fine-tune storage duration to better meet specific system needs. This study's findings provide a side-by-side evaluation of discrete and continuous battery modeling approaches and offer guidance for improving the representation of real-world systems, flexibility, and computational efficiency for representing energy storage in long-term power system planning models.

25 ENERGY STORAGE↗
DOE OSTI2021

Battery asset management with cycle life prognosis

We report Battery Asset Management problem determines the minimum cost replacement schedules for each individual asset in a group of battery assets that operate in parallel. Battery cycle life varies under different operating conditions including temperature, depth of discharge (DOD), charge rate, etc., and a battery deteriorates due to usage, which cannot be handled by current asset management models. This paper presents a new battery asset management methodology where battery cycle life prognosis is integrated with parallel asset management to reduce lifecycle cost of the Battery Energy Storage Systems (BESS). For the battery failure time prognosis, a nonlinear physics-based battery capacity fade model is developed and incorporated in parallel asset management model to update battery capacity over time. Experiment results have shown that the developed battery asset management methodology can be conveniently used to facilitate BESS asset management decision making thereby decreasing asset lifecycle costs.

25 ENERGY STORAGE↗
DOE OSTI2018

Optimal Control for Battery Storage Using Nonlinear Models

Battery storage system (BSS) becomes increasingly popular for grid applications due to the advance in battery and power electronics technologies as well as the growing need of flexibility and reserve from power systems with rapidly developed renewable generation. Successful assessment and deployment of BSS requires optimizing its operation and therefore maximizing the potential benefits. Although there exist studies that develop optimal control for evaluation or operational scheduling of BSS, modeling of charging/discharging operation and the corresponding impacts on state-of-charge (SOC) is over simplified in these methods. This paper develops an optimal control for BSS evaluation and operational scheduling using a general nonlinear model that expresses the change of SOC as a function of charging/discharging power and SOC level. The proposed method is compared with a typical existing method through a real-world energy storage evaluation project to show the significance of the proposed method.

battery, energy storage system, dynamic programmin↗