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DOE OSTI2020

Review—Thermal Safety Management in Li-Ion Batteries: Current Issues and Perspectives

Approaches for thermal management of lithium-ion (Li-ion) batteries do not always keep pace with advances in energy storage and power delivering capabilities. Root-cause analysis and empirical evidence indicate that thermal runaway (TR) in cells and cell-to-cell thermal propagation are due to adverse changes in physical and chemical characteristics internal to the cell. However, industry widely uses battery management systems (BMS) originally designed for aqueous-based batteries to manage Li-ion batteries. Even the "best" BMS that monitor both voltage and outside-surface temperature of each cell are not capable of preventing TR or TR propagation, because voltage and surface-mounted temperature sensors do not track fast-emerging adverse events inside a cell. Most BMS typically include a few thermistors mounted on select cells to monitor their surface temperature. Technology to track intra-cell changes that are TR precursors is becoming available. Simultaneously, the complex pathways resulting in cell-to-cell TR propagation are being successfully modelled and mapped. Innovative solutions to prevent TR and thermal propagation are being advanced. These include modern BMS for rapid monitoring the internal health of each individual cell and physical as well as chemical methods to reduce the deleterious effects of rapid cell-to-cell heat and material transport in case of TR.

25 ENERGY STORAGE↗

DOE OSTI2021

Operating a commercial building HVAC load as a virtual battery through airflow control

Virtual battery (VB) is an innovative method to model flexibility of building loads and effectively coordinate them with other resources at a system level. Unlike a real battery with a dedicated power conversion system for charging control, methods are required for operating building loads to deviate from the baseline to respond to grid signals. This paper presents a VB control for a commercial heating, ventilation, and air conditioning (HVAC) system to follow the desired power consumption in real-time by adjusting zonal airflow rates. The proposed method consists of two parts. At the system level, a mixed feedforward and feedback control is used to estimate the desired total airflow rate. At the zone level, two priority-based algorithms are then proposed to distribute the total airflow rate to individual zones. In particular, a zonal airflow limit estimation method is proposed using machine-learning techniques, in contrast to physics-based thermal models in existing studies, to more accurately capture zonal thermal dynamics and improve temperature control performance. An office building on the Pacific Northwest National Laboratory campus is implemented in EnergyPlus, and used to illustrate and validate the proposed control.

Wang, Jiyu↗

DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗

DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗

DOE OSTI2024

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗

DOE OSTI2023

Renewable electricity capacity planning with uncertainty at multiple scales

Abstract We formulate and compare optimization models of investment in renewable generation using a suite of social planning models that compute optimal generation capacity investments for a hydro-dominated electricity system where inflow uncertainty results in a risk of energy shortage. The models optimize the expected cost of capacity expansion and operation allowing for investments in hydro, geothermal, solar, wind, and thermal plant, as well as battery storage for smoothing load profiles. A novel feature is the integration of uncertain seasonal hydroelectric energy supply and short-term variability in renewable supply in a two-stage stochastic programming framework. The models are applied to data from the New Zealand electricity system and used to estimate the costs of moving to a 100% renewable electricity system by 2035. We also explore the outcomes obtained when applying different forms of CO 2 constraint that limit respectively non-renewable capacity, non-renewable generation, and CO 2 emissions on average, almost surely, or in a chance-constrained setting, and show how our models can be used to investigate the merits of a proposed pumped-hydro scheme in New Zealand’s South Island.

Ferris, Michael C.↗

NASA NTRS1980

Wind-energy storage

Program SIMWEST can model wind energy storage system using any combination of five types of storage: pumped hydro, battery, thermal, flywheel, and pneumatic. Program is tool to aid design of optional system for given application with realistic simulation for further evaluation and verification.

Gordon, L. H.↗

DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗

DOE OSTI2026

MAT 332: Recyclable-By-Design Carbon Fiber Composites for Battery Enclosures

This work aims to fabricate a small-scale battery module with the baseline RBD-CFRC and conduct mechanical crush test to develop an initial thermal runaway model. Test the adhesive properties of the RBD-CFRCs using their resin constituent, ultrasonic welding, and other resins employed today. Recommend a future direction for resin development to enable the welding of RBDCFRCs to dissimilar materials. Time and Cost Permitting. Iterate on resin development for flame resistance and adhesive properties, demonstrating how thermal runaway can be reduced or joining properties can be improved.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Development of Electro-chemical Battery Model for Plug-and-Play Eco-system Library

Energy storage components are fundamental to the concept of an Integrated Energy System (IES). They serve to store surplus energy during low-demand periods for later release when other IES components (i.e., Secondary Energy Source, Balance of Plant, etc.) would otherwise have to operate flexibly. This provision for storage avoids high-amplitude power ramps in these components thereby limiting thermal and mechanical stresses to their internals and providing for extended service life. This report describes a dynamic model that has been developed for an electrochemical battery. The lithium-ion (Li-ion) cell was selected as representative technology. The battery model was developed in the Dymola simulation environment and meets the requirements of the ecosystem plug-and-play library. The model accurately describes the electric dynamic response of a Li-ion battery for an imposed charging/discharging power profile. The corresponding physical limitations related to over-power scenarios, and the impact of the residual state of charge are accounted for in the model. A literature review of the major degradation processes affecting Li-ion batteries was performed. Given the purposes of the CTD-IES project, the progressive fade of the installed capacity, the reduction of the round-trip efficiency, and the limits on the number of charging/discharging cycles are aspects that need to be taken into account in techno-economic analyses. The modeling of these degradation phenomena becomes crucial when predictions over long time horizons (capacity expansion) are made. For each one of these phenomena, a brief description is given, and some figures to be implemented in the HERON optimization algorithm are presented.

25 ENERGY STORAGE↗

DOE OSTI2022

Thermal design analysis for SuperTruck II lithium-titanate battery pack

Here, this paper presents a systematic thermal management analysis for a new lithium-titanate-oxide battery pack to be installed in a SuperTruck II, Class 8 hybrid truck. The authors investigate the feasibility of mounting the battery pack inside the vehicle and air-cooling it with fans supplying conditioned air from the cabin. Moreover, the cells within each module are to be immersed in a heat-transfer fluid to improve temperature homogeneity. A multi-stage thermal analysis is performed to ensure adequate thermal regulation of the battery under the proposed design, considering installation and operational constraints. The authors perform thermal and electrical characterization tests on a single cell. Results inform the development of computational fluid dynamics models of the cells, modules, and pack. Module-level analysis shows that the cell temperatures can be maintained below their upper operational limit of 55 °C with module wall-to-air heat transfer coefficients between 10 and 20 Wm -2 K -1 . Pack-level analysis of distinct configurations determines effective airflow paths for adequate heat transfer and delivers a final battery pack design that achieves sufficient cooling and temperature uniformity. A reduced-order electrothermal model is developed to rapidly predict the transient battery performance and to develop a temperature control strategy.

25 ENERGY STORAGE↗

NASA NTRS2016

An Influenced Future

Phobos is a vital precursor and catalyst before our next giant leap to Mars. The principle period of a Phobos' mission could be a series of robotic precursor missions for experimental perception, soil examination, ecological approval and landing site distinguishing proof. For my summer intern position at Johnson Space Center I chipped away at creating a GUNNS (General Use Nodal Network Solver) based power subsystem model for the miniATHLETE hopper, which is a conceptual (idea-based) robotic lander that will operate on Phobos. Keeping in mind the end goal to begin on my venture, I needed to comprehend my undertaking before whatever else, in which I concentrated on C++ to see how to implement the code that GUNNS generates to a Trick S_define file. Prior to coming to this internship at Johnson Space Center Dr. Edwin Zack Crues provided a class on modeling and simulation, which introduced me to the Trick simulation environment. The goal of my project was to develop a GUNNS based power subsystem model for the miniATHLETE hopper. The model needed to incorporate a solar array, battery, hopping legs, and onboard scientific instruments (sensitive measuring/recording devices). The secondary bonus goal after I completed the electrical aspect of my model was to develop a GUNNS based thermal subsystem model for the miniATHLETE hopper. Stringing the two aspects together, I would need to code up a signal aspect to make the system work as one. Accomplishing my goals would not be an easy thing, however I had successfully completed the electrical aspect model with twenty-four servos, six cameras, and multiple sensors. Venturing to complete my project has eluded me to many failures in my design to tune many things like the battery to the proper voltage and the load to the proper wattage. During this time I had touched up on advanced topics in calculus in which I implemented in the converter in my electrical model. I am currently working with my mentor Zu Qun Li to create a signal aspect to control the temperatures inside my electrical aspect model. During my time at JSC I had effectively figured out how to create subsystem models utilizing Trick and GUNNS. I obtain essential knowledge of power and thermal subsystem design for a robotic vehicle. I also learned how to work and communicate in a team effectively to accomplish a goal. Before coming to Johnson Space Center my future career and educational goals included uncertainty, however now I have a completely new look on my path to a prosperous future. My NASA experience has unquestionably impacted me to accomplish and surpass my own particular desires. After my time at Johnson Space Center I plan to apply for a coop position for NASA. This has been a dream come true that I adored each moment being at JSC realizing that I am far fit for doing things most individuals can just long for.

Owens, Christopher↗

DOE OSTI2023

Estimate long-term impact on battery degradation by considering electric vehicle real-world end-use factors

Many estimates of battery capacity degradation are based on accelerated lab tests that involve charge-discharge cycles or rely on data or electrochemical modeling. These methods are reasonable for technology benchmarking but rarely consider real-world end-use factors. To address this issue, this study develops the Battery Run-down under Electric Vehicle Operation (BREVO) model. It links the driver's travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. It finds that, over a 10-year timespan, firstly, for a random driver situated in the New England area, daily direct-current fast charging (60 kW) could lead to up to 22% less battery capacity when compared to daily Level-1 charging (1.8 kW). Second, the battery thermal management system can delay battery degradation by approximately 0.5% in the New England area. Third, warmer ambient temperatures enhance BEV battery usage. The model indicates that the battery capacity in the Los Angeles area is 6% higher than that in the New England area. The BREVO model provides crucial information for consumers and BEV manufacturers on range anxiety, BEV battery design, and decision support of battery warranty.

25 ENERGY STORAGE↗

NASA NTRS1979

An expanded system simulation model for solar energy storage (technical report), volume 1

The simulation model for wind energy storage (SIMWEST) program now includes wind and/or photovoltaic systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) and is available for the UNIVAC 1100 series and the CDC 6000 series computers. The level of detail is consistent with a role of evaluating the economic feasibility as well as the general performance of wind and/or photovoltaic energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind and/or photovoltaic source/storage/application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/0, the integration of system dynamics, and the iteration for conveyance of variables.

Warren, A. W.↗

DOE OSTI2024

Coupled Multiphysics Modeling of Lithium-Ion Batteries for Automotive Crashworthiness Applications

Considerable advances have been made in battery safety models, but achieving predictive accuracy across a wide range of conditions continues to be challenging. Interactions between dynamically evolving mechanical, electrical, and thermal state variables make model prediction difficult during mechanical abuse scenarios. In this study, we develop a physics-based modeling approach that allows for choosing between different mechanical and electrochemical models depending on the required level of analysis. We demonstrate the use of this approach to connect cell-level abuse response to electrode-level and particle-level transport phenomena. A pseudo-two-dimensional model and simplified single-particle models are calibrated to electrical-thermal cycling data and applied to mechanically induced short-circuit scenarios to understand how the choice of electrochemical model affects the model prediction under abuse scenarios. These models are implemented using user-defined subroutines on ls-dyna finite element software and can be coupled with existing automotive crash safety models.

analysis and design of components↗

DOE OSTI2023

Modelling and Optimizing CSP-PV Hybrid Systems Using the Hybrid Optimization and Performance Platform (HOPP)

The hybridization of concentrating solar power (CSP) with thermal energy storage (TES), photovoltaics (PV), and electrochemical battery energy storage systems (BESS) has the potential to provide continuous, high-capacity-factor energy production at a lower cost than a PV-BESS or CSP with TES alone. Because of the system complexity of CSP technology, it is challenging to evaluate the technological and financial performance of a CSP-PV hybrid system without detailed modeling of annual operations. To address this challenge, we have developed a modeling framework for evaluating the performance and financial viability of CSP systems hybridized with PV and BESS technologies. This modeling effort incorporates CSP tower and trough configurations into an existing modeling tool recently developed by NREL, the Hybrid Optimization and Performance Platform (HOPP). This paper provides a brief overview of our methodology, as well as an example case study. CSP with TES hybridized with PV provides the best benefit-to-cost ratio compared to the other simulated technology combinations. However, for the conditions considered, this configuration only increases the benefit-to-cost ratio by about 1% compared to the CSP with TES configuration. The PV-BESS system provides the lowest benefit-to-cost ratio compared to the other configurations explored because of the relatively low capacity credit received by the system.

Hamilton, William (ORCID:0000000244654239)↗

DOE OSTI2021

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗

DOE OSTI2023

BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py

Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.

Smith, Kandler↗