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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
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DOE OSTI2025

Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems

Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.

25 ENERGY STORAGE↗
DOE OSTI2020

Contributions of Solar + Storage to Future Power Needs

The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid. Additionally, as battery costs decline, there is increasing interest in understanding the benefits and limitations of battery storage for the grid as well as potential co-benefits of coupling battery storage and photovoltaics. This paper presents recent methodological developments to more accurately represent the value and limitations of coupled PV and battery systems in capacity expansion models. These are demonstrated using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch through 2045. We simulate the evolution of the generation and transmission system in the Western Interconnection both with and without a coupled PV and battery technology option under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and mid PV and battery cost projections. We analyze the degree to which a variety of configurations of coupled PV + Battery systems are able to meet future electricity needs, under which system conditions this coupled technology becomes beneficial to the electric grid and identify the displaced technologies when coupled solar and storage is introduced into the model. We find that capturing the benefits of co-locating these systems becomes increasingly important as the penetration of solar PV rises, and that in particular it is important to accurately capture the ability of these technologies to shift energy, provide firm capacity, and reduce expected curtailment.

14 SOLAR ENERGY↗
DOE OSTI2021

Data‐Driven Safety Risk Prediction of Lithium‐Ion Battery

Abstract Inevitable safety issues have pushed battery engineers to become more conservative in battery system design; however, battery‐involved accidents still frequently are reported in headlines. Identifying, understanding, and predicting safety risks have become priorities to further accelerate technology and industry development. However, diverse loading scenarios, significantly varied stress‐induced short circuit mechanisms, and highly coupled mechanical–electrochemical safety behaviors have remained grand challenges. Herein, the safety risk is termed as the probability of the mechanical triggering of an internal short circuit, to reflect the safety related behaviors of lithium‐ion batteries. Based on a mechanical model and experimental results, a sufficient dataset is generated consisting of strain states and their corresponding safety risks, covering both cylindrical and pouch cells, various states of charges, and loading conditions. Machine‐learning tools combined with the established finite element mechanical model are applied to predict the safety risks of the cells. The results achieve a high level of accuracy on the test data (the relative error of the average short circuit prediction deviation is less than 6.2%.). This work underpins the safety risk concept and highlights the promise of physics combined with data‐driven modeling methodology to predict the safety behaviors of energy storage systems.

Jia, Yikai↗
DOE OSTI2021

SiC-Based 5-kV Universal Modular Soft-Switching Solid-State Transformer (M-S4T) for Medium-Voltage DC Microgrids and Distribution Grids

Medium-voltage DC (MVDC) grids are attractive for electric aircraft and ship power systems, battery energy storage system (BESS), fast charging electric vehicle (EV), etc. Such EV or BESS applications need isolated bidirectional MVDC to LVDC or LVAC converters. However, the existing Si-based solutions cannot fulfill the requirements of a high-efficiency and robust converter for MVDC grids. This paper presents a 5 kV SiC-based universal modular solid-state transformer (SST). This universal current-source SST can interface either a LVAC or LVDC grid with a MVDC grid in single-stage power conversion, while the conventional dual active bridge (DAB) converter needs an additional inverter. The proposed SST module using 3.3 kV SiC MOSFETs and diodes is bidirectional and can serve as a building block in series or parallel for higher-voltage higher-power systems. The topology of each module is based on the soft-switching solid-state transformer (S4T) with reduced conduction loss, which features reduced EMI through controlled dv/dt, and high efficiency with full-range ZVS for main devices and ZCS for auxiliary devices. Operation principle of the modular S4T (M-S4T), capacitor voltage balancing control between the cascaded modules, design of components including a medium-voltage (MV) medium-frequency transformer (MFT) to realize a 50 kVA 5 kV DC to 600 V DC or 480 V AC M-S4T are presented. Importantly, the MV MFT prototype achieves very low leakage inductance (0.13%) and 15 kV insulation with coaxial cables and nanocrystalline cores. Here, the proposed universal modular SST is compared against the DAB solution and verified with DC-DC and DC-AC simulation and 4 kV experimental results. Significantly, the MV experimental results of a modular DC transformer with each module at MVDC are rarely covered in the literature and reported for the first time.

14 SOLAR ENERGY↗
DOE OSTI2020

Development and Validation of a Simulation Tool to Predict the Combined Structural, Electrical, Electrochemical and Thermal Responses of Automotive Batteries

Battery safety is one of the most important design factors of electrified vehicles (EVs) since battery failure may lead to a catastrophic consequence. To improve the safety of battery systems in EVs, battery behaviors under various abuse conditions should be well understood. One way to examine battery response under extreme conditions is to conduct abuse tests in different scenarios. They can provide first-hand pass/fail information on battery safety, but they are usually expensive and time-consuming, which is inconvenient during design iterations and optimization. On the other hand, computational modeling can predict the battery behaviors in a more efficient and cost-effective way, which becomes an important tool to evaluate battery safety. Modeling battery responses and failure is challenging since it involves multiple coupled physical processes, needs to consider complex material properties and is computationally intensive. This project aims to develop a practical simulation tool to predict the combined structural, electrical, electrochemical, and thermal responses of automotive batteries to crash-induced crush and short circuit and validate it for conditions relevant to automotive crash. Advanced material constitutive models will be utilized to capture the mechanical response of cell components. Moreover, methods will be developed to reduce computational complexity of the model and allow battery safety simulations to extend from cell-level to module/pack level with affordable computational resources.

25 ENERGY STORAGE↗
DOE OSTI2024

Understanding ion-selective Li/Na metal plating behavior in hybrid Li-Na battery

This study investigates ion-selective Li/Na metal plating behavior in hybrid Li-Na battery systems, revealing the critical role of electrolyte solvents in these processes. Using a hybrid battery design with a LiFePO 4 cathode, Na metal anode, and NaPF 6 -based electrolytes, we observed contrasting effects of carbonate- and ether-based electrolyte solvents. While ether-based electrolytes showed expected Na plating/stripping, carbonate-based electrolytes surprisingly favored a Li-dominant plating/stripping reaction despite the Na-rich environment. X-ray photoelectron spectroscopy revealed that this selectivity is linked to the composition of the solid electrolyte interphase (SEI) layer, with carbonate electrolytes forming Li-based inorganic-rich SEI layers that facilitate Li-ion diffusion while screening Na ions. In conclusion, these findings challenge the conventional understanding of metal plating in multi-ion environments and offer insights for designing future hybrid battery systems.

25 ENERGY STORAGE↗
DOE OSTI2021

C3PU:Real-Time Predictive Charge Control Software for Battery Management Systems (Code for Charge Control and Predictive Unit) [SWR-21-48]

C3PU sets up a model predictive control formulation for the optimal charging control of battery packs and can be deployed for real-time operation on an embedded microprocessor. C3PU uses electrochemical and thermal models of battery packs to predict the charging trajectories of the battery pack over a time horizon under different operating conditions. It then selects the optimal charging trajectory such that a pre-defined objective is minimized, which in the present state of the code is to minimize the charging duration of the battery pack. The optimal charging trajectory is obtained by solving an underlying mathematical problem. However, C3PU is flexible to incorporate other charging objectives. The underlying battery models can be swapped as well, as long as they follow certain mathematical properties. Mathematically, optimal control problems (in this case, optimally controlling the charging current of the battery pack) are computationally expensive. C3PU implements advanced numerical techniques, namely pseudo-spectral optimization, to reduce the computational burden of the underlying problem to solve. This allows for the problem to be solved in real-time in an embedded system. Once the optimal charging trajectory is computed over a time horizon, C3PU can package such data and send it out via appropriate communication protocols.

Mishra, Partha↗
DOE OSTI2022

Control Oriented Model of Cabin-HVAC System in a Long-Haul Trucks for Energy Management Applications

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output. Second, a two-node cabin model formulated to estimate the cabin temperature as a function of the Global Horizontal Irradiance (GHI), HVAC load and ambient temperature. The models are calibrated using experimental cabin-HVAC system data as for long-haul class 8 truck (e.g. ST-II). Here, the model simulations show that the overall Root Mean Square Error (RMSE) value of 0.4°C between the experimental and simulated cabin temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Surface analysis insight note: X‐ray photoelectron spectroscopy analysis of battery electrodes—Challenges with nickel–manganese–cobalt and Li examples using an Al Kα x‐ray source

X‐ray photoelectron spectroscopy (XPS) has become a highly important tool for the analysis of battery materials and components. However, both anecdotal and detailed analysis of selected parts of the literature indicate that many reports of XPS on battery electrodes have significant analysis or data flaws. In this paper, we highlight several of the common challenges that analysts face when using XPS for battery materials, pointing to recent literature that addresses many of the critical issues associated with sample preparation as well as data collection and analysis. A common error for battery materials (and other materials) involves ignoring peak overlaps and interferences. Specifically, when a “minor” peak associated with a component in relatively high concentration overlaps or contributes to the primary peak (or one recommended for quantitative analysis) from a different element in the material. Overlap issues apply to many battery electrodes composed of many elements with complex photoelectron peak structures, as well as those involving peaks with seemingly simpler spectral envelopes such as Li and F. Examples of issues associated with battery systems are highlighted by a discussion of challenges associated with XPS analysis of Li and nickel–manganese–cobalt (NMC) electrodes in battery systems. Lithium analysis has challenges associated with the preparation and an often‐unrecognized peak overlap with F. In our laboratory and in the literature, NMC electrodes are often examined and new XPS users do not always recognize interference of the Auger signal from F KLL (in or on the electrode) with Ni 2p photoelectron spectrum when generated with Al Kα X‐rays. The use of simulated spectra involving both F and NiO demonstrates the extent of F Auger contributions to the Ni 2p signal strength as a function of the F/Ni atom ratio in the material and suggests spectra information that can be used to identify how significant effects will be on the resultant spectra. Our analysis demonstrates that in many cases overlap issues are significant for real electrode materials.

25 ENERGY STORAGE↗
DOE OSTI2020

Cost Projections for Utility-Scale Battery Storage (2020 Update)

In this work we describe the development of cost and performance projections for utility-scale lithium-ion battery systems, with a focus on 4-hour duration systems. The projections are developed from an analysis of 19 publications that consider utility-scale storage costs. The suite of publications demonstrates varied cost reductions for battery storage over time. Figure ES-1 shows the low, mid, and high cost projections developed in this work (on a normalized basis) relative to the published values. Figure ES-2 shows the overall capital cost for a 4-hour battery system based on those projections, with storage costs of $\$$144/kWh, $\$$208/kWh, and $\$$293/kWh in 2030 and $\$$88/kWh, $\$$156/kWh, and $\$$219/kWh in 2050. Battery variable operations and maintenance costs, lifetimes, and efficiencies are also discussed, with recommended values selected based on the publications surveyed.

14 SOLAR ENERGY↗
DOE OSTI2021

Cost Projections for Utility-Scale Battery Storage: 2021 Update

In this work we describe the development of cost and performance projections for utility-scale lithium-ion battery systems, with a focus on 4-hour duration systems. The projections are developed from an analysis of recent publications that consider utility-scale storage costs. The suite of publications demonstrates varied cost reductions for battery storage over time. Figure ES-1 shows the low, mid, and high cost projections developed in this work (on a normalized basis) relative to the published values. Figure ES-2 shows the overall capital cost for a 4-hour battery system based on those projections, with storage costs of $\$$143/kWh, $\$$198/kWh, and $\$$248/kWh in 2030 and $\$$87/kWh, $\$$149/kWh, and $\$$248/kWh in 2050. Battery variable operations and maintenance costs, lifetimes, and efficiencies are also discussed, with recommended values selected based on the publications surveyed.

25 ENERGY STORAGE↗
DOE OSTI2022

Multi-service battery energy storage system optimization and control

Battery energy storage systems (BESS) have become fundamental part of modern power systems due to their capability to provide multiple grid services. As the renewable penetration increases, BESS procurement is also expected to increase where it is envisioned to play a systematic and strategical role in power systems planning and operation. Hence, in this paper we present a multiple grid service procurement and operation for BESS - ranging from energy arbitrage, reserve/regulation services, power factor correction, and demand management. The proposed framework considers an optimal multi-temporal dimension, designed to be operable for both planning and real-time operation. Moreover, non-linearity inherent to BESS services and uncertainty associated to market forecasts variables are addressed using techniques such as polyhedral norms and robust optimization approaches. Here, the developed model is tested using a utility-scaled BESS and the obtained results show the effectiveness of the systematic BESS multi-service planning and operation approach.

25 ENERGY STORAGE↗
DOE OSTI2021

Apparatuses and methods for testing electrochemical cells by measuring frequency response

Real-time battery impedance spectra are acquired by stimulating a battery or battery system with a signal generated as a sum of sine signals at related frequencies. An impedance measurement device can be used to interface between the battery system and a host computer for generating the signals. The impedance measurement device may be calibrated to adapt the response signal to more closely match other impedance measurement techniques. The impedance measurement device may be adapted to operate at mid-range voltages of about 50 volts and high-range voltages up to about 300 volts.

Christophersen, Jon P.↗
DOE OSTI2020

Lithium ion battery with thermal runaway protection

Lithium ion batteries are provided that include materials that provide advantageous endothermic functionalities contributing to the safety and stability of the batteries. The endothermic materials may include a ceramic matrix incorporating an inorganic gas-generating endothermic material. If the temperature of the lithium ion battery rises above a predetermined level, the endothermic materials serve to provide one or more functions to prevent and/or minimize the potential for thermal runaway, e.g., thermal insulation (particularly at high temperatures); (ii) energy absorption; (iii) venting of gases produced, in whole or in part, from endothermic reaction(s) associated with the endothermic materials, (iv) raising total pressure within the battery structure; (v) removal of absorbed heat from the battery system via venting of gases produced during the endothermic reaction(s) associated with the endothermic materials, and/or (vi) dilution of toxic gases (if present) and their safe expulsion from the battery system.

25 ENERGY STORAGE↗
DOE OSTI2020

Recent Advances in Rechargeable Aluminum-Ion Batteries and Considerations for Their Future Progress

Owing to their high theoretical capacity and reliable operational safety, nonaqueous rechargeable aluminum batteries (RABs) have emerged as a promising class of battery materials and been intensively studied in recent years; however, a lack of suitable, high-performing positive electrode materials, along with the need for air-sensitive and expensive ionic liquid electrolytes, has significantly hindered the practical use of RABs in large-scale applications. Therefore, we sought to carefully analyze positive electrode materials and the associated electrolytes that have been reported in these battery systems in order to stimulate the design of the next generation of high-performance and low-cost RABs. In this review, we have summarized the electrode materials that have been used in both nonaqueous and aqueous RAB systems and provided a rational classification based on the types of materials used and their respective structures. Additionally, we have reviewed electrolytes employed in RABs and have categorized them according to two main types of applications, either for fixed battery systems or for use in portable devices. Here, a systematic account of recent developments on RABs, with a focus on electrode materials, innovative perspectives, and impending research efforts on future RABs, has been included. Finally, a proposed liquid RAB system is discussed with the aim of solving issues regarding fast-charging and long operational lifetimes, followed by insights into solid RABs for use in both portable and multistructural RAB systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Cost and Efficiency Analysis for Hybrid AC/DC Distribution System Planning with PV and Battery

Distribution system planning is one of the main tasks for the electric utilities. Cost and energy efficiency are two main concerns in the distribution planning process. In this work, cost and efficiency analyses are conducted for the hybrid AC and DC distribution grids for the planning purposes. The IEEE 34-bus feeder has been applied for the case studies. The investment cost, operation and maintenance cost, replacement cost, etc., have been considered in the life cycle cost analysis. Power losses of both the AC and DC section are calculated with an open source simulation tool, the Open Distribution Simulator Software (OpenDSS). The proposed framework can be applied to quantitatively evaluate the cost and efficiency of hybrid AC and DC distribution grids and help comparing different planning options.

AC/DC hybrid system planning↗