SEARCH · Search NASA
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.
We face the grand challenge of a growing number of end-of-life lithium-ion batteries over the upcoming years. A recent Cell Reports Sustainability article presents a model for effective end-of-life battery management in China for rural electrification. Here, we emphasize the need for incorporating various stakeholders early in the design phase to remove the barriers to the reuse of retired batteries.
A digital twin system has been established to model the long term degradation of the state of health of lithium ion batteries. Two data streams result from the computational model of the system and from the physical experiment measurements. A machine learning pipeline has been developed at the nexus of these data streams. Leveraging the unique data sources in multiple transfer learning approaches has lead to the development of multiple cell specific machine learning digital twins. Our discussion on this first of its kind technology will cover challenges in data ingestion, scalability, architecture and orchestration, and research findings.
Here, we report a mechano-chemical model for anodic degradation during fast-charging of nickel-manganese-cobalt (NMC)/graphite (C) cell due to SEI growth, lithium plating/stripping, dead lithium storage, and film fracture of composite SEI and plated lithium film. Degradation of the battery is analyzed for a range of charging rates from 1 to 6 C-rates, and the influence of plating mechanisms – lithium plating and dead lithium deposition and recovery during stripping – on the film resistance of the anode are accounted for in the model. Dynamic evolution of the interfacial properties is modeled using rule-of-mixture approach. Model predictions of plating associated stress fields are used to compute critical energy release rate for film cracking. The results indicate an increased tendency of fracture for thinner SEI film with lithium plating at higher charging rates. The process of reforming the cracked film absorbs a significant portion of the electrode current thereby reducing the cell capacity and plating efficiency. The mechano-chemical model provides an extensive analytical framework for understanding the synergistic coupling of anodic degradation mechanisms, prognosticating conditions of SEI failure, and evaluating the capacity fade and efficiency of lithium-ion battery.
Electrolyte systems in contemporary batteries are tasked with operating under increasing performance requirements. All battery operation is in some way tied to the electrolyte and how it interacts with various regions within the cell environment. Seeing the electrolyte plays a crucial role in battery performance and longevity, it is imperative that accurate, physics-based models be developed that will characterize key electrolyte properties while keeping pace with the increasing complexity of these liquid systems. Advanced models are needed since laboratory measurements require significant resources to carry out for even a modest experimental matrix. The Advanced Electrolyte Model (AEM) developed at the INL is a proven capability designed to explore molecular-to-macroscale level aspects of electrolyte behavior, and can be used to drastically reduce the time required to characterize and optimize electrolytes. Although it is applied most frequently to lithium-ion battery systems, it is general in its theory and can be used toward numerous other targets and intended applications. This capability is unique, powerful, relevant to present and future electrolyte development, and without peer. It redefines electrolyte modeling for highly-complex contemporary systems, wherein significant steps have been taken to capture the reality of electrolyte behavior in the electrochemical cell environment. This capability can have a very positive impact on accelerating domestic battery development to support aggressive vehicle and energy goals in the 21st century.
The IBM Thinkpad 760XD has been used in the Orbiter and International Space Station since 2000. The Thinkpad is powered by a Panasonic Li-ion battery that has a voltage of 10.8 V and 3.0 Ah capacity. This Thinkpad is now being replaced by the IBM Thinkpad A31P which has a Panasonic Li-ion battery that has a voltage of 10.8 V and 4.0 Ah capacity. Both batteries have protective circuit boards. The Panasonic battery for the Thinkpad 760XD had 12 Panasonic 17500 cells of 0.75 Ah capacity in a 4P3S cOnfiguration. The new Panasonic battery has 6 Panasonic 18650 cells of 2.0 Ah capacity in a 2P3S configuration. The batteries and cells for both models have been evaluated for performance and safety. A comparison of the cells under similar test conditions will be presented. The performance of the cells has been evaluated under different rates of charge and discharge and different temperatures. The cells have been tested under abuse conditions and the safety features in the cells evaluated. The protective circuit board in the battery was also tested under conditions of overcharge, overdischarge, short circuit and unbalanced cell configurations. The results of the studies will be presented in this paper.
Abuse tests are designed to determine the safe operating limits of HEV\PHEV energy storage devices. Testing is intended to achieve certain worst-case scenarios to yield quantitative data on cell\module\pack response, allowing for failure mode determination and guiding developers toward improved materials and designs. Standard abuse tests with defined start and end conditions are performed on all devices to provide comparison between technologies. New tests and protocols are developed and evaluated to more closely simulate real-world failure conditions. When scaling from cell to the battery level, a detailed understanding of cell interactions provides insight on safety performance. Single point failures from a cell or group of cells can be initiated by a number of triggers including internal short circuit, misuse or abuse, or component failure at the battery or system level. Propagation of a single failure event (regardless of the initiation trigger) through an entire battery, system, or vehicle is an unacceptable outcome with regards to EV battery safety. In this FY, our work has focused on evaluating the propagation of a single cell thermal runaway event through a battery using a variety of design considerations with an emphasis on passive thermal management impacts. This has been coupled with thermal modeling by NREL for these testing conditions. In addition, alternative failure initiation methods have been evaluated to provide direct comparisons of possible energy injection between modes. This data was compiled to better identify what propagation test method is appropriate given certain battery designs. Expanding the analysis of short circuit current during failure propagation has been done for EV relevant chemistries. Ongoing test development and validation to obtain these values has been achieved. While robust mechanical models for vehicles and vehicle components exist, there is a gap for mechanical modeling of EV batteries. The challenge with developing a mechanical model for a battery is the heterogeneous nature of the materials and components (polymers, metals, metal oxides, liquids). Our work will provide empirical data on the mechanical behavior of batteries under compressive load to understand how a battery may behave in a vehicle crash scenario. This work is performed in collaboration with the U.S. Council for Automotive Research (USCAR) and Computer Aided Engineering of Batteries (CAEBAT). These programs have supported the design and development of a drop tower testing apparatus to close the gap between cell/string level testing and full scale crash testing with true dynamic rate effects.
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.
The analysis discussed in this report was performed as part of DOE award DE-EE0009232 to model the effects of charging Heavy Duty Battery Electric Trucks (HDBETs) on the grid. This project combines best in class freight modeling by the National Renewable Energy Laboratory (NREL) with advanced distribution modeling by EPRI using detailed data from Xcel Energy and Salt River Project to analyze the effects of depot charging and utility-grade transmission modeling by Tri-State Transmission and Generation Association Inc. to analyze the effects of en-route charging.
A collection is presented of MHD problems that will provide researchers who have interests in modeling MHD phenomena with a battery of tests (a 'test suite') for calibrating their numerical algorithms. Use of these tests will provide a common reference for comparison of different numerical MHD algorithms. The test suite includes both 1D and 2D problems. Taken together, these problems test the abilities of a numerical method to propagate accurately all of the MHD wave families in moving and stationary media, to capture MHD shocks and contact discontinuities, and to model accurately Lorentz force terms in multiple dimensions. An example solution of each test problem is presented. Diagnostic convergence-testing procedures that provide a quantitative evaluation of MHD algorithms are demonstrated.
A new type of battery named 'Vaporvolt' cell is in the early stage of its development. A mathematical model of a CuO/Cu 'Vaporvolt' cell is presented that can be used to predict the potential and the transport behavior of the cell during discharge. A sensitivity analysis of the various transport and electrokinetic parameters indicates which parameters have the most influence on the predicted energy and power density of the 'Vaporvolt' cell. This information can be used to decide which parameters should be optimized or determined more accurately through further modeling or experimental studies. The optimal thicknesses of electrodes and separator, the concentration of the electrolyte, and the current density are determined by maximizing the power density. These parameter sensitivities and optimal design parameter values will help in the development of a better CuO/Cu 'Vaporvolt' cell.
A theoretical model of the nickel hydrogen battery cell has been utilized to describe the chemical and physical changes during charge and overcharge in a recirculating stack nickel hydrogen cell. In particular, the movement of gas and electrolyte have been examined as a function of the amount of electrolyte put into the cell stack during cell activation, and as a function of flooding in regions of the gas screen in this cell design. Additionally, a two-dimensional variation on this model has been utilized to describe the effects of non-uniform loading in the nickel-electrode on the movement of gas and electrolyte within the recirculating stack nickel hydrogen cell. The type of nonuniform loading that has been examined here is that associated with higher than average loading near the surface of the sintered nickel electrode, a condition present to some degree in many nickel electrodes made by electrochemical impregnation methods. The effects of high surface loading were examined primarily under conditions of overcharge, since the movement of gas and electrolyte in the overcharging condition was typically where the greatest effects of non-uniform loading were found. The results indicate that significant changes in the capillary forces between cell components occur as the percentage of free volume in the stack filled by electrolyte becomes very high. These changes create large gradients in gas-filled space and oxygen concentrations near the boundary between the separator and the hydrogen electrode when the electrolyte fill is much greater than about 95 percent of the stack free volume. At lower electrolyte fill levels, these gaseous and electrolyte gradients become less extreme, and shift through the separator towards the nickel electrode. Similarly, flooding of areas in the gas screen cause higher concentrations of oxygen gas to approach the platinum/hydrogen electrode that is opposite the back side of the nickel electrode. These results illustrate the need for appropriate pore size distributions, and the maintenance of both convective electrolyte and gas flow paths through the stack, if the recirculating stack nickel hydrogen cell design is to work properly.
The temperature and capacity of individual cells affect the current distribution in a battery pack. Non uniform current distribution among parallel-connected cells can lead to capacity imbalance and premature aging. This paper develops models that calculate the current in parallel-connected cells and predict their capacity fade. The model is validated experimentally for a nonuniform battery pack at different temperatures. The paper also proposes and validates the hypothesis that temperature control can reduce capacity mismatch in parallel-connected cells. Three Lithium Iron Phosphate cells, two cells at higher initial capacity than the third cell, are connected in parallel. The pack is cycled for 1500 Hybrid Electric Vehicles cycles with the higher capacity cells regulated at 40 C and the lower capacity cell at 20 C. As predicted by the model, the higher capacity and temperature cells age faster, reducing the capacity mismatch by 48% over the 1500 cycles. A case study shows that cooling of low capacity cells can reduce capacity mismatch and extend pack life.
This paper presents the validation of an entire vehicle model of the Honda Accord Plug-in Hybrid Electric Vehicle (PHEV), which has a new powertrain system that can be driven in both series and parallel hybrid drive using a clutch, including thermal aspects. The Accord PHEV is a series-parallel PHEV with about 21 km of all-electric range and no multi-speed gearbox. Vehicle testing was performed at Argonne’s Advanced Powertrain Research Facility on a chassis dynamometer set in a thermal chamber. First, components (engine, battery, motors and wheels) were modeled using the test data and publicly available assumptions. This includes calibration of the thermal aspects, such as engine efficiency as a function of coolant temperature. In the second phase, the vehicle-level control strategy, especially the energy management, was analyzed in normal conditions in both charge-depleting and charge-sustaining modes. The third part examined how different thermal conditions such as environmental conditions (–7°C or 35°C with solar load) or vehicle state (soaked or warmed-up vehicle) affect the control strategy. Finally, the validation of the model implemented in Autonomie, a high-fidelity, forward-looking vehicle simulation tool, is presented. The fuel consumption figures are within the test-to-test variability, while many of the operation and control signals are also matched. Now that it has been validated, this model can be used for a wide range of simulations studies that include temperature as a parameter for the comparison and optimization of components, vehicle powertrain system, or control algorithm.
A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. Electrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.
A new method of studying the flow of the water along the bottom of a model of a flying-boat hull is described. In this method, the model is fitted with a transparent bottom and is divided down the center line by a bulkhead. The flow is observed and photographed through one-half of the model by means of the diffused illumination from a battery of lamps contained in the other half of the model. Photographs of the flow, particularly of the changes that occur when the step ventilates, are shown. The results of the present investigation indicate that the method has considerable promise, chiefly in connection with motion-picture studies.
Li-metal storage in three-dimensional (3D) electrodes is considered a potential dendrite-mitigation strategy. The large surface area and high porosity of these electrodes result in reduced local Li-plating current densities. The porous topology provides a scaffold for Li-deposition and stripping, maintaining both mechanical integrity and Li accessibility. The goal of this study is to understand how characteristics, such as geometry and material properties, affect the current distribution and deposition pattern. To this end, we developed a computational method to track material growth driven by electrodeposition within a complex geometry. This method ensures that the finite-element discretization remains conforming to the moving boundary while preserving an adequate mesh quality, and thus maintains solution accuracy. Using this new computational tool, we analyze the conditions under which porous anode architectures effectively expand the surface area of the charge-transfer interface, and self-regulate current density and dendrite growth.
RSR Technologies (RSRT) wished to investigate the use of the AMUSE solvent extraction code, housed at Argonne National Laboratory (ANL) to evaluate the recycling of battery cells for the reclamation of metal values. The modeling studies were undertaken by the group at ANL to evaluate several separation schemes for battery metals using solvent extraction. These studies would develop a framework to be experimentally validated at RSRT at its facility in Dallas, TX. The AMUSE code modeling work would speed the development of recovery flowsheets for spent batteries.
In the search for efficient energy storage battery technologies, designing stable electrolytes has been a long-standing challenge. Electrolytes based on molten salt eutectics are known for their stability with minimum parasitic reactions when compared to their widely used organic counterparts. However, the operating temperatures of these molten salt electrolyte-based batteries are dictated by the melting point of the eutectic mixtures. Design and high throughput screening of low melting temperature eutectic molten salt mixtures have been hindered by the lack of computational models. In this work, we develop thermodynamic models to predict the eutectic points of several molten salt mixtures. The framework of the COSMO-SAC model is used for the predictions and is compared with experimental data and other thermodynamic approaches. Rapid thermodynamics-based approaches, as shown in this study, can accelerate the discovery of new materials, complementing experimental techniques.