15 results found
Brosa Planella F, Ai W, Boyce AM, et al., 2022, A continuum of physics-based lithium-ion battery models reviewed, Progress in Energy, Vol: 4
Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complexity, is needed for different applications. For example, in battery design we can afford longer computational times and the use of powerful computers, while for real-time battery control (e.g. in electric vehicles) we need to perform very fast calculations using simple devices. For this reason, simplified models that retain most of the features at a lower computational cost are widely used. Even though in the literature we often find these simplified models posed independently, leading to inconsistencies between models, they can actually be derived from more complicated models using a unified and systematic framework. In this review, we showcase this reductive framework, starting from a high-fidelity microscale model and reducing it all the way down to the single particle model, deriving in the process other common models, such as the Doyle-Fuller-Newman model. We also provide a critical discussion on the advantages and shortcomings of each of the models, which can aid model selection for a particular application. Finally, we provide an overview of possible extensions to the models, with a special focus on thermal models. Any of these extensions could be incorporated into the microscale model and the reductive framework re-applied to lead to a new generation of simplified, multi-physics models.
Wang AA, OKane SEJ, Brosa Planella F, et al., 2022, Review of parameterisation and a novel database (LiionDB) for continuum Li-ion battery models, Progress in Energ, Vol: 4, Pages: 1-40, ISSN: 2516-1083
The Doyle–Fuller–Newman (DFN) framework is the most popular physics-based continuum-level description of the chemical and dynamical internal processes within operating lithium-ion-battery cells. With sufficient flexibility to model a wide range of battery designs and chemistries, the framework provides an effective balance between detail, needed to capture key microscopic mechanisms, and simplicity, needed to solve the governing equations at a relatively modest computational expense. Nevertheless, implementation requires values of numerous model parameters, whose ranges of applicability, estimation, and validation pose challenges. This article provides a critical review of the methods to measure or infer parameters for use within the isothermal DFN framework, discusses their advantages or disadvantages, and clarifies limitations attached to their practical application. Accompanying this discussion we provide a searchable database, available at www.liiondb.com, which aggregates many parameters and state functions for the standard DFN model that have been reported in the literature.
Trotta F, Wang GJ, Guo Z, et al., 2022, A Comparative Techno-Economic and Lifecycle Analysis of Biomass-Derived Anode Materials for Lithium- and Sodium-Ion Batteries, ADVANCED SUSTAINABLE SYSTEMS, Vol: 6, ISSN: 2366-7486
The transition to clean energy and electric mobility is driving unprecedented demand for lithium-ion batteries (LIBs). This paper investigates the safety and sustainability of LIBs, exploring ways of reducing their impact on the environment and ensuring they do not pose a danger to health of workers or users.
O'Kane SEJ, Ai W, Madabattula G, et al., 2022, Lithium-ion battery degradation: how to model it, Publisher: Royal Society of Chemistry
Predicting lithium-ion battery degradation is worth billions to the globalautomotive, aviation and energy storage industries, to improve performance andsafety and reduce warranty liabilities. However, very few published models ofbattery degradation explicitly consider the interactions between more than twodegradation mechanisms, and none do so within a single electrode. In thispaper, the first published attempt to directly couple more than two degradationmechanisms in the negative electrode is reported. The results are used to mapdifferent pathways through the complicated path dependent and non-lineardegradation space. Four degradation mechanisms are coupled in PyBaMM, an opensource modelling environment uniquely developed to allow new physics to beimplemented and explored quickly and easily. Crucially it is possible to see'inside' the model and observe the consequences of the different patterns ofdegradation, such as loss of lithium inventory and loss of active material. Forthe same cell, five different pathways that can result in end-of-life havealready been found, depending on how the cell is used. Such information wouldenable a product designer to either extend life or predict life based upon theusage pattern. However, parameterization of the degradation models remains as amajor challenge, and requires the attention of the international batterycommunity.
Morgan LM, Islam MM, Yang H, et al., 2022, From Atoms to Cells: Multiscale Modeling of a LiNixMnyCozO2 Cathodes for Li-Ion Batteries, ACS ENERGY LETTERS, Vol: 7, Pages: 108-122, ISSN: 2380-8195
Morgan LM, Mercer MP, Bhandari A, et al., 2022, Pushing the boundaries of lithium battery research with atomistic modelling on different scales, Progress in Energy, Vol: 4
Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.
Lander L, Cleaver T, Rajaeifar MA, et al., 2021, Financial viability of electric vehicle lithium-ion battery recycling, ISCIENCE, Vol: 24
Lander L, Kallitsis E, Hales A, et al., 2021, Cost and carbon footprint reduction of electric vehicle lithium-ion batteries through efficient thermal management, Applied Energy, Vol: 289, Pages: 1-10, ISSN: 0306-2619
Electric vehicles using lithium-ion batteries are currently the most promising technology to decarbonise the transport sector from fossil-fuels. It is thus imperative to reduce battery life cycle costs and greenhouse gas emissions to make this transition both economically and environmentally beneficial. In this study, it is shown that battery lifetime extension through effective thermal management significantly decreases the battery life cycle cost and carbon footprint. The battery lifetime simulated for each thermal management system is implemented in techno-economic and life cycle assessment models to calculate the life cycle costs and carbon footprint for the production and use phase of an electric vehicles. It is demonstrated that by optimising the battery thermal management system, the battery life cycle cost and carbon footprint can be reduced by 27% (from 0.22 $·km−1 for air cooling to 0.16 $·km−1 for surface cooling) and 25% (from 0.141 kg CO2 eq·km−1 to 0.104 kg CO2 eq·km−1), respectively. Moreover, the importance of cell design for cost and environmental impact are revealed and an improved cell design is proposed, which reduces the carbon footprint and life cycle cost by 35% to 0.0913 kg CO2 eq·km−1 and 40% to 0.133 $·km−1, respectively, compared with conventional cell designs combined with air cooling systems.
Edge JS, O'Kane S, Prosser R, et al., 2021, Lithium ion battery degradation: what you need to know, Physical Chemistry Chemical Physics, Vol: 23, Pages: 8200-8221, ISSN: 1463-9076
The expansion of lithium-ion batteries from consumer electronics to larger-scale transport and energy storage applications has made understanding the many mechanisms responsible for battery degradation increasingly important. The literature in this complex topic has grown considerably; this perspective aims to distil current knowledge into a succinct form, as a reference and a guide to understanding battery degradation. Unlike other reviews, this work emphasises the coupling between the different mechanisms and the different physical and chemical approaches used to trigger, identify and monitor various mechanisms, as well as the various computational models that attempt to simulate these interactions. Degradation is separated into three levels: the actual mechanisms themselves, the observable consequences at cell level called modes and the operational effects such as capacity or power fade. Five principal and thirteen secondary mechanisms were found that are generally considered to be the cause of degradation during normal operation, which all give rise to five observable modes. A flowchart illustrates the different feedback loops that couple the various forms of degradation, whilst a table is presented to highlight the experimental conditions that are most likely to trigger specific degradation mechanisms. Together, they provide a powerful guide to designing experiments or models for investigating battery degradation.
Chitre A, Freake D, Lander L, et al., 2020, Towards a More Sustainable Lithium-Ion Battery Future: Recycling LIBs from Electric Vehicles, BATTERIES & SUPERCAPS, Vol: 3, Pages: 1124-1125
Chitre A, Freake D, Lander L, et al., 2020, Towards a more sustainable lithium-ion battery future: recycling LIBs from eectric vehicles, Batteries & Supercaps, Vol: 3, Pages: 1126-1136, ISSN: 2566-6223
With the number of electric vehicles (EVs) projected to increase 25-fold by 2030, effective recycling processes need to be developed to conserve the critical raw materials (in particular, cobalt and lithium) used to make lithium-ion batteries (LIBs). Industrial recycling of LIBs is underdeveloped due to two main reasons: i) complex and particularly variable cathodic chemistries; ii) physically different shapes and sizes of battery packs which are not designed for easy disassembly. Present processes use pyrometallurgical and/or hydrometallurgical recycling methods, with the latter being widely seen as the future in view of changing battery chemistries to lower cobalt contents. As such, this paper focuses on improvements, including sorting of batteries and using alternative water-soluble binders, to enhance LIB material recovery from hydrometallurgical processes. This review promotes the adoption of a holistic design approach for LIBs that includes ease of end-of-life recyclability.
Hanna RF, Gazis E, Edge J, et al., 2018, Unlocking the potential of Energy Systems Integration: An Energy Futures Lab Briefing Paper, Publisher: Energy Futures Lab
Energy Systems Integration’s (ESI) underlying concept is the coordination, and integration, of energy generation and use at local, regional and national levels. This relates to all aspects of energy from production and conversion to delivery and end use. Building such a system is potentially a cost-effective way to decarbonise our energy sector and produce a more reliable and resilient system. This Briefing Paper investigates how the UK can link heat, transport, electricity and other energy vectors into one interconnected ecosystem. It lays out the immense opportunities of having an interconnected and integrated energy ecosystem and the technologies that could make it a reality. Among these is enabling variable renewable electricity and lower-carbon fuels to provide energy services traditionally provided by higher-carbon sources. This could be realised through a more resilient system incorporating greater flexibility and more diverse energy sources.
Edge JS, Skipper NT, Fernandez-Alonso F, et al., 2014, Structure and Dynamics of Molecular Hydrogen in the Interlayer Pores of a Swelling 2:1 Clay by Neutron Scattering, The Journal of Physical Chemistry C, Vol: 118, Pages: 25740-25747, ISSN: 1932-7447
Edge J, 2014, HYDROGEN ADSORPTION AND DYNAMICS IN CLAY MINERALS
A new class of hydrogen storage material (HSM), the swelling clay minerals, is introduced by the investigation of laponite, a representative smectite. Simple ion exchange allows for a diverse range of charged species to be studied as possible adsorption sites for H2 within the laponite interlayer, while a sub-monolayer of water pillars the interlayers apart by 2.85 Å, close to the kinetic diameter of H2. Neutron diffraction shows that the 001 peak, representing the clay d-spacing, is directly affected by the introduction of H2 or D2, confirming intercalation into the interlayers.Volumetric adsorption isotherms and neutron scattering show that laponites with 3 wt% H2O rapidly physisorb 0.5-1 wt% H2 at 77 K and 80 bar, with low binding enthalpies (3.40-8.74 kJ mol-1) and consequently low room temperature uptake (0.1 wt% at 100 bar). The higher structural density of clays results in lower H2 densities than MOFs and activated carbons, however some cation-exchanged forms, such as Mg and Cs, show promise for improvement having capacities of 22.8 g H2 per litre at 77K, 80 bar, intermediate between AX-21 and IRMOF-20. At low coverage, INS spectra reveal up to five adsorption sites with low rotational energy barriers (0.7-4.8 kJ mol-1), persisting up to at least 50 K. Analysis of quasielastic neutron scattering (QENS) spectra for Ca-laponite expanded with 3 wt% H2O reveals two populations of interlayer H2: one immobile up to 100 K and localised to the Ca2+ cations, while the other diffuses by jump diffusion at a rate of 1.93 0.23 Å2 ps-1 at 80 K, 60% slower than in the bulk (Dbulk = 4.90 0.84 Å2 ps-1). Arrhenius analysis gives activation energies of 188 28 K for the calcium and 120 32 K for the sodium form, comparable to the range for activated carbons. The adsorbate phase density of H2 in laponite interlayers at 40 K is 67.08 kg m-3, close to the bulk liquid density of 70.6 kg m-3.Jump lengths of 3.2 0.4 Å for Ca-laponite measured by QENS at 40 K are
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.