73 results found
Chakrabarti BK, Kalamaras E, Ouyang M, et al., 2021, Trichome-like Carbon-Metal Fabrics Made of Carbon Microfibers, Carbon Nanotubes, and Fe-Based Nanoparticles as Electrodes for Regenerative Hydrogen/Vanadium Flow Cells, ACS APPLIED NANO MATERIALS, Vol: 4, Pages: 10754-10763, ISSN: 2574-0970
Tomaszewska A, Parkes M, Doel R, et al., 2021, Lithium Plating Heterogeneity Caused by Realistic Thermal Gradients, ECS Meeting Abstracts, Vol: MA2021-02, Pages: 460-460
Yang S, Zhang Z, Cao R, et al., 2021, Implementation for a cloud battery management system based on the CHAIN framework, Energy and AI, Vol: 5, Pages: 100088-100088, ISSN: 2666-5468
An intelligent battery management system is a crucial enabler for energy storage systems with high power output, increased safety and long lifetimes. With recent developments in cloud computing and the proliferation of big data, machine learning approaches have begun to deliver invaluable insights, which drives adaptive control of battery management systems (BMS) with improved performance. In this paper, a general framework utilizing an end-edge-cloud architecture for a cloud-based BMS is proposed, with the composition and function of each link described. Cloud-based BMS leverages from the Cyber Hierarchy and Interactional Network (CHAIN) framework to provide multi-scale insights, more advanced and efficient algorithms can be used to realize the state-of-X estimation, thermal management, cell balancing, fault diagnosis and other functions of traditional BMS system. The battery intelligent monitoring and management platform can visually present battery performance, store working-data to help in-depth understanding of the microscopic evolutionary law, and provide support for the development of control strategies. Currently, the cloud-based BMS requires more effects on the multi-scale integrated modeling methods and remote upgrading capability of the controller, these two aspects are very important for the precise management and online upgrade of the system. The utility of this approach is highlighted not only for automotive applications, but for any battery energy storage system, providing a holistic framework for future intelligent and connected battery management.
Schimpe M, Varela Barreras J, Wu B, et al., 2021, Battery degradation-aware current derating: an effective method to prolong lifetime and ease thermal management, Journal of The Electrochemical Society, Vol: 168, Pages: 1-13, ISSN: 0013-4651
To ensure the safe and stable operation of lithium-ion batteries in battery energy storage systems (BESS), the power/current is de-rated to prevent the battery from going outside the safe operating range. Most derating strategies use static limits for battery current, voltage, temperature and state-of-charge, and do not account for the complexity of battery degradation. Progress has been made with models of lithium plating for fast charging. However, this is a partial solution, does not consider other degradation mechanisms, and still requires complex optimization work, limiting widespread adoption. In this work, the calendar and cycle degradation model is analysed offline to predetermine the degradation rates. The results are integrated into the current-derating strategy. This framework can be adapted to any degradation model and allows flexible tuning. The framework is evaluated in simulations of an outdoors-installed BESS with passive thermal management, which operates in a residential photovoltaic application. In comparison to standard derating, the degradation-aware derating achieves: (1) increase of battery lifetime by 65%; (2) increase in energy throughput over lifetime by 49%, while III) energy throughput per year is reduced by only 9.5%. These results suggest that the derating framework can become a new standard in current derating.
Ojha M, Wu B, Deepa M, 2021, Cost-Effective MIL-53(Cr) metal–organic framework-based supercapacitors encompassing fast-ion (Li+/H+/Na+) conductors, ACS Applied Energy Materials, Vol: 4, Pages: 4729-4743, ISSN: 2574-0962
A chromium-based low-cost metal–organic framework (MOF) cathode, MIL (Matériaux de l′Institut Lavoisier)-53(Cr), is coupled with a bioderived porous carbon (BPC) anode, produced from abundantly available agricultural waste betel nut shells in an asymmetric supercapacitor, for the first time. The impact of the electrolyte on the electrochemical behavior of an asymmetric BPC//MIL-53(Cr) supercapacitor was assessed by constructing cells with the following electrolytes: proton-conducting camphorsulfonic acid (CSA), Li+-ion-conducting solutions of LiClO4, Na+-ion-conducting sodium poly(4-styrene sulfonate) solution, and ionic liquid (IL:1-butyl-1-methyl-pyrrolidinium trifluoromethanesulfonate)-based solutions. The aqueous H+-ion-based CSA electrolyte shows a superior ionic conductivity (270 mS cm–1) and an enhanced transport number (0.96), carries larger ionic currents, and retains high conductivity even at subambient temperatures, clearly outperforming all the other Li+/Na+/IL electrolytes. The BPC/aqueous CSA or LiClO4/MIL-53(Cr) supercapacitors show enhanced storage performances, with the H+ cell having a specific capacitance of 70 F g–1 and energy and power density maxima of 9.7 Wh kg–1 and 0.25 kW kg–1 and enduring 104 cycles. A detailed account of the dependence of the electrolyte cation/anion- and solvent-type on electrochemical charge storage provides a basis for adapting these design principles to developing high-performance MOF-based supercapacitors.
Ouyang M, Bertei A, Cooper SJ, et al., 2021, Model-guided design of a high performance and durability Ni nanofiber/ceria matrix solid oxide fuel cell electrode, Journal of Energy Chemistry, Vol: 56, Pages: 98-112, ISSN: 2095-4956
Mixed ionic electronic conductors (MIECs) have attracted increasing attention as anode materials for solid oxide fuel cells (SOFCs) and they hold great promise for lowering the operation temperature of SOFCs. However, there has been a lack of understanding of the performance-limiting factors and guidelines for rational design of composite metal-MIEC electrodes. Using a newly-developed approach based on 3D-tomography and electrochemical impedance spectroscopy, here for the first time we quantify the contribution of the dual-phase boundary (DPB) relative to the three-phase boundary (TPB) reaction pathway on real MIEC electrodes. A new design strategy is developed for Ni/gadolinium doped ceria (CGO) electrodes (a typical MIEC electrode) based on the quantitative analyses and a novel Ni/CGO fiber–matrix structure is proposed and fabricated by combining electrospinning and tape-casting methods using commercial powders. With only 11.5 vol% nickel, the designer Ni/CGO fiber–matrix electrode shows 32% and 67% lower polarization resistance than a nano-Ni impregnated CGO scaffold electrode and conventional cermet electrode respectively. The results in this paper demonstrate quantitatively using real electrode structures that enhancing DPB and hydrogen kinetics are more efficient strategies to enhance electrode performance than simply increasing TPB.
Niu Z, Pinfield V, Wu B, et al., 2021, Towards the digitalisation of porous energy materials: evolution of digital approaches for microstructural design, Energy and Environmental Science, Vol: 14, Pages: 2549-2576, ISSN: 1754-5692
Porous energy materials are essential components of many energy devices and systems, the development of which have been long plagued by two main challenges. The first is the ‘curse of dimensionality’, i.e. the complex structure–property relationships of energy materials are largely determined by a high-dimensional parameter space. The second challenge is the low efficiency of optimisation/discovery techniques for new energy materials. Digitalisation of porous energy materials is currently being considered as one of the most promising solutions to tackle these issues by transforming all material information into the digital space using reconstruction and imaging data and fusing this with various computational methods. With the help of material digitalisation, the rapid characterisation, the prediction of properties, and the autonomous optimisation of new energy materials can be achieved by using advanced mathematical algorithms. In this paper, we review the evolution of these computational and digital approaches and their typical applications in studying various porous energy materials and devices. Particularly, we address the recent progress of artificial intelligence (AI) in porous energy materials and highlight the successful application of several deep learning methods in microstructural reconstruction and generation, property prediction, and the performance optimisation of energy materials in service. We also provide a perspective on the potential of deep learning methods in achieving autonomous optimisation and discovery of new porous energy materials based on advanced computational modelling and AI techniques.
Gao X, Liu X, He R, et al., 2021, Designed high-performance lithium-ion battery electrodes using a novel hybrid model-data driven approach, Energy Storage Materials, Vol: 36, Pages: 435-458, ISSN: 2405-8297
Lithium-ion batteries (LIBs) have been widely recognized as the most promising energy storage technology due to their favorable power and energy densities for applications in electric vehicles (EVs) and other related functions. However, further improvements are needed which are underpinned by advances in conventional electrode designs. This paper reviews conventional and emerging electrode designs, including conventional LIB electrode modification techniques and electrode design for next-generation energy devices. Thick electrode designs with low tortuosity are the most conventional approach for energy density improvement. Chemistries such as lithium-sulfur, lithium-air and solid-state batteries show great potential, yet many challenges remain. Microscale structural modelling and macroscale functional modelling methods underpin much of the electrode design work and these efforts are summarized here. More importantly, this paper presents a novel framework for next-generation electrode design termed: Cyber Hierarchy And Interactional Network based Multiscale Electrode Design (CHAIN-MED), a hybrid solution combining model-based and data-driven techniques for optimal electrode design, which significantly shortens the development cycle. This review, therefore, provides novel insights into combining existing design approaches with multiscale models and machine learning techniques for next-generation LIB electrodes.
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.
Yang S, Zhou S, Hua Y, et al., 2021, A parameter adaptive method for state of charge estimation of lithium-ion batteries with an improved extended Kalman filter., Scientific Reports, Vol: 11, Pages: 1-15, ISSN: 2045-2322
An accurate state of charge (SOC) estimation in battery management systems (BMS) is of crucial importance to guarantee the safe and effective operation of automotive batteries. However, the BMS consistently suffers from inaccuracy of SOC estimation. Herein, we propose a SOC estimation approach with both high accuracy and robustness based on an improved extended Kalman filter (IEKF). An equivalent circuit model is established, and the simulated annealing-particle swarm optimization (SA-PSO) algorithm is used for offline parameter identification. Furthermore, improvements have been made with noise adaptation, a fading filter and a linear-nonlinear filtering based on the traditional EKF method, and rigorous mathematical proof has been carried out accordingly. To deal with model mismatch, online parameter identification is achieved by a dual Kalman filter. Finally, various experiments are performed to validate the proposed IEKF. Experimental results show that the IEKF algorithm can reduce the error to 2.94% under dynamic stress test conditions, and robustness analysis is verified with noise interference, hence demonstrating its practicability for extending to state estimation of battery packs applied in real-world operating conditions.
Ojha M, Liu X, Wu B, et al., 2021, Holey graphitic carbon nano-flakes with enhanced storage characteristics scaled to a pouch cell supercapacitor, Fuel, Vol: 285, Pages: 1-12, ISSN: 0016-2361
Supercapacitors with holey graphitic carbon nano-flakes (HGCNF) capable of demonstrating large specific capacitance (SC) have been developed for the first time. The unique approach of applying an additional conducting layer of carbon fabric (CF) coated with HGCNF at both half-cells provides a significant enhancement in SC, from 323 to 1142 F g−1, for the half cell and from 8 to 487 F g−1 for the symmetric supercapacitor, when the architecture is modified from Ni/HGCNF//HGCNF/Ni to Ni/HGCNF/CF/HGCNF//HGCNF/CF/HGCNF/Ni. HGCNF is composed of macro- and meso- pores enabling facile and deep penetration of electrolyte ions across the cross-section, ensuring maximum utilization at high current densities. Peak energy and power densities of 68 Wh kg−1 and 2.5 kW kg−1, achieved for the Ni/HGCNF/CF/HGCNF//HGCNF/CF/HGCNF/Ni cell, are superior to many reported nano-carbons, including HGCNF/Ni or HGCNF/CF symmetric cells. The corresponding 3 V pouch cell, showed an excellent SC of 80 F g−1.
Luo X, Varela Barreras J, Chambon C, et al., 2021, Hybridizing Lead-Acid Batteries with Supercapacitors: A Methodology, Energies, Vol: 14, ISSN: 1996-1073
Hybridizing a lead–acid battery energy storage system (ESS) with supercapacitors is a promising solution to cope with the increased battery degradation in standalone microgrids that suffer from irregular electricity profiles. There are many studies in the literature on such hybrid energy storage systems (HESS), usually examining the various hybridization aspects separately. This paper provides a holistic look at the design of an HESS. A new control scheme is proposed that applies power filtering to smooth out the battery profile, while strictly adhering to the supercapacitors’ voltage limits. A new lead–acid battery model is introduced, which accounts for the combined effects of a microcycle’s depth of discharge (DoD) and battery temperature, usually considered separately in the literature. Furthermore, a sensitivity analysis on the thermal parameters and an economic analysis were performed using a 90-day electricity profile from an actual DC microgrid in India to infer the hybridization benefit. The results show that the hybridization is beneficial mainly at poor thermal conditions and highlight the need for a battery degradation model that considers both the DoD effect with microcycle resolution and temperate impact to accurately assess the gain from such a hybridization.
Pang MC, Yang K, Brugge R, et al., 2021, Interactions are important: Linking multi-physics mechanisms to the performance and degradation of solid-state batteries, Materials Today, ISSN: 1369-7021
The behavior of solid-state batteries to many application-relevant operating conditions is intrinsically multiphysical and multiscale, involving the electrochemical performance and chemical stability coupled with the thermal and mechanical properties of multiple components. This review presents a holistic approach to discussing the multiscale physical-electro-chemical interactions and degradation mechanisms in solid-state batteries. While the propagation of lithium filaments depends strongly on the critical current densities, we show that effective prevention of excessive Li plating and stripping requires a combined understanding of solid-state electrochemistry, microstructure, mechanics, operating conditions, and their interactions. A review of how multiphysical interactions affect the optimum design of thin-film, three-dimensional and composite solid-state cell architectures is also included. Although the use of lithium metal as negative electrodes could improve the energy densities of solid-state batteries, we show that its high homologous temperature could cause cell failure during manufacturing. By comparing published model predictions with experimental observations, we present a critical analysis of the strengths and limitations of state-of-the-art models and characterization techniques in solid-state battery research. This comprehensive mechanistic analysis provides an insight into the interplay among the multiple complex multiphysical mechanisms, shedding light on the process of cell design for next-generation solid-state batteries.
Liu X, Qian X, Tang W, et al., 2021, Designer uniform Li plating/stripping through lithium–cobalt alloying hierarchical scaffolds for scalable high-performance lithium-metal anodes, Journal of Energy Chemistry, Vol: 52, Pages: 385-392, ISSN: 2095-4956
Lithium metal anodes are of great interest for advanced high-energy density batteries such as lithium-air, lithium-sulfur and solid-state batteries, due to their low electrode potential and ultra-high theoretical capacity. There are, however, several challenges limiting their practical applications, which include low coulombic efficiency, the uncontrollable growth of dendrites and poor rate capability. Here, a rational design of 3D structured lithium metal anodes comprising of in-situ growth of cobalt-decorated nitrogen-doped carbon nanotubes on continuous carbon nanofibers is demonstrated via electrospinning. The porous and free-standing scaffold can enhance the tolerance to stresses resulting from the intrinsic volume change during Li plating/stripping, delivering a significant boost in both charge/discharge rates and stable cycling performance. A binary Co-Li alloying phase was generated at the initial discharge process, creating more active sites for the Li nucleation and uniform deposition. Characterization and density functional theory calculations show that the conductive and uniformly distributed cobalt-decorated carbon nanotubes with hierarchical structure can effectively reduce the local current density and more easily absorb Li atoms, leading to more uniform Li nucleation during plating. The current work presents an advance on scalable and cost-effective strategies for novel electrode materials with 3D hierarchical microstructures and mechanical flexibility for lithium metal anodes.
Sowe J, Few S, Varela Barreras J, et al., 2020, How Can Insights from Degradation Modelling Inform Operational Strategies to Increase the Lifetime of Li-Ion Batteries in Islanded Mini-Grids?, ECS Meeting Abstracts, Vol: MA2020-02, Pages: 3780-3780
Schimpe M, Barreras JV, Wu B, et al., 2020, Novel Degradation Model-Based Current Derating Strategy for Lithium-Ion-Batteries, Publisher: The Electrochemical Society, Pages: 3808-3808
Lai C, Liu X, Wang Y, et al., 2020, Bimetallic organic framework-derived rich pyridinic N-doped carbon nanotubes as oxygen catalysts for rechargeable Zn-air batteries, Journal of Power Sources, Vol: 472, Pages: 1-8, ISSN: 0378-7753
Developing of low-cost and high-performance electrocatalysts provides a promising method to alleviate the burden of noble metals for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). The oxygen catalysts play an increasingly greater role in expanding the energy conversion efficiencies of rechargeable Zn-air batteries. Metal organic frameworks (MOFs) have greatly noticed as versatile precursors to design and establish highly efficient bifunctional catalysts owing to their adjustable component, flexible tailing capability and high surface area. Herein, a highly active OER/ORR catalyst was synthesized by a facile metal induction pyrolysis strategy using bimetallic NiCo-ZIF-67 as precursor, obtaining a special characteristics with high pyridinic N doping level (~42.6%) and ultrafine metal nanocrystals embedded in carbon nanotubes. The as-prepared Ni1Co3@N-CNTs demonstrates a moderate OER activity with a low overpotential of only ~290 mV at 10 mA cm−2 and a low Tafel slop of 56 mV dec−1. Meanwhile, it reaches a much higher half-wave potential of 0.85 V for ORR, which could rival the most of reported materials. Importantly, when being applied as oxygen catalyst in rechargeable Zn-air batteries, decent electrochemical performance of open-circuit potential and high power density were achieved, even superior than those of the commercial Pt/C and RuO2 electrode.
Ojha M, Wu B, Deepa M, 2020, NiCo metal–organic framework and porous carbon interlayer-based supercapacitors integrated with a solar cell for a stand-alone power supply system, ACS Applied Materials and Interfaces, Vol: 12, Pages: 42749-42762, ISSN: 1944-8244
Nickel cobalt-metal–organic framework (NiCo-MOF), with a semihollow spherical morphology composed of rhombic dodecahedron nanostructures, was synthesized using a scalable and facile wet chemical route. Such a structure endowed the material with open pores, which enabled rapid ion ingress and egress, and the high effective surface area of the MOF allowed the uptake and release of a large number of electrolyte ions during charge–discharge. By combining this NiCo-MOF cathode with a highly porous carbon (PC) anode (derived from the naturally grown and abundantly available bio-waste, namely, palm kernel shells), the resulting PC//NiCo-MOF supercapacitor using an aqueous potassium hydroxide (KOH) electrolyte delivered a capacitance of 134 F g–1, energy and power densities of 24 Wh kg–1 and 0.8 kW kg–1 at 1 A g–1, respectively, over an operational voltage window of 1.6 V. By employing thin interlayers of PC coated over a Whatman filter paper (PC@FP), the modified supercapacitor configuration of PC/PC@FP//PC@FP/NiCo-MOF delivered greatly enhanced performance. This cell delivered a capacitance of 520 F g–1 and an energy density of 92 Wh kg–1, improved by nearly 4-fold, compared to the analogous supercapacitor without the interlayers (at the same power and current densities and voltage window), thus evidencing the role of the cost-effective, electrically conducting porous carbon interlayers in amplifying the supercapacitor’s energy storage capabilities. Further, illumination of white light-emitting diodes (LEDs) using a three-series configuration and the photocharging of this supercapacitor with a solution-processed solar cell are also demonstrated. The latter confirms its ability to function as a stand-alone power supply system for electronic/computing devices, which can even operate under medium lighting conditions.
Liu X, Ouyang M, Orzech M, et al., 2020, In-situ fabrication of carbon-metal fabrics as freestanding electrodes for high-performance flexible energy storage devices, Energy Storage Materials, Vol: 30, Pages: 329-336, ISSN: 2405-8297
Hierarchical 1D carbon structures are attractive due to their mechanical, chemical and electrochemical properties however the synthesis of these materials can be costly and complicated. Here, through the combination of inexpensive acetylacetonate salts of Ni, Co and Fe with a solution of polyacrylonitrile (PAN), self-assembling carbon-metal fabrics (CMFs) containing unique 1D hierarchical structures can be created via easy and low-cost heat treatment without the need for costly catalyst deposition nor a dangerous hydrocarbon atmosphere. Microscopic and spectroscopic measurements show that the CMFs form through the decomposition and exsolution of metal nanoparticle domains which then catalyze the formation of carbon nanotubes through the decomposition by-products of the PAN. These weakly bound nanoparticles form structures similar to trichomes found in plants, with a combination of base-growth, tip-growth and peapod-like structures, where the metal domain exhibits a core(graphitic)-shell(disorder) carbon coating where the thickness is in-line with the metal-carbon binding energy. These CMFs were used as a cathode in a flexible zinc-air battery which exhibited superior performance to pure electrospun carbon fibers, with their metallic nanoparticle domains acting as bifunctional catalysts. This work therefore unlocks a potentially new category of composite metal-carbon fiber based structures for energy storage applications and beyond.
Wu B, Widanage WD, Yang S, et al., 2020, Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems, Energy and AI, Vol: 1, Pages: 1-12, ISSN: 2666-5468
Effective management of lithium-ion batteries is a key enabler for a low carbon future, with applications including electric vehicles and grid scale energy storage. The lifetime of these devices depends greatly on the materials used, the system design and the operating conditions. This complexity has therefore made real-world control of battery systems challenging. However, with the recent advances in understanding battery degradation, modelling tools and diagnostics, there is an opportunity to fuse this knowledge with emerging machine learning techniques towards creating a battery digital twin. In this cyber-physical system, there is a close interaction between a physical and digital embodiment of a battery, which enables smarter control and longer lifetime. This perspectives paper thus presents the state-of-the-art in battery modelling, in-vehicle diagnostic tools, data driven modelling approaches, and how these elements can be combined in a framework for creating a battery digital twin. The challenges, emerging techniques and perspective comments provided here, will enable scientists and engineers from industry and academia with a framework towards more intelligent and interconnected battery management in the future.
Chakrabarti BK, Kalamaras E, Singh AK, et al., 2020, Modelling of redox flow battery electrode processes at a range of length scales: a review, Sustainable Energy and Fuels, Vol: 4, Pages: 5433-5468, ISSN: 2398-4902
In this article, the different approaches reported in the literature for modelling electrode processes in redox flow batteries (RFBs) are reviewed. RFB models vary widely in terms of computational complexity, research scalability and accuracy of predictions. Development of RFB models have been quite slow in the past, but in recent years researchers have reported on a range of modelling approaches for RFB system optimisation. Flow and transport processes, and their influence on electron transfer kinetics, play an important role in the performance of RFBs. Macro-scale modelling, typically based on a continuum approach for porous electrode modelling, have been used to investigate current distribution, to optimise cell design and to support techno-economic analyses. Microscale models have also been developed to investigate the transport properties within porous electrode materials. These microscale models exploit experimental tomographic techniques to characterise three-dimensional structures of different electrode materials. New insights into the effect of the electrode structure on transport processes are being provided from these new approaches. Modelling flow, transport, electrical and electrochemical processes within the electrode structure is a developing area of research, and there are significant variations in the model requirements for different redox systems, in particular for multiphase chemistries (gas–liquid, solid–liquid, etc.) and for aqueous and non-aqueous solvents. Further development is essential to better understand the kinetic and mass transport phenomena in the porous electrodes, and multiscale approaches are also needed to enable optimisation across the relevent length scales.
Pan Y-W, Hua Y, Zhou S, et al., 2020, A computational multi-node electro-thermal model for large prismatic lithium-ion batteries, Journal of Power Sources, Vol: 459, ISSN: 0378-7753
During operation of large prismatic lithium-ion batteries, temperature heterogeneities are aggravated which affect the performance, lifetime and safety of the cells and packs. Therefore, an accurate model to predict the evolution of temperature profiles in a cell is essential for effective thermal management. In this paper, a pseudo 3D coupled multi-node electro-thermal model is presented for real-time prediction of the heterogeneous temperature field evolution on the surface and inside the battery. The model consists of two parts: a heat generation model based on a second-order equivalent-circuit model and a multi-node heat transfer model based on the battery geometry. Three types of nodes are adopted to describe the thermal characteristics of various components of the cell. Simulation results show that the proposed model has a great consistency with finite element method, and its computational cost is reduced by 90%. The validity of the coupled electrical and thermal model is also demonstrated experimentally for a 105 Ah prismatic cell applying wide ranges of temperature and SOC. The maximum error is less than 2 K throughout the cycles. The proposed model holds a great potential for online temperature estimation in advanced lithium-ion battery thermal management system design.
Madabattula G, Wu B, Marinescu M, et al., 2020, Degradation diagnostics for Li4Ti5O12-based lithium ion capacitors: insights from a physics-based model, Journal of The Electrochemical Society, Vol: 167, ISSN: 0013-4651
Lithium ion capacitors are an important energy storage technology, providing the optimum combination of power, energy and cycle life for high power applications. However, there has been minimal work on understanding how they degrade and how this should influence their design. In this work, a 1D electrochemical model of a lithium ion capacitor with activated carbon (AC) as the positive electrode and lithium titanium oxide (LTO) as the negative electrode is used to simulate the consequences of different degradation mechanisms in order to explore how the capacity ratio of the two electrodes affects degradation. The model is used to identify and differentiate capacity loss due to loss of active material (LAM) in the lithiated and de-lithiated state and loss of lithium inventory (LLI). The model shows that, with lower capacity ratios (AC/LTO), LAM in the de-lithiated state cannot be identified as the excess LTO in the cell balances the capacity loss. Cells with balanced electrode capacity ratios are therefore necessary to differentiate LAM in lithiated and de-lithiated states and LLI from each other. We also propose in situ diagnostic techniques which will be useful to optimize a LIC's design. The model, built in COMSOL, is available online.
Yang K, Jia L, Liu X, et al., 2020, Revealing the anion intercalation behavior and surface evolution of graphite in dual-ion batteries via in situ AFM, Nano Research, Vol: 13, Pages: 412-418, ISSN: 1998-0124
Graphite as a positive electrode material of dual ion batteries (DIBs) has attracted tremendous attentions for its advantages including low lost, high working voltage and high energy density. However, very few literatures regarding to the real-time observation of anion intercalation behavior and surface evolution of graphite in DIBs have been reported. Herein, we use in situ atomic force microscope (AFM) to directly observe the intercalation/de-intercalation processes of PF6− in graphite in real time. First, by measuring the change in the distance between graphene layers during intercalation, we found that PF6− intercalates in one of every three graphite layers and the intercalation speed is measured to be 2 µm·min−1. Second, graphite will wrinkle and suffer structural damages at high voltages, along with severe electrolyte decomposition on the surface. These findings provide useful information for further optimizing the capacity and the stability of graphite anode in DIBs.
Madabattula G, Wu B, Marinescu M, et al., 2020, How to design lithium ion capacitors: modelling, mass ratio ofelectrodes and pre-lithiation, Journal of The Electrochemical Society, Vol: 167, ISSN: 0013-4651
Lithium ion capacitors (LICs) store energy using double layer capacitance at the positive electrode and intercalation at the negative electrode. LICs offer the optimum power and energy density with longer cycle life for applications requiring short pulses of high power. However, the effect of electrode balancing and pre-lithiation on usable energy is rarely studied. In this work, a set of guidelines for optimum design of LICs with activated carbon (AC) as positive electrode and lithium titanium oxide (LTO) as negative electrode was proposed. A physics-based model has been developed and used to study the relationship between usable energy at different effective C rates and the mass ratio of the electrodes. The model was validated against experimental data from literature. The model was then extended to analyze the need for pre-lithiation of LTO. The limits for pre-lithiation in LTO and use of negative polarization of the AC electrode to improve the cell capacity have been analyzed using the model. Furthermore, the model was used to relate the electrolyte depletion effects to poorer power performance in a cell with higher mass ratio. The open-source model can be re-parameterised for other LIC electrode combinations, and should be of interest to cell designers.
Ai W, Kraft L, Sturm J, et al., 2020, Electrochemical thermal-mechanical modelling of stress inhomogeneity in lithium-ion pouch cells, Journal of The Electrochemical Society, Vol: 167, ISSN: 0013-4651
Whilst extensive research has been conducted on the effects of temperature in lithium-ion batteries, mechanical effects have not received as much attention despite their importance. In this work, the stress response in electrode particles is investigated through a pseudo-2D model with mechanically coupled diffusion physics. This model can predict the voltage, temperature and thickness change for a lithium cobalt oxide-graphite pouch cell agreeing well with experimental results. Simulations show that the stress level is overestimated by up to 50% using the standard pseudo-2D model (without stress enhanced diffusion), and stresses can accelerate the diffusion in solid phases and increase the discharge cell capacity by 5.4%. The evolution of stresses inside electrode particles and the stress inhomogeneity through the battery electrode have been illustrated. The stress level is determined by the gradients of lithium concentration, and large stresses are generated at the electrode-separator interface when high C-rates are applied, e.g. fast charging. The results can explain the experimental results of particle fragmentation close to the separator and provide novel insights to understand the local aging behaviors of battery cells and to inform improved battery control algorithms for longer lifetimes.
Madabattula G, Wu B, Marinescu M, et al., 2019, 1D Electrochemical Model for Lithium Ion Capacitors in Comsol
Lithium ion capacitor is an electrochemical energy storage device with optimum energy density, power density and longer cycle life. A 1D-electrochemical model for activated carbon (AC)/ lithium titanium oxide (LTO) based lithium ion capacitor was built in COMSOL multiphyisics, v5.3a. The model was used to generate the data in an open-access paper: How to Design Lithium Ion Capacitor: Modelling, Mass Ratio of Electrodes and Pre-lithiation, Journal of The Electrochemical Society, 2020, 167. (http://jes.ecsdl.org/content/167/1/013527.abstract) The model can be used to optimize the mass ratio of electrodes and pre-lithiation level. It can be extended to study the capacity fade in the devices.
Chen X, Liu X, Ouyang M, et al., 2019, Multi-metal 4D printing with a desktop electrochemical 3D printer, Scientific Reports, Vol: 9, ISSN: 2045-2322
4D printing has the potential to create complex 3D geometries which are able to react to environmental stimuli opening new design possibilities. However, the vast majority of 4D printing approaches use polymer based materials, which limits the operational temperature. Here, we present a novel multi-metal electrochemical 3D printer which is able to fabricate bimetallic geometries and through the selective deposition of different metals, temperature responsive behaviour can thus be programmed into the printed structure. The concept is demonstrated through a meniscus confined electrochemical 3D printing approach with a multi-print head design with nickel and copper used as exemplar systems but this is transferable to other deposition solutions. Improvements in deposition speed (34% (Cu)-85% (Ni)) are demonstrated with an electrospun nanofibre nib compared to a sponge based approach as the medium for providing hydrostatic back pressure to balance surface tension in order to form a electrolyte meniscus stable. Scanning electron microscopy, X-ray computed tomography and energy dispersive X-ray spectroscopy shows that bimetallic structures with a tightly bound interface can be created, however convex cross sections are created due to uneven current density. Analysis of the thermo-mechanical properties of the printed strips shows that mechanical deformations can be generated in Cu-Ni strips at temperatures up to 300 °C which is due to the thermal expansion coefficient mismatch generating internal stresses in the printed structures. Electrical conductivity measurements show that the bimetallic structures have a conductivity between those of nanocrystalline copper (5.41×106 S.m−1) and nickel (8.2×105 S.m-1). The potential of this novel low-cost multi-metal 3D printing approach is demonstrated with the thermal actuation of an electrical circuit and a range of self-assembling structures.
Chen X, Liu X, Ouyang M, et al., 2019, Electrospun composite nanofibre supercapacitors enhanced with electrochemically 3D printed current collectors, Journal of Energy Storage, Vol: 26, Pages: 100993-100993, ISSN: 2352-152X
Carbonised electrospun nanofibres are attractive for supercapacitors due to their relatively high surface area, facile production routes and flexibility. With the addition of materials such as manganese oxide (MnO), the specific capacitance of the carbon nanofibres can be further improved through fast surface redox reactions, however this can reduce the electrical conductivity. In this work, electrochemical 3D printing is used as a novel means of improving electrical conductivity and the current collector-electrode interfacial resistance through the deposition of highly controlled layers of copper. Neat carbonised electrospun electrodes made with a 30 wt% manganese acetylacetonate (MnACAC) and polyacrylonitrile precursor solution have a hydrophobic nature preventing an even copper deposition. However, with an ethanol treatment, the nanofibre films can be made hydrophilic which enhances the copper deposition morphology to enable the formation of a percolating conductive network through the electrode. This has the impact of increasing electrode electronic conductivity by 360% from 10 S/m to 46 S/m and increasing specific capacitance 110% from 99 F/g to 208 F/g at 5 mV/s through increased utilisation of the pseudocapacitive active material. This novel approach thus provides a new route for performance enhancement of electrochemical devices using 3D printing, which opens new design possibilities.
Liu X, George C, Wang H, et al., 2019, Novel inorganic composite materials for lithium‐ion batteries, Encyclopedia of Inorganic and Bioinorganic Chemistry, Publisher: Wiley
Lithium‐ion batteries (LIBs) have revolutionized the way we interact with the world around us. This is in part due to their unrivaled energy density and stability relative to other energy storage chemistries such as lead‐acid, nickel–metal hydride, and nickel–cadmium batteries. Given the drive to reduce greenhouse gas emissions from road transport, LIBs have now transitioned from application in consumer electronics to be the most critical component for electric vehicles (EVs); however, improvements in energy and power density, cost reduction, and lifetime are still required. The key aspects of an LIB that define its performance are mainly the anode, cathode, and electrolyte, however development of the separator and current collectors are also key considerations. In the vast majority of commercially available LIBs, the anode consists mostly of graphite and the cathode mostly of layered transition metal oxides, with an organic electrolyte facilitating the lithium‐ion transport between the two electrodes. This article provides an overview of the state of the art in developing inorganic composite materials for LIBs and concludes by highlighting the current challenges as well as the potential opportunities in the field.
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.