Batteries, Volume 9, Issue 10 (October 2023) – 42 articles

Determining both the average temperature and the underlying temperature distribution within a battery system is crucial for system design, control, and operation. Therefore, thermal battery system models, which allow for the calculation of these distributions, are required. In this work, a generic thermal equivalent circuit model for commercial battery modules with passive cooling is introduced. The model approach can be easily adopted to varying system designs and sizes and is accompanied by a corresponding low-effort characterization process. The validation of the model was performed on both synthetic and measured load profiles from stationary and marine applications. The results show that the model can represent both the average temperature and the occurring temperature spread (maximum to minimum temperature) with deviations below 1 K. In addition to the introduced full-scale model, further simplifying assumptions were tested in order to reduce the computational effort required by the model. By comparing the resulting simplified models with the original full-scale model, it can be shown that both reducing the number of simulated cells and assuming electrical homogeneity between the cells in the module offer a reduction in the computation time within one order of magnitude while still retaining a high model accuracy. Full article

Accurately estimating the state-of-charge (SOC) of lithium-ion batteries (LIBs) in electric vehicles is a challenging task due to the complex dynamics of the battery and the varying operating conditions. To address this, this paper proposes the establishment of an Industrial Internet-of-Things (IIoT)-based digital twin (DT) through the Microsoft Azure services, incorporating components for data collection, time synchronization, processing, modeling, and decision visualization. Within this framework, the readily available measurements in the LIB module, including voltage, current, and operating temperature, are utilized, providing advanced information about the LIBs’ SOC and facilitating accurate determination of the electric vehicle (EV) range. This proposed data-driven SOC-estimation-based DT framework was developed with a supervised voting ensemble regression machine learning (ML) approach using the Azure ML service. To facilitate a more comprehensive understanding of historical driving cycles and ensure the SOC-estimation-based DT framework is accurate, this study used three application programming interfaces (APIs), namely Google Directions API, Google Elevation API, and OpenWeatherMap API, to collect the data and information necessary for analyzing and interpreting historical driving patterns, for the reference EV model, which closely emulates the dynamics of a real-world battery electric vehicle (BEV). Notably, the findings demonstrate that the proposed strategy achieves a normalized root mean square error (NRMSE) of 1.1446 and 0.02385 through simulation and experimental studies, respectively. The study’s results offer valuable insights that can inform further research on developing estimation and predictive maintenance systems for industrial applications. Full article

The topic of battery state-of-health monitoring via electrical and non-electrical testing procedures has become of increased interest for scientific researchers, due to the imposed goal of expanded industrial sustainability. Within the present study, we propose a novel approach for monitoring the temperature of batteries by means of infrared thermography. In order to improve the accuracy of the performed measurements and to overcome the limitations imposed by the cylindrical housing of the batteries, we have developed a unique method for monitoring and capturing the temperature of the battery over the entire housing. An experimental system was built, through which the battery performs a rotational movement relative to its axis, with this rotation motion being synchronized with the frame rate of the thermal camera. The resulting thermographic images are processed using specifically developed software. This software enables the segmentation of certain sections of the battery’s surface from a defined spatial perspective. These selected segments are subsequently utilized to generate a three-dimensional representation of the battery’s surface temperature’s distribution. In this way, errors in the obtained results which are caused by the viewing angle are avoided. Additionally, we developed and presented a method for the increasing of the resolution of captured thermograms. Full article

The size of a lithium iron phosphate (LFP) cathode mix was increased by a factor of thirty, and the capacity of the cells produced with it by a factor of three-hundred. As well as rate and cycling tests, the coatings were also characterised for adhesion and resistivity. The adhesion and total through-plane resistance were both dependent on the drying conditions during coating. The discharge capacities at high rates and the pulse resistances showed much less influence from the drying temperature. The mix formulation contained 97 wt% LFP, and was based on an earlier design of experiments (DoE) study, using relatively high active material contents. Overall, the mix exceeded the performance predicted by the modelling study. Full article

Lithium-ion batteries, known for their high efficiency and high energy output, have gained significant attention as energy storage devices. Monitoring the state of charge through battery management systems plays a crucial role in enhancing the safety and extending the lifespan of lithium-ion batteries. In this paper, we propose a state-of-charge estimation method to overcome the limitations of the traditional open-circuit voltage method and electrochemical impedance spectroscopy. We verified changes in the shape of the voltage relaxation curve based on battery impedance through simulations and analyzed the impact of individual impedance on the voltage relaxation curve using differential equations. Based on this relationship, we estimated the impedance from the battery’s voltage relaxation curve through curve fitting and subsequently estimated the state of charge using a pre-established lookup table. In addition, we introduced a partial curve-fitting method to reduce the estimation time compared to the existing open-circuit voltage method and confirmed the trade-off relationship between the estimation time and estimation error. Full article

Simple parameter-based models are typically unable to function in all situations due to the rapidly tightening margins for error in the use of contemporary estimation techniques. The development of data-driven models as a result has made the availability of trustworthy battery data essential. The generation of such data from battery systems necessitates prolonged cycling tests that can last for months, which makes data collection challenging. In this article, a combination of approaches is presented that uses measured operational data from battery packs to generate synthetic data utilizing Markov chains and neural networks in order to ultimately estimate the capacity fade based on operational drive cycle data. The experimental data used for this study are generated using scaled operational cycles with multiple charge/discharge pulses applied repetitively on a commercially available battery pack. The synthetically generated data have the flexibility of matching user-imposed conditions, and have potential for a variety of applications in the analysis and safety of commercial battery systems. Finally, capacity estimation results present the outcome of a comprehensive study into capacity fade estimation in battery packs. Full article

LiFePO₄ (LFP) has undergone extensive research and is a promising cathode material for Li-ion batteries. The high interest is due to its low raw material cost, good electrochemical stability, and high-capacity retention. However, poor electronic conductivity and a low Li⁺ diffusion rate decrease its electrochemical reactivity, especially at fast charge/discharge rates. In this work, the volumetric energy density of lithium-ion batteries is successfully increased by using different amounts of conductive carbon (Super P) in the active material content. The particle size and morphology of the electrode material samples are studied using field emission scanning electron microscopy and dynamic light scattering. Two-point-probe DC measurements and adhesive force tests are used to determine the conductivity and evaluate adhesion for the positive electrode. Cyclic voltammetry, electrochemical impedance spectroscopy (EIS), and charge/discharge tests are used to analyze the electrochemical properties of the battery. The samples containing 88% LFP, 5.5% Super P, and 6.5% PVDF perform best, with discharge capacities reaching 169.8 mAh g⁻¹ at 0.1 C, and they can also manage charging/discharging of 5 C. EIS indicates that this combination produces the lowest charge-transfer impedance (67 Ω) and the highest Li⁺ ion diffusion coefficient (5.76 × 10⁻¹⁴ cm² s⁻¹). Full article

With the increasing number of electric vehicles (EVs) rises the need to recycle their used lithium-ion batteries (LIBs). During the mechanical process of the recycling of the LIB cells, a fine fraction, the so-called black mass, is created. This black mass consists mostly of the coatings originating from the cells’ electrodes and residues from the electrolyte, together with a low amount of Al and Cu from the crushed current collector foils. The amount of black mass as well as its composition is influenced by the chosen grid size at the crusher discharge. To reduce solvent emissions during the recycling process, a thermal pre-treatment can be added before crushing, which also influences the black mass and its properties due to changes in the adhesion between electrode foils and coating. This study investigates the influence of the crusher settings as well as the pre-treatment temperatures to find an optimum between the recovery of the coating and conductive salt, while limiting the amount of Al and Cu in the black mass. Full article

To deal with the flammability of PA (paraffin), this paper proposes a CPCM (composite phase change material) with a high heat-absorbing capacity for mitigating the thermal runaway of lithium-ion batteries. Two heating power levels were used to trigger thermal runaway in order to investigate the influence of heating power on thermal runaway characteristics and the mitigation effect of the PCM (phase change material). Thermal runaway processes and temperature changes were recorded. The results showed that heating results in a violent reaction of the battery, generating a high temperature and a bright flame, and the burning of PA increases the duration of a steady flame, indicating an increased threat. SA (sodium acetate trihydrate) effectively inhibited PA combustion, and the combustion time was reduced by 40.5%. PA/SA effectively retarded the rise in temperature of the battery, and the temperature rise rate was reduced by 87.3%. Increased heating power caused faster thermal runaway, and the thermal runaway mitigation effect of the CPCM was dramatically reduced. This study may provide a reference for the safe design and improvement of thermal management systems. Full article

The flexible energy storage device of high demand in wearable and portable electronics. Flexible supercapacitors have benefits over flexible batteries, and their development relies on the use of flexible components. Gel polymer electrolytes have the merits of liquid and solid electrolytes and are used in flexible devices. In this study, a gel derived from chia seed was used as a flexible electrolyte material, and its rheological, thermal, and electrochemical properties were investigated. High thermal stability and shear thinning behavior were observed via the electrolyte state of the chia mucilage gel. Compared to the conventional salt electrolyte, the chia mucilage gel electrolyte-based supercapacitor exhibited a more rectangular cyclic voltammetry (CV) curve, longer discharging time in galvanostatic charge–discharge (GCD) analysis, and low charge transfer resistance in electrochemical impedance spectroscopy (EIS). The maximum specific capacitance of 7.77 F g⁻¹ and power density of 287.7 W kg⁻¹ were measured, and stable capacitance retention of 94% was achieved after 10,000 cycles of charge/discharge with harsh input conditions. The biodegradability was also confirmed by the degraded mucilage film in soil after 30 days. The plant-driven chia mucilage gel electrolyte can facilitate the realization of flexible supercapacitors for the energy storage devices of the future. Full article

As power sources for electric vehicles, lithium-ion batteries (LIBs) have many advantages, such as high energy density and wide temperature range. In the algorithm design process for LIBs, various battery models with different model structures are needed, among which the electrochemical model is widely used due to its high accuracy. However, the electrochemical model is composed of multiple nonlinear partial differential equations (PDEs) that make the simulating process time-consuming. In this paper, a physics-informed neural network single-particle model (PINN SPM) is proposed to improve the accuracy of the single-particle model (SPM) under high C-rates, while ensuring high solving speed. In PINN SPM, an SPM-Net is designed to solve the distribution of lithium-ion concentration in the electrolyte. In the neural network learning process, a loss function is designed based on the physical constraints brought by the PDEs, which reduces the error of the neural network under dynamic working conditions. Finally, the PINN SPM proposed in this paper can achieve a maximum relative error of up to 1.2% compared with the high-fidelity data generated from the P2D model under various conditions. Additionally, the PINN SPM is 20.8% faster than traditional numerical solution methods with the same computational resources. Full article

Metal halide solid-state electrolytes (SSEs) (Li-M-X system, typically Li₃MX₆ and Li₂MX_4; M is metal or rare-earth element, X is halogen) exhibit significant potential in all solid-state batteries (ASSB) due to wide stability windows (0.36–6.71 V vs. Li/Li⁺), excellent compatibility with cathodes, and a water-mediated facile synthesis route for large-scale fabrication. Understanding the dynamics of Li⁺ transportation and the influence of the host lattice is the prerequisite for developing advanced Metal halide SSEs. Neutron powder diffraction (NPD), as the most cutting-edge technology, could essentially reflect the nuclear density map to determine the whole crystal structure. Through NPD, the Li+ distribution and occupation are clearly revealed for transport pathway analysis, and the influence of the host ion lattice on Li+ migration could be discussed. In this review, we stress NPD utilization in metal halide SSEs systems in terms of defect chemistry, phase transition, cation/anion disorder effects, dual halogen, lattice dynamics/polarizability, and in situ analysis of phase evolution. The irreplaceable role of NPD technology in designing metal halide SSEs with enhanced properties is stressed, and a perspective on future developments of NPD in metal halide SSEs is also presented. Full article

To address the challenges of efficient state monitoring of lithium-ion batteries in electric vehicles, a co-estimation algorithm of state-of-charge (SOC) and state-of-health (SOH) is developed. The algorithm integrates techniques of adaptive recursive least squares and dual adaptive extended Kalman filtering to enhance robustness, mitigate data saturation, and reduce the impact of colored noise. At 25 °C, the algorithm is tested and verified under dynamic stress test (DST) and Beijing bus DST conditions. Under the Beijing bus DST condition, the algorithm achieves a mean absolute error (MAE) of 0.17% and a root mean square error (RMSE) of 0.19% for SOC estimation, with a convergence time of 4 s. Under the DST condition, the corresponding values are 0.05% for MAE, 0.07% for RMSE, and 5 s for convergence time. Moreover, in this research, the SOH is described as having internal resistance. Under the Beijing bus DST condition, the MAE and the RMSE of the estimated internal resistance of the proposed approach are 0.018% and 0.075%, with the corresponding values of 0.014% and 0.043% under the DST condition. The results of the experiments provide empirical evidence for the challenges associated with the efficacious estimation of SOC and SOH. Full article

Real-time monitoring of the state of charge (SOC) of the batteries used in a wide variety of applications is becoming increasingly important, especially given the impetus by the current targets towards “net-zero”. In this research, an advanced approach was used involving fiber Bragg grating (FBG)-based sensors that were developed and implemented for the measurement of the key parameters required to ensure optimum battery performance. In this work, one of the biggest challenges to assess (and then map) the data from the sensor system developed is tackled in order to better understand the key parameters of the battery in an efficient and improved way. It is well known that the relationship between the changes in the resonance wavelength of the FBGs used in the sensor system, arising due to change in the electrical parameters of the battery, is complex and dependent on several different factors. In this work, this effect was evaluated by coupling the sensor data to a data-driven regression model approach that was developed for the measurement of the SOC of the batteries used, and this was obtained directly and conveniently from the FBG data. In this comprehensive study, FBG-based sensors were fabricated and then installed onto the battery, which then was subjected to a range of charging–discharging cycles, following which the electrical parameters of the battery were estimated from recorded data using a black-box machine learning (ML) model. Data-driven regression algorithms were employed for the training of the black-box model. The efficiency of the estimation of the SOC of the battery from the FBG-based sensor data was found to be high, at 99.62% (R² values of Estimated SOC and True SOC line), creating a very satisfactory result for this key measurement. Thus, the work shows the robustness of the FBG-based sensor system combined with the neural network algorithm as an effective way to evaluate the electrical parameters of the battery, which is particularly important, as no physical/electrochemical/electrical model of the system is thus required. Full article

Different classes of solid electrolytes for all-solid-state batteries (ASSB) are currently being investigated, with each of them suitable for a different ASSB concept. Their combination in hybrid battery cells enables the use of their individual benefits while mitigating their disadvantages. The cubic stuffed garnet Li₇La₃Zr₂O₁₂ (LLZO), for example, is stable in contact with metallic lithium but has only moderate ionic conductivity, whereas the thiophosphate Li₁₀SnP₂S₁₂ (LSPS) is processable using conventional battery manufacturing technologies and has an excellent lithium-ion conductivity but an inferior electrochemical stability. In this work, we, therefore, present a layered hybrid all-solid-state full-cell concept that accommodates a lithium metal anode, a LiNi_0.8Co_0.1Mn_0.1O₂-based composite cathode with an LSPS catholyte (LSPS/NCM811) and a sintered monolithic LLZO separator. The electrochemical stability of LLZO and LSPS at cathodic potentials (up to 4.2 V) was investigated via cyclic voltammetry in test cells, as well as by cycling half cells with LSPS or a mixed LSPS/LLZO catholyte. Furthermore, the pressure-dependency of the galvanostatic cycling of a Li | LLZO | LSPS/NCM811 full cell was investigated, as well as the according effect of the Li | LLZO interface in symmetric test cells. An operation pressure of 12.5 MPa was identified as the optimal value, which assures both sufficient inter-layer contact and impeded lithium penetration through the separator and cell short-circuiting. Full article

Solid-state batteries (SSB), characterized by solid-state electrolytes—in particular inorganic ones (ISSE)—are an ideal option for the safe implementation of metallic Li anodes. Even though SSBs with ISSEs have been extensively investigated over the last two decades, they still exhibit a series of technological drawbacks. In fact, mechano-chemical issues, mainly the stability of the electrolyte/anode interface, hinder their widespread application. The present investigation focusses on a thin-film LMO (Lithium-Manganese-Oxide)/LAGP (LiAlGe Phosphate)/Copper, anodeless Lithium-metal battery and explores the morphochemical evolution of the electrode/electrolyte interfaces with synchrotron-based Scanning Photoelectron Microscopy (SPEM) of intact pristine and cycled cells. Chemical images were acquired with submicrometer resolution, to highlight the coupled geometrical and chemical-state changes caused by electrochemical ageing. Geometrical changes of the electrolyte/cathode interface were induced by periodic volume changes, causing de-cohesion of the solid-solid contact, but no chemical-state changes accompany the cathodic damaging mode. Instead, shape changes of the electrolyte/anode region pinpoint the correlation between mechanical damaging with the decomposition of the LAGP ISSE, due to the reduction of Ge, triggered by the contact with elemental Li. The micro-spectroscopic approach adopted in this study enabled the assessment of the highly localized nature of the cathodic and anodic degradation modes in SSB devices and to single out the chemical and mechanical contributions. Full article

Alloying-type anode materials have considerably promoted the development of potassium-ion batteries (PIBs) and sodium-ion batteries (SIBs), enabling them to achieve high-energy-density. However, large volume expansion and sluggish dynamic behavior have become key issues affecting electrochemical performance. Herein, bismuth (Bi) nano-rods are anchored on reduced graphene (rGO) and encapsulated via N-doped C (NC) to construct Bi@rGO@NC architecture as anode materials for SIBs and PIBs. The hierarchical confinement effect of three-dimensional conductive networks can not only improve electrode stability upon cycling via suppressing the large volume variation, but also eliminate the band gap of Bi and accelerate ion diffusion, thereby exhibiting favorable electrochemical reaction kinetics. Thus, Bi@rGO@NC contributes an ultra-long lifetime, over 1000 cycles, and an outstanding rate property to SIBs and PIBs. This work can pave the way for the construction of high-performance alloying-type anode materials for SIBs and PIBs. Full article

Redox flow batteries (RFBs) have attracted significant attention as a promising electrochemical energy storage technology, offering various advantages such as grid-scale electricity production with variable intermittent electricity delivery, enhanced safety compared to metal-ion batteries, decoupled energy and power density, and simplified manufacturing processes. For this review, we exclusively focus on organic, non-aqueous redox flow batteries. Specifically, we address the most recent progress and the major challenges related to the design and synthesis of robust redox-active organic compounds. An extensive examination of the synthesis and characterization of a wide spectrum of redox-active molecules, focusing particularly on derivatives of posolytes such as quinone, nitroxyl radicals, dialkoxybenzenes, and phenothiazine and negolytes such as viologen and pyridiniums, is provided. We explore the incorporation of various functional groups as documented in the references, aiming to enhance the chemical and electrochemical stability, as well as the solubility, of both the neutral and radical states of redox-active molecules. Additionally, we offer a comprehensive assessment of the cell-cycling performance exhibited by these redox-active molecules. Full article

All-solid-state lithium-ion batteries based on solid electrolytes are attractive for electric applications due to their potential high energy density and safety. The sulfide solid electrolyte (e.g., argyrodite) shows a high ionic conductivity (10⁻³ S cm⁻¹). There is an open question related to the sulfide electrode’s fabrication by simply infiltrating methods applied for conventional lithium-ion battery electrodes via homogeneous solid electrolyte solutions, the structure of electrolytes after drying, chemical stability of binders and electrolyte, the surface morphology of electrolyte, and the deepening of the infiltrated electrolyte into the active materials to provide better contact between the active material and electrolyte and favorable lithium ionic conduction. However, due to the high reactivity of sulfide-based solid electrolytes, unwanted side reactions between sulfide electrolytes and polar solvents may occur. In this work, we explore the chemical and electrochemical properties of the argyrodite-based film produced by infiltration mode by combining electrochemical and structural characterizations. Full article

The automotive industry is rapidly transitioning to electric vehicles (EVs) in response to the global efforts to reduce greenhouse gas emissions. Lithium-ion battery (LIB) has emerged as the main tool for energy storage in electric vehicles. A widespread adoption of EVs, however, requires a fast-charging technology that can significantly reduce charging time while avoiding any unsafe conditions including short circuits due to failure of the separator in an LIB cell. Therefore, it is necessary to understand the mechanical stresses during fast charging and their long-term effect on the integrity of the separator. This paper presents a novel hybrid model for the prediction of the stress distribution in the separator of a pouch cell under various charging speeds, ambient temperatures, and pack assembly conditions, such as compressive pressures. The proposed hybrid model consists of three sub-models, namely, an electrochemical cell model, a lumped-parameter model, and a solid mechanics model. A robust parameter identification scheme is implemented to determine the model parameters using the experimental data. The separator within the test setup will experience maximum von Mises stress of 74 MPa during 4C charging, i.e., when the charge current in A is four times as high as the capacity of the battery cell in Ah. To assess the evolution of the damage in the separator under the estimated stress during fast charging, creep and fatigue tests are conducted on the separator. Their results indicate a progressive accumulation of damage in the separator, further emphasizing the importance of understanding and mitigating mechanical degradation in separator materials. Full article

Lithium-ion batteries are usually connected in series and parallel to form a pack for meeting the voltage and capacity requirements of energy storage systems. However, different pack configurations and battery module collector positions result in different equivalent connected resistances, leading to pack current inhomogeneity, which seriously reduces the lifetime and safety of the pack. Therefore, in order to quantitatively analyze the influence of the connected resistance on the current distribution, this study researched the initial cell current distribution of the parallel module by developing mathematical models of different configurations. Then, this study explored the influence of multiple module collector positions on the current inhomogeneity of the pack under the dynamic current condition. The results show that the inhomogeneity of cell current and discharge capacity in the pack with parallel modules connected in series can be improved by keeping each cell in a parallel module with the same distance to its module collector. Furthermore, the current homogeneity of the edge parallel modules in the pack is seriously affected by the position of the single module collector. Therefore, this study innovatively proposes the symmetrical multiple module collectors of the pack, which can greatly improve the current homogeneity of the edge parallel modules, thereby improving the lifetime and safety of the pack. Full article

This study explores the potential of titanium disulfide (TiS₂) as an active material for aqueous calcium-ion batteries (CIBs). We investigate the electrochemical redox reactions of calcium ions within TiS₂ and assess its suitability for use in aqueous CIBs. Additionally, we examine the impact of varying electrolyte concentrations, ranging from 1.0 to 8.0 mol dm⁻³, on TiS₂ electrode reactions. Our findings reveal that TiS₂ exhibits distinct charge–discharge behaviors in various aqueous calcium-ion electrolytes. Notably, at higher electrolyte concentrations, TiS₂ effectively suppresses the hydrogen generation reaction caused by water decomposition. In situ X-ray diffraction analysis confirms the intercalation of Ca²⁺ ions between the TiS₂ layers during charging, which is a groundbreaking discovery, signifying TiS₂’s applicability in aqueous CIBs. X-ray photoelectron spectroscopy analysis further supports the formation of a solid electrolyte interphase (SEI) on the TiS₂ electrode surface, contributing to the suppression of electrolyte decomposition reactions. Furthermore, we investigate the influence of anions in the electrolyte on charge–discharge behavior. Our findings suggest that the choice of anion coordinated with Ca²⁺ ions affects the SEI formation and cycling performance. Understanding the role of anions in SEI formation is crucial for optimizing aqueous CIBs. In conclusion, this research underscores TiS₂’s potential as an active material for aqueous calcium-ion batteries and emphasizes the importance of the electrolyte composition in influencing SEI formation and battery performance, contributing to sustainable and efficient energy storage technologies. Full article

Accurate online parameter identification and state of charge (SOC) estimation are both very crucial for ensuring the operating safety of lithium-ion batteries and usually the former is a base of the latter. To achieve accurate and stable SOC estimation results, this paper proposes a model-based method, which incorporates a vector forgetting factor least square (VFFLS) algorithm and an improved adaptive cubature Kalman filter (IACKF). Firstly, considering it is difficult for the traditional forgetting factor recursive least square (FFRLS) algorithm to balance the accuracy, convergence, and stability for multiple parameters with different time-varying periods, an improved VFFLS method is employed to determine the multiple parameters of the first-order RC battery model online. It supersedes the single forgetting factor in the FFRLS with multiple forgetting factors in a vector form for improving adaptive capability to multiple time-varying parameters. Secondly, aiming at the fact that the standard cubature Kalman filter (CKF) cannot operate properly when the error covariance matrix is non-positive definite, which is caused by disturbance, initial error, and the limit of the computer word length, the UR decomposition rather than the Cholesky decomposition is applied, thus improving the algorithm stability. In addition, an adaptive update strategy is added to the CKF to enhance accuracy and convergence speed. Finally, comparative experiments with different operating patterns, positive and non-positive definite error covariance matrices, and temperatures are carried out. Experimental results showed that the proposed method can estimate the SOC accurately and stably. Full article

Ni-rich LiNi_xMn_yCo_1−x−yO₂ (NMC) materials have been adopted in a range of applications, including electric vehicles. The recycled NMC material from a spent cell would be much more valuable if it could be upgraded to a Ni-rich, more energy-dense version of the material. This work demonstrates a simple, inexpensive, and facile method to upcycle LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111, 160 mAh∙g⁻¹), a cathode used in early generations of electric vehicle batteries, to LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811, 190 mAh∙g⁻¹), a more energy-dense cathode material. In this study, a preliminary investigation into a room-temperature eutectic synthesis of NMC811 is performed using NMC111, LiOH, and nickel nitrate as precursors. The synthesized material showed the desired crystal structure and stoichiometry, though the cycle life and Li diffusion coefficient need improvement when compared to commercially available NMC811. This study demonstrates an interesting proof of concept of the room-temperature eutectic synthesis process for LIB cathodes and could be improved by tuning the synthesis conditions. Full article

Herein, we design a cathode material based on layered Na_2/3(Mn_1/2Fe_1/2)O₂ for practical application by combining the Co substitution and MgO treatment strategies. The oxides are prepared via solid-state reactions at 900 °C. The structure, morphology, and oxidation state of transition metal ions for Co-substituted and MgO-treated oxides are carefully examined via X-ray diffraction, IR and Raman spectroscopies, FESEM with EDX, specific surface area measurement, and XPS spectroscopy. The ability of oxides to store sodium reversibly is analyzed within a temperature range of 10 to 50 °C via CV experiments, galvanostatic measurements, and EIS, using half and full sodium ion cells. The changes in the local structure and oxidation state of transition metal ions during Na⁺ intercalation are monitored via operando XAS experiments. It is found that the Co substituents have a positive impact on the rate capability of layered oxides, while Mg additives lead to a strong increase in the capacity and an enhancement of the cycling stability. Thus, the highest capacity is obtained for 2 at.%-MgO-treated Na_2/3(Mn_1/2Fe_1/2)_0.9Co_0.1O₂ (175 mAh/g, with a capacity fade of 28% after 100 cycles). In comparison with Co substituents, the Mg treatment has a crucial role in the improvement of the lattice stability during the cycling process. The best electrode materials, with a chemical formula of 2 at.%-MgO treated Na_2/3(Mn_1/2Fe_1/2)_0.9Co_0.1O₂, were also used for the full cells design, with hard carbon as an anode. In the voltage window of 2–4 V, the capacity of the cells was obtained as 78 mAh/g and 51 mAh/g for applied current densities of 12 mA/g and 60 mA/g, respectively. Full article

The internal short circuit (ISC) in lithium-ion batteries is a serious problem since it is probably the most common cause of a thermal runaway (TR) that still presents many open questions, even though it has been intensively investigated. Therefore, this article focusses on the generation and characterisation of the local single-layer ISC, which is typically caused by cell-internal impurity particles that cannot be completely eliminated in the cell production. A new, very promising method of precise and slow (1 $\mathsf{\mu }$m s${}^{-1}$) needle penetration made it possible to generate the most safety-critical reliable short-circuit type—the contact between the Al-Collector and the graphite active material of the anode—as demonstrated on a 10 Ah Graphite/NMC pouch cell. The special efforts in achieving high reproducibility as well as the detailed analysis of the initiated internal short-circuit conditions led to more reliable and meaningful results. A comprehensive approach to characterisation has been made by detailed measurement of the dynamic short-circuit evolution and a subsequent post-characterisation, which included the application of different electrochemical measurement techniques as well as a post-abuse analysis. It was shown that the cells demonstrated a very individual and difficult-to-predict behaviour, which is a major challenge for early failure detection and risk assessment of cells with an existing or former ISC. On the one hand, it is found that despite high local temperatures of over 1260 ${}^{\circ }$C and significant damage to the cell-internal structure, the cell did not develop a TR even with further cycling. On the other hand, it was observed that the TR occurs spontaneously without any previous abnormalities. Based on the overall test results, it was shown that at the high state of charge (SOC = 100%), even small, dynamically developing voltage drops (<10 mV) must be classified as safety-critical for the cell. For reliable and early failure detection, the first voltage drops of the ISC must already be detected. Full article

The growing interest in Na-ion batteries as a “beyond lithium” technologies for energy storage drives the research for high-performance and environment-friendly materials. Na₂Ti₃O₇ (NTO) as an eco-friendly, low-cost anode material shows a very low working potential of 0.3 V vs. Na⁺/Na but suffers from poor cycling stability, which properties can be significantly influenced by materials synthesis and treatment. Thus, in this work, the influence of the calcination time on the electrochemical performance and the reaction mechanism during cycling were investigated. NTO heat-treated for 48 h at 800 °C (NTO-48h) demonstrated enhanced cycling performance in comparison to NTO heat-treated for only 8 h (NTO-8h). The pristine material was thoroughly characterized by X-ray diffraction, laser granulometry, X-ray photoelectron spectroscopy, and specific surface area measurements. The reaction mechanisms induced by sodiation/desodiation and cycling were investigated by operando XRD. Electrochemical impedance spectroscopy was used to evidence the evolution of the solid electrolyte interface layer (SEI) and modification of charge transfer resistances as well as the influence of cycling on capacity decay. The evolution of the crystallographic structure of NTO-48h revealed a more ordered structure and lower surface contamination compared to NTO-8h. Moreover, the residual Na₄Ti₃O₇ phase detected after the sodium extraction step in NTO-8h seems correlated to the lower electrochemical performance of NTO-8h compared to NTO-48h. Full article

State-of-health (SoH) estimation is one of the key tasks of a battery management system, (BMS) as battery aging results in capacity- and power fade that must be accounted for by the BMS to ensure safe operation over the battery’s lifetime. In this study, an online SoH estimator approach for NMC Li-ion batteries is presented which is suitable for implementation in a BMS. It is based on an observer structure in which the difference between a calculated and expected open-circuit voltage (OCV) is used for online SoH estimation. The estimator is parameterized and evaluated using real measurement data. The data were recorded for more than two years on an electrified bus fleet of 10 buses operated in a mild European climate and used regularly in the urban transport sector. Each bus is equipped with four NMC Li-ion batteries. Every battery has an energy of 30.6 kWh. Additionally, two full-capacity checkup measurements were performed for one of the operated batteries: one directly after production and one after two years of operation. Initial validation results demonstrated a SoH estimation accuracy of ±0.5% compared to the last checkup measurement. Full article