Batteries

Accurate estimation of lithium-ion battery state of health (SOH) can effectively improve the operational safety of electric vehicles and optimize the battery operation strategy. However, previous SOH estimation algorithms developed based on high-precision laboratory data have ignored the discrepancies between field and laboratory data, leading to difficulties in field application. Therefore, aiming to bridge the gap between the lab-developed models and the field operational data, this paper presents a feature engineering-based SOH estimation method with downgraded laboratory battery data, applicable to real vehicles under different operating conditions. Firstly, a data processing pipeline is proposed to downgrade laboratory data to operational fleet-level data. The six key features are extracted on the partial ranges to capture the battery’s aging state. Finally, three machine learning (ML) algorithms for easy online deployment are employed for SOH assessment. The results show that the hybrid feature set performs well and has high accuracy in SOH estimation for downgraded data, with a minimum root mean square error (RMSE) of 0.36%. Only three mechanism features derived from the incremental capacity curve can still provide a proper assessment, with a minimum RMSE of 0.44%. Voltage-based features can assist in evaluating battery state, improving accuracy by up to 20%. Full article

Energy management in the residential sector contributes to energy system dispatching and security with the optimal use of renewable energy systems (RES) and energy storage systems (ESSs) and by utilizing the main grid based on its state. This work focuses on optimal energy flow, ESS parameters, and energy consumption scheduling based on demand response (DR) programs. The primary goals of the work consist of minimizing electricity costs while simultaneously extending the lifetime of ESSs in conjunction with extracting maximum benefits throughout their operational lifespan and reducing CO₂ emissions. Effective ESS and photovoltaic (PV) energy usage prices are modeled and an efficient energy flow management algorithm is presented, which considers the life cycle of the ESSs including batteries, electrical vehicles (EVs) and the efficient use of the PV system while reducing the cost of energy consumption. In addition, an optimization technique is employed to obtain the optimal ESS parameters including the size and depth of discharge (DOD), considering the installation cost, levelized cost of storage (LCOS), winter and summer conditions, energy consumption profile, and energy prices. Finally, an optimization technique is applied to obtain the optimal energy consumption scheduling. The proposed system provides all of the possibilities of exchanging energy between EV, battery, PV system, grid, and home. The optimization problem is solved using the particle swarm optimization algorithm (PSO) in MATLAB with an interval time of one minute. The results show the effectiveness of the proposed system, presenting an actual cost reduction of 28.9% and 17.7% in summer and winter, respectively, compared to a base scenario. Similarly, the energy losses were reduced by 26.7% in winter and 22.3% in summer, and the EV battery lifetime was extended from 9.2 to 19.1 years in the winter scenario and from 10.4 to 17.7 years in the summer scenario. The integrated system provided a financial contribution during the operational lifetime of EUR 11,600 and 7900 in winter and summer scenarios, respectively. The CO₂ was reduced by 59.7% and 46.2% in summer and winter scenarios, respectively. Full article

Second-life applications for lithium-ion batteries offer the industry opportunities to defer recycling costs, enhance economic value, and reduce environmental impacts. An accurate prognosis of the remaining useful life (RUL) is essential for ensuring effective second-life operation. Diagnosis is a necessary step for the establishment of a reliable prognosis, based on the aging modes involved in a cell. This paper introduces a method for characterizing specific aging phenomenon in Graphite/Lithium Iron Phosphate (G/LFP) cells. This method aims to identify aging related to the loss of active material at the negative electrode (LAM_NE). The identification and tracking of the state of health (SoH) are based on Incremental Capacity Analysis (ICA) and Differential Voltage Analysis (DVA) peak-tracking techniques. The remaining capacity of the electrode is thus evaluated based on these diagnostic results, using a model derived from half-cell electrode characterization. The method is used on a G/LFP cell in the format 18650, with a nominal capacity of 1.1 Ah, aged from its pristine state to 40% of state of health. Full article

Battery design efforts often prioritize enhancing the energy density of the active materials and their utilization. However, optimizing thermal management systems at both the cell and pack levels is also key to achieving mission-relevant battery design. Battery thermal management systems, responsible for managing the thermal profile of battery cells, are crucial for balancing the trade-offs between battery performance and lifetime. Designing such systems requires accounting for the multitude of heat sources within battery cells and packs. This paper provides a summary of heat generation characterizations observed in several commercial Li-ion battery cells using isothermal battery calorimetry. The primary focus is on assessing the impact of temperatures, C-rates, and formation cycles. Moreover, a module-level characterization demonstrated the significant additional heat generated by module interconnects. Characterizing heat signatures at each level helps inform manufacturing at the design, production, and characterization phases that might otherwise go unaccounted for at the full pack level. Further testing of a 5 kWh battery pack revealed that a considerable temperature non-uniformity may arise due to inefficient cooling arrangements. To mitigate this type of challenge, a combined thermal characterization and multi-domain modeling approach is proposed, offering a solution without the need for constructing a costly module prototype. Full article

While lithium metal is highly desired as a next-generation battery material due to its theoretically highest capacity and lowest electrode potential, its practical application has been impeded by stability issues such as dendrite formation and short cycle life. Ongoing research aims to enhance the stability of lithium metal batteries for commercialization. Among the studies, research on N-based electrolyte additives, which can stabilize the solid electrolyte interface (SEI) layer and provide stability to the lithium metal surface, holds great promise. The NO₃⁻ anion in the N-based electrolyte additive causes the SEI layer on the lithium metal surface to contain compounds such as Li₃N and Li₂O, which not only facilitates the conduction of Li⁺ ions in the SEI layer but also increases its mechanical strength. However, due to challenges with the solubility of N-based electrolyte additives in carbonate-based electrolytes, extensive research has been conducted on electrolytes based on ethers. Nonetheless, the low oxidative stability of ether-based electrolytes hinders their practical application. Hence, a strategy is needed to incorporate N-based electrolyte additives into carbonate-based electrolytes. In this review, we address the challenges of lithium metal batteries and propose practical approaches for the application and development of N-based electrolyte additives. Full article

GeFe₂O₄ (GFO) is a germanium mineral whose spinel crystal structure determines its interesting functional properties. Recently, it was proposed for application as an anode for Sodium and Lithium-Ion Batteries (SIBs and LIBs) thanks to its combined conversion and alloying electrochemical mechanism. However, its entire potential is limited by the poor electronic conductivity and volumetric expansion during cycling. In the present paper, pure and Sn or Mg doped GFO samples obtained from mechano-chemical solid-state synthesis and properly carbon coated were structurally and electrochemically characterized and proposed, for the first time, as anodes for SIBs. The spinel cubic structure of pure GFO is maintained in doped samples. The expected redox processes, involving Fe and Ge ions, are evidenced in the electrochemical tests. The Sn doping demonstrated a beneficial effect on the long-term cycling (providing 150 mAh/g at 0.2 C after 120 cycles) and on the capacity values (346 mAh/g at 0.2 C with respect to 300 mAh/g of the pure one), while the Mg substitution was less effective. Full article

Most investigations on flow batteries (FBs) make the assumption of perfectly mixed electrolytes inside the tanks without estimating their likelihood, while specific analyses are missing in the literature. This paper presents a pioneering investigation of the electrolyte flow dynamics inside FB tanks. This study considers the Open Circuit Voltage (OCV) measured at the stack of a 9 kW/27 kWh Vanadium FB with 500 L tanks. Order-of-magnitude estimates of the measured dynamics suggest that differences in densities and viscosities of the active species drive gradients of concentrations with different patterns in the positive and negative tanks and in charge and discharge, affected by current and flow rate, which result in significant deviation from homogeneity, affecting the State of Charge (SoC) of the electrolytes flowed into the stack and thus the FB performance. In particular, stratifications of the inlet electrolytes may appear which are responsible for delays in reaching the outlets, with initial plateau and following step (s) in the SoC at the stack. These events can have a major impact in the performance of industrial FBs with large tanks and suggest that specific tank designs may improve the overall dynamics, calling for further analysis. Full article

For all-solid-state batteries, the particle size distribution of the solid electrolyte is a critical factor. Small particles are preferred to obtain a high active mass loading of cathode active material and a small porosity in composite cathodes. In this work, the influence of the solid fraction in the wet-chemical synthesis of β-Li₃PS₄ in tetrahydrofuran (THF) is investigated. The solid fraction is varied between 50 and 200 mg/mL, and the obtained samples are evaluated using X-ray diffraction, SEM and electrochemical impedance measurements. The sizes of the resulting particles show a significant dependency on the solid fraction, while a good ionic conductivity is maintained. For the highest concentration, the particle sizes do not exceed 10 µm, but for the lowest concentration, particles up to ~73 µm can be found. The ionic conductivities at room temperature are determined to be 0.63 ± 0.01 × 10⁻⁴ S/cm and 0.78 ± 0.01 × 10⁻⁴ S/cm for the highest and lowest concentrations, respectively. These findings lead to an improvement towards the production of tailored sulfide solid electrolytes. Full article

In the context of the electrification of the mobility sector, smart algorithms have to be developed to control battery packs. Smart and reconfigurable batteries are a promising alternative to conventional battery packs and offer new possibilities for operation and condition monitoring. This work proposes a reinforcement learning (RL) algorithm to balance the State of Charge (SoC) of reconfigurable batteries based on the topologies half-bridge and battery modular multilevel management (BM3). As an RL algorithm, Amortized Q-learning (AQL) is implemented, which enables the control of enormous numbers of possible configurations of the reconfigurable battery as well as the combination of classical controlling approaches and machine learning methods. This enhances the safety mechanisms during control. As a neural network of the AQL, a Feedforward Neuronal Network (FNN) is implemented consisting of three hidden layers. The experimental evaluation using a 12-cell hybrid cascaded multilevel converter illustrates the applicability of the method to balance the SoC and maintain the balanced state during discharge. The evaluation shows a 20.3% slower balancing process compared to a conventional approach. Nevertheless, AQL shows great potential for multiobjective optimizations and can be applied as an RL algorithm for control in power electronics. Full article

Lithium-ion (Li-ion) batteries, despite their prevalence, face issues of resource scarcity and environmental concerns, prompting the search for alternative technologies. This study addresses the need to assess and identify viable metal-ion battery alternatives to Li-ion batteries, focusing on the rapidly industrializing context of Vietnam. It acknowledges the criticality of developing a sustainable, cost-effective, and resource-efficient energy storage solution that aligns with the country’s growth trajectory. The primary objective is to evaluate the suitability of emerging metal-ion batteries—specifically sodium-ion (SIB), sodium-ion saltwater (SIB-S), magnesium-ion (MIB), and zinc-ion (ZIB)—for Vietnam’s energy storage needs, guiding future investment and policy decisions. A Fuzzy Multiple-Criteria Decision-Making (MCDM) approach is employed, incorporating both quantitative and qualitative criteria. This study utilizes the Fuzzy Best-Worst Method (BWM) to determine the relative importance of various performance indicators and then applies the Bonferroni Fuzzy Combined Compromise Solution (Bonferroni FCoCoSo) method to rank the battery alternatives. The SIBs emerged as the most promising alternative, scoring the highest in the overall evaluation. The MIBs and SIB-saltwater batteries displayed competitive potential, while the ZIBs ranked the lowest among the considered options. This research provides a strategic framework for energy policy formulation and investment prioritization. It contributes to the field by applying a fuzzy-based MCDM approach in a novel context and offers a structured comparative analysis of metal-ion batteries, enhancing the body of knowledge on sustainable energy storage technologies. Full article

Lithium-ion batteries are widely used in modern society as important energy storage devices due to their high energy density, rechargeable performance, and light weight. However, the capacity and performance of lithium-ion batteries gradually degrade with the number of charge or discharge cycles and environmental conditions, which can affect the reliability and lifetime of the batteries, so it is necessary to accurately evaluate their health. The belief rule base (BRB) model is an evaluation model constructed based on rules that can handle uncertainties in the operation of lithium-ion batteries. However, lithium-ion batteries may be affected by disturbances from internal or external sources during operation, which may affect the evaluation results. To prevent this problem, this paper proposes a disturbance-considering BRB modeling approach that considers the possible effects of disturbances on the battery in the operating environment and quantifies the disturbance-considering capability of the assessment model in combination with expert knowledge. Second, robustness and interpretability constraints are added in this paper, and an improved optimization algorithm is constructed that maintains or possibly improves the resistance of the model to disturbance. Finally, using the lithium-ion batteries provided by the National Aeronautics and Space Administration (NASA) Prediction Centre of Excellence and the University of Maryland as a case study, this paper verifies that the proposed modeling approach is capable of constructing robust models and demonstrates the effectiveness of the improved optimization algorithm. Full article

The aging of supercapacitors (SCs) depends on several factors, with temperature being one of the most important. When this is high, degradation of the electrolyte occurs. The impurities generated in its decomposition reduce the accessibility of the ions to the porous structure on the surface of the electrode, which reduces its capacity and increases its internal resistance. In some applications, such as electric vehicles whose storage system consists of SCs, fast chargers, which supply very high power, are used. This can lead to an increase in temperature and accelerated aging of the cells. Therefore, it is important to know how the temperature of the SCs evolves in these cases and what parameters it depends on, both electrical and thermal. In this contribution, mathematical formulae have been developed to determine the evolution of the temperature in time and its maximum value during the transient state. The formulae for obtaining the mean and maximum temperature, once the thermal steady state (TSS) has been reached, are also shown, considering that the charger cells are recharged from the grid at a constant current. Based on this formulation, the thermal analysis of a specific case is determined. Full article

Aiming at the electrical safety problem of a high-voltage lithium-ion battery system caused by an arc, and based on the establishment of a battery arc fault experimental platform, the evolution law of safety caused by an arc in the negative terminal of a battery system under different working conditions is discussed. On this basis, a battery arc evolution model based on magnetohydrodynamics is established to analyze the arc’s electro-thermal coupling characteristics to further obtain the distribution of the arc’s multi-physical field. The results show that the arc generated by the high-voltage grade battery pack will break down the cell’s shell and form a hole, resulting in electrolyte leakage. When the loop current is 10 A, the evolution law of arc voltage and current is basically the same under different supply voltages, charges, and discharges. The accuracy of the battery arc simulation model is verified by comparing the simulation with the experimental results. The research in this paper provides a theoretical basis for the electrical safety design of lithium-ion batteries caused by the arc, fills the gaps in the field of battery system arc simulation, and is of great significance for improving the safety performance of arc protection. Full article

To estimate the state of health, charge, power, and safety (SoX) of lithium-ion batteries (LiBs) in real time, battery management systems (BMSs) need accurate and efficient battery models. The full-order partial two-dimensional (P2D) model is a common physics-based cell-level LiB model that faces challenges for real-time BMS implementation due to the complexity of its numerical solver. In this paper, we propose a method to discretise the P2D model equations using the Finite Volume and Verlet Integration Methods to significantly reduce the computational complexity of the solver. Our proposed iterative solver uses novel convergence criteria and physics-based initial guesses to provide high fidelity for discretised P2D equations. We also include both the kinetic-limited and diffusion-limited models for Solid Electrolyte Interface (SEI) growth into an iterative P2D solver. With these SEI models, we can estimate the capacity fade in real time once the model is tuned to the cell–voltage curve. The results are validated using three different operation scenarios, including the 1C discharge/charge cycle, multiple-C-rate discharges, and the Lawrence Livermore National Laboratory dynamic stress test. The proposed solver shows at least a 4.5 times improvement in performance with less than 1% error when compared to commercial solvers. Full article

Block copolymers (BCPs) as solid electrolytes for batteries are usually designed to have an ion-solvating block for ion conduction and an ionophobic block for providing mechanical strength. Here, we show a novel solid polymer electrolyte (SPE) for sodium batteries based on a poly(vinyl benzoate)-b-poly(diallyldimethyl ammonium bis(trifluoromethanesulfonyl)imide) PVB_x-b-PDADMATFSI_y-b-PVB_x ABA triblock copolymer. The SPE triblock copolymer comprises a polymerized ionic liquid (PIL) ion-solvating block combined with NaFSI salt as an internal block and an ionophilic PVB as an external block. Four distinct compositions with varying chain lengths of the blocks were synthesized by reversible addition−fragmentation chain-transfer (RAFT) polymerization. The neat copolymers were subsequently mixed with NaFSI in a 2:1 mol ratio of Na to ionic monomer units. Through comprehensive analysis using differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR), it was revealed that the ion coordination within the polymer–salt mixtures undergoes changes based on the composition of the starting neat polymer. Electrochemical evaluations identified the optimal composition for practical application as PVB_11.5K-b-PDADMATFSI_33K-b-PVB_11.5K, showing an ionic conductivity at 70 °C of 4.2 × 10⁻⁵ S cm⁻¹. This polymer electrolyte formulation was investigated for sodium in Na|Na symmetrical cells, showing an overpotential of 200 mV at 70 °C at 0.1 mA cm⁻². When applied in a sodium–air battery, the polymer electrolyte membrane achieved a discharge capacity of 1.59 mAh cm⁻² at 50 °C. Full article

The aim of this study is to investigate new materials that can be employed as cathode hosts in Li-S batteries, which would be able to overcome the effect of the shuttling of soluble polysulfides and maximize the battery capacity and energy density. Density functional theory (DFT) simulations are used to determine the adsorption energy of lithium sulfides in two types of cathode hosts: lithiated 1T-MoS₂ (1T-Li_xMoS₂) and hybrid 1T-Li_xMoS₂/graphene. Initial simulations of lithiated 1T-MoS₂ structures led to the selection of an optimized 1T-Li_0.75MoS₂ structure, which was utilized for the formation of an optimized 1T-Li_0.75MoS₂ bilayer and a hybrid 1T-Li_0.75MoS₂/graphene bilayer structure. It was found that all sulfides exhibited super-high adsorption energies in the interlayer inside the 1T-Li_0.75MoS₂ bilayer and very good adsorption energy values in the interlayer inside the hybrid 1T-Li_0.75MoS₂/graphene bilayer. The placement of sulfides outside each type of bilayer, over the 1T-Li_0.75MoS₂ surface, yielded good adsorption energies in the range of −2 to −3.8 eV, which are higher than those over a 1T-MoS₂ substrate. Full article

The aging mechanism of 10% and 30% nickel-substituted manganese hexacyanoferrate cathode material in aqueous zinc-ion batteries has been explored through the advanced synchrotron-based two-dimensional X-ray fluorescence technique. Thanks to the two-dimension modality, not only were the metal concentration dynamics throughout the entire electrodes followed during the aging process, but their spatial distribution was also revealed, suggesting the route of the material transformation. The dissolution of Mn and Ni, as well as the penetration of Zn inside the framework were detected, while the Mn aggregations were found outside the hexacyanoferrate framework. Additionally, the possibility of conducting X-ray absorption spectroscopy measurements on the regions of interest made it possible to explore the chemical state of each metal, and furthermore, synchrotron-based powder X-ray diffraction demonstrated the gradual structural modification in 30% Ni-containing sample series in terms of the different phase formation. Full article

A MnO₂/AgNP nanocomposite was synthesized using a sonochemical method and investigated as an electrode material in a solid-state hybrid supercapacitor. Aquivion’s sodium and lithium electrolyte membrane serves as an electrolyte and separator. For comparison, MnO₂ was used as the active material. The developed supercapacitor containing a carbon xerogel as a negative electrode, the MnO₂/AgNP composite as a positive electrode and a Na⁺-exchange membrane demonstrated the highest performance characteristics. These results indicate that the incorporation of silver nanoparticles into the MnO₂ structure is a prospect for obtaining an active composite electrode material for solid-state supercapacitors. Full article

Developing cost-effective cathode materials is conducive to accelerating the commercialization of sodium-ion batteries. Na₄Fe₃(PO₄)₂P₂O₇ (NFPP) has attracted extensive attention owning to its high theoretical capacity, stable structure, and low cost of raw materials. However, its inherent low conductivity hinders its further application. Herein, carbon-coated NFPP nanospheres are anchored to crumpled MXene nanosheets by an electrostatic self-assembly; this cross-linked structure induced by CTAB not only significantly expands the contact area between particles and improves the electronic conductivity, but also effectively reduces the aggregation of NFPP nanoparticles. The as-designed Na₄Fe₃(PO₄)₂(P₂O₇)@C/Ti₃C₂T_x (NFPP@MX) cathode exhibits a high discharge capacity (106.1 mAh g⁻¹ g at 0.2 C), good rate capability (60.4 mAh g⁻¹ at 10 C), and a long-life cyclic stability (85.2% capacity retention after 1000 cycles at 1 C). This study provides an effective strategy for the massive production of high-performance NFPP cathodes and broadens the application of MXene in the modification of other cathode materials. Full article