Search Results (1,575)

Lithium-rich manganese-based oxides (LMR) are promising next-generation cathode materials due to their high capacity and low cost, but safety remains a critical bottleneck restricting the practical application of high-energy-density cathodes. However, the safety level of LMR batteries and the thermal failure mechanism of the cathode are still poorly understood, especially when compared with traditional high-energy nickel-rich (Ni-rich) cathodes. Here, we investigate the LMR cell’s thermal runaway behavior and the thermal failure mechanism of the cathode. Compared to a Ni-rich cell, Accelerating Rate Calorimetry (ARC) shows the LMR pouch cell exhibits a 62.7 °C higher thermal runaway trigger temperature (T2) and 270.3 °C lower maximum temperature (T3). These results indicate that the cell utilizing a higher-energy-density LMR cathode presents significantly lower thermal runaway risks and hazards. The results of differential scanning calorimetry–thermogravimetry–mass spectrometry (DSC-TG-MS) and in situ heating X-ray diffraction (XRD) indicate that the LMR cathode has superior thermal stability compared with the Ni-rich cathode, with cathode oxygen released at higher temperatures and lower rates, which is beneficial for delaying and mitigating the exothermic reaction inside the battery. This study demonstrates that simultaneously enhancing cathode energy density and battery safety is achievable, and these findings provide theoretical guidance for the design of next-generation high-energy and high-safety battery systems. Full article

The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development of advanced battery technologies has become a critical priority. However, progress in electrochemical storage systems remains limited due to persistent technological barriers such as gaps in data, inadequate modeling tools, and difficulties in system integration, such as thermal management and interface instability. Safety concerns like thermal runaway and the lack of long-term performance data also hinder large-scale adoption. This study presents an in-depth analysis of lithium–ion (Li–ion) batteries, with a particular focus on evaluating their charging and discharging behaviors. To facilitate this, a series of automated experiments was conducted using a custom-built test bench equipped with MATLAB (2024b) programming and dSPACE data acquisition cards, enabling precise current and voltage measurements. The acquired data were analyzed to derive mathematical models that capture the operational characteristics of Li–ion batteries. Furthermore, various state-of-charge (SoC) estimation techniques were investigated to enhance battery efficiency and improve range management in EVs. This paper contributes to the advancement of energy storage technologies and supports global ecological goals by proposing safer and more efficient solutions for the electric mobility sector. Full article

Accurate modeling and performance analysis of brushless DC (BLDC) motors are essential for high-efficiency control in modern drive systems. In this article, a BLDC motor was modeled using system identification techniques. In addition, experimental data were collected from the BLDC motor, including its speed response to various input signals. Using system identification tools, particularly those provided by MATLAB/Simulink R2024b, an approximation model of the BLDC motor was constructed to represent the motor’s dynamic behavior. The identified model was experimentally validated using various input signals, demonstrating its accuracy and generalizability under different operating conditions. Additionally, a series of mechanical load tests was conducted using the AVL eddy-current dynamometer to evaluate performance under practical operating conditions. Fixed load torques were applied across a range of motor speeds, and multiple torque levels were tested to assess the motor’s dynamic response. Electrical power, mechanical power, and efficiency of the entire system were computed for each case to assess overall system performance. Moreover, the real-time state of charge (SOC) of Lithium-ion (Li-ion) battery was estimated using the Coulomb counting method to analyze the impact of Li-ion battery energy level on the BLDC motor efficiency. The study offers valuable insights into the motor’s dynamic and energetic behavior, forming a foundation for robust control design and real-time application development. Full article

Silicon carbide (SiC) and silicon nanoparticle-decorated carbon (Si/C) materials are electrodes that can potentially be used in various rechargeable batteries, owing to their inimitable merits, including non-flammability, stability, eco-friendly nature, low cost, outstanding theoretical capacity, and earth abundance. However, SiC has inferior electrical conductivity, volume expansion, a low Li⁺ diffusion rate during charge–discharge, and inevitable repeated formation of a solid–electrolyte interface layer, which hinders its commercial utilization. To address these issues, extensive research has focused on optimizing preparation methods, engineering morphology, doping, and creating composites with other additives (such as carbon materials, metal oxides, nitrides, chalcogenides, polymers, and alloys). Owing to the upsurge in this research arena, providing timely updates on the use of SiC and Si/C for batteries is of great importance. This review summarizes the controlled design of SiC-based and Si/C composites using various methods for rechargeable metal-ion batteries like lithium-ion (LIBs), sodium-ion (SIBs), zinc-air (ZnBs), and potassium-ion batteries (PIBs). The experimental and predicted theoretical performance of SiC composites that incorporate various carbon materials, nanocrystals, and non-metal dopants are summarized. In addition, a brief synopsis of the current challenges and prospects is provided to highlight potential research directions for SiC composites in batteries. Full article

Lithium-ion batteries (LIBs) have attracted extensive attention as a distinguished electrochemical energy storage system due to their high energy density and long cycle life. However, the initial irreversible lithium loss during the first cycle caused by the formation of the solid electrolyte interphase (SEI) leads to the prominent reduction in the energy density of LIBs. Notably, lithium formate (HCOOLi, LFM) is regarded as a promising cathode prelithiation reagent for effective lithium supplementation due to its high theoretical capacity of 515 mAh·g⁻¹. Nevertheless, the stable Li-O bond of LFM brings out the high reaction barrier accompanied by the high decomposition potential, which impedes its practical applications. To address this issue, a feasible strategy for reducing the reaction barrier has been proposed, in which the decomposition potential of LFM from 4.84 V to 4.23 V resulted from the synergetic effects of improving the electron/ion transport kinetics and catalysis of transition metal oxides. The addition of LFM to full cells consisting of graphite anodes and LiNi_0.834Co_0.11Mn_0.056O₂ cathodes significantly enhanced the electrochemical performance, increasing the reversible discharge capacity from 156 to 169 mAh·g⁻¹ at 0.1 C (2.65–4.25 V). Remarkably, the capacity retention after 100 cycles improved from 72.8% to 94.7%. Our strategy effectively enables LFM to serve as an efficient prelithiation additive for commercial cathode materials. Full article

The transition to high-energy-density lithium metal batteries (LMBs) is essential for advancing electric vehicle (EV) technologies beyond the limitations of conventional lithium-ion batteries. A key challenge in scaling LMB production is the precise, contamination-free separation of lithium metal (LiM) anodes, hindered by lithium’s strong adhesion to mechanical cutting tools. This study investigates high-speed, contactless laser cutting as a scalable alternative for shaping double-coated LiM anodes. The effects of pulse duration, pulse energy, repetition frequency, and scanning speed were systematically evaluated using a nanosecond pulsed laser system on 30 µm LiM foils laminated on both sides of an 8 µm copper current collector. A maximum single-pass cutting speed of 3.0 m/s was achieved at a line energy of 0.06667 J/mm, with successful kerf formation requiring both a minimum pulse energy (>0.4 mJ) and peak power (>2.4 kW). Cut edge analysis showed that shorter pulse durations (72 ns) significantly reduced kerf width, the heat-affected zone (HAZ), and bulge height, indicating a shift to vapor-dominated ablation, though with increased spatter due to recoil pressure. Optimal edge quality was achieved with moderate pulse durations (261–508 ns), balancing energy delivery and thermal control. These findings define critical laser parameter thresholds and process windows for the high-speed, high-fidelity cutting of double-coated LiM battery anodes, supporting the industrial adoption of nanosecond laser systems in scalable LMB electrode manufacturing. Full article

With the advancement of global carbon reduction efforts and the rapid development of battery industries, the scale of spent lithium-ion batteries (LIBs) has increased dramatically. Extracting lithium from spent LIBs to synthesize Li₄SiO₄ sorbents not only addresses the challenge of battery recycling but also reduces the production cost of CO₂ sorbents, making it a research hotspot. However, the CO₂ adsorption behavior of these sorbents under the effect of impurities may differ from the traditional Li₄SiO₄, and there is a lack of systematic research on the adsorption kinetics. To address this issue, two Li₄SiO₄ sorbents are prepared from spent ternary LIBs, and their adsorption kinetics are comprehensively investigated using classical kinetic models. Results show that the reaction order of LSO and Na-LSO is 0.41 and 1.63, respectively, with activation energies of 72.93 kJ/mol and 99.23 kJ/mol in the initial kinetic-controlled stage, and 323.15 kJ/mol and 176.79 kJ/mol in the following diffusion-controlled stage. In the cyclic processes, loss-in-capacity is observed on LSO due to the simultaneous decrease in rate constants in both the kinetic and diffusion-controlled stages, while Na-LSO could almost maintain its capacity by having a much bigger rate constant during the kinetic-controlled stage. This study reveals the adsorption kinetics of Li₄SiO₄ prepared from spent LIBs and could provide theoretical support for the targeted design of efficient and low-cost CO₂ sorbents. Full article

With the rapid advancement of new energy electric vehicles, high-capacity nickel-rich layered oxides have emerged as predominant cathode materials in lithium-ion battery systems. However, their widespread implementation necessitates rigorous investigation into cycling stability. We synthesized nickel-manganese-aluminum hydroxide precursors as raw materials by co-precipitation method, and synthesized ultrathin Al₂O₃-coated LiNi_0.9Mn_0.05Al_0.05O₂ cathode materials by hydrolysis reaction. The cathode material was uniformly covered by an Al₂O₃ layer with an average thickness of 5–10 nm by high resolution transmission electron microscopy (HRTEM). Electrochemical performance tests showed that the modified cathode material exhibited significantly enhanced reversible capacity, cycling stability, and rate performance, and a more favorable differential capacity curve. In particular, the LNMA-2 samples were able to maintain 90.6% and 88.3% of their initial capacity after 100 cycle tests (with cutoff voltages of 4.3 and 4.5 V, respectively) at 0.5 C charge/discharge rate. These improved electrochemical properties are mainly attributed to the advantages offered by the unique Al₂O₃ coating structure. This study provides significant theoretical value for designing and optimizing the production of high-nickel cobalt-free cathode materials with high cycling performance. Full article

The energy generated from renewable sources has an intermittent nature since solar irradiation and wind speed vary continuously. Hence, their energy should be stored to be utilized throughout their shortage. There are various forms of energy storage systems while the most widespread technique is the battery storage system since its cost is low compared to other techniques. Therefore, batteries are employed in several applications like power systems, electric vehicles, and smart grids. Due to the merits of the lithium-ion (Li-ion) battery, it is preferred over other kinds of batteries. However, the accuracy of the Li-ion battery model is essential for estimating the state of charge (SOC). Additionally, it is essential for consistent simulation and operation throughout various loading and charging conditions. Consequently, the determination of real battery model parameters is vital. An innovative application of the red-billed blue magpie optimizer (RBMO) for determining the model parameters and the SOC of the Li-ion battery is presented in this article. The Shepherd model parameters are determined using the suggested optimization algorithm. The RBMO-based modeling approach offers excellent execution in determining the parameters of the battery model. The suggested approach is compared to other programmed algorithms, namely dandelion optimizer, spider wasp optimizer, barnacles mating optimizer, and interior search algorithm. Moreover, the suggested RBMO is statistically evaluated using Kruskal–Wallis, ANOVA tables, Friedman rank, and Wilcoxon rank tests. Additionally, the Li-ion battery model estimated via the RBMO is validated under variable loading conditions. The fetched results revealed that the suggested approach achieved the least errors between the measured and estimated voltages compared to other approaches in two studied cases with values of 1.4951 × 10⁻⁴ and 2.66176 × 10⁻⁴. Full article

In this study, we successfully synthesized olivine-type FePO₄ via an in situ oxidation method and further developed two composite cathode materials (o-FePO₄-1/GR-1 and o-FePO₄-1/GR-2) by incorporating graphene. The composites were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray Photoelectron Spectroscopy (XPS), revealing a three-dimensional porous layered structure with an enhanced surface area and strong interaction between FePO₄ nanoparticles and graphene layers. Electrochemical tests demonstrated that the composite electrodes exhibited significantly improved performance compared to pristine FePO₄, with discharge capacities of 147 mAh g⁻¹ at 1C and 163 mAh g⁻¹ at 0.1C for o-FePO₄-1/GR-2, approaching the level of LiFePO₄. The incorporation of graphene effectively enhanced the electrochemical reaction kinetics, highlighting the innovation of our method in developing high-performance cathode materials for lithium-ion batteries. Full article

In this work, graphite anodes and lithium iron phosphate (LFP) cathodes are used to examine the effects of sodium hexafluorophosphate (NaPF₆) and potassium hexafluorophosphate (KPF₆) electrolyte additives on the formation of the solid electrolyte interphase and the performance of lithium-ion batteries in both half-cell and full-cell designs. The objective is to assess whether these additives may increase cycle performance, decrease irreversible capacity loss, and improve interfacial stability. Compared to the control electrolyte (1.22 M Lithium hexafluorophosphate (LiPF₆)), cells with NaPF₆ and KPF₆ additives produced less SEI products, which decreased irreversible capacity loss and enhanced initial coulombic efficiency. Following the formation of the solid electrolyte interphase, the specific capacity of the control cell was 607 mA·h/g, with 177 mA·h/g irreversible capacity loss. In contrast, irreversible capacity loss was reduced by 38.98% and 37.85% in cells containing KPF₆ and NaPF₆ additives, respectively. In full cell cycling, a considerable improvement in capacity retention was achieved by adding NaPF₆ and KPF₆. The electrolyte, including NaPF₆, maintained 67.39% greater capacity than the LiPF₆ baseline after 20 cycles, whereas the electrolyte with KPF₆ demonstrated a 30.43% improvement, indicating the positive impacts of these additions. X-ray photoelectron spectroscopy verified that sodium (Na⁺) and potassium (K⁺) ions were present in the SEI of samples containing NaPF₆ and KPF₆. While K⁺ did not intercalate in LFP, cyclic voltammetry confirmed that Na⁺ intercalated into LFP with negligible impact on the energy storage of full cells. These findings demonstrate that NaPF₆ and KPF₆ are suitable additions for enhancing lithium-ion battery performance in the popular artificial graphite/LFP system. Full article

Polyethylene oxide (PEO) is the most well-studied polymer used in solid polymer electrolytes (SPEs) for lithium ion batteries (Li-ion batteries). However, ionic conductivity is greatly reduced in the low temperature range due to the crystallization of PEO. Therefore, methods to suppress the crystallization of PEO at room temperature by cross-linking or introducing a branched structure are currently being investigated. In this study, we synthesized new comb-type ion-conducting polyethers with two different side chains such as polydimethylsiloxane (PDMS) and polyethylene glycol monomethyl ether (mPEG) segments as flexible and ion-conducting segments, respectively. The introduction of the PDMS segment was found to prevent a decrease in ionic conductivity in the low-temperature region, but led to an ionic conductivity decrease in the high temperature region. On the other hand, the introduction of mPEG segments improved ionic conductivity in the high-temperature region. The introduction of mPEG segments with longer chains resulted in a significant decrease in ionic conductivity in the low-temperature region. Full article

This study presents a hybrid method for state-of-charge (SOC) estimation of lithium-ion batteries using LSTM neural networks optimized with genetic algorithms (GA), combined with Coulomb Counting (CC) as an initial estimator. Experimental tests were conducted using medium-voltage (48–72 V) lithium-ion battery packs under standardized driving cycles (NEDC and WLTP). The proposed method enhances prediction accuracy under dynamic conditions by recalibrating the LSTM output with CC estimates through a dynamic fusion parameter $\alpha$. The novelty of this approach lies in the integration of machine learning and physical modeling, optimized via evolutionary algorithms, to address limitations of standalone methods in real-time applications. The hybrid model achieved a mean absolute error (MAE) of 0.181%, outperforming conventional estimation strategies. These findings contribute to more reliable battery management systems (BMS) for electric vehicles and second-life applications. Full article

This study aims to develop a method for analyzing real-world battery degradation in electric vehicles in order to identify the optimal battery management system (BMS) during the early digital phase of vehicle development. Battery management of lithium-ion batteries (LiBs) in electric vehicles is important to ensure a stable output and to counteract degradation and thermal runaway. To design the optimal system, it is most effective to use a 1D (one-dimensional) vehicle system simulation model, which connects each unit model inside the vehicle, due to the system’s complexity. In order to create a long-term degradation simulation in a vehicle system model, it is important to reduce computational load. Therefore, in this paper, we studied a suitable battery degradation calculation for the vehicle system model based on an equivalent circuit model (ECM) and degradation approximation formulas. After implementing these models, we analyzed long-term degradation behavior through the real-world operation of an electric vehicle driver. We first implemented a high-accuracy ECM using transient charge–discharge tests and Bayesian Optimization. Next, we formulated approximation formulas for degradation prediction based on calendar and cycle degradation tests. Finally, we simulated real-world degradation behavior using these models. The simulation results revealed that even for users who frequently use electric vehicles, degradation under storage conditions is the dominant factor in overall degradation. Full article

Lithium-ion batteries (LiBs) are utilized in numerous applications due to advancements in technology, and the recovery of end-of-life (EoL) LiBs is imperative for environmental and economic reasons. Pyrometallurgical and hydrometallurgical methods have been used in the recovery of metals such as Li, Co, and Ni in the EoL LiBs. Hydrometallurgical methods, which have been demonstrated to exhibit higher recovery efficiency and reduced energy consumption, have garnered increased attention in recent research. Inorganic acids, including HCl, HNO₃, and H₂SO₄, as well as organic acids such as acetic acid and citric acid, are employed in the hydrometallurgical recovery of these metals. It is imperative to acknowledge the environmental hazards posed by these acids. Consequently, solvometallurgical processes, which involve the use of organic solvents with minimal or no water, are gaining increasing attention as alternative or complementary techniques to conventional hydrometallurgical processes. In the context of solvent systems that have been examined for a range of solvometallurgical methods, deep eutectic solvents (DESs) have garnered particular interest due to their low toxicity, biodegradable nature, tunable properties, and efficient metal recovery potential. In this study, the leaching process of black mass containing graphite, LCO, NMC, and LMO was carried out in a short time using the ternary DES system. The ternary DES system consists of choline chloride (ChCl), glycolic acid (GLY), and ascorbic acid (AA). As a result of the leaching process of cathode powders in the black mass without any pre-enrichment process, Li, Co, Ni, and Mn elements passed into solution with an efficiency of over 95% at 60 °C and within 1 h. Moreover, the kinetics of the leaching process was investigated, and Density Functional Theory (DFT) calculations were used to explain the leaching mechanism. Full article