Ionics最新文献

Accurately estimating the state of charge (SOC) and state of power (SOP) of the battery is essential for optimizing the use of electric quantity and ensuring the safe and efficient operation and energy management of the battery system of electric vehicles. In this paper, a particle swarm optimization algorithm is used to identify the model parameters of lithium-ion batteries under wide temperature range, and a SOC estimation method of adaptive cubature Kalman filter algorithm based on singular value decomposition (SVD-ACKF) is proposed. The Cholesky decomposition of covariance of state variables is replaced by singular value decomposition, which successfully avoids the problem of the non-positive definite matrix during the adaptive updating of the cubature Kalman filter algorithm, and improves the convergence stability of the iterative computation process. Based on accurate SOC estimation at each temperature, the key constraints in this study are composed of the combination of the SOC, voltage, and current of the battery, and changes in battery model parameters due to ambient temperature are considered, developing an SOP estimation strategy under multi-constraint conditions, realizing the joint estimation of SOC and SOP, verifying the feasibility of the proposed state estimation algorithm in different ambient temperatures. The results show that the maximum error of SOC estimation under different ambient temperatures is less than 0.015, and the SOC estimation error of the proposed method is the smallest compared with the extended Kalman filter (EKF) and the cubature Kalman filter (CKF), and the average relative errors of peak charge power and peak discharge power estimation with a duration of 30 s at 25 °C can be kept within 2.5% and 1.5%, respectively. It is proved that the proposed method has good accuracy and adaptability.

As a large-scale energy storage battery, the all-vanadium redox flow battery (VRFB) holds great significance for green energy storage. The electrolyte, a crucial component utilized in VRFB, has been a research hotspot due to its low-cost preparation technology and performance optimization methods. This work provides a comprehensive review of VRFB principles and structure, V₂O₅ price speculation, and VRFB electrolyte preparation and modification. The effects of three types of additives on positive and negative vanadium electrolytes are particularly emphasized. Furthermore, a preliminary analysis of the environmental and recyclability impacts of vanadium electrolyte preparation methods and additive modifications is presented. Lastly, future research directions for vanadium electrolyte preparation technology and additives to enhance performance are anticipated.

One of the foremost challenges currently faced by society pertains to the accessibility of renewable power generation in order to sustain the growth and productivity of civilization. Solid-state batteries offer a multitude of advantages in many energy storage applications. The objective of this work is to examine the synthesis and analysis of solid biopolymer electrolytes in primary proton batteries. A polymer electrolyte composed of guar gum as the polymer host, ammonium bromide as the salt dopant, and propylene carbonate as the plasticizer was synthesized utilizing the solution casting process. The maximum ionic conductivity of 1.38 × 10⁻⁴ Scm⁻¹ is obtained for the sample with 25 wt% of propylene carbonate. Investigation of temperature-dependent conductivity indicates the developed electrolyte obeys Arrhenius behaviour. XRD has been employed to investigate the amorphous characteristics of the prepared electrolyte. The study of the complexation between the polymer and the salt is conducted using the Fourier transform infrared (FTIR) technique. Transference number measurement indicates that the majority contribution of conductivity is through ions. The highest conducting membrane is electrochemically stable up to 1.48 V.

Titanium dioxide (TiO₂) has been widely studied as an inexpensive and efficient electrochromic material. However, slow response speed and poor cycling performance still constrain the further application of TiO₂ electrochromic materials. In this work, a series of cobalt-doped TiO₂ electrochromic films were fabricated via hydrothermal method combined with a spin-coated approach. The effects of doped cobalt ions on the electrochemical and electrochromic performance of TiO₂ were explored. The cobalt-doping concentrations on the morphology and electrochromic performance of the samples were investigated by means of XRD, XPS, FESEM, HR-TEM, and electrochemical techniques. It is found that the ionic diffusion coefficient of the 0.5% Co-TiO₂ composite film is 6.44 × 10⁻¹⁰ cm²/s, the coloring efficiency is 34.11 cm²/C, and the coloring and bleaching switching time are 1.92 s and 10.71 s, respectively. Moreover, the 0.5% and 1% Co-TiO₂ composite films showed superior cyclic performance than pristine TiO₂. This indicates that the appropriate amount of Co doping can significantly enhance the electrochromic properties of titanium dioxide films.

Lithium-sulfur batteries have great potential for application in next generation energy storage. However, the further development of lithium-sulfur batteries is hindered by various problems, especially three main issues: poor electronic conductivity of the active materials, the severe shuttle effect of polysulfide, and sluggish kinetics of polysulfide conversion. Therefore, it is important to overcome these above problems. In this work, carbon/Co₃O₄ composite heterostructures are designed to deal with these problems. The Co₃O₄ particles imbedded into carbon matrix with high-electronic conductivity could maximize the synergistic effect that stems from the advantages of each component. The carbon/Co₃O₄ (C/CO) hosts have advantages of excellent catalytic activity, effectively confining polysulfide and thereby inhibiting the shuttle effect. As a result, the C/CO@S cathode exhibits high initial specific capacity of 1116 mAh/g at 0.1 °C. This work provides a novel strategy to design cathode host for advanced lithium–sulfur batteries.

To address the challenge of low electronic and ionic conductivities in lithium-ion batteries (LIBs), we synthesized oxidized mixed-phase Ti₃C₂T_x MXene nanosheets using a wet chemical etching route. This prepared negative electrode demonstrated a reversible specific discharge capacity of 538.49 mAh/g at 0.1C (67 mA/g), which is significantly higher than the pristine MXene and retained 75.46% of its initial capacity during the rate performance test. During its testing for cycling stability, it demonstrated a stable discharge capacity of 383.33 mAh/g after 264 cycles at 0.1C (67 mA/g) and showed an increasing profile with a rosed capacity of 551.98 mAh/g after 404 cycles at 0.4C (268 mA/g). The exceptional electrochemical performance is attributed to the Ti₃C₂T_x MXene architecture, with oxidation of its nanosheets resulting in an increase in exposed Li⁺ sites leading to structural stability. The galvanostatic intermittent titration technique (GITT) was performed for the numerical analysis of Li⁺ mobility. To analyze the effective charge storage mechanism, electrochemical impedance spectroscopy (EIS) was also performed. This MXene electrode is found to be a promising negative electrode with a simple synthesis route demonstrating enhanced electrochemical performance and stability.

The growing demand for sustainable energy has fueled advancements in bio-fuel cells. Pencil graphite–based electrodes, known for their electrochemical properties and affordability, are increasingly valued. The major aim of the study is to develop an eco-friendly, cost-effective for modifying pencil graphite electrodes (PGE) using plant-based iron nanoparticles, targeting advancements in biofuel cells. Iron nanoparticles synthesized via green methods were analyzed using UV–visible spectroscopy (UV–Vis), X-ray photon spectroscopy (XPS), scanning electron microscopy (SEM), and energy dispersive X-ray analyzer (EDX). Their electrochemical properties, when coated on PGL from various plant extracts, were analyzed using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and open circuit potential (OCP). This study also involves optimization of iron nanoparticle–coated pencil graphite electrodes (FeNP/PGE) using a central composite design (CCD) model. Independent variables were selected and optimized, with their effects correlated to the current density and the effective surface area (ESA) of the modified PGEs. The R² and adjusted R² values, 0.9992 and 0.9984, respectively, demonstrate that the model is significant. The optimum conditions for maximum current density were obtained at temperature (70 °C), Rosa centifolia flower as an extract, thickness of graphite electrode (0.7 mm), and scan rate (50 mV/s). The maximum current density of 2790.13 μA cm⁻² with an effective surface area of 0.3991 cm² (0.7 mm HB-grade) clearly shows the model predicted was accurate resulting in higher potential in biofuel cells.

This work introduces a template-free approach for the direct activation of resorcinol–formaldehyde/thiourea polymer to synthesize O-, N-, and S-tridoped carbon spheres (TDCSs) and further discusses the effect of the ratio between thiourea and resorcinol on the electrochemical performances. The interconnected spherical morphology of TDCSs facilitates the formation of conductive networks, enabling electron transfer over shorter pathways, while the stacked porosity acts as ion reservoirs, promoting rapid ion diffusion. Additionally, the large surface area and high heteroatom content of the TDCSs enhance double-layer capacitance and provide additional pseudocapacitance. Consequently, the typical TDCS-2 electrode displays outstanding electrochemical performance, achieving a high specific capacitance of up to 319 F g⁻¹ at 0.2 A g⁻¹ and excellent long-term stability (92.4% retention after 10,000 cycles at 5 A g⁻¹) in 6 M KOH-loaded symmetric supercapacitor (KOH-SS). Moreover, the assembled KOH-SS demonstrates a noteworthy energy density of 11.08 Wh kg⁻¹ and a power density of 5000 W kg⁻¹. This study provides a straightforward and efficient method for fabricating heteroatoms doped carbon spheres for high-performance energy storage applications.

Accurate estimation of the state of health (SOH) of lithium batteries is crucial to ensure the reliable and safe operation of lithium batteries. Aiming at the problems of low accuracy of extreme learning machine and poor mapping ability of conventional kernel function, this paper constructs a kernel extreme learning machine model and uses a multi-strategy improved dung beetle algorithm to find the optimal parameters. In this paper, for the poor estimation effect caused by the difficulty of adapting the conventional kernel function to nonlinear batteries, we design a cosine polynomial kernel function, which improves the linear divisibility of the data; in addition, for the global search, local development, and convergence improvement of the dung beetle algorithm, we introduce the optimal Latin hypercubic idea, the Cauchy variation strategy, and the sparrow alert mechanism, which successfully improve the parameter searching capability and sensitivity of the algorithm, respectively. We successfully improve the capability and sensitivity of the algorithm in parameter searching. We experimentally verify the reliability and validity of the proposed model, and the maximum root mean square error and the average absolute percentage error obtained in the test are not higher than 0.00753 and 0.00399, respectively, and the minimum fit is not lower than 0.9921, which reflects the high accuracy and strong adaptive ability of the model.