Search Results (16)

Lithium-ion batteries are the core energy storage technology for electric vehicles and energy storage systems. Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. This review systematically examines the research progress on SOC estimation techniques over a wide temperature range, focusing on two mainstream approaches: model improvement and data-driven methods. The model improvement method enhances temperature adaptability through temperature compensation and dynamic parameter adjustment. Still, it has limitations in dealing with the nonlinear behavior of batteries and accuracy and real-time performance at extreme temperatures. In contrast, the data-driven method effectively copes with temperature fluctuations and complex operating conditions by extracting nonlinear relationships from historical data. However, it requires high-quality data and substantial computational resources. Future research should focus on developing high-precision, temperature-adaptive models and lightweight real-time algorithms. Additionally, exploring the deep coupling of physical models and data-driven methods with multi-source heterogeneous data fusion technology can further improve the accuracy and robustness of SOC estimation. These advancements will promote the safe and efficient application of lithium batteries in electric vehicles and energy storage systems. Full article

As more renewable energy sources are integrated into the United Kingdom’s power grid, flexibility services are becoming integral to ensuring energy security. This has encouraged the proliferation of Lithium-ion battery storage systems, with 85 GW in development. However, battery degradation impacts both system lifespan and the economic viability of large-scale projects. With rising commodity costs and supply chain issues, maximising the value of energy storage is critical. Traditional methods of mitigating battery ageing rely on static limits based on inflexible warranties, which do not fully account for the complexity of battery degradation. This study examined an alternative, degradation-aware current derating strategy to improve system performance. Using an optimisation model simulating UK energy trading, combined with an electro-thermal and semi-empirical battery model, we assessed the impact of this approach. Interviews with industry leaders validated the modelled parameters and the relevance of the alternative strategy. Results show the degradation-aware strategy can extend battery lifetime by 5–8 years and improve net present value and internal rate of return over a 15-year period compared with traditional methods. These findings highlight the economic benefits of flexible, degradation-aware operational strategies and suggest that more adaptive warranties could accelerate renewable energy integration and lower costs for storage operators. Full article

This study presents the development of a ferrite core inductively coupled plasma (ICP) radio frequency (RF) ion source designed to improve the lifetime of ion sources in commercial ion implanters. Unlike existing DC methods, this novel approach aims to enhance the performance and lifetime of the ion source. We constructed a high-vacuum evaluation chamber to thoroughly examine RF ion source characteristics using a Langmuir probe. Comparative experiments assessed the extraction current of two upgraded ferrite core RF ion sources in a commercial ion implanter setting. Additionally, we tested the plasma lifetime of the ICP source and took temperature measurements of various components to verify the operational stability and efficiency of the innovative design. This study confirmed that the ICP RF ion source operated effectively under a high vacuum of 10⁻⁵ torr and in a high-voltage environment of 30 kV. We observed that the extraction current increased linearly with RF power. We also confirmed that BF₃ gas, which presents challenging conditions, was stably ionized in the ICP RF ion sources. 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

Lithium-ion battery health and remaining useful life (RUL) are essential indicators for reliable operation. Currently, most of the RUL prediction methods proposed for lithium-ion batteries use data-driven methods, but the length of training data limits data-driven strategies. To solve this problem and improve the safety and reliability of lithium-ion batteries, a Li-ion battery RUL prediction method based on iterative transfer learning (ITL) and Mogrifier long and short-term memory network (Mogrifier LSTM) is proposed. Firstly, the capacity degradation data in the source and target domain lithium battery historical lifetime experimental data are extracted, the sparrow search algorithm (SSA) optimizes the variational modal decomposition (VMD) parameters, and several intrinsic mode function (IMF) components are obtained by decomposing the historical capacity degradation data using the optimization-seeking parameters. The highly correlated IMF components are selected using the maximum information factor. Capacity sequence reconstruction is performed as the capacity degradation information of the characterized lithium battery, and the reconstructed capacity degradation information of the source domain battery is iteratively input into the Mogrifier LSTM to obtain the pre-training model; finally, the pre-training model is transferred to the target domain to construct the lithium battery RUL prediction model. The method’s effectiveness is verified using CALCE and NASA Li-ion battery datasets, and the results show that the ITL-Mogrifier LSTM model has higher accuracy and better robustness and stability than other prediction methods. Full article

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period. Full article

A series of composite CdS/TiO₂ powders was obtained by nucleation of TiO₂ on CdS nanoseeds. This combination presents the appropriate band edge position for photocatalytic redox reactions: visible light irradiation of CdS allows the injection of electrons into dark TiO₂, increasing the lifetimes of separated charges. The electrons have been used for the quantitative photoreduction of 4-nitrobenzaldehyde to 4-aminobenzaldehyde, whose formation was pointed out by ¹H NMR and ESI-MS positive ion mode. Concomitant sacrificial oxidation of 2-propanol, which was also the proton source, occurred. The use of characterization techniques (XRD, N₂ adsorption-desorption) evidenced the principal factors driving the photocatalytic reaction: the nanometric size of anatase crystalline domains, the presence of dispersed CdS to form an extended active junction CdS/anatase, and the presence of mesopores as nanoreactors. The result is an efficient photocatalytic system that uses visible light. In addition, the presence of TiO₂ in combination with CdS improves the stability of the photoactive material, enabling its recyclability. Full article

The capacity fade during the cycling of lithium batteries is a key factor limiting further progress in the improvement of electric vehicles, wearable electronic devices, alternative energy sources, etc. One of the main reasons for capacity loss is battery cathode degradation, which significantly influences the battery lifetime. Despite in-depth knowledge of battery degradation at the chemical level, the kinetics of the degradation at the resolution of the individual elements of the cathode are not fully understood. Here, we studied lithiation kinetics in commercial cathodes based on lithium manganese spinel using the electrochemical strain microscopy local method. Supported by the experimental finding, the “viscous fingers” model of lithium ions intercalation–deintercalation in individual particles of the cathode was proposed. The non-linear dynamics of the lithiation front were suggested to be stimulated by the non-uniform stress field and gradient of the chemical potential. Irregularity of the lithiation front causes the formation of the residual lithiated pocket in the delithiated particles, which effectively reduces the volume available for chemical reaction. The obtained results shed further light on the degradation of the lithium battery cathodes and can be applicable for other cathode materials. Full article

We fabricated a Yb:YAG crystal-derived silica fiber (YCDSF) by the melt-in-tube method with a CO₂ laser-heated drawing tower and explored the influences of the heat treatment method on fluorescent properties in the YCDSF. After the heat treatment, the intensity of the emission peaks and the fluorescence lifetime of the YCDSFs improved. In particular, after 1350 °C of heat treatment, a series of sharp peaks appeared in the core layer, which may form a new crystalline phase. Moreover, its emission intensity at 1030 nm was significantly enhanced, over 2 times greater than before the heat treatment. Additionally, the fluorescence lifetime of Yb ions was also increased from 129 to 621 μs, indicating the changes in local environments around Yb ions. Then, schematic models were set up to show how the local environments around Yb ions are gradually changing. These results revealed that the assessed YCDSF is of excellent performance; after the heat treatment, it may be a potential material for realizing optical amplification, light sources, fiber lasers, and so on. Full article

Nowadays, the growing integration of renewable energy sources poses several challenges to electrical energy systems. The latter need be controlled by grid rules to ensure their stability and maintain the efficiency of renewable energy consumption. In this context, a novel HESS (hybrid energy storage system) control strategy, combining the PV (photovoltaic) generator with FLC (fuzzy logic control), SC (super-capacitor), and lithium-ion battery modules, is advanced. The proposed energy control rests on monitoring of the low-frequency and high-frequency electrical power components of the mismatch between power demand and generation, while applying the error component of the lithium-ion battery current. On accounting for the climatic condition and load variation considerations, the SC undertakes to momentarily absorb the high-frequency power component, while the low-frequency component is diverted to the lithium-ion battery. To improve the storage system’s performance, lifetime, and avoid load total disconnection during sudden variations, we consider equipping the envisioned energy control design with controllers of SM and ANN types. The MATLAB/Simulink based simulation results turn out to testify well the investigated HESS control scheme’s outstanding performance and efficiency in terms of DC bus voltage rapid regulation, thereby enhancing the battery’s lifetime and ensuring the PV system’s continuous flow. Full article

Modern vehicles have increased functioning necessities, including more energy/power, storage for recovering decelerating energy, start/stop criteria, etc. However, lead-acid batteries (LABs) possess a shorter lifetime than lithium-ion and supercapacitors energy storage systems. The use of LABs harms the operation of transport vehicles. Therefore, this research paper pursues to improve the operating performance of LABs in association with their lifetime. Integrated LAB and supercapacitor improve the battery lifetime and efficiently provide for transport vehicles’ operational requirements and implementation. The study adopts an active-parallel topology approach to hybridise LAB and supercapacitor. A fully active-parallel topology structure comprises two DC-to-DC conversion systems. LAB and supercapacitor are connected as inputs to these converters to allow effective and easy control of energy and power. A cascaded proportional integrate-derivative (PID) controller regulates the DC-to-DC converters to manage the charge/release of combined energy storage systems. The PID controls energy share between energy storage systems, hence assisting in enhancing LAB lifetime. The study presents two case studies, including the sole battery application using different capacities, and the second, by combining a battery with a supercapacitor of varying capacity sizes. A simulation software tool, Matlab/Simulink, is used to develop the model and validate the results of the system. The simulation outcomes show that the battery alone cannot serve the typical transport vehicle (TV) requirements. The battery and output voltage of the DC-to-DC conversion systems stabilises at 12 V, which ensures consistent DC bus link voltage. The energy storage (battery) state-of-charge (SoC) is reserved in the range of 90% to 96%, thus increasing its lifespan by 8200 cycles. The battery is kept at the desired voltage to supply all connected loads on the DC bus at rated device voltage. The fully active topology model for hybrid LAB and supercapacitor provides a complete degree of control for individual energy sources, thus allowing the energy storage systems to operate as they prefer. Full article

New materials for advanced fission/fusion nuclear facilities must inevitably demonstrate resistance to radiation embrittlement. Thermal and radiation ageing accompanied by stress corrosion cracking are dominant effects that limit the operational condition and safe lifetime of the newest nuclear facilities. To study these phenomena and improve the current understanding of various aspects of radiation embrittlement, ion bombardment experiments are widely used as a surrogate for neutron irradiation. While avoiding the induced activity, typical for neutron-irradiated samples, is a clear benefit of the ion implantation, the shallow near-surface region of the modified materials may be a complication to the post-irradiation examination (PIE). However, microstructural defects induced by ion implantation can be effectively investigated using various spectroscopic techniques, including slow-positron beam spectroscopy. This method, typically represented by techniques of positron annihilation lifetime spectroscopy and Doppler broadening spectroscopy, enables a unique depth-profile characterisation of the near-surface region affected by ion bombardment or corrosion degradation. One of the best slow-positron beam facilities is available at the pulsed low-energy positron system (PLEPS), operated at FRM-II reactor in Munich (Germany). Bulk studies (such as high energy ion implantation or neutron irradiation experiments) can be, on the other hand, effectively performed using radioisotope positron sources. In this paper, we outline some basics of the two approaches and provide some recommendations to improve the validity of the positron annihilation spectroscopy (PAS) data obtained on ion-irradiated samples using a conventional ²²Na positron source. Full article

Currently, Lithium-ion batteries (LiB) are widely applied in energy storage devices in smart grids and electric vehicles. The state of charge (SOC) is an indication of the available battery capacity, and is one of the most important factors that should be monitored to optimize LiB’s performance and improve its lifetime. However, because the SOC relies on many nonlinear factors, it is difficult to estimate accurately. This paper presented the design of an effective SOC estimation method for a LiB pack Battery Management System (BMS) based on Kalman Filter (KF) and Artificial Neural Network (ANN). First, considering the configuration and specifications of the BMS and LiB pack, an ANN was constructed for the SOC estimation, and then the ANN was trained and tested using the Google TensorFlow open-source library. An SOC estimation model based on the extended KF (EKF) and a Thevenin battery model was developed. Then, we proposed a combined mode EKF-ANN that integrates the estimation of the EKF into the ANN. Both methods were evaluated through experiments conducted on a real LiB pack. As a result, the ANN and KF methods showed maximum errors of 2.6% and 2.8%, but the EKF-ANN method showed better performance with less than 1% error. Full article

Levofloxacin (LF) is a medically important antibiotic drug that is used to treat a variety of bacterial infections. In this study, three highly sensitive and selective carbon paste electrodes (CPEs) were fabricated for potentiometric determination of the LF drug: (i) CPEs filled with carbon paste (referred to as CPE); (ii) CPE coated (drop-casted) with ion-selective PVC membrane (referred to as C-CPE); (iii) CPE filled with carbon paste modified with a plasticizer (PVC/cyclohexanone) (referenced as P-CPE). The CPE was formulated from graphite (Gr, 44.0%) and reduced graphene oxide (rGO, 3.0%) as the carbon source, tricresyl phosphate (TCP, 47.0%) as the plasticizer; sodium tetrakis[3,5-bis(trifluoromethyl)phenyl] borate (St-TFPMB, 1.0%) as the ion exchanger; and levofloxacinium-tetraphenylborate (LF-TPB, 5.0%) as the lipophilic ion pair. It showed a sub-Nernstian slope of 49.3 mV decade⁻¹ within the LF concentration range 1.0 × 10⁻² M to 1.0 × 10⁻⁵ M, with a detection limit of 1.0 × 10⁻⁵ M. The PVC coated electrode (C-CPE) showed improved sensitivity (in terms of slope, equal to 50.2 mV decade⁻¹) compared to CPEs. After the incorporation of PVC paste on the modified CPE (P-CPE), the sensitivity increased at 53.5 mV decade⁻¹, indicating such improvement. The selectivity coefficient (${\log \mathrm{K}}_{{\mathrm{LF}}^{2+},{\mathrm{Fe}}^{+3}}^{\mathrm{pot}.}$) against different interfering species (Na⁺, K⁺, NH⁴⁺, Ca²⁺, Al³⁺, Fe³⁺, Glycine, Glucose, Maltose, Lactose) were significantly improved by one to three orders of magnitudes in the case of C-CPE and P-CPE, compared to CPEs. The modification with the PVC membrane coating significantly improved the response time and solubility of the LF-TPB within the electrode matrix and increased the lifetime. The constructed sensors were successfully applied for LF determination in pharmaceutical preparation (Levoxin^® 500 mg), spiked urine, and serum samples with high accuracy and precision. Full article

We describe some modifications to a Bernas-type ion source that improve the ion beam production efficiency and source operating lifetime. The ionization efficiency of a Bernas type ion source has been improved by using a small anode that is a thin rod, oriented along the magnetic field. The transverse electric field of the small anode causes the plasma to drift in the crossed ExB field to the emission slit. The cathode material recycling was optimized to increase the operating lifetime, and the wall potential optimized to suppress deposition of material and subsequent flake formation. A three-electrode extraction system was optimized for low energy ion beam production and efficient space charge neutralization. An ion beam with emission current density up to 60 mA/cm² has been extracted from the modified source running on BF₃ gas. Space charge neutralization of positive ion beams was improved by injecting electronegative gases. Full article