Search Results (5,665)

Ensuring safety in energy storage systems increasingly relies on advanced diagnostic tools, among which magnetic field mapping plays a critical role. This work aims to develop and validate a high-sensitivity magnetic field sensor array for accurate field mapping and preliminary battery diagnostics. We present a 4 × 4 array of magnetic sensors integrated with a calibration procedure to ensure accurate output. The system was experimentally tested by characterizing the magnetic field generated by two planar copper conductors. Finite element simulations were performed for comparison and validation. Experimental measurements exhibited strong agreement with the simulation results, confirming the reliability of the sensor array. Next, the system was employed to map the magnetic field distribution of a pouch-type lithium-ion battery, demonstrating its capability for noninvasive diagnostics. Although this study focuses on magnetic field measurement rather than direct battery diagnosis, the results suggest that the proposed system—capable of measuring magnetic fields in batteries operating under normal conditions—could also perform these measurements under abusive conditions, thereby enabling diagnostic assessments. The proposed sensor array provides a scalable and precise solution for low-intensity magnetic field mapping, with potential applications in battery health monitoring and safety assessment. Full article

Advanced aerospace vehicle concepts demand concurrent advances in energy storage technologies that improve both specific energy and safety. Commercial lithium-ion batteries commonly employ polyolefin microporous separators and carbonate-based liquid electrolytes, which can deliver room-temperature ionic conductivities on the order of 10⁻³–10⁻² S/cm but rely on inherently flammable solvents. Room-temperature ionic liquids (RTILs) offer a nonvolatile, nonflammable alternative with a stable electrochemical window; however, many RTILs exhibit poor compatibility and wetting with polyolefin separators. Here, we evaluate highly porous, cross-linked polyimide (PI) gel separators based on 4,4′-oxydianiline (ODA) and biphenyl-3,3′,4,4′-tetracarboxylic dianhydride (BPDA), cross-linked with Desmodur N3300A, formulated with repeating unit lengths (n) of 30 and 60. These PI gel separators exhibit an open, fibrillar network with high porosity (typically >85%), high thermal stability (onset decomposition > 561 °C), and high char yield. Six imidazolium-based RTILs containing 10 wt% LiTFSI were screened, yielding nonflammable separator/electrolyte systems with room-temperature conductivities in the 10⁻³ S/cm range. Among the RTILs studied, 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMIM-TFSI) provided the best overall performance. Ionic conductivity and its retention after four months of storage at 75 °C were evaluated in the EMIM-TFSI/LiTFSI system, and the corresponding gel separator exhibited a tensile modulus of 26.66 MPa. Collectively, these results demonstrate that PI gel separators can enable carbonate-free, nonflammable RTIL electrolytes while maintaining the ionic conductivity suitable for lithium-based cells. Full article

To improve the dynamic response and steady-state frequency quality of a wind–storage coordinated system during primary frequency regulation, and to address the secondary frequency dip caused by rotor kinetic energy recovery when a doubly fed induction generator (DFIG)-based wind turbine (DFIG-WT) participates in frequency support, this paper proposes a coordinated wind–storage primary frequency regulation strategy. This strategy synergistically controls the wind turbine’s rotor kinetic energy recovery and exploits the advantages of hybrid energy storage system (HESS). During the DFIG-WT control stage, an adaptive weighted model is developed for the inertial and droop power contributions of the DFIG-WT based on the available rotor kinetic energy, enabling a rational distribution of primary frequency regulation power. In the control segment of HESS, an adaptive complementary filtering frequency division strategy is proposed. This approach integrates an adaptive adjustment method based on state of charge (SOC) to control both the battery energy storage system (BESS) and supercapacitor (SC). Additionally, the BESS assists in completing the rotor kinetic energy recovery process. Through simulation experiments, the results demonstrate that under operating conditions of 9 m/s wind speed and a 30 MW step disturbance, the proposed adaptive weight integrated inertia control elevates the frequency nadir to 49.84 Hz and reduces the secondary frequency dip to 0.0035 Hz. Under the control strategy where wind and storage coordinated participate in frequency regulation and BESS assist in rotor kinetic energy recovery, secondary frequency dips were eliminated, with steady-state frequency rising to 49.941 Hz. The applicability of this strategy was further validated under higher wind speeds and larger disturbance conditions. Full article

The increasing penetration of photovoltaic (PV) generation, energy storage systems, and flexible loads within modern buildings demands advanced control strategies capable of harnessing dynamic assets while maintaining grid reliability. This Perspective article presents a comprehensive overview of reinforcement learning-driven (RL-driven) control methods for DC flexible microgrids—focusing in particular on building-integrated systems that shift from AC microgrid architectures to true PV–Energy storage–DC flexible (PEDF) systems. We examine the structural evolution from traditional AC microgrids through DC microgrids to PEDF architectures, highlight core system components (PV arrays, battery storage, DC bus networks, and flexible demand interfaces), and elucidate their coupling within building clusters and urban energy networks. We then identify key challenges for RL applications in this domain—including high-dimensional state and action spaces, safety-critical constraints, sample efficiency, and real-time deployment in building energy systems—and propose future research directions, such as multi-agent deep RL, transfer learning across building portfolios, and real-time safety assurance frameworks. By synthesizing recent developments and mapping open research avenues, this work aims to guide researchers and practitioners toward robust, scalable control solutions for next-generation DC flexible microgrids. Full article

This comprehensive review examines hierarchical control principles and frameworks for grid-connected microgrids operating in environments prone to load shedding and under demand response. The particular emphasis is on South Africa’s current electricity grid issues, experiencing regular planned and unplanned outages, due to numerous factors including ageing and underspecified infrastructure, and the decommissioning of traditional power plants. The study employs a systematic literature review methodology following PRISMA guidelines, analysing 127 peer-reviewed publications from 2018–2025. The investigation reveals that conventional microgrid controls require significant adaptation to address the unique challenges brought about by scheduled power outages, including the need for predictive–proactive strategies that leverage known load-shedding schedules. The paper identifies three critical control layers of primary, secondary, and tertiary and their modifications for resilient operation in environments with frequent, planned grid disconnections alongside renewables integration, regular supply–demand balancing and dispatch requirements. Hybrid optimisation approaches combining model predictive control with artificial intelligence show good promise for managing the complex coordination of solar–storage–diesel systems in these contexts. The review highlights significant research gaps in standardised evaluation metrics for microgrid resilience in load-shedding contexts and proposes a novel framework integrating predictive grid availability data with hierarchical control structures. South African case studies demonstrate techno-economic advantages of adapted control strategies, with potential for 23–37% reduction in diesel consumption and 15–28% improvement in battery lifespan through optimal scheduling. The findings provide valuable insights for researchers, utilities, and policymakers working on energy resilience solutions in regions with unreliable grid infrastructure. Full article

As the use of renewable energy increases, the inertia and frequency stability of the power system continuously decrease, which seriously threatens the stable operation of the power grid. To address the problem of frequency instability, grid-forming energy storage systems (ESS) and associated microgrids have arisen as promising solutions, and their scheduling and capacity planning have become critical issues directly affecting operational costs. However, existing research often ignores battery aging, which may lead to excessive degradation and higher equipment replacement costs. To solve this problem, this paper proposes a grid-forming battery energy storage system capacity planning method that explicitly considers device lifetime, incorporating battery aging into the optimization objective through the rain-flow counting algorithm. Furthermore, an optimization framework combining the genetic algorithm, rain-flow counting method, and branch-and-cut algorithm is developed. To verify the effectiveness of the proposed method, simulations of 12 typical days are conducted on the Gurobi platform to compare the overall cost in five different cases. The results prove that the proposed method can reduce the overall cost by 1.51–6.82% compared to cases where the device lifetime and workload flexibility are not considered, and a good frequency-support performance is achieved. Full article

Spinel LiNi_0.5Mn_1.5O₄ (LNMO) has emerged as a highly competitive cobalt-free cathode material for higher-energy-density lithium-ion batteries. However, its practical application is hindered by severe capacity degradation, particularly under high-voltage operation. To solve this problem, we put forward a surface modification strategy employing a Li_0.4La_0.54TiO₃ (LLTO) coating. The LLTO coating forms a protective cathode–electrolyte interphase that helps to inhibit interfacial side reactions, enabling enhanced electrochemical performance up to 5 V. As a result, the optimized 1 wt% LLTO-coated LNMO exhibits a remarkable capacity retention of 96.5% after 200 cycles at 0.1 C and delivers a high-rate capacity of 103.5 mAh g⁻¹ at 2 C, significantly outperforming its pristine counterpart (86.8% and 89.6 mAh g⁻¹, respectively). This work provides a viable and efficient surface modification approach for achieving robust high-voltage LNMO cathode material, underscoring its great potential for next-generation energy storage systems. Full article

The fastest growth in electricity demand in the industrialized world will likely come from the broad adoption of artificial intelligence (AI)—accelerated by the rise of generative AI models such as OpenAI’s ChatGPT. The global “data center arms race” is driving up power demand and grid stress, which creates local and regional challenges because people in the area understand that the additional data center-related electricity demand is coming from faraway places, and they will have to support the additional infrastructure while not directly benefiting from it. So, there is an incentive for the data center operators to manage the fast and unpredictable power surges internally so that their loads appear like a constant baseload to the electricity grid. Such high-intensity and short-duration loads can be served by hybrid energy storage systems (HESSs) that combine multiple storage technologies operating across different timescales. This review presents an overview of energy storage technologies, their classifications, and recent performance data, with a focus on their applicability to AI-driven computing. Technical requirements of storage systems, such as fast response, long cycle life, low degradation under frequent micro-cycling, and high ramping capability—which are critical for sustainable and reliable data center operations—are discussed. Based on these requirements, this review identifies lithium titanate oxide (LTO) and lithium iron phosphate (LFP) batteries paired with supercapacitors, flywheels, or superconducting magnetic energy storage (SMES) as the most suitable HESS configurations for AI data centers. This review also proposes AI-specific evaluation criteria, defines key performance metrics, and provides semi-quantitative guidance on power–energy partitioning for HESSs in AI data centers. This review concludes by identifying key challenges, AI-specific research gaps, and future directions for integrating HESSs with on-site generation to optimally manage the high variability in the data center load and build sustainable, low-carbon, and intelligent AI data centers. Full article

Lithium-ion batteries (LIBs) are essential for electric vehicles, consumer electronics, and grid storage, but their rapidly increasing demand is paralleled by growing waste volumes. Current disposal methods remain costly, complex, energy-intensive, and environmentally unsustainable. This pilot study investigates a scalable, low-impact disposal method by incorporating LIB waste into concrete, evaluating both the structural and environmental effects of LIB waste on concrete performance. Several cement–mortar cube specimens were cast and tested under compression using the cement–mortar mix with varying battery waste components, such as black mass and varied metals. All mortar mixes maintained an identical water-to-cement ratio. The compressive strength of the cubes was measured at 3, 7, 14, 21, and 28 days after casting and compared. The mix containing black mass exhibited a 35% reduction in compressive strength on day 28, whereas the mix containing varied metals showed a 55% reduction relative to the control mix without LIB waste. A case study was conducted to evaluate the combined structural and environmental performance of a concrete specimen incorporating LIB waste by estimating the embodied carbon (EC) for each mix and comparing the strength-to-net EC ratio. Selective incorporation of LIB waste into concrete provides a practical, low-carbon upcycling pathway, reducing both embodied carbon and landfill burden while enabling greener, non-structural construction materials. This sustainable approach simultaneously mitigates battery waste and lowers cement-related CO₂ emissions, delivering usable concrete for non-structural and low-strength structural applications. Full article

Hard carbon is widely recognized as a viable anode candidate for sodium-ion batteries (SIBs) owing to its electrochemical advantages, yet simultaneously enhancing specific capacity and rate capability, arising from insufficient plateau capacity, remains a long-standing challenge. Herein, we present a strategy for fabricating ZnCl₂-modified hard carbon (HCMZ-X) using waste macadamia shells and ZnCl₂ as a multifunctional structural modifier through a facile high-temperature carbonization. This approach effectively expands the graphite interlayer spacing to 0.394 nm, reduces microcrystalline size, and induces abundant closed pores, synergistically improving sodium-ion storage kinetics within the hard carbon framework. Mechanistic investigations confirm an “adsorption-intercalation-filling” storage mechanism. Hence, the optimized HCMZ-3 delivers a high reversible capacity of 382.05 mAh g⁻¹ at 0.05 A g⁻¹, with the plateau region contributing approximately 70%, significantly outperforming that of unmodified hard carbon (262.64 mAh g⁻¹). Remarkably, it achieves stable rate performance, delivering 190 mAh g⁻¹ at 1 A g⁻¹, along with excellent cycling stability, retaining over 90% after 500 cycles. By rational pore-structure modulation rather than excessive surface activation, this cost-effective method utilizing agricultural waste and ZnCl₂ dual-functional modification partially alleviates the intrinsic energy-density limitation of hard carbon anodes, advancing the development of high-performance, eco-friendly anodes for scalable energy storage systems. Full article

Decarbonisation of the aviation sector is essential for achieving global-climate targets, with hydrogen propulsion emerging as a viable alternative to battery–electric systems for vertical flight. Unlike previous studies focusing on clean-sheet eVTOL concepts or fixed-wing platforms, this work provides a comprehensive retrofit evaluation of a two-seat light helicopter (Cabri G2/Robinson R22 class) to a hydrogen–electric hybrid powertrain built around a Toyota TFCM2-B PEM fuel cell (85 kW net), a 30 kg lithium-ion buffer battery, and 700 bar Type-IV hydrogen storage totalling 5 kg, aligned with the Vertical Flight Society (VFS) mission profile. The mass breakdown, mission energy equations, and segment-wise hydrogen use for a 100 km sortie are documented using a single main rotor with a radius of R = 3.39 m, with power-by-segment calculations taken from the team’s final proposal. Screening-level simulations are used solely for architectural assessment; no experimental validation is performed. Mission analysis indicates a 100 km operational range with only 3.06 kg of hydrogen consumption (39% fuel reserve). The main contribution is a quantified demonstration of a practical retrofit pathway for light rotorcraft, showing approximately 1.8–2.2 times greater range (100 km vs. 45–55 km battery-only baseline, including respective safety reserves). The Hawk demonstrates a 28% reduction in total propulsion system mass (199 kg including PEMFC stack and balance-of-plant 109 kg, H₂ storage 20 kg, battery 30 kg, and motor with gearbox 40 kg) compared to a battery-only configuration (254.5 kg battery pack, plus equivalent 40 kg motor and gearbox), representing approximately 32% system-level mass savings when thermal-management subsystems (15 kg) are included for both configurations. Full article

Structural failure of the lead-carbon battery casing under external loads poses a serious threat to the safety of its energy storage function. To overcome the limitations of traditional protective casings regarding specific energy absorption (SEA) and crush force efficiency (CFE), this study proposes a novel thin-walled protective structure utilizing graded aperture honeycomb sandwich panels fabricated via additive manufacturing (AM). Finite element (FE) models were established using HyperMesh and validated against experimental data. Subsequently, the impact resistance and energy absorption characteristics of four distinct cellular topologies were systematically investigated under varying pore-size gradients, impact directions, and velocities. Experimental and numerical simulation results indicate that, among the investigated configurations, the triangular honeycomb structure exhibits superior impact resistance and energy absorption capability under both axial and lateral loading conditions. Furthermore, the synergistic enhancement mechanism based on topological configuration and gradient design effectively optimizes the progressive crushing mode, thereby reducing the initial peak crushing force transmitted to the battery and resulting in a pronounced advantage in impact performance. This research provides a novel design approach for optimizing next-generation high-performance, lightweight protection systems for energy storage devices. Full article

In the context of small, battery-powered systems, a lightweight, reusable architecture is needed for integrated measurement, visualization, and cloud telemetry that minimizes hardware complexity and energy footprint. Existing solutions require high resources. This limits their applicability in Internet of Things (IoT) devices with low power consumption. The present work demonstrates the process of design, implementation and experimental evaluation of a single-cell lithium-ion battery monitoring prototype, intended for standalone operation or integration into other systems. The architecture is compact and energy efficient, with a reduction in complexity and memory usage: modular architecture with clearly distinguished responsibilities, avoidance of unnecessary dynamic memory allocations, centralized error handling, and a low-power policy through the usage of deep sleep mode. The data is stored in a cloud platform, while minimal storage is used locally. The developed system combines the functional requirements for an embedded external battery monitoring system: local voltage and current measurement, approximate estimation of the State of Charge (SoC) using a look-up table (LUT) based on the discharge characteristic, and visualization on a monochrome OLED display. The conducted experiments demonstrate the typical U(t) curve and the triggering of the indicator at low charge levels (LOW − SoC ≤ 20% and CRITICAL − SoC ≤ 5%) in real-world conditions and the absence of unwanted switching of the state near the voltage thresholds. Full article

This paper presents a PSCAD-based analysis of short-circuit faults and protection characteristics in a real distribution-level microgrid that integrates a 1 MWh battery energy storage system (BESS) with a 500 kW power conversion system (PCS) and a 500 kW photovoltaic (PV) plant connected to a 22.9 kV feeder. While previous studies often rely on simplified inverter models, this paper addresses the critical gap by integrating actual manufacturer-defined control parameters and cable impedances. This allows for a precise analysis of sub-millisecond transient behaviors, which is essential for developing robust protection schemes in inverter-dominated microgrids. The PSCAD model is first verified under grid-connected steady-state operation by examining PV output, BESS power, and grid voltage at the point of common coupling. Based on the validated model, DC pole-to-pole faults at the PV and ESS DC links and a three-phase short-circuit fault at the low-voltage bus are simulated to characterize the fault current behavior of the grid, BESS and PV converters. The DC fault studies confirm that current peaks are dominated by DC-link capacitor discharge and are strongly limited by converter controls, while the AC three-phase fault is mainly supplied by the upstream grid. As an initial application of the model, an instantaneous current change rate (ICCR) algorithm is implemented as a dedicated DC-side protection function. For a pole-to-pole fault, the ICCR index exceeds the 100 A/ms threshold and issues a trip command within 0.342 ms, demonstrating the feasibility of sub-millisecond DC fault detection in converter-dominated systems. Beyond this example, the validated PSCAD model and associated data set provide a practical platform for future research on advanced DC/AC protection techniques and protection coordination schemes in real BESS–PV microgrids. Full article

In recent years, the energy revolution has driven the rapid development of lithium-ion batteries (LIBs). A fire suppression system capable of rapidly and effectively extinguishing LIB fires constitutes the last line of defense for ensuring the safe operation of the LIB industry. In this study, an experimental platform simulating the storage environment of LIBs in energy-storage stations was constructed, and liquid nitrogen (LN) was employed to conduct fire suppression tests on LIBs. The effective utilization of 17.4 kg of LN during the suppression process inside the battery module was quantified. In addition, fire compartments were established within the battery module, and a strategy for enhancing the LN suppression effectiveness was proposed. The results indicate that, without intervention, the thermal runaway propagation (TRP) rate within the LIB module gradually accelerates. After LN injection, the effective utilization of LN for extinguishing individual LIBs decreases progressively along the sequence of TRP. Creating fire compartments inside the PACK using 6 mm aerogel blankets effectively reduces the transfer of energy from the region undergoing thermal runaway (TR) to other regions, while simultaneously enhancing the extinguishing performance of LN. Under the same LN dosage, the introduction of fire compartments increases the effective utilization from 0.037 to 0.051. However, as the compartment volume decreases, the degree of improvement in LN utilization is reduced. This work is expected to provide guidance for the engineering application of LN-based fire suppression systems to inhibit LIB TR and its propagation. Full article