2026 October - 60 articles
Aqueous organic flow batteries (AOFBs) are a promising technology for large-scale energy storage. The electrolyte solution is significant in determining the battery’s performance, which has so far remained poorly understood, especially for conc...
A growing number of second-life battery companies are entering North America’s stationary energy storage market as the demand for both electric vehicles and electricity grid energy storage continues to rise. These companies have many potential...
Accurate state of charge (SOC) estimation for lithium-ion batteries (LIBs) is essential. To overcome the susceptibility of conventional data-driven models to local optima and terminal divergence under complex conditions, this paper proposes a novel j...
Thermally induced damage in lithium-ion batteries (LIBs) is a critical safety concern, especially when approaching thermal runaway (TR) conditions. In this study, electrochemical impedance spectroscopy (EIS) was used to detect thermally induced damag...
With the increasing renewable penetration in electrical grids, high power ramp rates can lead to grid instability. Power ramp-rate control (PRRC) requirements are being implemented in an increasing number of countries, with penalties for non-complian...
Lithium-ion batteries (LIBs) have been widely used in electric vehicles and energy storage systems. Due to their high energy density and complex structural components, thermal runaway of LIBs can lead to severe fire and explosion hazards. Densely arr...
The structural design of self-standing electrodes without binders and current collectors is critical for maximizing the energy density of lithium-ion batteries, yet achieving electrical conductivity, ion accessibility, and mechanical integrity in a s...
As a core component of the new power system, energy-storage batteries undergo capacity degradation, increasing internal resistance and declining state of health (SOH) as a result of calendar aging. These changes compromise the operational safety and...
Vehicle-level battery labels paired with many charging records create a weakly supervised rare-event problem. We evaluated a two-level multiple-instance framework on 191 vehicles (184 normal and seven source-coded abnormal) from the public EVBattery...
The safety of lithium-ion batteries is a critical concern, and this paper introduces a novel simulation approach for thermal runaway using the control volume free element method (CVFrEM). This method uniquely integrates the geometric adaptability of...
Electric vehicles offer a sustainable alternative to combustion engines but still face range and safety limitations. Integrating battery cells as structural elements (Cell-to-X, CTX) is a promising route to address both, but requires cells that relia...
Against the backdrop of the energy crisis and environmental pollution, semi-solid lithium-ion batteries have been widely applied in energy storage and electric vehicles. Accurate joint estimation of state of charge (SOC) and state of energy (SOE) is...
State of charge (SoC) is the unobserved quantity that a battery management system must reconstruct from terminal voltage, current and temperature. Recent estimators adapt frozen large language models by prompt-tuning the key–value cache of a de...
Silicon (Si) anodes suffer from severe structural degradation caused by large volume variation during lithiation/delithiation, requiring binders that can simultaneously provide mechanical support and deformation adaptability. Inspired by the function...
Detecting internal short-circuit (ISC) conditions in lithium-ion batteries is difficult because fault-induced voltage deviations are often masked by load transients, state-of-charge variation, model mismatch, and measurement noise. This study propose...
Feature selection and model tuning are coupled decisions in real-world electric-vehicle battery analysis: the search must balance predictive performance, feature burden, model complexity, and computational demand. This study develops three integrated...
This work systematically explores the core foundational mechanisms and kinetics of the metal electrocrystallization processes at the anodes of the most studied rechargeable batteries relying on electrodeposition. The analysis requires a consideration...
High-energy-density Li-ion batteries demand highly graphitized graphite anodes, yet elevated graphitization inevitably amplifies structural anisotropy, obstructing Li+ intercalation and compromising rate capability. To resolve this trilemma, we estab...
Component calorimetry is widely used to assess the thermal stability of lithium-ion battery cathode materials, yet it remains unclear which material-scale descriptors retain consistent relationships with whole-cell self-heating kinetics across indepe...
Accurate internal temperature estimation is of great significance to the safe and dependable working performance of lithium-ion batteries (LIBs). Nevertheless, conventional purely data-driven prediction models suffer from inherent limitations, includ...
Ni-rich layered oxide cathodes are promising candidates for high-energy-density lithium-ion batteries; however, their electrochemical performance is strongly influenced by structural evolution, lithium stoichiometry, interfacial properties, and parti...
Trigger selection underpins thermal runaway (TR) and thermal propagation (TP) testing of lithium-ion batteries, yet its influence on the TR response is rarely quantified, and data for a cell with manganese-based composite cathode (MCC) material are s...
Lithium-ion batteries (LIBs) in electric vehicle battery packs are assembled under mechanical constraints that exert compression force during operation. During operation, battery cells undergo volumetric changes that cause thickness variations, known...
The research demonstrates a national project combining solar photovoltaics with second-life automotive lithium batteries for local-scale agricultural irrigation and greenhouse climate control. The auto-opening greenhouse system can adapt to various c...
Early fault warning in lithium-ion battery packs is challenged by weak labels and changing operating conditions. This study combines cell-wise Local Outlier Factor (LOF) scoring with validity-gated Streaming Peaks-Over-Threshold (SPOT). Five descript...
Accurate and reliable state of health (SOH) estimation is essential for lithium-ion battery safety and lifetime management. Physics-informed neural networks (PINNs) integrate battery degradation knowledge with deep learning to improve the physical co...
Lithium-ion batteries are widely used in modern energy storage systems; however, increasing power demand makes thermal management a critical challenge, particularly for cylindrical cells operating under high discharge conditions. This study investiga...
Batteries are regarded as a uniform heat source in traditional thermal management system design. Inconsistencies in electrochemical reactions across time and space are often ignored, which leads to an unreasonable battery thermal management system. T...
This study investigates four semi-solid-state battery cell types by using X-ray photoemission spectroscopy to characterize fresh cathodes from unabused cells according to their electrolyte systems and interphase strategies. Their safety behaviour is...
Residential battery energy management systems increasingly rely on model predictive control (MPC), yet most schemes assume a fixed horizon, a noise-free state and an uncalibrated forecaster. This paper proposes DT-AAMPC, an adaptive MPC that combines...
The recycling and secondary utilization of retired power batteries have become increasingly important with the rapid growth of new energy vehicle ownership. Assessing their residual value and guiding trade-in decisions have emerged as key challenges....
The new energy vehicle (NEV) industry is expanding globally, yet safety accidents induced by collisions have become a major challenge to its high-quality development. In addition, the risks associated with battery state variations from fast-charging...
Magnesiothermic reduction is a promising route for synthesizing nanostructured silicon for battery anodes, yet commercial scalability is hindered by highly exothermic reaction conditions and reliance on hydrofluoric acid (HF) for purification. Here,...
This paper presents the optimal sizing of wind turbine (WT), photovoltaic (PV) and battery energy storage system (BES) for standalone houses with electric vehicles (EVs) by considering vehicle-to-home (V2H) operation. To minimise the net present cost...
Accurate state-of-health (SOH) estimation is essential for the safe, reliable, and cost-effective operation of lithium-ion battery systems. However, practical SOH modeling remains challenging because battery degradation data are often limited, degrad...
Fast charging provides convenience for electric vehicle users but can accelerate Li-ion battery degradation and compromise lifetime energy utilization. Here, we investigate how fast-charging protocols govern first- and second-life performance of comm...
Day-ahead battery arbitrage requires assessing the return and downside risk of complete charge–discharge cycles. We propose Scenario-Conditioned Risk Optimization (SCARO), which corrects supply and demand forecasts and maps jointly resampled wh...
Additive-free electrode architectures are important for clarifying the intrinsic lithium-storage behavior of MOF-derived conversion-type anode materials, because conventional slurry electrodes contain polymer binders and conductive carbon additives t...
Accurate health assessment is essential for the reliable and cost-effective operation of lithium-ion battery energy storage systems. This study presents a physics-informed explainable machine-learning framework for hybrid State-of-Health (SoH) estima...
Lithium cobalt oxide (LCO) remains the industry-standard cathode for lithium-ion batteries in consumer electronics, but its mechanical reliability under repeated deformation—a critical requirement for flexible and wearable devices—has not...
This study presents a comprehensive machine learning (ML) evaluation methodology, grounded in physical principles, for range estimation in battery-electric vehicles (BEVs). In a simulation environment consisting of 50 driving and 12 virtual vehicles,...
The widespread adoption of lithium-ion batteries as energy storage components necessitates accurate prediction of their remaining useful life, which is critical to ensuring operational safety and enabling timely maintenance. To address this challenge...
Accurate state-of-energy (SOE) estimation on the flat voltage plateau of lithium iron phosphate (LFP) batteries depends on observation calibration and initialization. This study implements an iterated cubature Kalman filter–extended Kalman filt...
The performance of aqueous Mg–air batteries is determined by the interplay between magnesium dissolution, self-corrosion, and Mg(OH)2 surface passivation. Electrolyte additives that enhance one of these processes often compromise the others, ma...
Large-scale battery energy storage systems (BESSs) continuously generate cell-level monitoring data. These data increase storage demand and communication load in cloud-edge systems. Exact measurement values are required for archival and diagnostic ta...
This study compares the failure characteristics of four 1.5 Ah 18650 cells, including lithium nickel manganese cobalt oxide (NMC), lithium iron phosphate (LFP), lithium titanate (LTO), and sodium-ion (NFM), alongside a 3 Ah 26700 NFM cell. Cells at a...
The actual voltage data collected by the cloud-based battery management system (BMS) are susceptible to disturbances caused by sensor failures, electromagnetic interference, and communication anomalies, which may lead to four types of anomalies: rand...
All-solid-state lithium metal batteries (ASSLMBs) promise enhanced safety and high energy density, yet their solid–solid interfaces create mechanical constraints absent from conventional liquid-electrolyte cells. Electrochemical reactions, ion...
Accurate prediction of the state-of-charge (SOC) of batteries is essential for reliable energy management and safety in electric vehicles (EVs). Although machine learning (ML) models have shown strong predictive performance for SOC estimation, their...
This study proposes a probabilistic data-driven ensemble framework for the remaining useful life (RUL) prognostics of lithium-ion batteries. This work addresses the limitations of single-model and deterministic methods by integrating Bayesian neural...
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