Charge State Research Articles

Elucidating 'Transfer-Lithiation' from Graphite to Si within Composite Anodes during Pre-Lithiation and Regular Charging.

Si-based anodes can increase specific energy and energy density of Li ion batteries. However, the volume-induced material stress and capacity loss necessitates only a partial Si utilization within composite anodes, typically with state-of-the-art graphite, so called Si/Gr composites. In this work, various Si nanowires (SiNWs), a promising Si architecture for these composites, are investigated and modified via pre-lithiation. Though, charged pre-lithiated anodes show potentials below 0 V vs. Li|Li+ in the initial cycles, they do not show indications for metallic Li, which is likely a hint for a triggered surface Li depletion in course of a continuous "transfer-lithiation" from lithiated Gr to Si, which is indicated by decreasing LiC6 and increasing LixSiy signals via nuclear magnetic resonance (NMR), X-ray diffraction (XRD) as well as shifts in capacities of respective voltage plateaus during discharge after storage. A relevant contribution of self-discharge is unlikely as shown by a stable open-circuit-voltage during storage in charged state and similar subsequent discharge capacities, being consequently also a hint for an intra-electrode capacity shift. The process of transfer lithiation is finally validated via solid-state 7Li NMR for varied Si morphology, i.e., amorphous and crystalline, as well as during pre-lithiation with passivated lithium metal powder (PLMP).

State-of-Charge Estimation Method for Lithium Batteries Based on Adaptive Fusion Factors

Abstract Accurate estimation of the state of charge is significant for battery safety. To improve robustness, computational efficiency, and noise stability in state of charge estimation for lithium batteries, we propose a method based on adaptive fusion factors. Based on the methodological properties of the open circuit voltage method and the ampere hour method, we designed a fusion factor function to combine the strong correction ability of the open circuit voltage method with the smoothing advantages of the ampere hour method. The proposed method utilizes an adaptive forgetting factor recursive least squares approach to address the limitation of the traditional open circuit voltage method, which cannot estimate state of charge online. It corrects the battery capacity using historical data to achieve accurate state of charge estimation. The effectiveness and robustness of the proposed method are validated using self-tests and a public dataset. The results demonstrate that the mean absolute error in state of charge estimation is approximately 1%, even when the initial state of charge value deviates from the actual value and the dataset contains noise.

Adaptive Joint Sigma-Point Kalman Filtering for Lithium-Ion Battery Parameters and State-of-Charge Estimation

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different operating conditions. In this paper, an advanced joint estimation approach of the model parameters and SoC is proposed utilizing an enhanced Sigma Point Kalman Filter (SPKF). Based on the second-order equivalent circuit model (2RC-ECM), the proposed approach was compared to the two most widely used methods for simultaneously estimating the model parameters and SoC, including a hybrid recursive least square (RLS)-extended Kalman filter (EKF) method, and simple joint SPKF. The proposed adaptive joint SPKF (ASPKF) method addresses the limitations of both the RLS+EKF and simple joint SPKF, especially under dynamic operating conditions. By dynamically adjusting to changes in the battery’s characteristics, the method significantly enhances model accuracy and performance. The results demonstrate the robustness, computational efficiency, and reliability of the proposed ASPKF approach compared to traditional methods, making it an ideal solution for battery management systems (BMS) in modern EVs.

Comprehensive study of rapid capacity fade in prismatic Li-ion cells with flexible packaging

Prismatic lithium-ion batteries (LIBs) are considered promising electric energy sources in electromobility applications due to their efficient space utilization. However, their sensitivity to external and internal influences and reduced durability lead to inflation risk and potential explosions throughout their lifecycle. These critical processes are strongly influenced by the inner construction of the cell, especially concerning the coating and mechanical fixation. This study subjects a commercially available prismatic LIB cell to comprehensive, correlative analysis employing various imaging techniques. The inner structure of the entire cell is visualized non-destructively by X-ray computed tomography (CT), enabling the identification of critical design flaws prior to electrochemical cycling. Electrochemical cycling simulates the battery lifecycle, and the cell is subsequently disassembled in the fully charged state. The usage of the inert-gas transfer system allowed the preparation of Broad Ion Beam (BIB) electrodes cross-sections in a fully native state and for the first time to observe the tearing of graphite particles due to over-lithiation. Established region labeling system allowed to use CT and scanning electron microscopy (SEM) correlatively to identify critical regions. After 100 cycles, a 40% capacity loss was observed and event diagram describing deagradation mechanisms, related both to the cell design and to the processes occurring at high load, was created.

Lithium-Ion Battery Health Management and State of Charge (SOC) Estimation Using Adaptive Modelling Techniques

Effective health management and accurate state of charge (SOC) estimation are crucial for the safety and longevity of lithium-ion batteries (LIBs), particularly in electric vehicles. This paper presents a health management system (HMS) that continuously monitors a 4s2p LIB pack’s parameters—current, voltage, and temperature—to mitigate risks such as overcurrent and thermal runaway while ensuring balanced charge distribution between cells. An improved online battery model (IOBM) is developed to enhance SOC estimation accuracy. The system utilises forgetting factor recursive least squares (FFRLS) for real-time parameter updates, an adaptive nonlinear sliding mode observer (ANSMO) for SOC estimation, and a long short-term memory (LSTM) network to dynamically adjust capacity based on operating conditions. Validation using the urban dynamometer driving schedule (UDDS) test demonstrated high accuracy, with the proposed battery model achieving a root mean square error (RMSE) of 12.13 mV and the LSTM achieving an RMSE of 0.0118 Ah. Regular updates to the battery’s current capacity, along with the proposed IOBM, significantly improved SOC estimation performance, maintaining estimation errors within 1.08%.

Multi-objective optimized energy management strategy using an artificial tree algorithm for extended range hybrid loaders

Aiming at the problems that existing energy management strategies (EMS) are rarely applied to 100-ton loaders and the engine start-stops frequently under complex driving conditions, this paper proposes a novel EMS for 100-ton extended range hybrid loaders based on an artificial tree algorithm (AT). Firstly, using the equivalent fuel consumption minimization strategy (ECMS) as a foundation, a penalty function is designed to restrict the range extender’s start-stop frequency and integrated into the ECMS control framework. Secondly, a real-time driving condition recognition model based on AT optimized back propagation (BP) Neural Network is proposed. Finally, with the equivalent factor, scale factor of state of charge (SOC) penalty function and range extender start-stop penalty function as optimization variables, and fuel economy, SOC stability, and range extender start-stop frequency as optimization objectives, AT is used for multi-objective optimization to obtain the optimal control parameters corresponding to the identified driving conditions. The simulation results demonstrate that compared with ECMS and Proportional-Integral-Derivative (PID) based ECMS, the proposed strategy is more effective for maintaining SOC stability. Besides, it improves the fuel economy by 5.937% and 1.353%, respectively, and decreases the number of range extender start-stops by 50.000% and 55.556%, respectively.

Real‐Time Energy Management System for a Hybrid Renewable Microgrid System

ABSTRACTThis paper gives a detailed study for the design and implementation of an energy management system (EMS) for a hybrid renewable microgrid system using real‐time software. Microgrids, with their ability to integrate renewable energy sources, face challenges in maintaining stability and reliability. The implemented EMS aimed to maximize the renewable energy sources utilization, including PV and wind power, in conjunction with a battery energy storage system. The objectives of this research included the implementation of an EMS that ensures a reliable and stable operation between the microgrid system and the main grid including the control of charge and discharge of the battery using Typhoon Hardware‐in‐the‐Loop (HIL) software. The simulation results and case studies demonstrated the effectiveness and performance of the developed EMS in managing a hybrid renewable microgrid system. The results also demonstrated that the time of charging was maximized by utilizing a higher power. By doing so, the battery was fully charged in a shorter timeframe. The battery state of charge (SOC) was maintained between the fixed values (20% and 100%) as stated by the algorithm.

A Three‐Phase Omnidirectional Wireless Charger Based on Segmented Arc‐Shaped Coupler With High Anti‐Rotation Offset Feature for AUVs

ABSTRACTWhen the autonomous underwater vehicle (AUV) is charged by wireless charging technology (WCT), the coupler will be misalignment due to the impact of marine environment factors, which can lead to the weak stability of the system output. Besides, the electromagnetic field generated by the coaxial coil is concentrated in the center of the AUV hull, and the strong electromagnetic field may interfere with the normal operation of the power electronic equipment inside the AUVs. To address the above problems, this paper proposes a novel coupler with high anti‐offset and suppression of the central magnetic field of the AUVs. The coupler is composed of a three‐phase segmented arc‐shaped transmitter coils and a cylindrical receiver coil. The coupler can implement the suppression of the AUV central magnetic field and the promotion of anti‐rotation offset feature under the omnidirectional uniform magnetic field control method. To better adapt the proposed coupler and meet the battery charging requirements, a three‐phase wireless charging topology with a relay is designed, which can acquire the smooth transition between the two charging modes without constructing the wireless communication between two sides and detecting the state of charge (SOC). Finally, to verify the feasibility of the proposed scheme, a 1‐kW AUV wireless charging prototype is built. The experimental results indicate that the maximum output power fluctuation rate of the system is 1.1% in the case of the full‐angle rotation offset.

Performance and Efficiency Evaluation of a Secondary Loop Integrated Thermal Management System with a Multi-Port Valve for Electric Vehicles

Recently, battery electric vehicles (BEVs) have faced various technical challenges, such as reduced driving range due to ambient temperature, slow charging speeds, fire risks, and environmental regulations. This numerical study proposes an integrated thermal management system (ITMS) utilizing R290 refrigerant and a 14-way valve to address these issues, proactively meeting future environmental regulations, simplifying the system, and improving efficiency. The performance evaluation was conducted under high-load operating conditions, including driving and fast charging in various environmental conditions of 35 °C and −10 °C. As a result, the driving efficiency was 4.82 km/kWh in high-temperature conditions (35 °C) and 4.69 km/kWh in low-temperature conditions (−10 °C), which demonstrated higher efficiency than the Octovalve-ITMS applied to the Tesla Model Y. Furthermore, in fast charging tests, the high voltage battery was charged from a 10% to a 90% state of charge in 26 min at 35 °C and in 31 min at −10 °C, outperforming the Octovalve-ITMS-equipped Tesla Model Y’s fast charging time of 27 min under moderate ambient conditions. This result highlights the superior fast-charging performance of the 14-way valve-based ITMS, even under high cooling load conditions.

Ring Currents in the Clar Goblet Calculated Using Configurational State Averaging.

The closed-shell Hückel-London-Pople-McWeeny formalism for ring currents is extended to Aufbau configurations with open shells calculated as configurational averages. The method is applied to the non-Kekulean benzenoid known as the Clar goblet, recently synthesized on the Au(111) surface. Multiplicity of the ground state is a complication: for the Clar goblet, Hund's rule of maximum multiplicity implies a triplet whereas Ovchinnikov's rule implies a singlet. This disagreement has little effect on the predicted ring currents. Ring-current maps are calculated for the 36π dication, 40π dianion, and low-lying states of the 38π neutral, using Hückel-London and Hubbard-London models. All show twin diatropic perimeter currents on separate halves of the molecule. These are compared with ipsocentric pseudo-π and ab initio maps of induced π-current for closed-shell singlet configurations of dianion, dication, and neutral. Configurationally averaged Hückel-London calculations give a good account of the consistent diatropic ring currents in the Clar goblet for the three charge states.

A Hybrid Technique for Bidirectional Smart Charging of EVs Using BLDC Motor and Bidirectional Converter

This paper introduces a novel hybrid approach for bidirectional smart charging of electric vehicles (EVs) powered by brushless DC (BLDC) motors. The proposed technique, named Atomic Orbital Search-Rat Swarm Optimizer (AOS-RSO), leverages the Atomic Orbital Search (AOS) for optimizing energy storage management and the Rat Swarm Optimizer (RSO) for enhancing motor control. The modular hybrid energy storage system (HESS) is designed with five modules, each consisting of a bidirectional DC-DC converter connecting a battery and super capacitor module. A multi-level cascaded converter (MCC) connects the HESS to the BLDC motor inverter of the EV drive, controlling the DC bus voltage. The AOS-RSO approach efficiently manages the state-of-charge (SOC) across the modules, achieving a balanced SOC of 98%. Implemented in MATLAB, the method is evaluated in both open and closed-loop systems and compared with existing techniques. Results show the proposed method achieves 96% efficiency in simulation and 94% in experiments, with a CPU time of 2.84 s. This approach significantly advances smart charging solutions for EVs, offering improved energy management and operational efficiency.

Hiding in plain sight: The prevalence and impact of trions and Fermi polarons in transient absorption spectroscopy experiments of 2D semiconductors.

Transient absorption (TA) spectroscopy is one of the most popular experimental methods to measure the excited state lifetimes and charge carrier recombination mechanisms in two dimensional (2D) semiconductors. This fundamental information is essential for designing and optimizing the next generation of ultrathin and lightweight 2D semiconductor-based optoelectronic devices. However, the interpretation of TA spectroscopy data varies across the community. The community lacks a unifying physical explanation for how and why experimental variables such as incident light intensity, sample-substrate interactions, and/or applied bias affect TA spectral data. This Perspective (1) compares the physical chemistry TA literature to nanomaterial physics literature from a historical perspective, (2) reviews multiple physical explanations that the TA community developed to explain spectral features and experimental trends, (3) provides a unifying explanation for how and why trions-and, more generally, Fermi polarons-contribute to TA spectra, and (4) quantifies the extent to which various physical interpretations and data analysis procedures yield different timescales and mechanisms for the same set of experimental results. We highlight the importance of considering trions/Fermi polarons in TA measurements and their implications for advancing our understanding of 2D material properties.

Probing the Charge State and the Intermolecular Environment by Vibrational Spectroscopy: The Peculiar Modulation of Frequencies and Band Intensities of F4TCNQ and Its Anion

2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) is a molecule widely employed as a very effective p-dopant of semi-conducting polymers, such as poly(3-hexylthiophene-2,5-diyl) (P3HT). The CN stretching transitions of F4TCNQ are exceptionally sensitive to the charge state of the molecule, thus allowing the doping diagnosis via IR spectroscopy. Less pronounced frequency shifts can reveal characteristics of the intermolecular environment. We present a systematic study based on Density Functional Theory (DFT) calculations and on experiments aimed at exploring how different factors, such as the charge state and the environment, modify the vibrational spectra of F4TCNQ. While several effects on the vibrational frequencies are well known and have been thoroughly investigated in the past, this study focuses on the infrared intensities of the CN stretching modes and reveals that they are strongly affected both by the charge state of the molecule and by the surrounding medium: it is then mandatory to consider such remarkable intensity modulation for any quantitative diagnosis based on spectroscopic measurements, e.g., concerning the number of F4TCNQ molecules involved in the formation of charge transfer complexes.

Take-off performance of a single engine battery-electric aeroplane

AbstractThis paper investigates the take-off performance of a single engine battery-electric aeroplane, using the example of the 300kg Sherwood eKub. It shows analysis of take-off performance of such an aeroplane must include as a minimum two new parameters not normally considered: time at full throttle and state of charge. It was shown in both ground and flight test that the state of available power reduces both as the throttle is fully open, and as battery charge is consumed, although recovers partially when power is reduced for a period. It is possible to schedule take-off performance as a function of the usual parameters plus state of charge. Because of the reducing climb performance with use of state of charge, and the requirement in airworthiness standards for minimum climb performance being available, it becomes necessary to introduce the concept of minimum-indicated state of charge for take-off, SoCiMTO; means to calculate that are shown for compliance with both microlight aeroplane standards and larger aeroplane standards, and the calculations are demonstrated for the eKub. Conclusions are also drawn about the use of commercial products SkyDemon and Google Earth for recording and analysing aeroplane performance data.

Short-term anticorrelations between in situ averaged charge states of Fe and O in the solar wind

Observations of the Fe and O charge states in the solar wind and interplanetary coronal mass ejections (ICMEs) generally exhibit a positive correlation between the average charge states of Fe and O ($ avQ Fe $ and $ avQ O $). Because Fe and O charge states freeze at different heights in the corona, this positive correlation indicates that conditions at different heights in the corona vary as a whole. We identify short time periods in the solar wind that exhibit anticorrelations between the average Fe and O charge states and investigate their properties. We aim to distinguish whether these anticorrelations are due to the related solar sources or to transport effects (e.g., differential streaming). We study kinetic properties of the solar wind related to these anticorrelated structures as well as heavy ion differential streaming in order to infer a possible relationship between conditions in coronal source regions and the reported in situ measurements. We employed a recently developed sliding-window cross-correlation method to locate anticorrelated structures in the solar wind composition measurements between 2001 and 2010 from the Advanced Composition Explorer (ACE). To account for fluctuations and measurement uncertainties, we varied the timescales and temporal lags. We determined the onset and end times of the gradual increases or decreases in the average charge states of O and Fe and analyzed the kinetic and plasma properties of the anticorrelated structures. We identified 103 anticorrelated structures both in the solar wind and in ICMEs. The behavior of $ avQ Fe $ is strongly related to solar wind kinetic properties, including proton speed, proton temperature, and the proton-proton collisional age. We find that the anticorrelation of $ avQ Fe $ and $ avQ O $ during these time periods cannot be explained by differential streaming nor by unrecorded hot plasma ejections. Thus, the measured anticorrelated variations in $ avQ Fe $ and $ avQ O $ probably indicate that changes in coronal conditions at different freeze-in heights may follow opposite monotonic trends.

Direct visualization of the charge transfer state dynamics in dilute-donor organic photovoltaic blends

The interconversion dynamics between charge transfer state charges (CTCs) and separated charges (SCs) is still an unresolved issue in the field of organic photovoltaics. Here, a transient absorption spectroscopy (TAS) study of a thermally evaporated small-molecule:fullerene system (α6T:C60) in different morphologies (dilute intermixed and phase separated) is presented. Spectral decomposition reveals two charge species with distinct absorption characteristics and different dynamics. Using time-dependent density functional theory, these species are identified as CTCs and SCs, where the spectral differences arise from broken symmetry in the charge transfer state that turns forbidden transitions into allowed ones. Based on this assignment, a kinetic model is formulated allowing the characterization of the charge generation, separation, and recombination mechanisms. We find that SCs are either formed directly from excitons within a few picoseconds or more slowly (~30–80 ps) from reversible splitting of CTCs. These findings constitute the first unambiguous observation of spectrally resolved CTCs and SCs.

Rational Electrode Design for Enhanced Battery Performance: Addressing SOC Heterogeneity and Achieving Energy Density

AbstractThe heterogeneity in the state of charge (SOC) across electrodes can significantly abbreviate battery lifespan, deteriorate safety metrics, and diminish capability rate. Despite being a known issue for some time, the factors contributing to this phenomenon have not been systematically summarized. Without a thorough understanding of the underlying causes, it is difficult to devise preventive strategies that can effectively enhance electrode behavior. This paper provides a comprehensive analysis of the factors inducing electrode SOC heterogeneity, identifying the unequal distribution of ions and electrons as the primary cause of the varied reaction rates across the electrode, which ultimately leads to SOC heterogeneity. Subsequently, preventive measures are outlined with a focus on electrode composition and structure. Furthermore, implications of SOC heterogeneity and the challenges associated with achieving both large power density and high energy density in electrodes are discussed. A more profound grasp of the mechanisms governing ion and electron conduction, coupled with materials that can resolve these dilemmas into win–win outcomes, is essential for the advancement of electrodes.

Enhanced Control of Single-Molecule Emission Frequency and Spectral Diffusion.

The Stark effect provides a powerful method to shift the spectra of molecules, atoms, and electronic transitions in general, becoming one of the simplest and most straightforward ways to tune the frequency of quantum emitters by means of a static electric field. At the same time, in order to reduce the emitter sensitivity to charge noise, inversion symmetric systems are typically designed, providing a stable emission frequency with a quadratic-only dependence on the applied field. However, such nonlinear behavior might be reflected in correlations between the tuning ability and unwanted spectral fluctuations. Here, we provide experimental evidence of this trend using molecular quantum emitters in the solid state cooled down to liquid helium temperatures. We finally combine the electric field generated by electrodes, which is parallel to the molecule's induced dipole, with optically excite long-lived charge states acting in the perpendicular direction. Based on the anisotropy of the molecule's polarizability, our two-dimensional control of the local electric field allows us not only to tune the emitter's frequency but also to sensibly suppress the spectral instabilities associated with field fluctuations.

Assessing fire dynamics and suppression techniques in electric vehicles at different states of charge: Implications for maritime safety

The maritime transportation of electric vehicles (EVs) poses significant fire risks due to the potential for thermal runaway in lithium-ion batteries, particularly when the state of charge (SOC) varies. This study uniquely examines the effects of SOC on fire behavior and suppression efficacy, going beyond previous research by focusing on the maritime environment. Experiments were conducted on EV battery packs at SOC levels of 70 %, 50 %, and 30 %, and on a full-scale EV at 50 % SOC, to evaluate fire dynamics and the effectiveness of suppression methods, including seawater injection and fire blankets. Results showed that higher SOC levels are associated with significantly increased heat release rates and extended fire durations, while lower SOC levels (30 %) reduce fire intensity yet necessitate continuous monitoring for re-ignition risks. Moreover, the combination of seawater injection and fire blankets showed promise in cases where rapid cooling and containment of fire spread were priorities, illustrating a potential strategy for managing EV battery fires during maritime transport. These findings underscore the need for strategic SOC management, recommending lower SOC thresholds to minimize fire severity, and the use of combined suppression techniques to enhance EV fire safety during maritime transport.

State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control

To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by hybrid energy storage systems (HESSs), this paper proposes a state of charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.