Charging Current Research Articles

Revisiting Pseudo-OCV Pulse-Based Incremental Capacity Analysis

Li-ion batteries are more prone to safety incidents than other battery technologies. This is due to the inherently higher energy density as well as the flammability of especially anode materials, separator, and electrolyte solvents. During charging, metallic Lithium may form on the anode surface and could in the worst case short the battery from within and cause a fire and or explosion [1]. It is therefore vital to be able to monitor the battery’s state-of-health (SoH) and state-of-safety (SoS) [2], to avoid further use of Li-ion batteries that may have aged in a detrimental fashion and can have an increased safety risk. Especially when a battery has aged considerably (SoH < 80%) the path of ageing can significantly affect the safety properties of the battery and cause dramatic differences in the severity of a possible safety incident.Incremental capacity analysis (ICA, dQ/dV) has emerged as a very powerful diagnostic technique for Li-ion batteries. We recently used ICA to identify different degradation mechanisms in commercial Li-ion cells through classification and tracking of selected dQ/dV features [3]. This allowed us to identify safety critical ageing at an early stage. ICA requires constant charge and discharge at slow currents (C-rate < C/10) [4, 5]. However, a slow controlled constant current charge or discharge is normally not feasible and cannot be easily applied to battery systems without access to high precision battery pack testers.In this work we will revisit applying ICA on the Open-Circuit-Voltage (OCV) curve in the capacity space [6]. The OCV curve can be obtained from any sequence of current or power pulses followed by a rest period to allow the cell to reach a pseudo-OCV after each pulse. By pulsing through the entire state-of-charge window an OCV vs capacity curve can be obtained with sufficient accuracy to perform ICA.A direct comparison of conventional constant current ICA (cc-ICA) and high-resolution-OCV ICA (ocv-ICA) is presented. A strong correlation between ageing patterns is observed providing a first proof-of-concept for the method.

(Battery Division Postdoctoral Associate Research Award Sponsored by MTI Corporation and the Jiang Family Foundation) Science of Multiphysics Behavior of Si/C Composite Anodes in High-Energy-Density Lithium-Ion Batteries

The rapidly growing demands on energy storage technologies over the last decade have imposed further requirements for the high energy/power density, safety, and durability of lithium-ion batteries (LIBs). Si/C composite materials have attracted enormous research interest as the most promising candidates for the anodes of next-generation lithium-ion batteries, owing to their high energy density and mechanical buffering property. However, the major disadvantage of materials with ultra-high capacities, such as Si-based materials, is the significant volume change during cycling, which further leads to mechanical and electrochemical degradation. However, a sophisticated and quantitative understanding of the highly electrochemical-mechanical coupling behaviors is still lacking.A comprehensive computational model is indispensable in the developing process of the excellent performance of anode material due to the low-realizability, inconvenience, and high-cost of experiments, which also provides powerful tools for fabrication guidance of novel Si/C composites designs. Hence, a multiphysics modeling framework is established with a detailed geometric description to quantitatively reveal the underlying governing mechanisms of Si/C composite anode behaviors. We studied the effects of the Si weight percentage, the Si-related particle distribution, the Si-related particle size, the mechanical constraint, and the binder domain gradient on the battery performance regarding the potential behavior, capacity delivery, mechanical stress/strain, Li plating, and polarization evolution. In our study, we used silicon monoxide (SiO) as the Si element source and graphite (Gr) as the C element source. Results discover that an 8-10 wt% of SiO would be an optimal choice regarding capacity delivery and minimizing Li plating under 1C constant current charging condition. Positioning SiO particles near the separator and reducing the sizes of SiO particles are also demonstrated to be beneficial for electrochemical performance with trivial influence on mechanical mismatch. In addition, the mechanical constraint demonstrates a balanced effect on the overall performance of cells and the local behaviors of particles. Our findings also indicate that reducing the proportion of carbon-binder domain (CBD) in the upper domain (near the anode surface) compared to the lower domain (near the current collector) positively influences electrochemical performance, particularly in terms of capacity and Li plating. However, such an arrangement introduces potential risks of mechanical failures and we recommend to incorporate a higher proportion of CBD alongside the SiO particles. Finally, an anode design with a lower CBD proportion in the upper domain exhibits superior rate performance.This study explores the multiphysics behavior of Si/C anodes material using a comprehensive methodology combining experimental and FEA techniques, systematically revealing the coupling mechanism among various physical fields, as well as providing efficient and powerful tools in the design, development, and evaluation of high energy density lithium-ion batteries.

Using magnons as a quantum technology platform: a perspective

Traditional electronics rely on charge currents for controlling and transmitting information, resulting in energy dissipation due to electron scattering. Over the last decade, magnons, quanta of spin waves, have emerged as a promising alternative. This perspective article provides a brief review of experimental and theoretical studies on quantum and hybrid magnonics resulting from the interaction of magnons with other quasiparticles in the GHz frequency range, offering insights into the development of functional magnonic devices. In this process, we discuss recent advancements in the quantum theory of magnons and their coupling with various types of qubits in nanoscale ferromagnets, antiferromagnets, synthetic antiferromagnets, and magnetic bulk systems. Additionally, we explore potential technological platforms that enable new functionalities in magnonics, concluding with future directions and emerging phenomena in this burgeoning field.

Demonstration of high-efficiency microwave heating producing record highly charged xenon ion beams with superconducting electron cyclotron resonance ion sources

Intense highly charged ion beam production is essential for high-power heavy ion accelerators. A novel movable Vlasov launcher for superconducting high charge state electron cyclotron resonance ion source has been devised that can affect the microwave power effectiveness by a factor of about 4 in terms of highly charged ion beam production. This approach based on a dedicated microwave launching system instead of the traditional coupling scheme has led to new insight on microwave-plasma interaction. With this new understanding, the world record highly charged xenon ion beam currents have been enhanced by up to a factor of 2, which could directly and significantly enhance the performance of heavy ion accelerators and provide many new research opportunities in nuclear physics, atomic physics, and other disciplines. Published by the American Physical Society 2024

Extending battery life in CubeSats by charging current control utilizing a long short-term memory network for solar power predictions

Recently, there has been a surge in small satellites and CubeSats. A crucial factor limiting the duration of their missions is the lifespan of their batteries. Typically, batteries are charged immediately when there is sufficient power generated from the solar panels. However, this practice results in additional charging stress and degradation due to unnecessarily high current amplitudes. In this work, a distributed charging strategy based on solar power prediction is proposed to mitigate charging stress and thereby extend battery life, ensuring sufficient charging without jeopardizing spacecraft operation. The proposed method for power generation prediction relies on a Long Short-Term Memory (LSTM) network, trained on GOMX-4A satellite telemetry data. The proposed LSTM method performed an order of magnitude better, with a root mean square error (RMSE) of 0.2274 W, while a baseline prediction utilizing a Seasonal Auto-Regressive Moving Average has an RMSE of 1.2406 W. Using the predicted power generation from the LSTM method, the current is distributed using a proposed charging multiplier control, resulting in 72.0882% reduction in the median charging current. A direct possible impact on lithium-ion batteries was evaluated by employing an electrochemical model from the literature, confirming that the proposed strategy effectively reduces degradation caused by lithium plating. Moreover, the capacity fade in the example scenario at 25 °C was reduced by 0.0849%. The extent of degradation reduction will vary according to the required mission profile, the operational conditions, the specific chemistry, and the type of battery in use.

Assessment of Economic Viability of Direct Current Fast Charging Infrastructure Investments for Electric Vehicles in the United States

As the global transportation sector increasingly adopts electric vehicles, the demand for advanced and accessible charging infrastructure is rising. In addition to at-home electric vehicle (EV) charging, there is a growing need for the swift development of commercial direct current fast charging (DCFC) stations to meet on-the-go EV charging demands. While government funds are available to support the expansion of the EV charging network in the United States, the establishment of a robust nationwide EV charging infrastructure requires significant private sector investment. This study was conducted to assess the economic feasibility of various business models for fast charging stations in the U.S. using two case studies and exploring different operational strategies including sole ownership and collaborative ventures with public and private entities. The results indicate that based on the current adoption and utilization rates in the U.S., the business model involving an owner-operator collaborating with a public partner ensures profitability and protects the investment in DCFC stations from financial losses. The study also highlights that demand charges and electricity retail prices are the factors that affect the profitability of a DCFC station.

An optimized AC side startup strategy of E‐STATCOM for ITER pulsed power electrical network

AbstractDuring the operation of the ITER machine, hundreds of MW/Var of active and reactive power will be exchanged with the grid. The E‐STATCOM scheme composed of the Modular Multilevel Converter (MMC) and split supercapacitor energy storage has been proposed to improve the power compensation performance of the existing reactive power compensation system in the previous study. However, one of the main technical challenges which is lack of research is to precharge all submodule capacitors and supercapacitors from zero to their nominal voltage values efficiently during a startup process. As the capacitance and operating voltage of supercapacitors are much different from capacitors in each submodule, the startup of E‐STATCOM is a more complicated process. To coordinate the energy exchange between submodule capacitors and supercapacitors, submodule capacitors and the grid, this paper presents an optimized four‐stage AC side startup strategy for the E‐STATCOM. The proposed method minimizes the use of current‐limiting resistors while suppressing the surge current in the zero‐voltage startup process of supercapacitors, in addition to optimizing the energy consumption. The pulse current charging, constant current charging and constant power charging strategies of supercapacitors are adopted in different charging stages, and the detailed coordinated control scheme between submodule capacitors and supercapacitors are described and analyzed. The effectiveness and performance of the proposed method are verified by simulation results and hardware‐in‐the‐loop (HIL) experiments.

Revisiting Pulse-Based OCV Incremental Capacity Analysis for Diagnostics of Li-Ion Batteries

This paper presents the concept of applying incremental capacity analysis (ICA) on the OCV curve in the SoC space. The OCV curve can be obtained from any sequence of discharge or charge current or power pulse with a necessary rest period to allow the cell to reach a pseudo-OCV after each pulse. With a high resolution (&gt;100 pulses) in the full SoC window, an OCV-vs.-SoC curve can be obtained with sufficient accuracy to perform an ICA on the obtained OCV curve. ICA as a diagnostic technique has commonly been applied on Li-ion cells with constant charge and discharge at slow currents. However, a slow controlled constant current charge or discharge is normally not feasible and cannot be easily applied to a battery in an application. Here, we revisit pulse-based ICA to supplement the conventional constant-current-based technique. Based on actual ageing data, we show that ICA performed on a selection of high-resolution OCV curves is comparable or better than conventional ICA with constant current. The main advantage of OCV-ICA is that it can be applied to most cells and systems without a significant interruption of normal cell operation. OCV-ICA can provide valuable insights into ageing mechanisms as well as, e.g., detailed information on changes in internal resistance.

Flavor composition of ultrahigh-energy cosmic neutrinos: Measurement forecasts for in-ice radio-based EeV neutrino telescopes

In-ice radio detection is a promising technique to discover and characterize ultrahigh-energy (UHE) neutrinos, with energies above 1017 eV, adopted by present—ARA, ARIANNA, and RNO-G—and planned—IceCube-Gen2—experiments. So far, their ability to measure neutrino flavor had remained unexplored. We show and quantify how the neutrino flavor can be measured with in-ice radio detectors using two complementary detection channels. The first channel, sensitive to νe, identifies them via their charged-current interactions, whose radio emission is elongated in time due to the Landau-Pomeranchuk-Migdal effect. The second channel, sensitive to νμ and ντ, identifies events made up of multiple showers generated by the muons and taus they generate. We show this in state-of-the-art forecasts geared at IceCube-Gen2, for representative choices of the UHE neutrino flux. This newfound sensitivity could allow us to infer the UHE neutrino flavor composition at their sources—and thus the neutrino production mechanism—and to probe UHE neutrino physics. Published by the American Physical Society 2024

Enhanced detection sensitivity of X-ray detectors via CdSe nanoplatelet aspect ratio control

This study investigated the use of inorganic cadmium selenide nanoplatelets (CdSe NPLs) to enhance the performance of X-ray detectors. The active layer of the detector comprised a bulk heterojunction composed of PCDTBT:PC71BM: CdSe NPLs with three different aspect ratios (ARs = 3:1, 1:1, and 6:1). The CdSe NPLs, synthesized with a thickness of five monolayers, were controlled by adjusting the molar mass ratios of Cd(OAc)2 and Cd(OAc)2∙2 H2O. Each detector was characterized by analyzing its series resistance, collection irradiation, dark current density, detection sensitivity, charge mobility, and defect density via the collected charges. The detector containing CdSe NPLs with an aspect ratio of 1:1 demonstrated the most favorable performance, exhibiting improved carrier generation and transport properties, resulting in a 23.36 % increase in sensitivity compared with the detector without CdSe NPLs. Through experimentation, the optimal content of CdSe NPLs in the active layer was determined to be 1 wt%, yielding the highest sensitivity of 3.96 × 103 μC∙Gy−1∙cm−2. This study underscores the potential of CdSe NPLs as promising materials for X-ray detector applications.

Target decomposition-led light-weighted offline training strategy-aided data-driven state-of-charge online estimation during constant current charging conditions over battery entire lifespan

This paper develops a novel target decomposition-led light-weighted offline training strategy-aided data-driven state-of-charge (SOC) online estimation method during constant current (CC) charging conditions over battery entire lifespan. Firstly, real SOC is conceptually decomposed into base SOC and SOC error. Subsequently, taking voltage and real SOC of initial CC charging cycle as input and output, machine learning algorithm is adopted to offline establish base SOC acquisition model without considering battery aging. Thirdly, the errors between real SOC and acquired base SOC are calculated, where the extremely similar distribution of SOC error against different battery degradation with two aging-dependent peaks can be clearly observed. Following this precious characteristic, a SOC error calculation model is further built only via several typical CC charging cycles with base SOC and battery capacity as input. Finally, the acquired base SOC is compensated by the computed SOC error for real SOC calculation. The validation results demonstrate that the proposed target decomposition-led method has overwhelming advantages in light-weighted offline training and accurate SOC online estimation during CC charging conditions, where maximum mean absolute error and maximum root mean squared error of SOC estimation results over the same type of batteries’ entire lifespan are only 0.98 % and 1.2 %, respectively.

Inclusive cross section measurements in final states with and without protons for charged-current νμ -Ar scattering in MicroBooNE

A detailed understanding of inclusive muon neutrino charged-current interactions on argon is crucial to the study of neutrino oscillations in current and future experiments using liquid argon time projection chambers. To that end, we report a comprehensive set of differential cross section measurements for this channel that simultaneously probe the leptonic and hadronic systems by dividing the channel into final states with and without protons. Measurements of the proton kinematics and proton multiplicity of the final state are also presented. For these measurements, we utilize data collected with the MicroBooNE detector from 6.4×1020 protons on target from the Fermilab booster neutrino beam at a mean neutrino energy of approximately 0.8 GeV. We present in detail the cross section extraction procedure, including the unfolding, and model validation that uses data to model comparisons and the conditional constraint formalism to detect mismodeling that may introduce biases to extracted cross sections that are larger than their uncertainties. The validation exposes insufficiencies in the overall model, motivating the inclusion of an additional data-driven reweighting systematic to ensure the accuracy of the unfolding. The extracted results are compared to a number of event generators and their performance is discussed with a focus on the regions of phase space that indicate the greatest need for modeling improvements. Published by the American Physical Society 2024

First Simultaneous Measurement of Differential Muon-Neutrino Charged-Current Cross Sections on Argon for Final States with and without Protons Using MicroBooNE Data.

We report the first double-differential neutrino-argon cross section measurement made simultaneously for final states with and without protons for the inclusive muon neutrino charged-current interaction channel. The proton kinematics of this channel are further explored with a differential cross section measurement as a function of the leading proton's kinetic energy that extends across the detection threshold. These measurements use data collected with the MicroBooNE detector from 6.4×10^{20} protons on target from the Fermilab booster neutrino beam with a mean neutrino energy of ∼0.8 GeV. Extensive data-driven model validation utilizing the conditional constraint formalism is employed. This motivates enlarging the uncertainties with an empirical reweighting approach to minimize the possibility of extracting biased cross section results. The extracted nominal flux-averaged cross sections are compared to widely used event generator predictions revealing severe mismodeling of final states without protons for muon neutrino charged-current interactions, possibly from insufficient treatment of final state interactions. These measurements provide a wealth of new information useful for improving event generators which will enhance the sensitivity of precision measurements in neutrino experiments.

Reinforcement learning-based charging cluster determination algorithm for optimal charger placement in wireless rechargeable sensor networks

Wireless power transfer (WPT) provides a promising technology for energy replenishment of wireless rechargeable sensor networks (WRSNs), where wireless chargers can be deployed at fixed locations for charging nodes simultaneously within their effective charging range. Optimal charger placement (OCP) for sustainable operations of WRSN with cheaper charging cost is a challenging and difficult problem due to its NP-completeness in nature. This paper proposes a novel reinforcement learning (RL) based approach for OCP, where the problem is firstly formulated as a charging cluster determination problem with a fixed clustering radius and then tackled by the reinforcement learning-based charging cluster determination (RL-CCD) algorithm. Specifically, nodes are coarsely clustered by the K-Means++ algorithm, with chargers placed at the cluster center. Meanwhile, RL is applied to explore the potential locations of the cluster centers to adjust the center locations and reduce the number of clusters, using the number of nodes in the cluster and the summation of distances between the cluster center and nodes as the reward. Moreover, an experience-strengthening mechanism is introduced to learn the current optimal charging experience. Extensive simulations show that RL-CCD significantly outperforms existing algorithms.

Tunable intermediate states for neuromorphic computing with spintronic devices

In the pursuit of advancing neuromorphic computing, our research presents a novel method for generating and precisely controlling intermediate states within heavy metal/ferromagnet systems. These states are engineered through the interplay of a strong in-plane magnetic field and an applied charge current. We provide a method for fine-tuning these states by introducing a small out-of-plane magnetic field, allowing for the modulation of the system’s probabilistic response to varying current levels. We also demonstrate the implementation of a spiking neural network (SNN) with a tri-state spike timing-dependent plasticity (STDP) learning rule using our devices. Our research furthers the development of spintronics and informs neural system design. These intermediate states can serve as synaptic weights or neuronal activations, paving the way for multi-level neuromorphic computing architectures.

Generalized eikonal identities for charged currents

We discuss QED radiative corrections to contact operators coupling two heavy fields and one light field. These operators appear ubiquitously in weak interactions with nuclei such as beta decay and neutrino nucleus scattering. New eikonal identities are derived in the static limit (i.e., neglecting nuclear recoil) that allow for manifest power counting of enhancements proportional to the charge of the nucleus. We apply these new identities to nuclear beta decays and find that the “independent particle model” used by Jaus, Rasche, Sirlin & Zucchini is closely related, though not identical, to a model independent effective field theorcalculation.

Three-Coil Wireless Charging System Based on S-PS Topology

To protect the battery, radio energy transmission charging typically uses constant current (CC) charging before switching to constant voltage (CV) charging to enhance battery durability. This paper proposes adding an auxiliary clamp coil to the original circuit topology. The IPT battery charger designed with the auxiliary clamp coil can achieve both constant current (CC) and constant voltage (CV) outputs. The mutual inductance between the auxiliary clamp coil and the primary side coil greatly influences the output performance of the entire IPT system, so the auxiliary clamp coil should not be too large. To solve this problem, an S-S-PS circuit with secondary compensation topology in the secondary coil is proposed. This circuit topology reduces the size of the auxiliary clamp coil, allowing it to be placed in an optimal position. When the constant voltage output critical position is reached, the IPT system can still automatically, continuously, and smoothly switch between CC and CV modes. Consequently, this approach avoids increased cost consumption associated with detecting CC-CV switching thresholds, adding wireless transmission communication modules, real-time control of the power transmitter, and active protection of the circuit during constant current charging. Finally, a 48 V/2.5 A prototype was built to verify that the IPT system has CC-CV conversion functionality.

Exploring spin current and dielectric switching characteristics of doped-multiferroic in hexagonal phase for advance RAM technology: A theoretical study

The single-phase bismuth ferrite BiFeO3 (BFO) has garnered significant interest due to its spintronic-based switching properties observed at room temperature. The first-principles calculations were executed to examine the spin-polarized electronic, dielectric, and structural characteristics of co-doped BFO with lanthanum (La) at A-site and cobalt (Co), nickel (Ni) at B-site in its hexagonal phase (Bi1-αLaαFe1-βNiβO3 with α = β = 0.04) with generalized gradient approximation (GGA-PBE). The highest value (1.01 × 10−11 A) of total current observed in La Ni co-doped BFO, featuring a distinct spin current of the same magnitude, attributed to spin polarization at the Fermi level (100 %). Additionally, Co-doped BFO exhibits the highest observed spin current density (1.05 × 109A/m2) and charge current density (1.03 × 10−5A/m2). In case of dielectric switching properties, the Ni-doped BFO displays the lowest values of linear dielectric polarization (6.00 × 10−2 C/m2), polarization charge at its interface (1.27 × 10−17 C), capacitance (4.23 × 10−15 F), and switching energy (3.81 × 10−19 J), which is particularly lower than the reported switching energy (1.92 aJ) of multiferroic capacitor.

Fuel Cell-Based Inductive Power Transfer System for Supercapacitor Constant Current Charging

The majority of urban CO2 emissions come from the transportation sector. To be able to reduce them, it is definitely necessary to replace Internal Combustion Engine (ICE) vehicles with electric ones. In this article, a public transport system is proposed, consisting of a supercapacitor (SC)-powered electric vehicle (EV) charged through a fuel cell-powered (FC) Inductive Power Transfer (IPT) system. The bus runs the usual route and it is charged each time it reaches the terminal, where the charging system is placed. The main advantages of the proposed system are related to the long-term cost of the EV, compared to a classic battery-powered system, to the aspects of ease of use and safety for charging operations and to the possibility of realizing a net-zero-energy transport system thanks to the use of green hydrogen. In addition, the proposed charging methodology allows for better energy utilization avoiding major changes to the main power grid. In this article, the system is presented considering a real case study; it is simulated at system and hardware level, and then validated through the realization of a scaled-down prototype.

An improved wireless power transmission system for micro unmanned aerial vehicles

AbstractDue to its limited load capacity, the piggybacking of wireless charging systems for micro unmanned aerial vehicles has become a challenging task in the design of micro unmanned aerial vehicles. Therefore, this paper proposes an improved lightweight design method for micro unmanned aerial vehicles to carry a wireless charging system. The improved system uses an inductor–capacitor–capacitor‐parallel (LCC‐P) topology compensation network instead of a bilateral inductor–capacitor–capacitor (LCC) topology compensation network to achieve constant current charging (CC) and constant voltage charging (CV). Then the adaptive frequency conversion control is used to realize the automatic conversion from CC charging to CV charging during the charging process. Compared with the traditional wireless charging system based on a direct current‐direct current converter (DC‐DC converter) to achieve CC charging and CV charging, this improved system reduces the total weight of the receiving end of the wireless charging system based on ensuring the charging efficiency, which meets the demand of wireless charging systems carried by micro drone aircraft. The test results of the constructed physical system coincide with the simulation design results, and the total weight of the receiving end is only 8 g, which verifies the correctness and effectiveness of the improved design scheme.