A SOE estimation method for lithium batteries considering available energy and recovered energy

State of energy (SOE) is a critical index of lithium battery. The problem of the inaccurate available energy and recovered energy of lithium battery affects the accuracy of SOE estimation. In order to solve the problem, this paper proposes a method to estimate the available discharge energy of lithium batteries based on response surface model. In this method, the energy efficiency of lithium batteries in different states is obtained by establishing the relationship model of external charge voltage and external discharge voltage, so as to estimate the actual available energy of lithium batteries in different charge states. On this basis, a correction method based on radial basis function (RBF) neural network is proposed to estimate the actual energy released by the recovered energy when the current direction of the battery is changed. The proposed energy correction method is combined with the adaptive particle filter algorithm to estimate SOE. This method is not limited to the assumption of Gaussian function and can accurately predict the noise variance, so as to improve the estimation accuracy of SOE. Simulations under urban dynamometer driving schedule (UDDS) are conducted, and the result shows that the proposed method can effectively estimate the battery energy and improve the accuracy of SOE estimation.

Effect of Charge Voltage on the Microstructural, Mechanical, and Tribological Properties of Mo–Cu–V–N Nanocomposite Coatings

As an important high-power impulse magnetron sputtering (HIPIMS) parameter, charge voltage has a significant influence on the microstructure and properties of hard coatings. In this work, the Mo–Cu–V–N coatings were prepared at various charge voltages using HIPIMS technique to study their mechanical and tribological properties. The microstructure was analyzed by scanning electron microscope (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM). The mechanical and tribological properties were investigated by nano-indentation and ball-on-disc tribometer. The results revealed that all the coatings showed a solid-solution phase of B1-MoVN, the V atoms dissolved into face-centered cubic (FCC) B1-MoN lattice by partial substitution of Mo, and formed a solid-solution phase. Even at a high Cu content (~8.8 at. %), the Cu atoms existed as an amorphous phase. When the charge voltage increased, more energy was put into discharge, and the microstructure changed from coarse structure into dense columnar structure, resulting in the highest hardness of 28.2 GPa at 700 V. An excellent wear performance with low friction coefficient of 0.32 and wear rate of 6.3 × 10−17 m3/N·m was achieved at 750 V, and the wear mechanism was dominated by mild abrasive and tribo-oxidation wear.

An air insulated linear pulse transformer for electrodischarge technology

A linear pulse transformer with air insulation at atmospheric pressure was created and tested under both constant resistance and non linear loads. The maximum power of the transformer output pulse reached ∼500 MW at a matched load with a charge voltage 50 kV. The transformer transferred ∼60% of the stored energy to the load over a characteristic time of about 1 μs. The scalability the generator was studied by connecting two identical transformers in series which gave a power output of ∼850 MW with doubled output voltage and reduced current. The frequency mode of operation was studied using one and two transformers with a charge voltage of 50 kV and a load that was, close to matched. In both cases, the power maximum and jitter showed no significant changes at any of the frequencies tested (up to 5 Hz). These results mean that the use of this generator can be recommended for a wide field of applications due to its scalability and low internal impedance.

Modeling Battery Connections in the Electronic Lab

The paper deals with the modeling of the processes of charge-discharge of battery assemblies taking into account their degradation. The results of simulating the cyclic operation of battery assemblies in the Electronics Workbench electronic laboratory are presented, possible schemes of inclusion are given, and options for re-switching batteries during operation are considered as well as connecting additional elements to extend the life of the connection. The simulation took into account the presence of one defective battery in the assembly. The operation of the assembly with a defective battery and a reference battery was compared. As a result of the analysis of parallel-serial and serial-parallel battery connections, the first one is considered preferable. For an assembly with a parallel-serial connection, the time parameters of operation remained almost unchanged, but the differences in the voltages of the defective and other batteries changed more than twice as compared with a serial-parallel connection. The changes in charge, voltage and current of assemblies with a degraded battery and a reference battery are analyzed. Timing diagrams are shown for batteries connected in parallel and in series with defective batteries. Power losses in a defective battery are reduced by choosing a parallel-series assembly, while switching a connection from a serial-parallel connection to a parallel-series one does not lead to compensation for the degradation of battery parameters. Changing the switching time intervals in a wide range does not contribute to increasing the capacity of a defective battery. Degradation of battery parameters leads to sharper surges in voltage, charge and current. The additional power recharge of the defective battery maintains the performance of the entire assembly. Recharge can be performed by connecting in parallel a defective additional battery or a capacitor, which is equivalent to replacing a degraded battery with a new one.

Applicability of Different Double-Layer Models for the Performance Assessment of the Capacitive Energy Extraction Based on Double Layer Expansion (CDLE) Technique

Capacitive energy extraction based on double layer expansion (CDLE) is a renewable method of harvesting energy from the salinity difference between seawater and freshwater. It is based on the change in properties of the electric double layer (EDL) formed at the electrode surface when the concentration of the solution is changed. Many theoretical models have been developed to describe the structural and thermodynamic properties of the EDL at equilibrium, e.g., the Gouy–Chapman–Stern (GCS), Modified Poisson–Boltzmann–Stern (MPBS), modified Donnan (mD) and improved modified Donnan (i-mD) models. To evaluate the applicability of these models, especially the rationality and the physical interpretation of the parameters that were used in these models, a series of single-pass and full-cycle experiments were performed. The experimental results were compared with the numerical simulations of different EDL models. The analysis suggested that, with optimized parameters, all the EDL models we examined can well explain the equilibrium charge–voltage relation of the single-pass experiment. The GCS and MPBS models involve, however, the use of physically unreasonable parameter values. By comparison, the i-mD model is the most recommended one because of its accuracy in the results and the meaning of the parameters. Nonetheless, the i-mD model alone failed to simulate the energy production of the full-cycle CDLE experiments. Future research regarding the i-mD model is required to understand the process of the CDLE technique better.

Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Deep Learning and Soft Sensing

The Remaining useful life (RUL) prediction is of great concern for the reliability and safety of lithium-ion batteries in electric vehicles (EVs), but the prediction precision is still unsatisfactory due to the unreliable measurement and fluctuation of data. Aiming to solve these issues, an adaptive sliding window-based gated recurrent unit neural network (GRU NN) is constructed in this paper to achieve the precise RUL prediction of LIBs with the soft sensing method. To evaluate the battery degradation performance, an indirect health indicator (HI), i.e., the constant current duration (CCD), is firstly extracted from charge voltage data, providing a reliable soft measurement of battery capacity. Then, a GRU NN with an adaptive sliding window is designed to learn the long-term dependencies and simultaneously fit the local regenerations and fluctuations. Employing the inherent memory units and gate mechanism of a GRU, the designed model can learn the long-term dependencies of HIs to the utmost with low computation cost. Furthermore, since the length of the sliding window updates timely according to the variation of HIs, the model can also capture the local tendency of HIs and address the influence of local regeneration. The effectiveness and advantages of the integrated prediction methodology are validated via experiments and comparison, and a more precise RUL prediction result is provided as well.

Electrolyte/Structure-Dependent Cocktail Mediation Enabling High-Rate/Low-Plateau Metal Sulfide Anodes for Sodium Storage

As promising anodes for sodium-ion batteries, metal sulfides ubiquitously suffer from low-rate and high-plateau issues, greatly hindering their application in full-cells. Herein, exemplifying carbon nanotubes (CNTs)-stringed metal sulfides superstructure (CSC) assembled by nano-dispersed SnS2 and CoS2 phases, cocktail mediation effect similar to that of high-entropy materials is initially studied in ether-based electrolyte to solve the challenges. The high nano-dispersity of metal sulfides in CSC anode underlies the cocktail-like mediation effect, enabling the circumvention of intrinsic drawbacks of different metal sulfides. By utilizing ether-based electrolyte, the reversibility of metal sulfides is greatly improved, sustaining a long-life effectivity of cocktail-like mediation. As such, CSC effectively overcomes low-rate flaw of SnS2 and high-plateau demerit of CoS2, simultaneously realizes a high rate and a low plateau. In half-cells, CSC delivers an ultrahigh-rate capability of 327.6 mAh g−1anode at 20 A g−1, far outperforming those of monometallic sulfides (SnS2, CoS2) and their mixtures. Compared with CoS2 phase and SnS2/CoS2 mixture, CSC shows remarkably lowered average charge voltage up to ca. 0.62 V. As-assembled CSC//Na1.5VPO4.8F0.7 full-cell shows a good rate capability (0.05 ~ 1.0 A g−1, 120.3 mAh g−1electrode at 0.05 A g−1) and a high average discharge voltage up to 2.57 V, comparable to full-cells with alloy-type anodes. Kinetics analysis verifies that the cocktail-like mediation effect largely boosts the charge transfer and ionic diffusion in CSC, compared with single phase and mixed phases. Further mechanism study reveals that alternative and complementary electrochemical processes between nano-dispersed SnS2 and CoS2 phases are responsible for the lowered charge voltage of CSC. This electrolyte/structure-dependent cocktail-like mediation effect effectively enhances the practicability of metal sulfide anodes, which will boost the development of high-rate/-voltage sodium-ion full batteries.

Simulation Charging of the Forming Line by the Operator Method

The application of repeated Laplace transform to the analysis of a line with distributed parameters is considered. As an example, pulse forming lines are analyzed, which are widely used in microwave radio devices and high-current charged particle accelerators. The results of the calculation of the charge voltage of the forming line from the voltage source are given. The dependence of the line charging mode on the relationship between the internal resistance of the source and the characteristic impedance of the line is shown.

Expansion of cylindrical tubular workpieces on high-voltage magnetic-pulse installation with controlled vacuum discharger

Purpose. An experimental verification of the existence of a range of values for the parameters of the capacitive energy storage of the magnetic-pulse installations with controlled vacuum discharger, in which, with a high probability, there is a «cut» of the discharge current pulses and the expansion of cylindrical thin-walled tubular workpieces using an external coil. Methodology. High voltage magnetic-pulse installation of NTU «KhPI» with controlled vacuum discharger, multiturn coil with inside dielectrical die and inside aluminum alloy workpiece are used. The capacitance and charge voltage of capacitive energy storage are changed. Discharge current pulses are measured by Rogowski coil and the oscillograph. Results. Parts of complicated shape are made by expansion of cylindrical tubular workpieces with help of external coil. Pressed metallic tubular part is removable from inner dielectric rod. Originality. The frequency of «cut» pulse is defined by negative magnetic field pressure amplitude. It is shown that we must coordinate this frequency and charge voltage with capacitive storage parameters by high probability of pulse «cut». Practical value. It is shown how to use installations with controlled vacuum dischargers in magnetic forming technology based on «cut» pulses.

The AMIGO1 adhesion protein modulates movement of Kv2.1 voltage sensors

Voltage-gated potassium (Kv) channels sense voltage and facilitate transmembrane flow of K+ to control the electrical excitability of cells. The Kv2.1 channel subtype is abundant in most brain neurons and its conductance is critical for homeostatic regulation of neuronal excitability. Many forms of regulation modulate Kv2.1 conductance, yet the biophysical mechanisms through which the conductance is modulated are unknown. Here, we investigate the mechanism by which the neuronal adhesion protein AMIGO1 modulates Kv2.1 channels. With voltage clamp recordings and spectroscopy of heterologously expressed Kv2.1 and AMIGO1 in mammalian cell lines, we show that AMIGO1 modulates Kv2.1 voltage sensor movement to change Kv2.1 conductance. AMIGO1 speeds early voltage sensor movements and shifts the gating charge-voltage relationship to more negative voltages. Fluorescence measurements from voltage sensor toxins bound to Kv2.1 indicate that the voltage sensors enter their earliest resting conformation, yet this conformation is less stable upon voltage stimulation. We conclude that AMIGO1 modulates the Kv2.1 conductance activation pathway by destabilizing the earliest resting state of the voltage sensors.