Data-driven short circuit resistance estimation in battery safety issues

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Extreme Learning Machine-Based Thermal Model for Lithium-Ion Batteries of Electric Vehicles under External Short Circuit

External short circuit(ESC)of lithium-ion batteries is one of the common and severe electrical failures in electric vehicles.In this study,a novel thermal modelis developed to capture the temperature behavior of batteries under ESC conditions.Experiments were systematically performed under different battery initial state of charge and ambient temperatures.Based on the experimental results,we employed an extreme learming machine(ELM)-based thermal(ELMT)model to depict battery temperature behavior under ESC,where a lumped-state thermal model was used to replace the activation function of conventional ELMs.To demonstrate the effectiveness of the proposed model,wecompared the ELMT model with a multi-lumped-state thermal(MLT)model parameterized by thegenetic algorithm using the experimental data from various sets of battery cells.It is shown that the ELMT model can achieve higher computa-tional efficiency than the MLT model and better fitting and prediction accuracy,where the average root mean squared error(RMSE)of the fitting is 0.65℃ for the ELMT model and 3.95℃ for the MLT model,and the RMES of the prediction under new data set is 3.97℃ for the ELMT model and 6.11℃ for the MLT model.

Internal short circuit evaluation and corresponding failure mode analysis for lithium-ion batteries

Internal short circuit(ISC)is the major failure problem for the safe application of lithium-ion batteries,especially for the batteries with high energy density.However,how to quantify the hazard aroused by the ISC,and what kinds of ISC will lead to thermal runaway are still unclear.This paper investigates the thermal-electrical coupled behaviors of ISC,using batteries with Li(Ni_(1/3)CO_(1/3)Mn_(1/3))O_(2) cathode and composite separator.The electrochemical impedance spectroscopy of customized battery that has no LiPF6 salt is utilized to standardize the resistance of ISC.Furthermore,this paper compares the thermal-electrical coupled behaviors of the above four types of ISC at different states-of-charge.There is an area expansion phenomenon for the aluminum-anode type of ISC.The expansion effect of the failure area directly links to the melting and collapse of separator,and plays an important role in further evolution of thermal runaway.This work provides guidance to the development of the ISC models,detection algorithms,and correlated countermeasures.

A fault warning for inter-turn short circuit of excitation winding of synchronous generator based on GRU-CNN

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.

DETECTION AND ANALYSIS OF WELD POOL SHAPE FOR CO_2 SHORT CIRCUITING ARC WELDING

A general industrial CCD( ICCD) camera is redesigned to detect the weld pool without arc at the period of short circuiting, so that the interference of arc and spatter during CO2 short circuiting arc welding is eliminated. Through the analysis of weld pool image, both size parameters (such as weld pool area A, weld pool length L1, L2 and weld pool breadth b) and contour parameters (b, which describe the curves of weld pool boundany) ,which could indicate the shape features of weld pool, had been defined to express weld pool information quantitatively. The investigation of the relationships between weld pool shape parameters and welding process parameters may be beneficial to the quality control of CO2 welding.

Study on chaos in short circuit gas metal arc welding process

Based on the chaos theory, an idea is put forward to analyze the short circuit Gas Metal Arc Welding （ GMAW-S） process. The theory of phase space reconstruction and related algorithms such as mutual information and so on, are applied to analyze the chaos of the GMAW-S process. The largest Lyapunov exponents of some current time series are calculated, and the results indicate that chaos exists in the GMAW-S process. The research of the chaos in the GMAW-S process can be help to get new knowledge of the process.

Influence of optical interference and carrier lifetime on the short circuit current density of organic bulk heterojunction solar cells

Based on simple analytical equations, short circuit current density （Jsc） of the organic bulk heterojunction solar cells has been calculated. It is found that the optical interference effect plays a very important role in the determination of Jsc; and obvious oscillatory behaviour of Jsc was observed as a function of thickness. At the same time, the influence of the carrier lifetime on Jsc also cannot be neglected. When the carrier lifetime is relatively short, Jsc only increases at the initial stage and then decreases rapidly with the increase of active layer thickness. However, for a relatively long carrier lifetime, the exciton dissociation probability must be considered, and Jsc behaves wave-like with the increase of active layer thickness. The validity of this model is confirmed by the experimental results.

Investigation on microprocessor based waveform control of short circuit transfer CO_2 welding

A new kind of simple and flexible CO2 welding system was developed to carry out waveform control. The system consisted of IGBT inverter, PWM circuit and microprocessor unit （ MPU） , in which the output current of constant current （CC） power supply could be changed according to transient physical state, and the variable down slope rate control could be used to ensure a stable welding process. The welding experiment results proved the effectiveness of this control approach.

Determining the feature values of parameters indicating the critical states of molten metal bridge in short circuit transfer

Short circuit transfer involves bridging between the consumable electrode and the weld pool, associated with variations of electrical parameters which characterize the change of molten metal bridge state and are very important for the control of .spatter. In this paper, electrical process parameters and short circuit transfer images were simultaneously recorded with a LabView-based synchronous sensing and visualizing system. The arc^bridge resistance and derivatives of welding current, arc voltage and arc resistance at various instants were calculated by means of offline analysis of the welding current, arc voltage and droplet images. Parameters and their feature values indicating the onset of short circuit and the oncoming necking-down of molten metal bridge were determined. Using the calculated feature values, bridge-state-feedback control for .short circuit transfer was realized with a spatter rate less than 0. 25%.

Appearance and characteristics of non explosive short circuit transfer using basic electrodes

By means of high-speed photograph and synchronous oscillograph, the appearance and technical features of non-explosive short circuiting transfer using basic electrodes are investigated, and the conditions to form this metal transfer mode are discussed. It is shown that the metal transfer mode has its high frequency of droplet, short period of arc extinguishing and long arc igniting period. This metal transfer mode is expected for basic electrodes for its less spatter and higher deposition efficiency.

The Detection of Inter-Turn Short Circuits in the Stator Windings of Sensorless Operating Induction Motors

This work proposes an alternative strategy to the use of a speed sensor in the implementation of active and reactive power based model reference adaptive system (PQ-MRAS) estimator in order to calculate the rotor and stator resistances of an induction motor (IM) and the use of these parameters for the detection of inter-turn short circuits (ITSC) faults in the stator of this motor. The rotor and stator resistance estimation part of the IM is performed by the PQ-MRAS method in which the rotor angular velocity is reconstructed from the interconnected high gain observer (IHGO). The ITSC fault detection part is done by the derivation of stator resistance estimated by the PQ-MRAS estimator. In addition to the speed sensorless detection of ITSC faults of the IM, an approach to determine the number of shorted turns based on the difference between the phase current of the healthy and faulty machine is proposed. Simulation results obtained from the MATLAB/Simulink platform have shown that the PQ-MRAS estimator using an interconnected high-gain observer gives very similar results to those using the speed sensor. The estimation errors in the cases of speed variation and load torque are almost identical. Variations in stator and rotor resistances influence the performance of the observer and lead to poor estimation of the rotor resistance. The results of ITSC fault detection using IHGO are very similar to the results in the literature using the same diagnostic approach with a speed sensor.

Test for random in electrical signals time series of CO_2 short circuit transition welding process by the method of surrogate data

This paper introduced the basic theory and algorithm of the surrogate data method, which proposed a rigorous way to detect the random and seemingly stochastic characteristics in a system. The Gaussian data and the Rossler data were used to show the availability and effectivity of this method. According to the analysis by this method based on the short-circuiting current signals under the conditions of the same voltage and different wire feed speeds, it is demonstrated that the electrical signals time series exhibit apparently randomness when the welding parameters do not match. However, the electrical signals time series are deterministic when a match is found. The stability of short-circuiting transfer process could be judged exactly by the method of surrogate data.

A New Method of Early Short Circuit Detection

To reduce the pressure on contacts and circuit breaker and realize the zone selective interlocking (ZSI) function above the instantaneous protection threshold (e.g., >10In), the short circuit current needs to be early detected. The state-of–art of early short circuit detection (ESCD) method is reviewed. Based on the equivalent model of the short circuit, a new method based on the current and its integration is proposed. The prospective current value can be detected in the early stage of the short circuit. According to the evaluation result, the short circuit current can be early forecasted with the proposed method.

Study on Short Circuit Current Calculation of Power System with UHVDC and New Energy Source

With the development of power system, the level of short circuit current will increase accordingly. In general, the influence of the HVDC system and the new energy source is not considered in the calculation of the short circuit current. For the power grid that short circuit current level closes to the interrupting capacity of circuit breaker, it’s necessary to fully consider all kinds of influence factors, careful checking, so as to obtain more accurate calculation results of short circuit current. In 2018, two ±800 kV high-power Ultra High Voltage Direct Current (UHVDC) transmission projects will be connected with Shaanxi power grid, accompanied by a lot of concomitant fossil-fuel generating plants as power resource, and also a large number of new energy source, includes wind power generation and photovoltaic power generation. Around one of the UHVDC converter stations, short circuit current may exceed the withstand limit of some certain circuit breakers. In order to get more accurate short circuit current calculation results, three measures are used: 1) contrastive calculation and analysis by algorithm based on schemes and algorithm based on power flow;2) analysis the influence of UHVDC by electromagnetic transient and electromechanical transient hybrid simulation;3) considered a detailed model of Doubly Fed Induction Generator (DFIG) with low voltage ride through characteristics. The calculation results shows that: in the typical operation mode of Shaanxi power grid of 2018, the original calculation results by conventional calculation method are coincident with the results by considering the influence of algorithms, UHVDC and DFIG in large, in which: the results of the algorithm based on power flow are smaller than that of the algorithm based on schemes about 2 - 8 kA;the steady values of the short circuit current provided by UHVDC converterstation (includes rectifiers and smoothing capacitors) are about 0 - 3 kA;the steady values of the short circuit current provided by DFIG are about 0 - 5 kA. The calculation results can provide reference for the selection of the circuit breaker, and it can be verified by fault recording data in the future.

Study on Effect of UHV Power Grid Construction Schemes on Short Circuit Current

The commissioning of Southern Hami-Zhengzhou ±800 kV UHVDC transmission project has important significance to heighten operation reliability, transfer capability and supply electric ability of Henan power grid. However, short circuit currents of 500 kV buses in the Center of Henan are almost close to the operation upper limitation. In order to decrease the short circuit currents effectively, it’s necessary to strengthen the network structure of Center of Henan power grid and calculate short circuit currents. Two schemes of strengthening the network structure of Center of Henan power grid are studied. The calculated values of short circuit currents of some important 500 kV buses in the two schemes are still bigger than excepted. According to the latest Plan of State Grid, Yubei UHV substation and Zhumadian UHV substation located in Henan power grid. The calculated values of short circuit currents of some important 500 kV buses with the commissioning of Yubei UHV and Zhumadian UHV are qualified. So, reasonable network structure with UHV is suitable to heighten transfer capability and supply electric ability of Henan power grid.

Fault Diagnosis Based on ANN for Turn-to-Turn Short Circuit of Synchronous Generator Rotor Windings

Rotor winding turn-to-turn short circuit is a common electrical fault in steam turbines. When turn-to-turn short circuit fault happens to rotor winding of the generator, the generator terminal parameters will change. According to these parameters, the conditions of the rotor winding can be reflected. However, it is hard to express the relations between fault information and generator terminal parameters in accurate mathematical formula. The satisfactory results in fault diagnosis can be obtained by the application of neural network. In general, the information about the severity level of the generator faults can be acquired directly when the faulty samples are found in the training samples of neural network. However, the faulty samples are difficult to acquire in practice. In this paper, the relations among active power, reactive power and excitation current are discovered by analyzing the generator mmf with terminal voltage constant. Depending on these relations, a novel diagnosis method of generator rotor winding turn-to-turn short circuit fault is proposed by using ANN method to obtain the fault samples directly, without destructive tests.

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.