3722results about "Electrical testing" patented technology

An apparatus is dedicated to controlling the voltage of a battery comprising at least two modules connected in series and each comprising at least one electrochemical cell, and each coupled to voltage balancing means. The apparatus comprises measurement means for determining first voltages across the terminals of each of the modules, calculation means for measuring a second voltage across the terminals of the battery and for determining a mean voltage per module representative of the second voltage divided by the number of modules, and processor means for comparing each measured first voltage with the mean voltage per module and for delivering to the balancing means signals representative of the result of the comparison whenever the first voltage of a module is greater than the mean voltage, such that the balancing means reduce the voltage across the terminals of the module.

An apparatus for diagnosing a battery according to an embodiment of the present disclosure includes a voltage measuring unit configured to measure a voltage of a battery during a discharge process of the battery; a pulse output unit configured to generate a discharge pulse at every predetermined cycle and output the generated discharge pulse to the battery; and a control unit configured to calculate a resistance value of the battery based on a voltage deviation of the battery due to the discharge pulse, determine a resistance pattern in a preset initial discharge region based on the calculated resistance value, and diagnose whether there is lithium precipitation in the battery according to the determined resistance pattern.

There is provided a charge / discharge inspection system that enables easy maintenance such as cleaning the tips of probes or replacing defective probes without a complex configuration. The charge / discharge inspection system includes: a battery inspection unit of a charge / discharge inspection apparatus; a tray that is capable of containing a probe unit, a charge / discharge power supply unit, and a charge / discharge power supply-integrated probe unit in a storage part, is conveyed with one of them contained in the tray, and is placed in the battery inspection unit; and a conveying apparatus that conveys the tray from the battery inspection unit to another location, or conveys the tray from another location to the battery inspection unit.

A battery capacity analysis and predication method and system for a storage battery, relating to the technical field of data processing. The method comprises: acquiring operation data of a target storage battery within a preset time period, wherein the operation data comprises a voltage sequence, an internal resistance sequence, a temperature sequence, and a charge and discharge cycle number sequence; on the basis of the operation data, determining time intervals corresponding to a plurality of operation conditions; on the basis of operation sub-data within each time interval, calculating a temperature influence factor, a power loss factor, and a cycle aging factor within each time interval; acquiring a battery capacity attenuation amount of the target storage battery within each time interval; on the basis of the battery capacity attenuation amount, temperature influence factor, power loss factor, and cycle aging factor within each time interval, generating a capacity attenuation amount curve of the target storage battery; and on the basis of the capacity attenuation amount curve, predicting battery capacity in the next time period.

A method for detecting thermal runaway of a battery pack including a battery module in a master battery management system, the method comprising detecting a communication error with a slave battery management system that detects information on the battery module, if the communication error with the slave battery management system is detected, obtaining temperature of a master board from a temperature sensor located on the master board in which the master battery management system is installed, and detecting thermal runaway of the battery pack using the temperature of the master board.

A battery such as, but not limited to, electric vehicle battery packs and cells, lithium iron phosphate batteries, lead acid batteries, gel batteries, and absorbed gel mat batteries, may include a battery management system for engine start applications. The battery may include a first power port configured to receive power from a first power source and a second power port configured to received power from a second power source, whereby the first and second power sources are different.

This invention proposes a method for predicting the health status of lithium batteries based on multidimensional features and neural network constant differential equations. The method includes the following steps: S1, preprocessing the capacity data and charging stage operation data collected during lithium battery operation, and constructing features from historical health status data; S2, constructing multidimensional feature inputs for health status prediction based on the charging stage operation data; S3, inputting the multidimensional features into a gated recurrent unit network to fuse and encode the historical health status sequence and constant current charging stage features to obtain a potential feature representation characterizing the battery degradation state; S4, comparing the predicted health status value output by the neural network constant differential equation model with the corresponding actual health status value, calculating the prediction error, and evaluating the prediction accuracy. This application achieves high-precision prediction of lithium battery health status by integrating a multidimensional feature screening mechanism and a continuous-time state evolution modeling method.

The present disclosure provides a method for estimating state of charge in a lithium iron phosphate battery. The method includes initiating a relaxation period during which no current flows, measuring voltage features during relaxation at predetermined intervals, and extracting a feature vector from measured voltage features and historical current data preceding relaxation. The method applies a machine learning model to the feature vector to predict state of charge, wherein the model comprises three sequential sub-models where a first sub-model predicts voltage difference between measured voltage and equilibrium open circuit voltage, a second sub-model predicts state of charge difference based on outputs from the first sub-model, and a third sub-model generates final predictions through model fusion.

The present invention discloses a method and a device for quality control of battery packs in the field of new energy technologies.The specific implementation of this procedure includes: determining several parameter values ​​for one or more parameters for several cells to be assembled; counting an initial number of cells to be assembled with the same parameter value under each parameter; calculating a first cumulative probability for each parameter value under that parameter based on this initial count and the total number of cells to be assembled; calculating a second cumulative probability for each parameter value under that parameter using a predefined distribution function; calculating the difference between the first and second cumulative probabilities; determining whether the cells to be assembled meet the battery pack's quality standards using the difference and predefined quality control conditions for the battery pack.This implementation method enables multi-cell battery packs that meet battery pack quality standards to have higher accuracy in power prediction, thus improving the quality reliability of the battery pack.

A cell balancing method for a battery pack containing multiple battery cells includes the steps of: determining which of the multiple battery cells is a balancing target cell that requires cell balancing; measuring a first voltage to the balancing target cell and measuring a first pack current flowing through the battery pack; turning on a balancing switch connected to the balancing target cell; measuring a second voltage to the balancing target cell and measuring a second pack current flowing through the battery pack; determining a balancing current calculation method according to the difference between the first pack current and the second pack current; calculating the balancing current using the first voltage and the second voltage if the difference between the first pack current and the second pack current is within a predetermined range; calculating the balancing current using the first voltage, the second voltage and the voltage change due to the internal resistance of the balancing target cell if the difference between the first pack current and the second pack current exceeds a predetermined range; and estimating the SOC (state of charge) of the balancing target cell according to the balancing current.

To greatly shorten a stopping time of charge and discharge of a battery, and to detect a residual amount of battery quickly.SOLUTION: A method of detecting a residual amount of a battery is a detection method that detects an open battery of the battery, and identifies a residual amount (%) from the detected open voltage. The detection method includes: a voltage detection step of detecting a plurality of open voltages at prescribed time intervals after stopping the charge / discharge of the battery; a function setting step of computing a prediction function in which the open voltage drops from the plurality of detected open voltages in the voltage detection step; a computation step of computing a prediction open voltage in a convergence timing where the open voltage of the battery drops and converges on the basis of the prediction function to be identified in the function setting step; and a residual amount prediction step of identifying a prediction residual amount (%) from the computed prediction open voltage in the computation step.SELECTED DRAWING: Figure 2

The application is a kind of predictive fault diagnosis method and system of mining electromechanical equipment, relates to the technical field of mining electromechanical equipment fault diagnosis, and comprises: natural excitation pickup and quantization module; response measurement module; synchronous acquisition and preprocessing module; frequency response function estimation module; modal parameter extraction module; stiffness degradation diagnosis module.In the application, the inherent non-stationary event during the operation of the mining electromechanical equipment is used as a wideband excitation, and an indirect quantization method of current to electromagnetic torque is combined to construct a digital twin mapping relationship between electrical quantity and mechanical excitation, so that accurate excitation measurement is realized under the condition of no mechanical force sensor, and the industry problems of difficult installation, high cost and easy damage of force sensors caused by high temperature, high humidity, high dust and strict explosion-proof in coal mine are solved.

The application relates to a battery state of charge prediction method, device, equipment, medium and program product. The method comprises the following steps: acquiring discharge sequence data of a target battery, wherein the discharge sequence data comprises real-time discharge data and historical discharge data before the real-time discharge data; inputting the historical discharge data into an encoder of a target state of charge prediction model to extract discharge time sequence features of the historical discharge data; inputting the discharge time sequence features and the real-time discharge data into a decoder of the target state of charge prediction model together, and outputting a state of charge prediction result of the target battery under the guidance of the real-time discharge data. The method can improve the accuracy of the state of charge prediction of the battery.

According to some embodiments disclosed herein, the vehicle assistance device includes a communication module configured to collect battery data of the vehicle from a data port of the vehicle; a controller configured to manage the battery data and to provide at least one of a video acquisition function for acquiring images of the area surrounding the vehicle and a route guidance function for guiding the vehicle's driving path; and storage configured to store at least a portion of the battery data.

The application discloses a state evaluation detection system based on response speed of a window regulator, relates to the technical field of vehicle electrical component detection, and acquires environment data and displacement data of the window regulator through a data acquisition module to construct a displacement-time sequence; a data processing module extracts a response delay time and a speed fluctuation coefficient as operating parameter features based on the displacement-time sequence, defines the operating parameter features and the environment data as internal dynamic response related data and external influence related data respectively; a state evaluation module sets corresponding state evaluation items according to the external influence related data and the internal dynamic response related data, and outputs evaluation results of the corresponding state evaluation items; and a result output module comprehensively judges the two evaluation results to generate a window regulator operating state conclusion. The system realizes the cooperative evaluation of mechanical performance and operating environment of the window regulator, and improves the reliability and intelligent maintenance level of the window lifting system.

This invention discloses a method and system for real-time monitoring and prediction of carbon intensity, belonging to the field of carbon emission monitoring technology. The method acquires and processes electricity-related data such as installed capacity and real-time load of each province hourly through an ETL data channel; it draws a map of China based on ECharts, dividing it into five color-level intervals according to carbon intensity values: 0-300, 301-500, 501-700, 701-900, and 901-1200 gCO2 / kWh; responding to user clicks on provinces, it displays detailed data for each province through indicator cards, circular progress charts, and one-sided bar charts; it calls a pre-trained STFCI hybrid model to predict carbon intensity hourly for the next 24 hours. This model integrates a 2-layer 128-neuron LSTM unit with an XGBoost unit with 100 trees and a learning rate of 0.1, outputting predicted values ​​after feature concatenation and a fully connected layer; the prediction results are displayed as a bar chart, marking customizable low-carbon threshold lines, highlighting low-carbon periods, and generating electricity consumption suggestions. The corresponding system includes a data interface, database, visualization, prediction, and WeChat service modules. The database adopts an InfluxDB+MySQL combined architecture, and the WeChat service module supports mobile text and image queries. The STFCI model of this invention has an average absolute error of only 12.3 gCO2 / kWh, significantly improving prediction accuracy, realizing hourly real-time monitoring and multi-dimensional visualization of carbon intensity, and providing precise decision support for power dispatching and energy conservation and emission reduction when combined with mobile services.

The invention relates to a method for detecting a fault condition (F) of at least one first battery cell (16a) of a battery (18) having a plurality of battery cells (16), the cell voltage (Ul) of the first battery cell (16a) being determined repeatedly in an operating state (22, T) of the battery, in which operating state the change in the battery current (I) over time is less than a predefinable limit value, an electrical cell variable of the first battery cell being determined from the cell voltage of the first battery cell. The cell variable is then compared with a reference value (26a, 26b, U2), which is determined from the cell voltage detected at the respective point in time of the measurement of at least one battery cell different from the first battery cell, the fault condition (F) of the first battery cell being detected at least when the deviation (dl, d2) of the electrical cell variable (24a, 24b, Ul) from the first reference value provided at the same point in time of the measurement exceeds a predetermined first threshold value.

A propulsion system (20) for an aircraft (1000) includes a battery (64), an electrical distribution system (66), a ground-based charger, and a battery management system (68). The battery includes a plurality of battery strings (72) each including a plurality of battery cells (76). The electrical distribution system includes a battery string switch assembly (98) operable to electrically interconnect each of the plurality of battery strings together in parallel. The ground-based charger includes a charger controller (132) including a simple electronic hardware (SEH) system. The battery management system includes a battery management system (BMS) controller (108) connected in signal communication with the SEH system. The BMS controller is configured to determine a battery charging profile specific to the battery and charge the battery by controlling the ground-based charger, through the SEH system, to supply electrical power to the electrical distribution system at a set voltage and a set current defined by the battery charging profile.

The application relates to the field of lithium battery life prediction, and discloses a lithium battery residual life prediction method based on VMD and an improved BiGRU, capacity attenuation time series are constructed by acquiring lithium battery charging and discharging data; the VMD algorithm is used to pretreat the capacity data, a plurality of intrinsic mode function (IMF) components and a residual term are acquired; the improved eagle algorithm is used to determine the key parameters of VMD decomposition; for each IMF component and the residual term, an improved BiGRU neural network prediction model is constructed, independent training and prediction are carried out on each component prediction model, linear superposition is carried out on the prediction results of the components, a final battery capacity prediction sequence is obtained, and the residual life of the lithium battery is calculated.

The application provides a power system fault diagnosis method, system, device, equipment and storage medium, relates to the power system technical field, is applied to the cloud server in the power system, and the power system also contains the data acquisition module built-in edge computing unit. The method comprises the following steps: in response to receiving the acquisition data diagnosed as abnormal by the edge computing unit, obtaining the first power measurement data at the current time; inputting the acquisition data and the first power measurement data into a multi-modal feature fusion algorithm based on a transformer to obtain a feature fusion vector representing the operating state of the power equipment; updating a knowledge graph representing the change of the operating state of the equipment based on the feature fusion vector; and generating a fault diagnosis result based on the knowledge graph. The application adopts the diagnosis mode of combining edge computing with cloud servers, and fuses multi-source heterogeneous data, realizes comprehensive analysis and accurate diagnosis of the operating state of the equipment, and thus improves the accuracy of fault diagnosis.

The application provides a performance test method, system, device and medium of a parallel converter, the parallel converter comprising a plurality of first devices and a plurality of second devices; each device comprises at least two modules; the module types comprise first modules and second modules; the method comprises: controlling the first modules to operate in a voltage source mode and the second modules to operate in an alternating current source mode; sending a power reference value instruction to realize parallel power test of each module; controlling the first devices to operate in the voltage source mode and the second devices to operate in the alternating current source mode; sending the power reference value instruction to realize parallel power test of the devices, and obtaining a performance test result of the parallel converter. By controlling part of the modules or devices in the parallel converter to be in the voltage source mode and simultaneously controlling another part of the modules or devices to be in the alternating current source mode, the power demand for external test power supply can be reduced.

The application discloses a lithium ion battery thermal runaway early warning method and system based on a multi-parameter monitoring system, real-time collection of lithium ion battery working temperature data, voltage data, current data, surface deformation data, characteristic gas concentration data and ultrasonic scanning transmission data; the collected ultrasonic scanning transmission data is subjected to wavelet denoising using a soft and hard threshold compromise method to obtain ultrasonic scanning transmission denoising data, and the ultrasonic signal amplitude in the ultrasonic scanning transmission denoising data is subjected to initial value processing to obtain initial value processing data; the lithium ion battery working temperature data, the voltage data, the current data, the surface deformation data, the characteristic gas concentration data and the initial value processing data are input into a trained prediction model, the lithium ion battery thermal runaway safety valve opening time is predicted, and early warning response is performed according to the prediction result. The application has higher lithium ion battery thermal runaway identification accuracy and earlier thermal runaway early warning time.

The present invention provides a system that, based on the test conditions of a degradation test and the corresponding capacity degradation rate of the degradation test, sets the test conditions for the next degradation test for each of several secondary batteries, or estimates the capacity degradation rate of secondary batteries corresponding to unexecuted test conditions. [Solution] In step S3, a degradation test is performed on each secondary battery using a constant temperature chamber and a charge / discharge device based on the set test conditions. Next, in step S4, a charge / discharge test is performed. After the charge / discharge process in step S4, in step S5, a degradation rate calculation process is performed based on the results of the charge / discharge test in step S4. Next, in step S6, a degradation rate map is estimated based on the test conditions of the degradation test performed in step S3 and the degradation rate calculated in step S5. The degradation rate map shows the correspondence between the test conditions and the capacity degradation rate.

Aspects of the disclosure are directed to variable shift frequency implementation. In accordance with one aspect, the disclosure includes synthesizing a divided clock (511) from a shift clock (501) with a divided frequency equal to a reference frequency divided by a selected integer divisor in a logical built-in self-test (LBIST) mode; transitioning the LBIST mode from a shift state to a capture state by enabling a capture control enable signal (502) while pacing with the divided clock (511); generating a stretched capture control enable signal from the capture control enable signal using a slow cycle programmer (SCP, 530) with a plurality of quad stage pipelines; and transitioning the LBIST mode from the capture state to a subsequent shift state with the stretched capture control enable signal in a HIGH state to mitigate voltage droop.

This application provides a method, device, and medium for identifying parameters of a second-order battery equivalent circuit model. The method includes: randomly initializing the positions of an osprey population within a defined parameter feasible solution space to obtain the initial position of each osprey. Each osprey's position represents a set of candidate parameter feasible solutions, with parameters including the ohmic internal resistance, two polarization resistors, and two polarization capacitors in the second-order battery equivalent circuit model; executing an iterative loop of the osprey optimization algorithm based on the initial position of each osprey to obtain the optimal position; and determining the parameter feasible solution corresponding to the optimal position as the optimal solution for the parameters of the second-order battery equivalent circuit model. During the iterative loop of the osprey optimization algorithm, the update of the osprey positions is controlled by dynamic coefficients, which change non-linearly with the number of iterations. This improves the identification accuracy and reliability of the second-order battery equivalent circuit model parameters.

The application discloses a kind of liquid cooling wire harness detection method, device, storage medium and electronic device, it is related to vehicle technical field.Therein, the method comprises: according to test requirement determines test working condition;In test working condition, obtain first temperature, wherein, first temperature includes the temperature of liquid cooling wire harness, the temperature of environmental chamber and the temperature of electrical connection point, environmental chamber is used to isolate liquid cooling wire harness with external environment, and electrical connection point is the connecting point of environmental chamber and temperature sensor;In response to first temperature greater than or equal to temperature threshold value, adjust cooling parameter, wherein, cooling parameter is used to indicate the flow rate and water temperature of cooling loop;In the preset time period after adjusting cooling parameter, obtain second temperature;According to second temperature, liquid cooling wire harness is detected.The application solves the technical problem that related art tests liquid cooling wire harness by appearance inspection or electrical test, resulting in complex method, not easy to implement, low efficiency, low accuracy, low safety.

The utility model discloses a kind of double-station terminal detection equipment, belong to terminal detection field, including base station;Double-station positioning clamping conveying mechanism for clamping and positioning terminal and conveying terminal is installed on the base station;Multi-process detection mechanism for carrying out multi-process detection to the terminal clamped and conveyed by double-station positioning clamping conveying mechanism is installed on the base station;The base station rear side is provided with wire rod detector for detecting wire rod;The double-station positioning clamping conveying mechanism includes clamping and positioning assembly, double-station moving assembly and blanking assembly;Clamping and positioning assembly is connected with double-station moving assembly;Double-station moving assembly and double-station moving assembly are connected with base station. By the above-mentioned mode, the utility model can realize the continuous detection of the terminal of two stations by multi-process detection mechanism, save time cost.

A method to test a battery pack in a vehicle comprises determining the vehicle is driven in electric vehicle and regenerative braking modes with respective output rates continuously for threshold amounts of time. The method includes determining first and second sets of battery voltage values for multiple battery pack components in the battery pack as the vehicle is driven in the electric vehicle mode and the regenerative braking mode, respectively. Each first and second set of battery voltage values includes a value for each battery pack component in the multiple battery pack components. The method includes outputting an indicator regarding a state of the battery pack based on differences in pairs of battery voltage values among the first or second sets of battery voltage values. Each pair of battery voltage values includes a maximum and minimum battery voltage value from each first or second sets of battery voltage values.

The application belongs to the technical field of power quality detection, and provides a portable distributed photovoltaic power quality detection method and system, which comprises the following steps: obtaining power signals of a distributed photovoltaic line based on passive coupling; continuously sampling the obtained power signals adaptively to obtain discrete digital signals of the power signals; extracting multi-dimensional frequency domain characteristic parameters of the obtained discrete digital signals; performing traceability analysis on the extracted multi-dimensional frequency domain characteristic parameters to generate traceability analysis results; performing multi-dimensional collaborative security protection of the distributed photovoltaic based on the generated traceability analysis results and a protection effectiveness calculation model, feeding back obtained protection state information to the passive coupling acquisition stage, forming closed-loop control on the acquisition of the power signals, and completing power quality detection of the distributed photovoltaic.

This application discloses a pickup mechanism and device, belonging to the field of superconducting quantum chip manufacturing. The pickup mechanism includes an operating arm, a telescopic component, and a fixing component. The telescopic component is axially telescopically fitted onto the operating arm. In its original length state, the telescopic component exposes a portion of the operating arm, and in a compressed state, it exposes another portion of the operating arm. The fixing component cooperates with the operating arm and is also used to connect a probe. This pickup mechanism allows for convenient probe replacement, reducing the risk of probe damage.