4886results about "Power supply testing" patented technology

The invention discloses an emergency power supply state monitoring method and system based on multi-modal data, and relates to the technical field of power supply monitoring, and the method comprises the steps: obtaining the power supply attribute data of an emergency power supply; based on the sensor group, collecting multi-channel time sequence sampling data of the emergency power supply corresponding to a preset sampling time period in real time; performing data preprocessing on the multi-channel time sequence sampling data to obtain corresponding online monitoring time sequence data; extracting a multi-modal fusion feature group corresponding to the online monitoring time sequence data; and inputting the power supply attribute data and the multi-modal fusion feature group into a power supply state identification model to determine the operation health state of the emergency power supply, the operation health state including any one of the following state types: a normal state, an early warning state, a limited operation state and a fault state. Therefore, technical means such as multi-modal parameter acquisition, feature fusion analysis and model reasoning are comprehensively adopted, and real-time and accurate monitoring of the state of the emergency power supply is realized.

The invention discloses an intelligent electromagnetic interference protection system for a power supply module, and the system comprises an electromagnetic interference detection module which is configured to deploy at least one type of electromagnetic interference sensor at the internal and peripheral preset positions of the power supply module, the acquisition module is used for acquiring electromagnetic interference signals received by the power supply module in a working process and running state parameters of the power supply module in real time; the intelligent control module is configured to input the characteristic parameters of the electromagnetic interference signals extracted by the electromagnetic interference detection module into a trained intelligent control model so as to identify different types of electromagnetic interferences; the filtering module is configured to customize a reconfigurable filtering network; the shielding module is configured to be of a multi-layer shielding structure; and the communication and monitoring module is configured for data interaction between the power supply module and external equipment. According to the system provided by the invention, the stability and the anti-interference performance of the power supply module in a complex electromagnetic environment can be effectively improved, and the reliability and the stability of the power supply module are improved.

The invention discloses a fault processing method and system for a distributed power supply, and the method comprises the steps: carrying out the real-time monitoring of the operation data of the distributed power supply in a limit operation state, and combining with the historical fault data, so as to carry out the judgment of a fault mode; according to the current fault mode of the distributed power supply, corresponding fault operation state characteristics are extracted from historical monitoring data for severity evaluation, and according to an evaluation result, a current response measure is extracted from a fault response measure library to control execution of the distributed power supply; and acquiring a second real-time monitoring parameter when the distributed power supply executes the response measures to evaluate the response effect, and when the effect does not reach the expected standard, selecting a better target response measure from the fault response measure library based on the recovery rate of the distributed power supply under the current response measure and executing the better target response measure. The reliability and the safety of the distributed power supply in the limit operation state can be remarkably improved, and the fault response speed and the fault processing efficiency are greatly improved.

The invention relates to the technical field of power system monitoring, in particular to an intelligent direct-current power supply whole-course fault recording analysis system which comprises a dynamic threshold self-adaption module, a multi-dimensional data fusion module, an event triggering module, a long-period data accumulation module, a complex boundary condition monitoring module and a fault mode recognition early warning module. Wherein the dynamic threshold adaptive module is used for collecting multi-dimensional data of a direct current power supply system in real time and dynamically adjusting a threshold range of fault detection; the multi-dimensional data fusion module is used for generating a comprehensive system operation state evaluation result; and the event triggering module is used for triggering a fault recording process when an abnormal condition meeting a threshold range condition is detected. According to the invention, through real-time data monitoring, deep learning and fault mode identification and long-term data accumulation, the fault early warning capability and the operation and maintenance efficiency of the DC power supply system are significantly improved, and stable and reliable operation of the system is ensured.

The invention discloses a DC-DC power supply dynamic response optimization system based on digital PID, which relates to the technical field of DC-DC power supply dynamic response optimization, and comprises a voltage and current sampling module, a reference signal generation module, an output signal generation module, a digital signal generation module, a control module and an output signal generation module, the digital PID controller calculates control output according to errors, the PWM signal generation module generates corresponding PWM signals according to the control output, the power switch driving module amplifies the signals to drive a switch tube, the load monitoring module monitors load changes in real time, output of the load monitoring module can be fed back to other modules, and power supply dynamic response optimization is achieved. According to the invention, the dynamic response performance of the DC-DC power supply is remarkably improved, the output fluctuation is reduced, the recovery time is shortened, the power supply efficiency is improved, the stability is guaranteed by adopting multiple anti-interference design, peripheral elements are reduced, miniaturization is realized, the cost is reduced, fault diagnosis is realized, and the service life is prolonged.

The invention discloses a power supply fault rapid detection system and method based on an intelligent diagnosis engine, and belongs to the technical field of power electronic equipment fault diagnosis, and the system comprises a function region division module which is mainly used for dividing a plurality of function regions according to a power supply topological structure; the real-time data acquisition module is mainly used for acquiring parameter data of each functional area in a power supply operation stage; the current model building module is mainly used for building a current time sequence prediction model; the trend prediction module is mainly used for generating a future current change trend; the abnormity judgment module is mainly used for identifying an abnormal condition by performing similarity matching with real-time data; the fault positioning module is mainly used for matching with a fault mode based on an abnormal current waveform and constructing a directed graph to position a fault position; the method has the advantages that early warning and accurate positioning of the power supply fault are realized through multi-modal data fusion and a deep learning model, and the operation and maintenance efficiency and reliability of the power electronic equipment are remarkably improved.

The invention relates to the technical field of power supply detection, and discloses a fire-fighting equipment power supply detection method and system.The detection method comprises the following steps that voltage fluctuation, current phase and ripple coefficients are collected through a multi-channel sensor group, a feature sequence is generated through sliding window noise reduction, the Euclidean distance is calculated through Z-score standardization, and a calibration instruction is generated when a threshold value is exceeded; kalman filtering adjusts frequency output detection parameters, fast Fourier transform is executed to extract harmonic amplitude to generate a suppression vector, and a least square reconstruction model outputs a state identifier; according to the method, voltage, current and ripples are collected through multiple channels, anti-interference performance and data integrity are enhanced through sliding window noise reduction, a threshold value is adjusted through Z-score and Euclidean distance self-matching, sampling frequency and detection parameters are optimized through Kalman filtering, harmonic characteristics are extracted through FFT, and the state is evaluated through a least square reconstruction model. And a multi-dimensional classification system is constructed by fusing the distortion rate and the phase deviation, so that the detection precision, the sensitivity and the response real-time performance are improved.

The invention discloses an energy storage power supply residual life prediction method and system based on dynamic weight distribution, and belongs to the technical field of energy storage power supply health management. The method comprises the following steps: acquiring voltage, current and temperature time sequence signals of energy storage power supply operation through a multi-source sensor, and constructing a degradation characteristic sequence by adopting a sliding window method; a degradation inflection point division stage is detected and identified by using a curvature extreme value, a historical degradation mode is matched based on a dynamic time warping algorithm, and an optimal model group is selected; respectively carrying out dynamic weight distribution on the time step length and the feature dimension by adopting a dual-channel attention network, and fusing a learnable coefficient with space-time attention output to generate a life prediction result; residual errors and feature drift are monitored and predicted in combination with an incremental learning mechanism, and model parameters are updated and a degradation knowledge base is expanded by adopting an elastic weight consolidation algorithm. According to the method, the key information capturing capability is enhanced through a space-time attention mechanism, the model adaptability is optimized in combination with incremental learning, and the energy storage power supply life prediction precision and the working condition generalization performance are remarkably improved.

The invention discloses a method for testing the dynamic response characteristic of a power supply by simulating the load change of the power supply, and relates to the technical field of power supply testing, and the method comprises the steps: generating a simulation load change sequence based on a preset load change mode, and enabling each load value to correspond to a specific time point; inputting the simulated load change sequence into the power supply to be tested, and controlling the power supply to be tested to work according to the simulated load change sequence by using the multi-channel synchronous test system so as to simulate the load change in the actual use process; a high-precision data acquisition module is used for acquiring and recording output voltage values, output current values and corresponding timestamps of the to-be-tested power supply under different load conditions at a sampling rate not lower than a first set value, and a dynamic response data set is formed; and processing the dynamic response data set by using a preset data calibration algorithm, and calculating dynamic response parameters of the to-be-tested power supply at each load change point. The motor power supply testing device has the effect of improving motor power supply testing precision.

The invention discloses a control circuit of an electronic load, the electronic load and a power supply test system. The circuit comprises an MCU; the signal output end of the MCU is connected with the input end of the DAC module; the closed-loop control circuit comprises a first error amplifier, a mutual inductor, an MOS (Metal Oxide Semiconductor) tube, a current sampling resistor and a power supply end VBUS; a mutual inductor is arranged between a first error amplifier and an MOS tube of the closed-loop control circuit, a power supply end VBUS is connected with a drain electrode of the MOS tube through a primary side of the mutual inductor, a first secondary side of the mutual inductor feeds back an input signal of the first error amplifier, and a second secondary side of the mutual inductor feeds back a driving signal of the first error amplifier to the MOS tube. According to the invention, the dynamic response speed when the electronic load pulls the high-frequency current can be improved, and the test requirements of high precision and high dynamic response are met.

The invention discloses an electromagnetic compatibility testing method and an electromagnetic compatibility testing system for an industrial control power supply, which are used for evaluating conducted interference, radiated interference and immunity performance. The system comprises a load module, a signal connection module, an electromagnetic interference measurement module, an immunity test module, a data processing module and a hardware acceleration module. The load module simulates the actual working state of the industrial control power supply through resistive, inductive, capacitive and dynamic loads; the signal connection module adopts high-frequency shielding and grounding optimization design, so that external interference is reduced; the electromagnetic interference measurement module is combined with the frequency domain analysis and time domain response module to capture interference signal characteristics and power supply dynamic output; the data processing module generates an electromagnetic compatibility report through a comprehensive evaluation algorithm; and the hardware acceleration module realizes real-time processing of high-frequency sampling data by utilizing the FPGA. The method is suitable for the electromagnetic compatibility test of the industrial control power supply in the fields of industrial automation, communication equipment and power electronics, and has wide engineering application value.

The invention discloses a leakage current monitoring and early warning system based on current monitoring of a new energy photovoltaic inverter, and belongs to the technical field of leakage current monitoring. The invention discloses a leakage current monitoring and early warning system based on current monitoring of a new energy photovoltaic inverter, and the system comprises a sensing module, a data collection and preprocessing module, a central processing module, a multi-stage dynamic threshold module, a complex mode recognition module, and a multi-stage early warning module. And real-time early warning cannot be realized, and a complex leakage current mode cannot be identified. According to the environment parameters monitored in real time and the working state of the inverter, the threshold value of the leakage current is dynamically adjusted, the complex leakage current mode is recognized by adopting a machine learning and mode recognition algorithm in combination with the comprehensive analysis result of the zero-sequence current, the phase and the frequency parameters, and the reliability of the inverter is improved. The multi-level early warning module can give alarms of different levels according to the degree of the leakage current.

The invention discloses an intelligent monitoring method for a parallel DC power supply system based on an edge gateway, and the method comprises the following steps: S1, collecting and processing real-time data, and generating a health baseline; s2, comparing the real-time data with the health baseline, and automatically identifying an abnormal state; s3, generating a fault fingerprint based on a fault fingerprint generation algorithm, and storing the fault fingerprint in a fingerprint database to form a fault file; s4, generating an intention map by using a situation modeling algorithm, dynamically predicting a load demand based on an intention prediction algorithm, and performing adjustment according to a load priority; s5, generating a dynamic power supply parameter adjustment scheme through an evolution rule engine, and performing real-time optimization by adopting a self-evolution algorithm; s6, a multi-time window adaptive memory management module based on an edge gateway performs hierarchical storage and management on real-time data according to time windows; and S7, analyzing the real-time monitoring data based on a closed-loop feedback control system. According to the invention, the edge gateway and the adaptive algorithm are utilized to realize real-time monitoring and optimization of the parallel DC power supply system.

The invention provides a multi-dimensional grid-connected test system for a photovoltaic string inverter, and the system comprises a power grid simulation module which is used for constructing a power grid simulation environment based on a multi-dimensional coupling mechanism of voltage fluctuation, frequency deviation and harmonic distortion; the photovoltaic array simulation module is used for constructing IV characteristic dynamic deduction models of different irradiance and temperature gradient effects based on a photovoltaic array equivalent circuit physical model to realize a natural simulation environment; the loading module is used for loading the power grid simulation environment and the natural simulation environment to the photovoltaic string inverter to be tested; the data acquisition module is used for monitoring running state data of the photovoltaic string type inverter in real time and constructing a running state data set containing multi-physical-quantity coupling characteristics; and the diagnosis module is used for inputting the running state data set into the trained LSTM neural network model to obtain a test result of the photovoltaic string inverter. According to the invention, the efficiency and convenience of the grid-connected test of the inverter can be improved, and the accuracy and reliability of the grid-connected performance of the inverter are ensured.

The invention discloses an intelligent operation and maintenance fault early warning method for a rail transit variable-frequency power supply, and relates to the technical field of power electronics and intelligent operation and maintenance, and the method comprises the following steps: setting a multi-point synchronous collection device to carry out the high-precision real-time collection of voltage and current signals of a variable-frequency power supply system, and carrying out the digital coding processing of data; and performing frequency domain analysis on the acquired voltage and current signals by using a preset spectrum analysis algorithm, and extracting harmonic amplitudes and phase characteristic parameters of different orders. According to the invention, through high-precision synchronous acquisition and spectrum analysis, rapid and accurate identification of harmonic abnormity is realized; a machine learning model and dynamic threshold adjustment are fused, and the adaptability and intelligent recognition capability of the system to fault modes under multiple working conditions are enhanced; and a trend prediction and graphical early warning platform is introduced, so that the fault risk is pre-judged in advance and visually responded, and the operation and maintenance efficiency and the operation safety of the rail transit power supply system are remarkably improved.

The invention discloses a protection measurement and control device power supply fault early warning method and system and a storage medium. The invention aims to solve the problem that fault early warning and detection cannot be accurately carried out when power supply fault early warning is carried out by monitoring ripple change in the prior art. The method comprises the following steps: establishing a transition mapping relation from a normal state to a fault state according to physical parameter characteristic changes in a historical fault scene; respectively acquiring each physical parameter characteristic according to a set sampling frequency, and respectively adjusting each sampling frequency according to the sampled physical parameter characteristics; the sampled physical parameter characteristics are imported into a power supply fault early warning model, and a fault scene of the power supply of the measurement and control device is matched; and executing preset processing preparation according to the matched and predicted fault scene. And a power supply fault early warning and evaluation model is established according to the transition mapping relationship, so that the fault occurrence precursor can be found as early as possible, and the power supply fault early warning and detection cannot be accurately carried out.

The invention relates to the technical field of power electronic equipment testing, and discloses a special intelligent testing device and method for a power UPS, and the device comprises a multi-source power supply system which comprises a three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a DC program-controlled power supply, the output voltage of the three-phase program-controlled variable-frequency power supply is 0-480V and is adjustable, and the output voltage of the single-phase program-controlled variable-frequency power supply is 0-480V; the output voltage of the single-phase programmable variable-frequency power supply is 0-280V and the frequency of the single-phase programmable variable-frequency power supply is 45-64Hz and adjustable; the output voltage of the direct-current programmable power supply is 50-1000V and adjustable; an electronic load system; a signal acquisition system; an embedded control system; and an upper computer software system. A three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a direct-current program-controlled power supply are integrated to form a multi-source power supply system, a resistive and rectifying dual-mode electronic load is combined, millisecond-level synchronous switching of a voltage level and a load state is realized through an embedded control system, a closed-loop test capability of multi-dimensional performance of the power UPS is formed, and the test efficiency is improved.

The invention discloses a DC power supply health state prediction model optimization method based on an extreme learning machine, and relates to the technical field of power supply intelligent management. According to the method, an extreme learning machine basic model is improved, multi-layer ELM-AE is adopted to carry out greedy unsupervised learning on input data layer by layer, advanced features of an original data set are extracted, a mixed kernel function is adopted as a regression layer of a supervised learning stage, the complex nonlinear problem is solved, and the method has the advantages of being high in robustness and high in robustness. The adaptability of the prediction model to diversified characteristics under different battery working conditions is improved, the generalization ability and prediction precision of the model are improved, and the convergence speed and prediction precision of the model are remarkably improved by optimizing the model parameters through the improved black-wing calculation algorithm.

The invention discloses an electronic load system, a power supply test method, an electronic device and a storage medium, and relates to the technical field of electrics. A main control circuit can provide a reference voltage for a current sampling and control circuit, and can also obtain load current setting parameters; the current sampling and control circuit determines a control voltage mainly by acquiring a sampling voltage and comparing the sampling voltage with a reference voltage so as to control an on-resistor in the power circuit through the control voltage and further control the magnitude of the current passing through the on-resistor, and meanwhile, the change rate of the current can be controlled due to a load current parameter. Therefore, the rapid change of the load current can be realized. Therefore, the technical problems of how to realize the rapid change of the current and improve the accuracy of the test result can be solved, and the technical effects of meeting the rapid change requirement of the current and improving the test result are achieved.

The present application discloses a method and apparatus for detecting insulation impedance of a direct current side of a photovoltaic inverter. The method includes the following steps: sampling a voltage of a protective earthing and a voltage of the positive terminal of a direct current bus respectively; obtaining a first voltage difference between voltages of the protective earthing at different moments and a second voltage difference between voltages of the positive terminal of the direct current bus at different moments; and calculating the insulation impedance of the direct current side of the photovoltaic inverter based on the first voltage difference, the second voltage difference, a resistance of an equivalent resistor between each terminal of the photovoltaic inverter and a signal ground, and resistances of equivalent resistors between the positive terminal and the negative terminal of the direct current bus and the protective earthing.

The invention provides a coal mine underground 3DR electric leakage detection protection method, which comprises the following steps of: constructing an auxiliary star point connected with a system by using three-phase half-waves of a power supply system of a converter substation through a common cathode or common anode connecting wire; a residual current Hall sensor is used for detecting electric leakage residual current of different harmonic waves, and a 3DR electric leakage insulation resistance measurement technology is discriminated based on a Fourier algorithm; according to the harmonic component, the electric leakage resistance, the electric leakage value and the area of the frequency converter of the power supply system of the coal mine mobile converter substation can be judged, and alarm protection is judged; and the harmonic current is dynamically detected, so that selective leakage protection can be realized. According to the invention, through a 3DR electric leakage technology, electric leakage detection and instantaneous protection of the frequency converter are realized; selective earth leakage protection is realized according to the detection of the fundamental component and the harmonic wave; through harmonic leakage current and fundamental wave detection system distributed capacitance, electric leakage protection and capacitive current accurate judgment of power supply equipment in a coal mine power supply system are realized.

The invention relates to the technical field of electrical fault detection, in particular to a mobile power supply fault detection method and system based on intelligent diagnosis, and the method comprises the following steps: collecting voltage and current data of a mobile power supply in a normal operation state, and generating an electrical performance baseline data set through recording the timestamp of the data and a corresponding electrical performance index; and based on the electrical performance baseline data set, extracting time sequence features of voltage and current to obtain electrical performance feature data. According to the invention, based on voltage and current data acquisition in a normal state of the mobile power supply, a baseline data set covering timestamps and electrical performance indexes is established, and detail information of electrical performance changes is captured by extracting time sequence features such as peak values, mean values and standard deviations; meanwhile, frequency spectrum features are accurately extracted by means of fast Fourier transform, the intensity and phase information of frequency components is mastered, then signals are decomposed through wavelet transform, and richer electrical performance anomaly information under multiple scales is obtained.

The invention provides a power supply equipment temperature characteristic detection method and system. The method comprises the following steps: acquiring temperature data sets of power supply equipment under different working conditions; performing partial derivative calculation on the mathematical model, quantifying the contribution degree of each working condition to the temperature characteristic, and determining a main influence factor and a secondary influence factor; a time sequence analysis method is introduced, the temperature data set is analyzed, the dynamic change trend of the working conditions is captured, and nonlinear relation characteristics between the working conditions and temperature characteristics are identified; a self-adaptive filtering algorithm is adopted, changes of working conditions are tracked in real time, and parameters and structures in the mathematical model are dynamically adjusted, so that the mathematical model can adapt to the dynamic changes of the working conditions; and training and optimizing the adjusted mathematical model by using a support vector machine algorithm, thereby improving the prediction precision and generalization ability of the mathematical model.

The invention relates to the technical field of power electronics and energy management. The invention provides an AC / DC power supply system monitoring device and method. The method comprises the following steps: constructing a historical data set; preprocessing the historical data set to obtain a preprocessed data set; based on the preprocessed data set and a machine learning algorithm, constructing a system monitoring model, and presetting a voltage anomaly judgment threshold value of the system monitoring model; acquiring real-time power data of the AC / DC power supply system and real-time operation state and load change data of the power grid, inputting the data into the system monitoring model, and identifying the mode, trend and potential abnormity of voltage fluctuation of the AC / DC power supply system; and dynamically adjusting a preset voltage abnormity judgment threshold value, and giving a corresponding AC / DC power supply system adjustment strategy and early warning information. The problems that in the prior art, an alternating-current and direct-current power supply system monitoring method is low in efficiency, frequent in false alarm and missing alarm conditions, difficult to adapt to a complex and changeable power grid environment and lack of intelligent analysis and early warning functions are solved.

The invention discloses a fault prediction method for a front-end isolated switching power supply of an aging table, and the method comprises the steps: carrying out the dimension reduction of preset time sequence signals of a plurality of aging table switching power supplies, and extracting feature parameters; calculating the performance degradation path similarity of the switch power supply of each aging station according to the characteristic parameters of each preset time sequence signal; clustering the degradation paths according to the performance degradation path similarity of the switch power supplies of the aging stations to obtain N degradation path sets; establishing N switching power supply life prediction models, and training the N switching power supply life prediction models according to the N degradation path sets; and based on the trained N switching power supply service life prediction models, predicting the service life of the aging station switching power supply to obtain the residual service life of the switching power supply. According to the aging table front-end isolated switching power supply fault prediction method considering multiple degradation paths provided by the invention, the residual service life of the switching power supply can be accurately predicted.

A method and system for evaluating strength of a voltage source converter (VSC)-penetrated power grid based on voltage stiffness are provided. First data corresponding to a to-be-analyzed power grid is acquired in real time, and processed to generate a first admittance matrix corresponding to the to-be-analyzed power grid. The first admittance matrix is processed to generate device impedance data of each VSC and a second admittance matrix corresponding to the to-be-analyzed power grid. Rows and columns where a grid-forming VSC node and a rated alternating-current (AC) bus voltage grid-following VSC node are located are removed from the second admittance matrix to generate a third admittance matrix, which is processed to generate second data and third data corresponding to the VSC node. Strength evaluation data corresponding to the to-be-analyzed power grid is generated based on the third data in combination with the second data.

The invention provides a shelter rapid power supply recovery method and system suitable for an emergency rescue task. The method comprises the following steps: collecting a power interruption signal, analyzing the power interruption signal, and generating an emergency response instruction; fault points are automatically identified and accurately positioned, the importance level of each electric device in the shelter is evaluated, and a dynamic priority list and a device demand report are generated; intelligently selecting a stand-by power supply combination scheme, starting a stand-by power supply switching process, and generating a stand-by power supply activation instruction; after a standby power supply activation instruction is received, the power supply sequence and power distribution of all devices are dynamically adjusted, normal operation of key facilities is preferentially guaranteed, and a device power supply plan is generated; and continuously monitoring the working state of the standby power supply and the influence of the standby power supply on the overall power system of the cabin, dynamically optimizing the power supply strategy, and generating an optimized power supply scheme. According to the technical scheme provided by the invention, the response speed and the power supply reliability of the shelter hospital or the temporary emergency facility during power interruption are improved.

The invention relates to the technical field of power supply electric quantity monitoring, in particular to an elevator emergency power supply electric quantity monitoring method and system. The method comprises the following steps: collecting emergency state starting time data; performing real-time battery electric quantity measurement on the emergency power supply battery according to the emergency state starting time data to obtain emergency power supply electric quantity measurement data; step pulse power supply testing is conducted on the elevator emergency lighting lamp, and multiple sets of pulse response data of the lamp are obtained; performing real-time lamp working state judgment according to the multiple groups of pulse response data of the lamp, and performing monitoring power supply electric quantity periodic updating on the electric quantity measurement data of the emergency power supply to obtain electric quantity monitoring data of the emergency power supply; and gradient brightness regulation and control are conducted according to the emergency power supply electric quantity monitoring data, and an intelligent elevator emergency dimming strategy is obtained. By intelligently monitoring the residual electric quantity of the elevator emergency power supply, dynamic adjustment of the elevator emergency lighting brightness is achieved, and the lighting time is prolonged.

The invention relates to a detection control method and system for a vehicle emergency starting power supply, and the method comprises the steps: obtaining multi-battery type interface data of the vehicle emergency starting power supply, and carrying out the electrical characteristic recognition processing, and obtaining the characteristic information of a battery interface; acquiring real-time operation data of the vehicle emergency starting power supply, and performing association processing on the real-time operation data and the battery interface feature information to obtain a battery operation state evaluation result; acquiring battery charging and discharging energy data of the vehicle emergency starting power supply, and performing battery state prediction according to the battery charging and discharging energy data to obtain a battery energy balance trend; comprehensively analyzing the battery operation state evaluation result and the battery energy balance trend to obtain an initial power management control scheme; and performing iterative optimization on the initial power management control scheme according to the fault early warning information to obtain a corresponding emergency start power protection strategy. According to the invention, the emergency starting power supply can be ensured to operate efficiently under different use conditions.

The invention provides a driving power supply testing method, device and equipment and a storage medium, and relates to the technical field of driving power supply testing, and the method comprises the steps: obtaining an input voltage, an input current, an output voltage and an output current of a to-be-tested driving power supply under different loads; according to the input voltage, the input current, the output voltage and the output current of the to-be-tested driving power supply under different loads, calculating the conversion efficiency of the to-be-tested driving power supply under different loads; according to the conversion efficiency of the to-be-tested driving power supply under different loads, determining stable parameters of the to-be-tested power supply; acquiring output voltage fluctuation ranges of the to-be-tested driving power supply under different loads, and determining precision parameters of the to-be-tested driving power supply according to the output voltage fluctuation ranges of the to-be-tested driving power supply under different loads; and determining the working performance grade of the to-be-tested driving power supply in combination with the stable parameters and the precision parameters. The technical effect of the invention is that the comprehensive performance of the driving power supply can be accurately evaluated.