577 results about "Charge detection" patented technology

The invention relates to the technical field of electric vehicle battery charging detection, and discloses an intelligent charging pile system and method integrating real-time battery state detection. A data fusion module; a battery health state prediction module; a charging optimization control module; the fault early warning module is connected with the cloud platform and edge computing cooperative processing module; the method comprises the following steps: acquiring battery data through multiple sensors, and constructing a data frame; extracting electrical characteristics, and generating a battery state vector; a digital twin model is constructed, and health state prediction is carried out; formulating a dynamic charging power regulation strategy; comparing the health trend of the battery with an expected behavior, and generating a fault early warning signal; and uploading the data and the strategy to the cloud platform, and updating the control strategy. According to the invention, a multi-sensor data fusion technology is adopted, twin modeling and a deep learning algorithm are combined, the health state of the battery is monitored in real time, the health state of the battery is comprehensively evaluated, and the fault risk of the battery is accurately predicted.

The invention relates to the field of machine learning, and discloses a charging pile fault diagnosis method, which comprises the following steps: S1, preparing an environment, building a deep learning development environment, and providing a necessary technical environment for the training and deployment of a subsequent model; and S2, data acquisition and processing: installing a current sensor, a voltage sensor and a temperature sensor on a new energy automobile charging detection vehicle, and acquiring operation data of the charging pile in real time. And S3, model definition: a fault diagnosis model based on deep learning is constructed, a fully connected neural network (DNN) is adopted, and the model comprises an input layer, a hidden layer and an output layer. The key operation data of the charging pile are collected in real time through the sensor, the fault state is intelligently judged in combination with the deep learning model, rapid and accurate fault positioning and diagnosis are achieved, and the maintenance efficiency of the charging pile is remarkably improved. The system can automatically extract data features and analyze fault types, and manual intervention is reduced.

The invention belongs to the technical field of charging detection, and particularly relates to a charging pile extreme environment test method based on composite stress simulation, a terminal and a storage medium, and the method comprises the steps: inputting an identifier corresponding to a target test scene through a human-computer interaction interface of a test cabin, and executing a query operation based on the input identifier, retrieving a preset parameter combination from a preset scenarized stress library by using the mapping function; in a closed test cabin, environment parameter data are collected in real time through a distributed sensor array and fed back to a central controller, and the central controller drives an execution component to cooperatively regulate and control parameters such as temperature and humidity, so that the environment parameters are stabilized in a preset range; a sequential stress scheme is generated based on a pre-stored dynamic loading algorithm, an execution component is controlled to realize stress superposition or stress alternation, and a charging load is synchronously adjusted to simulate a composite stress effect under an actual working condition; simulation of multi-factor combined stress and dynamic loading is realized, an actual use fault can be found in advance, and the matching degree of a test result and a real environment is remarkably improved.

The invention relates to the field of LED driving controllers, in particular to a control method of a waterproof touch type LED driving controller, which automatically identifies environmental conditions and user preferences through an AI algorithm, dynamically adjusts sensor parameters, realizes self-adaptive configuration, intelligently distinguishes real touch control and false triggering through charge detection, capacitive sensing and weak magnetic field change, and improves the control accuracy of the waterproof touch type LED driving controller. A user operation intention such as light touch, long press and sliding is deeply analyzed in combination with machine learning, after a control strategy is dynamically generated, LED brightness and color temperature are automatically adjusted and a command is executed according to the user intention and environmental parameters, the control strategy is optimized through a reinforcement learning algorithm, meanwhile, a health monitoring function is integrated, a user operation mode and environmental data are analyzed, and the user experience is improved. The health state of the equipment is intelligently judged, potential faults are warned in advance, and stable operation of the equipment and user experience are ensured.

The invention discloses an oil return buffer device and an impact test system with the same. The oil return buffer device comprises a cylinder barrel assembly, a buffer piston, an impact piston, an overflow detection loop, an oil charge detection loop and an air charge detection loop. A first inner barrel cavity, a damping hole and a buffering cavity are formed in the cylinder barrel assembly, and the buffering cavity is connected with an oil filling detection loop. The buffer piston is arranged in the first inner cylinder cavity so as to divide the first inner cylinder cavity into a first side cavity and a second side cavity. The buffer piston is provided with a second inner cylinder cavity, the impact piston is arranged in the second inner cylinder cavity to divide the second inner cylinder cavity into an oil return cavity and an air cavity, the oil return cavity communicates with the first side cavity, and the air cavity communicates with the inflation detection loop. The device has the obvious impact stage and the buffering stage, the instant impact pressure is rapidly reduced in the impact stage, the deceleration back pressure is obtained through oil pressure loss in the buffering stage, the buffering effect is obvious and easy to control, and the device is suitable for the field of high-speed large-flow oil return buffering of an impact hydraulic system.

The invention discloses a battery state-of-charge detection method based on deep learning and ultrasonic feature fusion. The method comprises the following steps: collecting and preprocessing battery ultrasonic signals and battery electrical parameters; extracting an ultrasonic amplitude; extracting and fusing the characteristics of the battery voltage, the surface temperature, the ultrasonic amplitude and the phase difference; the method comprises the following steps of: optimizing parameter values of a BiTCN-BiLSTM-Multi-Head Attention network on the basis of a WAA weighted average optimization algorithm, extracting basic characteristics related to the SOC of the battery in a characteristic matrix on the basis of a bidirectional time convolution network BiTCN, extracting long-term information related to the SOC of the battery in the basic characteristics on the basis of a BiLSTM network, extracting important characteristics related to the SOC of the battery in the long-term information on the basis of a Multi-Head Attention network, and calculating the SOC of the battery according to the extracted important characteristics. And outputting a predicted value of the SOC of the battery through the full connection layer. According to the invention, the estimation precision of the battery SOC can be improved.

A charge detection mass spectrometer includes an ion trap configured to store ions therein and to release stored ions therefrom, and an electrostatic linear ion trap (ELIT) array, in the form of at least two ELITs or ELIT regions each spaced apart from the ion trap, each ELIT or ELIT region including first and second ion mirrors and a charge detection cylinder positioned therebetween. The ion trap is controlled to release at least some of the stored ions to travel toward and into each of the ELITs or ELIT regions, and the first and second ion mirrors of each of the ELITs or ELIT regions is controlled in a manner which traps one or more ions traveling therein and causes the trapped ion(s) to oscillate back and forth between the first and second ion mirrors each time passing through and inducing a corresponding charge on the charge detection cylinder.

A charge detection mass spectrometer includes an ion trap configured to store ions therein and to release stored ions therefrom, and an electrostatic linear ion trap (ELIT) array, in the form of at least two ELITs or ELIT regions each spaced apart from the ion trap, each ELIT or ELIT region including first and second ion mirrors and a charge detection cylinder positioned therebetween. The ion trap is controlled to release at least some of the stored ions to travel toward and into each of the ELITs or ELIT regions, and the first and second ion mirrors of each of the ELITs or ELIT regions is controlled in a manner which traps one or more ions traveling therein and causes the trapped ion(s) to oscillate back and forth between the first and second ion mirrors each time passing through and inducing a corresponding charge on the charge detection cylinder.

The invention discloses a new energy automobile charging detection system, and relates to the field of new energy automobiles, and the system comprises a battery state monitoring module which is used for collecting and analyzing the health condition, residual capacity and chargeable quantity parameters of a battery in real time. The system has the beneficial effects that the charging strategy is modulated in real time through the battery state monitoring module and the intelligent charging control module, the charging efficiency is high, and the damage to the service life of the battery is reduced; a safety protection module is arranged, the states of the battery pack and the charging system are monitored in real time, response to abnormal conditions such as short circuit, over-temperature and over-current is fast, and potential safety hazards are reduced; the user interaction module is arranged, the user interactivity is high, and a user can know the charging state and the battery health condition in real time and flexibly adjust charging setting according to requirements; and a cloud data management module is arranged to deeply analyze the charging data, so that decision support is provided, and remote data access and sharing are realized.

The invention belongs to the technical field of circuit board manufacturing and detecting, and particularly relates to a circuit board detecting device and method.The device comprises a workbench, two visual detecting heads arranged on the workbench, a feeding rotary table, a lifting table and a rotary table, the feeding rotary disc is rotationally installed on the upper surface of the workbench, at least six material carrying holes are distributed in the feeding rotary disc in a circumferential array mode, the inner walls of the material carrying holes are in a step shape, material carrying molds are inserted into the steps, and clamping channels are formed in the two sides of each material carrying mold. The upper surface of the workbench is sequentially divided into a lower surface detection area, an upper surface detection area, an X-ray detection area and a live detection area around the feeding turntable; the method comprises steps 1-6. Detection can be carried out in four areas through the same material carrying die, particularly, horizontal clamping and transferring of the circuit board are kept, the deviation correction performance is good in the double-face continuous rapid detection process, and surface electronic elements are not damaged in the whole process.

The invention belongs to the technical field of porcelain insulator detection in a power system, and provides a porcelain insulator live detection method and system based on mechanical pulse excitation, and the method comprises the steps: S1, building an insulator detection result database through vibration response simulation; s2, detecting the insulator to be detected: performing the same excitation operation on the insulator to be detected, and detecting and extracting voiceprint feature data of the insulator to be detected; s3, contrastive analysis: inputting the extracted feature values into a pre-trained deep BP neural network model, adding at least one hidden layer to the model on the basis of a standard BP neural network, and improving the model by using a ReLU activation function and a dropout strategy; and outputting a detection result through the deep BP neural network model, and judging the state of the insulator. According to the scheme, on-line, rapid and accurate detection of the porcelain insulator is realized, meanwhile, the detection cost and time are reduced, the operation condition can be grasped in time, and power failure accidents are avoided.

Disclosed in the present application are an electrical load measurement method and apparatus for an electric bicycle, and a device and a storage medium. The method comprises: collecting original current data, in a power distribution network, of electricity consumers that belong to residential household electricity consumption; according to electricity consumption behavior data, clustering the electricity consumers to obtain user categories to which the electricity consumers belong; on the basis of the user categories, extracting part of the original current data to serve as target current data; loading a charging detection network on the basis of the user categories; encoding the target current data in an encoder to obtain first target current features configured for distinguishing whether there is an electric bicycle charging behavior; decoding the first target current features in a decoder, and on the basis of a decoding result, performing reconstruction to obtain second target current features, wherein the second target current features represent current features of a plurality of levels of when the user categories have the electric bicycle charging behavior; and in a classifier, under the enhancement of the second target current features of the plurality of levels and on the basis of the first target current features, detecting an electrical load for indicating whether the electricity consumers have the electric bicycle charging behavior.

A method of discriminating noise, the method implemented by a computer comprising a processor and a memory, the method comprising: obtaining a time-domain signal representative of a charge induced in an inductive charge detector by an ion moving in a charge-detection mass spectrometer, CDMS; transforming the time-domain signal into a frequency-domain spectrum comprising a series of frequency-amplitude pairs; and rejecting a particular frequency-amplitude pair of the series of frequency-amplitude pairs not having a respective harmonic frequency-amplitude pair amongst the series of frequency-amplitude pairs.

The invention belongs to the technical field of space environment detection, and relates to an ASIC (application specific integrated circuit)-based multichannel parallel charge detection device for space charged particle detection, which comprises an anode plate, a front placing plate and a digital acquisition and processing plate, and signal transmission is performed between the anode plate and the front placing plate as well as between the front placing plate and the digital acquisition and processing plate through inter-plate connectors; the anode plate is an annular anode and is divided into a plurality of anodes, the output of each anode is connected with a current-limiting resistor in series, and a charge signal output by each anode is transmitted to the front amplifier plate through the inter-plate connector; the pre-amplification board adopts an integrated charge sensitive amplifier ASIC to amplify multiple paths of charge signals output by the anode plate, and outputs multiple paths of digital pulses to be input into the digital acquisition processing board through an inter-board connector; and the digital acquisition and processing board is used for detecting and counting multiple paths of digital pulses output by the pre-amplification board in parallel, and periodically packaging and outputting the digital pulses to a PC (Personal Computer) end.

The invention discloses a solid-state battery performance testing device, and relates to the technical field of battery performance testing devices.The solid-state battery performance testing device comprises a placement frame, a placement table is fixedly installed at the bottom of the inner wall of the placement frame, and a cover plate is rotatably installed on the inner wall of the placement frame; a fire extinguishing device is fixedly installed on the side, close to the containing frame, of the cover plate, and a clamping device is further arranged on the inner wall of the containing frame. Wherein the clamping device comprises an electric push rod, a push plate, a clamping plate, a push rod, a sliding rod, a sliding plate, a rotating rod and a pushing rod, the electric push rod is fixedly installed on the inner wall of the placing frame, the push plate is fixedly installed at the movable end of the electric push rod, the clamping plate is fixedly installed on the side, close to the placing table, of the push plate, and the clamping plate can fix a battery; the battery is fixed, so that the battery is prevented from deviating when charging detection is carried out on the battery, which may cause that a plug of a power supply cannot be well inserted into the battery.

The invention relates to the technical field of live detection, in particular to a power distribution gap lightning arrester live detection result compensation algorithm, which comprises the following steps: acquiring a voltage signal and dividing a period section, extracting waveform characteristics to generate a mark set, identifying trend reversal to construct a sudden change section list, analyzing intersection point spacing to form an abnormal set, and calculating a power distribution gap lightning arrester live detection result. And tracking trend deviation to determine correction data, mapping a reference path to reconstruct a reference baseline, and completing conduction state correction recording. According to the method, the detection data of the operation state of the power distribution gap lightning arrester is processed, waveform segmentation marks of a continuous period are constructed, a reversal trend path and slope abrupt change characteristics are combined, potential interference is identified, an abnormal fluctuation area is formed, and a voltage recovery deviation trend is constructed and analyzed through a front window and a trend line segment; and the offset starting and ending points are positioned and the reference path is corrected, so that the reliability of detection data, the accuracy of state judgment and the adaptability of operation conditions are effectively improved.

The invention discloses an electric vehicle charging detection method, which comprises the following steps: taking the change of an active power transient waveform in a socket as a transient event, and monitoring the transient event based on a time sliding window; when the transient event is ended, calculating the variable quantity of the active power before and after the transient event; comparing the variable quantity of the active power with an active power threshold value of the electric vehicle to determine that the electric vehicle is inserted into the socket, and acquiring an active power sampling sequence in the socket in the time sliding window; processing the active power sampling sequence based on an electric vehicle charging detection model, and detecting the charging state of the electric vehicle; the detection accuracy of the charging state of the electric bicycle is improved, and the charging misjudgment event of the electric bicycle is avoided.

The invention relates to the field of power grid power load detection, in particular to a power grid power load real-time detection method and system. The method comprises the following steps: acquiring load values of a power grid after preprocessing, constructing a load sequence, and labeling each load value; decomposing the load sequence based on VMD to obtain a plurality of modal components, classifying frequency values in any modal component into a normal class and an abnormal class according to labels, and calculating a first offset mean value of the normal class and a second offset mean value of the abnormal class; and training a preset network based on the calculated importance, inputting frequency values of a plurality of modal components of the real-time load value into the correspondingly trained preset network, outputting sub-probabilities, integrating all the sub-probabilities to obtain a state probability, and completing detection. According to the technical scheme, the precision of the charge detection result can be improved, and a guarantee is provided for safe operation of a power grid.

The invention relates to a vehicle battery detector, and relates to the field of new energy vehicle charging system detection. The vehicle battery detector comprises a detection device and a charging gun. The charging gun is used for connecting a charging interface of a to-be-detected vehicle; the detection device is electrically connected with the charging gun; the detection device comprises a power supply module and a signal module; the power supply module is electrically connected with the signal module; the power supply module comprises a battery; the power module is used for using a battery to supply power to the signal module and the charging gun; and the signal module is used for sending the detection signal to the vehicle, receiving a feedback signal returned by the vehicle according to the detection signal, and detecting the power battery of the vehicle according to the feedback signal. According to the scheme, the portability of the vehicle battery detector can be improved, and the detection efficiency of the power battery is improved.

The invention discloses an electric vehicle troubleshooting system and method. The system comprises a pre-charging detection module and a pre-charging detection loop module which are connected to an electric vehicle bus in parallel. The pre-charging detection loop module comprises a plurality of pre-charging detection branch circuits which are connected in parallel, each pre-charging detection branch circuit is connected with an electric vehicle bus, and each pre-charging detection branch circuit comprises a high-voltage component and a high-voltage relay used for controlling the on-off of the current pre-charging detection branch circuit; the detection end of the pre-charging detection module is connected with an electric vehicle bus, the power supply end of the pre-charging detection module is connected with an electric vehicle battery system, and the pre-charging detection module is used for carrying out pre-charging troubleshooting on a high-voltage part corresponding to the high-voltage relay according to the resistance value and / or tube voltage drop value of the electric vehicle bus. According to the electric vehicle troubleshooting system and method provided by the embodiment of the invention, automatic insulation and pre-charging troubleshooting are realized.

The invention relates to the field of data processing, in particular to a lithium battery charging data monitoring method and system. The method comprises the steps of obtaining feature sequences of historical charging data points, obtaining feature data of any dimension from the feature sequences of all the historical charging data points, calculating category consistency between the feature data of each dimension and the feature data of other dimensions, and determining a reference weight of the feature data of each dimension according to the category consistency; obtaining classification meticulousness of the feature data of each dimension, and obtaining a time sequence weight adjustment coefficient of the feature data of each dimension according to the classification meticulousness; and setting the weight of each clustering stage according to the time sequence weight adjustment coefficient and the reference weight, and enabling the weight of each clustering stage to participate in clustering iteration updating to complete clustering processing so as to realize anomaly detection of the charging data point at the current moment. The accuracy of charging detection is improved by improving the accuracy of clustering.

The invention relates to an intelligent light storage charging detection energy collaborative optimization control method and system. The method comprises the following steps: predicting a high-frequency fluctuation period of each charging station based on historical information; when photovoltaic power generation in the charging station is in a high-frequency fluctuation period at the current moment, the monitoring frequency of meteorological data is determined according to the average duration, predicted by the fluctuation prediction model, of each fluctuation, and a power supply mode is adjusted according to the meteorological data; and when the photovoltaic power generation in the charging station is not in the high-frequency fluctuation period at the current moment, judging that the monitoring frequency of the meteorological data is a fixed preset frequency. According to the invention, the monitoring frequency and the power supply mode are dynamically adjusted to cope with the fluctuation of photovoltaic power generation and the abnormity of meteorological data. The strategy optimization not only improves the stability and reliability of the system, but also reduces the operation cost and the impact on the power grid. The operation efficiency and stability of the charging station can be effectively improved, and the influence of photovoltaic power generation fluctuation and meteorological abnormity on charging of the electric vehicle is reduced.

The invention relates to the technical field of slag charge detection, in particular to urban ecological environment detection equipment which comprises a sampling barrel, a sampling mechanism and a material stirring part, the sampling barrel is sequentially divided into a plurality of sampling sections distributed at equal intervals and a sampling tip convenient for the sampling barrel to be inserted into a sample from top to bottom, and the sampling mechanism is arranged in the sampling section. The sampling ports in all the sampling sections are controlled by the operating rod to be switched among the three states of complete closing, semi-closing and complete opening, slag samples in a plurality of set heights are obtained through a single sampling process under the condition that the initial positions of the slag samples are not affected, and the problem of multiple sampling operations is avoided. Secondly, the slag samples around the sampling barrel are shifted by the shifting plate, and the slag samples around the sampling opening are scratched by the edge of the scratching strip, so that the taking process of the slag samples is assisted.

The invention relates to a battery charge state detection method and device, equipment, a storage medium and a product. The method comprises the steps that first sample data without a battery state-of-charge label is used as a first training data set, a first battery state-of-charge detection model with battery operation characteristics changing along with time is constructed, and the first sample data is generated according to battery historical operation total data; constructing a second battery charge state detection model according to the feature encoder; constructing second sample data carrying a battery charge state label according to battery historical operation sampling data extracted from the battery historical operation total data, and obtaining sample feature data through a feature encoder; and iteratively optimizing a feature predictor of a second battery state-of-charge detection model by taking the sample feature data as a second training data set, and taking the iteratively optimized second battery state-of-charge detection model as a target battery state-of-charge detection model. By adopting the method, the detection accuracy of the battery charge state detection is improved.

The invention relates to the technical field of battery replacement cabinet charging detection, and provides a charging detection method and system for batteries of a battery replacement cabinet. The method comprises the following steps: setting initial parameters according to layout information of a charging bin of a battery changing cabinet; determining a candidate strategy based on the initial parameters in combination with voltage overcharge protection and current overcurrent protection conditions; based on a candidate strategy, configuring a first regulation and control vector in a gain space in a stepped manner by direct-current voltage, and configuring a second regulation and control vector in a digital space in a stepped manner by a pulse width duty ratio; establishing a charging strategy search space through the two types of regulation and control vectors; and performing Pareto screening in the space to obtain a service life, efficiency and safety performance non-dominated solution set, and determining an optimal strategy, so as to solve the technical problem that safety, charging efficiency and cycle life optimization are difficult to consider in the charging process of the battery of the battery changing cabinet, and achieve the purposes of constructing a charging strategy search space through a multi-dimensional regulation and control vector and performing Pareto screening to obtain a charging strategy. The technical effects of prolonging the charging and discharging service life, improving the charging efficiency and improving the safety performance are achieved.

The invention discloses a charging pile internal temperature detection method, a charging detection system and a charging pile, and relates to the technical field of electric vehicle charging, the method comprises the following steps: obtaining a target data packet, and analyzing the target data packet to obtain a first parameter; acquiring a second parameter; the second parameter comprises the current environment temperature and the current charging power in the charging pile; obtaining a current compensation temperature based on a temperature compensation model, the first parameter and the second parameter; the temperature compensation model is used for indicating the relation among the compensation temperature, the charging power and the environment temperature; obtaining a target voltage, and determining a target temperature of a detection point of the charging pile based on the target voltage; and determining the actual temperature of the detection point according to the current compensation temperature and the target temperature. According to the method, the detection precision is improved through temperature compensation, and charging safety is guaranteed.

The invention provides a lithium battery state-of-charge rapid detection method, and belongs to the technical field of lithium battery detection.The lithium battery state-of-charge rapid detection method comprises the steps that the surface temperature and the initial end voltage of a to-be-detected lithium battery are collected, and the internal resistance growth rate and the capacity fading rate are obtained through a pulse discharge test to evaluate the health state grade; carrying out impedance measurement on the characteristic frequency points to obtain impedance real part and imaginary part data to form a characteristic frequency impedance vector, extracting a statistical moment characteristic vector, inputting a battery state topology reasoning model to output a primary charge state estimation value and local area charge state distribution, extracting auxiliary characteristics in a low-resolution interval to carry out dynamic correction, and judging whether to increase the measurement frequency points according to the confidence interval width. The method solves the technical problems that the lithium battery state-of-charge detection is insufficient in estimation precision and cannot quantify the uncertainty when facing health state degradation and a low-resolution interval.

The invention provides a charging control method and system, electronic equipment and a storage medium. The charging control method comprises the following steps: setting a first threshold temperature according to a first charging gear, and setting a second threshold temperature according to a second charging gear; in response to selection of the charging gear, calling a target threshold temperature corresponding to the selected charging gear; in the charging mode, the charging detection temperature of the direct current conversion module is collected in real time, and whether the charging detection temperature is larger than or equal to the target threshold temperature or not is judged; when it is judged that the charging detection temperature is larger than or equal to the target threshold temperature, the output control module reduces the current charging current until the charging detection temperature is smaller than the target threshold temperature. According to the charging control method, a switching device in the direct current conversion module can be prevented from being burnt out, and the safety and reliability of the charging process are effectively improved.

The invention relates to the technical field of battery management, and relates to a battery protection circuit and power supply equipment. The circuit comprises a charging and discharging switch unit, a voltage stabilizing circuit unit, a self-locking circuit unit, a charging detection unit and a battery management unit, the charge-discharge switch unit is arranged between the battery and the load circuit, and the driving end of the charge-discharge switch unit is connected with the battery management unit; the self-locking circuit unit is arranged between the positive electrode of the load circuit and the voltage input end of the voltage stabilizing circuit unit, and the voltage output end of the voltage stabilizing circuit unit is connected with the power supply end of the battery management unit; the charging detection unit is used for feeding back a first level signal to the battery management unit based on the potentials of the negative electrode of the battery and the grounding end of the load circuit, and driving the self-locking circuit unit to enter a self-locking conduction state; the battery management unit is used for comparing the battery electric quantity with a preset value and then outputting a second level signal so as to drive the self-locking circuit unit to enter a turn-off state. The service lives of the battery and the applied power supply equipment can be prolonged, and potential safety hazards are reduced.

The present application relates to a kind of new energy vehicle operation safety detection system and charging detection method, it is related to new energy vehicle detection technical field, solve the technical problem of small use range of new energy vehicle operation safety detection equipment in prior art.The new energy vehicle operation safety detection system includes: solar module, battery module, inverter, charging module, control system, direct current charging gun, communication module, charging detection module, display module and 220V power module.The new energy vehicle operation safety detection system of the present application uses high-power battery pack as power supply, and can detect the safety of power storage battery, drive motor, electric control system and electrical safety of new energy vehicle, compared with the prior art using 380v industrial power grid as power supply, since there is no grid restriction, increase the use range and flexibility of new energy vehicle operation safety detection equipment.