CN113533965A - Storage battery performance analysis platform and method - Google Patents
Storage battery performance analysis platform and method Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
Abstract
The embodiment of the invention discloses a storage battery performance analysis platform and a storage battery performance analysis method, wherein the storage battery performance analysis platform comprises a data acquisition module, a data analysis module and a data analysis module, wherein the data acquisition module is used for continuously acquiring state data of each storage battery in a storage battery; the nuclear capacity discharge module is used for receiving the control instruction sent by the background analysis module, performing nuclear capacity discharge operation on the storage battery pack according to the control instruction, and collecting nuclear capacity discharge test data of each storage battery in the process of performing the nuclear capacity discharge operation; the background analysis module is used for sending a control command to the nuclear capacity discharge module, acquiring state data and nuclear capacity discharge test data, extracting characteristic parameters from the state data and the nuclear capacity discharge test data, inputting the characteristic parameters into the performance analysis model, obtaining a performance analysis result of each storage battery, and visually displaying the performance analysis result. According to the embodiment of the invention, the nuclear qualitative discharge test of the storage battery pack is not required to be carried out on the storage battery pack by manpower on the installation site, and the technical problem of low efficiency of detecting the performance of the storage battery pack in the prior art is solved.
Description
Technical Field
The embodiment of the application relates to the field of storage battery packs, in particular to a storage battery pack performance analysis platform and a storage battery pack performance analysis method.
Background
The storage battery pack is a device for directly converting chemical energy into electric energy, can regenerate internal active substances through external electric energy in the charging process, stores the electric energy into the chemical energy, and converts the chemical energy into the electric energy for output in the discharging process. At present, most of backup power supplies of UPS and DC power supply systems are composed of valve-controlled sealed lead-acid storage batteries, and due to the reasons of manufacturing, storage, maintenance and the like of the valve-controlled sealed lead-acid storage batteries, the valve-controlled sealed lead-acid storage batteries often break down after being used for a period of time, and are also one of components which are easy to damage in equipment. The causes of the performance degradation of the battery pack include the following: water loss, sulfation, corrosion and deformation of the grid, softening of the active species, short circuiting of the dendrites, and the like.
At present, a mode for analyzing the performance of the storage battery pack is to perform a nuclear qualitative discharge test on the storage battery pack, however, manual operation is required when the discharge test is performed on the storage battery pack, the discharge test time of each storage battery pack is long, at least 3-8 hours are required, and when the number of the storage battery packs is large, the efficiency of detecting the performance of the storage battery pack is low, and the workload is large.
Disclosure of Invention
The embodiment of the invention provides a storage battery performance analysis platform and a storage battery performance analysis method, which are used for solving the technical problem of low efficiency of detecting the performance of a storage battery in the prior art.
In a first aspect, an embodiment of the present invention provides a storage battery performance analysis platform, including:
the data acquisition module is used for continuously acquiring the state data of each storage battery in the storage battery pack;
the nuclear capacity discharge module is used for receiving a control instruction sent by the background analysis module, performing a nuclear capacity discharge test on the storage battery pack according to the control instruction, and collecting nuclear capacity discharge test data of each storage battery in the process of performing the nuclear capacity discharge test;
the background analysis module is used for sending a control command to the nuclear capacitor discharge module, acquiring the state data and the nuclear capacitor discharge test data, extracting characteristic parameters from the state data and the nuclear capacitor discharge test data, inputting the characteristic parameters into a performance analysis model, obtaining a performance analysis result of each storage battery, and visually displaying the performance analysis result.
Preferably, the system further comprises an online sulfur removal module, wherein the online sulfur removal module is used for receiving a sulfur removal instruction sent by the background analysis module and performing sulfur removal operation on the storage battery pack according to the sulfur removal instruction;
correspondingly, the background analysis module is further configured to:
and sending the sulfur removal instruction to the online sulfur removal module.
Preferably, the state data includes working voltage data, working current data, float voltage data and temperature data;
correspondingly, the data acquisition module comprises a power supply unit, a voltage sensor, a current sensor, a floating charge voltage sensor and a temperature sensor;
the voltage sensor is used for acquiring voltage data of each storage battery;
the current sensor is used for acquiring current data of each storage battery;
the float charge voltage sensor is used for acquiring float charge voltage data of each storage battery;
the temperature sensor is used for acquiring temperature data of each storage battery;
the power supply unit is used for providing working voltages for the voltage sensor, the current sensor, the float charge voltage sensor and the temperature sensor.
Preferably, the nuclear capacity discharging module comprises a test data acquisition unit, a processor unit, a discharging unit and a charging unit;
the test data acquisition unit is used for acquiring the nuclear capacity discharge test data of each storage battery in the nuclear capacity discharge test process of the storage battery pack;
the processor unit is used for receiving the control instruction and controlling the discharging unit and the charging unit according to the control instruction;
the discharge unit is used for carrying out nuclear capacity discharge operation on the storage battery pack;
the charging unit is used for carrying out the core-capacity charging operation on the storage battery pack.
Preferably, the system further comprises a cloud storage module, and the cloud storage module is used for storing the state data, the nuclear capacity discharge test data and the performance analysis result.
Preferably, the nuclear capacity discharge test data includes storage battery internal resistance data and charge-discharge parameters.
Preferably, the characteristic parameters include a first dispersion variable of each storage battery relative to the float voltage of the storage battery, a second dispersion variable of each storage battery relative to the float voltage of the storage battery pack, an internal resistance variation, a uniform charging characteristic parameter, a discharging characteristic parameter, a working voltage characteristic parameter, a working current characteristic parameter and a temperature characteristic parameter.
Preferably, the background analysis module is configured to input the characteristic parameters into a performance analysis model, and a specific process of obtaining a performance analysis result of each storage battery is as follows:
the background analysis module is used for inputting the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charging characteristic parameter, the discharging characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter into a performance analysis model, so that the performance analysis model can carry out deep learning on the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charge characteristic parameter, the discharge characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter to obtain the performance analysis result of each storage battery, and the performance analysis model is obtained by training a neural network model by adopting the historical characteristic parameters of each storage battery and the historical performance analysis result of each storage battery.
In a second aspect, an embodiment of the present invention further provides a storage battery performance analysis method, including the following steps:
sending a control instruction to a nuclear capacity discharge module to enable the nuclear capacity discharge module to perform a nuclear capacity discharge test on a storage battery pack, and acquiring nuclear capacity discharge test data of each storage battery, which is acquired by the nuclear capacity discharge module in the process of performing the nuclear capacity discharge test on the storage battery pack;
acquiring state data of each storage battery in the storage battery pack continuously acquired by a data acquisition module;
extracting characteristic parameters from the state data and the nuclear capacity discharge test data, inputting the characteristic parameters into a performance analysis model to obtain a performance analysis result of each storage battery, and visually displaying the performance analysis result.
Preferably, the method further comprises the following steps:
and storing the state data, the nuclear capacity discharge test data and the performance analysis result to a cloud storage module.
Preferably, the nuclear capacity discharge test data includes storage battery internal resistance data and charge-discharge parameters.
Preferably, the characteristic parameters include a first dispersion variable of each storage battery relative to the float voltage of the storage battery, a second dispersion variable of each storage battery relative to the float voltage of the storage battery pack, an internal resistance variation, a uniform charging characteristic parameter, a discharging characteristic parameter, a working voltage characteristic parameter, a working current characteristic parameter and a temperature characteristic parameter.
Preferably, the specific process of inputting the characteristic parameters into a performance analysis model to obtain the performance analysis result of each storage battery is as follows:
inputting the first dispersion variable, the second dispersion variable, the internal resistance variation, the equalizing charge characteristic parameter, the discharge characteristic parameter, the operating voltage characteristic parameter, the operating current characteristic parameter, and the temperature characteristic parameter into a performance analysis model, so that the performance analysis model can carry out deep learning on the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charge characteristic parameter, the discharge characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter to obtain the performance analysis result of each storage battery, and the performance analysis model is obtained by training a neural network model by adopting the historical characteristic parameters of each storage battery and the historical performance analysis result of each storage battery.
Preferably, the method further comprises the following steps:
sending a sulfur removal instruction to an online sulfur removal module so that the online sulfur removal module performs sulfur removal operation on the storage battery pack according to the sulfur removal instruction after receiving the sulfur removal instruction sent by the background analysis module
Preferably, the state data includes working voltage data, working current data, float voltage data and temperature data;
the data acquisition module acquires voltage data of each storage battery through a voltage sensor;
the data acquisition module acquires current data of each storage battery through a current sensor;
the data acquisition module acquires the float charge voltage data of each storage battery through a float charge voltage sensor;
the data acquisition module is used for acquiring the temperature data of each storage battery through a temperature sensor.
The data acquisition module provides working voltage for the voltage sensor, the current sensor, the floating charge voltage sensor and the temperature sensor through the power supply unit.
Preferably, the nuclear capacity receiving electrical module collects the nuclear capacity discharge test data of each storage battery in the process of performing the nuclear capacity discharge test on the storage battery pack through a test data collecting unit;
the nuclear receiving electrical module receives the control instruction through a processor unit and controls the discharging unit and the charging unit according to the control instruction;
the nuclear capacity discharge module carries out nuclear capacity discharge operation on the storage battery pack through a discharge unit;
and the nuclear capacity discharging module carries out nuclear capacity charging operation on the storage battery pack through a charging unit.
The storage battery performance analysis platform and the storage battery performance analysis method provided by the embodiment of the invention comprise a data acquisition module, a storage battery management module and a storage battery management module, wherein the data acquisition module is used for continuously acquiring state data of each storage battery in the storage battery; the nuclear capacity discharge module is used for receiving the control instruction sent by the background analysis module, performing nuclear capacity discharge operation on the storage battery pack according to the control instruction, and collecting nuclear capacity discharge test data of each storage battery in the process of performing the nuclear capacity discharge operation; the background analysis module is used for sending a control command to the nuclear capacity discharge module, acquiring state data and nuclear capacity discharge test data, extracting characteristic parameters from the state data and the nuclear capacity discharge test data, inputting the characteristic parameters into the performance analysis model, obtaining a performance analysis result of each storage battery, and visually displaying the performance analysis result. The embodiment of the invention controls the nuclear capacity containing discharge module to carry out nuclear capacity discharge operation on the storage battery by arranging the background analysis module, acquires the state data of the storage battery from the data acquisition module and acquires the nuclear capacity discharge test data from the nuclear capacity discharge module, extracts the characteristic parameters from the state data and the nuclear capacity discharge test data, inputs the characteristic parameters into the performance analysis model to carry out analysis, obtains the performance analysis result of each section of storage battery, and automatically completes the performance analysis of the storage battery by the storage battery performance analysis platform.
Drawings
Fig. 1 is a schematic structural diagram of a storage battery performance analysis platform according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for analyzing battery pack performance according to an embodiment of the present invention.
Detailed Description
The following description and the annexed drawings set forth in detail certain illustrative embodiments of the application so as to enable those skilled in the art to practice them. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the embodiments of the present application includes the full ambit of the claims, as well as all available equivalents of the claims. Embodiments may be referred to herein, individually or collectively, by the term "invention" merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed. The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the structures, products and the like disclosed by the embodiments, the description is relatively simple because the structures, the products and the like correspond to the parts disclosed by the embodiments, and the relevant parts can be just described by referring to the method part.
Example one
As shown in fig. 1, fig. 1 is a schematic structural diagram of a storage battery performance analysis platform provided in an embodiment of the present invention, and includes:
and the data acquisition module 101 is used for continuously acquiring the state data of each storage battery in the storage battery pack.
The nuclear capacitor electricity receiving module 102 is configured to receive the control instruction sent by the background analysis module 103, perform a nuclear capacitor electricity discharge test on the storage battery pack according to the control instruction, and acquire nuclear capacitor electricity discharge test data during the nuclear capacitor electricity discharge test of each storage battery.
The background analysis module 103 is configured to send a control instruction to the nuclear capacity discharge module 102, acquire state data and nuclear capacity discharge test data, extract characteristic parameters from the state data and the nuclear capacity discharge test data, input the characteristic parameters into the performance analysis model, obtain a performance analysis result of each storage battery, and visually display the performance analysis result.
Specifically, in the embodiment of the present application, a data acquisition module 101 and a nuclear capacity discharge module 102 are installed in the battery pack, communication units are further disposed on the data acquisition module 101 and the nuclear capacity discharge module 102, the data acquisition module 101 continuously acquires state data of each storage battery in the battery pack, and the acquired state data is sent to the background analysis module 103 through the communication units. In the operation process of the storage battery pack, the background analysis module 103 sends a control instruction to the nuclear capacity discharge module 102, after receiving the control instruction through the communication unit, the nuclear capacity discharge module 102 performs a nuclear capacity discharge test on the storage battery pack, collects nuclear capacity discharge test data of each storage battery in the nuclear capacity discharge test process, and sends the collected nuclear capacity discharge test data to the background analysis module 103 through the communication unit. It should be further noted that the status data includes the number information of the storage battery pack corresponding to the status data, and the capacity discharge test data also includes the number information of the storage battery pack corresponding to the capacity discharge test data, so that the corresponding storage battery pack can be determined during subsequent performance analysis. It is understood that in the present embodiment, the specific type of the communication unit may be set according to actual needs, and for example, the communication unit may adopt any one of a bluetooth communication unit, a GPRS communication unit, and a ZigBee communication unit, and the specific type of the communication unit is not limited in the present embodiment.
The background analysis module 103 acquires the state data after acquiring the nuclear capacity discharge test data, extracts the characteristic parameters of each storage battery from the state data and the nuclear capacity discharge test data, inputs the characteristic parameters into the performance analysis model for analysis and learning, and outputs the performance analysis result of each storage battery. In this embodiment, the background analysis module 103 is further provided with a display unit, and after the performance analysis result of each storage battery is obtained, the display unit further performs visual display on the performance analysis result of each storage battery, so that a worker can visually observe the performance analysis result. The performance of the storage battery is automatically analyzed by arranging the background analysis module 103, and the storage battery does not need to be subjected to a verification discharge test on the installation site of the storage battery manually in the process, so that the labor cost and the time cost are saved, and the analysis efficiency of the performance of the storage battery is improved.
Fig. 2 is a flowchart of a method for analyzing battery pack performance according to an embodiment of the present disclosure, where the method for analyzing battery pack performance according to the present disclosure may be executed by a battery pack performance analysis device, the battery pack performance analysis device may be implemented by software and/or hardware, and the battery pack performance analysis device may be formed by two or more physical entities or may be formed by one physical entity. Generally, the storage battery performance analysis device can be a computer, a mobile phone, a tablet or a server.
As shown in fig. 2, the method for analyzing the performance of the battery pack specifically includes:
In one embodiment, the nuclear capacity discharging module 102 includes a test data acquisition unit, a processor unit, a discharging unit, and a charging unit. The test data acquisition unit is used for acquiring the nuclear capacity discharge test data of each storage battery in the nuclear capacity discharge operation process of the storage battery pack. The processor unit is used for receiving the control instruction and controlling the discharging unit and the charging unit according to the control instruction. The discharge unit is used for carrying out the nuclear capacity discharge operation on the storage battery pack. The charging unit is used for carrying out the capacity checking charging operation on the storage battery pack.
The background analysis module 103 sends a control instruction to the core capacity discharge module 102, it can be understood that the manner of sending the control instruction may be set according to actual needs, and for example, the background analysis module 103 may automatically send the control instruction to the core capacity discharge module 102, or may manually control the background analysis module 103 to send the control instruction to the core capacity discharge module 102. After receiving the control instruction sent by the background analysis module 103, the processor unit of the nuclear capacity discharge module 102 controls the discharge unit to perform the nuclear capacity discharge operation on the storage battery pack according to the control instruction, and after the discharge is completed, controls the charge unit to perform the nuclear capacity charge operation on the storage battery pack, thereby completing the nuclear capacity discharge test. In the process of performing the nuclear capacity discharge test, the test data acquisition unit acquires the nuclear capacity discharge test data of each storage battery and sends the data to the background analysis module 103. In one embodiment, the process of performing the nuclear capacity charging operation on the storage battery by the charging unit is to uniformly charge the storage battery by using a large current, and perform floating charge on the storage battery by using a small current after the storage battery is fully charged by using a current, so as to complete the nuclear capacity discharge test. It can be understood that, in the present embodiment, the nuclear capacity discharge module 102 is further provided with a power supply, and the power supply is used for supplying power to the capacity discharge test data acquisition unit, the processor unit, the discharge unit and the charging unit, so as to ensure normal operation of the nuclear capacity discharge module 102.
In one embodiment, the nuclear capacity discharge test data includes internal resistance data of the storage battery and charge and discharge parameters. The test data acquisition unit acquires internal resistance data of each storage battery and charge and discharge parameters of each storage battery in the process of carrying out the nuclear capacity discharge test, wherein the charge and discharge parameters comprise charge cut-off voltage, discharge cut-off voltage, charge current and discharge current.
In this embodiment, the data acquisition module 101 continuously acquires the status data of each storage battery in the storage battery pack, and sends the status data to the background analysis module 103. It should be noted that, in another embodiment, the data collection module 101 collects the status data at certain time intervals.
In one embodiment, the status data includes operating voltage data, operating current data, float voltage data, and temperature data;
correspondingly, the data acquisition module 101 comprises a power supply unit, a voltage sensor, a current sensor, a floating charge voltage sensor and a temperature sensor; the power supply unit is used for providing working voltage for the voltage sensor, the current sensor float charge voltage sensor and the temperature sensor. The voltage sensor is used for collecting voltage data of each storage battery. The current sensor is used for collecting current data of each storage battery. The float voltage sensor is used for acquiring float voltage data of each storage battery. The temperature sensor is used for collecting the temperature data of each storage battery.
Because the storage battery pack is a standby power supply of the electric power direct current system, under the condition that the commercial power is normal, the charging device connected with the direct current bus supplies power to a conventional load and also supplies constant float charging voltage and constant float charging current to the storage battery pack, so that the natural discharging process of the storage battery pack is counteracted. Therefore, a float voltage sensor is provided in the data acquisition module 101 to acquire float voltage data of each battery in the battery pack. Meanwhile, the performance of the storage battery pack is affected by overhigh or overlow ambient temperature, so that a temperature sensor is further arranged in the data acquisition module 101, and the temperature data of each storage battery is acquired through the temperature sensor. The data acquisition module 101 is further provided with a voltage sensor and a current sensor, which are respectively used for acquiring working voltage data and working current data of each storage battery. In order to ensure the normal operation of the data acquisition module 101, a power supply unit is arranged in the data acquisition module 101, the power supply unit is used for providing working voltage for a voltage sensor, a current sensor, a float charge voltage sensor and a temperature sensor, the type of the power supply unit can be set according to actual needs, and the power supply unit can be a solar power supply unit.
And 203, extracting characteristic parameters from the state data and the nuclear capacity discharge test data, inputting the characteristic parameters into a performance analysis model to obtain a performance analysis result of each storage battery, and visually displaying the performance analysis result.
In this embodiment, after the state data and the nuclear capacity discharge test data are acquired, the characteristic parameters are extracted from the state data and the nuclear capacity discharge test data, the characteristic parameters are input into a pre-trained performance analysis model, the performance analysis module analyzes and learns the characteristic parameters to obtain a performance analysis result of the storage battery pack, and then the performance analysis result is visually displayed.
In one embodiment, the characteristic parameters include a first dispersion variable of each storage battery relative to the float voltage of the storage battery, a second dispersion variable of each storage battery relative to the float voltage of the storage battery, an internal resistance variation, an equalizing charge characteristic parameter, a discharge characteristic parameter, an operating voltage characteristic parameter, an operating current characteristic parameter and a temperature characteristic parameter.
In this embodiment, the criterion for determining the battery performance mainly includes the following points:
along with the deterioration of the battery performance, the first dispersion variable of the float charging voltage of each storage battery relative to the storage battery is gradually increased;
along with the deterioration of the battery performance, the second dispersion variable of each storage battery relative to the float charging voltage of the storage battery pack is gradually increased;
along with the deterioration of the battery performance, the internal resistance of each storage battery becomes large;
along with the deterioration of the battery performance, the difference of the charge-discharge curve voltage of each storage battery is gradually increased relative to the values of other storage batteries of the battery pack;
with the deterioration of the battery performance, the operating voltage and the operating current of each secondary battery are gradually decreased.
When the temperature is too high or too low, deterioration of battery performance occurs.
According to the judgment basis of the battery performance, in this embodiment, a first dispersion variable of each storage battery relative to the float voltage of the storage battery, a second dispersion variable of each storage battery relative to the float voltage of the storage battery pack, an internal resistance variation, an average charging characteristic parameter, a discharging characteristic parameter, a working voltage characteristic parameter, a working current characteristic parameter and a temperature characteristic parameter are used as characteristic parameters, and after state data and nuclear capacity discharging test data are obtained, the characteristic parameters need to be extracted from the state data and the nuclear capacity discharging test data, so that the performance of the storage battery is analyzed.
In the embodiment, the floating charge voltage data is calculated by using a theory of floating charge dispersion of storage batteries, so that a first dispersion variable of each storage battery relative to the floating charge voltage of the storage battery and a second dispersion variable of each storage battery relative to the floating charge voltage of a storage battery pack are obtained, the internal resistance variation of each storage battery is calculated according to the internal resistance data of the storage batteries, the value of the difference between the average charge parameter of a single storage battery and the voltage of a charge-discharge curve relative to other storage batteries of the battery pack is calculated according to charge-discharge parameters, a working voltage curve and a working current curve are generated according to the working voltage data and the working current data, the voltage difference value between the working voltage curve and a standard working voltage curve is calculated to obtain a working voltage characteristic parameter, and the current difference value between the working current curve and the standard working current curve is calculated to obtain a working current characteristic parameter; and generating a temperature change curve according to the temperature data, and determining a temperature change rate and a temperature mean value according to the temperature change curve to obtain a temperature characteristic parameter.
In one embodiment, the specific process of inputting the characteristic parameters into the performance analysis model to obtain the performance analysis result of each storage battery is as follows:
inputting the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charging characteristic parameter, the discharging characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter into a performance analysis model, so that the performance analysis model can carry out deep learning on the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charging characteristic parameter and the discharging characteristic parameter to obtain a performance analysis result of each storage battery, and the performance analysis model is obtained by training a neural network model by using the historical characteristic parameters of each storage battery and the historical performance analysis result of each storage battery.
In one embodiment, the neural network model is a convolutional neural network model, and the process of training the convolutional neural network model is as follows: the method comprises the steps of obtaining historical state data and historical nuclear-capacitive discharge test data of storage batteries, extracting historical characteristic parameters from the historical state data and the historical nuclear-capacitive discharge test data, inputting the historical characteristic parameters and historical performance analysis results of each storage battery into a convolutional neural network model as training samples, training the convolutional neural network model by using a reverse error propagation method until the output error of the convolutional neural network model is smaller than an error threshold value, and obtaining the trained convolutional neural network model, namely a performance analysis model. And then, inputting the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charge characteristic parameter, the discharge characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter into a performance analysis model to obtain a performance analysis result of the storage battery.
In this embodiment, the performance analysis model has an adaptive learning function, and when the storage battery is subjected to a full-capacity or half-capacity check discharge test, the performance analysis model replaces the training samples and trains itself again to form a new performance analysis model. Meanwhile, for storage batteries of different models, the performance analysis model can replace training samples of corresponding storage batteries for training, so that the performance analysis model can analyze the performance of the storage batteries of different models, and the application range of the performance analysis model is expanded through self-adaptive learning.
On the basis of the above embodiment, the method further comprises the following steps: and storing the state data, the nuclear capacity discharge test data and the performance analysis result into a cloud storage module.
In one embodiment, the storage battery performance analysis platform further comprises a cloud storage module, the cloud storage module is used for storing the state data, the nuclear capacity discharge test data and the performance analysis result, a worker can call the state data, the nuclear capacity discharge test data and the performance analysis result from the cloud storage module at any time as needed, and even if local data is lost, the data can be recovered from the cloud storage module at any time, so that the data security is ensured. In one embodiment, the cloud storage module encrypts and stores the state data, the nuclear capacity discharge test data and the performance analysis result, and a worker can read data from the cloud storage module only by inputting a correct password, so that the safety of the data is further improved.
On the basis of the above embodiment, the method further comprises the following steps:
and sending a sulfur removal instruction to the online sulfur removal module so that the online sulfur removal module performs sulfur removal operation on the storage battery pack.
In one embodiment, the system further comprises an online sulfur removal module, wherein the online sulfur removal module is used for receiving a sulfur removal instruction sent by the background analysis module 103 and performing sulfur removal operation on the storage battery pack according to the sulfur removal instruction; correspondingly, the background analysis module 103 is further configured to: and sending a sulfur removal instruction to the online sulfur removal module.
Because the storage battery pack is a standby power supply, the storage battery pack is usually only in a floating charge state and is rarely used, and the storage battery pack is scrapped too early because the storage battery pack is vulcanized more and more seriously over time. Therefore, the sulfur removal operation needs to be carried out on the storage battery pack, the vulcanization phenomenon of the storage battery pack is removed, and the service life of the storage battery is prolonged. In this embodiment, when online desulfurization is required, the background analysis module sends a desulfurization instruction to the online desulfurization module, and after receiving the desulfurization instruction, the online desulfurization module performs desulfurization operation on the storage battery pack according to the desulfurization instruction. It can be understood that, in this embodiment, the sending mode of the sulfur removal command may be sent by the background analysis module under manual control, or may be sent automatically by the background analysis module.
In the embodiment of the invention, the background analysis module is arranged to control the nuclear capacity discharge module to perform the nuclear capacity discharge operation on the storage battery, the state data of the storage battery is acquired from the data acquisition module, the nuclear capacity discharge test data is acquired from the nuclear capacity discharge module, the characteristic parameters extracted from the state data and the nuclear capacity discharge test data are input into the performance analysis model to be analyzed, the performance analysis result of each section of storage battery is obtained, the performance analysis of the storage battery is automatically completed by the storage battery performance analysis platform, the storage battery does not need to be subjected to the nuclear fixed discharge test on the storage battery manually at the installation site of the storage battery in the process, the labor cost and the time cost are saved, and the analysis efficiency of the storage battery performance is improved.
It should be noted that the foregoing is only a preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will appreciate that the embodiments of the present invention are not limited to the specific embodiments described herein, and that various obvious changes, adaptations, and substitutions are possible, without departing from the scope of the embodiments of the present invention. Therefore, although the embodiments of the present invention have been described in more detail through the above embodiments, the embodiments of the present invention are not limited to the above embodiments, and many other equivalent embodiments may be included without departing from the concept of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A storage battery performance analysis platform, comprising:
the data acquisition module is used for continuously acquiring the state data of each storage battery in the storage battery pack;
the nuclear capacity discharge module is used for receiving a control instruction sent by the background analysis module, performing a nuclear capacity discharge test on the storage battery pack according to the control instruction, and collecting nuclear capacity discharge test data of each storage battery in the process of performing the nuclear capacity discharge test;
the background analysis module is used for sending a control command to the nuclear capacitor discharge module, acquiring the state data and the nuclear capacitor discharge test data, extracting characteristic parameters from the state data and the nuclear capacitor discharge test data, inputting the characteristic parameters into a performance analysis model, obtaining a performance analysis result of each storage battery, and visually displaying the performance analysis result.
2. The storage battery performance analysis platform according to claim 1, further comprising an online sulfur removal module, wherein the online sulfur removal module is configured to receive a sulfur removal instruction sent by the background analysis module, and perform a sulfur removal operation on the storage battery according to the sulfur removal instruction;
correspondingly, the background analysis module is further configured to:
and sending the sulfur removal instruction to the online sulfur removal module.
3. The battery pack performance analysis platform of claim 1, wherein the status data comprises operating voltage data, operating current data, float voltage data, and temperature data;
correspondingly, the data acquisition module comprises a power supply unit, a voltage sensor, a current sensor, a floating charge voltage sensor and a temperature sensor;
the voltage sensor is used for acquiring voltage data of each storage battery;
the current sensor is used for acquiring current data of each storage battery;
the float charge voltage sensor is used for acquiring float charge voltage data of each storage battery;
the temperature sensor is used for acquiring temperature data of each storage battery;
the power supply unit is used for providing working voltages for the voltage sensor, the current sensor, the float charge voltage sensor and the temperature sensor.
4. The storage battery performance analysis platform according to claim 3, wherein the nuclear capacity discharge module comprises a test data acquisition unit, a processor unit, a discharge unit and a charging unit;
the test data acquisition unit is used for acquiring the nuclear capacity discharge test data of each storage battery in the nuclear capacity discharge test process of the storage battery pack;
the processor unit is used for receiving the control instruction and controlling the discharging unit and the charging unit according to the control instruction;
the discharge unit is used for carrying out nuclear capacity discharge operation on the storage battery pack;
the charging unit is used for carrying out the core-capacity charging operation on the storage battery pack.
5. The storage battery performance analysis platform according to claim 4, further comprising a cloud storage module, wherein the cloud storage module is configured to store the status data, the nuclear capacity discharge test data, and the performance analysis result.
6. A storage battery performance analysis method is characterized by comprising the following steps:
sending a control instruction to a nuclear capacity discharge module to enable the nuclear capacity discharge module to perform a nuclear capacity discharge test on a storage battery pack, and acquiring nuclear capacity discharge test data of each storage battery, which is acquired by the nuclear capacity discharge module in the process of performing the nuclear capacity discharge test on the storage battery pack;
acquiring state data of each storage battery in the storage battery pack continuously acquired by a data acquisition module;
extracting characteristic parameters from the state data and the nuclear capacity discharge test data, inputting the characteristic parameters into a performance analysis model to obtain a performance analysis result of each storage battery, and visually displaying the performance analysis result.
7. The battery pack performance analysis method according to claim 6, further comprising the steps of:
and storing the state data, the nuclear capacity discharge test data and the performance analysis result to a cloud storage module.
8. The storage battery pack performance analysis method according to claim 6, wherein the nuclear capacity discharge test data comprises storage battery internal resistance data and charge-discharge parameters.
9. The method according to claim 8, wherein the characteristic parameters include a first dispersion variable of each battery with respect to its float voltage, a second dispersion variable of each battery with respect to the battery float voltage, an internal resistance variation, an equalizing charge characteristic parameter, a discharge characteristic parameter, an operating voltage characteristic parameter, an operating current characteristic parameter, and a temperature characteristic parameter.
10. The storage battery pack performance analysis method according to claim 9, wherein the specific process of inputting the characteristic parameters into the performance analysis model to obtain the performance analysis result of each storage battery is as follows:
inputting the first dispersion variable, the second dispersion variable, the internal resistance variation, the equalizing charge characteristic parameter, the discharge characteristic parameter, the operating voltage characteristic parameter, the operating current characteristic parameter, and the temperature characteristic parameter into a performance analysis model, so that the performance analysis model can carry out deep learning on the first dispersion variable, the second dispersion variable, the internal resistance variation, the uniform charge characteristic parameter, the discharge characteristic parameter, the working voltage characteristic parameter, the working current characteristic parameter and the temperature characteristic parameter to obtain the performance analysis result of each storage battery, and the performance analysis model is obtained by training a neural network model by adopting the historical characteristic parameters of each storage battery and the historical performance analysis result of each storage battery.
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