CN115980608A - Storage battery pack nuclear-capacity discharge centralized control system - Google Patents
Storage battery pack nuclear-capacity discharge centralized control system Download PDFInfo
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Abstract
The invention belongs to the technical field of power systems, in particular to a storage battery pack nuclear capacity discharge centralized control system, which comprises a server for operating the storage battery pack nuclear capacity discharge centralized control system and further comprises: the remote control module is used for initiating a storage battery pack nuclear capacity discharge experiment; the parameter setting module is used for setting various parameters of the storage battery pack and storing the parameters in the server; the measurement and collection module is used for measuring and collecting various performance parameters of the storage battery pack when the storage battery pack performs nuclear capacity discharge; the comparison and estimation module is used for estimating the service life of the storage battery pack according to the data measured and collected in the measurement and collection module and in combination with the data in the parameter setting module.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a storage battery pack nuclear capacity discharge centralized control system.
Background
With the rapid development of communication technology and power electronic technology, batteries are widely used as a reliable direct current power supply in power systems, communication systems, transportation systems, emergency lighting and other places. If the storage battery pack of the direct current system fails to provide direct current electric energy normally after the alternating current of the transformer substation loses power, the storage battery pack of the direct current system can not provide direct current electric energy normally, so that equipment of the whole transformer substation stops working, and the secondary system of the transformer substation is broken down.
At present, in order to find detailed performance data of a storage battery pack in an operation process, a centralized monitoring system is generally adopted, a centralized monitoring unit in a direct current system of a transformer substation at the present stage cannot comprehensively monitor the detailed performance data of the storage battery pack in the operation process, particularly when a storage battery is in an emergency state to cause a functional fault, the centralized monitoring unit cannot prompt the operation state of the storage battery in time, only when the storage battery is in an inferior state for a long time, an alarm is given to prompt a dispatching center, but a larger accident is caused, the storage battery pack which is just installed in the direct current system of the transformer substation is definitely required to be subjected to a checking discharge test according to 13.1.2 which is the latest eighteen anti-accident measure issued by a national power grid company, and the storage battery pack can be put into operation only under the condition that the quality of the storage battery pack does not have any problem. And in the previous six years, a discharge test needs to be carried out on the storage battery pack every two years to ensure the quality of the storage battery, the storage battery pack is continuously put into use in a transformer substation for six years, and a check discharge test needs to be carried out every other one year.
When the storage battery pack in the substation performs checking discharge work, a 10-hour checking discharge mode is usually adopted, that is, a person on duty performing discharge maintenance work needs to continuously work for at least 10 hours. Once the working time is too long, the operator on duty is likely to be tired for a long time, and misoperation is likely to be caused. Generally, at least 2 people are needed for discharging one group of storage batteries, 4 people are needed for two groups of storage batteries, the work is started from 8 am, the relevant preparation work before the test such as safety measures is done needs 1 hour, the discharging is started at 9 am, if the storage batteries are discharged according to the rate of 10 hours, the discharging is finished at 7 pm, the equipment is disassembled and assembled, and the discharging of the storage batteries is finished at 8 am. And at this time, the battery pack cannot leave the substation because the battery pack needs to be charged after being discharged. Only when the charging of the storage battery is basically completed, the field can be recovered, the substation is evacuated, and the process also needs hours. According to the maintenance regulation, the storage battery pack with the capacity unqualified due to the initial discharge needs 2 discharge tests to finally determine the capacity of the storage battery. Therefore, the discharge maintenance test of a group of storage battery packs can be completed only in 1 working day and 3 working days, and manpower and material resources are seriously wasted.
In recent years, with the acceleration of the construction pace of power stations, the number of the power stations is increased in a geometric manner, and with the increase of the number, the workload of the nuclear capacity discharge test of the storage battery every year is increased, the nuclear capacity discharge test needs professional personnel to carry discharge equipment to the site for operation, and accidents can be caused by carelessness in the operation process.
In recent years, direct current system storage battery remote online monitoring systems are developed at home and abroad, such as alber in the United states and powerton in Korea, which are developed rapidly and mature in technology. The online detection only tests the internal resistance, and the method is single, the online content discharge test cannot be carried out, and the operation interface is foreign language, so the use is inconvenient; and meanwhile, only the internal resistance is tested, but the actual capacity condition of the storage battery pack in the whole direct current system cannot be judged.
At present, the function of an on-line monitoring device of a storage battery pack researched domestically is relatively simple, the monitoring of the voltage, the internal resistance, the current and the like of the storage battery pack is only realized, some manufacturers can also realize the function of containing electric power in a line core, mainly resistance and insufficient discharge, and the realization of remote on-line centralized control management in a certain area does not involve, and simultaneously does not involve the technology of estimating the service life of the storage battery pack.
Disclosure of Invention
In order to make up for the defects of the prior art, in order to solve the problem that an online monitoring device of a storage battery pack is relatively simple in function, only monitors the voltage, the internal resistance, the current and the like of the storage battery pack, but does not relate to remote online centralized control management in a certain area, and simultaneously does not relate to the technology of estimating the service life of the storage battery pack, the invention provides a storage battery pack nuclear capacity discharge centralized control system.
The technical scheme adopted by the invention for solving the technical problems is as follows: the storage battery nuclear capacity discharge centralized control system comprises a server for operating the storage battery nuclear capacity discharge centralized control system, and further comprises:
the remote control module is used for initiating a storage battery pack nuclear capacity discharge experiment;
the parameter setting module is used for setting various parameters of the storage battery pack and storing the parameters in the server;
the measurement and collection module is used for measuring and collecting various performance parameters of the storage battery pack when the storage battery pack performs nuclear capacity discharge;
and the comparison and estimation module is used for estimating the service life of the storage battery pack according to the data measured and collected in the measurement and collection module and by combining the data in the parameter setting module.
Optionally, the server is divided into a main server and a sub-server, and the main server and the sub-server are connected via the internet.
Optionally, the master server and the sub-servers may operate a storage battery pack core-capacitor discharge centralized control system.
Optionally, the method further comprises the step of sending data during the capacity discharge of the storage battery pack to a centralized component and a communication component in a remote control module, wherein the centralized component is controlled by the remote control module.
Optionally, the remote control module issues a start command to the central component when the control core capacitance discharge starts, and issues a stop command to the central component when the core capacitance discharge meets the stop condition.
Optionally, the concentration component is a LoRa module.
Optionally, the communication module is connected between the remote control module and the centralized module, the communication module is a network connection device, and the communication module is in communication connection with the centralized module.
Optionally, the centralized component transmits the parameters of the storage battery pack measured and collected by the measurement and collection module to the server through the communication component.
Optionally, the battery pack further comprises a switching component, and the switching component switches the discharge state of the battery pack under the control of an instruction sent by the remote control module.
Optionally, the measurement collection module includes a total measurement component and a sub-measurement component.
Optionally, the total measurement component is used for measuring the real-time total voltage and the total current of the storage battery pack.
Optionally, the total measurement component is a current and voltage monitor.
Optionally, the sub-measurement assemblies correspond to the single storage batteries in the storage battery pack one by one, and are used for measuring real-time parameters of the single storage batteries, wherein the real-time parameters include a single temperature, a single voltage and a single resistance.
Optionally, the comparison estimation module estimates the service life of the storage battery pack by using a BP neural network method.
Optionally, the comparison and estimation module further includes a record comparison module, which is used for recording and comparing the obtained real-time parameters of the storage battery pack.
Optionally, the device further comprises a safety module, and the safety module is used for improving the accuracy of the nuclear capacity discharge experiment.
Optionally, the security module includes a face recognition component, a fingerprint recognition component, and a monitoring component.
Optionally, the face recognition component is a face recognition camera or a face recognizer.
Optionally, the fingerprint identification component is a fingerprint identifier.
Optionally, the monitoring component is a monitoring camera and a mobile terminal, the mobile terminal and the monitoring camera establish a communication connection through the internet, and the mobile terminal can remotely operate the remote control module.
Has the advantages that:
1. the storage battery pack nuclear capacity discharge centralized control system can detect the actual capacity of the storage battery pack, and meanwhile, the health service life state of the storage battery pack is predicted by monitoring the parameters of the floating charge state of the storage battery pack, so that the service life of the storage battery is prolonged, and manpower and material resources during manual nuclear capacity discharge are released.
2. According to the storage battery pack nuclear-capacity discharge centralized control system, due to the arrangement of the safety module, the situation that workers without operation qualification execute the storage battery pack nuclear-capacity discharge experiment to cause inaccurate experiment results, if the situation that the operation of the workers is not standard or the workers are replaced by workers without operation qualification in the experiment process is found in the storage battery pack nuclear-capacity discharge experiment process, a general responsible person can operate the mobile terminal to control the remote control module and stop the storage battery pack nuclear-capacity discharge experiment, and therefore the accuracy of the storage battery pack nuclear-capacity discharge experiment is guaranteed.
Drawings
The invention will be further explained with reference to the drawings.
FIG. 1 is a schematic diagram of a metro-level site structure;
FIG. 2 is a schematic diagram of a provincial site structure;
FIG. 3 is a diagram of a partial operation page of the centralized control system according to the present invention;
FIGS. 4-11 are photographs of the nuclear capacity discharge experiment performed according to the present invention;
FIG. 12 is a sample graph of data experimentally determined for the present invention;
FIG. 13 is a graph of training results (trainscg function);
fig. 14 is a graph of training results (traincgp function);
fig. 15 is a graph of training results (traingdx function);
fig. 16 is a graph of training results (traincgf function);
FIG. 17 is a graph comparing the performance of algorithms under different training functions;
fig. 18 is SOC values of the battery in a float state at different temperatures;
FIG. 19 is a graph of SOC versus temperature;
FIG. 20 is a diagram showing the result of temperature correction of the predicted SOC value of the BP network;
FIG. 21 is a graph of battery state of health versus SOH;
FIG. 22 is a graph showing the estimation of SOH values;
fig. 23 is a comparison graph of the predicted value and the actual value of the storage battery SOH by the BP neural network.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
As shown in fig. 1 to 11, the storage battery nuclear-capacity discharge centralized control system includes a server for operating the storage battery nuclear-capacity discharge centralized control system, where the server includes a main server and a sub-server, both the main server and the sub-server can operate the storage battery nuclear-capacity discharge centralized control system, a display end of the storage battery nuclear-capacity discharge centralized control system is a computer display screen, and the storage battery nuclear-capacity discharge centralized control system can be displayed on the computer display screen in a network connection or APP manner, and certainly, can also be displayed in other forms;
for the server including the main server and sub servers, as shown in 1-2, the sub servers are local-level servers, and can operate the storage battery pack nuclear-capacity discharge centralized control system alone to perform the storage battery pack nuclear-capacity discharge experiment, the main server is a provincial-level server, and can operate the storage battery pack nuclear-capacity discharge centralized control system to perform all local-level in provinces, or several local-level servers therein to perform the storage battery pack nuclear-capacity discharge experiment.
Based on the above description, when the storage battery pack nuclear capacity discharge centralized control system is operated, firstly, a nuclear capacity discharge instruction is issued through the remote control module, so that the centralized component is triggered through the communication component, the centralized component triggers the switching component, and a discharge object of the storage battery pack is switched to a discharge box or other discharge devices;
it should be noted that the communication component is a network connection device, such as a repeater or a switch, and only needs to implement the communication connection between the remote control module and the centralized component;
wherein, the centralized component is a LoRa module, which is collocated with an operating system, of course, other communication modules can be used, as shown in fig. 3; the remote control module is used for receiving an instruction issued by the remote control module;
further, the switching component is an automatic switch so as to change the discharge state of the storage battery pack, and the switching component is in communication connection with the concentration component through a network.
Then, in the process of the nuclear capacity discharge of the storage battery pack, the measurement and collection module is involved, real-time parameters of the storage battery pack are transmitted to the server by using the concentration component and the communication component, and the parameters of the storage battery pack measured and collected by the measurement and collection module are displayed through the display screen;
it should be noted that, the measurement collection module includes a total measurement component and a sub-measurement component, the total measurement component is a power voltage monitor, and the purpose is to measure the real-time total voltage and total current of the storage battery pack, and the real-time total voltage and total current monitoring interval period can be freely selected, such as once every 2h or once every 1h, and the real-time total voltage and total current of the storage battery pack are transmitted to the server, preferably once every 1 h;
the sub-measurement component corresponds to each single storage battery in the storage battery pack one by one and is used for measuring real-time parameters of the single storage batteries, and the real-time parameters comprise the single temperature, the single voltage and the single resistance of the single storage batteries;
further, as above, the interval period of the real-time parameter measurement of the single storage battery can be freely selected, such as once every 2h or once every 1h, and the present invention preferably once every 1 h;
then, after the server receives the real-time parameters measured by the total measurement component and the sub-measurement components, the server compares the record comparison component in the estimation module, sums the real-time parameters into a table, and compares the table with the parameters set in the parameter setting module, so as to judge the service life condition of the storage battery pack and the single storage battery, and further complete the storage battery pack nuclear capacity discharge experiment;
it should be noted that the parameters set in the parameter setting module include total voltage and total current preset by the storage battery pack, and preset cell temperature, cell voltage, and cell resistance of the cell storage battery, and may be set according to the capacity, volume, or power of the storage battery, which is not specifically limited herein.
Then, during intervention work of the comparison estimation module, estimating the service life of the storage battery by using a BP neural network method, which comprises the following steps:
because the capacity of the storage battery is influenced by various factors such as open-circuit voltage, working current, temperature and the like in the working process, the electrical performance parameters and the SOC value corresponding to the electrical performance parameters are acquired in real time in the discharging process of the storage battery pack, the trained BP network is utilized to predict the residual capacity of the storage battery,
the invention adopts the storage battery with the specification of 12V/40AH to carry out experimental data, the storage battery is fully charged at the constant temperature of 25 ℃, 3 groups of different discharge multiplying factors (2A, 4A and 8A) are set, and the constant current discharge is respectively started, at the moment, the residual capacity of the storage battery is continuously reduced, and the terminal voltage of the storage battery is gradually reduced. Part of the sample data measured by the experimental method is shown in fig. 12:
in the discharging process, real-time data acquisition is carried out on the discharging time t and the terminal voltage during discharging, and data corresponding to current, voltage and discharging time one to one can be obtained according to the acquired data. The electric quantity released in the discharging process of the storage battery can be obtained by calculating in an integral mode of discharging current to discharging time, and the residual capacity at the moment can be obtained by calculating a difference value with the initial capacity of the storage battery. For example, a battery with a specification of 12V/40AH is discharged at a constant current of 2A for 2 hours, and the discharged capacity is 4AH, and at this time, the remaining capacity of the battery is 36AH, whereby an SOC of 90% can be obtained.
When the BP network is used for estimating the residual capacity of the storage battery, firstly, the acquired storage battery data is processed, because each input data in the network often has different physical meanings and different dimensions, in order to enable the network training to give each input the same important position at the beginning, normalization processing needs to be performed on the input data, so that all input components are changed between an interval [0,1], the BP network generally adopts a maximum and minimum method to perform transformation processing on the input data, and the transformation formula is shown as follows:
wherein X i Representing actual data, X min Represents the minimum value of the data variation range, X max Representing the maximum value of the range of variation of the data.
When the residual capacity of the storage battery is estimated, a BP network with a three-layer structure is constructed, the network takes the discharge current and the discharge voltage selected by the storage battery in the discharge process as input variables, and the state of charge (SOC) of the storage battery as a final output result. Therefore, the number of the network input layer neuron and the number of the network output layer neuron are respectively 2 and 1. The transfer function of the hidden layer is tansig and the transfer function of the output layer is purelin. In the process of constructing the BP neural network, the selection of the number of the hidden layer nodes can directly influence the performance of the neural network. If the number of hidden nodes is too small, the training performance of the network cannot be guaranteed, and errors can occur in the learning process; if the number of hidden nodes is too large, the training time of the network is too long, and the prediction speed of the network is reduced. The number of neurons in the hidden layer is usually determined using empirical formulas. The formula is as follows:
in the formula, L is the number of hidden layer nodes; m is the number of input nodes; n is the number of output nodes; a is a tuning constant between 1 and 10.
Before the BP network is applied to predict the capacity of the storage battery, a series of early preparation work needs to be done. Because the number of neurons in each layer in the network is large and the algorithm structure is complex, proper learning efficiency and enough training times must be selected before network training.
In the application process of the BP network, different training algorithms have different performances, in order to guarantee the precision of the service life prediction result of the storage battery, the project compares several commonly used BP network algorithms, and an algorithm scheme with the optimal performance is selected after comprehensive consideration. Setting the maximum training times to be 5000; the number of hidden layer neurons is 10; the maximum error index is 0.00065; the learning rate is 0.035; other parameters are set to default values. The training results are shown in FIGS. 13-16:
as can be seen from the above diagram, for the estimation of the remaining capacity of the storage battery, different training functions are used, and the training results thereof also have deviation, specifically, as shown in fig. 17, BP algorithm performance comparison diagrams under different training functions;
by analyzing various parameters in the table, compared with other improved BP algorithms, the training function selected as the traincgf can enable the network to obtain a training result with higher precision in shorter training time, the traincgf occupies the minimum storage space, and the training function is finally selected as a Fletcher-Reeves conjugate gradient method, namely the traincgf function, because the estimated residual capacity of the storage battery is large in the number of connection weights in the network.
It can be known from the operating characteristics of the storage battery that there is a certain relationship between the capacity of the storage battery and the ambient temperature, and when the ambient temperature is low, the utilization rate of the active material inside the storage battery will be reduced, and therefore the capacity of the storage battery will be reduced. On the contrary, when the ambient temperature is gradually increased, the movement rate of the free ions in the electrolyte is increased while participating in the reaction, and the capacity of the battery is increased. Placing the storage battery in different temperature environments for short-time constant current discharge, so as to obtain the correspondence between the SOC value of the storage battery estimated by the BP network and different temperatures, specifically as shown in FIG. 18, the SOC values of the storage battery at different temperatures in a floating charge state;
as can be seen from the table, the capacity of the battery is certainly susceptible to the temperature, and a curve of the change of the SOC with the temperature is shown in fig. 19;
during the operation of the storage battery, the temperature factors have great randomness, which may be caused by improper storage battery placing environment or heat generated by electrochemical reaction inside the storage battery. Since the temperature has a large influence on the remaining capacity of the battery, in order to improve the accuracy of estimating the SOC value by the system, a temperature compensation method must be used to reduce the influence of the temperature. In practical applications, the relationship between the capacity and the temperature of the battery is generally expressed by the following formula:
wherein: t is t 1 And t 2 Two different temperatures are indicated; c t1 Represents t 1 Capacity of the battery at temperature; c t2 Represents t 2 Capacity of the battery at temperature; k is a temperature coefficient.
During the correction, the standard temperature t is generally taken 1 =25 ℃ as reference temperature, t 2 The measured temperature is obtained, and when the working temperature is different from the reference temperature, the SOC value predicted by the BP network can be subjected to temperature correction by using the formula.
With f (x) i And b) representing a relation between temperature and SOC, and taking the regression coefficient k as a vector return value b, x i (i =1 … N) represents a 2 × N array of both temperature and SOC, and the weighted final two-power equation for vectorization minimization at the regression coefficient b can be expressed as:
when the weight of the nonlinear regression coefficient meets the requirement, the standard deviation value can be calculated, and the standard deviation calculation function can be expressed as
The value of b can be solved by solving the curve through a nonlinear fitting method, and at the moment, b is the temperature coefficient k of the correction capacity.
The result of temperature correction of the SOC value predicted by the BP network is shown in fig. 20;
in the actual use process of the storage battery pack, the storage battery pack is formed by connecting single storage batteries in series, so that the health condition of each storage battery can influence the normal work of the storage battery pack, and the operation condition of each storage battery is very important to grasp in time. From the foregoing, it can be known that, for the evaluation of the health condition of the storage battery, the SOH value of the storage battery is generally used as an index for judging whether the storage battery can be put into use, the SOH value reflects the maximum charge capacity of the storage battery, for a new storage battery which is just delivered from a factory, the SOH value should be equal to or greater than 100%, and then the SOH value gradually decreases with the long-term use of the storage battery, which is that the actual capacity of the storage battery is irreversibly reduced due to the gradual aging of the storage battery. When the SOH value of the battery drops to 80% according to the industry standard, the battery cannot be put into service and should be replaced as shown in fig. 21.
Therefore, it is necessary to estimate the SOH value of the battery as a criterion for evaluating the state of health, and the estimation of the SOH value of the battery is substantially the estimation of the maximum charge capacity of the battery. The system realizes the estimation of the residual capacity of the storage battery and carries out temperature compensation on the estimated SOC value of the storage battery, so that when the SOH value of the storage battery is estimated, the storage battery in a floating charging state is only required to carry out short-time constant current discharge with 1A current. From the discharge start time t s Start integrating the discharge current until the discharge termination time t e The value of the integrated electric quantity during discharge is marked as C se At the discharge end time t e The corresponding SOC value can be estimated by the BP network algorithm described above, and temperature correction is performed, so that the SOH value of the battery can be calculated by the following formula:
constant current discharging is performed on a section of storage battery in a floating charge state by using 1A current, data of 20 time points in the discharging process are collected as test data, SOH values of the data at different moments are estimated through the formula, and the estimation result is shown in FIG. 22:
FIG. 23 (left) is a graph comparing the predicted value and the actual value of SOH of the storage battery based on the BP neural network, and an absolute error graph and a relative error graph (right) of the predicted value of SOH can be respectively made according to the graph. The health condition of the storage battery is influenced by various complex factors, and the method for evaluating the health of the storage battery based on the BP network can enable a user to timely master the current health condition of the storage battery, and once the predicted SOH value is lower than 80%, the comparison and estimation module sends out early warning information to recommend timely maintenance of the storage battery;
and finally, after the service life of the storage battery pack is estimated by the comparison estimation module, the remote control module issues a stop instruction to the centralized component, and the centralized component instructs the switching component to switch the discharging object of the storage battery pack into a direct current bus so as to complete the nuclear capacity discharging experiment of the storage battery pack.
It should be further explained that, before the storage battery pack nuclear capacity discharge experiment is performed, the safety module intervenes, and the specific operation mode is that, before a worker operates the storage battery pack nuclear capacity discharge centralized control system and executes the storage battery pack nuclear capacity discharge experiment, a human face and a fingerprint need to be entered at first, so that the situation that the worker who does not have operation qualification executes the storage battery pack nuclear capacity discharge experiment to cause inaccurate experiment results is avoided, and the human face and the fingerprint of the worker can be entered in advance and stored in the server;
then, in the process that a worker operates the storage battery pack nuclear capacity discharge centralized control system to perform the storage battery pack nuclear capacity discharge experiment, the monitoring camera monitors the whole experiment process, the monitoring camera is located in an operation machine room, the mobile terminal and the monitoring camera establish communication connection through the internet, the mobile terminal is a mobile phone or other equipment capable of performing mobile communication, the mobile terminal is held by a person responsible for the storage battery pack nuclear capacity discharge centralized control system and can observe the process of the storage battery pack nuclear capacity discharge experiment in real time, if the situation that the operation of the worker is not standard or the worker is replaced by the worker without operation qualification (the worker without operation qualification refers to face data which does not exist in a server) in the experiment process of the storage battery pack nuclear capacity discharge experiment is found, the person responsible for the worker can operate the mobile terminal to control the remote control module to stop the storage battery pack nuclear capacity discharge experiment, and therefore the accuracy of the storage battery pack nuclear capacity discharge experiment is guaranteed.
Further, after developing the centralized control system for the nuclear capacity discharge of the battery pack, as shown in fig. 4-11 and tables 1-2, we have performed the following experiments using the centralized control system:
test samples: storage battery nuclear capacity discharge centralized control system
Technical documentation (code, name) on which the test is based:
JJG780-92 AC digital power meter calibration procedure;
a JJG440-86 power frequency single-phase meter calibration procedure;
DL/T980-2005 digital multimeter verification protocol;
checking a JJG603-2006 frequency table;
ordering technical conditions of the DL/T459 power system direct-current power supply cabinet;
the operation and maintenance technical rules of the storage battery direct-current power supply device for the DL/T724 electric power system; a DL/T856 DC power supply monitoring device;
and (3) testing environment: temperature 17 ℃, relative humidity: 58 percent.
Table 1 shows the discharge addresses of the storage battery pack nuclear capacity discharge experiment reports:test workshopDate:22.5.17ambient temperature:17 ℃
TABLE 2 is a voltmeter for single battery with nuclear capacity discharge
According to the experiment, the storage battery pack nuclear capacity discharge centralized control system researched and designed by the invention can be used for detecting the actual capacity of the storage battery pack, and predicting the health service life state of the storage battery pack by monitoring the parameters of the floating charge state of the storage battery pack, so that the service life of the storage battery is prolonged, and manpower and material resources during manual nuclear capacity discharge are released.
Claims (20)
1. The storage battery pack nuclear-capacitance discharge centralized control system comprises a server for operating the storage battery pack nuclear-capacitance discharge centralized control system, and is characterized by further comprising:
the remote control module is used for initiating a storage battery pack nuclear capacity discharge experiment;
the parameter setting module is used for setting various parameters of the storage battery pack and storing the parameters in the server;
the measurement and collection module is used for measuring and collecting various performance parameters of the storage battery pack when the storage battery pack performs nuclear capacity discharge;
and the comparison and estimation module is used for estimating the service life of the storage battery pack according to the data measured and collected in the measurement and collection module and by combining the data in the parameter setting module.
2. The centralized control system for battery pack nuclear capacity discharge according to claim 1, wherein the servers are divided into a main server and a sub-server, and the main server and the sub-server are connected through the internet.
3. The storage battery pack nuclear capacity discharge centralized control system according to claim 2, wherein the master server and the sub-servers can operate the storage battery pack nuclear capacity discharge centralized control system.
4. The storage battery pack nuclear capacity discharge centralized control system according to claim 1, further comprising a centralized component and a communication component which send data when the storage battery pack nuclear capacity discharges to a remote control module, wherein the centralized component is controlled by the remote control module.
5. The centralized control system for the nuclear capacity discharge of the storage battery pack according to claim 4, wherein the remote control module issues a start command to the centralized component when the control of the nuclear capacity discharge is started, and issues a stop command to the centralized component when the nuclear capacity discharge meets a stop condition.
6. The storage battery pack nuclear capacity discharge centralized control system according to claim 5, wherein the centralized component is a LoRa module.
7. The centralized control system for battery pack nuclear capacity discharge according to claim 5, wherein the communication component is connected between the remote control module and the centralized component, the communication component is a network connection device, and the communication component is in communication connection with the centralized component.
8. The storage battery pack nuclear capacity discharge centralized control system according to claim 7, wherein the centralized component transmits the storage battery pack parameters measured and collected by the measurement and collection module to the server through the communication component.
9. The storage battery pack nuclear-capacity discharge centralized control system according to claim 1, further comprising a switching component, wherein the switching component is controlled by an instruction sent by the remote control module to switch the discharge state of the storage battery pack.
10. The battery pack nuclear capacity discharge centralized control system according to claim 8, wherein the measurement collection module comprises a total measurement component and a sub-measurement component.
11. The battery pack nuclear capacity discharge centralized control system according to claim 10, wherein the total measurement component is used for measuring the real-time total voltage and the total current of the battery pack.
12. The centralized control system of battery pack nuclear capacity discharge according to claim 11, wherein the total measurement component is a current-voltage monitor.
13. The centralized control system for storage battery pack nuclear capacity discharge according to claim 11, wherein the sub-measurement assemblies correspond to the individual storage batteries in the storage battery pack one by one to measure real-time parameters of the individual storage batteries, and the real-time parameters include individual temperature, individual voltage and individual resistance.
14. The storage battery pack nuclear capacity discharge centralized control system according to claim 1, wherein the comparison estimation module estimates the service life of the storage battery pack by adopting a BP neural network method.
15. The storage battery pack nuclear capacity discharge centralized control system according to claim 14, wherein the comparison estimation module further comprises a record comparison component for recording and comparing the obtained storage battery pack real-time parameters.
16. The storage battery pack nuclear capacity discharge centralized control system according to claim 1, further comprising a safety module, wherein the safety module is used for improving the accuracy of a nuclear capacity discharge experiment.
17. The battery pack capacity discharge centralized control system according to claim 16, wherein the security module comprises a face recognition component, a fingerprint recognition component and a monitoring component.
18. The storage battery pack nuclear capacity discharge centralized control system according to claim 17, wherein the face recognition component is a face recognition camera or a face recognizer.
19. The battery pack capacity discharge centralized control system according to claim 16, wherein the fingerprint identification component is a fingerprint identifier.
20. The storage battery pack nuclear capacity discharge centralized control system according to claim 16, wherein the monitoring components are a monitoring camera and a mobile terminal, the mobile terminal and the monitoring camera establish communication connection through the internet, and the mobile terminal can remotely operate the remote control module.
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| CN117129880A (en) * | 2023-10-26 | 2023-11-28 | 通号通信信息集团有限公司 | Method for estimating available capacity and health state of lead-acid storage battery |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117129880A (en) * | 2023-10-26 | 2023-11-28 | 通号通信信息集团有限公司 | Method for estimating available capacity and health state of lead-acid storage battery |
| CN117129880B (en) * | 2023-10-26 | 2024-02-09 | 通号通信信息集团有限公司 | Method for estimating available capacity and health state of lead-acid storage battery |
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