CN211785999U - Battery monitoring statistical system based on Internet of things - Google Patents
Battery monitoring statistical system based on Internet of things Download PDFInfo
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- CN211785999U CN211785999U CN201820663531.2U CN201820663531U CN211785999U CN 211785999 U CN211785999 U CN 211785999U CN 201820663531 U CN201820663531 U CN 201820663531U CN 211785999 U CN211785999 U CN 211785999U
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Abstract
The utility model provides a battery monitoring statistical system based on thing networking belongs to battery life management technical field. The method solves the problems of difficult battery monitoring, inaccurate battery use experimental data statistics and the like. The utility model comprises a server end and a monitored end which is in communication connection with the server end; the data acquisition module reads a voltage value of the battery and a time point corresponding to the voltage value to form a detection data signal; the data sending module receives a detection data signal; the data receiving module receives a detection data signal; the data temporary storage module receives and stores the detection data signal for reading; the data calculation module reads the detection data signal and calculates the detection data signal; the storage comparison module stores comparison data, receives the calculated data signal, compares the data signal with the comparison data, judges whether the fault occurs or not and counts the fault; the display module displays the statistical data or the fault reporting signal. The utility model has the advantages of the monitoring is simple, the statistics is accurate.
Description
Technical Field
The utility model belongs to the technical field of battery life management, a battery monitoring statistical system is related to, in particular to battery monitoring statistical system based on thing networking.
Background
A battery refers to a device that can convert chemical energy into electrical energy. The battery is used as an energy source, so that the design of stable voltage, stable current, long-time stable power supply, less limitation by external environment, low power consumption, convenient maintenance, stable and reliable performance and wide application in various aspects of modern social life can be obtained. In the normal working process of product, need make statistics of the service data of battery, different battery power consumption models can influence real life, often can the distortion through all kinds of acceleration test, so, the truest data derive from the statistics to the field data, but this kind of data statistics work load is very huge, though also have the statistical system to the battery among the prior art, the statistical mode is incomplete, and the statistics is limited. In addition, faults may occur in the use process of the battery, the fault data cannot be removed by the conventional statistical system, and errors exist in statistical results.
SUMMERY OF THE UTILITY MODEL
The utility model aims at providing a complete, accurate battery monitoring statistical system based on thing networking to the above-mentioned problem that exists among the prior art.
The purpose of the utility model can be realized by the following technical proposal: a battery monitoring and counting system based on the Internet of things is characterized by comprising a server end and a monitored end in communication connection with the server end;
the monitored end comprises a battery, a data acquisition module and a data sending module;
the server side comprises a data receiving module, a data temporary storage module, a data calculation module, a storage comparison module, a statistic module, an error reporting module and a display module;
the data acquisition module is used for reading the voltage value of the battery and the time point corresponding to the voltage value, forming a detection data signal and sending the detection data signal to the data sending module;
the data sending module is used for receiving the detection data signal and forwarding the detection data signal to the data receiving module;
the data receiving module is used for receiving the detection data signal and forwarding the detection data signal to the data temporary storage module;
the data temporary storage module is used for receiving, storing and reading the detection data signals;
the data calculation module is used for reading the detection data signals, calculating the detection data signals and sending the calculated data signals to the storage comparison module;
the storage comparison module is used for receiving the calculated data signal and comparing the data signal with the comparison data to judge whether the battery at the monitored end is in fault or not, if the battery is judged to be normal, the statistical module reads the detection data signal, performs statistics and generates statistical data, and if the battery is judged to be in fault, the fault reporting module generates a fault reporting signal;
the display module is used for displaying statistical data or fault reporting signals.
The working principle is as follows: after the battery is installed, a data acquisition module at a monitored end reads an initial voltage value of the battery and a time point corresponding to the initial voltage value, reads a termination voltage value of the battery and a time point corresponding to the termination voltage value, forms a detection data signal and sends the detection data signal to a data sending module, the data sending module receives the detection data signal and forwards the detection data signal to a data receiving module at a server end, the data receiving module receives the detection data signal and forwards the detection data signal to a data temporary storage module, a data calculation module at the server end reads the detection data signal in the data temporary storage module and calculates the detection data signal, the data signal obtained by calculation is sent to a storage comparison module, the storage comparison module compares the detection data signal with comparison data to judge whether the battery is normal or not, and if the battery is judged to be normal, an instruction counting module reads the detection data signal to the data temporary storage, the statistical module performs detection data statistics to form statistical data; and if the battery is judged to be in a fault state, the fault reporting module generates a fault reporting signal, and finally the display module receives and displays the statistical data or the fault reporting signal. The utility model discloses can carry out battery data statistics on a large scale, convenient high-efficient, the low cost of greatly acquireing battery experimental data moreover reduces experiment cost of labor. The service state of a certain type of equipment with the battery can be monitored in a large range, and fault reporting is carried out when a fault is monitored, so that the equipment can be conveniently and timely maintained by workers, and the detection cost is saved.
In the battery monitoring and counting system based on the internet of things, the initial voltage value of the battery read by the data acquisition module is set as V1Record V1Is set to T1Reading the end voltage value of the battery as V2Record V2Is set to T2The data calculation module is used for calculating the slope of a battery discharge curve and setting the slope as K, and the slope K of the battery discharge curve is calculated through the following formula: k ═ V1-V2)/(T2-T1)。
In the battery monitoring and counting system based on the internet of things, the storage comparison module is preset with the slope K of the battery discharge curvePreparation ofSaid KPreparation ofFor a predetermined range of the slope of the battery discharge curve,
when K is at KPreparation ofWhen the battery is within the range, the battery is judged to be normal,
when K exceeds KPreparation ofWhen the range is reached, the battery is judged to be faulty.
In the battery monitoring and counting system based on the internet of things, the data acquisition module is further connected with a threshold judgment module, and the threshold judgment module is used for setting the lowest working voltage V of the monitored endThreshold(s)Said V is2＝VThreshold(s)。
In the battery monitoring and counting system based on the Internet of things, the counting module is further connected with a data rejection module, and the data rejection module is provided with a voltage value VFirst stageWhen V isFirst stageA predetermined initial voltage range for the battery, said V1Beyond VFirst stageThe set of detected data is rejected.
In foretell battery monitoring statistical system based on thing networking, the monitored end contains address information, data sending module still be used for sending the address information to the data receiving module of monitored battery, data receiving module forward address information to data temporary storage module, data temporary storage module receive, save address information and supply to read, when the battery is judged for the trouble, display module reads address information and shows.
In the above battery monitoring and statistics system based on the internet of things, the battery is particularly an alkaline battery or/and a carbon battery used for a metering device.
In the above battery monitoring and counting system based on the internet of things, KPreparation ofComprising KAlkaliAnd KCarbon (C)Said KAlkaliThe slope range of the discharge curve of the alkaline battery, the KCarbon (C)The slope range of the discharge curve of the carbon battery is shown, the statistical module comprises an alkaline statistical module and a carbon statistical module,
-said alkaline statistics module is used for counting alkaline cells when K is at KAlkaliWhen the range is in, the alkaline statistic module reads the detection data signal and counts,
the carbon counting module is used for counting the carbon batteries when K is KCarbon (C)When the range is in, the carbon counting module reads the detection data signal and counts.
Compared with the prior art, the utility model has the advantages of it is following:
1. the utility model discloses can be to the huge quilt monitoring end of cardinal number, each is by monitoring the end with truest service data transmission to server end, supply server end statistics, the condition of having got rid of the data distortion takes place.
2. The utility model discloses can detect whether there is the trouble by the gas table of monitoring end, when the gas table has the trouble, can fix a position the gas table of trouble, and will this group of data rejection, make things convenient for maintenance personal in time to repair trouble gas table, and improved the accuracy of statistics.
3. The utility model discloses can be to different types of batteries, automatic identification is by the type that the monitoring end used the battery to the classification makes statistics of, makes statistics of more accurate and application scope extensively.
4. The utility model discloses can also reject because the initial voltage of battery itself is not up to standard and the abnormal data that produces, further reduce the error of statistical result
Drawings
Fig. 1 is a schematic diagram of the system of the present invention.
In the figure, 1, a server side; 2. a monitored end; 3. a battery; 4. a data acquisition module; 5. a data transmission module; 6. a data receiving module; 7. a data temporary storage module; 8. a data calculation module; 9. a storage comparison module; 10. an alkalinity statistic module; 11. a carbon statistics module; 12. a fault reporting module; 13. a display module; 14. a statistical module; 15. a data elimination module; 16. and a threshold determination module.
Detailed Description
The following are specific embodiments of the present invention and the accompanying drawings are used to further describe the technical solution of the present invention, but the present invention is not limited to these embodiments.
As shown in fig. 1, the battery monitoring and statistics system based on the internet of things comprises a server end 1 and a plurality of monitored ends 2 in communication connection with the server end 1, wherein each monitored end 2 comprises a battery 3, a data acquisition module 4 and a data sending module 5, and the server end 1 comprises a data receiving module 6, a data temporary storage module 7, a data calculation module 8, a storage comparison module 9, a statistics module 14, an obstacle reporting module 12 and a display module 13; the data acquisition module 4 is configured to read a voltage value of the battery 3 and a time point corresponding to the voltage value, specifically, the data acquisition module 4 reads an initial voltage value of the battery 3 and sets the initial voltage value as V1Record V1Is read outThe time point is set to T1Reading the end voltage value of the battery 3 as V2Record V2Is set to T2Therefore, a detection data signal is formed and sent to the data sending module 5, the data sending module 5 receives the detection data signal and forwards the detection data signal to the data receiving module 6, the data receiving module 6 receives the detection data signal and forwards the detection data signal to the data temporary storage module 7, and the detection data signal can be read by other modules after being stored in the data temporary storage module 7. The data calculation module 8 reads the detection data signal from the data temporary storage module 7 and then calculates the slope K of the battery discharge curve, and the slope K of the battery discharge curve is calculated by the following formula: k ═ V1-V2)/(T2-T1) So as to obtain a calculated data signal and forward it to the memory comparison module 9. The storage comparison module 9 is preset with the slope K of the battery discharge curvePreparation of，KPreparation ofIs a preset slope range of the battery discharge curve. The storage comparison module 9 receives the calculated data signal and the comparison data KPreparation ofComparing, when K is KPreparation ofWhen the voltage is within the range, the command counting module 14 reads the detection data signal, counts and generates counting data after the battery 3 is judged to be normal, and when K exceeds KPreparation ofIn the range, the battery 3 is determined to be faulty and instructs the fault reporting module 12 to generate a fault reporting signal, and then the generated statistical data or fault reporting signal is displayed on the display module 13.
In further detail, the data acquisition module 4 is connected with a threshold value determination module 16, and the threshold value determination module 16 is used for setting the lowest working voltage V of the monitored end 2Threshold(s)，V2＝VThreshold(s). The lowest working voltage required by different equipment, therefore, the monitored end 2 needs to adjust the termination voltage according to the equipment, and then the slope K of the discharge curve of the battery 3 under the use condition of the equipment is calculated for judgment. The utility model discloses in set up threshold value decision module 16, the system can be adjusted by the minimum operating voltage V of monitoring end 2 through this moduleThreshold(s)Adjusting the detected minimum operating voltage V2＝VThreshold(s)The data acquisition module 4 reads the time point T at this time2Is actually VThreshold(s)Corresponding points in time, i.e. detecting tonesMinimum working voltage V after finishingThreshold(s)Corresponding time point, and the data calculating module 8 reads the detection data signal from the data temporary storage module 7 and then calculates the slope of the battery discharge curve, namely from the initial voltage to the lowest working voltage VThreshold(s)The slope of the battery discharge curve over the corresponding time period.
In further detail, the statistical module 14 is further connected with a data removing module 15, and the data removing module 15 is provided with a voltage value VFirst stageWhen V isFirst stageInitial voltage range, V, preset for the battery 31Beyond VFirst stageThe set of detected data is rejected. In actual use, the used batteries are not all fully charged batteries, and the service life of the battery obtained by monitoring the battery with insufficient charging is shorter than that of a normal battery, so that the experimental data can be influenced. In addition, the slope of the battery discharge curve calculated by the battery in the non-fully-charged state in the time period corresponding to the time period from the initial voltage to the lowest working voltage has little reference significance in the research and development process, and the data is necessary to be rejected, so that the validity of experimental data statistics is ensured.
In further detail, the monitored terminal 2 contains address information, the data sending module 5 is further configured to send the address information of the monitored battery 3 to the data receiving module 6, the data receiving module 6 forwards the address information to the data temporary storage module 7, the data temporary storage module 7 receives, stores and reads the address information, and when the battery 3 is determined to be faulty, the display module 13 reads and displays the address information. The information of the monitored end 2 comprises unique address information, the information sent to the server end 1 by the data sending module 5 comprises the address information, and when the monitored end 2 is judged to be in fault, the display module 13 of the server end 1 displays the address information of the monitored end 2 in time so as to facilitate the staff to timely maintain and repair the specified address.
In further detail, the battery 3 is specifically intended for use in an alkaline battery or/and a carbon battery on a meter.
To put it more closely, KPreparation ofComprising KAlkaliAnd KCarbon (C)，KAlkaliIs the slope range of the discharge curve of the alkaline cell, KCarbon (C)Counting the slope range of the discharge curve of the carbon batteryThe module 14 comprises an alkaline statistic module 10 and a carbon statistic module 11, wherein the alkaline statistic module 10 is used for counting alkaline batteries, and when K is at KAlkaliWhen the range is in, the alkaline statistic module 10 reads the detection data signal and counts, the carbon statistic module 11 is used for counting the carbon batteries, and when K is in KCarbon (C)When the range is in, the carbon counting module 11 reads the detection data signal and counts. In the monitored terminal 2 for daily use, dry batteries mainly include alkaline batteries and carbon batteries. Therefore, the use information of the alkaline battery and the carbon battery is specially counted, and the management and the use in later-period experiments are convenient.
The utility model discloses in, whether the slope that at first detects the battery discharge curve is in normal within range, can reach and provide whether the gas table of this group data breaks down, if there is the trouble, in time report the trouble and reject this group data, can also judge the type of battery through the slope of battery discharge curve simultaneously, can classify the data of different grade type battery, then, through the initial voltage that detects the battery, reject the abnormal constant data that initial voltage is low excessively, only leave normal data after multiple rejection, the life of each piece of normal use battery of statistics module record is counted.
Application example: the system is used for counting and monitoring the gas meter batteries applied to the Internet of things, the gas meter batteries in the field usually use alkaline batteries and carbon batteries, the factory initial voltage value of the gas meter batteries is generally 6.5V, the lowest working voltage is 5V, and the system judges whether the batteries are in fault and carries out classified statistics by calculating the slope of a discharge curve from the initial voltage to the lowest working voltage and comparing the slope of a preset discharge curve. The slope of the existing preset discharge curve is: the battery discharge slope of the alkaline gas meter battery from the initial voltage to 5V is 0.08, the battery discharge slope of the carbon gas meter battery from the initial voltage to 5V is 0.2, and when the battery discharge slope of the monitored end 2 is other large values, the fault can be judged. Specifically, the method comprises the following steps: after the battery 3 is installed, the data acquisition module 4 reads the initial voltage value of the gas meter battery 3 as V1Recording time point of T1When the battery 3 is discharged to the lowest working voltage of 5V, the recording time point is T2Therefore, a detection data signal is formed and sent to the data sending module 5, the data sending module 5 receives the detection data signal and forwards the detection data signal to the data receiving module 6, the data receiving module 6 receives the detection data signal and forwards the detection data signal to the data temporary storage module 7, and the detection data signal can be read by other modules after being stored in the data temporary storage module 7. The data calculation module 8 reads the detection data signal from the data temporary storage module 7 and then calculates the slope K of the battery discharge curve, where the slope K of the battery discharge curve is calculated as K ═ V1-5)/(T2-T1) So as to obtain the calculated data signal and forward the data signal to the storage comparison module 9, wherein the slope K of the battery discharge curve is preset in the storage comparison module 9Alkali＝0.08、KCarbon (C)The storage comparison module 9 counts or reports failure according to the comparison result of the slope K value and the preset comparison data, before counting, the detection data signals stored in the data temporary storage module 7 are selectively removed from useless data, and the data removing module 15 is provided with a voltage value VFirst stageWhen V isFirst stageInitial voltage range, V, preset for the battery 31Beyond VFirst stageThe set of detected data is rejected. The specific judgment of the storage comparison module 9 is as follows: when the value of K is equal to KAlkaliOr KCarbon (C)When the battery 3 is judged to be normal, the storage comparison module 9 instructs the statistic module 14 to read the detection data signal in the data temporary storage module 7, and when the value K is equal to KAlkaliThe detection data signal enters an alkalinity statistic module 10 to carry out detection data signal statistics, and when the K value is equal to KCarbon (C)The detection data signal enters a carbon statistics module 11 to carry out detection data signal statistics; when the value of K is not equal to KAlkaliOr KCarbon (C)When the electric quantity of the battery of the gas meter is leaked in a short time, the battery 3 has a fault and generates an obstacle-reporting signal. In addition, when the monitored end 2 uses gas meters of other models and the lowest working voltage is not 5V, the threshold value determination module 16 is used for adjusting the lowest working voltage to be VThreshold(s)The data acquisition module 4 reads the voltage of the battery 3 to be the lowest working voltage VThreshold(s)Recording time point of T2The data acquisition module 4 sends the detection data signal to the data receiving module 6 to repeat the above stepsAnd judging and counting.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications, additions and substitutions for the specific embodiments described herein may be made by those skilled in the art without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Although the terms of the server side 1, the monitored side 2, the battery 3, the data acquisition module 4, the data transmission module 5, the data reception module 6, the data temporary storage module 7, the data calculation module 8, the storage comparison module 9, the alkalinity statistical module 10, the carbon statistical module 11, the fault reporting module 12, the display module 13, the statistical module 14, the data rejection module 15, the threshold determination module 16, and the like are used more frequently, the possibility of using other terms is not excluded. These terms are used merely to more conveniently describe and explain the nature of the present invention; they are to be construed in a manner that is inconsistent with the spirit of the invention.
Claims (2)
1. A battery monitoring and counting system based on the Internet of things is characterized by comprising a server end (1) and a plurality of monitored ends (2) which are in communication connection with the server end (1);
the monitored end (2) comprises a battery (3), a data acquisition module (4) and a data transmission module (5);
the server side (1) comprises a data receiving module (6), a data temporary storage module (7), a data calculating module (8), a storage comparison module (9), a counting module (14), an obstacle reporting module (12) and a display module (13);
the data acquisition module (4) is used for reading the voltage value of the battery (3) and the time point corresponding to the voltage value, forming a detection data signal and sending the detection data signal to the data sending module (5);
the data sending module (5) is used for receiving the detection data signal and forwarding the detection data signal to the data receiving module (6);
the data receiving module (6) is used for receiving the detection data signal and forwarding the detection data signal to the data temporary storage module (7);
the data temporary storage module (7) is used for receiving, storing and reading detection data signals;
the data calculation module (8) is used for reading the detection data signals, calculating the detection data signals and sending the calculated data signals to the storage comparison module (9);
the storage comparison module (9) is used for storing comparison data, the storage comparison module (9) is used for receiving the calculated data signals and comparing the data signals with the comparison data, judging whether the battery (3) of the monitored end (2) is in fault or not, if the battery (3) is judged to be normal, the statistic module (14) reads the detection data signals, carries out statistics and generates statistic data, and if the battery (3) is judged to be in fault, the fault reporting module (12) generates fault reporting signals;
the display module (13) is used for displaying statistical data or fault reporting signals.
2. The battery monitoring and counting system based on the internet of things as claimed in claim 1, wherein the monitored terminal (2) contains address information, the data sending module (5) is further used for sending the address information of the monitored battery (3) to the data receiving module (6), the data receiving module (6) forwards the address information to the data temporary storage module (7), the data temporary storage module (7) receives, stores and reads the address information, and when the battery (3) is judged to be faulty, the display module (13) reads and displays the address information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108387850A (en) * | 2018-05-04 | 2018-08-10 | 金卡智能集团股份有限公司 | A kind of battery detection statistical system and its method based on Internet of Things |
| CN116598613A (en) * | 2023-05-19 | 2023-08-15 | 清安储能技术(重庆)有限公司 | Energy storage management system and method |
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2018
- 2018-05-04 CN CN201820663531.2U patent/CN211785999U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108387850A (en) * | 2018-05-04 | 2018-08-10 | 金卡智能集团股份有限公司 | A kind of battery detection statistical system and its method based on Internet of Things |
| CN116598613A (en) * | 2023-05-19 | 2023-08-15 | 清安储能技术(重庆)有限公司 | Energy storage management system and method |
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