CN115663312B - Battery operation monitoring system and method based on battery protection - Google Patents
Battery operation monitoring system and method based on battery protection Download PDFInfo
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Abstract
The invention discloses a battery operation monitoring system and method based on battery protection, which belong to the field of batteries and are used for solving the problems that an irregular use method and an abnormal condition of a battery greatly shorten the service life of the battery in the use process.
Description
Technical Field
The invention belongs to the field of batteries, relates to an operation monitoring technology, and particularly relates to a battery operation monitoring system and method based on battery protection.
Background
A battery refers to a device that converts chemical energy into electrical energy in a cup, tank, or other container or portion of a composite container that contains an electrolyte solution and metal electrodes to generate an electrical current. Has a positive electrode and a negative electrode. With the advancement of technology, batteries are widely referred to as small devices capable of generating electrical energy. Such as a solar cell. The performance parameters of the battery are mainly electromotive force, capacity, specific energy and resistance. The battery is used as an energy source, the current which has stable voltage, stable current, long-time stable power supply and little influence from the outside can be obtained, the battery has simple structure, convenient carrying, simple and easy charging and discharging operation, no influence from the outside climate and temperature, stable and reliable performance and great effect in various aspects in life nowadays.
The battery is used as a lossy article, the service life of the battery is gradually reduced in the use process, in addition, the battery in abnormal conditions is not treated and remedied in time by an irregular use method of the battery and the abnormal conditions of the battery in the use process, the service life of the battery is greatly shortened, and therefore, how to monitor the running state of the battery in real time to realize battery protection is a problem which needs to be solved at present;
for this reason, we propose a battery operation monitoring system and method based on battery protection.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a battery operation monitoring system and method based on battery protection.
The technical problems to be solved by the invention are as follows:
how to monitor the running state of the battery in real time based on the past use state so as to realize the problem of battery protection.
The aim of the invention can be achieved by the following technical scheme:
the battery operation monitoring system based on battery protection comprises a user terminal, an intelligent matching module, a history analysis module, a database, a data acquisition module, an operation monitoring module, an intelligent judgment module and a server, wherein the user terminal is used for inputting the model of a battery and sending the model of the battery to the server, and the server is used for sending the model of the battery to the intelligent matching module; the database is used for storing historical use data of batteries of different preset models;
the intelligent matching module is used for intelligently matching the model of the battery, the intelligent matching is carried out to obtain the preset model of the battery and the preset model is fed back to the server, the server sends the preset model of the battery to the database, and the database sends the historical use data of the battery to the historical analysis module according to the preset model;
the history analysis module is used for analyzing the history use condition of the battery, obtaining an operation monitoring value of the battery, feeding the operation monitoring value back to the server, setting an error threshold of the battery according to the operation monitoring value by the server, and sending the error threshold to the intelligent judgment module;
the data acquisition module is used for acquiring real-time operation data of the battery and transmitting the real-time operation data to the server, the database also stores standard operation data corresponding to the battery and transmits the standard operation data to the server, and the server transmits the real-time operation data and the standard operation data to the operation monitoring module;
the operation monitoring module is used for monitoring the real-time operation condition of the battery, obtaining an operation error value of the battery in an operation monitoring period and feeding the operation error value back to the server, and the server sends the operation error value of the battery in the operation monitoring period to the intelligent judging module; the intelligent judging module is used for intelligently judging the running state of the battery and generating a normal running signal or an abnormal running signal.
Further, the historical usage data is the number of faults of the battery, and the maintenance duration and the fault time of each fault;
the real-time operation data are a real-time current value, a real-time voltage value and a real-time temperature value of the battery; the standard operation data are a standard current value, a standard voltage value and a standard temperature value of the battery.
Further, the analysis process of the history analysis module is specifically as follows:
acquiring the fault times of the battery, and marking the fault times as GC;
then, the maintenance time length of each fault of the battery is obtained, and the maintenance time length of each fault is added, summed and averaged to obtain the maintenance average time length JWT of the battery;
finally, obtaining the fault time of each fault of the battery, calculating the time difference value of adjacent fault time to obtain a plurality of groups of fault interval time, adding and summing the plurality of groups of fault interval time to obtain the fault interval average time JGT of the battery;
the operation monitoring value YJ of the battery is calculated by the formula yj=1/(gc×a1+jwt×a2+jgt×a3); wherein a1, a2 and a3 are all proportional coefficients with fixed values, and the values of a1, a2 and a3 are all larger than zero.
Further, the error threshold setting process specifically includes:
if YJ is less than X1, the error threshold of the battery is Y1;
if X1 is less than or equal to YJ and less than X2, the error threshold of the battery is Y2;
if X2 is less than or equal to YJ, the error threshold of the battery is Y3; wherein X1 and X2 are operation monitoring thresholds with fixed values, X1 is less than X2, Y1, Y2 and Y3 are fixed values, and Y1 is less than Y2 and less than Y3.
Further, the monitoring process of the operation monitoring module is specifically as follows:
setting an operation monitoring period of the battery, and setting a plurality of time points in the operation monitoring period;
acquiring a real-time current value, a real-time voltage value and a real-time temperature value corresponding to each time point;
calculating the difference value between the real-time current value and the standard current value to obtain a current deviation value at each time point;
the current deviation value at each time point is added and divided by the average value to obtain a current deviation value DLW of the battery in the operation monitoring period;
similarly, calculating to obtain a voltage error value DYW and a temperature error value WDW of the battery in the operation monitoring period according to the steps;
calculating an operation error value YW of the battery in the operation monitoring period by the formula yw=dlw×b1+dyw×b2+wdw×b3; wherein b1, b2 and b3 are weight coefficients with fixed values, and the values of b1, b2 and b3 are all larger than zero.
Further, the intelligent judging process of the intelligent judging module is specifically as follows:
obtaining an error threshold value corresponding to the battery according to the operation monitoring value;
then obtaining an operation error value of the battery in an operation monitoring period;
if the operation error value of the battery is smaller than or equal to the corresponding error threshold value, generating an operation normal signal;
and if the operation error value of the battery is larger than the corresponding error threshold value, generating an operation abnormal signal.
Further, the intelligent judging module feeds back a normal operation signal or an abnormal operation signal to the server;
if the server receives the normal operation signal, no operation is performed;
and if the server receives the abnormal operation signal, forwarding the abnormal operation signal to the user terminal.
A battery operation monitoring method based on battery protection comprises the following steps:
step S101, a user terminal inputs the model of a battery and sends the model of the battery to a server, the server sends the model of the battery to an intelligent matching module, the intelligent matching module carries out intelligent matching on the model of the battery, the intelligent matching obtains the preset model of the battery and feeds the preset model back to the server, the server sends the preset model of the battery to a database, and the database sends historical use data of the battery to a historical analysis module according to the preset model;
step S102, a history analysis module analyzes the history service condition of the battery to obtain the fault times of the battery, then obtains the maintenance time length of the battery when each fault occurs, adds, sums and averages the maintenance time length when each fault occurs to obtain the maintenance average time length of the battery, finally obtains the fault time when each fault occurs to the battery, calculates the time difference value of adjacent fault time to obtain a plurality of groups of fault interval time lengths, adds, sums and averages the plurality of groups of fault interval time lengths to obtain the fault interval average time length of the battery, calculates the operation monitoring value of the battery, and the history analysis module feeds back the operation monitoring value of the battery to a server, and the server sets the error threshold value of the battery according to the operation monitoring value and sends the error threshold value to an intelligent judgment module;
step S103, the data acquisition module acquires real-time operation data of the battery and sends the real-time operation data to the server, the database also stores standard operation data corresponding to the battery and sends the standard operation data to the server, and the server sends the real-time operation data and the standard operation data to the operation monitoring module;
step S104, monitoring the real-time operation condition of the battery through an operation monitoring module, setting an operation monitoring period of the battery, setting a plurality of time points in the operation monitoring period, obtaining a real-time current value, a real-time voltage value and a real-time temperature value corresponding to each time point, calculating the difference value of the real-time current value and a standard current value to obtain a current deviation value at each time point, adding and dividing the current deviation value at each time point by an average value to obtain the current deviation value of the battery in the operation monitoring period, and similarly, calculating the voltage deviation value and the temperature deviation value of the battery in the operation monitoring period according to the steps, calculating the operation deviation value of the battery in the operation monitoring period, feeding back the operation deviation value of the battery in the operation monitoring period to a server, and sending the operation deviation value of the battery in the operation monitoring period to an intelligent judging module by the server;
step S105, the intelligent judging module intelligently judges the running state of the battery, obtains the corresponding error threshold value of the battery according to the running monitoring value, then obtains the running error value of the battery in the running monitoring period, generates a running normal signal if the running error value of the battery is smaller than or equal to the corresponding error threshold value, generates a running abnormal signal if the running error value of the battery is larger than the corresponding error threshold value, feeds back the running normal signal or the running abnormal signal to the server, does not perform any operation if the server receives the running normal signal, and forwards the running abnormal signal to the user terminal if the server receives the running abnormal signal.
Compared with the prior art, the invention has the beneficial effects that:
the invention inputs the model of the battery through the user terminal and sends to the intelligent matching module, the intelligent matching module carries on intelligent matching to the model of the battery, get the preset model of the battery and sends to the database, the database sends the historical use data to the historical analysis module according to the preset model, the historical analysis module analyzes the historical use condition of the battery, get the operation monitoring value of the battery and feeds back to the server, the server sets the error threshold of the battery according to the operation monitoring value and sends to the intelligent judgment module, then monitors the real-time operation condition of the battery through the operation monitoring module, gets the operation error value of the battery in the operation monitoring period and sends to the intelligent judgment module, finally carries on intelligent judgment to the operation state of the battery through the intelligent judgment module, generates the operation normal signal or the operation abnormal signal;
according to the invention, firstly, based on the past use state of the battery, an adaptive monitoring standard is set for the battery, then the real-time running state of the battery is monitored, and the monitoring result is compared with the monitoring standard to judge whether the battery is in an abnormal state or not, so that the protection of the battery in the use process is realized.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is an overall system block diagram of the present invention;
fig. 2 is a flow chart of the operation of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In one embodiment, referring to fig. 1, a battery operation monitoring system based on battery protection includes a user terminal, an intelligent matching module, a history analysis module, a database, a data acquisition module, an operation monitoring module, an intelligent determination module and a server;
in specific implementation, the user terminal is used for inputting personal information by using a person and sending the personal information to a server for storage; wherein, the personal information comprises the name, the mobile phone number and the like of the user;
the user terminal is used for inputting the model of the battery and sending the model of the battery to the server, and the server sends the model of the battery to the intelligent matching module; the database is used for storing historical use data of batteries of different preset models;
the historical usage data is the number of faults of the battery, and the maintenance time and the fault time of each fault are required to be specified;
the intelligent matching module is used for intelligently matching the model of the battery, the intelligent matching is carried out to obtain the preset model of the battery and the preset model is fed back to the server, the server sends the preset model of the battery to the database, and the database sends the historical use data of the battery to the historical analysis module according to the preset model;
in this embodiment, the matching process of the preset model may specifically use a chinese analysis technology and combine with a shape comparison technology, and model comparison is similar to name comparison, which is a more mature prior art, so that redundant description is not performed;
the history analysis module is used for analyzing the history use condition of the battery, and the analysis process is specifically as follows:
acquiring the fault times of the battery, and marking the fault times as GC;
then, the maintenance time length of each fault of the battery is obtained, and the maintenance time length of each fault is added, summed and averaged to obtain the maintenance average time length JWT of the battery;
finally, obtaining the fault time of each fault of the battery, calculating the time difference value of adjacent fault time to obtain a plurality of groups of fault interval time, adding and summing the plurality of groups of fault interval time to obtain the fault interval average time JGT of the battery;
the operation monitoring value YJ of the battery is calculated by the formula yj=1/(gc×a1+jwt×a2+jgt×a3); wherein a1, a2 and a3 are all proportionality coefficients with fixed values, and the values of a1, a2 and a3 are all larger than zero, and in the specific implementation, the specific values of a1, a2 and a3 only need not influence the positive-negative ratio relation between the parameters and the result values;
the history analysis module feeds back the operation monitoring value YJ of the battery to the server, and the server sets an error threshold of the battery according to the operation monitoring value and sends the error threshold to the intelligent judgment module, specifically:
if YJ is less than X1, the error threshold of the battery is Y1;
if X1 is less than or equal to YJ and less than X2, the error threshold of the battery is Y2;
if X2 is less than or equal to YJ, the error threshold of the battery is Y3; wherein X1 and X2 are operation monitoring thresholds with fixed values, X1 is less than X2, Y1, Y2 and Y3 are fixed values, and Y1 is less than Y2 and less than Y3;
the data acquisition module is used for acquiring real-time operation data of the battery and transmitting the real-time operation data to the server, the database also stores standard operation data corresponding to the battery and transmits the standard operation data to the server, and the server transmits the real-time operation data and the standard operation data to the operation monitoring module;
specifically, the data acquisition module may be a current and voltage detector for detecting the current and voltage of the battery, and a temperature sensor or a related temperature monitoring device for monitoring the temperature of the battery in actual use, which is not particularly limited herein;
the real-time operation data are a real-time current value, a real-time voltage value, a real-time temperature value and the like of the battery; the standard operation data are a standard current value, a standard voltage value and a standard temperature value of the battery;
the operation monitoring module is used for monitoring the real-time operation condition of the battery, and the monitoring process is specifically as follows:
setting an operation monitoring period of the battery, and setting a plurality of time points in the operation monitoring period;
acquiring a real-time current value, a real-time voltage value and a real-time temperature value corresponding to each time point;
calculating the difference value between the real-time current value and the standard current value to obtain a current deviation value at each time point;
the current deviation value at each time point is added and divided by the average value to obtain a current deviation value DLW of the battery in the operation monitoring period;
similarly, calculating to obtain a voltage error value DYW and a temperature error value WDW of the battery in the operation monitoring period according to the steps;
calculating an operation error value YW of the battery in the operation monitoring period by the formula yw=dlw×b1+dyw×b2+wdw×b3; wherein b1, b2 and b3 are weight coefficients with fixed values, and the values of b1, b2 and b3 are all larger than zero, and in the specific implementation, the specific values of b1, b2 and b3 are only required to be enough as long as the positive-negative ratio relation between the parameters and the result values is not influenced;
the operation monitoring module feeds back an operation error value YW of the battery in an operation monitoring period to the server, and the server sends the operation error value YW of the battery in the operation monitoring period to the intelligent judging module; the intelligent judging module is used for intelligently judging the running state of the battery, and the intelligent judging process is specifically as follows:
obtaining an error threshold value corresponding to the battery according to the operation monitoring value;
then obtaining an operation error value of the battery in an operation monitoring period;
if the operation error value of the battery is smaller than or equal to the corresponding error threshold value, generating an operation normal signal;
if the operation error value of the battery is larger than the corresponding error threshold value, generating an operation abnormal signal;
the intelligent judging module feeds back an operation normal signal or an operation abnormal signal to the server, if the server receives the operation normal signal, the operation normal signal is not operated, if the server receives the operation abnormal signal, the operation abnormal signal is forwarded to the user terminal, and after the user at the user terminal knows that the battery is in an abnormal state, the operation of the battery is immediately stopped;
the formula is a formula for obtaining the numerical value calculation by removing dimensions, the formula is a formula for obtaining the latest real situation by collecting a large amount of data and performing software simulation, the weight coefficient and the scale coefficient are specific numerical values obtained by quantizing each parameter, and the weight coefficient and the scale coefficient are only required to have no influence on the proportional relation between the parameter and the quantized numerical value;
compared with the prior art, the invention has the beneficial effects that:
the invention inputs the model of the battery through the user terminal and sends to the intelligent matching module, the intelligent matching module carries on intelligent matching to the model of the battery, get the preset model of the battery and sends to the database, the database sends the historical use data to the historical analysis module according to the preset model, the historical analysis module analyzes the historical use condition of the battery, get the operation monitoring value of the battery and feeds back to the server, the server sets the error threshold of the battery according to the operation monitoring value and sends to the intelligent judgment module, then monitors the real-time operation condition of the battery through the operation monitoring module, gets the operation error value of the battery in the operation monitoring period and sends to the intelligent judgment module, finally carries on intelligent judgment to the operation state of the battery through the intelligent judgment module, generates the operation normal signal or the operation abnormal signal;
according to the invention, firstly, based on the past use state of the battery, an adaptive monitoring standard is set for the battery, then the real-time running state of the battery is monitored, and the monitoring result is compared with the monitoring standard to judge whether the battery is in an abnormal state or not, so that the protection of the battery in the use process is realized.
In another embodiment, referring to fig. 2, a battery operation monitoring method based on battery protection is now provided, and the battery operation monitoring method specifically includes the following steps:
step S101, a user terminal inputs the model of a battery and sends the model of the battery to a server, the server sends the model of the battery to an intelligent matching module, the intelligent matching module carries out intelligent matching on the model of the battery, the intelligent matching obtains the preset model of the battery and feeds the preset model back to the server, the server sends the preset model of the battery to a database, and the database sends historical use data of the battery to a historical analysis module according to the preset model;
step S102, a history analysis module analyzes the history service condition of the battery to obtain the fault times of the battery, then obtains the maintenance time length of the battery when each fault occurs, adds, sums and averages the maintenance time length when each fault occurs to obtain the maintenance average time length of the battery, finally obtains the fault time when each fault occurs to the battery, calculates the time difference value of adjacent fault time to obtain a plurality of groups of fault interval time lengths, adds, sums and averages the plurality of groups of fault interval time lengths to obtain the fault interval average time length of the battery, calculates the operation monitoring value of the battery, and the history analysis module feeds back the operation monitoring value of the battery to a server, and the server sets the error threshold value of the battery according to the operation monitoring value and sends the error threshold value to an intelligent judgment module;
step S103, the data acquisition module acquires real-time operation data of the battery and sends the real-time operation data to the server, the database also stores standard operation data corresponding to the battery and sends the standard operation data to the server, and the server sends the real-time operation data and the standard operation data to the operation monitoring module;
step S104, monitoring the real-time operation condition of the battery through an operation monitoring module, setting an operation monitoring period of the battery, setting a plurality of time points in the operation monitoring period, obtaining a real-time current value, a real-time voltage value and a real-time temperature value corresponding to each time point, calculating the difference value of the real-time current value and a standard current value to obtain a current deviation value at each time point, adding and dividing the current deviation value at each time point by an average value to obtain the current deviation value of the battery in the operation monitoring period, and similarly, calculating the voltage deviation value and the temperature deviation value of the battery in the operation monitoring period according to the steps, calculating the operation deviation value of the battery in the operation monitoring period, feeding back the operation deviation value of the battery in the operation monitoring period to a server, and sending the operation deviation value of the battery in the operation monitoring period to an intelligent judging module by the server;
step S105, the intelligent judging module intelligently judges the running state of the battery, obtains the corresponding error threshold value of the battery according to the running monitoring value, then obtains the running error value of the battery in the running monitoring period, generates a running normal signal if the running error value of the battery is smaller than or equal to the corresponding error threshold value, generates a running abnormal signal if the running error value of the battery is larger than the corresponding error threshold value, feeds back the running normal signal or the running abnormal signal to the server, does not perform any operation if the server receives the running normal signal, and forwards the running abnormal signal to the user terminal if the server receives the running abnormal signal.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (4)
1. The battery operation monitoring system based on battery protection is characterized by comprising a user terminal, an intelligent matching module, a history analysis module, a database, a data acquisition module, an operation monitoring module, an intelligent judgment module and a server, wherein the user terminal is used for inputting the model of a battery and sending the model of the battery to the server, and the server is used for sending the model of the battery to the intelligent matching module; the database is used for storing historical use data of batteries of different preset models;
the intelligent matching module is used for intelligently matching the model of the battery, the intelligent matching is carried out to obtain the preset model of the battery and the preset model is fed back to the server, the server sends the preset model of the battery to the database, and the database sends the historical use data of the battery to the historical analysis module according to the preset model;
the history analysis module is used for analyzing the history use condition of the battery, and the analysis process is specifically as follows:
acquiring the fault times of the battery, and marking the fault times as GC;
then, the maintenance time length of each fault of the battery is obtained, and the maintenance time length of each fault is added, summed and averaged to obtain the maintenance average time length JWT of the battery;
finally, obtaining the fault time of each fault of the battery, calculating the time difference value of adjacent fault time to obtain a plurality of groups of fault interval time, adding and summing the plurality of groups of fault interval time to obtain the fault interval average time JGT of the battery;
the operation monitoring value YJ of the battery is calculated by the formula yj=1/(gc×a1+jwt×a2+jgt×a3); wherein a1, a2 and a3 are all proportional coefficients with fixed values, and the values of a1, a2 and a3 are all larger than zero;
the history analysis module feeds back the operation monitoring value of the battery to the server, and the server sets an error threshold of the battery according to the operation monitoring value and sends the error threshold to the intelligent judgment module, wherein the error threshold setting process is specifically as follows:
if YJ is less than X1, the error threshold of the battery is Y1;
if X1 is less than or equal to YJ and less than X2, the error threshold of the battery is Y2;
if X2 is less than or equal to YJ, the error threshold of the battery is Y3; wherein X1 and X2 are operation monitoring thresholds with fixed values, X1 is less than X2, Y1, Y2 and Y3 are fixed values, and Y1 is less than Y2 and less than Y3;
the data acquisition module is used for acquiring real-time operation data of the battery and transmitting the real-time operation data to the server, the database also stores standard operation data corresponding to the battery and transmits the standard operation data to the server, and the server transmits the real-time operation data and the standard operation data to the operation monitoring module;
the operation monitoring module is used for monitoring the real-time operation condition of the battery, and the monitoring process is specifically as follows:
setting an operation monitoring period of the battery, and setting a plurality of time points in the operation monitoring period;
acquiring a real-time current value, a real-time voltage value and a real-time temperature value corresponding to each time point;
calculating the difference value between the real-time current value and the standard current value to obtain a current deviation value at each time point;
the current deviation value at each time point is added and divided by the average value to obtain a current deviation value DLW of the battery in the operation monitoring period;
similarly, calculating to obtain a voltage error value DYW and a temperature error value WDW of the battery in the operation monitoring period according to the steps;
calculating an operation error value YW of the battery in the operation monitoring period by the formula yw=dlw×b1+dyw×b2+wdw×b3; wherein b1, b2 and b3 are weight coefficients with fixed values, and the values of b1, b2 and b3 are all larger than zero;
the operation monitoring module feeds back an operation error value of the battery in an operation monitoring period to the server, and the server sends the operation error value of the battery in the operation monitoring period to the intelligent judging module; the intelligent judging module is used for intelligently judging the running state of the battery and generating a normal running signal or an abnormal running signal, and the intelligent judging process is specifically as follows:
obtaining an error threshold value corresponding to the battery according to the operation monitoring value;
then obtaining an operation error value of the battery in an operation monitoring period;
if the operation error value of the battery is smaller than or equal to the corresponding error threshold value, generating an operation normal signal;
and if the operation error value of the battery is larger than the corresponding error threshold value, generating an operation abnormal signal.
2. The battery operation monitoring system based on battery protection according to claim 1, wherein the historical usage data is the number of failures of the battery and the maintenance duration and failure time at each failure;
the real-time operation data are a real-time current value, a real-time voltage value and a real-time temperature value of the battery; the standard operation data are a standard current value, a standard voltage value and a standard temperature value of the battery.
3. The battery operation monitoring system based on battery protection according to claim 1, wherein the intelligent determination module feeds back an operation normal signal or an operation abnormal signal to a server;
if the server receives the normal operation signal, no operation is performed;
and if the server receives the abnormal operation signal, forwarding the abnormal operation signal to the user terminal.
4. A battery operation monitoring method based on battery protection, characterized in that the battery operation monitoring system based on battery protection as claimed in any one of claims 1-3 is specifically as follows:
step S101, a model of a battery is input by a user terminal and sent to an intelligent matching module, the intelligent matching module carries out intelligent matching on the model of the battery, a preset model of the battery is obtained and sent to a database, and the database sends historical use data to a historical analysis module according to the preset model;
step S102, a history analysis module analyzes the history use condition of the battery, an operation monitoring value of the battery is obtained and fed back to a server, and the server sets an error threshold of the battery according to the operation monitoring value and sends the error threshold to an intelligent judgment module;
step S103, the data acquisition module acquires real-time operation data of the battery, standard operation data corresponding to the battery is also stored in the database, and the real-time operation data and the standard operation data are sent to the operation monitoring module;
step S104, the operation monitoring module monitors the real-time operation condition of the battery, and obtains an operation error value of the battery in an operation monitoring period and sends the operation error value to the intelligent judging module;
in step S105, the intelligent determination module intelligently determines the operation state of the battery, and generates an operation normal signal or an operation abnormal signal.
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| CN115991117B (en) * | 2023-03-24 | 2023-07-28 | 深圳市今朝时代股份有限公司 | Data processing-based automobile battery operation environment supervision system |
| CN116184216B (en) * | 2023-04-28 | 2023-07-14 | 广汽埃安新能源汽车股份有限公司 | Battery state detection method and device |
| CN116366757B (en) * | 2023-06-01 | 2023-09-22 | 深圳市冠群电子有限公司 | Intelligent detection system for errors of mobile phone POS machine of off-line store |
| CN116567127B (en) * | 2023-06-15 | 2024-01-23 | 深圳市誉源通讯技术有限公司 | Smart phone with fault monitoring function |
| CN116627080B (en) * | 2023-07-19 | 2023-09-15 | 欧米勒电气有限公司 | Digital intelligent control system suitable for operation of molded case circuit breaker |
| CN116961741B (en) * | 2023-07-24 | 2024-04-02 | 尚宁光电无锡有限公司 | Optical module test and debug system based on data analysis |
| CN116757482B (en) * | 2023-08-14 | 2024-02-09 | 深圳市泰科动力系统有限公司 | Fault supervision and maintenance system for new energy power battery production |
| CN116800200B (en) * | 2023-08-28 | 2023-12-29 | 广州丰久新能源科技有限公司 | Solar panel safety monitoring system based on data analysis |
| CN117071000B (en) * | 2023-10-17 | 2023-12-15 | 深圳润世华研发科技有限公司 | Remote safety monitoring system for PEM (PEM) water electrolysis hydrogen production equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130061268A (en) * | 2011-12-01 | 2013-06-11 | 현대자동차주식회사 | Hydrogen safety charging system and method using real-time tank deformation data of fuel cell vehicle |
| CN107040154A (en) * | 2017-05-12 | 2017-08-11 | 深圳市海浦蒙特科技有限公司 | Battery inversion system and its Current limited Control method with Current limited Control function |
| CN115407216A (en) * | 2022-08-19 | 2022-11-29 | 国网山东省电力公司莱芜供电公司 | Ring main unit storage battery health state online monitoring system |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101570181A (en) * | 2009-06-03 | 2009-11-04 | 奇瑞汽车股份有限公司 | Hybrid vehicle battery fault management system and management method thereof |
| JP5841489B2 (en) * | 2012-05-17 | 2016-01-13 | 東京瓦斯株式会社 | Operation information management method for fuel cell system |
| CN108400395A (en) * | 2018-02-12 | 2018-08-14 | 国家电网公司 | Intelligent battery and its long-distance management system |
| CN109649349A (en) * | 2018-12-27 | 2019-04-19 | 广西特斯途汽车科技有限公司 | A kind of battery shared system |
| US11480625B2 (en) * | 2020-03-12 | 2022-10-25 | Wisk Aero Llc | Real-time battery fault detection and state-of-health monitoring |
| CN112104038A (en) * | 2020-09-15 | 2020-12-18 | 广州邦禾检测技术有限公司 | Battery online monitoring method and device, equipment and system thereof |
| CN113540526B (en) * | 2021-07-16 | 2023-01-17 | 同济大学 | Fuel cell fault diagnosis method and system based on historical data analysis |
| CN114744312A (en) * | 2022-03-08 | 2022-07-12 | 杭州拓谦晨科技有限公司 | Battery state intelligent monitoring system for new energy vehicle |
| CN114640173B (en) * | 2022-03-10 | 2023-04-18 | 江苏国电南自海吉科技有限公司 | Early warning model of transformer and generator based on many characteristic quantities |
| CN114944514A (en) * | 2022-04-28 | 2022-08-26 | 浙江大学 | Lead-acid storage battery management method and device |
| CN114744734B (en) * | 2022-05-25 | 2023-01-10 | 深圳市今朝时代股份有限公司 | Battery operation control-based battery charging and discharging protection method and management system |
| CN114977414B (en) * | 2022-06-14 | 2024-04-19 | 中储绿能(山东)新能源有限公司 | Battery storage intelligent management system based on multi-cluster parallel energy storage |
| CN115390513A (en) * | 2022-07-14 | 2022-11-25 | 深圳市博硕科技股份有限公司 | Remote intelligent monitoring system of automatic laminating machine |
| CN115378141B (en) * | 2022-10-18 | 2023-02-28 | 华能辛店发电有限公司 | Power cable fault diagnosis early warning system and method based on data analysis |
| CN115528329B (en) * | 2022-11-09 | 2024-02-20 | 智洋创新科技股份有限公司 | Storage battery real-time operation detection method and detection system |
-
2022
- 2022-12-27 CN CN202211681656.5A patent/CN115663312B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130061268A (en) * | 2011-12-01 | 2013-06-11 | 현대자동차주식회사 | Hydrogen safety charging system and method using real-time tank deformation data of fuel cell vehicle |
| CN107040154A (en) * | 2017-05-12 | 2017-08-11 | 深圳市海浦蒙特科技有限公司 | Battery inversion system and its Current limited Control method with Current limited Control function |
| CN115407216A (en) * | 2022-08-19 | 2022-11-29 | 国网山东省电力公司莱芜供电公司 | Ring main unit storage battery health state online monitoring system |
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