CN113359036A - Online monitoring system for health state of power consumption of mining power battery pack - Google Patents
Online monitoring system for health state of power consumption of mining power battery pack Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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Abstract
The invention discloses an on-line monitoring system for the electricity utilization health state of a mining power battery pack, which comprises a data acquisition unit, a database, a type identification unit, a battery analysis unit, a service life judgment unit and intelligent equipment, wherein the data acquisition unit is used for acquiring a data; the data acquisition unit is used for acquiring battery information related to the battery pack during working and transmitting the battery information to the type identification unit; the invention analyzes the relevant data identified by the type identification unit through the battery analysis unit, increases the accuracy of data analysis, increases the reliability of data, saves the time consumed by data analysis, calculates and judges the relevant data analyzed by the battery analysis unit through the service life judgment unit, avoids the problems of judgment error and inaccurate judgment and improves the working efficiency.
Description
Technical Field
The invention relates to the technical field of battery state detection, in particular to an on-line monitoring system for the electricity health state of a mining power battery pack.
Background
The lithium ion battery draws wide attention of scientists in various countries by virtue of the advantages of higher energy density, longer service life, lower self-discharge rate, no pollution and the like, is the most widely applied and rapidly developed battery at present, and is widely applied to electric automobiles;
with the development of social science and technology, the situation that batteries are scrapped in the using process is avoided, the requirement on the service life of the batteries is more and more strict, people are required to analyze and judge the service life of the batteries, but the service life of the existing batteries is obtained through the using times of the batteries, each battery cannot be guaranteed to be the same, a large number of batteries are consumed in the testing of the service life of the batteries, and the service life of the analysis is not accurate;
therefore, an online monitoring system for the health state of the power utilization of the mining power battery pack is provided.
Disclosure of Invention
The invention aims to provide an on-line monitoring system for the health state of electricity consumption of a mining power battery pack.
The purpose of the invention can be realized by the following technical scheme: an on-line monitoring system for the electricity health state of a mining power battery pack comprises a data acquisition unit, a database, a type identification unit, a battery analysis unit, a service life judgment unit and intelligent equipment;
the data acquisition unit is used for acquiring battery information related to the battery pack during working and transmitting the battery information to the type identification unit;
the database stores record information related to the operation of the battery pack, the type identifying unit obtains the record information from the database, and performing type identification operation on the recorded information and the battery information together, recording completion data, recording use data, recording operation data, recording temperature data, recording service life data, recording speed data, recording model data, completion time data, use time data, operation time data, real-time temperature data, standard service life data and real-time speed data, the system comprises a service life judging unit, a battery analysis unit, a service life judging unit, a battery model judging unit and a battery management unit, wherein the service life judging unit is used for judging whether the service life of the battery is required to be recorded or not according to the service life data, the real-time temperature data, the standard service life data and the real-time speed data;
the battery analysis unit is used for carrying out battery analysis operation on the recorded model data, the recorded completion data, the recorded use data, the recorded operation data, the recorded temperature data, the recorded service life data, the recorded speed data and the recorded model data to obtain an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value, and transmitting the idle influence factor mean value, the operation influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value to the service life judgment unit;
the service life judging unit is used for judging and operating completion time data, use time data, operation time data, real-time temperature data, standard service life data, real-time speed data, an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value together to obtain actual remaining service life data and transmitting the actual remaining service life data to the intelligent equipment;
the intelligent device is used for receiving and displaying actual remaining life data.
As a further improvement of the invention: the specific operation process of the type identification operation is as follows:
the method comprises the following steps: acquiring recording information, and calibrating the recording information to obtain recording completion data, recording use data, recording operation data, recording temperature data, recording service life data, recording speed data and recording model data;
step two: acquiring battery information, calibrating the battery information to obtain completion time data, use time data, running time data, real-time temperature data, standard service life data and real-time speed data, and transmitting the completion time data, the use time data, the running time data, the real-time temperature data, the standard service life data and the real-time speed data to a service life judging unit;
step three: extracting the collected model data, and matching the collected model data with the recorded model data in the recorded information, specifically, when the collected model data is matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is stored, and generating an existence signal, and when the collected model data cannot be matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is not stored, and generating an absence signal;
step four: extracting the existing signal and the non-existing signal, identifying the existing signal and the non-existing signal, acquiring data again when the non-existing signal is identified, extracting the record type data and corresponding record completion data, record use data, record operation data, record temperature data, record service life data, record speed data and record type data when the existing signal is identified, and transmitting the record type data, the record use data, the record operation data, the record temperature data, the record life data, the record speed data and the record type data to a battery analysis unit;
step five: the completion time data, the use time data, the running time data, the real-time temperature data, the standard life data and the real-time speed data are extracted and transmitted to the life determination unit together.
As a further improvement of the invention: the specific operation process of the battery analysis operation is as follows:
k1: acquiring record model data, selecting corresponding record completion data and record use data according to the record model data, bringing the record completion data and the record use data into a difference calculation formula, calculating a difference between the record completion data and the record use data, and calibrating the difference as idle difference data;
k2: select out the different idle difference data of a plurality of among the above-mentioned K1 to it is inequality to set for idle difference data, and record operation data, record temperature data and record speed data are all the same, select out corresponding record life data, bring two different record life data into the difference formula of calculation, calculate the life difference, bring a plurality of life difference and a plurality of idle difference data into the formula of calculation: calculating u1 according to a calculation formula, wherein u1 represents an influence factor of idle time on the life, namely an idle influence factor, and substituting a plurality of idle influence factors into an average value calculation formula so as to calculate an idle influence factor average value;
k3: according to the above calculation method of the average value of the idle influence factors in K2, the corresponding influence factors are calculated for the recorded operation data, the recorded temperature data and the recorded speed data, so as to obtain the average value of the operation influence factors, the average value of the temperature influence factors and the average value of the speed influence factors.
As a further improvement of the invention: the specific operation process of the judgment operation is as follows:
h1: acquiring completion time data and use time data, and bringing the completion time data and the use time data into a difference calculation formula, thereby calculating a difference between the completion time data and the use time data and calibrating the difference as a storage time difference;
h2: acquiring real-time temperature data, bringing the temperatures of a plurality of different time points into an average value calculation formula, calculating the average temperatures of the different time points, and calibrating the average temperatures to be real-time temperature average values;
h3: acquiring real-time speed data, bringing a plurality of real-time speed data into an average value calculation formula, calculating an average value corresponding to the real-time speed data, and calibrating the average value as a real-time speed average value;
h4: extracting real-time speed mean value, real-time temperature mean value, storage time difference value, standard life data and operation time data, and bringing the real-time speed mean value, real-time temperature mean value, storage time difference value, standard life data and operation time data into a residual life calculation formula together with idle influence factor mean value, operation influence factor mean value, temperature influence factor mean value and speed influence factor mean value to obtain actual residual life data SYFruit of Chinese wolfberry；
H5: actual remaining life data is extracted.
As a further improvement of the invention: the remaining life calculation formula in H4 is specifically:
As a further improvement of the invention: the method comprises the steps of marking the time point of the battery pack in the record information after the battery pack finishes charging as record completion data, marking the time point of the battery pack in the record information after the battery pack finishes charging as record use data, marking the running time of the battery pack in the record information as record running data, marking the environment temperature of the battery pack in the record information as record temperature data, marking the service life of the battery pack in the record information as record life data, marking the speed of the battery pack in the record information at different time points as record speed data, and marking the model of the battery pack in the record information as record model data.
As a further improvement of the invention: the method comprises the steps of marking the time point of a battery pack in battery information after the battery pack finishes charging as completion time data, marking the time point of the battery pack in the battery information after the battery pack finishes charging as use time data, marking the running time of the battery pack in the battery information as running time data, marking the environment temperature of the battery pack in the battery information as real-time temperature data, marking the normal service life of the battery pack in the battery information as standard service life data, marking the speed of the battery pack in the battery information at different time points as real-time speed data, and marking the model of the battery pack in the battery information as acquisition model data.
As a further improvement of the invention: selecting a plurality of different recording operation data, setting the recording operation data to be different, wherein idle difference data, recording temperature data and recording speed data are the same, selecting corresponding recording service life data, bringing the two different recording operation data into a difference calculation formula, calculating an operation difference value, and bringing a plurality of corresponding service life difference values and a plurality of operation difference values into a calculation formula: calculating u2 according to a calculation formula, wherein u2 is an influence factor of the operating time on the life, namely an operating influence factor, and substituting a plurality of operating influence factors into an average value calculation formula so as to calculate an operating influence factor average value;
select out the different record temperature data of a plurality of to it is inequality to set for record temperature data, and idle difference data, record operation data and record speed data are all the same, select out corresponding record life data, bring two different record temperature data into the mean value formula of calculating, calculate temperature mean value, bring two different temperature mean values into the difference value formula of calculating, calculate the temperature difference value, bring the life difference value and the several operation difference value that a plurality of corresponds into the formula of calculating: recording temperature data u 3-a life difference, calculating u3 according to a calculation formula, wherein u3 represents influence factors of different temperatures on life, namely temperature influence factors, and substituting a plurality of temperature influence factors into an average value calculation formula so as to calculate an average value of the temperature influence factors;
selecting a plurality of different recording speed data in the K1, setting the recording speed data to be different, setting idle difference data, recording temperature data and recording operation data to be the same, selecting corresponding recording residual data, bringing two different recording speed data into a mean value calculation formula, calculating a speed mean value, bringing two different speed mean values into a difference value calculation formula, calculating a speed difference value, and bringing a plurality of corresponding service life difference values and a plurality of speed difference values into a calculation formula: the speed difference u4 is a life difference, u4 is calculated according to a calculation formula, wherein u4 is expressed as a speed influence factor which is an influence factor of speed on life, and a plurality of speed influence factors are substituted into an average value calculation formula, so that a speed influence factor average value is calculated.
The invention has the beneficial effects that:
(1) the acquisition unit is used for acquiring the battery information related to the battery pack during working and transmitting the battery information to the type identification unit; the type identification unit acquires the recorded information from the database, performs type identification operation on the recorded information and the battery information together, quickly identifies the collected related data, saves the time consumed by identification and improves the working efficiency;
(2) the battery analysis unit is used for carrying out battery analysis operation on the recorded model data, the recorded completion data, the recorded use data, the recorded operation data, the recorded temperature data, the recorded service life data, the recorded speed data and the recorded model data, the service life judging unit is used for judging the completion time data, the used time data, the operation time data, the real-time temperature data, the standard service life data, the real-time speed data, the idle influence factor mean value, the operation influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value together, the battery analysis unit is used for analyzing the relevant data identified by the type identification unit, the accuracy of data analysis is improved, the reliability of the data is improved, the time consumed by data analysis is saved, and the service life judging unit is used for calculating and judging the relevant data analyzed by the battery analysis unit, the problems of wrong judgment and inaccurate judgment are avoided, and the working efficiency is improved.
Drawings
The invention will be further described with reference to the accompanying drawings;
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to an online monitoring system for the health status of power consumption of a mining power battery pack, which comprises a data acquisition unit, a database, a type identification unit, a battery analysis unit, a service life determination unit and intelligent equipment, wherein the data acquisition unit is used for acquiring the health status of the power consumption of the mining power battery pack;
the data acquisition unit is used for acquiring battery information related to the battery pack during working and transmitting the battery information to the type identification unit;
the database stores record information related to the operation of the battery pack, the type identification unit acquires the record information from the database and performs type identification operation on the record information and the battery information together, and the specific operation process of the type identification operation is as follows:
the method comprises the following steps: acquiring record information, calibrating a time point of the battery pack in the record information after the battery pack finishes charging as record completion data, calibrating a time point of the battery pack in the record information after the battery pack finishes charging as record use data, calibrating the running time of the battery pack in the record information as record running data, calibrating the environment temperature of the battery pack in the record information as record temperature data, calibrating the service life of the battery pack in the record information as record life data, calibrating the speed of the battery pack in the record information at different time points as record speed data, and calibrating the model of the battery pack in the record information as record model data;
step two: acquiring battery information, marking a time point after the battery pack in the battery information is charged as completion time data, marking a time point used after the battery pack in the battery information is charged as use time data, marking the running time of the battery pack in the battery information as running time data, marking the environment temperature of the battery pack in the battery information as real-time temperature data, marking the normal life of the battery pack in the battery information as standard life data, marking the speed of the battery pack in the battery information at different time points as real-time speed data, and marking the model of the battery pack in the battery information as acquisition model data;
step three: extracting the collected model data, and matching the collected model data with the recorded model data in the recorded information, specifically, when the collected model data is matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is stored, and generating an existence signal, and when the collected model data cannot be matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is not stored, and generating an absence signal;
step four: extracting the existing signal and the non-existing signal, identifying the existing signal and the non-existing signal, acquiring data again when the non-existing signal is identified, extracting the record type data and corresponding record completion data, record use data, record operation data, record temperature data, record service life data, record speed data and record type data when the existing signal is identified, and transmitting the record type data, the record use data, the record operation data, the record temperature data, the record life data, the record speed data and the record type data to a battery analysis unit;
step five: extracting completion time data, use time data, running time data, real-time temperature data, standard life data and real-time speed data, and transmitting the completion time data, the use time data, the running time data, the real-time temperature data, the standard life data and the real-time speed data to a life judgment unit;
the battery analysis unit is used for performing battery analysis operation on the recorded model data, the recorded completion data, the recorded use data, the recorded operation data, the recorded temperature data, the recorded service life data, the recorded speed data and the recorded model data, and the specific operation process of the battery analysis operation is as follows:
k1: acquiring record model data, selecting corresponding record completion data and record use data according to the record model data, bringing the record completion data and the record use data into a difference calculation formula, calculating a difference between the record completion data and the record use data, and calibrating the difference as idle difference data;
k2: select out the different idle difference data of a plurality of among the above-mentioned K1 to it is inequality to set for idle difference data, and record operation data, record temperature data and record speed data are all the same, select out corresponding record life data, bring two different record life data into the difference formula of calculation, calculate the life difference, bring a plurality of life difference and a plurality of idle difference data into the formula of calculation: calculating u1 according to a calculation formula, wherein u1 represents an influence factor of idle time on the life, namely an idle influence factor, and substituting a plurality of idle influence factors into an average value calculation formula so as to calculate an idle influence factor average value;
k3: selecting a plurality of different recording operation data, setting the recording operation data to be different, wherein idle difference data, recording temperature data and recording speed data are the same, selecting corresponding recording service life data, bringing the two different recording operation data into a difference calculation formula, calculating an operation difference value, and bringing a plurality of corresponding service life difference values and a plurality of operation difference values into a calculation formula: calculating u2 according to a calculation formula, wherein u2 is an influence factor of the operating time on the life, namely an operating influence factor, and substituting a plurality of operating influence factors into an average value calculation formula so as to calculate an operating influence factor average value;
k4: select out the different record temperature data of a plurality of to it is inequality to set for record temperature data, and idle difference data, record operation data and record speed data are all the same, select out corresponding record life data, bring two different record temperature data into the mean value formula of calculating, calculate temperature mean value, bring two different temperature mean values into the difference value formula of calculating, calculate the temperature difference value, bring the life difference value and the several operation difference value that a plurality of corresponds into the formula of calculating: recording temperature data u 3-a life difference, calculating u3 according to a calculation formula, wherein u3 represents influence factors of different temperatures on life, namely temperature influence factors, and substituting a plurality of temperature influence factors into an average value calculation formula so as to calculate an average value of the temperature influence factors;
k5: selecting a plurality of different recording speed data in the K1, setting the recording speed data to be different, setting idle difference data, recording temperature data and recording operation data to be the same, selecting corresponding recording residual data, bringing two different recording speed data into a mean value calculation formula, calculating a speed mean value, bringing two different speed mean values into a difference value calculation formula, calculating a speed difference value, and bringing a plurality of corresponding service life difference values and a plurality of speed difference values into a calculation formula: calculating u4 according to a calculation formula, wherein u4 is a speed influence factor, namely an influence factor of speed on the service life, and substituting a plurality of speed influence factors into an average value calculation formula so as to calculate a speed influence factor average value;
k6: extracting an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value, and transmitting the idle influence factor mean value, the operation influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value to a service life judging unit;
the service life judging unit is used for judging and operating completion time data, service time data, running time data, real-time temperature data, standard service life data, real-time speed data, an idle influence factor mean value, a running influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value together, and the specific operation process of the judging operation is as follows:
h1: acquiring completion time data and use time data, and bringing the completion time data and the use time data into a difference calculation formula, thereby calculating a difference between the completion time data and the use time data and calibrating the difference as a storage time difference;
h2: acquiring real-time temperature data, bringing the temperatures of a plurality of different time points into an average value calculation formula, calculating the average temperatures of the different time points, and calibrating the average temperatures to be real-time temperature average values;
h3: acquiring real-time speed data, bringing a plurality of real-time speed data into an average value calculation formula, calculating an average value corresponding to the real-time speed data, and calibrating the average value as a real-time speed average value;
h4: extracting a real-time speed mean value, a real-time temperature mean value, a storage time difference value, standard life data and operation time data, and bringing the extracted data, an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value into a residual life calculation formula together:
h5: extracting actual residual life data and transmitting the actual residual life data to the intelligent equipment;
the intelligent device is used for receiving and displaying actual residual life data, and is specifically a tablet computer.
When the battery pack type identification device works, the acquisition unit acquires battery information related to the working of the battery pack and transmits the battery information to the type identification unit; the type identification unit acquires record information from a database, performs type identification operation on the record information and the battery information together, records completion data, record use data, record operation data, record temperature data, record life data, record speed data, record model data, completion time data, use time data, operation time data, real-time temperature data, standard life data and real-time speed data, transmits the completion time data, the use time data, the operation time data, the real-time temperature data, the standard life data and the real-time speed data to the life judgment unit, and transmits the record completion data, the record use data, the record operation data, the record temperature data, the record life data, the record speed data and the record model data to the battery analysis unit; the battery analysis unit performs battery analysis operation on the recorded model data, the recorded completion data, the recorded use data, the recorded operation data, the recorded temperature data, the recorded service life data, the recorded speed data and the recorded model data to obtain an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value, and transmits the idle influence factor mean value, the operation influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value to the service life judgment unit; the service life judging unit judges the completion time data, the use time data, the running time data, the real-time temperature data, the standard service life data, the real-time speed data, the idle influence factor mean value, the running influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value together to obtain actual remaining service life data, and transmits the actual remaining service life data to the intelligent equipment; and the intelligent equipment receives and displays the actual remaining life data.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. The on-line monitoring system for the electricity health state of the mining power battery pack is characterized by comprising a data acquisition unit, a database, a type identification unit, a battery analysis unit, a service life judgment unit and intelligent equipment;
the data acquisition unit is used for acquiring battery information related to the battery pack during working and transmitting the battery information to the type identification unit;
the database stores record information related to the operation of the battery pack, the type identifying unit obtains the record information from the database, and performing type identification operation on the recorded information and the battery information to obtain recorded data, recorded service data, recorded operation data, recorded temperature data, recorded service life data, recorded speed data, recorded model data, completion time data, service time data, operation time data, real-time temperature data, standard service life data and real-time speed data, the system comprises a service life judging unit, a battery analysis unit, a service life judging unit, a battery model judging unit and a battery management unit, wherein the service life judging unit is used for judging whether the service life of the battery is required to be recorded or not according to the service life data, the real-time temperature data, the standard service life data and the real-time speed data;
the battery analysis unit is used for carrying out battery analysis operation on the recorded model data, the recorded completion data, the recorded use data, the recorded operation data, the recorded temperature data, the recorded service life data, the recorded speed data and the recorded model data to obtain an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value, and transmitting the idle influence factor mean value, the operation influence factor mean value, the temperature influence factor mean value and the speed influence factor mean value to the service life judgment unit;
the service life judging unit is used for judging and operating completion time data, use time data, operation time data, real-time temperature data, standard service life data, real-time speed data, an idle influence factor mean value, an operation influence factor mean value, a temperature influence factor mean value and a speed influence factor mean value together to obtain actual remaining service life data and transmitting the actual remaining service life data to the intelligent equipment;
the intelligent device is used for receiving and displaying actual remaining life data.
2. The online monitoring system for the health state of the electric power used by the mining power battery pack according to claim 1, characterized in that the specific operation process of the type identification operation is as follows:
the method comprises the following steps: acquiring recording information, and calibrating the recording information to obtain recording completion data, recording use data, recording operation data, recording temperature data, recording service life data, recording speed data and recording model data;
step two: acquiring battery information, calibrating the battery information to obtain completion time data, use time data, running time data, real-time temperature data, standard service life data and real-time speed data, and transmitting the completion time data, the use time data, the running time data, the real-time temperature data, the standard service life data and the real-time speed data to a service life judging unit;
step three: extracting the collected model data, and matching the collected model data with the recorded model data in the recorded information, specifically, when the collected model data is matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is stored, and generating an existence signal, and when the collected model data cannot be matched in the recorded model data, judging that the recorded model data corresponding to the collected model data is not stored, and generating an absence signal;
step four: extracting the existing signal and the non-existing signal, identifying the existing signal and the non-existing signal, acquiring data again when the non-existing signal is identified, extracting the record type data and corresponding record completion data, record use data, record operation data, record temperature data, record service life data, record speed data and record type data when the existing signal is identified, and transmitting the record type data, the record use data, the record operation data, the record temperature data, the record life data, the record speed data and the record type data to a battery analysis unit;
step five: the completion time data, the use time data, the running time data, the real-time temperature data, the standard life data and the real-time speed data are extracted and transmitted to the life determination unit together.
3. The online monitoring system for the state of health of electricity consumption of the mining power battery pack according to claim 2, characterized in that the specific operation process of the battery analysis operation is as follows:
k1: acquiring record model data, selecting corresponding record completion data and record use data according to the record model data, bringing the record completion data and the record use data into a difference calculation formula, calculating a difference between the record completion data and the record use data, and calibrating the difference as idle difference data;
k2: select out the different idle difference data of a plurality of among the above-mentioned K1 to it is inequality to set for idle difference data, and record operation data, record temperature data and record speed data are all the same, select out corresponding record life data, bring two different record life data into the difference formula of calculation, calculate the life difference, bring a plurality of life difference and a plurality of idle difference data into the formula of calculation: calculating u1 according to a calculation formula, wherein u1 represents an influence factor of idle time on the life, namely an idle influence factor, and substituting a plurality of idle influence factors into an average value calculation formula so as to calculate an idle influence factor average value;
k3: according to the above calculation method of the average value of the idle influence factors in K2, the corresponding influence factors are calculated for the recorded operation data, the recorded temperature data and the recorded speed data, so as to obtain the average value of the operation influence factors, the average value of the temperature influence factors and the average value of the speed influence factors.
4. The online monitoring system for the health state of the power consumption of the mining power battery pack according to claim 3, characterized in that the specific operation process of the judgment operation is as follows:
h1: acquiring completion time data and use time data, and bringing the completion time data and the use time data into a difference calculation formula, thereby calculating a difference between the completion time data and the use time data and calibrating the difference as a storage time difference;
h2: acquiring real-time temperature data, bringing the temperatures of a plurality of different time points into an average value calculation formula, calculating the average temperatures of the different time points, and calibrating the average temperatures to be real-time temperature average values;
h3: acquiring real-time speed data, bringing a plurality of real-time speed data into an average value calculation formula, calculating an average value corresponding to the real-time speed data, and calibrating the average value as a real-time speed average value;
h4: extracting real-time speed mean value, real-time temperature mean value, storage time difference value, standard life data and operation time data, and bringing the real-time speed mean value, real-time temperature mean value, storage time difference value, standard life data and operation time data into a residual life calculation formula together with idle influence factor mean value, operation influence factor mean value, temperature influence factor mean value and speed influence factor mean value to obtain actual residual life data SYFruit of Chinese wolfberry；
H5: actual remaining life data is extracted.
5. The online monitoring system for the state of health of electricity consumption of the mining power battery pack according to claim 4, wherein the residual life calculation formula in H4 is specifically as follows:
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113933088A (en) * | 2021-10-08 | 2022-01-14 | 淮北矿业股份有限公司淮北选煤厂 | Intelligent sampling and pretreatment system for coal samples |
| CN117148169A (en) * | 2023-10-30 | 2023-12-01 | 东方旭能(山东)科技发展有限公司 | Battery service time prediction method, system, equipment and medium based on big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113933088A (en) * | 2021-10-08 | 2022-01-14 | 淮北矿业股份有限公司淮北选煤厂 | Intelligent sampling and pretreatment system for coal samples |
| CN113933088B (en) * | 2021-10-08 | 2023-04-25 | 淮北矿业股份有限公司淮北选煤厂 | Intelligent sampling and pretreatment system for coal samples |
| CN117148169A (en) * | 2023-10-30 | 2023-12-01 | 东方旭能(山东)科技发展有限公司 | Battery service time prediction method, system, equipment and medium based on big data |
| CN117148169B (en) * | 2023-10-30 | 2024-01-30 | 东方旭能(山东)科技发展有限公司 | Battery service time prediction method, system, equipment and medium based on big data |
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