CN117318209A - Battery pack multi-mode operation control system based on data analysis - Google Patents
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The invention relates to the technical field of multi-mode operation control of battery packs, in particular to a multi-mode operation control system of a battery pack based on data analysis, which comprises a management and control center, a dynamic analysis unit, a static analysis unit, a charging supervision unit, a discharging supervision unit, an early warning unit, an integrated management and control analysis unit and a management and control unit; according to the invention, the states of the battery pack are subjected to supervision analysis from two angles of dynamic and static states, namely, the dynamic risk assessment coefficient and the static state risk assessment coefficient are analyzed through management and control risk assessment analysis, so that management and control grades of the battery pack are reasonably divided, rationalization and targeted management and control are performed according to comprehensive assessment results, the accuracy of analysis results is improved, and further, the control effect of the battery pack is improved, and deep analysis is performed from two angles of charging and discharging, so that the comprehensiveness of analysis data is improved.
Description
Technical Field
The invention relates to the technical field of battery pack control, in particular to a battery pack multi-mode operation control system based on data analysis.
Background
The storage battery pack is a power supply which outputs electric energy in a discharging mode and absorbs and recovers the electric energy in a charging mode, a plurality of storage batteries are generally used as a backup power supply, the storage batteries are connected in series and in parallel, the parallel storage batteries require the same voltage of each battery, the output voltage is equal to the voltage of one battery, the parallel storage batteries can provide stronger current, and the series storage batteries have no excessive requirements;
the battery pack is a chemical battery capable of being charged and discharged repeatedly, and can provide a power source for power utilization systems such as a transportation system, a communication power system and the like, but the battery pack in the prior art cannot be reasonably controlled according to the state of the battery pack in the use process, so that the normal use and the use effect of the battery pack are affected, and the analysis result error of the battery pack state evaluation system in the prior art is large, the analysis is not comprehensive enough, and the management and control rationality and the accuracy of the battery pack are further affected;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a multi-mode operation control system of a battery pack based on data analysis, which is used for solving the technical defects, wherein the state of the battery pack is subjected to supervision analysis from two angles of dynamic state and static state, namely, the dynamic risk assessment coefficient and the static state risk assessment coefficient are analyzed through management and control risk assessment analysis, so that the management and control grade of the battery pack is reasonably divided, the management and control are reasonably and pertinently carried out according to the comprehensive assessment result, the accuracy of the analysis result is improved, and the control effect of the battery pack is further achieved.
The aim of the invention can be achieved by the following technical scheme: the multi-mode operation control system of the battery pack based on data analysis comprises a management and control center, a dynamic analysis unit, a static analysis unit, a charging supervision unit, a discharging supervision unit, an early warning unit, an integrated management and control analysis unit and a management and control unit;
when a management and control command is generated by a management and control center, the management and control command is sent to a dynamic analysis unit and a static analysis unit, the dynamic analysis unit immediately collects charging data and discharging data of the battery pack after receiving the management and control command, wherein the charging data comprises a shell charging temperature and a charging multiplying power of the battery pack, the discharging data comprises a discharging current and a discharging internal resistance value of the battery pack, dynamic integration state evaluation analysis is carried out on the charging data and the discharging data, the charging data and the discharging data of the battery pack are respectively sent to a charging supervision unit and a discharging supervision unit, the charging supervision unit immediately carries out charging state evaluation analysis on the charging data of the battery pack after receiving the charging data, and an obtained early warning signal is sent to a warning unit through the dynamic analysis unit;
the discharge supervision unit immediately carries out discharge state evaluation analysis on the discharge data of the battery pack after receiving the discharge data, and sends an obtained risk signal to the early warning unit through the dynamic analysis unit;
the dynamic analysis unit performs dynamic integration state evaluation analysis to obtain a dynamic risk evaluation coefficient D, and sends the dynamic risk evaluation coefficient D to the integration management and control analysis unit;
the static analysis unit immediately collects idle data of the battery pack after receiving the management and control instruction, wherein the idle data comprises an external environment interference value, an average voltage drop rate and a static temperature risk value of the battery pack, carries out safety supervision evaluation analysis on the idle data, sends an obtained static risk evaluation coefficient J to the integrated management and control analysis unit, and sends an obtained abnormal signal to the early warning unit;
and after receiving the dynamic risk assessment coefficient D and the static risk assessment coefficient J, the integrated management and control analysis unit immediately carries out management and control risk assessment analysis on the dynamic risk assessment coefficient D and the static risk assessment coefficient J, and sends the obtained primary management and control signal, secondary management and control signal and tertiary management and control signal to the management and control unit.
Preferably, the charge state evaluation and analysis process of the charge supervision unit is as follows:
the first step: acquiring the duration from the beginning of the charging of the battery pack to the ending of the charging, marking the duration as the charging duration, dividing the charging duration into i sub-time nodes, wherein i is a natural number larger than zero, acquiring the shell charging temperature of the battery pack in each sub-time node, taking time as an X axis, taking the shell charging temperature as a Y axis, establishing a rectangular coordinate system, drawing a shell charging temperature curve in a dot drawing manner, acquiring charging risk data from the shell charging temperature curve, wherein the charging risk data comprises the duration of the part, corresponding to the shell charging temperature reaching a preset shell charging temperature threshold, exceeding the preset duration, the duration of the part, corresponding to the shell charging temperature exceeding the preset shell charging temperature threshold, and the area surrounded by the part, corresponding to the part, of the shell charging temperature curve exceeding the preset shell charging temperature curve threshold, and carrying out data normalization processing on the charging risk data, thereby acquiring the charging runaway value of the battery pack in the charging duration;
and a second step of: marking each single battery in the battery pack as g, wherein g is a natural number larger than zero, acquiring the charging rate of each single battery in the charging time period, comparing the charging rate with a preset charging rate threshold, if the ratio of the charging rate to the preset charging rate threshold is smaller than one, marking the total number of the single batteries corresponding to the ratio of the charging rate to the preset charging rate threshold as k, k epsilon g, marking the ratio of k to g as a battery risk value, and comparing the charging runaway risk value, the battery risk value, the preset charging runaway risk value threshold and the preset battery risk value threshold which are recorded and stored in the battery risk value and the battery risk value threshold to analyze the battery risk value:
if the charging runaway risk value is smaller than the preset charging runaway risk value threshold value and the battery risk value is smaller than the preset battery risk value threshold value, no signal is generated;
and if the charging runaway risk value is greater than or equal to a preset charging runaway risk value threshold or the battery risk value is greater than or equal to a preset battery risk value threshold, generating an early warning signal.
Preferably, the discharge state evaluation and analysis process of the discharge supervision unit is as follows:
collecting the duration from the beginning to the ending of the discharge of the battery pack, marking the duration as a discharge threshold, dividing the discharge threshold into o sub-time nodes, wherein o is a natural number greater than zero, obtaining the discharge current of each single battery in each sub-time node, further obtaining the discharge rate of each single battery in the discharge threshold, constructing a set A of the discharge rates of each single battery, further obtaining the average value of the set A, and marking the average value as the average discharge rate;
obtaining a discharge internal resistance value of the battery pack in a discharge threshold, and obtaining a factory discharge internal resistance value of the battery pack when the battery pack is shipped, so as to obtain a wear assessment value of the battery pack according to the discharge internal resistance value and the factory discharge internal resistance value, comparing the wear assessment value with a preset wear assessment value threshold, if the value obtained by subtracting the preset wear assessment value threshold from the wear assessment value is larger than zero, marking the value obtained by subtracting the preset wear assessment value threshold from the wear assessment value as a discharge inefficiency value, and comparing the average discharge rate and the discharge inefficiency value with a preset average discharge rate threshold and a preset discharge inefficiency value threshold which are recorded and stored in the battery pack:
if the ratio of the average discharge rate to the preset average discharge rate threshold is less than one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is less than one, generating no signal;
and if the ratio of the average discharge rate to the preset average discharge rate threshold is greater than or equal to one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is greater than or equal to one, generating a risk signal.
Preferably, the dynamic integration state evaluation analysis process of the dynamic analysis unit is as follows:
respectively calling a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value from a charging supervision unit and a discharging supervision unit, and respectively marking the charging runaway risk value, the battery risk value, the average discharging rate and the discharging inefficiency value as CF, DF, PF and FX;
according to the formulaObtaining a dynamic risk assessment coefficient, wherein a1, a2, a4 and a5 are preset scale factor coefficients of a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value respectively, a1, a2, a4 and a5 are positive numbers larger than zero, a3 is a preset fault-tolerant correction coefficient, the value is 1.662, and D is the dynamic risk assessment coefficient.
Preferably, the safety supervision and evaluation analysis process of the static analysis unit is as follows:
s1: acquiring the time length from the opening idle time to the ending idle time of the battery pack, marking the time length as a time threshold, acquiring an external environment interference value WH of the battery pack in the time threshold, wherein the external environment interference value refers to the product value obtained by carrying out data normalization processing on the part of the external environment humidity value and the environment dust content value of the battery pack exceeding the preset environment dust content value threshold;
s12: obtaining the average voltage drop rate of the battery pack in the time threshold, comparing the average voltage drop rate with a preset average voltage drop rate threshold, and if the average voltage drop rate is larger than the preset average voltage drop rate threshold, marking the ratio of the part of the average voltage drop rate larger than the preset average voltage drop rate threshold to the preset average voltage drop rate threshold as a voltage drop risk value XZ;
s13: acquiring a static temperature risk value JW of the battery pack in a time threshold, wherein the static temperature risk value refers to the difference value between the lowest shell temperature and the highest shell temperature of the battery pack in the time threshold;
s14: obtaining a static risk assessment coefficient J according to a formula, and comparing the static risk assessment coefficient J with a preset static risk assessment coefficient threshold value recorded and stored in the static risk assessment coefficient J:
if the static risk assessment coefficient J is smaller than or equal to a preset static risk assessment coefficient threshold value, no signal is generated;
if the static risk assessment coefficient J is larger than a preset static risk assessment coefficient threshold value, an abnormal signal is generated.
Preferably, the management risk assessment analysis process of the integrated management analysis unit is as follows:
acquiring a dynamic risk assessment coefficient D and a static risk assessment coefficient J;
according to the formulaObtaining comprehensive state risk assessment coefficients, wherein alpha and beta are respectivelyThe ratio coefficients of the dynamic risk assessment coefficient and the static risk assessment coefficient are respectively 1.886 and 1.776, Z is a comprehensive state risk assessment coefficient, and the comprehensive state risk assessment coefficient Z is compared with a preset comprehensive state risk assessment coefficient interval which is recorded and stored in the comprehensive state risk assessment coefficient Z:
if the comprehensive state risk assessment coefficient Z is larger than the maximum value in the preset comprehensive state risk assessment coefficient interval, generating a primary management and control signal;
if the comprehensive state risk assessment coefficient Z is located in a preset comprehensive state risk assessment coefficient interval, generating a secondary management and control signal;
and if the comprehensive state risk assessment coefficient Z is smaller than the minimum value in the preset comprehensive state risk assessment coefficient interval, generating a three-level control signal.
The beneficial effects of the invention are as follows:
(1) The invention carries out supervision analysis on the state of the battery pack from two angles of dynamic and static states, namely analyzes the dynamic risk assessment coefficient and the static risk assessment coefficient through management and control risk assessment analysis so as to reasonably divide the management and control grades of the battery pack, rationalize and pertinently manage and control the battery pack according to the comprehensive assessment result, and simultaneously help to improve the accuracy of the analysis result so as to control the battery pack;
(2) In dynamic angle analysis, the invention is favorable for improving the comprehensiveness of analysis data by carrying out deep analysis from the angles of charge and discharge, namely collecting charge data and discharge data for analysis, carrying out early warning supervision in a feedback mode so as to improve the supervision and early warning effect on the battery pack, carrying out data integration on dynamic charge and discharge through dynamic integration state evaluation analysis so as to provide data support for overall state evaluation of the battery pack, and carrying out safety supervision evaluation analysis through collecting static idle data, thereby being favorable for carrying out early warning management on the battery pack in time on one hand and being favorable for improving the comprehensiveness of overall state evaluation analysis of the battery pack on the other hand.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a flow chart of the system of the present invention;
fig. 2 is a partial analysis reference diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Example 1:
referring to fig. 1 to 2, the invention discloses a multi-mode operation control system of a battery pack based on data analysis, which comprises a management and control center, a dynamic analysis unit, a static analysis unit, a charging monitoring unit, a discharging monitoring unit, an early warning unit, an integrated management and control analysis unit and a management and control unit, wherein the management and control center is in unidirectional communication connection with the dynamic analysis unit and the static analysis unit, the dynamic analysis unit is in bidirectional communication connection with the charging monitoring unit and the discharging monitoring unit, the dynamic analysis unit and the static analysis unit are in unidirectional communication connection with the early warning unit, the dynamic analysis unit and the static analysis unit are in unidirectional communication connection with the integrated management and control analysis unit, and the integrated management and control analysis unit is in unidirectional communication connection with the management and control unit;
when a management and control command is generated by a management and control center, the management and control command is sent to a dynamic analysis unit and a static analysis unit, the dynamic analysis unit immediately collects charging data and discharging data of the battery pack after receiving the management and control command, wherein the charging data comprise a shell charging temperature and a charging multiplying power of the battery pack, the discharging data comprise a discharging current and a discharging internal resistance value of the battery pack, dynamic integration state evaluation analysis is carried out on the charging data and the discharging data, the charging data and the discharging data of the battery pack are respectively sent to a charging supervision unit and a discharging supervision unit, the charging supervision unit immediately carries out charging state evaluation analysis on the charging data of the battery pack after receiving the charging data so as to improve the charging supervision effect on the battery pack, and the specific charging state evaluation analysis process is as follows:
acquiring the duration from the beginning of the charging time to the ending of the charging time of the battery pack, marking the duration as the charging duration, dividing the charging duration into i sub-time nodes, wherein i is a natural number larger than zero, acquiring the charging temperature of the shell of the battery pack in each sub-time node, taking the time as an X axis, taking the charging temperature of the shell as a Y axis, establishing a rectangular coordinate system, drawing a charging temperature curve of the shell in a dot drawing manner, acquiring charging risk data from the charging temperature curve of the shell, wherein the charging risk data comprises the duration of the part, corresponding to the charging temperature of the shell, exceeding the preset charging temperature threshold of the shell, of the duration of the part, corresponding to the charging temperature of the shell, exceeding the preset charging temperature threshold of the shell, and the area surrounded by the charging temperature curve of the shell exceeding the preset charging temperature threshold of the shell, and carrying out data normalization processing on the charging risk data, so as to acquire the charging risk value of the battery pack in the charging duration of the charging runaway, and the charging runaway risk value is an influence parameter reflecting the charging abnormality of the battery pack;
marking each single battery in the battery pack as g, wherein g is a natural number larger than zero, acquiring the charging rate of each single battery in the charging time period, comparing the charging rate with a preset charging rate threshold, if the ratio of the charging rate to the preset charging rate threshold is smaller than one, marking the total number of the single batteries corresponding to the ratio of the charging rate to the preset charging rate threshold as k, k epsilon g, and marking the ratio of k and g as a battery risk value, wherein the larger the value of the battery risk value is, the larger the abnormal risk of battery charging is;
and comparing the charging runaway risk value and the battery risk value with a preset charging runaway risk value threshold value and a preset battery risk value threshold value which are recorded and stored in the charging runaway risk value and the battery risk value, and analyzing the charging runaway risk value and the battery risk value:
if the charging runaway risk value is smaller than the preset charging runaway risk value threshold value and the battery risk value is smaller than the preset battery risk value threshold value, no signal is generated;
if the charging runaway risk value is greater than or equal to a preset charging runaway risk value threshold value or the battery risk value is greater than or equal to a preset battery risk value threshold value, generating an early warning signal, sending the early warning signal to an early warning unit through a dynamic analysis unit, and immediately carrying out early warning display in a mode of the word "battery pack charging abnormality" after the early warning unit receives the early warning signal, so that charging early warning is carried out on a battery pack in time, and the supervision early warning effect on the battery pack is improved;
the discharge monitoring unit immediately carries out discharge state evaluation analysis on the discharge data of the battery pack after receiving the discharge data so as to improve the discharge monitoring effect on the battery pack, and the specific discharge state evaluation analysis process is as follows:
collecting the duration from the beginning discharge time to the ending discharge time of the battery pack, marking the duration as a discharge threshold, dividing the discharge threshold into o sub-time nodes, wherein o is a natural number larger than zero, acquiring the discharge current of each single battery in each sub-time node, further acquiring the discharge rate of each single battery in the discharge threshold, constructing a set A of the discharge rates of each single battery, further acquiring the average value of the set A, and marking the average value as an average discharge rate, wherein the average discharge rate is an influence parameter reflecting the overall discharge state of the battery pack;
obtaining a discharge internal resistance value of the battery pack in a discharge threshold value, and obtaining a factory discharge internal resistance value of the battery pack when the battery pack is shipped, so as to obtain a wear assessment value of the battery pack according to the discharge internal resistance value and the factory discharge internal resistance value, comparing the wear assessment value with a preset wear assessment value threshold value, if the value obtained by subtracting the preset wear assessment value threshold value from the wear assessment value is larger than zero, marking the value obtained by subtracting the preset wear assessment value threshold value from the wear assessment value as a discharge inefficiency value, wherein the larger the value of the discharge inefficiency value is, the larger the abnormal risk of the battery pack is, and comparing the average discharge rate and the discharge inefficiency value with the preset average discharge rate threshold value and the preset discharge inefficiency value threshold value which are recorded and stored in the battery pack.
If the ratio of the average discharge rate to the preset average discharge rate threshold is less than one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is less than one, generating no signal;
if the ratio of the average discharge rate to the preset average discharge rate threshold is greater than or equal to one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is greater than or equal to one, generating a risk signal, sending the risk signal to an early warning unit through a dynamic analysis unit, and immediately carrying out early warning display in a mode of the word 'abnormal discharge of the battery pack' after the early warning unit receives the risk signal, so that the battery pack is timely subjected to discharge supervision early warning, and the discharge safety of the battery pack is passed;
the dynamic integration state evaluation analysis process of the dynamic analysis unit is as follows:
respectively calling a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value from a charging supervision unit and a discharging supervision unit, and respectively marking the charging runaway risk value, the battery risk value, the average discharging rate and the discharging inefficiency value as CF, DF, PF and FX;
according to the formulaAnd obtaining a dynamic risk assessment coefficient, wherein a1, a2, a4 and a5 are respectively preset scale factor coefficients of a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value, the scale factor coefficients are used for correcting deviation of various parameters in a formula calculation process, so that calculation results are more accurate, a1, a2, a4 and a5 are positive numbers larger than zero, a3 is a preset fault tolerance correction coefficient, the value is 1.662, D is the dynamic risk assessment coefficient, and the dynamic risk assessment coefficient D is sent to an integrated management and control analysis unit.
Example 2:
the static analysis unit immediately collects idle data of the battery pack after receiving the management and control instruction, wherein the idle data comprises an external environment interference value, an average voltage drop rate and a static temperature risk value of the battery pack, and carries out safety supervision evaluation analysis on the idle data so as to provide data support for overall state evaluation of the battery pack, and the specific safety supervision evaluation analysis process comprises the following steps:
acquiring the time length from the opening idle time to the ending idle time of the battery pack, marking the time length as a time threshold, acquiring an external environment interference value WH of the battery pack in the time threshold, wherein the external environment interference value refers to the product value obtained after data normalization processing of the external environment humidity value and the part of the environment dust content value of the battery pack exceeding the preset environment dust content value threshold, and the larger the numerical value of the external environment interference value WH is, the larger the abnormal risk of the battery pack is;
obtaining the average voltage drop rate of the battery pack in the time threshold, comparing the average voltage drop rate with a preset average voltage drop rate threshold, and if the average voltage drop rate is larger than the preset average voltage drop rate threshold, marking the ratio of the part of the average voltage drop rate larger than the preset average voltage drop rate threshold to the preset average voltage drop rate threshold as a voltage drop risk value, wherein the mark is XZ, and the voltage drop risk value XZ is an influence parameter reflecting the state of the battery pack;
acquiring a static temperature risk value JW of the battery pack in a time threshold, wherein the static temperature risk value refers to the difference value between the lowest temperature of the shell and the highest temperature of the shell of the battery pack in the time threshold, and the larger the value of the static temperature risk value JW is, the larger the abnormal risk of the battery pack is;
according to the formulaObtaining static risk assessment coefficients, wherein b1, b2 and b3 are preset weight coefficients of an external environment interference value, a voltage drop risk value and a static temperature risk value respectively, b4 is a preset correction factor coefficient, b1, b2, b3 and b4 are positive numbers larger than zero, J is a static risk assessment coefficient, the static risk assessment coefficient J is sent to an integrated management analysis unit, and the static risk assessment coefficient J is compared with a preset static risk assessment coefficient threshold value recorded and stored in the static risk assessment coefficient J:
if the static risk assessment coefficient J is smaller than or equal to a preset static risk assessment coefficient threshold value, no signal is generated;
if the static risk assessment coefficient J is larger than a preset static risk assessment coefficient threshold value, generating an abnormal signal, sending the abnormal signal to an early warning unit, and immediately carrying out early warning display in a mode of word "battery pack placement abnormality" after the early warning unit receives the abnormal signal, so that the battery pack is managed in time, and meanwhile, the provision of data support for overall state assessment of the battery pack is facilitated;
the integrated management and control analysis unit immediately carries out management and control risk assessment analysis on the dynamic risk assessment coefficient D and the static risk assessment coefficient J after receiving the dynamic risk assessment coefficient D and the static risk assessment coefficient J so as to strengthen the rationality and the accuracy of safety management of the target battery pack, and the specific management and control risk assessment analysis process is as follows:
acquiring a dynamic risk assessment coefficient D and a static risk assessment coefficient J;
according to the formulaObtaining a comprehensive state risk assessment coefficient, wherein alpha and beta are proportional coefficients of a dynamic risk assessment coefficient and a static risk assessment coefficient respectively, alpha and beta are 1.886 and 1.776 respectively, Z is the comprehensive state risk assessment coefficient, and the comprehensive state risk assessment coefficient Z is compared with a preset comprehensive state risk assessment coefficient interval recorded and stored in the comprehensive state risk assessment coefficient Z:
if the comprehensive state risk assessment coefficient Z is larger than the maximum value in the preset comprehensive state risk assessment coefficient interval, generating a primary management and control signal;
if the comprehensive state risk assessment coefficient Z is located in a preset comprehensive state risk assessment coefficient interval, generating a secondary management and control signal;
if the comprehensive state risk assessment coefficient Z is smaller than the minimum value in the preset comprehensive state risk assessment coefficient interval, generating a third-level control signal, wherein the control degrees corresponding to the third-level control signal, the third-level control signal and the first-level control signal are sequentially reduced, the third-level control signal and the first-level control signal are sent to the control unit, and the control unit immediately makes preset early warning operation corresponding to the third-level control signal, the second-level control signal and the first-level control signal after receiving the third-level control signal, the second-level control signal and the first-level control signal so as to perform rationalization and targeted control according to the comprehensive assessment result, and meanwhile, the accuracy of an analysis result is improved, and further the control effect of the battery pack is achieved;
in summary, the invention performs supervision analysis on the state of the battery pack from two angles of dynamic and static states, namely analyzes the dynamic risk assessment coefficient D and the static risk assessment coefficient J through management and control risk assessment analysis, so as to reasonably divide the management and control grades of the battery pack, rationalize and pertinently manage and control the battery pack according to the comprehensive assessment result, and simultaneously help to improve the accuracy of the analysis result, and further control the battery pack through the control effect; in dynamic angle analysis, through carrying out deep analysis from two angles of charging and discharging, the comprehensive of analysis data is facilitated, namely, the charging data and the discharging data are collected and analyzed, and early warning supervision is carried out in a feedback mode, so that the supervision early warning effect on the battery pack is improved, and data integration is carried out on dynamic charging and discharging through dynamic integration state evaluation analysis, so that data support is provided for overall state evaluation of the battery pack, and through collecting static idle data and carrying out safety supervision evaluation analysis, on one hand, early warning management on the battery pack is facilitated timely, and on the other hand, the comprehensive of overall state evaluation analysis of the battery pack is facilitated.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected. The above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (6)
1. The multi-mode operation control system of the battery pack based on data analysis is characterized by comprising a management and control center, a dynamic analysis unit, a static analysis unit, a charging supervision unit, a discharging supervision unit, an early warning unit, an integrated management and control analysis unit and a management and control unit;
when a management and control command is generated by a management and control center, the management and control command is sent to a dynamic analysis unit and a static analysis unit, the dynamic analysis unit immediately collects charging data and discharging data of the battery pack after receiving the management and control command, wherein the charging data comprises a shell charging temperature and a charging multiplying power of the battery pack, the discharging data comprises a discharging current and a discharging internal resistance value of the battery pack, dynamic integration state evaluation analysis is carried out on the charging data and the discharging data, the charging data and the discharging data of the battery pack are respectively sent to a charging supervision unit and a discharging supervision unit, the charging supervision unit immediately carries out charging state evaluation analysis on the charging data of the battery pack after receiving the charging data, and an obtained early warning signal is sent to a warning unit through the dynamic analysis unit;
the discharge supervision unit immediately carries out discharge state evaluation analysis on the discharge data of the battery pack after receiving the discharge data, and sends an obtained risk signal to the early warning unit through the dynamic analysis unit;
the dynamic analysis unit performs dynamic integration state evaluation analysis to obtain a dynamic risk evaluation coefficient D, and sends the dynamic risk evaluation coefficient D to the integration management and control analysis unit;
the static analysis unit immediately collects idle data of the battery pack after receiving the management and control instruction, wherein the idle data comprises an external environment interference value, an average voltage drop rate and a static temperature risk value of the battery pack, carries out safety supervision evaluation analysis on the idle data, sends an obtained static risk evaluation coefficient J to the integrated management and control analysis unit, and sends an obtained abnormal signal to the early warning unit;
and after receiving the dynamic risk assessment coefficient D and the static risk assessment coefficient J, the integrated management and control analysis unit immediately carries out management and control risk assessment analysis on the dynamic risk assessment coefficient D and the static risk assessment coefficient J, and sends the obtained primary management and control signal, secondary management and control signal and tertiary management and control signal to the management and control unit.
2. The battery multi-mode operation control system based on data analysis according to claim 1, wherein the charge state evaluation analysis process of the charge supervision unit is as follows:
the first step: acquiring the duration from the beginning of the charging of the battery pack to the ending of the charging, marking the duration as the charging duration, dividing the charging duration into i sub-time nodes, wherein i is a natural number larger than zero, acquiring the shell charging temperature of the battery pack in each sub-time node, taking time as an X axis, taking the shell charging temperature as a Y axis, establishing a rectangular coordinate system, drawing a shell charging temperature curve in a dot drawing manner, acquiring charging risk data from the shell charging temperature curve, wherein the charging risk data comprises the duration of the part, corresponding to the shell charging temperature reaching a preset shell charging temperature threshold, exceeding the preset duration, the duration of the part, corresponding to the shell charging temperature exceeding the preset shell charging temperature threshold, and the area surrounded by the part, corresponding to the part, of the shell charging temperature curve exceeding the preset shell charging temperature curve threshold, and carrying out data normalization processing on the charging risk data, thereby acquiring the charging runaway value of the battery pack in the charging duration;
and a second step of: marking each single battery in the battery pack as g, wherein g is a natural number larger than zero, acquiring the charging rate of each single battery in the charging time period, comparing the charging rate with a preset charging rate threshold, if the ratio of the charging rate to the preset charging rate threshold is smaller than one, marking the total number of the single batteries corresponding to the ratio of the charging rate to the preset charging rate threshold as k, k epsilon g, marking the ratio of k to g as a battery risk value, and comparing the charging runaway risk value, the battery risk value, the preset charging runaway risk value threshold and the preset battery risk value threshold which are recorded and stored in the battery risk value and the battery risk value threshold to analyze the battery risk value:
if the charging runaway risk value is smaller than the preset charging runaway risk value threshold value and the battery risk value is smaller than the preset battery risk value threshold value, no signal is generated;
and if the charging runaway risk value is greater than or equal to a preset charging runaway risk value threshold or the battery risk value is greater than or equal to a preset battery risk value threshold, generating an early warning signal.
3. The multi-mode operation control system for a battery pack based on data analysis according to claim 2, wherein the discharge state evaluation and analysis process of the discharge supervision unit is as follows:
collecting the duration from the beginning to the ending of the discharge of the battery pack, marking the duration as a discharge threshold, dividing the discharge threshold into o sub-time nodes, wherein o is a natural number greater than zero, obtaining the discharge current of each single battery in each sub-time node, further obtaining the discharge rate of each single battery in the discharge threshold, constructing a set A of the discharge rates of each single battery, further obtaining the average value of the set A, and marking the average value as the average discharge rate;
obtaining a discharge internal resistance value of the battery pack in a discharge threshold, and obtaining a factory discharge internal resistance value of the battery pack when the battery pack is shipped, so as to obtain a wear assessment value of the battery pack according to the discharge internal resistance value and the factory discharge internal resistance value, comparing the wear assessment value with a preset wear assessment value threshold, if the value obtained by subtracting the preset wear assessment value threshold from the wear assessment value is larger than zero, marking the value obtained by subtracting the preset wear assessment value threshold from the wear assessment value as a discharge inefficiency value, and comparing the average discharge rate and the discharge inefficiency value with a preset average discharge rate threshold and a preset discharge inefficiency value threshold which are recorded and stored in the battery pack:
if the ratio of the average discharge rate to the preset average discharge rate threshold is less than one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is less than one, generating no signal;
and if the ratio of the average discharge rate to the preset average discharge rate threshold is greater than or equal to one, and the ratio of the discharge inefficiency value to the preset discharge inefficiency value threshold is greater than or equal to one, generating a risk signal.
4. A multi-mode operation control system for a battery pack based on data analysis according to claim 3, wherein the dynamic integrated state evaluation analysis process of the dynamic analysis unit is as follows:
respectively calling a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value from a charging supervision unit and a discharging supervision unit, and respectively marking the charging runaway risk value, the battery risk value, the average discharging rate and the discharging inefficiency value as CF, DF, PF and FX;
according to the formulaObtaining a dynamic risk assessment coefficient, wherein a1, a2, a4 and a5 are preset scale factor coefficients of a charging runaway risk value, a battery risk value, an average discharging rate and a discharging inefficiency value respectively, a1, a2, a4 and a5 are positive numbers larger than zero, a3 is a preset fault-tolerant correction coefficient, the value is 1.662, and D is the dynamic risk assessment coefficient.
5. The battery multi-mode operation control system based on data analysis according to claim 1, wherein the safety supervision evaluation analysis process of the static analysis unit is as follows:
s1: acquiring the time length from the opening idle time to the ending idle time of the battery pack, marking the time length as a time threshold, acquiring an external environment interference value WH of the battery pack in the time threshold, wherein the external environment interference value refers to the product value obtained by carrying out data normalization processing on the part of the external environment humidity value and the environment dust content value of the battery pack exceeding the preset environment dust content value threshold;
s12: obtaining the average voltage drop rate of the battery pack in the time threshold, comparing the average voltage drop rate with a preset average voltage drop rate threshold, and if the average voltage drop rate is larger than the preset average voltage drop rate threshold, marking the ratio of the part of the average voltage drop rate larger than the preset average voltage drop rate threshold to the preset average voltage drop rate threshold as a voltage drop risk value XZ;
s13: acquiring a static temperature risk value JW of the battery pack in a time threshold, wherein the static temperature risk value refers to the difference value between the lowest shell temperature and the highest shell temperature of the battery pack in the time threshold;
s14: obtaining a static risk assessment coefficient J according to a formula, and comparing the static risk assessment coefficient J with a preset static risk assessment coefficient threshold value recorded and stored in the static risk assessment coefficient J:
if the static risk assessment coefficient J is smaller than or equal to a preset static risk assessment coefficient threshold value, no signal is generated;
if the static risk assessment coefficient J is larger than a preset static risk assessment coefficient threshold value, an abnormal signal is generated.
6. The multi-mode operation control system of a battery pack based on data analysis according to claim 1, wherein the management risk assessment analysis process of the integrated management analysis unit is as follows:
acquiring a dynamic risk assessment coefficient D and a static risk assessment coefficient J;
according to the formulaObtaining a comprehensive state risk assessment coefficient, wherein alpha and beta are proportional coefficients of a dynamic risk assessment coefficient and a static risk assessment coefficient respectively, alpha and beta are 1.886 and 1.776 respectively, Z is the comprehensive state risk assessment coefficient, and the comprehensive state risk assessment coefficient Z is compared with a preset comprehensive state risk assessment coefficient interval recorded and stored in the comprehensive state risk assessment coefficient Z:
if the comprehensive state risk assessment coefficient Z is larger than the maximum value in the preset comprehensive state risk assessment coefficient interval, generating a primary management and control signal;
if the comprehensive state risk assessment coefficient Z is located in a preset comprehensive state risk assessment coefficient interval, generating a secondary management and control signal;
and if the comprehensive state risk assessment coefficient Z is smaller than the minimum value in the preset comprehensive state risk assessment coefficient interval, generating a three-level control signal.
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| CN117706413A (en) * | 2024-02-02 | 2024-03-15 | 青岛元通电子有限公司 | Standard power module operation self-checking system based on data analysis |
| CN117937700A (en) * | 2024-03-21 | 2024-04-26 | 超耐斯(深圳)新能源集团有限公司 | Lithium battery charge and discharge safety early warning system based on Internet |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117706413A (en) * | 2024-02-02 | 2024-03-15 | 青岛元通电子有限公司 | Standard power module operation self-checking system based on data analysis |
| CN117706413B (en) * | 2024-02-02 | 2024-04-19 | 青岛元通电子有限公司 | Standard power module operation self-checking system based on data analysis |
| CN117937700A (en) * | 2024-03-21 | 2024-04-26 | 超耐斯(深圳)新能源集团有限公司 | Lithium battery charge and discharge safety early warning system based on Internet |
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