CN115932610A - Battery monitoring method and device, terminal equipment and storage medium - Google Patents
Battery monitoring method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a battery monitoring method, a device, terminal equipment and a storage medium, wherein a power battery capacity monitoring instruction is received; calling a state of charge value and a battery capacity variation of the power battery which is recorded in history after the power battery is subjected to T-time standing in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour; and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of the power battery. The embodiment of the invention can estimate the battery capacity of the power battery more accurately, thereby monitoring the state of the power battery better.
Description
Technical Field
The invention relates to the field of power batteries, in particular to a battery monitoring method, a battery monitoring device, terminal equipment and a storage medium.
Background
With the development of society, people's environmental protection consciousness is gradually strengthened, and more people use new energy vehicle. At present, new energy vehicles are generally electric vehicles in China, electric energy stored in power batteries is mainly used for providing power for driving of the vehicles, and the new energy vehicles have the advantages of zero pollution and zero emission. Firstly, the battery power is needed to provide the real-time battery capacity of the power battery for estimating the remaining mileage in the using process of the electric vehicle, and the performance of the power battery is sharply declined after the battery capacity of the power battery is reduced to 80%, so that the electric vehicle is easy to lose efficacy, the electric vehicle cannot run, and even traffic accidents can be caused in serious cases. Secondly, the battery capacity, the self-discharge and the balance state are important characteristic parameters of the power battery, and accurate calculation of the parameters is beneficial to more accurately calculating the endurance mileage of the electric vehicle and improving the performance of the power battery, so that the service life of the power battery is prolonged. Therefore, how to accurately estimate the battery capacity, self-discharge, and equilibrium state is a problem that is quite important in the field of electric vehicles.
At present, a simple two-point method is generally used for estimating the battery capacity, the method mainly comprises the steps of calculating the state of charge value of the battery through the open-circuit voltage of the battery after standing, calculating the capacity through the capacity difference between two different state of charge values, and the method needs data screening, so that the battery capacity cannot be calculated through data with small changes of the state of charge values, and the method is easily influenced by individual data errors. Estimating self-discharge generally uses a voltage drop method, which mainly measures open-circuit voltages of the battery at two different moments through a sensor and determines self-discharge current according to the change of the measured voltage between the two different moments. Therefore, it is difficult for these two methods to estimate the battery capacity and self-discharge more accurately.
Disclosure of Invention
The invention provides a battery monitoring method, a battery monitoring device, terminal equipment and a storage medium, which can more accurately estimate the battery capacity of a power battery through linear regression analysis so as to better monitor the state of the power battery.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides a battery monitoring method, including:
receiving a power battery capacity monitoring instruction;
calling a state of charge value and a battery capacity variation of the power battery which is recorded in history after the power battery is subjected to T-time standing in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of the power battery.
As an improvement of the above scheme, the performing linear regression analysis on the adjusted state of charge value and battery capacity variation to obtain the battery capacity of the power battery specifically includes:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC n The historical state of charge value of the power battery after the power battery is stood for the nth time within the past m days;
the historical average value of the state of charge values of the power battery at k times in the past m days; Δ Ah n The battery capacity variation quantity of the power battery after the power battery is statically left for the nth time in the past m days is recorded; />
The historical average value of k battery capacity variation quantities of the power battery in the past m days.
As an improvement of the above scheme, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of the power battery after standing for T time; the state of charge-open circuit voltage curve table records one-to-one corresponding relation data of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of the power battery at the current moment in real time by using an ampere-hour integration method after the power battery is stood for T time, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
As an improvement of the above scheme, after obtaining the battery capacity of the power battery, the method further comprises the following steps:
and counting the latest acquired battery capacity and the battery capacity in the historical record to obtain the change trend of the battery capacity, and updating through a sliding calculation window.
In a second aspect, an embodiment of the present invention further provides another battery monitoring method, including:
receiving a monitoring instruction for the power battery;
calling a state of charge value and a battery capacity variable quantity of each single battery cell of the power battery, which are recorded historically, after standing for a T time each time within the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
As an improvement of the foregoing scheme, the performing linear regression analysis on the adjusted state of charge value and battery capacity variation to obtain the battery capacity of each single battery cell of the power battery specifically includes:
performing linear regression analysis on the called state of charge value and the battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing each single battery cell in the past m days in the T time history; SOC n Setting a state of charge value of each historical single battery cell after the battery cell is subjected to T-time standing for the nth time within the past m days;
is historyRecording an average value of k times of state of charge values of each single cell in the past m days; Δ Ah n The battery capacity variation of each historical single battery cell after standing for the nth time T within the past m days is recorded; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
As an improvement of the above scheme, after obtaining the battery capacity of each single battery cell of the power battery, the method further includes:
calculating to obtain the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so as to obtain the self-discharge of the power battery;
and counting the obtained self-discharge and the self-discharge in the history record to obtain the change trend of the self-discharge, and updating through a sliding calculation window.
As an improvement of the above scheme, the calculating, according to a linear relationship between the battery capacity of the single battery cell, the state of charge value, and the battery capacity variation, to obtain the self-discharge current of each single battery cell, so as to obtain the self-discharge of the power battery, specifically includes:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating to obtain the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the first intercept of the linear equation is calculated as:
the calculation formula of the second intercept of the linear equation is as follows:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
Averaging the previously p state-of-charge values of each cell over the past m days, which are historically recorded; intercept 2 Is a second intercept of the linear equation;
the historical average value of the q times of battery capacity variation of each single battery cell in the past m days is recorded;
the average value of the state of charge values of each single battery cell recorded historically q times within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each of the monomer cells historically experienced T-time standing within the past m days; slfDch _ A is the self-discharge current of each single battery cell; Δ T is a time difference, recorded historically, between the p-th time of standing for T time and the last time of standing for T time in the past m days of each single battery cell.
As an improvement of the above scheme, after obtaining the battery capacity of each single battery cell of the power battery, the method further includes:
calculating to obtain a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
under the condition that the state of charge values of all the single battery cells of the power battery are the same, acquiring the battery capacity variation of all the single battery cells; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
As an improvement of the above scheme, the calculating, according to the linear relationship between the battery capacity of the single battery cell, the state of charge value, and the battery capacity variation, to obtain the linear equation of each single battery cell specifically includes:
calculating to obtain the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
As an improvement of the above scheme, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of each single battery cell after standing for T time; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of each single battery cell of the power battery at the current moment in real time by using an ampere-hour integration method after each single battery cell of the power battery is subjected to T-time standing, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
In a third aspect, an embodiment of the present invention provides a battery monitoring apparatus, including:
the receiving module is used for receiving a power battery capacity monitoring instruction;
the calling module is used for calling the historical charge state value and the battery capacity variation of the power battery after the power battery is stood for each time within m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the capacity analysis module is used for carrying out linear regression analysis on the called charge state value and the battery capacity variation to obtain the battery capacity of the power battery.
As an improvement of the foregoing solution, the capacity analysis module is specifically configured to:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC n The historical state of charge value of the power battery after the power battery is stood for the nth time within the past m days;
the historical average value of the state of charge values of the power battery for k times in the past m days is recorded; Δ Ah n The power battery recorded for history is m in the pastThe battery capacity variation after the nth time of the day is subjected to T time standing; />
And the historical average value of the variation of the battery capacity of the power battery for k times in the past m days is recorded.
In a fourth aspect, an embodiment of the present invention further provides another battery monitoring apparatus, including:
the receiving module is used for receiving a monitoring instruction for the power battery;
the calling module is used for calling a state of charge value and a battery capacity variation of each single battery cell of the power battery after standing for T time in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the analysis module is used for carrying out linear regression analysis on the called charge state value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
As an improvement of the foregoing solution, the parsing module is specifically configured to:
performing linear regression analysis on the called state of charge value and battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing of each single battery cell within the past m days in the T time recorded in history; SOC n Setting a state of charge value of each historical single battery cell after the battery cell is subjected to T-time standing for the nth time within the past m days;
averaging the historical k-times state of charge values of each cell over the past m daysA value; Δ Ah n The battery capacity variation of each historical single battery cell after standing for the time T n within the past m days is recorded; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
As an improvement of the above scheme, the battery monitoring device further includes:
the estimation module is used for calculating the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so that the self-discharge of the power battery is obtained;
and the counting module is used for counting the obtained self-discharge and the self-discharge in the historical record to obtain the change trend of the self-discharge and updating the change trend through a sliding calculation window.
As an improvement of the above solution, the estimation module is specifically configured to:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating to obtain the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the first intercept of the linear equation is calculated as:
the calculation formula of the second intercept of the linear equation is as follows:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
The average value of the previous p charge state values of each single battery cell in the past m days is recorded in history; intercept 2 Is a second intercept of the linear equation;
the historical average value of the q times of battery capacity variation of each single battery cell in the past m days is recorded;
averaging the historical q-time SOC values of each single battery cell within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each of the monomer cells historically experienced T-time standing within the past m days; slfDch _ a is the self-discharge current of each single cell; and Δ T is a time difference, which is recorded historically, between the p-th time of standing for the T time and the last time of standing for the T time in the past m days.
As an improvement of the above solution, the battery monitoring device further comprises:
the calculation module is used for calculating a linear equation of each single battery cell according to the linear relationship among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
the analysis module is used for acquiring the battery capacity variation of each single battery cell under the condition that the charge state values of the single battery cells of the power battery are the same; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
As an improvement of the foregoing solution, the calculating module is specifically configured to:
calculating the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
In a fifth aspect, embodiments of the present invention correspondingly provide a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the battery monitoring method described above is implemented.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the above battery monitoring method.
Compared with the prior art, the battery monitoring method, the battery monitoring device, the terminal equipment and the storage medium disclosed by the embodiment of the invention have the advantages that the linear regression analysis is carried out on the state of charge value and the battery capacity variation of the power battery (or each single battery cell) which are recorded in a past period of time after each time of T time standing, so that the battery capacity of the power battery (or each single battery cell) is obtained, and the state of the power battery is better monitored. For example, the self-discharge current and the linear equation of each single battery cell can be calculated according to the linear relationship among the battery capacity, the state of charge value and the battery capacity variation of the single battery cell, so as to obtain the self-discharge of the power battery; under the condition that the state of charge values of all the single battery cells of the power battery are the same, acquiring the battery capacity variation of all the single battery cells; analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery; the embodiment of the invention uses more charge state values and battery capacity variation data for statistical analysis, can effectively avoid the influence caused by individual data errors, can more accurately estimate the battery capacity of the power battery, and can calculate the self-discharge of the power battery and obtain the battery capacity variation among the single battery cells to analyze the equilibrium state of the power battery on the basis of the battery capacity of each single battery cell, thereby avoiding the equilibrium calculation error caused by the battery capacity deviation of the power battery, and simultaneously being convenient for carrying out equilibrium control on the power battery by taking any charge state value as an equilibrium target point, and realizing more accurate monitoring of the state of the power battery.
Drawings
Fig. 1 is a schematic flow chart of a battery monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of another battery monitoring method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a battery monitoring device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of another battery monitoring device according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a terminal device according to a fifth embodiment 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.
It is noted that the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Referring to fig. 1, fig. 1 is a schematic flow chart of a battery monitoring method according to an embodiment of the present invention, where the battery monitoring method includes steps S11 to S13:
s11: receiving a power battery capacity monitoring instruction;
optionally, the user inputs a power battery capacity monitoring instruction, the vehicle forwards the power battery capacity monitoring instruction to the cloud server, and the server executes the following steps after receiving the power battery capacity monitoring instruction.
S12: calling a historical state of charge value and a battery capacity variable quantity of the power battery after the power battery is subjected to T-time standing every time within m days in the past; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
the state of charge value and the battery capacity variation after the T-time standing are the state of charge value and the battery capacity variation at the moment immediately after the power battery stands for the T-time. In the past m days of the power battery, the state of charge value and the battery capacity variation after standing for the T time every time are recorded historically, and the standing for the T time can be inconsistent at different temperatures, generally half an hour to three hours; the more days of m days, the more accurate the calculation of the data, but the more susceptible the self-discharge of the battery, so that it is generally about 1 to 100 days.
S13: and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of the power battery.
It should be noted that, it is considered that there is a linear relationship between the total battery capacity, the state of charge change and the battery capacity change, wherein the state of charge value and the battery capacity change should be obtained by unrelated methods. Generally, the state of charge value can be obtained by looking up a table of open circuit voltages, and the capacity can be obtained by ampere-hour integration or the like.
Preferably, in step S13, the method specifically includes:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC n The historical state of charge value of the power battery after the power battery is stood for the nth time within the past m days;
the historical average value of the state of charge values of the power battery at k times in the past m days; Δ Ah n The battery capacity variation quantity of the power battery after the power battery is statically left for the nth time in the past m days is recorded; />
Average historical change of battery capacity of the power battery over k times in past m daysThe value is obtained. />
Specifically, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of the power battery after standing for T time; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is the variation obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of the power battery at the current moment in real time by using an ampere-hour integration method after the power battery is subjected to standing for T time and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
In the concrete implementation, in the battery use process, the vehicle can identify specific working conditions, such as standing for a long time. The ampere-hour integration method is to integrate the current value acquired by the current sensor in the time dimension to obtain the accumulated charge-discharge capacity. In practice, for example, if the sampling frequency of the current sensor is 10ms, the cumulative charge/discharge capacity is increased by the capacity of current sample value × 10/3600000 (Ah) every 10 ms.
Further, after obtaining the battery capacity of the power battery, the method further comprises:
and counting the latest acquired battery capacity and the battery capacity in the historical record to obtain the change trend of the battery capacity, and updating through a sliding calculation window.
In specific implementation, the obtained battery capacity variation trend can be used for battery performance analysis and fault early warning, and can also be returned to a vehicle to improve the calculation accuracy of the controller.
According to the battery monitoring method provided by the embodiment of the invention, the battery capacity of the power battery is obtained by performing linear regression analysis on the state of charge value and the battery capacity variation recorded in a period of time in the past after the power battery is subjected to T-time standing every time, namely, more data of the state of charge value and the battery capacity variation are used for statistical analysis, so that the influence caused by individual data errors can be effectively avoided, and the battery capacity of the power battery can be estimated more accurately.
Referring to fig. 2, fig. 2 is a schematic flow chart of another battery monitoring method according to a second embodiment of the present invention, where the battery monitoring method includes steps S21 to S23:
s21: receiving a monitoring instruction for the power battery;
optionally, the user inputs a power battery monitoring instruction, the vehicle forwards the instruction to the cloud server, and the server executes the following steps after receiving the power battery monitoring instruction.
S22: calling a state of charge value and a battery capacity variation of each single battery cell of the power battery after standing for T time in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
it should be noted that the power battery includes a plurality of single cells, and the state of charge value and the battery capacity variation after standing for the T time are the state of charge value and the battery capacity variation at the moment immediately after the single cell stands for the T time. In the past m days, the historically recorded charge state value and battery capacity variation after standing for the T time each time of the single battery cell can be inconsistent after standing for the T time at different temperatures, and generally the standing time is half an hour to three hours; the more days of m days, the more accurate the calculation of the data, but the more susceptible it is to the self-discharge of the battery, so it is generally 7 days to 30 days, and it is not necessary to exceed 100 days at last.
S23: and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
It should be noted that, it is considered that there is a linear relationship between the total battery capacity, the state of charge change and the battery capacity change, wherein the state of charge value and the battery capacity change should be obtained by unrelated methods. Generally, the state of charge value can be obtained by looking up a table of open circuit voltages, and the capacity can be obtained by ampere-hour integration or the like.
Optionally, in the step S23, the method specifically includes:
performing linear regression analysis on the called state of charge value and the battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing each single battery cell in the past m days in the T time history; SOC n Setting a state of charge value of each historical single battery cell after the battery cell is subjected to T-time standing for the nth time within the past m days;
averaging the state of charge values of each cell in the past m days, which are recorded historically, k times; Δ Ah n The battery capacity variation of each historical single battery cell after standing for the nth time T within the past m days is recorded; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
Further, after obtaining the battery capacity of each single battery cell of the power battery, the method further includes:
calculating to obtain the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so as to obtain the self-discharge of the power battery;
and counting the obtained self-discharge and the self-discharge in the historical record to obtain the change trend of the self-discharge, and updating through a sliding calculation window.
In specific implementation, the obtained self-discharge variation trend can be used for battery performance analysis and fault early warning, and can also be returned to the vehicle to improve the calculation accuracy of the controller.
Optionally, the calculating, according to a linear relationship between the battery capacity of the single battery cell, the state of charge value, and the battery capacity variation, to obtain the self-discharge current of each single battery cell, so as to obtain the self-discharge of the power battery, specifically includes:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the calculation formula of the first intercept of the linear equation is as follows:
the calculation formula of the second intercept of the linear equation is as follows:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
The previous p charges of each single cell recorded for history within the past m daysAn average value of the state values; intercept 2 Is a second intercept of the linear equation;
the average value of the capacity variation of each single battery cell recorded historically for q times within the past m days;
the average value of the state of charge values of each single battery cell recorded historically q times within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each of the monomer cells historically experienced T-time standing within the past m days; slfDch _ A is the self-discharge current of each single battery cell; Δ T is a time difference, recorded historically, between the p-th time of standing for T time and the last time of standing for T time in the past m days of each single battery cell.
Further, after obtaining the battery capacity of each single battery cell of the power battery, the method further includes:
calculating to obtain a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
under the condition that the state of charge values of all the single battery cells of the power battery are the same, acquiring the battery capacity variation of all the single battery cells; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
Optionally, the calculating, according to the linear relationship between the battery capacity of the single battery cell, the state of charge value, and the battery capacity variation, to obtain the linear equation of each single battery cell specifically includes:
calculating to obtain the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
In a specific implementation, the power battery may perform balancing control of the power battery with any state of charge value as a balancing target point, for example, if two unit cells in the power battery are at 90% soc, the unit cell No. 1 is 20Ah higher than the unit cell No. 2, and it is desired that the two unit cells are balanced at 90% soc, the unit cell No. 1 is controlled to be charged for 20Ah alone, or the unit cell No. 2 is controlled to be discharged for 20Ah alone.
Specifically, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of each single battery cell after standing for T time; the state of charge-open circuit voltage curve table records one-to-one corresponding relation data of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of each single battery cell of the power battery at the current moment in real time by using an ampere-hour integration method after each single battery cell of the power battery is subjected to T-time standing, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
According to the battery monitoring method provided by the embodiment of the invention, linear regression analysis is carried out on the state of charge value and the battery capacity variation of each single battery cell of the power battery after each time of standing for T time recorded in a period of time in the past to obtain the battery capacity of each single battery cell, then the self-discharge current and the linear equation of each single battery cell are calculated according to the linear relation among the battery capacity, the state of charge value and the battery capacity variation of each single battery cell, so that the self-discharge of the power battery is obtained, then the battery capacity variation of each single battery cell is obtained under the condition that the state of charge values of each single battery cell of the power battery are the same, the relative deviation of the battery capacity variation among the single battery cells is analyzed, and the equilibrium state of the power battery is obtained; the embodiment of the invention uses more charge state values and battery capacity variation data for statistical analysis, can effectively avoid the influence caused by individual data errors, has higher accuracy and robustness, and can more accurately estimate the self-discharge of the power battery.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a battery monitoring device according to a third embodiment of the present invention, where the battery monitoring device includes:
the receiving module 31 is used for receiving a power battery capacity monitoring instruction;
the calling module 32 is configured to call a state of charge value and a battery capacity variation of the power battery, which are recorded historically, after the power battery is left standing for each time within m days in the past; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the capacity analysis module 33 is configured to perform linear regression analysis on the adjusted state of charge value and battery capacity variation to obtain the battery capacity of the power battery.
Preferably, the capacity analysis module 33 is specifically configured to:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC n The historical state of charge value of the power battery after the power battery is stood for the nth time within the past m days;
the historical average value of the state of charge values of the power battery at k times in the past m days; Δ Ah n The battery capacity variation quantity of the power battery after the power battery is statically left for the nth time in the past m days is recorded; />
The historical average value of k battery capacity variation quantities of the power battery in the past m days.
Specifically, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of the power battery after standing for T time; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is the variation obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of the power battery at the current moment in real time by using an ampere-hour integration method after the power battery is subjected to standing for T time and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
Further, the battery monitoring device further includes:
and the counting module is used for counting the latest obtained battery capacity and the battery capacity in the historical record to obtain the change trend of the battery capacity and updating the change trend through a sliding calculation window.
The battery monitoring device provided in the third embodiment of the present invention can implement all processes of the battery monitoring method in the first embodiment, and the functions and technical effects of the modules in the device are respectively the same as those of the battery monitoring method in the first embodiment, and are not described herein again.
Referring to fig. 4, fig. 4 is a schematic structural diagram of another battery monitoring device according to a fourth embodiment of the present invention, the battery monitoring device includes:
the receiving module 41 is used for receiving a monitoring instruction for the power battery;
the calling module 42 is configured to call a state of charge value and a battery capacity variation of each single battery cell of the power battery, which are recorded in history, after standing for T time each time in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the analysis module 43 is configured to perform linear regression analysis on the obtained state of charge value and battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
Optionally, the parsing module 43 is specifically configured to:
performing linear regression analysis on the called state of charge value and the battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing each single battery cell in the past m days in the T time history; SOC n Setting a state of charge value of each historical single battery cell after the battery cell is subjected to T-time standing for the nth time within the past m days;
averaging the state of charge values of each cell in the past m days, which are recorded historically, k times; Δ Ah n For each of the history recordsThe battery capacity variation of each single battery cell after standing for the nth time T within the past m days; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
Further, the battery monitoring device further includes:
the estimation module is used for calculating the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so that the self-discharge of the power battery is obtained;
and the counting module is used for counting the obtained self-discharge and the self-discharge in the historical record to obtain the change trend of the self-discharge and updating the change trend through a sliding calculation window.
Optionally, the estimation module is specifically configured to:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the calculation formula of the first intercept of the linear equation is as follows:
the calculation formula of the second intercept of the linear equation is as follows:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
The average value of the previous p charge state values of each single battery cell in the past m days is recorded in history; intercept 2 Is a second intercept of the linear equation;
the average value of the capacity variation of each single battery cell recorded historically for q times within the past m days;
the average value of the state of charge values of each single battery cell recorded historically q times within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each individual cell historically experiences T time standing within the past m days; slfDch _ a is the self-discharge current of each single cell; and Δ T is a time difference, which is recorded historically, between the p-th time of standing for the T time and the last time of standing for the T time in the past m days.
Further, the battery monitoring device further includes:
the calculation module is used for calculating a linear equation of each single battery cell according to the linear relationship among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
the analysis module is used for acquiring the battery capacity variation of each single battery cell under the condition that the charge state values of the single battery cells of the power battery are the same; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
Optionally, the calculation module is specifically configured to:
calculating the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
Specifically, the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of each single battery cell after standing for T time; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is the variation obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of each single battery cell of the power battery at the current moment in real time by using an ampere-hour integration method after each single battery cell of the power battery is subjected to T-time standing, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
The battery monitoring device provided in the fourth embodiment of the present invention can implement all the processes of the battery monitoring method of the second embodiment, and the functions and technical effects of each module in the device are respectively the same as those of the battery monitoring method of the second embodiment, and are not described herein again.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a terminal device according to a fifth embodiment of the present invention. The terminal device 5 of this embodiment includes: a processor 51, a memory 52 and a computer program stored in said memory 52 and executable on said processor 51. The processor 51, when executing the computer program, implements the steps in the above-described battery monitoring method embodiments. Alternatively, the processor 51 implements the functions of the modules in the above-described battery monitoring apparatus embodiment when executing the computer program.
Illustratively, the computer program may be divided into one or more modules, which are stored in the memory 52 and executed by the processor 51 to accomplish the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the terminal device 5.
The terminal device 5 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device 5 may include, but is not limited to, a processor 51 and a memory 52. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a terminal device, and does not constitute a limitation to the terminal device, and may include more or less components than those shown, or some components may be combined, or different components, for example, the terminal device 5 may further include an input-output device, a network access device, a bus, etc.
The Processor 51 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general processor may be a microprocessor or the processor may be any conventional processor or the like, and the processor 51 is a control center of the terminal device 5 and connects various parts of the whole terminal device 5 by using various interfaces and lines.
The memory 52 can be used for storing the computer programs and/or modules, and the processor 51 implements various functions of the terminal device 5 by running or executing the computer programs and/or modules stored in the memory 52 and calling data stored in the memory 52. The memory 52 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 52 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the module integrated by the terminal device 5 can be stored in a computer readable storage medium if it is implemented in the form of software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow in the method according to the above embodiments may be realized by a computer program, which may be stored in a computer readable storage medium, and the computer program may realize the steps of the above method embodiments when executed by the processor 51. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
The embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the battery monitoring method according to the above embodiment.
In summary, the embodiment of the present invention discloses a battery monitoring apparatus, a terminal device, and a storage medium, in which a linear regression analysis is performed on a state of charge value and a battery capacity variation of a power battery (or each single battery cell) after each time of standing for a T time, which are recorded in a past period of time, to obtain a battery capacity of the power battery (or each single battery cell), so as to better monitor a state of the power battery. For example, the self-discharge current and the linear equation of each single battery cell can be calculated according to the linear relationship among the battery capacity, the state of charge value and the battery capacity variation of the single battery cell, so as to obtain the self-discharge of the power battery; under the condition that the state of charge values of all the single battery cells of the power battery are the same, acquiring the battery capacity variation of all the single battery cells; analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery; the embodiment of the invention uses more charge state values and battery capacity variation data for statistical analysis, can effectively avoid the influence caused by individual data errors, can more accurately estimate the battery capacity of the power battery, and can calculate the self-discharge of the power battery and obtain the battery capacity variation among the single battery cells to analyze the equilibrium state of the power battery on the basis of the battery capacity of each single battery cell, thereby avoiding the equilibrium calculation error caused by the battery capacity deviation of the power battery, and simultaneously being convenient for carrying out equilibrium control on the power battery by taking any charge state value as an equilibrium target point, and realizing more accurate monitoring of the state of the power battery.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (21)
1. A battery monitoring method, comprising:
receiving a power battery capacity monitoring instruction;
calling a state of charge value and a battery capacity variation of the power battery which is recorded in history after the power battery is subjected to T-time standing in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of the power battery.
2. The battery monitoring method according to claim 1, wherein the performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of the power battery specifically comprises:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC n The historical state of charge value of the power battery after the power battery is stood for the nth time within the past m days;
the historical average value of the state of charge values of the power battery at k times in the past m days; Δ Ah n The battery capacity variation quantity of the power battery after the power battery is statically left for the nth time in the past m days is recorded;
the historical average value of k battery capacity variation quantities of the power battery in the past m days.
3. The battery monitoring method according to claim 1, wherein the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of the power battery after the power battery is subjected to T-time standing; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of the power battery at the current moment in real time by using an ampere-hour integration method after the power battery is stood for T time, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
4. The battery monitoring method of claim 1, after obtaining the battery capacity of the power battery, further comprising:
and counting the latest acquired battery capacity and the battery capacity in the historical record to obtain the change trend of the battery capacity, and updating through a sliding calculation window.
5. A battery monitoring method, comprising:
receiving a monitoring instruction for the power battery;
calling a state of charge value and a battery capacity variation of each single battery cell of the power battery after standing for T time in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
6. The battery monitoring method according to claim 5, wherein the performing linear regression analysis on the adjusted state of charge value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery specifically includes:
performing linear regression analysis on the called state of charge value and the battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing each single battery cell in the past m days in the T time history; SOC n Is said of historyThe charge state value of each single battery cell after standing for the nth time T within the past m days;
averaging the state of charge values of each cell in the past m days, which are recorded historically, k times; Δ Ah n The battery capacity variation of each historical single battery cell after standing for the time T n within the past m days is recorded; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
7. The battery monitoring method of claim 6, after obtaining the battery capacity of each cell of the power battery, further comprising:
calculating to obtain the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so as to obtain the self-discharge of the power battery;
and counting the obtained self-discharge and the self-discharge in the history record to obtain the change trend of the self-discharge, and updating through a sliding calculation window.
8. The battery monitoring method according to claim 7, wherein the calculating, according to a linear relationship among the battery capacities of the unit cells, the state of charge values, and the battery capacity variation amounts, a self-discharge current of each unit cell is obtained, so as to obtain self-discharge of the power battery, specifically including:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating to obtain the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the first intercept of the linear equation is calculated as:
the second intercept of the linear equation is calculated as:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
The average value of the previous p charge state values of each single battery cell in the past m days is recorded in history; intercept 2 Is a second intercept of the linear equation; />
The average value of the capacity variation of each single battery cell recorded historically for q times within the past m days; />
The average value of the state of charge values of each single battery cell recorded historically q times within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each of the monomer cells historically experienced T-time standing within the past m days; slfDch _ a is the self-discharge current of each single cell; and Δ T is a time difference, which is recorded historically, between the p-th time of standing for the T time and the last time of standing for the T time in the past m days. />
9. The battery monitoring method of claim 6, after obtaining the battery capacity of each cell of the power battery, further comprising:
calculating to obtain a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
under the condition that the state of charge values of all the single battery cells of the power battery are the same, acquiring the battery capacity variation of all the single battery cells; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
10. The battery monitoring method according to claim 9, wherein the calculating a linear equation of each cell according to a linear relationship between a battery capacity of a cell, a state of charge value, and a battery capacity variation amount specifically includes:
calculating the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
11. The battery monitoring method according to claim 5, wherein the state of charge value is obtained by querying a preset state of charge-open circuit voltage curve table according to the open circuit voltage of each single cell of the power battery after standing for T time; the state of charge-open circuit voltage curve table records data of one-to-one correspondence of a plurality of open circuit voltages and state of charge values;
and the battery capacity variation is obtained by calculating the accumulated charging capacity and the accumulated discharging capacity of each single battery cell of the power battery at the current moment in real time by using an ampere-hour integration method after each single battery cell of the power battery is subjected to T-time standing, and subtracting the accumulated charging capacity and the accumulated discharging capacity from each other.
12. A battery monitoring device, comprising:
the receiving module is used for receiving a power battery capacity monitoring instruction;
the calling module is used for calling the historical charge state value and the battery capacity variation of the power battery after the power battery is stood for each time within m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the capacity analysis module is used for carrying out linear regression analysis on the called charge state value and the battery capacity variation to obtain the battery capacity of the power battery.
13. The battery monitoring device of claim 12, wherein the capacity resolution module is specifically configured to:
performing linear regression analysis on the adjusted state of charge value and battery capacity variation according to a least square formula to obtain the battery capacity of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of the power battery; k is the total number of times of the power battery which is recorded historically and is subjected to standing for T time within the past m days; SOC (system on chip) n The historical state of charge value of the power battery after the power battery is subjected to T time standing for the nth time within the past m days;
the historical average value of the state of charge values of the power battery at k times in the past m days; Δ Ah n The battery capacity variation quantity of the power battery after the power battery is statically left for the nth time in the past m days is recorded;
the historical average value of k battery capacity variation quantities of the power battery in the past m days.
14. A battery monitoring device, comprising:
the receiving module is used for receiving a command for monitoring the power battery;
the calling module is used for calling a state of charge value and a battery capacity variation of each single battery cell of the power battery after standing for T time in the past m days; wherein m is more than or equal to 1 and less than or equal to 100, and T is more than or equal to 0.1 hour;
and the analysis module is used for carrying out linear regression analysis on the called charge state value and the battery capacity variation to obtain the battery capacity of each single battery cell of the power battery.
15. The battery monitoring device of claim 14, wherein the parsing module is specifically configured to:
performing linear regression analysis on the called state of charge value and battery capacity variation according to a least square method formula to obtain the battery capacity of each single battery cell of the power battery; the least square method formula is as follows:
in the formula, CAP is the battery capacity of each single battery cell; k is the total number of times of standing each single battery cell in the past m days in the T time history; SOC n Setting a state of charge value of each historical single battery cell after the battery cell is subjected to T-time standing for the nth time within the past m days;
averaging the state of charge values of each cell in the past m days, which are recorded historically, k times; Δ Ah n The battery capacity variation of each historical single battery cell after standing for the time T n within the past m days is recorded; />
And averaging the historical k times of battery capacity variation of each single battery cell in the past m days.
16. The battery monitoring device of claim 15, further comprising:
the estimation module is used for calculating the self-discharge current of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells, so that the self-discharge of the power battery is obtained;
and the counting module is used for counting the obtained self-discharge and the self-discharge in the historical record to obtain the change trend of the self-discharge and updating the change trend through a sliding calculation window.
17. The battery monitoring device of claim 16, wherein the estimation module is specifically configured to:
calculating to obtain a first intercept and a second intercept of a linear equation of each single battery cell according to a linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
calculating to obtain the self-discharge current of each single battery cell according to the first intercept and the second intercept so as to obtain the self-discharge of the power battery;
the calculation formula of the first intercept of the linear equation is as follows:
the second intercept of the linear equation is calculated as:
the calculation formula of the self-discharge current of each single battery cell is as follows:
in the formula, intercept 1 Is a first intercept of the linear equation;
the average value of the previous p times of battery capacity variation of each single battery cell in the past m days is recorded in history; />
For each of said monomers of historyAverage value of the previous p charge state values of the battery cell in the past m days; intercept 2 Is a second intercept of the linear equation; />
The average value of the capacity variation of each single battery cell recorded historically for q times within the past m days; />
Averaging the historical q-time SOC values of each single battery cell within the past m days; p + q = k, wherein p = q or p-1= q, k is the total number of times that each of the monomer cells historically experienced T-time standing within the past m days; slfDch _ A is the self-discharge current of each single battery cell; and Δ T is a time difference, which is recorded historically, between the p-th time of standing for the T time and the last time of standing for the T time in the past m days.
18. The battery monitoring device of claim 15, further comprising:
the calculation module is used for calculating a linear equation of each single battery cell according to the linear relationship among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
the analysis module is used for acquiring the battery capacity variation of each single battery cell under the condition that the charge state values of the single battery cells of the power battery are the same; and analyzing the relative deviation of the battery capacity variation among the single battery cores to obtain the equilibrium state of the power battery.
19. The battery monitoring device of claim 18, wherein the computing module is specifically configured to:
calculating to obtain the intercept of a linear equation of each single battery cell according to the linear relation among the battery capacity, the charge state value and the battery capacity variation of the single battery cells;
substituting the calculated intercept to obtain a linear equation of each monomer battery cell;
wherein, the calculation formula of the intercept of the linear equation is as follows:
the linear equation of each single battery cell is as follows:
ΔAh＝CAP×SOC+Intercept，
in the formula, intercept is the Intercept of a linear equation; the SOC is the state of charge value of each single battery cell; and Δ Ah is the battery capacity variation of each single battery cell.
20. A terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the battery monitoring method of any one of claims 1-11 when executing the computer program.
21. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the battery monitoring method according to any one of claims 1-11.
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