CN117214734A - Battery cell inconsistency determining method and device and electronic equipment - Google Patents
Battery cell inconsistency determining method and device and electronic equipment Download PDFInfo
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Abstract
The invention discloses a method and a device for determining inconsistency of battery cells, and electronic equipment, wherein the method comprises the following steps: acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell; at any moment, determining whether the battery is in a charging end stage or a discharging end stage at the current moment according to the data information of each battery cell; selecting at least one charge end stage and discharge end stage according to a time period input by a user; calculating the outlier degree of each cell in the selected at least one charging end stage and discharging end stage by setting an algorithm and the data information of each cell in the selected at least one charging end stage and discharging end stage; and respectively determining m electric cores with highest outliers in each charging end stage and discharging end stage according to the outliers of each electric core in at least one selected charging end stage and discharging end stage, so as to facilitate the analysis of the electric core inconsistency in the battery by the auxiliary technicians.
Description
Technical Field
The invention relates to the technical field of battery detection, in particular to a method and a device for determining inconsistency of battery cells and electronic equipment.
Background
With global control of greenhouse gas emissions, various countries have added lines to reduce greenhouse gas emissions, and renewable energy sources are increasingly used, particularly in the field of power supply. Most renewable energy sources, such as wind power generation, photovoltaic power generation and the like, have the problem of unstable power generation, so that the participation of an energy storage system is needed, the wind and electricity abandoning is reduced, and the effect of stabilizing a power grid is achieved. Lithium ion batteries have been widely used in the field of energy storage in recent years due to their high charge/discharge efficiency, high energy density, and the like. In order to meet the voltage use requirement of the energy storage system, the lithium ion battery system is usually formed by connecting a plurality of single battery cells in series, and is limited by the current process level, the self characteristics of the lithium ion battery and the like, and certain inconsistencies exist in the single battery cells, and the inconsistencies gradually deteriorate in the long-term use process, so that the problems of available energy reduction, power limitation and the like of the battery system are caused.
Disclosure of Invention
The invention provides a method and a device for determining the inconsistency of battery cells, and electronic equipment, and provides a quantized single battery cell outlier degree evaluation method, so that the most outlier battery cells are identified, and the analysis of the inconsistency of the battery cells in the battery by technicians is facilitated.
According to an aspect of the present invention, there is provided a battery cell inconsistency determining method, the battery comprising a plurality of cells connected in series; the method for determining the inconsistency of battery cells comprises the following steps:
acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell;
at any moment, determining whether the battery is in a charging end stage or a discharging end stage at the current moment according to the data information of each battery cell;
selecting at least one of the charge end stage and the discharge end stage according to a time period input by a user;
calculating the outlier of each cell in the selected at least one charging end stage by setting algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage by setting algorithm and the data information of each cell in the selected at least one discharging end stage;
determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
Optionally, at any time, determining, according to the data information of each electrical core, whether the battery is at a charging end stage or a discharging end stage at the current time includes:
when the voltage of the battery cell with the largest voltage is larger than a charging voltage threshold value and the battery is in a charging state according to the current direction of the battery cell, determining that the battery is in the charging terminal stage at the current time;
and under the current moment, when the voltage of the battery cell with the minimum voltage is smaller than a discharge voltage threshold value and the battery is in a discharge state according to the current direction of the battery cell, determining that the battery is in the discharge end stage under the current moment.
Optionally, at any time, determining, according to the data information of each electrical core, whether the battery is at a charging end stage or a discharging end stage at the current time includes:
according to the h moment and a plurality of moments after the h moment, determining that the voltage of the battery cell with the maximum voltage at the h moment in the battery is gradually increased, and determining that the h moment is in the charging tail end stage when the voltage change rate of the battery cell with the maximum voltage at the h moment is larger than a set voltage change threshold value;
And determining that the h moment is in the discharge end stage when the voltage of the cell with the minimum voltage gradually decreases and the voltage change rate of the cell with the minimum voltage is larger than the set voltage change threshold according to the h moment and a plurality of moments after the h moment.
Optionally, the selecting at least one of the charging end stage and the discharging end stage according to a time period input by a user includes:
according to the time period input by the user, at least one charging end stage and at least one discharging end stage closest to the end time of the time period input by the user are selected.
Optionally, the setting algorithm at least includes: z score method, local outlier factor algorithm and pearson correlation coefficient algorithm.
Optionally, the setting algorithm is a Z-score method, the calculating the outlier of each cell in the selected at least one charging end stage by the setting algorithm and the data information of each cell in the selected at least one discharging end stage includes:
Calculating the average value of the voltages of the cells at the ith moment according to the voltages of the cells at the ith moment in the selected charging end phase or discharging end phase, wherein i=1, 2, … … and L, 1 is the starting moment of the selected charging end phase or discharging end phase, and L is the ending moment of the selected charging end phase or discharging end phase;
determining the Z fraction of each battery cell at the ith moment according to the voltage of each battery cell at the ith moment, the average value of the voltages of the battery cells at the ith moment and the standard deviation of the voltages of the battery cells at the ith moment;
and for any cell, calculating the average value of the Z scores of the cells at all moments in the selected charging end stage or discharging end stage as the outlier of the cell.
Optionally, after determining m cells with highest outliers in each charging end stage according to the outliers in each cell in at least one selected charging end stage, and determining m cells with highest outliers in each discharging end stage according to the outliers in each cell in at least one selected discharging end stage, the method includes:
Generating data information curves corresponding to m electric cores according to data information of m electric cores with highest outliers, which are determined in at least one charging end stage, in a time period input by a user, wherein the data information curves at least comprise a voltage curve and a current curve;
and generating data information curves corresponding to the m electric cores according to the data information of the m electric cores with the highest outliers, which are determined in at least one discharge end stage, in the time period input by the user, wherein the data information curves at least comprise a voltage curve and a current curve.
Optionally, after determining m cells with highest outliers in each charging end stage according to the outliers in each cell in at least one selected charging end stage, and determining m cells with highest outliers in each discharging end stage according to the outliers in each cell in at least one selected discharging end stage, the method further includes:
and when the outlier degree of the battery cell is larger than a set outlier degree threshold, determining that the battery cell is an outlier monomer.
According to another aspect of the present invention, there is provided a battery cell inconsistency determining device, the battery including a plurality of cells connected in series, the battery cell inconsistency determining device comprising:
The information acquisition module is used for acquiring the data information of each battery cell in real time, wherein the data information at least comprises the voltage and the current of the battery cell;
the terminal determining module is used for determining whether the battery is in a charging terminal stage or a discharging terminal stage at the current moment according to the data information of each battery cell at any moment;
a selection module for selecting at least one of the charge end stage and the discharge end stage according to a time period input by a user;
the outlier calculating module is used for calculating the outlier of each cell in the selected at least one charging end stage through a setting algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage through the setting algorithm and the data information of each cell in the selected at least one discharging end stage;
the analysis module is used for determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, and determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the battery cell inconsistency determination method of any of the embodiments of the present invention.
According to the technical scheme, after determining whether any moment is in a charging end stage or a discharging end stage according to the data information of each battery cell, at least one charging end stage and at least one discharging end stage are selected according to a time period input by a user, and the outlier degree of each battery cell is calculated according to the data information of each battery cell in each selected charging end stage or each selected discharging end stage, so that the outlier degree of each battery cell in each selected charging end stage or each selected discharging end stage can be obtained, the outlier degree of each battery cell in each charging end stage or each selected discharging end stage is sequenced, and a plurality of battery cells with the largest outlier are obtained and used for assisting a technician in subsequent positioning abnormal monomers and further analysis.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for determining inconsistency of battery cells according to an embodiment of the present invention;
FIG. 2 is a flowchart of another method for determining battery cell inconsistency according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for determining inconsistency of battery cells according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device implementing a method for determining battery cell inconsistency according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," 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.
Fig. 1 is a flowchart of a method for determining battery cell inconsistency according to an embodiment of the present invention, where the method may be implemented by a device for determining battery cell inconsistency, and the device for determining battery cell inconsistency may be implemented in hardware and/or software. The battery comprises a plurality of cells connected in series, as shown in fig. 1, the method comprising:
S110: and acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell.
Each cell in the battery is connected to a battery management system (Battery Management System, BMS) through which the voltage and current of each cell is obtained.
S120: at any moment, according to the data information of each battery cell, determining whether the battery is in a charging end stage or a discharging end stage at the current moment.
And marking whether the battery cells are in a charging end stage or a discharging end stage according to the voltage, current and other data of each battery cell. Methods of determining whether a cell is in a charge end phase or a discharge end phase include, but are not limited to: voltage threshold method, single voltage difference method, current commutation method, etc. The starting time of the charging end stage and the charging end time are different by a first set time threshold, and the end time of the charging end stage may be the charging end time. The start time of the discharge end phase and the discharge end time differ by a second set time threshold, and the end time of the discharge end phase may be the discharge end time. The charging end time can be considered when the charging current is zero during the charging of the battery, and the discharging end time can be considered when the discharging current is zero during the discharging of the battery.
S130: at least one charge end stage and discharge end stage is selected according to a time period input by a user.
The time period of the user input is set according to the user's needs, and illustratively, if the user wants to view the states of the individual cells in the battery from 2023, 2, 23, 8:00 to 2023, 2, 25, 8:00, at least one charge end stage and at least one discharge end stage are arbitrarily selected from 2023, 2, 23, 8:00 to 2023, 2, 25, 8:00. Illustratively, 2 charge end phases and 2 discharge end phases may be selected in this embodiment.
S140: calculating the outlier of each cell in the selected at least one charging end stage by setting the algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage by setting the algorithm and the data information of each cell in the selected at least one discharging end stage.
Optionally, the setting algorithm at least includes: z score method, local outlier factor algorithm and pearson correlation coefficient algorithm. Through any algorithm, the outlier degree of each cell at each charging end stage and the outlier degree of each cell at each discharging end stage are calculated.
S150: determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, and determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
After the outliers of the electric cores at each selected charging end stage are calculated, sorting the outliers of the electric cores at each selected charging end stage from small to large, and selecting m electric cores with the largest outliers. After calculating the outlier of each cell in each selected discharge end stage, sorting the outlier of each cell in each selected discharge end stage, and selecting m cells with the largest outlier. Each cell in the battery is provided with a number, and the numbers of the cells are different. Therefore, when m cells with highest outliers are selected for the outlier ranking, the m cells can be positioned to respectively correspond to which battery in the batteries. For example, if the battery includes 100 cells, 5 cells with highest outliers at each charging end stage and 5 cells with highest outliers at each discharging end stage can be selected for subsequent analysis and attention, so as to assist the user in subsequent positioning of abnormal monomers and further analysis.
According to the technical scheme, after determining whether any moment is in a charging end stage or a discharging end stage according to the data information of each battery cell, at least one charging end stage and at least one discharging end stage are selected according to a time period input by a user, and the outlier degree of each battery cell is calculated according to the data information of each battery cell in each selected charging end stage or each selected discharging end stage, so that the outlier degree of each battery cell in each selected charging end stage or each selected discharging end stage can be obtained, the outlier degree of each battery cell in each charging end stage or each selected discharging end stage is sequenced, and a plurality of battery cells with the largest outlier are obtained and used for assisting a technician in subsequent positioning abnormal monomers and further analysis.
Fig. 2 is a flowchart of another method for determining inconsistency of battery cells according to an embodiment of the present invention, and referring to fig. 2, optionally, the method includes:
s111: and acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell.
S121: at any moment, determining whether the battery is in a charging end stage or a discharging end stage at the current moment according to the data information of each battery cell.
Determining whether the battery is in the charge end stage or the discharge end stage may include two specific ways, alternatively, way one: when the voltage of the battery cell with the largest voltage is larger than a charging voltage threshold value at the current moment and the battery is in a charging state according to the current direction of the battery cell, the battery is in a charging terminal stage at the current moment; and when the voltage of the battery cell with the minimum voltage is smaller than the discharge voltage threshold value at the current moment and the battery is in a discharge state according to the current direction of the battery cell, determining that the battery is in a discharge end stage at the current moment.
The battery includes a plurality of cells in which the current direction is the same. As the charging process proceeds, the voltage of the battery cell gradually increases. And under the current moment, acquiring the voltage of each battery cell, and determining that the battery is at the terminal stage of charging at the current moment when the voltage of the battery cell with the largest voltage is larger than the charging voltage threshold value and the current of the battery cell flows to the battery cell from the bidirectional inverter. As the discharge process proceeds, the voltage of the cell gradually decreases. And under the current moment, acquiring the voltage of each battery cell, and determining that the battery at the current moment is in a discharge end stage when the voltage of the battery cell with the minimum voltage is smaller than a discharge voltage threshold value and the current of the battery cell flows from the battery cell to the bidirectional inverter. The charge voltage threshold and the discharge voltage threshold may be set according to requirements, and exemplary, the charge voltage threshold may be 3.5V and the discharge voltage threshold may be 3.1V.
Alternatively, mode two: according to the h moment and a plurality of moments after the h moment, determining that the voltage of the battery cell with the maximum voltage at the h moment in the battery is gradually increased, and determining that the h moment is in a charging end stage when the voltage change rate of the battery cell with the maximum voltage at the h moment is larger than a set voltage change threshold; and according to the h moment and a plurality of moments after the h moment, determining that the voltage of the cell with the minimum voltage in the battery is gradually reduced, and determining that the h moment is in a discharge end stage when the voltage change rate of the cell with the minimum voltage is larger than a set voltage change threshold value at the h moment.
The characteristics of a battery such as a lithium battery are that the voltage change rate of the battery cell becomes large at the charge end or the discharge end as charge or discharge proceeds. And when the voltage of the battery cell with the largest voltage in all battery cells is gradually increased at the current moment and a plurality of moments after the current moment, and the voltage change rate is larger than a set voltage change threshold value such as 2mV/s, marking that the current moment belongs to a charging terminal stage. And when the voltage of the battery cell with the minimum voltage in all battery cells is gradually reduced at the current moment and a plurality of moments after the current moment, and the voltage change rate is larger than a set voltage change threshold value such as 2mV/s, marking that the current moment belongs to a discharge end stage.
S131: at least one charge end stage and discharge end stage is selected according to a time period input by a user.
Optionally, according to the time period entered by the user, at least one charge end stage and at least one discharge end stage closest to the end time of the time period entered by the user are selected.
The closer the user input time period is to the end time of the input time period, the more the latest state of each cell in the battery can be reflected, and therefore, at least one charge end stage and at least one discharge end stage closest to the end time of the user input time period are selected for outlier calculation. And the range of analysis data is reasonably selected to carry out outlier analysis, so that the calculated amount is reduced.
S141: calculating the outlier of each cell in the selected at least one charging end stage by setting the algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage by setting the algorithm and the data information of each cell in the selected at least one discharging end stage.
Alternatively, the algorithm is set as the Z-score method. Optionally, according to the voltage of each cell at the i-th time in the selected charging end stage or discharging end stage, calculating an average value of the voltages of the cells at the i-th time, i=1, 2, … …, L, wherein 1 is the start time of the selected charging end stage or discharging end stage, and L is the end time of the selected charging end stage or discharging end stage; determining the Z fraction of each battery cell at the ith moment according to the voltage of each battery cell at the ith moment, the average value of the voltage of the battery cell at the ith moment and the standard deviation of the voltage of the battery cell at the ith moment; for any cell, the average value of the Z fractions of the cell at all times in the selected charge end stage or discharge end stage is calculated as the outlier of the cell.
For each selected charge end stage or discharge end stage, the charge end stage or discharge end stage includes L sampling moments, the outlier of each cell at each moment is calculated, and finally the outlier of a certain cell in the charge end stage or discharge end stage is the average value of the outlier of the cell at the L sampling moments. And when the outlier degree of any battery cell at any moment is calculated, taking the Z fraction of the battery cell as the outlier degree of the battery cell. The Z fraction is equal to the standard deviation of the difference between the voltage of the battery cell and the average value of all the battery cell voltages at the moment and the battery cell voltage at the moment. The outlier degree of each cell at any time can be calculated according to the specific calculation mode of the Z score.
S151: determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, and determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
S161: generating data information curves corresponding to m electric cores according to data information of m electric cores with highest outliers, which are determined at least at one charging end stage, in a time period input by a user, wherein the data information curves at least comprise a voltage curve and a current curve; and generating data information curves corresponding to the m electric cores according to the data information of the m electric cores with the highest outlier degree, which is determined in at least one discharge end stage, in the time period input by the user, wherein the data information curves at least comprise a voltage curve and a current curve.
After determining m electric cores with highest outliers at each selected charging end stage, respectively generating m voltage curves corresponding to the m electric cores one by one and m current curves corresponding to the m electric cores one by one according to data information of the m electric cores in a time period input by a user. After determining m electric cores with highest outliers at each discharge end stage, respectively generating m voltage curves corresponding to the m electric cores one by one and m current curves corresponding to the m electric cores one by one according to data information of the m electric cores in a time period input by a user so as to assist the user in analyzing the outliers of the electric cores.
In this embodiment, according to the time period input by the user, at least one charge end stage and at least one discharge end stage closest to the end time of the time period input by the user are selected, so that the data range selection is more reasonable, and the calculation amount is reduced.
On the basis of the above embodiment, optionally, after S150 or S151, the method further includes:
and when the outlier degree of the battery core is larger than the set outlier degree threshold value, determining the battery core as an outlier monomer.
Aiming at the method for determining the inconsistency of battery cells, the invention provides a specific embodiment, as shown in table 1, wherein the battery in the embodiment comprises n battery cells in total: cell 1, cell 2, cells 3, …, cell n, table 1, counts the voltage (units, mV) of each cell at each sampling time at a selected end of discharge stage, and the current (units, a) of the cell. Table 2 shows the outliers of the cells at each sampling time calculated after outlier analysis.
Table-cell raw data table
Table two post outlier analysis data table
Fig. 3 is a schematic structural diagram of a device for determining inconsistency of battery cells according to an embodiment of the present invention, where a battery includes a plurality of cells connected in series; as shown in fig. 3, the apparatus includes:
the information acquisition module 1 is used for acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell;
the terminal determining module 2 is used for determining whether the battery is in a charging terminal stage or a discharging terminal stage at the current time according to the data information of each battery cell at any time;
a selection module 3 for selecting at least one charge end stage and discharge end stage according to a time period input by a user;
the outlier calculating module 4 is configured to calculate an outlier of each cell in the selected at least one charging end stage by setting data information of each cell in the selected at least one charging end stage according to the algorithm and the selected at least one discharging end stage, and calculate an outlier of each cell in the selected at least one discharging end stage according to the data information of each cell in the selected at least one discharging end stage according to the algorithm and the selected at least one discharging end stage;
the analysis module 5 is configured to determine m cells with highest outliers at each charging end stage according to the outliers of the cells at the selected at least one charging end stage, and determine m cells with highest outliers at each discharging end stage according to the outliers of the cells at the selected at least one discharging end stage, where 0< m < n, n is the number of cells in the battery, and m and n are both positive integers.
The battery cell inconsistency determining device provided by the embodiment of the invention can execute the battery cell inconsistency determining method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method.
Optionally, the end determining module includes:
the charging terminal determining unit is used for determining that the battery is in a charging terminal stage at the current moment when the voltage of the battery cell with the largest voltage is larger than a charging voltage threshold value and the battery is in a charging state according to the current direction of the battery cell;
and the discharge end determining unit is used for determining that the battery is in a discharge end stage at the current time when the voltage of the battery cell with the minimum voltage is smaller than a discharge voltage threshold value and the battery is in a discharge state according to the current direction of the battery cell.
Alternatively, the end determination module includes:
the charging terminal determining unit is used for determining that the h moment is in a charging terminal stage when the voltage of the cell with the largest voltage at the h moment in the battery is gradually increased and the voltage change rate of the cell with the largest voltage at the h moment is larger than a set voltage change threshold according to the h moment and a plurality of moments after the h moment;
And the discharging end stage determining unit is used for determining that the h moment is in the discharging end stage when the voltage of the cell with the minimum voltage at the h moment in the battery is gradually reduced according to the h moment and a plurality of moments after the h moment and the voltage change rate of the cell with the minimum voltage at the h moment is larger than the set voltage change threshold value.
Optionally, the selecting module includes:
and the selection unit is used for selecting at least one charging end stage and at least one discharging end stage which are closest to the ending moment of the time period input by the user according to the time period input by the user.
Optionally, the outlier calculating module includes:
the average value calculating unit is used for calculating the average value of the voltages of the battery cells at the ith moment according to the voltages of the battery cells at the ith moment in the selected charging end phase or discharging end phase, wherein i=1, 2, … … and L, 1 is the starting moment of the selected charging end phase or discharging end phase, and L is the ending moment of the selected charging end phase or discharging end phase;
the Z score calculating unit is used for determining the Z score of each battery cell at the ith moment according to the voltage of each battery cell at the ith moment, the average value of the voltages of the battery cells at the ith moment and the standard deviation of the voltages of the battery cells at the ith moment;
And the outlier determining unit is used for calculating the average value of the Z scores of the battery cells at all moments in the selected charging end stage or discharging end stage for any battery cell, and taking the average value as the outlier of the battery cells.
Optionally, the battery cell inconsistency determining device further includes:
the charging curve generating unit is used for generating data information curves corresponding to the m electric cores according to the data information of the m electric cores with the highest outliers, which are determined at least at one charging end stage, in the time period input by a user, wherein the data information curves at least comprise a voltage curve and a current curve;
the discharging curve generating unit is used for generating data information curves corresponding to the m electric cores according to the data information of the m electric cores with the highest outliers, which are determined in the selected at least one discharging end stage, in the time period input by the user, wherein the data information curves at least comprise a voltage curve and a current curve.
Optionally, the battery cell inconsistency determining device further includes:
and the outlier monomer determining module is used for determining that the battery cell is an outlier monomer when the outlier degree of the battery cell is larger than a set outlier degree threshold value.
Fig. 4 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the battery cell inconsistency determination method described above.
In some embodiments, the battery cell inconsistency determination method may be implemented as a computer program tangibly embodied on a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the battery cell inconsistency determination method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the battery cell inconsistency determination method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of determining cell inconsistency, wherein the battery comprises a plurality of cells connected in series; the method for determining the inconsistency of battery cells comprises the following steps:
acquiring data information of each battery cell in real time, wherein the data information at least comprises voltage and current of the battery cell;
at any moment, determining whether the battery is in a charging end stage or a discharging end stage at the current moment according to the data information of each battery cell;
Selecting at least one of the charge end stage and the discharge end stage according to a time period input by a user;
calculating the outlier of each cell in the selected at least one charging end stage by setting algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage by setting algorithm and the data information of each cell in the selected at least one discharging end stage;
determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
2. The method for determining the inconsistency of battery cells according to claim 1, wherein determining whether the battery is in a charge end stage or a discharge end stage at a current time according to the data information of each of the battery cells at any of the time points comprises:
When the voltage of the battery cell with the largest voltage is larger than a charging voltage threshold value and the battery is in a charging state according to the current direction of the battery cell, determining that the battery is in the charging terminal stage at the current time;
and under the current moment, when the voltage of the battery cell with the minimum voltage is smaller than a discharge voltage threshold value and the battery is in a discharge state according to the current direction of the battery cell, determining that the battery is in the discharge end stage under the current moment.
3. The method for determining the inconsistency of battery cells according to claim 1, wherein determining whether the battery is in a charge end stage or a discharge end stage at a current time according to the data information of each of the battery cells at any of the time points comprises:
according to the h moment and a plurality of moments after the h moment, determining that the voltage of the battery cell with the maximum voltage at the h moment in the battery is gradually increased, and determining that the h moment is in the charging tail end stage when the voltage change rate of the battery cell with the maximum voltage at the h moment is larger than a set voltage change threshold value;
and determining that the h moment is in the discharge end stage when the voltage of the cell with the minimum voltage gradually decreases and the voltage change rate of the cell with the minimum voltage is larger than the set voltage change threshold according to the h moment and a plurality of moments after the h moment.
4. The method of claim 1, wherein selecting at least one of the charge end phase and the discharge end phase according to a time period entered by a user comprises:
according to the time period input by the user, at least one charging end stage and at least one discharging end stage closest to the end time of the time period input by the user are selected.
5. The method for determining the inconsistency of battery cells according to claim 1, wherein the setting algorithm comprises at least: z score method, local outlier factor algorithm and pearson correlation coefficient algorithm.
6. The method of claim 1, wherein the setting algorithm is a Z-score method, the calculating the outlier of each cell of the selected at least one charge end stage by the setting algorithm and the data information of each cell of the selected at least one discharge end stage, and the calculating the outlier of each cell of the selected at least one discharge end stage by the setting algorithm and the data information of each cell of the selected at least one discharge end stage comprises:
Calculating the average value of the voltages of the cells at the ith moment according to the voltages of the cells at the ith moment in the selected charging end phase or discharging end phase, wherein i=1, 2, … … and L, 1 is the starting moment of the selected charging end phase or discharging end phase, and L is the ending moment of the selected charging end phase or discharging end phase;
determining the Z fraction of each battery cell at the ith moment according to the voltage of each battery cell at the ith moment, the average value of the voltages of the battery cells at the ith moment and the standard deviation of the voltages of the battery cells at the ith moment;
and for any cell, calculating the average value of the Z scores of the cells at all moments in the selected charging end stage or discharging end stage as the outlier of the cell.
7. The method of claim 1, wherein after said determining m cells having highest outliers for each of said charge end stages based on outliers for each of said cells for at least one of said charge end stages selected, and determining m cells having highest outliers for each of said discharge end stages based on outliers for each of said cells for at least one of said discharge end stages selected, comprising:
Generating data information curves corresponding to m electric cores according to data information of m electric cores with highest outliers, which are determined in at least one charging end stage, in a time period input by a user, wherein the data information curves at least comprise a voltage curve and a current curve;
and generating data information curves corresponding to the m electric cores according to the data information of the m electric cores with the highest outliers, which are determined in at least one discharge end stage, in the time period input by the user, wherein the data information curves at least comprise a voltage curve and a current curve.
8. The method of claim 1, further comprising, after said determining m cells having highest outliers for each of said charge end stages based on outliers for each of said cells for at least one of said charge end stages selected, and determining m cells having highest outliers for each of said discharge end stages based on outliers for each of said cells for at least one of said discharge end stages selected:
and when the outlier degree of the battery cell is larger than a set outlier degree threshold, determining that the battery cell is an outlier monomer.
9. A battery cell inconsistency determining device, wherein the battery comprises a plurality of cells connected in series, the battery cell inconsistency determining device comprising:
The information acquisition module is used for acquiring the data information of each battery cell in real time, wherein the data information at least comprises the voltage and the current of the battery cell;
the terminal determining module is used for determining whether the battery is in a charging terminal stage or a discharging terminal stage at the current moment according to the data information of each battery cell at any moment;
a selection module for selecting at least one of the charge end stage and the discharge end stage according to a time period input by a user;
the outlier calculating module is used for calculating the outlier of each cell in the selected at least one charging end stage through a setting algorithm and the data information of each cell in the selected at least one charging end stage, and calculating the outlier of each cell in the selected at least one discharging end stage through the setting algorithm and the data information of each cell in the selected at least one discharging end stage;
the analysis module is used for determining m electric cores with highest outliers in each charging end stage according to the outliers of the electric cores in at least one selected charging end stage, and determining m electric cores with highest outliers in each discharging end stage according to the outliers of the electric cores in at least one selected discharging end stage, wherein 0< m < n, n is the number of the electric cores in the battery, and m and n are positive integers.
10. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the battery cell inconsistency determination method of any of the claims 1-8.
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