CN113871727B - Self-adaptive formation method and system for improving parameter consistency of lithium ion battery - Google Patents
Self-adaptive formation method and system for improving parameter consistency of lithium ion battery Download PDFInfo
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 28
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/05—Accumulators with non-aqueous electrolyte
- H01M10/058—Construction or manufacture
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/05—Accumulators with non-aqueous electrolyte
- H01M10/052—Li-accumulators
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
- Y02P70/50—Manufacturing or production processes characterised by the final manufactured product
Abstract
The invention discloses a self-adaptive formation method and a self-adaptive formation system for improving the parameter consistency of a lithium ion battery, wherein the method comprises the following steps: the method comprises the steps of calculating a voltage estimation value at the next sampling moment based on a forward estimation coefficient at the current sampling moment and a collected voltage vector at the current sampling moment, approaching a voltage ideal value at the next sampling moment on an ideal voltage curve based on the voltage estimation value at the next sampling moment, and adaptively adjusting the magnitude of charging current of each channel to influence the characteristics of thickness, compactness and the like generated by an SEI film, so that the curve of voltage of each cell changing along with time is dynamically approximated to the ideal curve, thereby compensating individual differences caused by a preceding stage process and improving the consistency of cell parameters.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a self-adaptive formation method and a self-adaptive formation system for improving the parameter consistency of a lithium ion battery.
Background
The consistency of the battery cell of the lithium battery is crucial to the power battery pack, when the battery cell forms a module, because the parameter values of the voltage, the internal resistance, the capacity and the like of different battery cells are different, the performance index of the formed module can not reach the original level of the single battery, and the application of the single battery on the electric automobile is seriously influenced, so the consistency of the battery parameter becomes a key factor influencing the service life of the battery pack. The production process of the lithium battery comprises 50 processes of stirring, coating, slitting, laminating/winding, liquid injection, formation, volume separation, standing, sorting and the like. The formation is one of the key processes in the production process of the lithium battery. The formation is the first activation charging process after the lithium battery is formed into a battery, the lithium battery is charged under a small current, positive lithium ions are embedded into negative graphite through electrolyte under the action of the current to form a potential to generate voltage, and a stable solid electrolyte interface film, namely an SEI film, is formed on the surface of the carbon negative electrode. The SEI film can stably exist in the organic electrolyte solution, allows lithium ions to freely pass through, is an excellent conductor of the lithium ions, and simultaneously solvent molecules cannot penetrate through the passivation film, so that the co-intercalation of the solvent molecules is effectively prevented, and the damage to an electrode material caused by the co-intercalation of the solvent molecules is avoided. The quality of the SEI film directly determines the core performances of the lithium battery, such as internal resistance, cycle life, self-discharge property, stability, safety and the like. In the formation process constant-current charging activation process, the voltages of the positive and negative stages are gradually increased along with time under the accumulation effect of charges to form a curve of voltage variation along with time. The cells of different models can be used for calculating an ideal curve of voltage change along with time under constant current by combining the factors such as materials, proportion, process and the like, and the ideal curve can also be obtained by detecting data of a large number of cells. In the former stage process, the consistency of raw materials, the uniformity of coating, the stability of winding lamination, the concentration of injection liquid and the like cause individual differences of batteries of the same type and different batches, and influence the consistency of the battery core.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect that when a large number of lithium batteries are manufactured in the prior art, batteries of the same type and different batches have individual differences, so as to provide a self-adaptive formation method and a system for improving the parameter consistency of lithium ion batteries.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, an embodiment of the present invention provides a self-adaptive formation method for improving parameter consistency of a lithium ion battery, including: initializing a forward estimation coefficient and adjusting an inverse matrix based on a preset number of voltage sampling data for forward estimation; calculating a voltage estimation value of the next sampling moment based on a forward estimation coefficient of the current sampling moment and a collected voltage vector of the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted or not according to the voltage estimation value of the next sampling moment and a voltage ideal value of the next sampling moment on an ideal voltage curve; when the voltage estimated value at the next sampling moment is not equal to the corresponding voltage ideal value, adjusting the charging current in the next sampling interval based on the difference value of the voltage estimated value and the voltage ideal value; calculating a forward estimation coefficient of the next sampling moment and an adjustment inverse matrix of the next sampling moment by using the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment; and returning to the step of calculating the voltage estimation value of the next sampling moment based on the forward estimation coefficient of the current sampling moment and the acquired voltage vector of the current sampling moment at the next sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value of the next sampling moment and the voltage ideal value of the next sampling moment on the ideal voltage curve until the voltage estimation value is equal to the corresponding voltage ideal value.
In an embodiment, the collected voltage vector at the current sampling time is composed of the voltage collected at the current sampling time and the voltages collected at a preset number of sampling times before the current sampling time.
In one embodiment, when the voltage estimated value at the next sampling time is not equal to the corresponding voltage ideal value, the process of adjusting the charging current in the next sampling interval based on the difference between the voltage estimated value and the corresponding voltage ideal value includes: calculating a voltage difference value based on the voltage estimated value and the voltage ideal value at the next sampling moment; calculating a current adjustment offset value based on the voltage difference value, the preset maximum voltage difference value and the preset maximum current difference value; taking the difference value between the preset charging current value and the current adjustment offset in the next sampling interval as a charging current calculation value in the next sampling interval; and when the calculated value of the charging current in the next sampling interval is in the preset range, taking the calculated value as the charging current in the next sampling interval.
In an embodiment, when the voltage estimated value at the next sampling time is not equal to the corresponding voltage ideal value, the process of adjusting the charging current in the next sampling interval based on the difference between the two values further includes: and when the calculated value of the charging current in the next sampling interval exceeds the preset maximum current threshold, taking the preset maximum current threshold as the charging current in the next sampling interval.
In an embodiment, when the voltage estimated value at the next sampling time is not equal to the corresponding voltage ideal value, the process of adjusting the charging current in the next sampling interval based on the difference between the two values further includes: and when the calculated value of the charging current in the next sampling interval is lower than the preset minimum current threshold, taking the preset minimum current threshold as the charging current in the next sampling interval.
In an embodiment, the process of calculating the forward estimation coefficient at the next sampling time by using the adjustment inverse matrix at the current sampling time, the collected voltage vector at the next sampling time, and the forward estimation coefficient at the current time includes: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment consists of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; and calculating the forward estimation coefficient of the next sampling moment based on the forward estimation coefficient of the current moment, the voltage difference value of the next sampling moment and the gain vector of the next sampling moment.
In an embodiment, the process of calculating the adjustment inverse matrix at the next sampling time by using the adjustment inverse matrix at the current sampling time, the collected voltage vector at the next sampling time, and the forward estimation coefficient at the current time includes: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment consists of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; and calculating the adjustment inverse matrix of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquisition voltage vector of the next sampling moment and the gain vector of the next sampling moment.
In a second aspect, an embodiment of the present invention provides an adaptive formation system for improving parameter consistency of a lithium ion battery, including: the device comprises an initialization module, a forward estimation module and a reverse matrix adjustment module, wherein the initialization module is used for initializing a forward estimation coefficient and adjusting the reverse matrix based on a preset number of voltage sampling data for forward estimation; the forward estimation judging module is used for judging whether the charging current in the next sampling interval needs to be adjusted or not based on a forward estimation coefficient at the current sampling moment and a collected voltage vector at the current sampling moment, wherein the collected voltage vector at the current sampling moment is composed of the voltage collected at the current sampling moment and the voltages collected at the sampling moments in a preset number before the current sampling moment; the adjusting module is used for adjusting the charging current in the next sampling interval based on the difference value of the voltage estimated value at the next sampling moment and the corresponding ideal voltage value when the voltage estimated value at the next sampling moment is not equal to the ideal voltage value; the backward verification updating module is used for calculating a forward estimation coefficient of the next sampling moment and an adjustment inverse matrix of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment; and the circulating module is used for returning to the step of calculating the voltage estimation value of the next sampling moment based on the forward estimation coefficient of the current sampling moment and the acquired voltage vector of the current sampling moment at the next sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value of the next sampling moment and the voltage ideal value of the next sampling moment on the ideal voltage curve until the voltage estimation value is equal to the corresponding voltage ideal value.
In a third aspect, an embodiment of the present invention provides a computer device, including: the adaptive lithium ion battery comprises at least one processor and a memory which is in communication connection with the at least one processor, wherein the memory stores instructions which can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor executes the adaptive formation method for improving the consistency of the parameters of the lithium ion battery according to the first aspect of the embodiment of the invention.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium, and the computer instructions are used to enable a computer to execute the adaptive formation method for improving the consistency of parameters of a lithium ion battery according to the first aspect of the embodiment of the present invention.
The technical scheme of the invention has the following advantages:
the self-adaptive forming method and the self-adaptive forming system for improving the parameter consistency of the lithium ion battery calculate the voltage estimation value at the next sampling moment based on the forward estimation coefficient at the current sampling moment and the acquired voltage vector at the current sampling moment, approach the voltage ideal value at the next sampling moment on an ideal voltage curve based on the voltage estimation value at the next sampling moment, and self-adaptively adjust the magnitude of the charging current of each channel so as to influence the characteristics of thickness, compactness and the like generated by an SEI film, so that the curve of the voltage of each cell changing along with time dynamically approaches the ideal curve, thereby compensating the individual difference caused by the prior process and improving the consistency of the cells.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of an adaptive formation method according to an embodiment of the present invention;
fig. 2 is a flowchart of another specific example of an adaptive formation method according to an embodiment of the present invention;
fig. 3 is a formation voltage curve of a formation battery cell formed by a conventional constant current charging method according to an embodiment of the present invention;
fig. 4 is a formation voltage curve of a city cell obtained by using a self-adaptive formation method according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a specific example of an adaptive formation method according to an embodiment of the present invention;
fig. 6 is a composition diagram of a specific example of a computer device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be connected through the inside of the two elements, or may be connected wirelessly or through a wire. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Furthermore, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment of the present invention provides an adaptive formation method for improving parameter consistency of a lithium ion battery, which is applied to a cell formation process, and the formation method provided by the embodiment of the present invention can be used for formation of each cell, as shown in fig. 1, the formation method includes:
step S11: initializing forward estimation coefficients and adjusting an inverse matrix based on a preset number of voltage sample data for forward estimation.
Specifically, the forward estimation coefficient h is initialized1(1)=[1/M,1/M,…1/M]1×MAnd M is a preset number of voltage acquisition numbers for forward estimation, and the initialization adjustment inverse matrix is a unit matrix:
it will be understood that h1(1) Is a forward estimation coefficient, P, at the 1 st sampling instant1(1) The inverse matrix is adjusted for the 1 st sampling instant.
Step S12: and calculating a voltage estimation value of the next sampling moment based on the forward estimation coefficient of the current sampling moment and the acquired voltage vector of the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted or not according to the voltage estimation value of the next sampling moment and the voltage ideal value of the next sampling moment on the ideal voltage curve.
Specifically, in the embodiment of the present invention, at each sampling time, a collected voltage vector at the current sampling time is formed according to the voltage collected at the first M-1 sampling times and the voltage collected at the current sampling time, and based on a forward estimation coefficient at the current sampling time, a voltage estimation value at the next sampling time is estimated, and a charging current in a sampling interval between the current sampling time and the next sampling time is adjusted by using the voltage estimation value at the next sampling time and a voltage ideal value at the next sampling time on an ideal voltage curve in an infinite approximation manner.
The calculation formula of the voltage estimation value at the next sampling moment is as follows:
in the formula, h1(n) Is the forward estimation coefficient at the nth sampling instant,v 1(n) isnThe collected voltage vector at the sampling instant,v 1(n)=[v 1(n-M+1),v 1(n-M+2),…v1(n)]，
is as followsnThe voltage estimate at +1 sample time.
Step S13: and when the voltage estimated value at the next sampling moment is not equal to the corresponding voltage ideal value, adjusting the charging current in the next sampling interval based on the difference value of the voltage estimated value and the corresponding voltage ideal value.
Specifically, the embodiment of the invention can influence the characteristics of thickness, compactness and the like generated by the SEI film by adaptively adjusting the charging current of each channel, and the curve of the voltage of each cell changing along with time is dynamically approximated to an ideal curve, thereby compensating individual difference caused by a preceding-stage process and improving the consistency of the cells.
Specifically, as shown in FIG. 2, step S13 is performed by steps S21-S24 as follows:
step S21: and calculating a voltage difference value based on the voltage estimated value and the voltage ideal value at the next sampling moment.
Specifically, in the formation process of constant-current charging activation, voltages of positive and negative two stages gradually rise with time under the accumulation effect of charges to form a curve of which the voltage changes with time, so that the embodiment of the present invention needs to infinitely approximate the curve to an ideal voltage curve of a battery cell, estimate a voltage estimation value at a next sampling time at a current sampling time by setting a plurality of sampling times, and adjust a charging current by judging in advance whether the voltage estimation value at the next sampling time is equal to a voltage ideal value (a voltage value at the next sampling time on the ideal voltage curve), wherein a voltage difference value is calculated by using the following formula:
in the formula,. DELTA.v(n+1) is thenThe voltage difference at the +1 sampling instant,
is the first on the ideal voltage curven+1 voltage value at the sampling instant.
Step S22: and calculating the current adjustment offset based on the voltage difference value, the preset maximum voltage difference value and the preset maximum current difference value.
Specifically, the embodiment of the present invention calculates an offset coefficient according to a voltage difference value based on the next sampling time and a preset maximum voltage difference value, and calculates a current adjustment offset value based on the offset coefficient and a preset maximum current difference value:
in the formula (I), the compound is shown in the specification,ΔI(n) Is as followsnThe amount of current offset within a sampling interval,ΔI max in order to preset the maximum current difference value,Δ V max is a preset maximum voltage difference.
It should be noted that the 1 st samplingThe 1 st sampling interval is between the sampling time and the 2 nd sampling time, the 2 nd sampling interval is between the 2 nd sampling time and the 3 rd sampling time, and so onnAt the sampling time andnbetween +1 sampling instantsnA sampling interval.
Step S23: and taking the difference value between the preset charging current value and the current adjustment offset in the next sampling interval as the charging current calculation value in the next sampling interval.
Calculating a charge current calculation value in a next sampling interval by:
in the formula (I), the compound is shown in the specification,I math (n) Is as followsnThe calculated value of the charging current over one sampling interval,I ref (n) Is as followsnA preset charging current value within each sampling interval.
Step S24: and when the calculated value of the charging current in the next sampling interval is in the preset range, taking the calculated value as the charging current in the next sampling interval.
Specifically, the charging current is clamped using the following equation:
in the formula (I), the compound is shown in the specification,I(n) For the charging current in the next sampling interval,I min in order to preset the minimum current threshold value,I max is a preset maximum current threshold.
It can be understood that, according to equation (5), the calculated value of the charging current in the next sampling intervalI math (n) Exceeding a preset maximum current thresholdI max Then, the maximum current threshold will be presetI max As the charging current in the next sampling intervalI(n) (ii) a Calculated value of charging current in next sampling intervalI math (n) Below a predetermined minimum current thresholdI min Will preset a minimum current thresholdI min As the charging current in the next sampling intervalI(n) (ii) a Calculated value of charging current in next sampling intervalI math (n) Within a predetermined range of (I min <I math (n)<I max ) Calculating the valueI math (n) As the charging current in the next sampling intervalI(n)。
Step S14: and calculating the forward estimation coefficient of the next sampling moment and the adjustment inverse matrix of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment.
The process of calculating the forward estimation coefficient at the next sampling time in the embodiment of the invention is as follows:
firstly, the adjustment inverse matrix P of the current sampling moment is utilized1(n) collected voltage vector at next sampling timev 1(n+1), calculating the gain vector K for the next sampling instant1(n+1), the collected voltage vector at the next sampling instantv 1(n+1) is composed of the voltage collected at the next sampling instant, the voltage collected at a preset number of sampling instants before the next sampling instant.
Then, based on the forward estimation coefficient h of the current time1(n) Voltage difference value at next sampling time∆v(n+1)Gain vector K at the next sampling instant1(n+1), calculating the forward estimation coefficient h of the next sampling moment1(n+1)。
The process of calculating the adjustment inverse matrix at the next sampling moment in the embodiment of the invention is as follows:
firstly, the adjustment inverse matrix P of the current sampling moment is utilized1(n) The collected voltage vector at the next sampling momentv 1(n+1), calculating the gain vector K for the next sampling instant1(n+1), the collected voltage vector at the next sampling instantv 1(n+1) is composed of the voltage collected at the next sampling time and the voltages collected at the preset number of sampling times before the next sampling time, and the calculation formula is shown in formula (7).
Then, the inverse matrix P is adjusted by using the current sampling time1(n) The collected voltage vector v at the next sampling moment1(n+1), gain vector K for the next sampling instant1(n+1), calculating the adjusted inverse matrix P for the next sampling instant1(n+1)。
Step S15: and returning to the step of calculating the voltage estimation value of the next sampling moment based on the forward estimation coefficient of the current sampling moment and the acquired voltage vector of the current sampling moment at the next sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value of the next sampling moment and the voltage ideal value of the next sampling moment on the ideal voltage curve until the voltage estimation value is equal to the corresponding voltage ideal value.
Based on the method, the embodiment of the invention is applied to a production field, a ternary battery cell of a certain model is formed in the production field, part of channels are formed by adopting the traditional constant charging current, and part of channels are formed by adopting the self-adaptive formation method provided by the embodiment of the invention. All channels are started to form at the same time in the same environment, the constant charging current is set to be 0.2C, and charging curves are compared after formation is finished. As can be seen from the results in fig. 3 and fig. 4, the battery cells formed by the conventional constant current charging method have large individual differences, and the charging curves are distributed loosely; the self-adaptive formation technology can effectively compensate the difference between the battery cores and improve the consistency of the battery cores, so that the charging curves are relatively concentrated.
Example 2
An embodiment of the present invention provides an adaptive formation system for improving parameter consistency of a lithium ion battery, as shown in fig. 5, including:
the device comprises an initialization module 1, a forward estimation module and a forward estimation module, wherein the initialization module is used for initializing a forward estimation coefficient and adjusting an inverse matrix based on a preset number of voltage sampling data for forward estimation; this module executes the method described in step S11 in embodiment 1, and is not described herein again.
The forward estimation judging module 2 is used for calculating a voltage estimation value at the next sampling moment based on a forward estimation coefficient at the current sampling moment and a collected voltage vector at the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted or not according to the voltage estimation value at the next sampling moment and a voltage ideal value at the next sampling moment on an ideal voltage curve; this module executes the method described in step S12 in embodiment 1, and is not described herein again.
The adjusting module 3 is used for adjusting the charging current in the next sampling interval based on the difference value between the voltage estimated value at the next sampling moment and the corresponding voltage ideal value when the voltage estimated value at the next sampling moment is not equal to the corresponding voltage ideal value; this module executes the method described in step S13 in embodiment 1, and is not described herein again.
The backward verification updating module 4 is used for calculating a forward estimation coefficient of the next sampling moment and an adjustment inverse matrix of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment; this module executes the method described in step S14 in embodiment 1, and is not described herein again.
The circulation module 5 is configured to, at the next sampling time, return to the step of "calculating a voltage estimation value at the next sampling time based on a forward estimation coefficient at the current sampling time and a collected voltage vector at the current sampling time, and determine whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value at the next sampling time and a voltage ideal value at the next sampling time on an ideal voltage curve" until the voltage estimation value is equal to the voltage ideal value corresponding thereto; this module executes the method described in step S15 in embodiment 1, and is not described herein again.
Example 3
An embodiment of the present invention provides a computer device, as shown in fig. 6, including: at least one processor 401, such as a CPU (Central Processing Unit), at least one communication interface 403, memory 404, and at least one communication bus 402. Wherein a communication bus 402 is used to enable connective communication between these components. The communication interface 403 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a standard wireless interface. The Memory 404 may be a RAM (random Access Memory) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 404 may optionally be at least one memory device located remotely from the processor 401. Wherein the processor 401 may execute the adaptive formation method for improving the consistency of the parameters of the lithium ion battery of embodiment 1. A set of program codes is stored in the memory 404, and the processor 401 invokes the program codes stored in the memory 404 for performing the adaptive formation method of embodiment 1 for improving the consistency of the parameters of the lithium ion battery.
The communication bus 402 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 402 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one line is shown in FIG. 6, but it is not intended that there be only one bus or one type of bus.
The memory 404 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated: HDD) or a solid-state drive (english: SSD); the memory 404 may also comprise a combination of memories of the kind described above.
The processor 401 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The processor 401 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 404 is also used to store program instructions. The processor 401 may call a program instruction to implement the adaptive formation method for improving the consistency of the lithium ion battery parameters in embodiment 1.
The embodiment of the invention also provides a computer-readable storage medium, wherein a computer-executable instruction is stored on the computer-readable storage medium, and the computer-executable instruction can execute the adaptive formation method for improving the parameter consistency of the lithium ion battery in the embodiment 1. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid-State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications of the invention may be made without departing from the spirit or scope of the invention.
Claims (8)
1. A self-adaptive formation method for improving parameter consistency of a lithium ion battery is characterized by comprising the following steps:
initializing a forward estimation coefficient and adjusting an inverse matrix based on a preset number of voltage sampling data for forward estimation;
calculating a voltage estimation value of the next sampling moment based on a forward estimation coefficient of the current sampling moment and a collected voltage vector of the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted or not according to the voltage estimation value of the next sampling moment and a voltage ideal value of the next sampling moment on an ideal voltage curve;
when the voltage estimated value at the next sampling moment is not equal to the corresponding voltage ideal value, adjusting the charging current in the next sampling interval based on the difference value of the voltage estimated value and the voltage ideal value;
calculating a forward estimation coefficient of the next sampling moment and an adjustment inverse matrix of the next sampling moment by using the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment;
at the next sampling moment, returning to the step of calculating the voltage estimation value at the next sampling moment based on the forward estimation coefficient at the current sampling moment and the acquired voltage vector at the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value at the next sampling moment and the voltage ideal value at the next sampling moment on the ideal voltage curve until the voltage estimation value is equal to the corresponding voltage ideal value;
initializing the forward estimation coefficient h1(1)=[1/M,1/M,…1/M]1×MAnd M is a preset number of voltage acquisition numbers for forward estimation, and the initialization adjustment inverse matrix is a unit matrix:
in the formula, h1(1) Is a forward estimation coefficient, P, at the 1 st sampling instant1(1) Adjusting an inverse matrix for the 1 st sampling moment;
the process of calculating the forward estimation coefficient of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquisition voltage vector of the next sampling moment and the forward estimation coefficient of the current moment comprises the following steps: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment is composed of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; calculating a forward estimation coefficient of the next sampling moment based on the forward estimation coefficient of the current moment, the voltage difference value of the next sampling moment and the gain vector of the next sampling moment;
the process of calculating the adjustment inverse matrix at the next sampling moment by utilizing the adjustment inverse matrix at the current sampling moment, the acquisition voltage vector at the next sampling moment and the forward estimation coefficient at the current moment comprises the following steps: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment is composed of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; calculating an adjustment inverse matrix at the next sampling moment by using the adjustment inverse matrix at the current sampling moment, the acquired voltage vector at the next sampling moment and the gain vector at the next sampling moment;
the gain vector calculation formula for the next sampling instant is as follows:
in the formula, K1(n+1) is the gain vector at the next sampling instant, P1(n) is the inverse of the adjustment for the current sampling instant, v1(n+1) is the collected voltage vector at the next sampling moment;
forward estimation coefficient h of next sampling moment1(n +1) the calculation formula is as follows:
in the formula, h1(n +1) is the forward estimation coefficient at the next sampling instant, h1(n) For the forward estimation coefficient at the current time, K1(n+1) is the gain vector at the next sampling timev(n+1) is the voltage difference value at the next sampling moment, and the difference value between the voltage estimation value and the voltage ideal value at the next sampling moment is the voltage difference value at the next sampling moment;
the adjustment inverse matrix calculation formula at the next sampling moment is as follows:
in the formula, P1(n+1) is the adjusted inverse matrix for the next sampling instant.
2. The adaptive formation method for improving the parameter consistency of the lithium ion battery according to claim 1, wherein the collected voltage vector at the current sampling time is composed of a voltage collected at the current sampling time and voltages collected at a preset number of sampling times before the current sampling time.
3. The adaptive formation method for improving the parameter consistency of the lithium ion battery according to claim 2, wherein when the voltage estimation value at the next sampling time is not equal to the corresponding voltage ideal value, the process of adjusting the charging current in the next sampling interval based on the difference between the voltage estimation value at the next sampling time and the corresponding voltage ideal value comprises:
calculating a voltage difference value based on the voltage estimated value and the voltage ideal value at the next sampling moment;
calculating a current adjustment offset based on the voltage difference value, a preset maximum voltage difference value and a preset maximum current difference value;
taking the difference value between the preset charging current value in the next sampling interval and the current adjustment offset value as a charging current calculation value in the next sampling interval;
and when the calculated value of the charging current in the next sampling interval is in the preset range, taking the calculated value as the charging current in the next sampling interval.
4. The adaptive formation method for improving the consistency of parameters of lithium ion batteries according to claim 3, wherein when the estimated voltage value at the next sampling time is not equal to the ideal voltage value corresponding to the estimated voltage value, the process of adjusting the charging current in the next sampling interval based on the difference between the estimated voltage value and the ideal voltage value further comprises:
and when the calculated value of the charging current in the next sampling interval exceeds the preset maximum current threshold, taking the preset maximum current threshold as the charging current in the next sampling interval.
5. The adaptive formation method for improving the consistency of parameters of lithium ion batteries according to claim 3, wherein when the estimated voltage value at the next sampling time is not equal to the ideal voltage value corresponding to the estimated voltage value, the process of adjusting the charging current in the next sampling interval based on the difference between the estimated voltage value and the ideal voltage value further comprises:
and when the calculated value of the charging current in the next sampling interval is lower than the preset minimum current threshold, taking the preset minimum current threshold as the charging current in the next sampling interval.
6. An adaptive formation system for improving the consistency of lithium ion battery parameters, comprising:
the device comprises an initialization module, a forward estimation module and a reverse matrix adjustment module, wherein the initialization module is used for initializing a forward estimation coefficient and adjusting the reverse matrix based on a preset number of voltage sampling data for forward estimation;
the forward estimation judging module is used for calculating a voltage estimation value at the next sampling moment based on a forward estimation coefficient at the current sampling moment and a collected voltage vector at the current sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted or not according to the voltage estimation value at the next sampling moment and a voltage ideal value at the next sampling moment on an ideal voltage curve;
the adjusting module is used for adjusting the charging current in the next sampling interval based on the difference value of the voltage estimated value at the next sampling moment and the corresponding voltage ideal value when the voltage estimated value at the next sampling moment is not equal to the corresponding voltage ideal value;
the backward verification updating module is used for calculating a forward estimation coefficient of the next sampling moment and an adjustment inverse matrix of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquired voltage vector of the next sampling moment and the forward estimation coefficient of the current moment;
the circulating module is used for returning to the step of calculating the voltage estimation value of the next sampling moment based on the forward estimation coefficient of the current sampling moment and the acquired voltage vector of the current sampling moment at the next sampling moment, and judging whether the charging current in the next sampling interval needs to be adjusted according to the voltage estimation value of the next sampling moment and the voltage ideal value of the next sampling moment on the ideal voltage curve until the voltage estimation value is equal to the corresponding voltage ideal value;
initializing the forward estimation coefficient h1(1)=[1/M,1/M,…1/M]1×MAnd M is a preset number of voltage acquisition numbers for forward estimation, and the initialization adjustment inverse matrix is a unit matrix:
in the formula, h1(1) Is a forward estimation coefficient, P, at the 1 st sampling instant1(1) For adjustment of the 1 st sampling instantAn inverse matrix;
the process of calculating the forward estimation coefficient of the next sampling moment by utilizing the adjustment inverse matrix of the current sampling moment, the acquisition voltage vector of the next sampling moment and the forward estimation coefficient of the current moment comprises the following steps: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment is composed of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; calculating a forward estimation coefficient of the next sampling moment based on a forward estimation coefficient of the current moment, a voltage difference value of the next sampling moment and a gain vector of the next sampling moment;
the process of calculating the adjustment inverse matrix at the next sampling moment by utilizing the adjustment inverse matrix at the current sampling moment, the acquisition voltage vector at the next sampling moment and the forward estimation coefficient at the current moment comprises the following steps: calculating a gain vector of the next sampling moment by using the adjustment inverse matrix of the current sampling moment and the acquired voltage vector of the next sampling moment, wherein the acquired voltage vector of the next sampling moment is composed of the voltage acquired at the next sampling moment and the voltages acquired at the sampling moments in a preset number before the next sampling moment; calculating an adjustment inverse matrix at the next sampling moment by using the adjustment inverse matrix at the current sampling moment, the acquired voltage vector at the next sampling moment and the gain vector at the next sampling moment;
the gain vector calculation formula for the next sampling instant is as follows:
in the formula, K1(n+1) is the gain vector at the next sampling instant, P1(n) is the inverse of the adjustment for the current sampling instant, v1(n+1) is the collected voltage vector at the next sampling moment;
forward estimation coefficient h of next sampling moment1(n +1) the calculation formula is as follows:
in the formula, h1(n +1) is the forward estimation coefficient at the next sampling instant, h1(n) For the forward estimation coefficient at the current time, K1(n+1) is the gain vector at the next sampling timev(n+1) is the voltage difference value at the next sampling moment, and the difference value between the voltage estimation value and the voltage ideal value at the next sampling moment is the voltage difference value at the next sampling moment;
the adjustment inverse matrix calculation formula at the next sampling moment is as follows:
in the formula, P1(n+1) is the adjusted inverse matrix for the next sampling instant.
7. A computer device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to cause the at least one processor to perform the adaptive formation method for improving lithium ion battery parameter uniformity of any of claims 1-5.
8. A computer-readable storage medium storing computer instructions for causing a computer to perform the adaptive formation method for improving consistency of lithium ion battery parameters according to any one of claims 1 to 5.
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