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CN-115902640-B - Construction method, estimation method, equipment and medium of battery OCV-SOC curve estimation model

CN115902640BCN 115902640 BCN115902640 BCN 115902640BCN-115902640-B

Abstract

The application discloses a construction method, an estimation method, equipment and a medium of a battery OCV-SOC curve estimation model, wherein the method comprises the steps of obtaining charging curves of a battery under different charging multiplying powers; the method comprises the steps of constructing a charging matrix under corresponding multiplying power according to a charging curve, calculating charging coefficients of the charging matrix under different multiplying power, and obtaining a battery OCV-SOC curve estimation model according to the charging curve and the charging coefficients. According to the method, the voltage curves under different multiplying powers are tested, and the voltage curves with multiplying powers of zero are obtained through deduction, so that the time required by the test is greatly reduced, and the problem of unstable test caused by the fact that the test process is too long is avoided.

Inventors

  • Li Miangang

Assignees

  • 欣旺达电动汽车电池有限公司

Dates

Publication Date
20260508
Application Date
20221130

Claims (8)

  1. 1. The method for constructing the OCV-SOC curve estimation model of the battery is characterized by comprising the following steps of: Acquiring charging curves of the battery under different charging multiplying powers; The method for constructing the charging matrix under the corresponding multiplying power according to the charging curve comprises the steps of obtaining voltage data and current data in charging data, constructing and obtaining the voltage matrix according to the obtained voltage data and the obtained current data, namely, the charging matrix, wherein a calculation formula is as follows: ; Wherein U is a voltage matrix, For a specific voltage value, SOC 1 ~SOC n represents n pieces of acquired SOC charging data, I 1 ~I m is a current corresponding to a voltage in the SOC charging data, and n and m are integers; The method comprises the steps of calculating the charging coefficients of the charging matrix under different multiplying powers, respectively carrying out singular value decomposition on the obtained charging matrix under different multiplying powers, reserving part of effective data after singular value decomposition to obtain a first decomposition matrix, splitting from the first decomposition matrix to obtain a second decomposition matrix, and carrying out linear fitting on elements in the second decomposition matrix to obtain the charging coefficients; the battery OCV-SOC curve estimation model is obtained according to the charging curve and the charging coefficient, and comprises the steps of fitting the charging coefficients under different multiplying powers to obtain a zero multiplying power charging coefficient, and obtaining a zero multiplying power charging curve according to the zero multiplying power charging coefficient to obtain the battery OCV-SOC curve estimation model.
  2. 2. The method for constructing the OCV-SOC curve estimation model of the battery according to claim 1, wherein the method for acquiring the charging curves of the battery at different charging rates comprises the steps of: discharging the battery from a first voltage to a second voltage by a stepwise discharge; charging the battery from the second voltage to the first voltage at an A multiplying power, and recording voltage data of the A multiplying power; Charging the battery from a second voltage to a first voltage at a 0.5A rate, and recording voltage data of the 0.5A rate; charging the battery from a second voltage to a first voltage at a 0.05A rate, and recording voltage data of the 0.05A rate; and drawing a charging curve of the battery according to the A multiplying power, the 0.5A multiplying power and the voltage data under the 0.05A multiplying power.
  3. 3. The method of constructing an OCV-SOC curve estimation model for a battery according to claim 1, wherein the charging curve is a voltage curve including a relationship between a voltage value and an electric power value of the battery.
  4. 4. The method of constructing an OCV-SOC curve estimation model for a battery according to claim 2, wherein the method of discharging the battery from the first voltage to the second voltage by the stepwise discharging comprises the steps of: discharging the battery at a first voltage to a second voltage at the 0.5A rate; and continuously discharging the battery discharged to the second voltage at the 0.05A multiplying power and then continuously discharging the battery at the 0.02A multiplying power.
  5. 5. The method of constructing an OCV-SOC curve estimation model for a battery of claim 4, wherein the a-magnification is 2C, the 0.5A-magnification is 1C, the 0.05A-magnification is 0.1C, and the 0.02A-magnification is 0.04C.
  6. 6. A battery SOC estimation method, comprising the steps of: acquiring a battery voltage; Inputting the battery voltage into an estimation model obtained by the battery OCV-SOC curve estimation model construction method of any one of claims 1 to 5, obtaining an SOC value of the battery by an operation of the estimation model.
  7. 7. An electronic device characterized by comprising a memory and a processor, the memory for storing a computer program, the processor for implementing the battery OCV-SOC curve estimation model construction method of any of claims 1 to 5 or the battery SOC estimation method of claim 6 when the computer program is executed.
  8. 8. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processor, implements the battery OCV-SOC curve estimation model construction method according to any one of claims 1 to 5 or implements the battery SOC estimation method according to claim 6.

Description

Construction method, estimation method, equipment and medium of battery OCV-SOC curve estimation model Technical Field The invention relates to the technical field of battery OCV-SOC estimation, in particular to a method for constructing a battery OCV-SOC curve estimation model, an estimation method, equipment and a medium. Background The existing testing method of the OCV-SOC curve of the lithium ion battery is mainly divided into a static method and a dynamic method. The static method adopts the steps that after the initial SOC is tested for the open-circuit voltage, a pulse current is applied to adjust the SOC, then the static method is kept for a long time to measure the completely stable voltage as the open-circuit voltage of the current SOC, and the OCV of a plurality of SOCs is repeatedly obtained. The dynamic method adopts a tiny current (usually 0.04C) to carry out full charge or discharge test, and the obtained voltage curve is approximately equivalent to an open-circuit voltage curve. The static method can not obtain the OCV of all the SOCs, the OCV of the unmeasured SOCs can only be obtained through interpolation, the precision of the obtained OCV-SOC curve is reduced, the standing time is long, and the short-time standing may not reach the thermodynamic condition yet. The test time of the dynamic method is too long, the theoretical time length required for obtaining a single charge or discharge OCV-SOC curve at 0.04C is 25 hours, the test failure can be caused by instability at any point in the process, the 0.04C is not equal to no current, and obvious polarization still can be generated in a battery with larger impedance so that the measured voltage curve deviates from the OCV. Therefore, neither the static method nor the dynamic method can fully meet the current demands for OCV-SOC testing. Disclosure of Invention The embodiment of the application provides a method for constructing a battery OCV-SOC curve estimation model, an estimation method, equipment and a medium, which are used for solving the technical problems of long test time and low test result precision in the prior art. In order to solve the technical problems, the embodiment of the application discloses the following technical scheme: in a first aspect, a method for constructing a battery OCV-SOC curve estimation model is provided, the method comprising: Acquiring charging curves of the battery under different charging multiplying powers; constructing a charging matrix under corresponding multiplying power according to the charging curve; Calculating the charging coefficients of the charging matrix under different multiplying powers; and obtaining the battery OCV-SOC curve estimation model according to the charging curve and the charging coefficient. With reference to the first aspect, the method for constructing a charging matrix according to the charging data includes the following steps: Acquiring voltage data and current data in the charging data; constructing and obtaining a voltage matrix according to the obtained voltage data and the obtained current data, namely a charging matrix; The calculation formula is as follows: Wherein, U is a voltage matrix, U I1,SOC1 is a specific voltage value, SOC 1～SOCn represents n pieces of obtained SOC charging data, I 1～Im is a current corresponding to a voltage in the SOC charging data, and n and m are integers. With reference to the first aspect, the method for calculating the charging coefficients of the charging matrix under different multiplying powers includes the following steps: Respectively carrying out singular value decomposition on the obtained charging matrixes under different multiplying powers; reserving part of effective data after singular value decomposition to obtain a first decomposition matrix; splitting from the first decomposition matrix to obtain a second decomposition matrix; And performing linear fitting on the elements in the second decomposition matrix to obtain a charging coefficient. With reference to the first aspect, the method for obtaining the OCV-SOC curve estimation model of the battery according to the charging curve and the charging coefficient includes the following steps: Fitting the charging coefficients under different multiplying powers to obtain a zero multiplying power charging coefficient; And obtaining a zero-rate charging curve according to the zero-rate charging coefficient, namely obtaining the OCV-SOC curve estimation model of the battery. With reference to the first aspect, the method for obtaining the charging curves of the battery under different charging rates includes the following steps: discharging the battery from a first voltage to a second voltage by a stepwise discharge; charging the battery from the second voltage to the first voltage at an A multiplying power, and recording voltage data of the A multiplying power; Charging the battery from a second voltage to a first voltage at a 0.5A rate, and recording voltage data of the 0