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CN-122021006-A - Method, device and storage medium for predicting moisture baking effect of battery cell

CN122021006ACN 122021006 ACN122021006 ACN 122021006ACN-122021006-A

Abstract

The invention discloses a method, a device and a storage medium for predicting a moisture baking effect of a battery cell, wherein the method comprises the steps of constructing a heat transfer simulation model comprising a heat source area and a heated area based on a baking cavity structure of battery cell baking equipment, acquiring initial data related to a heat field of a historical baking process and a pre-trained heat source model as simulation boundary conditions, wherein the heat source model represents a corresponding relation between temperature distribution and heating power of the heat source area, performing transient simulation on the thermal field distribution of the whole baking process to be tested according to the simulation boundary conditions and the initial data related to the heat field of the baking process to be tested through the heat transfer simulation model, predicting to obtain temperature changes of each battery cell in the heated area, dynamically positioning heating weak points based on the temperature changes of each battery cell, predicting to obtain worst baking effects of the baking process to be tested in different time periods, realizing accurate prediction on the temperature changes of each battery cell in the baking process, and obtaining the changes of the heating weak points in the whole baking process.

Inventors

  • WANG ZULIN
  • CHEN MINGTAO
  • Hao Pengjie

Assignees

  • 合肥国轩高科动力能源有限公司

Dates

Publication Date
20260512
Application Date
20260121

Claims (10)

  1. 1. The method for predicting the baking effect of the moisture of the battery cell is characterized by comprising the following steps of: Constructing a heat transfer simulation model based on a baking cavity structure of the battery cell baking equipment, wherein the heat transfer simulation model comprises a heat source area and a heated area; Acquiring thermal field related initial data of a historical baking process and a pre-trained heat source model as simulation boundary conditions, wherein the heat source model represents a corresponding relation between the temperature distribution of a heat source area and the heating power; According to the simulation boundary conditions and the thermal field related initial data of the baking process to be tested, carrying out transient simulation on the thermal field distribution of the whole baking process to be tested through a heat transfer simulation model, and predicting to obtain the temperature change of each cell in the heated area; And dynamically positioning the heating weak points based on the temperature change of each battery cell, and predicting to obtain the worst baking effect of the baking process to be tested in different time periods.
  2. 2. The method for predicting the baking effect of the moisture in the battery cell according to claim 1, wherein the constructing the heat transfer simulation model based on the baking cavity structure of the battery cell baking device comprises: measuring the size of the interior of a baking cavity of baking equipment, and building a three-dimensional simulation model according to the measured data; And cutting the three-dimensional simulation model into a heat source region and a heated region through Boolean operation.
  3. 3. The method for predicting the baking effect of the electric core moisture according to claim 1, wherein the initial data related to the thermal field comprises an initial heating device temperature of a heat source region, an initial heating device temperature of a heat receiving region, an initial environment temperature and a preset heating power curve; the simulation boundary conditions also comprise the heat conductivity coefficient, density and specific heat capacity of the heating device and the heated device.
  4. 4. The method for predicting the baking effect of the moisture in the battery cell according to claim 3, wherein the training method of the heat source model comprises the steps of: Acquiring historical operation data of a heat source area under different working conditions, wherein the historical operation data comprises a baking temperature sequence and a baking power output ratio sequence of a heating device; establishing a corresponding relation table between baking temperature and baking power output ratio according to the historical operation data; Segmenting the baking temperature sequence, and modeling a regression function adapted to the data trend on each segment of the corresponding relation according to the corresponding relation to obtain a heat source model.
  5. 5. The method for predicting the moisture baking effect of the electrical core according to claim 1, wherein the transient simulation of the thermal field distribution of the whole baking process to be tested by the heat transfer simulation model predicts the temperature change of each electrical core in the heated area, and comprises the following steps: Grid division is carried out on the solid area in the heat transfer simulation model, so that a plurality of heat source grid areas and heated grid areas are obtained; refining the heat source grid region and coarsening the heated grid region to obtain an optimized solid grid region; and solving a heat transfer equation by using a direct solver to obtain the temperature value of each solid grid area at each moment of the baking process to be tested.
  6. 6. The method for predicting the moisture baking effect of a battery cell according to claim 1, wherein the transient simulation is performed on the thermal field distribution of the whole baking process to be tested through a heat transfer simulation model, and the method for predicting the temperature change of each battery cell in the heated area further comprises: Displaying the temperature distribution and the change in the thermal simulation model by using a visualization tool; According to the visual result, analyzing the temperature field distribution of the battery cell in the baking industry to be tested; judging the temperature rising speed area of the power core according to the analysis result, and marking the specific position.
  7. 7. The method for predicting a moisture baking effect of a battery cell according to claim 1, wherein the dynamically positioning the heating weak point based on the temperature change of each battery cell comprises: Extracting a volume average temperature heating curve of each battery cell according to the temperature distribution of each battery cell in the current time period of the baking process to be tested; Analyzing characteristic parameters of volume average temperature heating curves of all the electric cores, screening out the electric core with the minimum volume average temperature heating rate or the lowest final volume average temperature, and taking the position of a baking cavity where the electric core is positioned as a heating weak point of the current time period of the baking process to be tested.
  8. 8. The method for predicting the baking effect of the moisture of the battery cell according to claim 1, wherein after the predicting obtains the worst baking effect of the baking process to be tested in different time periods, the method further comprises: And comparing the predicted baking effect at the heating weak point of each time period with a preset minimum baking effect threshold, and if the predicted baking effect is lower than the minimum baking effect threshold, adjusting relevant parameters of the heat source region.
  9. 9. The utility model provides a electricity core moisture toasts effect prediction device which characterized in that includes: the heat transfer simulation model construction module is used for constructing a heat transfer simulation model based on a baking cavity structure of the battery cell baking equipment, wherein the heat transfer simulation model comprises a heat source area and a heated area; the simulation boundary condition acquisition module is used for acquiring thermal field related initial data of a historical baking process and a pre-trained heat source model as simulation boundary conditions, wherein the heat source model represents the corresponding relation between the temperature distribution of a heat source area and the heating power; The thermal field simulation module of the heated area is used for carrying out transient simulation on the thermal field distribution of the whole process of the baking process to be tested through the heat transfer simulation model according to the simulation boundary conditions and the thermal field related initial data of the baking process to be tested, and predicting to obtain the temperature change of each battery core in the heated area; And the baking prediction effect obtaining module is used for dynamically positioning the heating weak points based on the temperature change of each battery cell and predicting to obtain the worst baking effect of the baking process to be tested in different time periods.
  10. 10. A computer storage medium having a computer program stored thereon, which, when executed by a processor, implements the cell moisture baking effect prediction method according to any of claims 1-8.

Description

Method, device and storage medium for predicting moisture baking effect of battery cell Technical Field The invention belongs to the technical field of battery manufacturing, and particularly relates to a method and a device for predicting a moisture baking effect of a battery cell and a storage medium. Background In the manufacturing process of the lithium ion battery, the battery cell (comprising the positive and negative plates and the diaphragm) is subjected to a strict baking procedure before liquid injection so as to remove residual moisture and solvent in the battery cell. The exceeding moisture content can generate side reaction with electrolyte to generate gas, so that the battery bulges, the internal resistance is increased, the capacity is attenuated, and even serious potential safety hazards are caused. Thus, the cell baking effect directly determines the performance, life and safety of the final battery product. At present, a baking effect monitoring method commonly adopted in the industry is to place one or more 'false cells' (namely, moisture test cells) in baking equipment, take out the false cells for destructive moisture detection after baking is finished, and represent whether baking of the whole batch of cells meets the standard or not according to the result. The invention discloses a Chinese patent with publication number CN110797583A, and the name of the Chinese patent is a method for detecting the water content of a pole piece of a lithium ion battery before liquid injection, which comprises a preparation operation step, a measurement operation step and a post-treatment operation step, wherein in the measurement operation step, 1 baked battery is taken out and disassembled in a glove box, the water content of the positive pole piece and the negative pole piece and a diaphragm is detected, if the positive pole piece and the diaphragm are failed, the positive pole piece and the diaphragm are re-dried, and the positive pole piece and the diaphragm are detected until the water content is qualified, so that repeated tests for a plurality of times and collection of a large amount of water content test data are needed, the test process period is too long, the efficiency is low, and a single test result cannot represent the water content condition of other batteries in the same oven, and the accuracy is low. In the prior art, a heating weak point in the baking equipment is found in advance, so that a detection scheme of moisture content of other cells is represented by using a cell moisture content detection result at the heating weak point, and the method has the obvious defects that 1, the position is fixed and the dynamic adjustment cannot be realized, and the distribution of a thermal field in the baking equipment is influenced by various factors such as power of a heating element, air circulation, cell placement density, equipment tightness and the like. In actual production, the factors may fluctuate, so that the weakest heating position is shifted, the fixed test point cannot catch the change, and the detection omission risk is generated, and 2, the hysteresis and the destructiveness are that the moisture detection result can be obtained after baking is finished, and the serious hysteresis is provided. Once the moisture is found to be out of standard, the entire batch of cells may be rejected, resulting in significant waste. And the detection is destructive and cannot be used for 100% detection of a real product, and 3, the representative defects are that one or a plurality of test points are difficult to comprehensively represent all positions in a baking cavity, and particularly the baking uniformity of hundreds of electric cores. Disclosure of Invention The invention aims to provide a method, a device and a storage medium for predicting a cell moisture baking effect, which are used for dynamically simulating thermal field distribution of a baking process to be tested by constructing a heat transfer simulation model and using related data in a historical baking process as a simulation boundary, predicting the position of a cell with the worst baking effect in real time, and realizing accurate quality early warning according to the baking result of the cell. In order to achieve the above purpose, the invention is realized by adopting the following technical scheme: In a first aspect, the present invention provides a method for predicting a baking effect of moisture in a battery cell, including: Constructing a heat transfer simulation model based on a baking cavity structure of the battery cell baking equipment, wherein the heat transfer simulation model comprises a heat source area and a heated area; Acquiring thermal field related initial data of a historical baking process and a pre-trained heat source model as simulation boundary conditions, wherein the heat source model represents a corresponding relation between the temperature distribution of a heat source area and the heating