Intelligent pulping method for lithium battery multi-phase slurry based on particle collaborative self-adaption

Abstract

The invention discloses a lithium battery multi-phase slurry intelligent pulping method based on particle collaborative self-adaption, and relates to the technical field of multi-phase slurry pulping. The method comprises the following steps: adding a lithium battery material, a conductive agent and a binder into a solvent in proportion, and stirring at a low speed to obtain coarse dispersion slurry; obtaining particle size distribution, conductivity change rate and shear residual pressure response through laser particle size analysis and conductivity induction, and generating a particle synergy degree feature vector; monitoring the variation trend of the vector based on the reconstruction period, dynamically adjusting the shearing rate, the stirring path and the impeller structure, and constructing slurry self-adaptive dynamic domain distribution; whether the slurry is stable or not is judged by combining the characteristic vector variation amplitude and the conductive path construction rate, and if not, feedback adjustment is conducted. According to the invention, intelligent regulation and control and structure self-optimization of the slurry beating process are realized, and the dispersion uniformity and the system stability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of multiphase slurry beating, and in particular to an intelligent beating method for multiphase slurry of lithium batteries based on particle collaborative self-adaptation. Background Art

[0002] The widespread application of energy storage lithium batteries in new energy power stations, communication base stations, and emergency energy supply scenarios places higher demands on electrode quality stability and slurry dispersion uniformity. Current slurry beating processes generally rely on high-speed shearing or staged stirring with fixed parameters. However, these processes lack the ability to identify the evolution of particle behavior in real time and are unable to adapt to complex variables such as differences in active material particle size distribution and fluctuations in the degree of conductive agent agglomeration. This results in unstable slurry structure and discontinuous conductive networks, which in turn affects electrode consistency and cycle performance.

[0003] Existing technologies have failed to establish a pulping feedback mechanism with particle synergy as the core indicator, and also lack the means to identify and control the slurry dynamic domain in real time. The pulping process has problems such as energy waste, low dispersion efficiency and poor repeatability, which restricts the consistent manufacturing of high-performance energy storage batteries. Summary of the Invention

[0004] In view of this, the present invention proposes an intelligent beating method for lithium battery multiphase slurry based on particle collaborative self-adaptation. By constructing a particle collaborative state recognition and power domain reconstruction mechanism, intelligent adjustment and structural self-optimization of the beating process are realized, thereby improving the slurry dispersion effect and structural stability.

[0005] The present invention proposes an intelligent beating method for lithium battery multiphase slurry based on particle collaborative self-adaptation, comprising: S1: adding lithium battery material, conductive agent and binder into a solvent according to a preset mass ratio and stirring at a low speed to obtain a slurry in a coarsely dispersed particle state; S2: Through laser particle size analysis and conductivity sensing, the particle size distribution, conductivity change rate and shear residual pressure response in the slurry are obtained in real time to generate the particle synergy feature vector; S3: Based on the preset dynamic domain reconstruction cycle and the particle synergy characteristic vector, the state change trend of the particle synergy characteristic vector is recorded, and the energy input of the stirring device is dynamically adjusted according to the state change trend of the particle synergy characteristic vector to construct an adaptive dynamic domain distribution of the slurry; S4: Based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period and the particle synergy characteristic vector, determine whether the slurry is in a stable state. If it is not a stable state, return to S3, change the energy input and adjust the adaptive power domain distribution.

[0006] Furthermore, the low-speed stirring specifically means that the stirring speed is not higher than 200 rpm and the stirring duration is not less than 10 minutes.

[0007] Furthermore, the particle synergy characteristic vector includes: particle size distribution deviation, particle-particle specific surface area coupling, and conductive path construction rate.

[0008] Furthermore, the particle size distribution deviation is obtained by the particle size distribution statistical variance, the particle-particle specific surface area coupling is calculated based on the particle-particle specific surface area overlap ratio, and the conductive path construction rate is estimated based on the conductivity change rate and the shear residual pressure response.

[0009] Furthermore, the power domain reconstruction cycle is no more than 90 seconds, the energy input includes shear rate, stirring path and impeller structure, and the adaptive power domain distribution of the slurry includes a shear-dominant region, a convection boundary region and an inefficient retention region.

[0010] Furthermore, the shear rate is 10 Hz-70 Hz, and the impeller structure has an inclination angle of 10°-45°.

[0011] Furthermore, the method of judging whether the slurry is in a stable state based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period in combination with the particle synergy characteristic vector is specifically based on whether the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period is less than a preset amplitude threshold, and whether the conductive path construction rate in the particle synergy characteristic vector is in a plateau period, to jointly judge whether the slurry is in a stable state.

[0012] Furthermore, the slurry is judged to be in a stable state when the variation amplitude of the particle synergy characteristic vector in the dynamic domain reconstruction period is less than a preset amplitude threshold and the conductive path construction rate is in a plateau period.

[0013] Compared with the prior art, the beneficial effects of the present invention are: the intelligent beating method for lithium battery multiphase slurry based on particle synergy self-adaptation of the present invention constructs a particle synergy characteristic vector through indicators such as particle size distribution deviation, particle-particle specific surface area coupling and conductive path construction rate, which can comprehensively reflect the spatial consistency, agglomeration trend and conductive network construction efficiency of multiphase particles in the slurry, thereby providing a quantitative and feedback criterion basis for beating control; the intelligent beating method for lithium battery multiphase slurry based on particle synergy self-adaptation of the present invention sets a dynamic domain reconstruction cycle, and based on the dynamic change trend of the particle synergy state, adaptively adjusts the shear rate, stirring path and impeller structure to construct functional areas such as shear dominant area, convection boundary area and inefficient retention area, so that the beating energy is focused on areas with severe agglomeration or uneven distribution, effectively improving the dispersion efficiency of particles and the uniformity of slurry structure, and reducing energy consumption redundancy; the intelligent beating method for lithium battery multiphase slurry based on particle synergy self-adaptation of the present invention realizes dynamic identification and feedback control of the slurry microstructure state by judging the change amplitude of the particle synergy characteristic vector in multiple dynamic domain reconstruction cycles and the plateau period of the conductive path construction rate. When the slurry has not reached a stable state, the beating parameters are automatically adjusted to avoid problems such as over-beating or insufficient dispersion due to insufficient manual intervention, ensuring the stability and repeatability of the slurry quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings: Figure 1 This is a flow chart of an intelligent beating method for lithium battery multiphase slurry based on particle collaborative adaptation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments. Example 1:

[0016] See Figure 1 As shown, an embodiment of the present invention provides a method for intelligent beating of lithium battery multiphase slurry based on particle collaborative self-adaptation, comprising: S1: adding lithium battery material, conductive agent and binder into a solvent according to a preset mass ratio and stirring at a low speed to obtain a slurry in a coarsely dispersed particle state; S2: Through laser particle size analysis and conductivity sensing, the particle size distribution, conductivity change rate and shear residual pressure response in the slurry are obtained in real time to generate the particle synergy feature vector; S3: Based on the preset dynamic domain reconstruction cycle and the particle synergy characteristic vector, the state change trend of the particle synergy characteristic vector is recorded, and the energy input of the stirring device is dynamically adjusted according to the state change trend of the particle synergy characteristic vector to construct an adaptive dynamic domain distribution of the slurry; S4: Based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period and the particle synergy characteristic vector, determine whether the slurry is in a stable state. If it is not a stable state, return to S3, change the energy input and adjust the adaptive power domain distribution.

[0017] Furthermore, the low-speed stirring specifically means that the stirring speed is not higher than 200 rpm and the stirring duration is not less than 10 minutes.

[0018] Specifically, the lithium battery material, conductive agent and binder are weighed in sequence according to a preset mass ratio and slowly added to a pre-prepared organic solvent or aqueous solvent. The solvent is selected from NMP, deionized water or a compound system thereof, and ensure that the viscosity of the system is moderate and the surface tension is adapted to the slurry dispersion requirements; at room temperature or set constant temperature conditions, preliminary mixing is carried out by a low-speed stirring device, and the stirring speed is controlled between 150-200rpm to make the solid phase components evenly distributed in the liquid phase, and gradually form a slurry in a coarsely dispersed particle state. No strong shear force is introduced at this stage, and the main purpose is to achieve the wet coating of each particle and the initial establishment of spatial distribution, laying the foundation for subsequent refined dispersion and coordinated adjustment of the power domain.

[0019] Specifically, the specific content of S2 is: through laser particle size analysis and conductivity sensing, the particle size distribution, conductivity change rate and shear residual pressure response in the slurry are obtained in real time, among which, the particle size distribution is collected by the online laser particle size analyzer to obtain the real-time distribution curve of the particles in the liquid phase, the conductivity change rate is monitored by the conductivity sensor to monitor the changing trend of the conductive properties of the slurry in unit time, and the shear residual pressure response is evaluated by the shear resistance sensing unit in the stirring device to evaluate the residual viscoelasticity change of the slurry under shear state; based on the above three parameters, the statistical deviation of the particle size distribution, the conductive path construction rate and the particle-particle specific surface area coupling degree and other parameters are extracted respectively, and the multi-dimensional particle synergy characteristic vector is constructed by setting weights to characterize the synergy, dispersion uniformity and network structure evolution state between the particles of each phase in the slurry.

[0020] Furthermore, the particle synergy characteristic vector includes: particle size distribution deviation, particle-particle specific surface area coupling, and conductive path construction rate.

[0021] Furthermore, the particle size distribution deviation is obtained by the particle size distribution statistical variance, the particle-particle specific surface area coupling is calculated based on the particle-particle specific surface area overlap ratio, and the conductive path construction rate is estimated based on the conductivity change rate and the shear residual pressure response.

[0022] Specifically, the particle size distribution deviation is calculated by statistically processing the particle size distribution data collected in real time in the slurry, and the variance value of the particle size distribution is calculated to measure the uniformity and concentration of the particles in the dispersed state. The larger the deviation, the more uneven the particle distribution. The particle-particle specific surface area coupling is calculated based on the specific surface area overlap ratio of the particles in the slurry, specifically the ratio of the specific surface area overlap area of ​​adjacent particles per unit volume to the theoretical maximum overlap area, which is used to reflect the spatial proximity between particles and the potential agglomeration risk. The conductive path construction rate is estimated based on the combined relationship between the conductivity change rate and the shear residual pressure response, reflecting the formation efficiency of the conductive network under specific shear energy input. When the shear residual pressure decreases and the conductivity rises rapidly, it means that the conductive particles have formed a stable path and the conductive path construction rate tends to saturation.

[0023] Furthermore, the power domain reconstruction cycle is no more than 90 seconds, the energy input includes shear rate, stirring path and impeller structure, and the adaptive power domain distribution of the slurry includes a shear-dominant region, a convection boundary region and an inefficient retention region.

[0024] Specifically, the dynamic domain reconstruction cycle is no more than 90 seconds, which means that during the slurry beating process, the changes in the particle synergy characteristic vector are regularly evaluated with a feedback cycle of no more than 90 seconds, and a dynamic domain structure adjustment is triggered accordingly; the energy input includes shear rate, stirring path and impeller structure, wherein the shear rate controls the intensity and frequency of the shear force exerted on the particles in the slurry, the stirring path changes the distribution direction of energy inside the slurry by adjusting the motion trajectory of the stirring device, and the impeller structure adjusts the local disturbance intensity by setting different inclination angles, levels or edge shapes; the adaptive dynamic domain distribution of the slurry includes a shear-dominant area, a convection boundary area and an inefficient retention area. The shear-dominant area is a high-energy area that mainly undertakes particle disaggregation and dispersion, the convection boundary area is a medium shear transition area connecting the dominant area and the groove wall area, and the inefficient retention area is an area with low local flow velocity and easy accumulation of particles; by periodically reconstructing the above-mentioned dynamic domain distribution, the internal flow field of the slurry can be optimized and adjusted, so that the particles can obtain adaptive energy input in different areas, thereby improving the overall dispersion efficiency and structural uniformity.

[0025] Furthermore, the shear rate is 10 Hz-70 Hz, and the impeller structure has an inclination angle of 10°-45°.

[0026] Furthermore, the method of judging whether the slurry is in a stable state based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period in combination with the particle synergy characteristic vector is specifically based on whether the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period is less than a preset amplitude threshold, and whether the conductive path construction rate in the particle synergy characteristic vector is in a plateau period, to jointly judge whether the slurry is in a stable state.

[0027] Specifically, during multiple consecutive power domain reconstruction cycles, the various indicator values ​​of the particle synergy characteristic vector are recorded in real time, and the variation range between adjacent cycles is calculated; when the variation range is lower than the preset amplitude threshold, it indicates that the particle synergy is in a stable trend, and at the same time, it is judged whether the conductive path construction rate in the particle synergy characteristic vector has entered a plateau period, that is, when the conductive path formation rate tends to be constant and the conductive performance has not been significantly improved, it can be comprehensively considered that the slurry has reached a microstructural stability state; if any condition is not met, the slurry is deemed to be still in the structural evolution stage, and power domain adjustment and energy input optimization need to continue; the stability judgment strategy effectively avoids misjudgment due to fluctuations in a single indicator, ensuring that the slurry has long-term consistency and batch repeatability.

[0028] Furthermore, the slurry is judged to be in a stable state when the variation amplitude of the particle synergy characteristic vector in the dynamic domain reconstruction period is less than a preset amplitude threshold and the conductive path construction rate is in a plateau period. Example 2:

[0029] This embodiment uses lithium iron phosphate as the positive electrode material, a conductive agent is a mixture of carbon nanotubes and acetylene black, a binder is PVDF, and a solvent is NMP. The raw materials are weighed in a mass ratio of 96:2:2, placed in a ball mill dispersion tank, and stirred at low speed for 10 minutes for pre-wetting; the particle size monitoring device and the conductivity array are turned on to record the particle size D50, D90, conductivity change rate, and shear residual pressure response in real time; when the D90-D10 deviation is greater than 20μm, or the conductive path construction rate is less than 90%, the impeller structure inclination angle is adjusted to 30° and the shear frequency is increased to 50Hz to construct a high-energy shear dominant zone, and the shear is continued for 3 minutes before re-evaluation; when the change amplitude of the particle synergy characteristic vector in the dynamic domain reconstruction cycle is less than the preset amplitude threshold and the conductivity reaches the set platform value (change rate <1% / min), the slurry structure is automatically judged to be stable, the power is reduced, and the stirring is stopped.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for intelligent beating of lithium battery multiphase slurry based on particle collaborative adaptation, characterized in that: include: S1: adding lithium battery material, conductive agent and binder into a solvent according to a preset mass ratio and stirring at a low speed to obtain a slurry in a coarsely dispersed particle state; S2: Through laser particle size analysis and conductivity sensing, the particle size distribution, conductivity change rate and shear residual pressure response in the slurry are obtained in real time to generate the particle synergy feature vector; S3: Based on the preset dynamic domain reconstruction cycle and the particle synergy characteristic vector, the state change trend of the particle synergy characteristic vector is recorded, and the energy input of the stirring device is dynamically adjusted according to the state change trend of the particle synergy characteristic vector to construct an adaptive dynamic domain distribution of the slurry; S4: Based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period and the particle synergy characteristic vector, determine whether the slurry is in a stable state. If it is not a stable state, return to S3, change the energy input and adjust the adaptive power domain distribution.

2. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 1, characterized in that: The low-speed stirring specifically means that the stirring speed is not higher than 200 rpm and the stirring duration is not less than 10 minutes.

3. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 2, characterized in that: The particle synergy characteristic vector includes: particle size distribution deviation, particle-particle specific surface area coupling, and conductive path construction rate.

4. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 3, characterized in that: The particle size distribution deviation is obtained by the particle size distribution statistical variance, the particle-particle specific surface area coupling is calculated based on the particle-particle specific surface area overlap ratio, and the conductive path construction rate is estimated based on the conductivity change rate and the shear residual pressure response.

5. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 4, characterized in that: The power domain reconstruction cycle is no more than 90 seconds, the energy input includes shear rate, stirring path and impeller structure, and the adaptive power domain distribution of the slurry includes a shear-dominant area, a convection boundary area and an inefficient retention area.

6. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 5, characterized in that: The shear rate is 10 Hz-70 Hz, and the impeller structure has an inclination angle of 10°-45°.

7. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 6, characterized in that: The method of judging whether the slurry is in a stable state based on the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period in combination with the particle synergy characteristic vector is specifically based on whether the change amplitude of the particle synergy characteristic vector in the power domain reconstruction period is less than a preset amplitude threshold, and whether the conductive path construction rate in the particle synergy characteristic vector is in a plateau period, to jointly judge whether the slurry is in a stable state.

8. The method for intelligent beating of lithium battery multiphase slurry based on particle cooperative adaptation according to claim 7, characterized in that: The slurry is judged to be in a stable state when the variation amplitude of the particle synergy characteristic vector in the dynamic domain reconstruction period is less than a preset amplitude threshold and the conductive path construction rate is in a plateau period.

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