CN-122017606-A - Impedance spectrum analysis-based lithium battery internal short circuit diagnosis method and system

CN122017606ACN 122017606 ACN122017606 ACN 122017606ACN-122017606-A

Abstract

The invention relates to the technical field of lithium battery safety diagnosis, in particular to a lithium battery internal short circuit diagnosis method and system based on impedance spectrum analysis. The system performs three-dimensional impedance distribution reconstruction by acquiring dynamic impedance spectrum data of the battery, and extracts ohmic impedance gradient, charge transfer impedance accumulation amount and diffusion impedance fluctuation coefficient as internal impedance characteristics. And carrying out nonlinear anomaly analysis on the characteristics based on the pre-training model to generate a short circuit risk level and a potential short circuit area identifier. And after the working condition compensation correction is carried out by combining the temperature monitoring data, generating a safety coping strategy comprising current path adjustment and thermal management intervention according to the region identification. The technology realizes the accurate positioning and active directional prevention and control of the early hidden trouble of the internal short circuit.

Inventors

Huang Chunteng
Liang Chunsi
XIAO DONGJIN
LI LIUYANG

Assignees

东莞市鑫晟达智能装备有限公司

Dates

Publication Date: 20260512
Application Date: 20260411

Claims (9)

1. An impedance spectroscopy analysis-based lithium battery internal short circuit diagnosis system, characterized in that the system comprises: The data acquisition module is used for acquiring a dynamic impedance spectrum data set of the target lithium battery in the charge-discharge cycle process, wherein the dynamic impedance spectrum data set comprises a multi-frequency excitation signal sequence, a voltage response waveform sequence and temperature distribution monitoring data; The impedance field reconstruction module is used for carrying out three-dimensional impedance distribution reconstruction processing on the dynamic impedance spectrum data set to generate internal impedance characteristics of the target lithium battery, wherein the internal impedance characteristics comprise ohmic impedance gradient, charge transfer impedance accumulation and diffusion impedance fluctuation coefficients; the short circuit diagnosis module is used for calling a pre-trained short circuit identification model to perform nonlinear exception analysis processing on the internal impedance characteristics and generating a short circuit risk grade and a potential short circuit area identifier of the target lithium battery; Comprising the following steps: Inputting the ohmic impedance gradient to an impedance anomaly detection layer of the short circuit identification model, and determining the space coordinates and the impedance change track of an ohmic impedance anomaly region through a gradient mutation identification algorithm; inputting the charge transfer impedance accumulation amount to an interface state analysis layer of the short circuit identification model, executing charge transfer disorder accumulation calculation, and generating an interface reaction activity degradation probability and a reaction rate attenuation predicted value; Inputting the diffusion impedance fluctuation coefficient to a mass transfer analysis layer of the short circuit identification model, and calculating electrolyte ion diffusion coefficient and concentration polarization evolution data based on an ion migration retardation model; Fusing the impedance change track, the interface reaction activity degradation probability and the ion diffusion coefficient to generate a comprehensive abnormality index of the target lithium battery, and determining a short circuit risk level according to a comparison result of the comprehensive abnormality index and a preset safety threshold; identifying geometrical boundaries of an impedance anomaly region, an interface degradation region and a mass transfer hindered region based on the spatial coordinates, the reaction rate attenuation predicted value and the spatial superposition result of the concentration polarization evolution data; The environment compensation module is used for carrying out battery condition compensation and correction processing on the short circuit risk level to generate a corrected short circuit risk level, and the battery condition compensation and correction processing is realized based on the association relation between the temperature distribution monitoring data and the electrochemical impedance temperature; And the strategy generation module is used for generating a safety coping strategy set according to the potential short circuit area identification, wherein the safety coping strategy set comprises a current path adjustment scheme and a thermal management intervention scheme.
2. The impedance spectroscopy analysis-based lithium battery internal short circuit diagnosis system according to claim 1, wherein the impedance field reconstruction module performs three-dimensional impedance distribution reconstruction processing on the dynamic impedance spectroscopy data set, and generates internal impedance characteristics of the target lithium battery, including: Dividing the multi-frequency excitation signal sequence into a plurality of excitation sub-bands according to the frequency band range, wherein each excitation sub-band corresponds to an impedance sampling interval; for each of the excitation subbands, the following is performed: Constructing a three-dimensional potential distribution topological structure of the target lithium battery according to the voltage response waveform sequence, wherein the three-dimensional potential distribution topological structure comprises spatial variation data of an anode potential field, a cathode potential field and an electrolyte potential field; Coupling analysis processing is carried out on the three-dimensional potential distribution topological structure and the excitation sub-band, so that an impedance distribution reconstruction result of a current sampling interval is generated, wherein the impedance distribution reconstruction result comprises a space distribution matrix of an ohmic impedance component, a charge transfer impedance component and a diffusion impedance component; Carrying out frequency domain fusion processing on the impedance distribution reconstruction results of a plurality of continuous sampling intervals, and calculating to obtain the ohmic impedance gradient, the charge transfer impedance accumulation amount and the diffusion impedance fluctuation coefficient, The ohmic impedance gradient is the rate of change of the ohmic impedance component in the thickness direction of the cell, The charge transfer impedance accumulation amount is the integral amount of the charge transfer impedance component in the normal direction of the electrode interface, The diffusion impedance fluctuation coefficient is the ratio of standard deviation to mean value of diffusion impedance components in a specified frequency range.
3. The impedance spectrum analysis-based lithium battery internal short circuit diagnosis system according to claim 2, wherein the impedance field reconstruction module performs coupling analysis processing on the three-dimensional potential distribution topological structure and the excitation sub-band to generate an impedance distribution reconstruction result of a current sampling interval, and the impedance field reconstruction module comprises: based on the corresponding relation between the anode potential field and the high-frequency excitation signal in the excitation sub-band, an anode potential-excitation mapping equation is established, and a distribution function of ohmic impedance components is obtained by solving the anode potential-excitation mapping equation; according to the correlation characteristics of the cathode potential field and the low-frequency excitation signal, constructing a charge transfer impedance calculation model, wherein the charge transfer impedance calculation model comprises dynamic calibration parameters of an electrode material active area and an interface capacitance; combining the spatial gradient and the ionic conductivity of the electrolyte potential field, and establishing a diffusion impedance iterative computation flow, wherein the iterative computation flow comprises a feedback correction mechanism of potential increment and diffusion impedance increment; And carrying out space grid fusion processing on the distribution function, the charge transfer impedance calculation model and the output result of the diffusion impedance iterative calculation flow to generate three-dimensional impedance distribution data comprising ohmic impedance, charge transfer impedance and diffusion impedance.
4. The impedance spectroscopy based lithium battery internal short circuit diagnostic system according to claim 1, wherein the environment compensation module performs battery condition compensation correction processing on the short circuit risk level, and generates a corrected short circuit risk level, comprising: extracting extreme temperature and temperature change gradient in the temperature distribution monitoring data, and calculating dynamic compensation quantity of electrochemical impedance temperature coefficient along with temperature change; performing temperature drift compensation calculation on the ohmic impedance gradient according to the dynamic compensation quantity to generate a corrected ohmic impedance gradient; Based on the association relation between the temperature change gradient and the electrode reaction kinetics, carrying out reaction rate correction processing on the charge transfer impedance accumulation amount to generate a corrected charge transfer impedance accumulation amount; Performing ion migration adaptive adjustment treatment on the diffusion impedance fluctuation coefficient according to the electrolyte conductivity change characteristic at the extreme temperature to generate a corrected diffusion impedance fluctuation coefficient; And inputting the corrected ohmic impedance gradient, charge transfer impedance accumulation amount and diffusion impedance fluctuation coefficient into the short circuit identification model for recalculation, and generating a short circuit risk level after compensating working condition factors.
5. The impedance spectroscopy based lithium battery internal short circuit diagnostic system according to claim 4, wherein the environmental compensation module performs a temperature drift compensation calculation on the ohmic impedance gradient according to the dynamic compensation amount, and generates a corrected ohmic impedance gradient, comprising: acquiring a reference impedance temperature coefficient and the dynamic compensation quantity of the target lithium battery at a reference temperature, and establishing an impedance temperature coefficient-temperature correlation function; calculating an impedance temperature drift amount according to the impedance temperature coefficient-temperature correlation function, wherein the impedance temperature drift amount is the product of the temperature variation amount and the impedance temperature coefficient variation amount; Adding the impedance temperature drift amount to the calculation process of the ohmic impedance gradient to generate an ohmic impedance gradient correction value containing a temperature compensation effect; And carrying out relaxation effect compensation treatment on the ohmic impedance gradient correction value, wherein the relaxation effect compensation treatment is realized based on a product factor of an electrochemical relaxation time constant and a temperature holding time length.
6. The impedance spectroscopy based lithium battery internal short circuit diagnostic system according to claim 1, wherein the policy generation module generates a set of security countermeasures policies from the potential short circuit region identification, comprising: Aiming at the identification of the impedance abnormal region, calculating an optimal current path adjustment scheme, wherein the optimal current path adjustment scheme is realized by adjusting the current distribution proportion of the parallel branch circuit in the battery; Constructing a thermal management intervention scheme according to the identification of the interface degradation region, wherein the thermal management intervention scheme comprises the selection of a local cooling region and the optimal configuration of cooling intensity parameters; Generating an electrolyte supplementing strategy based on the mark of the mass transfer blocked area, wherein the electrolyte supplementing strategy dynamically adjusts supplementing dosage and supplementing position according to the predicted value of the ion migration rate; And carrying out priority ranking treatment on the optimal current path adjustment scheme, the thermal management intervention scheme and the electrolyte supplementing strategy to generate a safety coping strategy set comprising an execution sequence and control parameters.
7. The impedance spectroscopy based lithium battery internal short circuit diagnostic system of claim 6, wherein the policy generation module constructs a thermal management intervention scheme comprising: Extracting thermal characteristic parameters of the interface degradation region, and calculating a heat generation rate and a heat diffusion coefficient; selecting the flow of a cooling medium according to the heat generation rate, wherein the flow and the heat generation rate are in a direct proportion relation; adjusting the arrangement density of the cooling flow channels based on the thermal diffusion coefficient to form dynamic balance between cooling efficiency and heat accumulation rate; dynamically adjusting the power of the semiconductor refrigerating sheet according to the real-time temperature monitoring data to ensure that the interface temperature is maintained below the material phase change point; A thermal management parameter configuration table is generated that includes cooling medium flow, flow passage arrangement density, and refrigeration power.
8. The impedance spectroscopy based lithium battery internal short circuit diagnostic system of claim 1, further comprising: The model optimization module is used for collecting actual impedance change data and thermal runaway characteristic parameters of the target lithium battery in a preset verification period; performing deviation analysis processing on the actual impedance change data and the predicted impedance distribution to generate a first calibration coefficient; performing time domain comparison processing on the thermal runaway characteristic parameters and the predicted risk level to generate a second calibration coefficient; adjusting a decision threshold of the short circuit identification model according to the first calibration coefficient and the second calibration coefficient, and generating an optimized short circuit identification model; and applying the optimized short circuit identification model to internal short circuit diagnosis tasks of lithium batteries in subsequent batches.
9. An impedance spectrum analysis-based lithium battery internal short circuit method is characterized by comprising all the modules and the method flow of the impedance spectrum analysis-based lithium battery internal short circuit system described in any one of claims 1 to 8.

Description

Impedance spectrum analysis-based lithium battery internal short circuit diagnosis method and system Technical Field The invention relates to the technical field of lithium battery safety diagnosis, in particular to a lithium battery internal short circuit diagnosis method and system based on impedance spectrum analysis. Background Current lithium battery internal short circuit diagnostics rely primarily on macroscopic voltage, temperature monitoring of the battery management system, or equivalent circuit model analysis based on electrochemical impedance spectroscopy. These methods treat the battery as a uniform unit by measuring the overall voltage response of the battery port to fit a global impedance parameter as a state of health indicator. Such techniques are slow to the early, highly localized abnormal reactions that occur inside the battery. The global parameter changes tend to lag behind the actual development of local defects, and it is difficult to provide effective early warning before internal shorts initiate thermal runaway. Limitations of the prior art diagnostic techniques are manifested by insufficient spatial resolution. Internal micro-shorting begins to fail in tiny areas such as electrode interfaces or separators, which produce electrochemical signals with small amplitude of variation and spatial specificity. The conventional method cannot analyze the spatial distribution difference of impedance parameters in the battery, so that the method is insensitive to early and local impedance changes, and cannot realize fault location. Another drawback of the existing solutions is that the diagnostic results are subject to environmental and operating conditions and lack a precise control response. The battery impedance characteristic has strong dependence on temperature and running state, and the existing method lacks an effective online dynamic compensation mechanism and is easy to cause misjudgment. Meanwhile, even if an abnormality is detected, the conventional system can only trigger general protection measures such as power reduction or global alarm, and can not implement differentiation and targeted intervention according to the specific space position where the fault occurs, and the control efficiency and the accuracy are insufficient. Disclosure of Invention The invention aims to solve the defects in the prior art, and provides a lithium battery internal short circuit diagnosis method and system based on impedance spectrum analysis. In order to achieve the above purpose, the invention adopts the following technical scheme that the lithium battery internal short circuit diagnosis system based on impedance spectrum analysis comprises: The data acquisition module is used for acquiring a dynamic impedance spectrum data set of the target lithium battery in the charge-discharge cycle process, wherein the dynamic impedance spectrum data set comprises a multi-frequency excitation signal sequence, a voltage response waveform sequence and temperature distribution monitoring data; The impedance field reconstruction module is used for carrying out three-dimensional impedance distribution reconstruction processing on the dynamic impedance spectrum data set to generate internal impedance characteristics of the target lithium battery, wherein the internal impedance characteristics comprise ohmic impedance gradient, charge transfer impedance accumulation and diffusion impedance fluctuation coefficients; the short circuit diagnosis module is used for calling a pre-trained short circuit identification model to perform nonlinear exception analysis processing on the internal impedance characteristics and generating a short circuit risk grade and a potential short circuit area identifier of the target lithium battery; The environment compensation module is used for carrying out battery condition compensation and correction processing on the short circuit risk level to generate a corrected short circuit risk level, and the battery condition compensation and correction processing is realized based on the association relation between the temperature distribution monitoring data and the electrochemical impedance temperature; And the strategy generation module is used for generating a safety coping strategy set according to the potential short circuit area identification, wherein the safety coping strategy set comprises a current path adjustment scheme and a thermal management intervention scheme. As a further aspect of the present invention, the impedance field reconstruction module performs three-dimensional impedance distribution reconstruction processing on the dynamic impedance spectrum data set, to generate an internal impedance characteristic of the target lithium battery, including: Dividing the multi-frequency excitation signal sequence into a plurality of excitation sub-bands according to the frequency band range, wherein each excitation sub-band corresponds to an impedance sampling interval; for each of