CN-122017579-A - Continuous DRT analysis method based on priority peak separation processing

CN122017579ACN 122017579 ACN122017579 ACN 122017579ACN-122017579-A

Abstract

The application provides a continuous DRT analysis method based on preferential peak splitting processing, which comprises the steps of carrying out peak splitting processing based on electrochemical characteristics of a target battery, determining a plurality of peak-shaped core kernel functions, wherein each core kernel function corresponds to a single dynamic process of the target battery and is adjustable in position parameter and shape parameter, determining an integral DRT curve and a DRT equation set of the target battery based on the core kernel functions, iteratively searching to obtain optimal values and corresponding amplitudes of the position parameter and the shape parameter of each core kernel function, and determining the integral DRT curve and/or the DRT curve corresponding to the single dynamic process of the target battery based on search results. According to the method, the core kernel function which is definitely corresponding to the dynamic process is established, the optimal values of the position and the shape and the corresponding amplitude values of the core kernel function are searched, and the analysis result does not depend on the frequency resolution of measured data and is definitely in physical meaning.

Inventors

WANG DAFANG
HAO ZIWEI
ZHANG QI
CHEN SHIQIN
ZHANG CONG
HU BINGBING
LIANG XUAN
XIONG KAI
ZHANG ZIHAO

Assignees

哈尔滨工业大学（威海）

Dates

Publication Date: 20260512
Application Date: 20260126

Claims (9)

1. A continuous DRT analysis method based on preferential peaking processing, comprising the steps of: Step one, carrying out peak separation processing based on electrochemical characteristics of a target battery, and determining a plurality of core kernel functions for representing an overall DRT curve of the target battery, wherein the core kernel functions are peak-shaped functions with adjustable position parameters and shape parameters, and each core kernel function corresponds to a single dynamic process of the target battery; step two, determining the integral DRT curve of the target battery and the expression of a DRT equation set based on the core kernel function; Step three, iteratively searching to obtain the optimal values and the corresponding amplitudes of the position parameters and the shape parameters of each core kernel function by taking the minimized fitness function as a target; and step four, determining the overall DRT curve of the target battery and/or the DRT curve corresponding to the single dynamic process of the target battery based on the search result.
2. A continuous DRT analysis method based on priority peak separation processing is characterized in that, Total number of single dynamic processes of the target battery And the total number of single dynamic processes of the target battery is far smaller than the total number of EIS measurement frequency points.
3. The continuous DRT analysis method based on preferential peaking processing as claimed in claim 2, wherein the step three is comprised of an initialization operation and a plurality of iterative search processes, wherein each iterative search process includes the steps of: s31, determining the amplitude of each core kernel function by solving a DRT equation set based on the current position parameters and the shape parameters; S32, based on the solving result in the step S31, updating the position parameter and the shape parameter with the minimum fitness function as a target, and entering the next iteration until reaching the iteration search ending condition.
4. The continuous DRT analysis method based on priority peaking processing as claimed in claim 3, wherein, And solving the DRT equation set in each iterative search process to obtain the amplitude of each core kernel function without any regularization treatment.
5. The continuous DRT analysis method based on prioritized peaking processing of claim 4, where the set of DRT equations is: , Wherein, the The total number of frequency points is measured for the EIS of the target cell, Is the total number of core kernel functions and , Is the first The angular frequency of the frequency points is measured, In the first place for the target battery Complex impedance corresponding to the DRT curve portion at each measurement frequency point, In units of imaginary numbers, And Respectively is Is used for the real and imaginary parts of (a), 、 Respectively the first The core kernel is at the first The real and imaginary coefficients at the individual measurement frequency points, Is the first The magnitude of the kernel function.
6. The continuous DRT analysis method based on priority peaking processing as claimed in claim 5, wherein, 、 The specific expression of (2) is: , Wherein, the As a relaxation time constant argument in logarithmic scale, Is the first The adjustable position parameters of the log coordinates of the individual core kernel functions, As an intermediate variable, the number of the variables, Is the first An adjustable shape parameter of the core kernel function; is the first The core kernel functions are arranged, the opening of each core kernel function is downward, the center position has the maximum value, and the function value approaches 0 along with the distance from the center position.
7. The continuous DRT analysis method based on priority peaking processing as claimed in claim 5, wherein, The fitness function is as follows: , Wherein, the In order to be an L2 norm, 、、 For the real coefficient matrix, the imaginary coefficient matrix and the core kernel function magnitude column vector in the DRT equation set, Is the measured column vector of the real part of the DRT impedance, Is the measured column vector of the imaginary part of the DRT impedance.
8. The continuous DRT analysis method based on priority peaking processing as claimed in claim 3, wherein, And step three, initializing operation is used for setting initial values of position parameters and shape parameters of each core kernel function, a search range, a search scale and search ending conditions, wherein the search range of the position parameters corresponding to the diffusion-related single dynamic process or equivalent resistance effect is larger than that of the position parameters corresponding to other single dynamic processes or equivalent resistance effect.
9. The continuous DRT analysis method based on priority peaking processing as claimed in claim 8, wherein, The target battery is a lithium ion battery, and the total number of core kernel functions The initial value of the position parameter of each core kernel function is 。

Description

Continuous DRT analysis method based on priority peak separation processing Technical Field The application belongs to the technical field of battery detection, and further relates to a DRT analysis technology of electrochemical impedance spectroscopy, in particular to a continuous DRT analysis method based on preferential peak separation treatment. Background EIS (Electrochemical Impedance Spectroscopy ) analysis is an in-situ battery performance analysis and detection technology, the impedance characteristics of a battery under corresponding frequencies are analyzed by testing excitation and response of the battery under alternating current signals, and because the EIS is intensively reflected by dynamic processes with different rates in the battery and has strong correlation with the electrochemical behaviors of the battery, effective information can be provided for in-depth analysis of the electrochemical principle, aging mechanism and failure characteristics of the battery, however, the EIS has strong complexity, the complicated dynamic processes are still difficult to explain from the EIS, and researchers usually use a DRT (Distribution of Relaxation Times, relaxation time distribution) analysis method to extract core characteristics of the EIS to solve the problem, so that analysis of the EIS is simplified. DRT is a model-free EIS analysis method that accounts for the contribution of internal dynamics to overall impedance by constructing a distribution of impedance versus relaxation time from measured discrete impedance data, the basic assumption of which is that any polarization process in an electrochemical system can be described by one or more standard relaxation processes with characteristic time constants, which typically involve discretization of the impedance expression and conversion to a solution to a system of linear equations. The current common DRT method for constructing a linear equation set is divided into a direct discrete method and a kernel function-based method. The method is characterized in that a DRT formula is directly discretized by a direct discretization method to construct an equation set, the processing process of the method is relatively simple, but resistance definition exists only at a specified relaxation time constant point, and definite physical meanings are absent at other positions. However, the existing continuous DRT method based on the kernel function generally has the problems that the influence of preset parameters such as the frequency density of the tested EIS and the peak width coefficient of regularization treatment is large, and the accuracy of the DRT solving result is poor when the frequency density is low and the parameters cannot be accurately estimated. Disclosure of Invention The application aims to provide a continuous DRT analysis method based on preferential peaking processing, which comprises the following steps: Step one, carrying out peak separation processing based on electrochemical characteristics of a target battery, and determining a plurality of core kernel functions for representing an overall DRT curve of the target battery, wherein the core kernel functions are peak-shaped functions with adjustable position parameters and shape parameters, and each core kernel function corresponds to a single dynamic process of the target battery; step two, determining the integral DRT curve of the target battery and the expression of a DRT equation set based on the core kernel function; Step three, taking the minimized fitness function as a target, and carrying out iterative search to obtain the optimal values and the corresponding amplitudes of the position parameters and the shape parameters of each core kernel function, wherein no regularization treatment is carried out when solving the DRT equation set in each iteration process to obtain the amplitudes of each core kernel function; and step four, determining the overall DRT curve of the target battery and/or the DRT curve corresponding to the single dynamic process of the target battery based on the search result. The continuous DRT analysis method based on the priority peak separation treatment provided by the application has at least the following beneficial effects: (1) The integral DRT curve is constructed through a small amount of core kernel functions corresponding to a single dynamics process, calculation uncertainty caused by selection of the number of kernel functions, regularization parameters and half-peak width coefficients in a traditional DRT method is avoided, and therefore the position and shape of the integral DRT curve obtained through calculation are highly controllable and have higher calculation stability. (2) The inherent characteristics of the battery are considered in the process of acquiring the DRT curve, so that the randomness of the DRT calculation is effectively restrained, and the interpretability of the whole DRT curve is stronger. (3) Besides the integral DRT curv