CN-122017616-A - Lithium ion battery state of charge monitoring method, device, equipment and storage medium

CN122017616ACN 122017616 ACN122017616 ACN 122017616ACN-122017616-A

Abstract

The application discloses a method, a device, equipment and a storage medium for monitoring the state of charge of a lithium ion battery, and relates to the technical field of state of charge management of the lithium ion battery; the method comprises the steps of extracting impedance parameters under characteristic frequency related to a state of charge based on electrochemical impedance spectrum data, carrying out dimension reduction processing on the extracted impedance parameters to obtain dimension reduced characteristic data, constructing a state of charge estimation model based on the dimension reduced characteristic data, obtaining first multi-frequency electrochemical impedance spectrum data of the lithium ion battery in the operation process, and obtaining a target state of charge of the lithium ion battery according to the first multi-frequency electrochemical impedance spectrum data and the state of charge estimation model. The method realizes high-precision online real-time monitoring of the state of charge of the lithium ion battery.

Inventors

WANG NING
GAO FENG
DING FEI

Assignees

河北工业大学

Dates

Publication Date: 20260512
Application Date: 20260310

Claims (10)

1. A method for monitoring the state of charge of a lithium ion battery, the method comprising: electrochemical impedance spectrum data of the lithium ion battery at different temperatures, different ageing states and different charge states are obtained; extracting impedance parameters under characteristic frequencies related to the state of charge based on the electrochemical impedance spectrum data; performing dimension reduction processing on the impedance parameters to obtain feature data after dimension reduction; Constructing a state of charge estimation model based on the feature data after dimension reduction; Acquiring first multi-frequency electrochemical impedance spectrum data of the lithium ion battery in the operation process; and obtaining the target state of charge of the lithium ion battery according to the first multi-frequency electrochemical impedance spectrum data and the state of charge estimation model.
2. The method of claim 1, wherein extracting impedance parameters at a characteristic frequency related to state of charge based on the electrochemical impedance spectrum data comprises: calculating correlation coefficients between impedance parameters and states of charge at different frequencies based on the electrochemical impedance spectrum data; screening out a first characteristic frequency with high correlation with the state of charge according to the magnitude of the correlation coefficient; and extracting an impedance parameter at the first characteristic frequency based on the electrochemical impedance spectrum data and the first characteristic frequency.
3. The method according to claim 1, wherein the performing the dimension reduction processing on the impedance parameter to obtain the feature data after dimension reduction includes: Performing principal component analysis and dimension reduction on the impedance parameters to obtain first principal component characteristics; And taking the first principal component characteristic as characteristic data after dimension reduction.
4. The method of claim 1, wherein constructing a state of charge estimation model based on the reduced-dimension feature data comprises: Taking the feature data after dimension reduction, the battery temperature data and the battery aging state data as inputs, and taking the state of charge of the lithium ion battery as output to construct an initial estimation model; performing global optimization on the super parameters of the initial estimation model by adopting an optimization algorithm to obtain a first super parameter combination; and training to obtain a state of charge estimation model based on the first super-parameter combination.
5. The method of claim 1, wherein the acquiring the first multi-frequency electrochemical impedance spectrum data of the lithium-ion battery during operation comprises: Applying a multi-frequency alternating current excitation signal to the lithium ion battery under a static working condition or a dynamic working condition; collecting response data of the lithium ion battery to the multi-frequency alternating current excitation signal; And calculating first multi-frequency electrochemical impedance spectrum data based on the response data.
6. The method of claim 1, wherein deriving the target state of charge of the lithium-ion battery from the first multi-frequency electrochemical impedance spectroscopy data and the state of charge estimation model comprises: Extracting a first impedance parameter corresponding to the first characteristic frequency from the first multi-frequency electrochemical impedance spectrum data; performing the dimension reduction processing on the extracted first impedance parameter to obtain first dimension reduction characteristic data; And inputting the first dimension reduction characteristic data into the state of charge estimation model, and outputting the target state of charge of the lithium ion battery.
7. The method of claim 1, wherein prior to obtaining electrochemical impedance spectrum data for the lithium-ion battery at different temperatures, different aging states, and different states of charge, the method further comprises: and carrying out standard charge-discharge cycle on the lithium ion battery, and determining the actual discharge capacity of the lithium ion battery.
8. A device for monitoring the state of charge of a lithium ion battery, the device comprising: The device comprises an acquisition module, an impedance parameter extraction module, a dimension reduction module and a dimension reduction module, wherein the acquisition module is used for acquiring electrochemical impedance spectrum data of the lithium ion battery at different temperatures, different ageing states and different charge states; The calculation module is used for constructing a state-of-charge estimation model based on the feature data after dimension reduction, acquiring first multi-frequency electrochemical impedance spectrum data of the lithium ion battery in the running process, and acquiring a target state-of-charge of the lithium ion battery according to the first multi-frequency electrochemical impedance spectrum data and the state-of-charge estimation model.
9. A computing device comprising a memory and a processor; wherein one or more computer programs are stored in the memory, the one or more computer programs comprising instructions, which when executed by the processor, cause the computing device to perform the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium is for storing a computer program, the computer program for performing the method of any one of claims 1 to 7.

Description

Lithium ion battery state of charge monitoring method, device, equipment and storage medium Technical Field The present application relates to the field of lithium ion battery state of charge management technologies, and in particular, to a method, an apparatus, a device, and a storage medium for monitoring a lithium ion battery state of charge. Background Currently, estimation methods of lithium ion battery State of Charge (SOC) represent diversified technical routes. The principle of the open-circuit voltage method is based on the fact that a certain functional relation exists between the open-circuit voltage and the state of charge of the battery in a static state, and the state of charge of the battery can be obtained by comparing the open-circuit voltage in a stable state. In addition, the ampere-hour integration method calculates the change of the electric quantity by integrating the charge and discharge current with time, and the data driving law relies on the mining of a large amount of historical operation data to construct an estimation model, which simulates and estimates the internal state of the battery by establishing an electrochemical model or an equivalent circuit model. However, the above-mentioned prior art has a certain limitation in practical application. Specifically, the open circuit voltage method requires that the battery must be in a standing state for a long time to reach voltage stabilization, which is difficult to meet during the actual operation of the battery, and thus cannot be applied to online monitoring under dynamic working conditions. More importantly, a relatively flat voltage platform exists in the middle area of the charge state of the lithium ion battery, and the variation amplitude of the voltage along with the charge state in the area is extremely small, so that the charge state is difficult to accurately distinguish by an open-circuit voltage method, and the estimation precision is reduced. Therefore, the prior art has the problem that the state of charge of the lithium ion battery cannot be monitored on line with high precision under the dynamic working condition. Disclosure of Invention The application provides a method, a device, equipment and a storage medium for monitoring the state of charge of a lithium ion battery, which can realize high-precision real-time monitoring of the state of charge of the lithium ion battery based on online impedance spectrum, and solve the problems that the traditional open-circuit voltage method cannot realize online monitoring and the precision of a voltage platform area is low through characteristic frequency optimization and model parameter global optimization. In order to achieve the above purpose, the application adopts the following technical scheme: In a first aspect, the present application provides a method for monitoring a state of charge of a lithium ion battery, the method comprising: electrochemical impedance spectrum data of the lithium ion battery at different temperatures, different ageing states and different charge states are obtained; extracting impedance parameters under characteristic frequencies related to the state of charge based on the electrochemical impedance spectrum data; Performing dimension reduction processing on the extracted impedance parameters to obtain feature data after dimension reduction; Constructing a state of charge estimation model based on the feature data after dimension reduction; Acquiring first multi-frequency electrochemical impedance spectrum data of the lithium ion battery in the operation process; and obtaining the target state of charge of the lithium ion battery according to the first multi-frequency electrochemical impedance spectrum data and the state of charge estimation model. In some possible implementations, the extracting, based on the electrochemical impedance spectrum data, an impedance parameter at a characteristic frequency related to a state of charge includes: The method comprises the steps of calculating correlation coefficients between impedance parameters and states of charge under different frequencies based on electrochemical impedance spectrum data, screening out first characteristic frequencies with high correlation with the states of charge according to the magnitude of the correlation coefficients, and extracting the impedance parameters under the first characteristic frequencies based on the electrochemical impedance spectrum data and the first characteristic frequencies. In some possible implementations, the performing the dimension reduction processing on the impedance parameter to obtain feature data after dimension reduction includes: and performing principal component analysis and dimension reduction on the impedance parameters to obtain first principal component characteristics, wherein the first principal component characteristics are used as feature data after dimension reduction. In some possible implementations, the constructing a state of ch