CN-122017651-A - Method for detecting state of health of vehicle battery and charging system of vehicle battery

CN122017651ACN 122017651 ACN122017651 ACN 122017651ACN-122017651-A

Abstract

The application provides a method for detecting the health state of a vehicle battery and a charging system of the vehicle battery, and relates to the technical field of electric vehicle battery management, wherein the method comprises the steps of starting EIS detection when a preset condition is met after a vehicle is connected with a charging pile; the method comprises the steps of acquiring a power supply source of EIS detection based on a preset EMS energy scheduling strategy, selecting a plurality of frequency points in a characteristic frequency band based on an adaptive sampling strategy in a frequency sweep mode, applying alternating current excitation signals of the frequency points to a vehicle battery, acquiring response data of the vehicle battery under the EIS detection, and calculating the health state of the vehicle battery based on the response data. The method provided by the application is beneficial to realizing accurate and rapid detection of the battery health state in the light storage and charge scene.

Inventors

QI JIAJIA
Du Yigao
ZANG PENGFEI

Assignees

浙江晶科储能有限公司

Dates

Publication Date: 20260512
Application Date: 20260331

Claims (11)

1. A method for detecting a state of health of a vehicle battery, the method comprising: After the vehicle is connected with the charging pile, when a preset condition is met, EIS detection is started; acquiring a power supply source detected by the EIS based on a preset EMS energy scheduling strategy, wherein the power supply source comprises a photovoltaic system, an energy storage system and a power grid; Under the sweep frequency mode, selecting a plurality of frequency points in a characteristic frequency band based on an adaptive sampling strategy, and applying alternating current excitation signals of the frequency points to a vehicle battery; collecting response data of the vehicle battery under the EIS detection; And calculating the health state of the vehicle battery based on the response data.
2. The method of claim 1, wherein the preset EMS energy scheduling policy includes: When the variation amplitude of the output power of the photovoltaic system is smaller than or equal to a first threshold value, selecting the photovoltaic system as a source of the power supply, or When the variation amplitude of the output power of the photovoltaic system is larger than the first threshold value, the energy storage system is selected as the source of the power supply source, or And when the output power of the photovoltaic system is smaller than a second threshold value and the state of charge of the energy storage system is smaller than or equal to a third threshold value, selecting the power grid as a source of the power supply.
3. A method according to claim 1 or 2, characterized in that, The voltage ripple of the power supply is smaller than or equal to a ripple threshold value, and the frequency precision of the power supply is within a preset range.
4. The method of claim 1, wherein the preset conditions include: And determining that the vehicle battery is in a stable state and the state of charge of the vehicle battery is greater than or equal to a state of charge threshold.
5. The method of claim 4, wherein the determining that the vehicle battery is in a steady state comprises: And when the amplitude variation of the current of the vehicle battery is smaller than or equal to a current threshold value, judging that the vehicle battery is in a stable state.
6. The method of claim 1, wherein the adaptive sampling strategy comprises: And adjusting the density of the selected frequency points based on the stability of the EIS detected power supply or the sensitivity of the frequency points to battery aging or the quality of the response data.
7. The method of claim 6, wherein adjusting the density of frequency bins based on stability of the EIS detected power supply or sensitivity of frequency bins to battery aging or quality of the response data comprises: Increasing the density of the frequency points selected in the characteristic frequency band when the variation amplitude of the output power of the photovoltaic system is smaller than or equal to a fourth threshold value, otherwise, decreasing the density of the frequency points selected in the characteristic frequency band, or Increasing the density of frequency points selected from a target frequency band, which is a frequency band strongly related to battery aging in the characteristic frequency band, or And when the signal-to-noise ratio of the response data is greater than or equal to a signal-to-noise ratio threshold, increasing the density of the frequency points selected in the characteristic frequency band, otherwise, reducing the density of the frequency points selected in the characteristic frequency band.
8. The method of claim 1, wherein the response data includes voltage response data and current response data generated by the vehicle battery under the action of the ac excitation signal, and wherein calculating the state of health of the vehicle battery based on the response data includes: Acquiring impedance data corresponding to each of the plurality of frequency points based on the voltage response data and the current response data; performing parameter fitting based on the impedance data and a pre-constructed equivalent circuit model, and extracting key parameters of the battery health state; Inputting the key parameters of the battery state of health into a pre-constructed battery state of health calculation model to obtain the state of health of the vehicle battery.
9. The method of claim 8, wherein the step of determining the position of the first electrode is performed, Key parameters of the battery state of health include charge transfer resistance and diffusion resistance.
10. The method of claim 1, wherein the step of determining the position of the substrate comprises, The frequency range of the characteristic frequency band is 0.1Hz-1kHz.
11. The charging system of the vehicle battery is characterized by comprising an EMS, the vehicle battery and a charging pile, wherein the vehicle battery is connected with the charging pile and used for executing EIS detection and returning response data under the EIS detection to the charging pile, the charging pile is used for starting the EIS detection when a preset condition is met after a vehicle is connected with the charging pile, acquiring a power supply source of the EIS detection based on a preset EMS energy scheduling strategy, selecting a plurality of frequency points in a characteristic frequency band based on an adaptive sampling strategy in a sweep frequency mode, applying alternating current excitation signals of the plurality of frequency points to the vehicle battery, collecting the response data of the vehicle battery under the EIS detection, calculating the health state of the vehicle battery based on the response data, and the EMS is used for carrying out energy scheduling on the power supply source of the EIS detection, wherein the power supply source comprises a photovoltaic system, an energy storage system and a power grid.

Description

Method for detecting state of health of vehicle battery and charging system of vehicle battery Technical Field The application relates to the technical field of electric automobile battery management, in particular to a method for detecting the health state of a vehicle battery and a charging system of the vehicle battery. Background Along with the rapid development of new energy automobile industry, the integrated charging station of light storage and charging (namely a photovoltaic system, an energy storage system and an electric automobile charging pile) has remarkable advantages in the aspects of energy utilization efficiency and operation economy as the integrated charging station can effectively integrate the functions of photovoltaic power generation, the energy storage system and electric automobile charging, and becomes an important development direction of future charging infrastructure. However, in the light storage and charge scenario, battery SOH (State of Health) detection faces many challenges, which not only lacks the discrimination of the internal aging mechanism of the battery, but also does not match the real-time requirement of the fast charge scenario of the charging station, and thus the accurate and fast detection of the battery Health State cannot be realized. Disclosure of Invention The application provides a method for detecting the health state of a vehicle battery and a charging system of the vehicle battery, which are beneficial to realizing accurate and rapid detection of the health state of the battery in an optical storage charging scene. In a first aspect, the present application provides a method for detecting a state of health of a vehicle battery, including: After the vehicle is connected with the charging pile, when a preset condition is met, EIS detection is started; acquiring a power supply source for EIS detection based on a preset EMS energy scheduling strategy, wherein the power supply source comprises a photovoltaic system, an energy storage system and a power grid; under the sweep frequency mode, selecting a plurality of frequency points in a characteristic frequency band based on an adaptive sampling strategy, and applying alternating current excitation signals of the plurality of frequency points to a vehicle battery; Collecting response data of a vehicle battery under EIS detection; The state of health of the vehicle battery is calculated based on the response data. In one possible implementation manner, the preset EMS energy scheduling policy includes: When the variation amplitude of the output power of the photovoltaic system is smaller than or equal to a first threshold value, the photovoltaic system is selected as a source of the power supply, or When the variation amplitude of the output power of the photovoltaic system is larger than a first threshold value, the energy storage system is selected as a source of the power supply, or And when the output power of the photovoltaic system is smaller than the second threshold value and the state of charge of the energy storage system is smaller than or equal to the third threshold value, selecting the power grid as a source of the power supply. In one possible implementation manner, the voltage ripple of the power supply is smaller than or equal to the ripple threshold, and the frequency accuracy of the power supply is within a preset range. In one possible implementation manner, the preset condition includes: The method includes determining that a vehicle battery is in a steady state and a state of charge of the vehicle battery is greater than or equal to a state of charge threshold. In one possible implementation, determining that the vehicle battery is in a steady state includes: And when the amplitude variation of the current of the vehicle battery is smaller than or equal to the current threshold value, determining that the vehicle battery is in a stable state. In one possible implementation, the adaptive sampling strategy includes: the density of the selected frequency points is adjusted based on the stability of the EIS detected power supply or the sensitivity of the frequency points to battery aging or the quality of the response data. In one possible implementation, adjusting the density of the frequency points based on the stability of the power supply or the sensitivity of the frequency points to battery aging or the quality of response data detected by the EIS includes: Increasing the density of the selected frequency points in the characteristic frequency band when the variation amplitude of the output power of the photovoltaic system is smaller than or equal to the fourth threshold value, otherwise, decreasing the density of the selected frequency points in the characteristic frequency band, or Increasing the density of frequency points selected from a target frequency band, which is a frequency band strongly related to battery aging in a characteristic frequency band, or And when the signal-to-noi