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CN-122017568-A - Battery monitoring system and method based on automobile battery parameters

CN122017568ACN 122017568 ACN122017568 ACN 122017568ACN-122017568-A

Abstract

The invention relates to the technical field of battery monitoring, and particularly discloses a battery monitoring system and method based on automobile battery parameters. The multi-level parameters of the battery are collected through the distributed sensor array, and after data cleaning and standardization processing, the comprehensive state coefficients of the battery cell, the module and the battery pack are calculated in sequence by the edge calculation module based on the working and power-off state parameters. And (3) quantitatively evaluating key indexes such as internal resistance health, polarization recovery, capacity attenuation, temperature influence and the like of the battery by adopting a multi-sub-coefficient weighted fusion model. The system realizes grading state evaluation according to the preset threshold value, and pushes early warning information and maintenance advice to the user terminal, thereby realizing real-time, accurate and layering intelligent monitoring and active early warning of the health state of the automobile battery.

Inventors

  • WANG GUANGDONG
  • SUN BAOJIAN
  • HAN PENG

Assignees

  • 山东高质新能源检测有限公司

Dates

Publication Date
20260512
Application Date
20260227

Claims (10)

  1. 1. The battery monitoring system based on the automobile battery parameters is characterized by comprising a parameter acquisition module, a data preprocessing module, an edge calculation module, a state evaluation module and an early warning interaction module, wherein the modules are sequentially in communication connection; The parameter acquisition module comprises a distributed sensor array, wherein the distributed sensor array is arranged on the battery core, the module and the battery pack layer of the automobile battery, is used for acquiring multidimensional parameters of the battery and adds a time stamp to each acquired parameter; The data processing module is used for receiving the parameter data transmitted by the parameter acquisition module, and carrying out outlier rejection, missing value completion and standardization processing on the data, wherein the outlier rejection adopts 3 The standard, the missing value complement adopts the adjacent time sequence data interpolation method, the standardized processing maps the parameter data to the [0,1] interval, get the standardized time sequence data; The edge computing module is used for receiving the standardized data output by the data preprocessing module, and obtaining the real-time state coefficient of the battery core, the real-time state coefficient of the module and the real-time state coefficient of the battery pack layer by layer through state sub-coefficient weighted computation based on the working parameters and the power-off parameters of the battery; The state evaluation module is used for receiving the real-time state coefficient and evaluating the states of the battery cells, the modules and the battery packs according to a preset threshold value; and the early warning interaction module is used for pushing abnormal early warning information, a battery health report and maintenance advice to the user mobile terminal according to the state evaluation result.
  2. 2. The battery monitoring system based on the automobile battery parameters according to claim 1, wherein the parameter acquisition module is internally provided with a clock unit and is used for adding time stamps to various acquired parameter data; the parameter acquisition module is provided with a self-adaptive acquisition frequency control unit, and can automatically adjust the acquisition frequency according to the working state of the battery, namely, the parameter acquisition module adopts a frequency of 10Hz to carry out high-frequency acquisition in the power-on working state of the battery, and adopts a frequency of once every 30 minutes to carry out low-frequency acquisition in the power-off standing state of the battery.
  3. 3. The battery monitoring system based on automotive battery parameters of claim 1, wherein the edge calculation module operation comprises: s1, acquiring working parameters of a battery and parameters during power failure, wherein the working parameters comprise working voltage Operating current And operating temperature The power-off parameter comprises a power-off instant open circuit voltage Recovery voltage after power-off for a predetermined time And a resting temperature ; S2, calculating four state sub-coefficients of the battery cell based on the working parameters and the power-off parameters, wherein the four state sub-coefficients comprise internal resistance health coefficients Coefficient of polarization recovery Capacity fade coefficient And temperature influence coefficient ; S3, weight is distributed to the four state sub-coefficients of the battery cell, and then the comprehensive state coefficient of the battery cell is calculated: Wherein, if 1, Then =1, 、 、 And The weight coefficients correspond to the internal resistance health coefficient, the polarization recovery coefficient, the capacity attenuation coefficient and the temperature influence coefficient respectively; And S4, outputting a battery cell state evaluation result according to the numerical range of the battery cell comprehensive state coefficient.
  4. 4. The battery monitoring system based on automotive battery parameters of claim 3, wherein the operation of S2 comprises: the internal resistance health coefficient is calculated by the following formula: In the formula, Is the internal resistance of the battery during operation, wherein, , Is the open circuit voltage of the power supply, Is the internal resistance of the battery when leaving the factory, Is the internal resistance at the end of the battery life, Is the internal resistance of the battery when the battery is kept stand, Standing for internal resistance when the battery leaves the factory; the polarization recovery coefficient is calculated by the following formula: In which, in the process, Is rated voltage; the capacity fade coefficient is calculated by the following formula: ; the temperature influence coefficient is assigned by a temperature difference, and the temperature difference When (when) At a temperature of <10 deg.c, When the temperature is 10 ℃ or less At a temperature of <20 deg.c, 0.95 When the temperature is 20 ℃ or less At a temperature of <30 deg.c, 0.9 When At a temperature of > 30C, the temperature, 0.8。
  5. 5. The battery monitoring system based on automotive battery parameters of claim 3, wherein the edge calculation module operation further comprises: M1, acquiring the comprehensive state coefficients of each of n electric cores in the module Wherein i=1, 2, n; M2, based on the respective comprehensive state coefficients of the n electric cores Calculating three state sub-coefficients of the module, including module balance coefficient Average health coefficient of module And module weakness coefficient ; M3, assigning weights to the three state sub-coefficients of the module, and then calculating the comprehensive state coefficients of the module: , wherein, 、 And The weight coefficients correspond to the module balance coefficient, the module average health coefficient and the module weak influence coefficient respectively; and M4, outputting a battery module state evaluation result according to the numerical range of the module comprehensive state coefficient.
  6. 6. The battery monitoring system based on automotive battery parameters of claim 5, wherein the M2 operation comprises: The module balance coefficient is calculated by the following formula: ; In the formula, And The maximum term and the minimum term of the comprehensive state coefficient in the n electric cores are respectively; The module average health coefficient is calculated by the following formula: ; The module weakness influence coefficient is calculated by the following formula: , wherein, As a result of the first adjustment factor, the first adjustment coefficient Determined according to the number of weak cells m when m=1, =0.8; When m is more than or equal to 2 and less than or equal to in the case of n x 0.2, =0.9, When m > n x 0.2, =1.0, The weak cell is defined as < X 0.8 cells.
  7. 7. The battery monitoring system based on automotive battery parameters of claim 5, wherein the edge calculation module operation further comprises: P1, acquiring the comprehensive state coefficients of each of x modules in the battery pack Where y=1, 2,..x; P2 based on the respective comprehensive state coefficients of the x modules Calculating three state sub-coefficients of the battery pack, including a battery pack balance coefficient, a battery pack average health coefficient and a battery pack weak influence coefficient; p3, assigning weights to the three state sub-coefficients of the battery pack, and then calculating the comprehensive state coefficient of the battery pack: , wherein, 、 And The weight coefficients correspond to the battery pack balance coefficient, the battery pack average health coefficient and the battery pack key module influence coefficient respectively; And P4, outputting a battery module state evaluation result according to the numerical range of the module comprehensive state coefficient.
  8. 8. The battery monitoring system based on automotive battery parameters of claim 7, wherein the P2 operation comprises: The average health coefficient of the battery pack is calculated by the following formula: The battery pack equalization coefficient is calculated by the following formula: ; the cell pack weakness influence coefficient is calculated by the following formula: , wherein, For the second adjustment coefficient, the second adjustment coefficient Determined by the number of weak modules g when g=1, =0.8; When the g is more than or equal to 2 and less than or equal to in the case of x 0.2, =0.9; When g > x 0.2, =1.0, The weak cell is defined as < X 0.8 cells.
  9. 9. The battery monitoring system based on automotive battery parameters of claim 7, wherein the operation of S4 comprises: comparing the integrated state coefficient C of the battery cell with a corresponding threshold value interval set by a system, if ≥ The state of the battery cell is evaluated to be excellent, if ≤ < The state of the battery cell is generally evaluated, and attention is required; if it is ≤ Evaluating that the state of the battery cell is unqualified and needs to be replaced; the working process of the M4 comprises the following steps: comparing the module comprehensive state coefficient M with the corresponding threshold value interval set by the system, if ≥ The state of the module is evaluated to be excellent, if ≤ < The state of the evaluation module is general and needs to be paid attention; if it is ≤ If the state of the evaluation module is unqualified, the evaluation module needs to be replaced; The working process of the P4 comprises the following steps: comparing the battery pack comprehensive state coefficient P with a corresponding threshold value interval set by a system, if ≥ The battery pack state is evaluated to be excellent, if ≤ < The state of the battery pack is generally evaluated, and attention is required; if it is ≤ And evaluating that the battery pack is unqualified and needs to be replaced.
  10. 10. A battery monitoring method based on automotive battery parameters, characterized in that the method is implemented based on the battery monitoring system based on automotive battery parameters according to any one of claims 1-9.

Description

Battery monitoring system and method based on automobile battery parameters Technical Field The invention relates to the technical field of battery monitoring, in particular to a battery monitoring system and method based on automobile battery parameters. Background With the rapid development of the new energy automobile industry, the power battery is used as a core component, and the performance state of the power battery is directly related to the safety, the endurance mileage and the service life of the whole automobile. At present, the traditional battery monitoring system has the following problems that 1, most of the traditional battery monitoring system depends on threshold value alarming of single or few parameters such as voltage, current and temperature, and the like, and can only generally reflect the real-time running state of a battery, so that quantitative evaluation and early warning of the internal health state of the battery are difficult, and 2, for a battery module and a battery pack consisting of a plurality of electric cells, the traditional method lacks a hierarchical state evaluation model from single cells to the system, cannot accurately identify the influence of individual electric cells or module performance degradation on the whole battery system, and causes rough maintenance strategies, resource waste or potential safety hazards. Therefore, the invention provides a battery monitoring system and a battery monitoring method based on automobile battery parameters. Disclosure of Invention The invention aims to provide a battery monitoring system and method based on automobile battery parameters, which solve the technical problems as follows: the aim of the invention can be achieved by the following technical scheme: A battery monitoring system based on automobile battery parameters comprises a parameter acquisition module, a data preprocessing module, an edge calculation module, a state evaluation module and an early warning interaction module, wherein the modules are sequentially in communication connection; The parameter acquisition module comprises a distributed sensor array, wherein the distributed sensor array is arranged on the battery core, the module and the battery pack layer of the automobile battery, is used for acquiring multidimensional parameters of the battery and adds a time stamp to each acquired parameter; The data processing module is used for receiving the parameter data transmitted by the parameter acquisition module, and carrying out outlier rejection, missing value completion and standardization processing on the data, wherein the outlier rejection adopts 3 The standard, the missing value complement adopts the adjacent time sequence data interpolation method, the standardized processing maps the parameter data to the [0,1] interval, get the standardized time sequence data; The edge computing module is used for receiving the standardized data output by the data preprocessing module, and obtaining the real-time state coefficient of the battery core, the real-time state coefficient of the module and the real-time state coefficient of the battery pack layer by layer through state sub-coefficient weighted computation based on the working parameters and the power-off parameters of the battery; The state evaluation module is used for receiving the real-time state coefficient and evaluating the states of the battery cells, the modules and the battery packs according to a preset threshold value; and the early warning interaction module is used for pushing abnormal early warning information, a battery health report and maintenance advice to the user mobile terminal according to the state evaluation result. As a further description of the technical scheme of the invention, the parameter acquisition module is internally provided with a clock unit and is used for adding time stamps to various acquired parameter data; the parameter acquisition module is provided with a self-adaptive acquisition frequency control unit, and can automatically adjust the acquisition frequency according to the working state of the battery, namely, the parameter acquisition module adopts a frequency of 10Hz to carry out high-frequency acquisition in the power-on working state of the battery, and adopts a frequency of once every 30 minutes to carry out low-frequency acquisition in the power-off standing state of the battery. As a further description of the technical solution of the present invention, the working process of the edge computing module includes: s1, acquiring working parameters of a battery and parameters during power failure, wherein the working parameters comprise working voltage Operating currentAnd operating temperatureThe power-off parameter comprises a power-off instant open circuit voltageRecovery voltage after power-off for a predetermined timeAnd a resting temperature; S2, calculating four state sub-coefficients of the battery cell based on the working parameters and the powe