CN113933736B - Battery pack consistency evaluation method based on cloud discharge data - Google Patents
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- G—PHYSICS
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
Abstract
The invention discloses a battery pack consistency evaluation method based on cloud discharge data, which comprises the following steps: step 1, data cleaning is carried out on cloud data to obtain a plurality of groups of battery cell discharge voltage data; step 2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope and a lower envelope; step 3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve at each moment and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment; step 4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve; and 5, quantitatively evaluating the consistency of the battery pack through the slope of the final addition curve.
Description
Technical Field
The invention relates to the technical field of battery safety, in particular to a battery pack consistency evaluation method based on cloud discharge data.
Background
In recent years, along with the transition of energy structures, new energy is continuously promoted, and batteries are widely used in the fields of energy storage systems, electric automobiles and the like. Battery energy storage is an energy storage technology that utilizes electrochemical reactions to achieve the conversion between electrical energy and chemical energy. Among them, lithium ion batteries are one of the most widely used batteries by virtue of their high energy density, low self-discharge rate, and no memory. Because the manufacturing technology of lithium ion battery single cells is limited, in order to meet the requirements of electric equipment on battery power and energy, a plurality of single cells are often combined into a battery pack in a serial-parallel connection mode to supply power for the electric equipment. However, due to the use of materials, manufacturing process and the like, there may be differences among the battery cells shipped from the factory, and the differences among the battery cells may be gradually deepened during the use due to the influence of the use environment. The voltage, the internal resistance and the capacity of the battery are changed, so that the available capacity of the battery pack is reduced, the service life is shortened, and the economy, the stability and the safety of electric equipment are directly influenced. Therefore, timely and accurately detecting inconsistent battery cells in the battery pack and replacing the battery cells are of great significance in maintaining safe and stable operation of the battery pack.
The inconsistency of the battery pack is an important influencing factor of the performance thereof, and can reduce the usable capacity and cycle life of the battery pack. The inconsistency in the decay rate of the cells in the parallel circuit can accelerate deterioration of the system. The most intuitive manifestation of battery pack inconsistencies is cell voltage inconsistencies, which are common in the current literature in statistical studies. At present, aiming at the formation reason of the inconsistency of the battery pack and the influence of the inconsistency on the service life of the battery pack, the method mainly focuses on the development of related researches on the power battery of the electric automobile, experimental and test environments.
At present, most of data analysis of the battery pack adopts charging section data, and the charging section data has the advantages of high quality, stable data fluctuation and the like, and the discharging data often cannot obtain the utilization value due to the excessively low quality.
Disclosure of Invention
The present invention has been made to solve the above problems, and an object of the present invention is to provide a method for evaluating consistency of a battery pack based on cloud discharge data.
The invention provides a battery pack consistency evaluation method based on cloud discharge data, which has the characteristics that the method comprises the following steps: step 1, data cleaning is carried out on cloud data to obtain a plurality of groups of battery cell discharge voltage data; step 2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope and a lower envelope; step 3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve at each moment and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment; step 4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve; and 5, quantitatively evaluating the consistency of the battery pack through the slope of the final addition curve.
The battery pack consistency evaluation method based on cloud discharge data provided by the invention can also have the following characteristics: in step 2, when performing envelope processing, the following method is adopted: recording and storing battery pack monomer voltage as U, and calling an endslope function in MATLAB
[U up ,U down ]＝envelope(U) (1)
In U up For the upper envelope, U down Is the lower envelope.
The battery pack consistency evaluation method based on cloud discharge data provided by the invention can also have the following characteristics: in step 3, when the judgment is performed, the following method is adopted:
V upmax，i ＝max{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (2)
V upmin，i ＝min{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (3)
V downmax，i ＝max{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (4)
V downmin，i ＝min{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (5)
where k is the number of battery cells, i is the number of time nodes of the effective data, V upmax，i For each time node, corresponding to the maximum value of the upper envelope, V upmin，i For each time node, corresponding to the minimum value of the upper envelope curve, V downmax，i For each time node, corresponding to the maximum value of the lower envelope, V downmin，i The lower envelope minimum is corresponding to each time node.
The battery pack consistency evaluation method based on cloud discharge data provided by the invention can also have the following characteristics: in step 4, when accumulation is performed, the following method is adopted: v at each moment calculated in the step 3 upmax And V is equal to upmin Subtracting to obtain U up ，V downmax And V is equal to downmin Subtracting to obtain U down Respectively at each moment U up And U down Accumulate and U up And U down The summation of the accumulation curves is carried out by the following method:
wherein V is upsum，i For each moment U up Maximum difference accumulated value, V downsum，i For each moment U down The maximum difference accumulated value.
The battery pack consistency evaluation method based on cloud discharge data provided by the invention can also have the following characteristics: in the step 5, the method for quantitatively evaluating the consistency comprises the following steps:
and judging the consistency condition of the battery pack by using the final addition curve, namely if the slope of the final addition curve is gradually increased, indicating that the consistency is gradually deteriorated, and if the slope of the final addition curve is stable, indicating that the consistency condition is kept unchanged.
The battery pack consistency evaluation method based on cloud discharge data provided by the invention can also have the following characteristics: the discharge voltage data of the battery cells are five groups, wherein in the step 5, the specific process of the method for quantitatively evaluating the consistency is as follows: drawing a final addition curve with a slope of 0 through five groups of identical battery cell discharge voltage data, and discharging the five groups of identical battery cellsDrawing a final addition curve with a slope of 0.05 by adding 25mV at each moment of one of the monomers in the electric voltage data, drawing a final addition curve with a slope of 0.1 by adding 50mV at each moment of one of the monomers in five identical sets of battery cell discharge voltage data, drawing a final addition curve with a slope of 0.15 by adding 75mV at each moment of one of the monomers in five identical sets of battery cell discharge voltage data, drawing a final addition curve with a slope of 0.2 by adding 100mV at each moment of one of the monomers in five identical sets of battery cell discharge voltage data, determining a threshold value of the slope by adopting a maximum score and minimum score determining threshold value method, setting the full score threshold value to 0, and setting the threshold value (0 score) of the slope k to t v =0.2, calculating the score of the slope by piecewise linear interpolation when the slope is in the interval [0,0.05 ]]Time corresponding score [100,90 ]]Linear interpolation when the slope is in the interval 0.05,0.1]Time corresponding score [90,70 ]]Linear interpolation when the slope is in the interval [0.1,0.15 ]]Time corresponding score [70,40 ]]Linear interpolation when the slope is in the interval [0.15,0.2 ]]Time corresponding score [40,0]Linear interpolation, i.e.:
effects and effects of the invention
According to the battery pack consistency evaluation method based on cloud discharge data, because the cloud data is subjected to data cleaning to obtain a plurality of groups of battery cell discharge voltage data, the battery cell discharge voltage data is subjected to envelope processing to obtain an upper envelope and a lower envelope, the upper envelope and the lower envelope are respectively judged to obtain an upper envelope maximum and minimum value difference value accumulation curve and a lower envelope maximum and minimum value difference value accumulation curve, the upper envelope maximum and minimum value difference value accumulation curve and the lower envelope maximum and minimum value difference value accumulation curve are accumulated at each moment to obtain a final addition curve, and the battery pack consistency is quantitatively evaluated according to the slope of the final addition curve. The invention quantitatively evaluates the consistency according to the slope, intuitively reflects the consistency change condition of the battery pack, reduces the dependence on charging data to a certain extent, detects the inconsistent condition of the battery pack through discharging data to a certain extent, has important significance for maintaining the safe and stable operation of the battery pack, has certain significance for redevelopment of discharging data, solves the current blindness of the utilization of the charging data, and provides scientific guidance for the effective utilization of the discharging data.
Drawings
Fig. 1 is a flowchart of a method for evaluating consistency of a battery pack based on cloud discharge data in embodiment 1 of the present invention;
fig. 2 is upper and lower envelopes of a battery pack consistency evaluation method based on cloud discharge data in embodiment 2 of the present invention;
FIG. 3 is a final sum curve and a linear fit curve of the method for evaluating battery pack consistency based on cloud discharge data in example 2 of the present invention;
fig. 4 is upper and lower envelopes of a battery pack consistency evaluation method based on cloud discharge data in embodiment 3 of the present invention; and
fig. 5 is a final sum curve and a linear fit curve of the battery pack consistency evaluation method based on cloud discharge data in example 3 of the present invention.
Detailed Description
In order to make the technical means, creation characteristics, achievement purposes and effects of the invention easy to understand, the following embodiment describes a battery pack consistency evaluation method based on cloud discharge data with reference to the accompanying drawings.
Example 1 ]
In this embodiment, a method for evaluating consistency of a battery pack based on cloud discharge data is provided.
Fig. 1 is a flowchart of a method for evaluating consistency of a battery pack based on cloud discharge data in the present embodiment.
As shown in fig. 1, the method for evaluating consistency of a battery pack based on cloud discharge data according to the present embodiment includes the following steps:
step S1, data cleaning is carried out on cloud data to obtain five groups of battery cell discharge voltage data.
And S2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope curve and a lower envelope curve.
When the envelope processing is carried out, the following method is adopted: recording and storing battery pack monomer voltage as U, and calling an endslope function in MATLAB
[U up ,U down ]＝envelope(U) (1)
In U up For the upper envelope, U down Is the lower envelope.
And S3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment.
In the judgment, the following method is adopted:
V upmax，i ＝max{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (2)
V upmin，i ＝min{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (3)
V downmax，i ＝max{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (4)
V downmin，i ＝min{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (5)
where k is the number of battery cells, i is the number of time nodes of the effective data, V upmax，i For each time node, corresponding to the maximum value of the upper envelope, V upmin，i For each time node, corresponding to the minimum value of the upper envelope curve, V downmax，i For each time node, corresponding to the maximum value of the lower envelope, V downmin，i The lower envelope minimum is corresponding to each time node.
And S4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve.
When accumulation is carried out, the following method is adopted: v at each moment calculated in the step 3 upmax And V is equal to upmin Subtracting to obtain U up ，V downmax And V is equal to downmin Subtracting to obtain U down Respectively at each moment U up And U down Accumulate and U up And U down The summation of the accumulation curves is carried out by the following method:
wherein V is upsum，i For each moment U up Maximum difference accumulated value, V downsum，i For each moment U down The maximum difference accumulated value.
And S5, quantitatively evaluating the consistency of the battery pack through the slope of the final addition curve.
The method for quantitatively evaluating the consistency comprises the following steps: and judging the consistency condition of the battery pack by using the final addition curve, namely if the slope of the final addition curve is gradually increased, indicating that the consistency is gradually deteriorated, and if the slope of the final addition curve is stable, indicating that the consistency condition is kept unchanged.
The specific process of the method for quantitatively evaluating the consistency is as follows: drawing a final addition curve with a slope of 0 through five groups of identical battery cell discharge voltage data, drawing a final addition curve with a slope of 0.05 by adding 25mV at each moment of one cell in the five groups of identical battery cell discharge voltage data, drawing a final addition curve with a slope of 0.1 by adding 50mV at each moment of one cell in the five groups of identical battery cell discharge voltage data, and drawing a final addition curve with a slope of 0.1 by adding one cell to each moment of one cell in the five groups of identical battery cell discharge voltage dataDrawing a final sum curve with a slope of 0.15 by adding 75mV at each moment of one monomer, drawing a final sum curve with a slope of 0.2 by adding 100mV at each moment of one monomer in five groups of identical battery monomer discharge voltage data, determining a threshold value of the slope by adopting a method of determining a highest score and a lowest score, setting a full score threshold value to be 0, and setting a threshold value (0 score) of the slope k to be t v =0.2, calculating the score of the slope by piecewise linear interpolation when the slope is in the interval [0,0.05 ]]Time corresponding score [100,90 ]]Linear interpolation when the slope is in the interval 0.05,0.1]Time corresponding score [90,70 ]]Linear interpolation when the slope is in the interval [0.1,0.15 ]]Time corresponding score [70,40 ]]Linear interpolation when the slope is in the interval [0.15,0.2 ]]Time corresponding score [40,0]Linear interpolation, i.e.:
example 2 ]
In example 2, a specific application in example 1 is provided.
In this example, the consistency of the battery pack 1 was evaluated, and the battery pack 1 was a square-case battery with a nominal capacity of 100Ah attenuated by 5% and 5 fresh batteries with a nominal capacity of 100Ah were connected in series.
The specific implementation mode of the composition is as follows:
step S1, data cleaning is carried out on cloud data to obtain a group of battery cell discharge voltage data.
And S2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope curve and a lower envelope curve.
Fig. 2 is an upper envelope and a lower envelope of the battery pack consistency evaluation method based on cloud discharge data in the present embodiment.
And S3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment.
And S4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve with gradually reduced slope in the initial stage, stable slope in the transition stage and gradually increased slope in the final stage.
Fig. 3 is a final sum curve and a linear fit curve of the battery pack consistency evaluation method based on cloud discharge data in the present embodiment.
As shown in fig. 3, the slope of the fitted curve is 0.0618.
And S5, quantitatively evaluating the consistency of the battery pack through the slope of the final addition curve.
As shown in fig. 3, the interpolation scores according to the fit curve slope correspondence evaluation criteria are: 85.2719.
example 3 ]
In example 3, a specific application in example 1 is provided.
In this example, the consistency of the battery pack 2 was evaluated, and the battery pack 2 was composed of a square-case battery with a nominal capacity of 100Ah attenuated by 10% and 5 fresh batteries with a nominal capacity of 100Ah connected in series. The specific implementation mode is as follows:
step S1, data cleaning is carried out on cloud data to obtain a group of battery cell discharge voltage data.
And S2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope curve and a lower envelope curve.
Fig. 4 is an upper envelope and a lower envelope of the battery pack consistency evaluation method based on cloud discharge data in the present embodiment.
And S3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment.
And S4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve with gradually reduced slope in the initial stage, stable slope in the transition stage and gradually increased slope in the final stage.
Fig. 5 is a final sum curve and a linear fit curve of the battery pack consistency evaluation method based on cloud discharge data in the present embodiment.
As shown in fig. 5, the slope of the fitted curve is 0.0838.
And S5, quantitatively evaluating the consistency of the battery pack through the slope of the final addition curve.
As shown in fig. 5, the interpolation scores according to the fit curve slope correspondence evaluation criteria are: 76.4453.
effects and effects of the examples
According to the battery pack consistency evaluation method based on cloud discharge data in embodiments 1 to 3, since a plurality of sets of battery cell discharge voltage data are obtained by performing data cleaning on the cloud data, an upper envelope and a lower envelope are obtained by performing envelope processing on the battery cell discharge voltage data, the upper envelope and the lower envelope are respectively judged to obtain an upper envelope maximum and minimum difference accumulation curve and a lower envelope maximum and minimum difference accumulation curve at each time, the upper envelope maximum and minimum difference accumulation curve and the lower envelope maximum and minimum difference accumulation curve at each time are accumulated to obtain a final sum curve, and the battery pack consistency is quantitatively evaluated by the slope of the final sum curve. The invention quantitatively evaluates the consistency according to the slope, intuitively reflects the consistency change condition of the battery pack, reduces the dependence on charging data to a certain extent, detects the inconsistent condition of the battery pack through discharging data to a certain extent, has important significance for maintaining the safe and stable operation of the battery pack, has certain significance for redevelopment of discharging data, solves the current blindness of the utilization of the charging data, and provides scientific guidance for the effective utilization of the discharging data.
The above embodiments are preferred examples of the present invention, and are not intended to limit the scope of the present invention.
Claims (4)
1. The battery pack consistency evaluation method based on cloud discharge data is characterized by comprising the following steps of:
step 1, data cleaning is carried out on cloud data to obtain a plurality of groups of battery cell discharge voltage data;
step 2, carrying out envelope processing on the discharge voltage data of the battery cells to obtain an upper envelope and a lower envelope;
step 3, respectively judging the upper envelope curve and the lower envelope curve to obtain a maximum and minimum value difference value accumulation curve of the upper envelope curve and a maximum and minimum value difference value accumulation curve of the lower envelope curve at each moment;
step 4, accumulating the maximum and minimum value difference accumulation curve of the upper envelope curve at each moment and the maximum and minimum value difference accumulation curve of the lower envelope curve at each moment to obtain a final addition curve;
step 5, quantitatively evaluating the consistency of the battery pack according to the slope of the final addition curve,
in the step 5, the method for quantitatively evaluating the consistency comprises the following steps:
judging the consistency condition of the battery pack by utilizing the final addition curve, namely if the slope of the final addition curve is gradually increased, indicating that the consistency is gradually deteriorated, if the slope of the final addition curve is smooth, indicating that the consistency condition is kept unchanged,
the discharge voltage data of the battery cells are five groups,
in step 5, the specific process of the method for quantitatively evaluating the consistency is as follows:
drawing a final addition curve with a slope of 0 through five identical sets of the battery cell discharge voltage data, drawing a final addition curve with a slope of 0.05 by adding 25mV at each moment of one cell in the five identical sets of the battery cell discharge voltage data, drawing a final addition curve with a slope of 0.1 by adding 50mV at each moment of one cell in the five identical sets of the battery cell discharge voltage data, drawing a final addition curve with a slope of 0.15 by adding 75mV at each moment of one cell in the five identical sets of the battery cell discharge voltage data, drawing a final addition curve with a slope of 0.2 by adding 100mV at each moment of one cell in the five identical sets of the battery cell discharge voltage data,
determining threshold value of slope by using the method of highest score and lowest score, setting threshold value of full score to 0, and setting threshold value of slope k to 0 score to t v =0.2, calculating the score of the slope by piecewise linear interpolation when the slope is in the interval [0,0.05 ]]Time corresponding score [100,90 ]]Linear interpolation when the slope is in the interval 0.05,0.1]Time corresponding score [90,70 ]]Linear interpolation when the slope is in the interval [0.1,0.15 ]]Time corresponding score [70,40 ]]Linear interpolation when the slope is in the interval [0.15,0.2 ]]Time corresponding score [40,0]Linear interpolation.
2. The method for evaluating consistency of a battery pack based on cloud discharge data according to claim 1, wherein the method comprises the steps of:
in step 2, when the envelope processing is performed, the following method is adopted:
recording and storing battery pack monomer voltage as U, and calling an endslope function in MATLAB
[ U up ,U down ] ＝ envelope ( U ) (1)
In U up For the upper envelope, U down Is the lower envelope.
3. The method for evaluating consistency of a battery pack based on cloud discharge data according to claim 1, wherein the method comprises the steps of:
in step 3, when the judgment is performed, the following method is adopted:
V upmax，i ＝max{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (2)
V upmin，i ＝min{U up，1 ，U up，2 ，U up，3 ...U up，i },i＝1,2,3...k (3)
V downmax，i ＝max{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (4)
V downmin，i ＝min{U down，1 ，U down，2 ，U down，3 ...U down，i },i＝1,2,3...k (5)
where k is the number of battery cells, i is the number of time nodes of the effective data, V upmax，i For each time node, corresponding to the maximum value of the upper envelope, V upmin，i For each time node, corresponding to the minimum value of the upper envelope curve, V downmax，i For each time node, corresponding to the maximum value of the lower envelope, V downmin，i The lower envelope minimum is corresponding to each time node.
4. The method for evaluating consistency of a battery pack based on cloud discharge data according to claim 1, wherein the method comprises the steps of:
in step 4, when accumulation is performed, the following method is adopted:
v at each moment calculated in the step 3 upmax And V is equal to upmin Subtracting to obtain U up ，V downmax And V is equal to downmin Subtracting to obtain U down Respectively at each moment U up And U down Accumulate and U up And U down The summation of the accumulation curves is carried out by the following method:
wherein V is upmax And V is equal to upmin Respectively expressed as an upper envelope maximum value and an upper envelope minimum value, V downmax And V is equal to downmin Respectively expressed as a lower envelope maximum value and a lower envelope minimum value, V upsum，i For each moment U up Maximum difference accumulated value, V downsum，i For each moment U down The maximum difference accumulated value.
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