CN117686913A - Method for predicting discharge residual time of storage battery pack of communication power supply - Google Patents
Method for predicting discharge residual time of storage battery pack of communication power supply Download PDFInfo
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- 238000004891 communication Methods 0.000 title claims abstract description 138
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- 238000007781 pre-processing Methods 0.000 claims abstract description 16
- 239000013598 vector Substances 0.000 claims description 22
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Abstract
The invention discloses a method for predicting discharge residual time of a communication power supply storage battery pack, which belongs to the technical field of storage battery evaluation and comprises the following steps: collecting discharge data of different-capacity communication power supply storage battery packs, preprocessing, fitting the preprocessed discharge data of the different-capacity communication power supply storage battery packs by using a least square method to obtain discharge time-voltage curves of the different-capacity communication power supply storage battery packs, and selecting a discharge time-voltage curve with the smallest average deviation in the discharge time-voltage curves of the different-capacity communication power supply storage battery packs as a prediction reference curve according to the capacity of the communication power supply storage battery packs to be predicted to obtain predicted residual discharge time. The invention can predict the residual discharge time of the storage battery packs of the communication power supplies with different capacities, is convenient for operation and maintenance personnel to know the residual discharge time of the communication power supply system, provides reliable time margin for the operation and maintenance personnel of the communication power supply to perform fault processing, and prevents the communication fault from further expanding.
Description
Technical Field
The invention belongs to the technical field of storage battery evaluation, and relates to a method for predicting discharge residual time of a storage battery pack of a communication power supply.
Background
Besides regular inspection of the communication power supply storage battery pack of the communication power supply system, communication operation and maintenance personnel can conduct periodic tests on the communication power supply storage battery pack and periodically conduct a storage battery check discharge test, terminal voltage, temperature, current and the like of a battery are monitored in the discharge process, the communication operation and maintenance personnel are helped to analyze the quality and capacity of the storage battery pack, the communication power supply storage battery pack is guaranteed to have certain electric storage capacity, and when a rectification module of the communication power supply system fails, the communication power supply storage battery pack can serve as a backup power supply to supply power to equipment of a communication machine room.
As the service time of the communication power supply storage battery pack increases, the battery capacity of the communication power supply storage battery pack becomes smaller, and the power storage capacity of the communication power supply storage battery pack decreases, so that the power supply time of the communication power supply storage battery pack also decreases. At present, when a communication power supply system rectifying module fails, a communication power supply storage battery pack supplies power to communication equipment, a monitoring module can only monitor the voltage value of the communication power supply storage battery pack in real time, and the residual discharge time of the communication power supply storage battery pack cannot be predicted according to the actual capacity of a storage battery. Therefore, the residual discharge time of the storage battery pack of the communication power supply is predicted, and the residual discharge time is informed to operation and maintenance personnel in a remote communication mode, so that reliable time margin is provided for the operation and maintenance personnel of the communication power supply to perform fault processing, and further expansion of communication faults is prevented.
Disclosure of Invention
The method for predicting the discharge residual time of the communication power supply storage battery pack can analyze and obtain the residual discharge time of the communication power supply storage battery, and solves the problem that a monitoring module can only monitor a voltage value in real time and cannot predict the residual discharge time when the communication power supply storage battery pack supplies power to communication equipment.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: a method for predicting discharge residual time of a communication power supply storage battery pack comprises the following steps:
s1: collecting discharge data of the storage battery packs of different capacity communication power supplies, and preprocessing to obtain the preprocessed discharge data of the storage battery packs of different capacity communication power supplies;
s2: fitting and calculating by using a least square method according to the preprocessed discharge data of the storage battery packs of different capacity communication power supplies to obtain discharge time-voltage curves of the storage battery packs of different capacity communication power supplies;
s3: and selecting a discharge time-voltage curve with the smallest average deviation in the discharge time-voltage curves of the communication power supply storage battery packs with different capacities as a prediction reference curve according to the capacity of the communication power supply storage battery pack to be predicted, and predicting to obtain predicted residual discharge time.
The beneficial effects of the invention are as follows: according to the invention, the discharge time-voltage curve is obtained through the discharge data of the existing communication power supply storage battery packs with different capacities, so that the residual discharge time of the communication power supply storage battery packs with different capacities can be predicted, the operation and maintenance personnel can know the residual discharge time of the communication power supply storage battery packs conveniently, a reliable time margin is provided for the operation and maintenance personnel of the communication power supply to perform fault treatment, and the communication fault is prevented from being further expanded.
Further: the specific mode of pretreatment in S1 is as follows: and judging whether the difference value of adjacent discharge data in the discharge data of the storage battery packs of different capacity communication power supplies is larger than a preset value, if so, taking the adjacent next data as abnormal data, deleting the abnormal data to obtain the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment, otherwise, obtaining the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment as normal discharge data.
The beneficial effects of the above-mentioned further scheme are: by eliminating abnormal data, the quality of the discharge data of the preprocessed storage battery packs with different capacity communication power supplies can be improved, and the accuracy of prediction is improved.
Further: the specific steps of the S2 are as follows:
s201: according to a group of discharge data in the preprocessed discharge data of the storage battery packs with different capacities, a polynomial fitting function is obtained by using a least square method;
s202: calculating to obtain an error square sum according to the polynomial fitting function and the set of discharge data;
s203: minimizing the square sum of the errors, and calculating to obtain coefficient vectors of the polynomial fitting function;
s204: obtaining coefficients of the polynomial fitting function according to coefficient vectors of the polynomial fitting function, and drawing to obtain a discharge time-voltage curve of the storage battery;
s205: and judging whether each group of data in the preprocessed discharge data of the storage battery packs with different capacities is drawn to obtain a storage battery discharge time-voltage curve, if so, obtaining a plurality of storage battery discharge time-voltage curves with different capacities, and entering into S3, otherwise, returning to S201.
The beneficial effects of the above-mentioned further scheme are: according to the discharge data of the storage battery packs of the communication power supplies with different capacities, the discharge time-voltage curves of the storage batteries with different capacities are obtained, and the applicability of the prediction method can be improved.
Further: the expression of the polynomial fitting function in S201 is as follows:
f(x)＝p 1 x n-1 +p 2 x n-2 +…+p n-2 x 2 +p n-1 x 1 +p n
wherein f (x) is a polynomial fitting function, p 1 、p 2 、p 3 、...、p n-1 And p n Are coefficients of polynomial fitting functions, x 1 、x 2 、...、x n-2 And x n-1 All are power functions of discharge time of a group of discharge data in the discharge data of the storage battery packs with different capacity communication power supplies after pretreatment, and n is the coefficient number of the polynomial fitting function.
The beneficial effects of the above-mentioned further scheme are: and a polynomial fitting function is established, so that the residual discharge time-voltage curve of the communication power supply storage battery pack can be accurately and more described.
Further: the expression of the coefficient vector of the polynomial fitting function in S203 is as follows:
A*p＝b
A(i，j)＝x i n-j
wherein p is the coefficient vector of the polynomial fitting function, A is an m×n matrix, b is the column vector, m is the length of the preprocessing discharge data set, n is the coefficient number of the polynomial fitting function, A (i, j) is one element in the matrix A, x i n-j To the power of n-j, x of the discharge time of the ith group of data in the m preprocessing discharge data groups 1 n-1 N-1 th power of discharge time, x, of the 1 st measurement point of discharge time of the 1 st group of data in the m preprocessed discharge data groups 1 0 To the zero power of the discharge time of the nth measurement point of the 1 st group of discharge time data in the m preprocessed discharge data groups, x m n-1 N-1 th power, x of the discharge time of the 1 st measurement point of the m-th set of discharge time data in the m-th preprocessed discharge data sets m 0 To the zero power, p, of the discharge time of the nth measurement point of the mth group of discharge data in the m preprocessed discharge data groups 1 Coefficient 1 of coefficient vector for polynomial fitting function, p m The mth coefficient, y, of the coefficient vector for the polynomial fit function 1 For the voltage of the 1 st discharge data in the m pre-processing discharge data groups, y m The voltage of the m-th discharge data among the m pre-processed discharge data sets.
The beneficial effects of the above-mentioned further scheme are: by converting coefficients of the polynomial fitting function with undetermined coefficients into coefficient vectors, the computational complexity can be simplified, and the computational efficiency can be improved.
Further: the specific steps of the S3 are as follows:
s301: calculating to obtain an average deviation value according to the first N discharge data of the capacity of the communication power supply storage battery to be predicted and the first N discharge data of the discharge time-voltage curve of the communication power supply storage battery with different capacities;
s302: selecting a discharge time-voltage curve of the communication power supply storage battery pack with the minimum average deviation value as a prediction reference curve;
s303: and predicting the time required by the voltage to drop to the target value according to the prediction reference curve, and obtaining the predicted discharge residual time.
The beneficial effects of the above-mentioned further scheme are: the average deviation value is utilized to select the discharge time-voltage curve which is most suitable for the storage battery to be predicted, so that the accuracy of the predicted residual discharge time can be improved.
Drawings
FIG. 1 is a flow chart of a method for predicting discharge remaining time of a battery pack of a communication power supply;
FIG. 2 is a graph of discharge time versus voltage for a battery of 469 Ah;
FIG. 3 is a discharge time-voltage curve of a battery of 404.5 Ah;
FIG. 4 is a graph of discharge time versus voltage for a battery of 300 Ah;
fig. 5 is a discharge time-voltage curve of a battery of 200 Ah.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
In one embodiment of the present invention, as shown in fig. 1, the present invention provides a method for predicting discharge remaining time of a battery pack of a communication power supply, comprising the steps of:
s1: collecting discharge data of the storage battery packs of different capacity communication power supplies, and preprocessing to obtain the preprocessed discharge data of the storage battery packs of different capacity communication power supplies;
s2: fitting and calculating by using a least square method according to the preprocessed discharge data of the storage battery packs of different capacity communication power supplies to obtain discharge time-voltage curves of the storage battery packs of different capacity communication power supplies;
s3: and selecting a discharge time-voltage curve with the smallest average deviation in the discharge time-voltage curves of the communication power supply storage battery packs with different capacities as a prediction reference curve according to the capacity of the communication power supply storage battery pack to be predicted, and predicting to obtain predicted residual discharge time.
In one embodiment of the present invention, the discharge curve of the storage battery is very gentle, and only drops by 0.1V after about 10 minutes, if a difference of more than 0.5V occurs between adjacent data during the data preprocessing, the difference is treated as abnormal data, and is ignored during the curve fitting, so the specific manner of preprocessing in S1 may be: judging whether the difference value of adjacent discharge data in the discharge data of the storage battery packs of different capacity communication power supplies is larger than 0.5V, if so, taking the adjacent next data as abnormal data, deleting to obtain the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment, otherwise, obtaining the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment for normal discharge data, and marking one group of the obtained discharge data as (x) m ，y m ) Wherein x is the discharge time of the communication power supply storage battery, y is the voltage of the communication power supply storage battery, and m is the number of data points in a set of discharge data.
The specific steps of S2 are as follows:
s201: according to a group of discharge data in the preprocessed discharge data of the storage battery packs with different capacities, a polynomial fitting function is obtained by using least square fitting, and the polynomial fitting function has the following expression:
f(x)＝p 1 x n-1 +p 2 x n-2 +…+p n-2 x 2 +p n-1 x 1 +p n
wherein f (x) is a polynomial fitting function, p 1 、p 2 、p 3 、...、p n-1 And p n Are coefficients of polynomial fitting functions, x 1 、x 2 、...、x n-2 And x n-1 All are power functions of discharge time of a group of discharge data in the discharge data of the storage battery packs with different capacity communication power supplies after pretreatment, and n is the number of coefficients of a polynomial fitting function;
s202: and calculating to obtain an error square sum according to the polynomial fitting function and the set of discharge data, wherein the expression of the error square sum is as follows:
E＝sum((f(x i )-y i ) 2 )
where E is the sum of squares of the errors, sum is the sum, f (x i ) Calculating a predicted voltage value of the ith data in the preprocessed group of data according to the fitting polynomial function with undetermined coefficients, y i Is the actual voltage value of the ith data in a group of discharge data, x i Discharge time for the ith data in a set of discharge data;
s203: and minimizing the square sum of the errors, and calculating to obtain coefficient vectors of a polynomial fitting function, wherein the expression of the coefficient vectors of the polynomial fitting function is as follows:
A*p＝b
A(i，j)＝x i n-j
wherein p is the coefficient vector of the polynomial fitting function, A is an m×n matrix, b is the column vector, m is the length of the preprocessing discharge data set, n is the coefficient number of the polynomial fitting function, A (i, j) is one element in the matrix A, x i n-j To the power of n-j, x of the discharge time of the ith group of data in the m preprocessing discharge data groups 1 n-1 N-1 th power of discharge time, x, of the 1 st measurement point of discharge time of the 1 st group of data in the m preprocessed discharge data groups 1 0 To the zero power of the discharge time of the nth measurement point of the 1 st group of discharge time data in the m preprocessed discharge data groups, x m n-1 N-1 th power, x of the discharge time of the 1 st measurement point of the m-th set of discharge time data in the m-th preprocessed discharge data sets m 0 To the zero power, p, of the discharge time of the nth measurement point of the mth group of discharge data in the m preprocessed discharge data groups 1 Coefficient 1 of coefficient vector for polynomial fitting function, p m The mth coefficient, y, of the coefficient vector for the polynomial fit function 1 For the voltage of the 1 st discharge data in the m pre-processing discharge data groups, y m The voltage of the m-th discharge data in the m pre-treatment discharge data groups is used;
s204: obtaining coefficients of the polynomial fitting function according to coefficient vectors of the polynomial fitting function, and drawing to obtain a discharge time-voltage curve of the storage battery;
s205: and judging whether each group of data in the preprocessed discharge data of the storage battery packs with different capacities is drawn to obtain a storage battery discharge time-voltage curve, if so, obtaining a plurality of storage battery discharge time-voltage curves with different capacities, and entering into S3, otherwise, returning to S201.
The specific steps of S3 are as follows:
s301: according to the first N discharge data of the capacity of the communication power supply storage battery pack to be predicted and the first N discharge data of the discharge time-voltage curve of the communication power supply storage battery packs with different capacities, calculating to obtain an average deviation value, wherein the expression of the average deviation value is as follows:
wherein sigma is the average deviation, N is the number of selected data, Y i The ith discharge data for the capacity of the communication power supply battery to be predicted, Y' i The ith discharge data of the discharge time-voltage curve of the storage battery pack of the different capacity communication power supply;
s302: selecting a discharge time-voltage curve of the communication power supply storage battery pack with the minimum average deviation value as a prediction reference curve;
s303: and predicting the time required by the voltage to drop to the target value according to the prediction reference curve, and obtaining the predicted discharge residual time.
In one embodiment of the present invention, discharge data of the communication power supply battery packs having capacities of 469Ah, 404.5Ah, 300Ah and 200Ah are collected, respectively, and a communication power supply battery pack discharge time-voltage curve of 469Ah shown in fig. 2, a communication power supply battery pack discharge time-voltage curve of 404.5Ah shown in fig. 3, a communication power supply battery pack discharge time-voltage curve of 300Ah shown in fig. 4 and a communication power supply battery pack discharge time-voltage curve of 200Ah shown in fig. 5 are obtained by the method of the present invention, respectively, wherein the abscissa of fig. 2, 3, 4 and 5 is discharge time(s) and the ordinate is voltage (V), wherein the predicted voltage is the predicted voltage obtained by the present invention, expressed in "-", the measured voltage is the voltage measured by an instrument, expressed in "+", the communication power supply battery packs of 200Ah are measured and recorded every two minutes, and the communication power supply battery packs of 469Ah, 404.5Ah and 300Ah are measured every three minutes.
The method comprises the following steps that the residual discharge time of a communication power supply storage battery pack of a substation A is predicted, wherein the actual capacity of the communication power supply storage battery pack of the substation A is 450Ah; collecting discharge data of a communication power supply storage battery pack of a transformer substation, comparing the first 5 sets of discharge data with the first 5 sets of discharge data on discharge time-voltage curves of the communication power supply storage battery packs of 469Ah, 404.5Ah, 300Ah and 200Ah respectively, calculating average deviation, selecting a communication power supply storage battery pack discharge time-voltage curve with the minimum average deviation value as a prediction reference curve, and predicting the residual discharge time of the communication power supply storage battery pack of the transformer substation A according to the prediction reference curve, wherein the average deviation is expressed as follows:
wherein sigma is the average deviation, Y i Ith discharge data of storage battery pack of communication power supply of A transformer substation, Y' i The ith discharge data, which is a discharge time-voltage curve;
according to the expression, average deviation of the first 5 sets of discharge data of the communication power supply storage battery pack of the A transformer substation and the first 5 sets of data of the communication power supply storage battery pack discharge time-voltage curves of 469Ah, 404.5Ah, 300Ah and 200Ah are calculated respectively, and the average deviation of the first 5 sets of discharge data of the communication power supply storage battery pack of the A transformer substation and the communication power supply storage battery pack discharge time-voltage curve of known capacity is obtained as shown in table 1:
TABLE 1
| Battery pack capacity | 469Ah | 200Ah | 300Ah | 404.5Ah |
| Average deviation | 0.02 | 0.11 | 0.49 | 0.044 |
As can be seen from table 1, the average deviation between the first five sets of data of the 469Ah communication power supply storage battery pack and the a-substation communication power supply storage battery pack is the smallest, and thus the discharge curve of the 469Ah communication power supply storage battery pack is selected to fit the discharge characteristics of the a-substation communication power supply lead-acid communication power supply storage battery pack.
Using 469Ah lead acid communication power supply battery pack discharge characteristics to predict the time versus actual time for a substation a communication power supply battery pack voltage to drop to 48v,47.5v,47v,46.5v, table 2:
TABLE 2
As can be seen from the above table, the discharge time-voltage curve of the 469Ah lead-acid communication power supply storage battery is used for prediction: the time when the voltage of the communication power supply storage battery pack of the substation A is predicted to be reduced to 48.0V is 14686s, about 245 minutes, and the time when the voltage of the communication power supply storage battery pack of the actual substation A is reduced to 48.0V is 14220s, about 237 minutes; the time when the voltage of the communication power supply storage battery pack of the substation A is predicted to be reduced to 47.5V is 19058s, about 317 minutes, and the time when the voltage of the communication power supply storage battery pack of the actual substation A is reduced to 47.5V is 18540s, about 309 minutes; the time when the voltage of the communication power supply storage battery pack of the substation A is predicted to be reduced to 47.0V is 23213s and is about 387 minutes, and the time when the voltage of the communication power supply storage battery pack of the substation A is actually reduced to 47.0V is predicted to be 22860s and is about 381 minutes; the time when the voltage of the communication power supply storage battery pack of the substation A is predicted to be reduced to 47.0V is 26535s, about 442 minutes, and the time when the voltage of the communication power supply storage battery pack of the actual substation A is predicted to be reduced to 47.0V is 26100s, about 435 minutes; the maximum error is 518s, about 8.6 minutes, the average error is 443s, and the accuracy of predicting the residual time is high relative to the whole residual discharge time.
The beneficial effects of the invention are as follows: according to the invention, the discharge time-voltage curve is obtained through the discharge data of the existing communication power supply storage battery packs with different capacities, so that the residual discharge time of the communication power supply storage battery packs with different capacities can be predicted, the operation and maintenance personnel can know the residual discharge time of the communication power supply storage battery packs conveniently, a reliable time margin is provided for the operation and maintenance personnel of the communication power supply to perform fault treatment, and the communication fault is prevented from being further expanded.
Claims (6)
1. The method for predicting the discharge residual time of the communication power supply storage battery pack is characterized by comprising the following steps of:
s1: collecting discharge data of the storage battery packs of different capacity communication power supplies, and preprocessing to obtain the preprocessed discharge data of the storage battery packs of different capacity communication power supplies;
s2: fitting and calculating by using a least square method according to the preprocessed discharge data of the storage battery packs of different capacity communication power supplies to obtain discharge time-voltage curves of the storage battery packs of different capacity communication power supplies;
s3: and selecting a discharge time-voltage curve with the smallest average deviation in the discharge time-voltage curves of the communication power supply storage battery packs with different capacities as a prediction reference curve according to the capacity of the communication power supply storage battery pack to be predicted, and predicting to obtain predicted residual discharge time.
2. The method for predicting discharge remaining time of a battery pack for a communication power supply according to claim 1, wherein the specific manner of preprocessing in S1 is as follows:
and judging whether the difference value of adjacent discharge data in the discharge data of the storage battery packs of different capacity communication power supplies is larger than a preset value, if so, taking the adjacent next data as abnormal data, deleting the abnormal data to obtain the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment, otherwise, obtaining the discharge data of the storage battery packs of different capacity communication power supplies after pretreatment as normal discharge data.
3. The method for predicting discharge remaining time of a battery pack for a communication power supply according to claim 1, wherein the specific step of S2 is as follows:
s201: according to a group of discharge data in the preprocessed discharge data of the storage battery packs with different capacities, a polynomial fitting function is obtained by using a least square method;
s202: calculating to obtain an error square sum according to the polynomial fitting function and the set of discharge data;
s203: minimizing the square sum of the errors, and calculating to obtain coefficient vectors of the polynomial fitting function;
s204: obtaining coefficients of the polynomial fitting function according to coefficient vectors of the polynomial fitting function, and drawing to obtain a discharge time-voltage curve of the storage battery;
s205: and judging whether each group of data in the preprocessed discharge data of the storage battery packs with different capacities is drawn to obtain a storage battery discharge time-voltage curve, if so, obtaining a plurality of storage battery discharge time-voltage curves with different capacities, and entering into S3, otherwise, returning to S201.
4. The method for predicting discharge remaining time of a battery pack for a communication power supply according to claim 3, wherein the polynomial fitting function in S201 has the expression:
f(x)＝p 1 x n-1 +p 2 x n-2 +…+p n-2 x 2 +p n-1 x 1 +p n
wherein f (x) is a polynomial fitting function, p 1 、p 2 、p 3 、…、p n-1 And p n Are coefficients of polynomial fitting functions, x 1 、x 2 、…、x n-2 And x n-1 All are in the discharge data of the pretreated communication power supply storage battery packs with different capacitiesAnd n is the number of coefficients of a polynomial fitting function.
5. The method for predicting discharge remaining time of a communication power supply battery pack according to claim 3, wherein the expression of the coefficient vector of the polynomial fitting function in S203 is as follows:
A*p＝b
A(i,j)＝x i n-j
wherein p is the coefficient vector of the polynomial fitting function, A is an m×n matrix, b is the column vector, m is the length of the preprocessing discharge data set, n is the coefficient number of the polynomial fitting function, A (i, j) is one element in the matrix A, x i n-j To the power of n-j, x of the discharge time of the ith group of data in the m preprocessing discharge data groups 1 n-1 N-1 th power of discharge time, x, of the 1 st measurement point of discharge time of the 1 st group of data in the m preprocessed discharge data groups 1 0 To the zero power of the discharge time of the nth measurement point of the 1 st group of discharge time data in the m preprocessed discharge data groups, x m n-1 N-1 th power, x of the discharge time of the 1 st measurement point of the m-th set of discharge time data in the m-th preprocessed discharge data sets m 0 To the zero power, p, of the discharge time of the nth measurement point of the mth group of discharge data in the m preprocessed discharge data groups 1 Coefficient 1 of coefficient vector for polynomial fitting function, p m The mth coefficient, y, of the coefficient vector for the polynomial fit function 1 For the voltage of the 1 st discharge data in the m pre-processing discharge data groups, y m The voltage of the m-th discharge data among the m pre-processed discharge data sets.
6. The method for predicting discharge remaining time of a battery pack for a communication power supply according to claim 1, wherein the specific step of S3 is as follows:
s301: calculating to obtain an average deviation value according to the first N discharge data of the capacity of the communication power supply storage battery to be predicted and the first N discharge data of the discharge time-voltage curve of the communication power supply storage battery with different capacities;
s302: selecting a discharge time-voltage curve of the communication power supply storage battery pack with the minimum average deviation value as a prediction reference curve;
s303: and predicting the time required by the voltage to drop to the target value according to the prediction reference curve, and obtaining the predicted discharge residual time.
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