CN117368768A - Method, system and medium for predicting residual capacity of lead-acid storage battery of direct-current system - Google Patents
Method, system and medium for predicting residual capacity of lead-acid storage battery of direct-current system Download PDFInfo
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- 239000002253 acid Substances 0.000 title claims abstract description 261
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000007599 discharging Methods 0.000 claims abstract description 27
- 238000007667 floating Methods 0.000 claims abstract description 13
- 208000028659 discharge Diseases 0.000 claims description 61
- 238000012937 correction Methods 0.000 claims description 48
- 238000012795 verification Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 6
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- 238000012423 maintenance Methods 0.000 abstract description 4
- 230000002035 prolonged effect Effects 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract 1
- 238000005457 optimization Methods 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 4
- 238000012887 quadratic function Methods 0.000 description 3
- QAOWNCQODCNURD-UHFFFAOYSA-N Sulfuric acid Chemical compound OS(O)(=O)=O QAOWNCQODCNURD-UHFFFAOYSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 239000003574 free electron Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- PIJPYDMVFNTHIP-UHFFFAOYSA-L lead sulfate Chemical compound [PbH4+2].[O-]S([O-])(=O)=O PIJPYDMVFNTHIP-UHFFFAOYSA-L 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
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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
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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]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
- G01R31/379—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator for lead-acid batteries
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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]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
The invention discloses a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system; the residual capacity prediction technology field is related to; the lead-acid storage battery pack is subjected to first discharging in a floating charge running state, terminal voltage of each lead-acid storage battery is collected, and the lead-acid storage battery with the minimum capacity is determined; the residual capacity of the lead-acid storage battery is predicted timely and accurately through the first discharging and the second discharging and by combining a residual capacity prediction model, so that a great amount of energy consumption of a power failure capacity-checking mode is avoided, the storage battery is prevented from being excessively charged and discharged, and the service life of the storage battery is prolonged; the scheme rapidly determines the lead-acid storage battery with the minimum capacity based on the terminal voltage of each lead-acid storage battery, and lays a foundation for maintenance work of the lead-acid storage battery; and meanwhile, during the second discharging, the lead-acid storage battery with the minimum capacity is used as a reference, and the standby battery pack is avoided.
Description
Technical Field
The invention relates to the technical field of residual capacity prediction, in particular to a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system.
Background
All levels of substations in the power grid play a role in importance, and the safe and stable operation of all levels of substations is more relevant to the stable operation of the whole large power grid. The relay protection device in each level of transformer substation, the operation loop, the computer monitoring equipment, the control system, the signal system, the accident lighting equipment, the AC uninterrupted power supply and other DC loads, and the storage battery pack for supplying power to the DC loads are commonly and collectively called as a DC system of a transformer substation; the storage battery pack in the direct current system provides a stable direct current power supply for relay protection, control, signals and operation loops, so that the storage battery in the direct current system can reliably supply power, and is one of the decisive conditions for ensuring the stable operation of the transformer substation.
Once the power grid fails, when the transformer substation is in a power-free state, equipment in the substation is controlled and illumination is supplied by discharging a storage battery; the residual capacity of the storage battery pack of the direct current system is accurately predicted, so that the storage battery can be prevented from being overcharged and discharged, and the service life of the storage battery pack is prolonged.
The existing common direct current system storage battery pack monitoring system can only monitor the running condition of the storage battery in real time in terms of current, voltage, node signals and the like of each part of the storage battery, and the monitoring of the residual capacity (SOC) of the storage battery is very small; the remaining capacity of the battery is often detected only by means of a dead capacity. The power failure capacity checking process needs to carry out deep discharge with 100% capacity on the storage battery pack, so that the problems of long discharge time, high risk, high energy consumption, influence on the service life of the battery and need of a standby battery pack exist.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the invention aims to provide a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system, wherein the method, the system and the medium for predicting the residual capacity of the lead-acid storage battery of the direct-current system can be used for predicting the residual capacity of the lead-acid storage battery in time by combining a residual capacity prediction model through first discharging and second discharging, so that a great amount of energy consumption of a power-off capacity-checking mode is avoided; the scheme rapidly determines the lead-acid storage battery with the minimum capacity based on the terminal voltage of each lead-acid storage battery, and lays a foundation for maintenance work of the lead-acid storage battery; and meanwhile, during the second discharging, the lead-acid storage battery with the minimum capacity is used as a reference, and the standby battery pack is avoided.
The invention is realized by the following technical scheme:
the scheme provides a method for predicting the residual capacity of a lead-acid storage battery of a direct-current system, which comprises the following steps:
step one: the lead-acid storage battery pack is subjected to first discharging in a floating charge running state, terminal voltage of each lead-acid storage battery is collected, and the lead-acid storage battery with the minimum capacity is determined;
step two: determining discharge time t according to the minimum capacity lead-acid storage battery, and enabling the lead-acid storage battery to be assembled into a direct current system to perform secondary discharge, wherein the discharge time is t; collecting an operation data set of each lead-acid storage battery;
step three: inputting the operation data set of the lead-acid storage battery into a constructed residual capacity prediction model, and carrying out parameter correction on the residual capacity prediction model;
step four: and predicting the residual capacity of the lead-acid storage battery at the future moment based on the residual capacity prediction model after parameter correction.
The working principle of the scheme is as follows: the invention aims to provide a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system, which are used for predicting the residual capacity of the lead-acid storage battery in time and accurately by combining a residual capacity prediction model through first discharging and second discharging, so that a great amount of energy consumption of a power-off capacity-checking mode is avoided, the storage battery is prevented from being overcharged and discharged, and the service life of the storage battery is prolonged; the scheme rapidly determines the lead-acid storage battery with the minimum capacity based on the terminal voltage of each lead-acid storage battery, and lays a foundation for maintenance work of the lead-acid storage battery; and meanwhile, during the second discharging, the lead-acid storage battery with the minimum capacity is used as a reference, and the standby battery pack is avoided.
In consideration of different lead-acid batteries in the lead-acid battery pack, when the lead-acid batteries are discharged at the same time, the time and the state of discharge start of the lead-acid batteries are different due to individual differences.
The further optimized scheme is that the lead-acid storage battery pack is subjected to first discharging in a floating charge running state, the terminal voltage of each lead-acid storage battery is collected, and the minimum terminal voltage lead-acid storage battery is determined, and the method comprises the following steps:
t1, discharging the lead-acid storage battery pack in a floating charge running state at the ith moment, and collecting terminal voltage U of each lead-acid storage battery i ＝{U i1 ,U i2 ,…,U in -a }; n represents the total number of lead-acid batteries; collecting terminal voltage U of each lead-acid storage battery at j=i+1 time j ＝{U j1 ,U j2 ,…,U jn }；
T2, calculating the slope of each lead-acid storage battery by taking the terminal voltage of the lead-acid storage battery as an ordinate and the acquisition time as an abscissa; and terminal voltage U of each lead-acid battery j ＝{U j1 ,U j2 ,…,U jn Sequencing from small to large to obtain a terminal voltage sequence;
t3, starting from the minimum terminal voltage in the terminal voltage sequence, judging the slope K of the current minimum terminal voltage: if K is greater than or equal to zero, discarding the minimum terminal voltage, taking the second minimum terminal voltage as the minimum terminal voltage, and returning to the step T3; if K is smaller than zero, entering a step T4;
t4, judging whether the slope K is smaller than the slope threshold K y If so, the lead-acid storage battery corresponding to the slope K is the lead-acid storage battery with the minimum capacity; otherwise, the minimum terminal voltage is discarded, the second smallest terminal voltage is taken as the minimum terminal voltage, and the process returns to the step T3.
Based on the relation curve of the terminal voltage and the discharge time of the lead-acid storage battery, the scheme discovers that different lead-acid storage batteries in the lead-acid storage battery pack are in different states when discharged at the same time, so that the minimum capacity lead-acid storage battery is determined according to the characteristic of the relation curve of the terminal voltage and the discharge time of the lead-acid storage battery; when the minimum capacity lead-acid storage battery is determined, the lead-acid storage battery corresponding to the minimum terminal voltage is not selected, but the minimum capacity lead-acid storage battery is determined after threshold logic judgment is carried out on the terminal voltage and the slope of the lead-acid storage battery, and the terminal voltage of the lead-acid storage battery with the minimum terminal voltage is not necessarily the minimum residual capacity when the terminal voltage discharges at the moment r, and the residual capacity is judged according to the state of the terminal voltage, so that the accuracy is improved.
The further optimization scheme is that the discharge time t is determined according to the minimum capacity lead-acid storage battery, so that the lead-acid storage battery is assembled into the direct current system to perform secondary discharge, and the discharge time is t; the method comprises the following steps:
leading the lead-acid storage battery to be assembled into a direct current system for secondary discharge;
collecting terminal voltage of each lead-acid storage battery in real time, and when the terminal voltage of the lead-acid storage battery with the minimum capacity is U m Ending the second discharge, U m ＝80％U jmin ,U jmin Is the terminal voltage at the j-th moment when the lead-acid storage battery with the minimum capacity is discharged for the first time.
The further optimization scheme is that the operation data set of each lead-acid storage battery comprises lead-acid storage battery terminal voltages U1, U2, … and UL corresponding to discharge time t1, t2 and … tL.
The further optimization scheme is that the constructed residual capacity prediction model is as follows:
wherein, the residual capacity of the S lead-acid storage battery; s is S n Indicating the rated capacity of a lead-acid battery, t n Indicating the end voltage of the lead-acid storage battery as U n The discharge time for discharging the rated capacity is determined according to the following equation:
x, y and z represent a first correction parameter, a second correction parameter and a third correction parameter, respectively, and t represents a discharge time.
The further optimization scheme is that the operation data set of the lead-acid storage battery is input into a constructed residual capacity prediction model, and the residual capacity prediction model is subjected to parameter correction, and the method comprises the following steps:
s1, dividing an operation data set of a lead-acid storage battery into f groups with every three groups, wherein f=L/3;
s2, dividing the f-group operation data set into a calculation group and b verification groups, wherein a+b=f; and inputting a calculation groups into the following formula:
calculating a first correction parameter, a second correction parameter and a third correction parameter set, and substituting the average value of the a first correction parameters, the average value of the second correction parameters and the average value of the third correction parameters into a residual capacity prediction model;
and S3, inputting the b verification groups into the residual capacity prediction model obtained in the S2, and verifying the accuracy of the current residual capacity prediction model by using root mean square error and goodness of fit.
According to the scheme, the residual capacity prediction model is obtained by directly fitting the trend of the terminal voltage along with the discharge time by using a quadratic function, and when different lead-acid batteries in the lead-acid battery pack are discharged at the same time, the difference exists between the time and the state of the discharge start of the lead-acid batteries due to individual difference, and certain error exists in the residual capacity prediction model obtained by directly fitting the trend of the terminal voltage along with the discharge time by using the quadratic function, so that the operation data set is divided into f groups by using every three groups, and the first correction parameter, the second correction parameter and the third correction parameter are calculated, so that the coefficients of the quadratic function are corrected, and the residual capacity prediction model is more matched with the lead-acid battery pack.
Further optimizing scheme is that the root mean square error E is expressed as:
the goodness of fit D is expressed as:
wherein U 'is' t Representing the measured value and the predicted value of the terminal voltage of the lead-acid storage battery of the t group, U' t ' represents the average of the measured values of the terminal voltages of the lead-acid batteries in the b verification groups.
The scheme predicts the residual capacity of the lead-acid storage battery by utilizing the operation data set of the lead-acid storage battery, and verifies the accuracy of the predicted residual capacity by comparing the residual capacity with the actual measured value and the predicted value of the actual terminal voltage of the lead-acid storage battery, thereby providing a reference for judging the residual capacity of the electric storage battery.
The further optimization scheme is that the method further comprises a step five, and specifically comprises the following sub-steps:
s51, acquiring the slope of each lead-acid storage battery;
s52, charging each lead-acid storage battery according to the slope of each lead-acid storage battery:
when the slope Ke of the lead-acid storage battery e is smaller than zero and smaller than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a first capacity interval;
when the slope Ke of the lead-acid storage battery e is greater than or equal to zero, the charging capacity of the lead-acid storage battery e is a second capacity interval;
when the slope Ke of the lead-acid storage battery e is smaller than zero and larger than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a third capacity interval;
wherein the first capacity interval is smaller than the second capacity interval, and the second capacity interval is smaller than the third capacity interval.
The scheme is used for supplementing energy with different capacities aiming at lead-acid storage batteries with different residual capacities, so that the phenomenon of overcharging and missing charging is avoided.
The scheme also provides a system for predicting the residual capacity of the lead-acid storage battery of the direct-current system, which is used for realizing the method for predicting the residual capacity of the lead-acid storage battery of the direct-current system; comprising the following steps:
the first acquisition module is used for enabling the lead-acid storage battery pack to discharge for the first time in a floating charge running state, acquiring terminal voltage of each lead-acid storage battery and determining the lead-acid storage battery with the minimum capacity;
the second acquisition module is used for determining discharge time t according to the minimum capacity lead-acid storage battery, so that the lead-acid storage battery is assembled into the direct current system to perform secondary discharge, and the discharge time is t; collecting an operation data set of each lead-acid storage battery;
the correction module is used for inputting the operation data set of the lead-acid storage battery into the constructed residual capacity prediction model and carrying out parameter correction on the residual capacity prediction model;
and the prediction module is used for predicting the residual capacity of the lead-acid storage battery at the moment T based on the residual capacity prediction model after parameter correction.
The present solution also provides a computer readable medium having stored thereon a computer program for execution by a processor to implement a method of predicting the remaining capacity of a lead-acid battery of a direct current system as described above.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the invention provides a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system; the residual capacity of the lead-acid storage battery is predicted timely and accurately through the first discharging and the second discharging and by combining a residual capacity prediction model, so that a great amount of energy consumption of a power failure capacity-checking mode is avoided, the storage battery is prevented from being excessively charged and discharged, and the service life of the storage battery is prolonged; the scheme rapidly determines the lead-acid storage battery with the minimum capacity based on the terminal voltage of each lead-acid storage battery, and lays a foundation for maintenance work of the lead-acid storage battery; and meanwhile, during the second discharging, the lead-acid storage battery with the minimum capacity is used as a reference, and the standby battery pack is avoided. In consideration of different lead-acid batteries in the lead-acid battery pack, when the lead-acid batteries are discharged at the same time, the time and the state of discharge start of the lead-acid batteries are different due to individual differences.
2. The invention provides a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system; and the lead-acid storage batteries with different residual capacities are subjected to energy supplementation with different capacities, so that the phenomenon of overcharging and missed charging is avoided.
3. The invention provides a method, a system and a medium for predicting the residual capacity of a lead-acid storage battery of a direct-current system; and predicting the residual capacity of the lead-acid storage battery by using an operation data set of the lead-acid storage battery, and comparing the residual capacity with an actual measured value and a predicted value of the actual terminal voltage of the lead-acid storage battery to verify the accuracy of the predicted residual capacity, thereby providing a reference for judging the residual capacity of the electric storage battery.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the drawings that are needed in the examples will be briefly described below, it being understood that the following drawings only illustrate some examples of the present invention and therefore should not be considered as limiting the scope, and that other related drawings may be obtained from these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow chart of a method for predicting the residual capacity of a lead-acid storage battery of a direct current system;
fig. 2 is a schematic diagram of a simultaneous discharge process of the lead-acid battery 1 and the lead-acid battery 2.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
The existing storage battery monitoring system has the problems that the discharging time is long, the energy consumption is high, the service life of a battery is influenced and a standby battery is needed in the capacity stopping process, and the following embodiments are provided for solving the problems:
example 1
The embodiment provides a method for predicting the residual capacity of a lead-acid storage battery of a direct-current system, as shown in fig. 1, comprising the following steps:
step one: the lead-acid storage battery pack is subjected to first discharging in a floating charge running state, terminal voltage of each lead-acid storage battery is collected, and the lead-acid storage battery with the minimum capacity is determined;
step two: determining discharge time t according to the minimum capacity lead-acid storage battery, and enabling the lead-acid storage battery to be assembled into a direct current system to perform secondary discharge, wherein the discharge time is t; collecting an operation data set of each lead-acid storage battery;
step three: inputting the operation data set of the lead-acid storage battery into a constructed residual capacity prediction model, and carrying out parameter correction on the residual capacity prediction model;
step four: and predicting the residual capacity of the lead-acid storage battery at the future moment based on the residual capacity prediction model after parameter correction.
The lead-acid storage battery is subjected to first discharging in a floating charge running state, terminal voltage of each lead-acid storage battery is collected, and the minimum terminal voltage lead-acid storage battery is determined, and the method comprises the following steps:
t1, discharging the lead-acid storage battery pack in a floating charge running state at the ith moment, and collecting terminal voltage U of each lead-acid storage battery i ＝{U i1 ,U i2 ,…,U in -a }; n represents the total number of lead-acid batteries; collecting terminal voltage U of each lead-acid storage battery at j=i+1 time j ＝{U j1 ,U j2 ,…,U jn }；
T2, calculating the slope of each lead-acid storage battery by taking the terminal voltage of the lead-acid storage battery as an ordinate and the acquisition time as an abscissa; and terminal voltage U of each lead-acid battery j ＝{U j1 ,U j2 ,…,U jn Sorting from small to largeObtaining a terminal voltage sequence;
t3, starting from the minimum terminal voltage in the terminal voltage sequence, judging the slope K of the current minimum terminal voltage: if K is greater than or equal to zero, discarding the minimum terminal voltage, taking the second minimum terminal voltage as the minimum terminal voltage, and returning to the step T3; if K is smaller than zero, entering a step T4;
t4, judging whether the slope K is smaller than the slope threshold K y If so, the lead-acid storage battery corresponding to the slope K is the lead-acid storage battery with the minimum capacity; otherwise, the minimum terminal voltage is discarded, the second smallest terminal voltage is taken as the minimum terminal voltage, and the process returns to the step T3.
Based on the relation curve of the terminal voltage and the discharge time of the lead-acid storage battery, the embodiment discovers that different lead-acid storage batteries in the lead-acid storage battery pack are in different states when discharged at the same time, so that the minimum capacity lead-acid storage battery is determined according to the characteristic of the relation curve of the terminal voltage and the discharge time of the lead-acid storage battery; when the minimum capacity lead-acid storage battery is determined, the lead-acid storage battery corresponding to the minimum terminal voltage is not selected, but the minimum capacity lead-acid storage battery is determined after threshold logic judgment is carried out on the terminal voltage and the slope of the lead-acid storage battery, and the terminal voltage of the lead-acid storage battery with the minimum terminal voltage is not necessarily the minimum residual capacity when the terminal voltage discharges at the moment r, and the residual capacity is judged according to the state of the terminal voltage, so that the accuracy is improved. As shown in fig. 2, the lead-acid storage battery 1 and the lead-acid storage battery 2 start to discharge simultaneously, the terminal voltage of the two storage batteries drops very fast, after the state of adapting to the current discharge, the reaction inside the storage battery continues, the lead sulfate in the polar plate hole is free or sunk due to physical action, the diffusion speed of the dilute sulfuric acid is recovered, the free electrons inside the lead-acid storage battery start to uniformly distribute and reduce the internal resistance, the electromotive force of the lead-acid storage battery starts to rise, the terminal voltage of the lead-acid storage battery starts to rise, the capacity of the storage battery is correspondingly recovered as the terminal voltages of three points A, B and C in the figure, the point C is in a state that the terminal voltage is slowly reduced, after the capacity is recovered, and the terminal voltage of the point a and the point B are before the capacity is recovered, so that the residual capacity of the point C is smaller than the capacities of the point a and the point B in practice, and the state of the lead-acid storage battery needs to be considered when judging the capacity of the storage battery according to the terminal voltage of the lead-acid storage battery.
Determining discharge time t according to the minimum capacity lead-acid storage battery, and enabling the lead-acid storage battery to be assembled into a direct current system to perform secondary discharge, wherein the discharge time is t; the method comprises the following steps:
leading the lead-acid storage battery to be assembled into a direct current system for secondary discharge;
collecting terminal voltage of each lead-acid storage battery in real time, and when the terminal voltage of the lead-acid storage battery with the minimum capacity is U m Ending the second discharge, U m ＝80％U jmin ,U jmin Is the terminal voltage at the j-th moment when the lead-acid storage battery with the minimum capacity is discharged for the first time.
The operation data set of each lead-acid storage battery comprises lead-acid storage battery terminal voltages U1, U2, … and UL corresponding to discharge time t1, t2 and … tL.
The constructed residual capacity prediction model is as follows:
wherein, the residual capacity of the S lead-acid storage battery; s is S n Indicating the rated capacity of a lead-acid battery, t n Indicating the end voltage of the lead-acid storage battery as U n The discharge time for discharging the rated capacity is determined according to the following equation:
x, y and z represent a first correction parameter, a second correction parameter and a third correction parameter, respectively, and t represents a discharge time.
Inputting an operation data set of the lead-acid storage battery into a constructed residual capacity prediction model, and carrying out parameter correction on the residual capacity prediction model, wherein the method comprises the following steps:
s1, dividing an operation data set of a lead-acid storage battery into f groups with every three groups, wherein f=L/3;
s2, dividing the f-group operation data set into a calculation group and b verification groups, wherein a+b=f; and inputting a calculation groups into the following formula:
calculating a first correction parameter, a second correction parameter and a third correction parameter set, and substituting the average value of the a first correction parameters, the average value of the second correction parameters and the average value of the third correction parameters into a residual capacity prediction model;
and S3, inputting the b verification groups into the residual capacity prediction model obtained in the S2, and verifying the accuracy of the current residual capacity prediction model by using root mean square error and goodness of fit.
The root mean square error E is expressed as:
the goodness of fit D is expressed as:
wherein U 'is' t Representing the measured value and the predicted value of the terminal voltage of the lead-acid storage battery of the t group, U' t ' represents the average of the measured values of the terminal voltages of the lead-acid batteries in the b verification groups.
The method also comprises a step five, which specifically comprises the following substeps:
s51, acquiring the slope of each lead-acid storage battery;
s52, charging each lead-acid storage battery according to the slope of each lead-acid storage battery:
when the slope Ke of the lead-acid storage battery e is smaller than zero and smaller than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a first capacity interval;
when the slope Ke of the lead-acid storage battery e is greater than or equal to zero, the charging capacity of the lead-acid storage battery e is a second capacity interval;
when the slope Ke of the lead-acid storage battery e is smaller than zero and larger than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a third capacity interval;
wherein the first capacity interval is smaller than the second capacity interval, and the second capacity interval is smaller than the third capacity interval.
Example 2
Based on the above embodiment, the residual capacity prediction model in this embodiment is:
S＝aU 2 +bU+c，U≥U 0 ；
S＝dU+e，U≤U 0
wherein, the residual capacity of the S lead-acid storage battery; u (U) 0 Represents the predicted inflection voltage of the lead-acid storage battery, U represents the rebound voltage of the lead-acid storage battery, a, b, c, d and e are to be quantified, wherein U is as follows 0 And a, b, c, d, e are determined according to experimental data fitting curves.
Example 3
The embodiment provides a system for predicting the residual capacity of a lead-acid storage battery of a direct-current system, which is used for realizing the method for predicting the residual capacity of the lead-acid storage battery of the direct-current system, which is described in the embodiment 1; comprising the following steps:
the first acquisition module is used for enabling the lead-acid storage battery pack to discharge for the first time in a floating charge running state, acquiring terminal voltage of each lead-acid storage battery and determining the lead-acid storage battery with the minimum capacity;
the second acquisition module is used for determining discharge time t according to the minimum capacity lead-acid storage battery, so that the lead-acid storage battery is assembled into the direct current system to perform secondary discharge, and the discharge time is t; collecting an operation data set of each lead-acid storage battery;
the correction module is used for inputting the operation data set of the lead-acid storage battery into the constructed residual capacity prediction model and carrying out parameter correction on the residual capacity prediction model;
and the prediction module is used for predicting the residual capacity of the lead-acid storage battery at the moment T based on the residual capacity prediction model after parameter correction.
Example 4
The present embodiment provides a computer-readable medium having stored thereon a computer program that is executed by a processor to implement a method of predicting the remaining capacity of a lead-acid battery of a direct current system as in embodiment 1.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The method for predicting the residual capacity of the lead-acid storage battery of the direct-current system is characterized by comprising the following steps:
step one: the lead-acid storage battery pack is subjected to first discharging in a floating charge running state, terminal voltage of each lead-acid storage battery is collected, and the lead-acid storage battery with the minimum capacity is determined;
step two: determining discharge time t according to the minimum capacity lead-acid storage battery, and enabling the lead-acid storage battery to be assembled into a direct current system to perform secondary discharge, wherein the discharge time is t; collecting an operation data set of each lead-acid storage battery;
step three: inputting the operation data set of the lead-acid storage battery into a constructed residual capacity prediction model, and carrying out parameter correction on the residual capacity prediction model;
step four: and predicting the residual capacity of the lead-acid storage battery at the future moment based on the residual capacity prediction model after parameter correction.
2. The method for predicting the remaining capacity of a lead-acid battery of a direct current system according to claim 1, wherein the step of discharging the lead-acid battery pack for the first time in a floating charge operation state, collecting terminal voltages of the respective lead-acid batteries and determining a minimum terminal voltage lead-acid battery comprises the steps of:
t1, discharging the lead-acid storage battery pack in a floating charge running state at the ith moment, and collecting terminal voltage U of each lead-acid storage battery i ＝{U i1 ,U i2 ,…,U in -a }; n represents the total number of lead-acid batteries; collecting terminal voltage U of each lead-acid storage battery at j=i+1 time j ＝{U j1 ,U j2 ,…,U jn }；
T2, calculating the slope of each lead-acid storage battery by taking the terminal voltage of the lead-acid storage battery as an ordinate and the acquisition time as an abscissa; and terminal voltage U of each lead-acid battery j ＝{U j1 ,U j2 ,…,U jn Sequencing from small to large to obtain a terminal voltage sequence;
t3, starting from the minimum terminal voltage in the terminal voltage sequence, judging the slope K of the current minimum terminal voltage: if K is greater than or equal to zero, discarding the minimum terminal voltage, taking the second minimum terminal voltage as the minimum terminal voltage, and returning to the step T3; if K is smaller than zero, entering a step T4;
t4, judging whether the slope K is smaller than the slope threshold K y If so, the lead-acid storage battery corresponding to the slope K is the lead-acid storage battery with the minimum capacity; otherwise, the minimum terminal voltage is discarded, the second smallest terminal voltage is taken as the minimum terminal voltage, and the process returns to the step T3.
3. The method for predicting the residual capacity of a lead-acid storage battery of a direct current system according to claim 2, wherein the discharge time t is determined according to the minimum capacity lead-acid storage battery, so that the lead-acid storage battery is assembled into the direct current system to perform the second discharge, and the discharge time is t; the method comprises the following steps:
leading the lead-acid storage battery to be assembled into a direct current system for secondary discharge;
collecting terminal voltage of each lead-acid storage battery in real time, and when the terminal voltage of the lead-acid storage battery with the minimum capacity is U m Ending the second discharge, U m ＝80％U jmin ,U jmin Is of minimum capacityTerminal voltage at j-th moment when lead-acid battery is discharged for the first time.
4. The method for predicting the remaining capacity of a lead-acid battery of a direct current system according to claim 2, wherein the operation data set of each lead-acid battery includes lead-acid battery terminal voltages U1, U2, …, UL corresponding to discharge times t1, t2, … tL.
5. The method for predicting the residual capacity of a lead-acid storage battery of a direct current system according to claim 4, wherein the constructed residual capacity prediction model is as follows:
wherein, the residual capacity of the S lead-acid storage battery; s is S n Indicating the rated capacity of a lead-acid battery, t n Indicating the end voltage of the lead-acid storage battery as U n The discharge time for discharging the rated capacity is determined according to the following equation:
x, y and z represent a first correction parameter, a second correction parameter and a third correction parameter, respectively, and t represents a discharge time.
6. The method for predicting the residual capacity of a lead-acid battery of a direct current system according to claim 5, wherein the step of inputting the operation data set of the lead-acid battery into the constructed residual capacity prediction model and performing parameter correction on the residual capacity prediction model comprises the steps of:
s1, dividing an operation data set of a lead-acid storage battery into f groups with every three groups, wherein f=L/3;
s2, dividing the f-group operation data set into a calculation group and b verification groups, wherein a+b=f; and inputting a calculation groups into the following formula:
calculating a first correction parameter, a second correction parameter and a third correction parameter set, and substituting the average value of the a first correction parameters, the average value of the second correction parameters and the average value of the third correction parameters into a residual capacity prediction model;
and S3, inputting the b verification groups into the residual capacity prediction model obtained in the S2, and verifying the accuracy of the current residual capacity prediction model by using root mean square error and goodness of fit.
7. The method for predicting the remaining capacity of a lead-acid battery of a direct current system according to claim 6, wherein the root mean square error E is expressed as:
the goodness of fit D is expressed as:
wherein U 'is' t Representing the measured value and the predicted value of the terminal voltage of the lead-acid storage battery of the t group, U' t ' represents the average of the measured values of the terminal voltages of the lead-acid batteries in the b verification groups.
8. The method for predicting the remaining capacity of a lead-acid battery of a direct current system according to claim 2, further comprising the steps of:
s51, acquiring the slope of each lead-acid storage battery;
s52, charging each lead-acid storage battery according to the slope of each lead-acid storage battery:
when the slope Ke of the lead-acid storage battery e is smaller than zero and smaller than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a first capacity interval;
when the slope Ke of the lead-acid storage battery e is greater than or equal to zero, the charging capacity of the lead-acid storage battery e is a second capacity interval;
when the slope Ke of the lead-acid storage battery e is smaller than zero and larger than the slope threshold K y When the charging capacity of the lead-acid storage battery e is a third capacity interval;
wherein the first capacity interval is smaller than the second capacity interval, and the second capacity interval is smaller than the third capacity interval.
9. A system for predicting the remaining capacity of a lead-acid battery of a direct current system, characterized by being used for realizing the method for predicting the remaining capacity of the lead-acid battery of the direct current system according to any one of claims 1 to 8; comprising the following steps:
the first acquisition module is used for enabling the lead-acid storage battery pack to discharge for the first time in a floating charge running state, acquiring terminal voltage of each lead-acid storage battery and determining the lead-acid storage battery with the minimum capacity;
the second acquisition module is used for determining discharge time t according to the minimum capacity lead-acid storage battery, so that the lead-acid storage battery is assembled into the direct current system to perform secondary discharge, and the discharge time is t; collecting an operation data set of each lead-acid storage battery;
the correction module is used for inputting the operation data set of the lead-acid storage battery into the constructed residual capacity prediction model and carrying out parameter correction on the residual capacity prediction model;
and the prediction module is used for predicting the residual capacity of the lead-acid storage battery at the moment T based on the residual capacity prediction model after parameter correction.
10. A computer readable medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the method of predicting the remaining capacity of a lead-acid battery of a direct current system as claimed in any one of claims 1 to 8.
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