CN112630666B - Storage battery test scheduling method and device - Google Patents
Storage battery test scheduling method and device Download PDFInfo
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- CN112630666B CN112630666B CN201910950899.6A CN201910950899A CN112630666B CN 112630666 B CN112630666 B CN 112630666B CN 201910950899 A CN201910950899 A CN 201910950899A CN 112630666 B CN112630666 B CN 112630666B
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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
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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
Abstract
The invention discloses a storage battery test scheduling method and a device, wherein the method comprises the following steps: obtaining the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested, determining the first performance of the storage battery to be tested according to the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested, determining the second performance of the storage battery to be tested through a pre-established first scheduling model according to the first performance and the first attribute set of the storage battery to be tested, and scheduling the storage battery to be tested through a fuzzy comprehensive evaluation method according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested. By utilizing the invention, reasonable arrangement can be carried out according to the test urgency, the fault storage battery can be found in time, the waste of test resources is avoided, and the test efficiency is improved.
Description
Technical Field
The invention relates to the technical field of storage battery testing, in particular to a storage battery testing scheduling method and device, electronic equipment and a storage medium.
Background
With the continuous development of internet communication technology, a communication machine room is widely established in different regions, and stable signals are provided for daily mobile phone communication.
At present, the situation of power failure of the commercial power for supplying power to the communication machine room is likely to occur, in order to ensure the stability and continuity of the mobile phone communication signals, a storage battery is usually installed in the communication machine room, and when the situation of power failure of the commercial power occurs, the storage battery is started to continuously supply power to the communication machine room.
Further, in order to ensure that the storage battery can be in a normal working state after the mains supply fails, the storage battery installed in each machine room needs to be tested periodically so as to ensure that the storage battery can work normally.
In practical application, since the number of the machine rooms is large, it is impossible to test the storage batteries in all the machine rooms at the same time, so that the storage batteries in the communication machine rooms need to be tested for a period, that is, it is required to determine which storage battery in which machine room is tested first, and then which storage battery in which machine room is tested.
In the prior art, the test schedule of the storage battery in the communication machine room mainly depends on the area where the storage battery belongs and the previous discharge time (including active discharge and passive discharge) of the storage battery, and the specific flow is as follows:
the test personnel randomly select a storage battery of an area for testing, take Ningbo as an example, there are 10 county areas of state, sea-water, jiangbei, voyage, zhenhai, north Lei, cixi, yuyao, ninghai and Xiangshan, the implementation personnel randomly select an area from the 10 areas before starting the test, the storage battery with the previous discharge time interval less than T is removed in the area, the rest storage batteries obtain a plurality of clusters according to the polymerization degree according to the position of a machine room, one cluster is randomly selected, and all the storage batteries in the cluster are randomly tested one by one.
Obviously, the existing storage battery test schedule has very large randomness, is irregular and can be circulated, the storage battery which needs to be tested urgently cannot be tested in time, the early test is not carried out, the waste of test resources can be caused, the fault battery cannot be found timely, and the test efficiency is low.
Disclosure of Invention
The present invention has been made in view of the above problems, and provides a battery test scheduling method and apparatus, an electronic device, and a storage medium that overcome or at least partially solve the above problems.
According to one aspect of the invention, a battery test scheduling method includes:
acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of a storage battery to be tested;
determining a first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and a preset theoretical discharge capacity;
determining a second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
and according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, scheduling the storage battery to be tested by a fuzzy comprehensive evaluation method.
According to another aspect of the present invention, there is provided a battery test scheduling apparatus, the apparatus comprising:
the acquisition module is used for acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested;
a first determining module, configured to determine a first performance of the storage battery to be tested according to an actual discharge amount of the storage battery to be tested and a predetermined theoretical discharge amount;
the second determining module is used for determining the second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
and the scheduling module is used for scheduling the storage battery to be tested through a fuzzy comprehensive evaluation method according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested.
According to another aspect of the present invention, there is provided an electronic apparatus including: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to hold at least one executable instruction that causes the processor to:
Acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of a storage battery to be tested;
determining a first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and a preset theoretical discharge capacity;
determining a second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
and according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, scheduling the storage battery to be tested by a fuzzy comprehensive evaluation method.
According to yet another aspect of the present invention, there is provided a storage medium having stored therein at least one executable instruction for causing a processor to:
acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of a storage battery to be tested;
determining a first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and a preset theoretical discharge capacity;
determining a second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
And according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, scheduling the storage battery to be tested by a fuzzy comprehensive evaluation method.
The invention provides a storage battery test scheduling method and a storage battery test scheduling device, wherein the method comprises the following steps: obtaining the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested, determining the first performance of the storage battery to be tested according to the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested, determining the second performance of the storage battery to be tested through a pre-established first scheduling model according to the first performance and the first attribute set of the storage battery to be tested, and scheduling the storage battery to be tested through a fuzzy comprehensive evaluation method according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested. By utilizing the invention, reasonable arrangement can be carried out according to the test urgency, the fault storage battery can be found in time, the waste of test resources is avoided, and the test efficiency is improved.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 illustrates a flow chart of a battery test scheduling method according to one embodiment of the invention;
FIG. 2 illustrates a schematic diagram of a battery discharging process according to one embodiment of the present invention;
FIG. 3 is a schematic diagram showing current of a battery as a function of time according to one embodiment of the invention;
FIG. 4 illustrates a schematic diagram of a battery test scheduling apparatus according to one embodiment of the invention;
fig. 5 shows a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Fig. 1 shows a flowchart of a battery test scheduling method according to an embodiment of the present invention. As shown in fig. 1, the method comprises the steps of:
s101: and acquiring the actual discharge amount and the predetermined theoretical discharge amount of the storage battery to be tested.
In practical application, in order to ensure that the storage battery can be in a normal working state after the mains supply fails, the storage battery installed in each machine room needs to be periodically tested so as to ensure that the storage battery can work normally.
Further, since the number of the machine rooms is large, it is impossible to test the storage batteries in all the machine rooms at the same time, so that it is necessary to test the storage batteries in the communication machine rooms, that is, to determine which of the storage batteries in the machine rooms is tested first, and then which of the storage batteries in the machine rooms is tested.
Further, in the embodiment of the present disclosure, during the test scheduling of the storage battery in the communication machine room, the actual discharge amount and the predetermined theoretical discharge amount of the storage battery to be tested need to be obtained first.
The actual discharge capacity refers to the electric quantity released by the storage battery in the actual discharge process; the theoretical discharge amount is an amount of electricity discharged during discharge of the battery from a theoretical point of view (i.e., an idealized point of view).
In addition, the discharging process of the storage battery is that the floating charge voltage of the storage battery is reduced to the cut-off voltage, and different voltage and current values are generated at each moment in the discharging process. As shown in fig. 2, the voltage in the discharging process of the storage battery is reduced from V to V, the duration of the discharging is T, and the voltage values collected by the system at the moments T1 and T2 are (V1, I1), (V2, I2).
The embodiment of the specification provides an implementation mode for determining the theoretical discharge amount, which is specifically as follows:
collecting a discharge data set of each storage battery to be tested, determining a functional relation between the current and the time of the storage battery to be tested according to the discharge data set, selecting a functional relation between the current and the time of one storage battery to be tested, determining a root mean square error between the selected functional relation and the functional relation between the current and the time of the rest storage batteries to be tested, and determining the theoretical discharge capacity according to the functional relation between the current and the time of the storage battery to be tested with the minimum root mean square error.
It should be noted that, the discharge data set of each battery to be tested is specifically that the data acquisition period in the discharge process of each battery to be tested is Δt, and the data set acquired by the i-th battery in the whole discharge process is ((V) i0 、I i0 、T 0 )、(V iΔt 、I iΔt 、T iΔt )、...(V imΔt 、I imΔt 、T imΔt ) Where mΔt.gtoreq.T i stop And (m-1) Δt<T i stop The method comprises the steps of carrying out a first treatment on the surface of the According to the discharging dataset, determining a functional relation between the current and the time of the storage battery to be tested, specifically, fitting data of (T, I) in the discharging process of the storage battery to be tested, as shown in fig. 3, to obtain a functional relation between the current and the time of the storage battery to be tested, i=f (T), and finally obtaining a relation function set of a plurality of storage batteries to be tested as (f) 1 (T)、f 2 (T)、...、f n (T)); selecting a functional relation between the current and time of a storage battery to be tested, and determining the root mean square error between the selected functional relation and the other functional relations between the current and time of the storage battery to be tested, specifically, by a certain relation function f in a relation function set i Based on (T), the root mean square error of the current values of the relation function and the remaining n-1 functions at m+1 times T (0, Δt, 2Δt..m Δt.)The root mean square error set of the plurality of batteries to be tested is g= (G) 1 、g 2 、...g n ) The method comprises the steps of carrying out a first treatment on the surface of the According to the functional relation between the current and time of the storage battery to be tested with minimum root mean square error, determining the theoretical discharge amount, namely selecting the storage battery with the minimum value in the set G as a first optimal standard function I=f i (T) and g i ＝g min And determining the theoretical discharge capacity according to the optimal standard function.
It should also be noted that when a new battery needs to be tested, the optimal standard function needs to be determined in the same manner as described above.
S102: and determining the first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and the preset theoretical discharge capacity.
In this embodiment of the present disclosure, after the actual discharge amount and the predetermined theoretical discharge amount of the battery to be tested are obtained, the first performance of the battery to be tested needs to be determined according to the actual discharge amount and the predetermined theoretical discharge amount of the battery to be tested.
Since the capacitance C (unit AH) is a unit for measuring the capacity of the battery device and is an important index of the battery performance, the calculation formula is c=it, and therefore, in the embodiment of the present specification, the first performance is specifically reflected by the capacitance, and the calculation formula is thatWherein C is i actual Refers to the actual discharge capacity of the storage battery to be tested, C i theory of Referring to the theoretical discharge amount, α represents the first performance of the battery, and the closer α is to 1, the better the performance of the battery.
It should be noted that the specific meaning of the above formula is: and determining the sum of the ratios between the actual discharge capacity of the storage battery to be tested and the preset theoretical discharge capacity at each acquisition time, and determining the ratio between the actual discharge capacity of the storage battery to be tested and the preset theoretical discharge capacity and the number of the acquisition time as the first performance of the storage battery to be tested.
It is also noted here that C i theory of The theoretical discharge capacity is obtained by applying the optimal standard function calculated in the previous step, and the theoretical discharge capacity of the storage battery at the moment TThe theoretical discharge capacity at each data acquisition time was (C Deltat theory 、C 2 Deltat theory 、…、C m deltat theory )；C i actual In particular, the discharge capacity is obtained during the actual discharge of the accumulator, i.e., the actual discharge capacity is (C Deltat actual 、C 2 Deltat actual 、…、C mDeltat actual )＝(I Δt *Δt、I 2Δt *2Δt、…、I mΔt *mΔt)。
S103: and determining the second performance of the storage battery to be tested through a pre-established first scheduling model according to the first performance and the first attribute set of the storage battery to be tested.
In practical application, as the battery capacity of the battery in the machine room can be observed and analyzed for a long time, the 4 parameters including the internal resistance, the rising maximum voltage, the floating charge voltage and the temperature of the battery can reflect the performance condition of the battery to the greatest extent, and particularly, when the battery works, the resistance of the charge through the inside of the battery is the internal resistance of the battery. As the service life of the storage battery increases, the internal resistance of the storage battery gradually increases, and the capacity of the storage battery decreases. Under the normal condition of alternating current, the rectifier is floated to charge the storage battery while supplying power to the load. If a single battery is in an overvoltage or undervoltage state for a long time, the service life of the battery can be seriously shortened, and the performance of the storage battery pack is further influenced. The storage battery is sensitive to temperature, and the change of the temperature has influence on discharge capacity, service life, internal resistance and floating charge voltage. When the battery is in a high-temperature or low-temperature environment for a long period of time, the performance can be cracked sharply. The battery in full charge state will drop to a certain value at initial stage of discharging, then rise to another higher voltage value, the process is a steep drop and rise again stage, under the same precondition, the lower the maximum voltage of rise again, the lower the residual capacity of the battery.
Therefore, in the embodiment of the present disclosure, in order to more accurately determine the performance of the battery to be tested, after determining the first performance of the battery to be tested, the four parameters that reflect the performance conditions of the battery to be tested may be combined to further determine the performance of the battery to be tested, that is, according to the first performance and the first attribute set of the battery to be tested, the second performance of the battery to be tested, that is, the actual performance of the battery to be tested, is determined through a first scheduling model established in advance.
It should be noted that the first attribute set includes: internal resistance of the storage battery, re-rising highest voltage, floating charge voltage and temperature of the storage battery.
Further, since the second performance of the battery to be tested needs to be determined by the first scheduling model that is established in advance, in the embodiment of the present disclosure, the first scheduling module needs to be established in advance before the second performance of the battery to be tested is determined by the first scheduling model that is established in advance according to the first performance and the first attribute set of the battery to be tested.
Specifically, historical first performance data, historical first attribute set data, historical second performance data and a to-be-built scheduling model of the storage battery are obtained, the to-be-built scheduling model is initialized, the historical first performance data and the historical first attribute set data are used as inputs, the historical second performance data are used as outputs, and the initialized to-be-built scheduling model is trained to obtain the first scheduling model.
The following provides a more detailed implementation procedure for establishing the first scheduling module:
a. collecting 5 types of historical operation data (namely, first performance, internal resistance of the storage battery, re-rising highest voltage, floating charge voltage and temperature of the storage battery) of a large number of storage batteries, and establishing a data sample library;
b. data preprocessing, namely modeling sample data, and generating an input set of a network (the input set of the system is first performance, internal resistance of a storage battery, maximum voltage of a re-rise, floating charge voltage and temperature of the storage battery), and a target output set (the output set of the system is accurate actual performance of the storage battery, namely second performance);
c. constructing a neural network model, and setting network parameters (the number of input nodes, the number of hidden layer neural network elements, the number of output nodes, a weight adjustment function, a network performance index and the like);
d. training the network, learning the input sample data, searching the rule hidden in the data, and enabling the output value of the network to be as close to the true value as possible.
e. Training to obtain a learning network model.
S104: and according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, scheduling the storage battery to be tested by a fuzzy comprehensive evaluation method.
In the embodiment of the present specification, after obtaining the second performance of the battery to be tested, the battery to be tested needs to be ranked according to the second performance of the battery to be tested.
Further, in practical application, the factors affecting the test schedule of the storage battery in the machine room are found through detailed analysis and include: the second performance of the battery to be tested, the previous time interval of discharging, the deep discharge history performance, the shallow discharge history performance, the power failure, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the number of batteries, so that the storage battery to be tested is scheduled according to the second performance of the storage battery to be tested, specifically, the storage battery to be tested is scheduled according to the second performance of the storage battery to be tested and the second attribute set, wherein the second attribute set comprises: the previous discharge time interval, the deep discharge history performance, the shallow discharge history performance, the power failure fault, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the quantity of the storage battery.
Further, in the embodiment of the present disclosure, the scheduling of the storage battery to be tested according to the second performance and the second attribute set of the storage battery to be tested may perform the scheduling of the storage battery to be tested according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested by a fuzzy comprehensive evaluation method.
Specifically, classifying the second performance and the second attribute set of the storage battery to be tested, determining at least one evaluation factor set, determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set for each evaluation factor set, determining a fuzzy matrix corresponding to the storage battery to be tested according to the evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set, acquiring the weight of each evaluation factor in the evaluation factor set, determining a first ranking value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested, and ranking the storage battery to be tested according to the first ranking value, the second performance and the third attribute set corresponding to the storage battery to be tested.
It should be noted that, the second performance and the second attribute set of the to-be-tested storage battery are classified, and the at least one evaluation factor set is determined specifically by classifying according to the influence degree of the elements on the performance of the storage battery, where the twelve elements directly or indirectly reflect the performance health degree of the storage battery, and are classified into three types according to the influence degree:
the main factors include the second performance of the last test battery, the time interval of previous discharge to date, the deep discharge history performance, the shallow discharge history performance. For example, the worse the last test cell performance, the more prioritized the test is; the greater the last time period, the more prioritized the test is.
Secondary factors include power failure, station attributes where the battery is located, battery capacity attributes, charge and discharge times, and charge and discharge frequency. For example, the more power failure, the more important the site attributes (Z Core(s) >Z Backbone >Z Convergence >Z Node >Z Access to a wireless communication system ) The more the number of charge and discharge, the higher the charge and discharge frequency, etc., the more preferably the battery is tested.
Accessory influencing factors include machine room environment (temperature and humidity, geographical position of the machine room, and the like), load current and battery number. Such as the worse the machine room environment, the greater the number of batteries, etc., the more preferably the test is scheduled. Weights of three kinds of elements Is w 1 、w 2 、w 3 And satisfy w 1 >w 2 >w 3 ,w 1 +w 2 +w 3 ＝1。
In the present embodiment, the evaluation factor set of m factors is expressed as u= { U 1 ,u 2 ,...,u m Therefore, in the present invention, the element u corresponds to the second performance of the last-time test battery, the previous time interval of discharge, the deep discharge history performance, the shallow discharge history performance, respectively; the second element u' corresponds to a power failure fault, a station attribute of the storage battery, a capacity attribute of the storage battery, charge and discharge times and charge and discharge frequency respectively; the three types of elements u' respectively correspond to the machine room environment, the load current and the battery number.
Determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set according to each evaluation factor value set of the storage battery to be tested under the evaluation factors in the evaluation factor set, determining a fuzzy matrix corresponding to the storage battery to be tested, acquiring the weight of each evaluation factor in the evaluation factor set, and determining a first scheduling value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested, wherein the n evaluation factor value sets are expressed as V= { V 1 ,v 2 ,...,v n In the invention, v can respectively correspond to extremely high priority, moderate priority, low priority and extremely low priority. If r is used ij And expressing the membership degree of the ith factor to the jth comment, wherein the fuzzy relation between the evaluation factor set and the evaluation factor value set can be expressed by an evaluation matrix. For example, the experts evaluate factors affecting the battery test schedule for the second performance u of the last tested battery 1 70% of people are considered to have very high priority, 20% are considered to have high priority, 5% are considered to have moderate priority, 4% are considered to have low priority, 1% are considered to have very low priority, then u 1 Single evaluation factor evaluation vector R of (2) 1 = {0.7,0.2,0.05,0.04,0.01}, i.e. the first column of R. R is obtained by the same method 2 、R 3 、...、R m 。
Wherein: r is 0 to or less ij ＝μ R (u i ,v j )≤1,i＝1,2,...,m；j＝1,2,...,n；
Before evaluation, the importance of the evaluator to the various evaluation factors, i.e., the weight of each evaluation factor, should be considered as a fuzzy subset a= (a) of the evaluation factor set U 1 a 2 ...a m ),0≤a i Not more than 1, i=1, 2,..m, where ai is the weight occupied by the i-th evaluation factor, the mathematical model of the fuzzy comprehensive judgment is then
Wherein:representing a fuzzy operator;
different definitions of fuzzy operators are adopted, and four different fuzzy comprehensive judgment models are corresponding. In determining whether a certain battery is the subject of the priority test, the factors are comprehensively considered, so a weighted average model is selected, wherein
By passing throughThe calculated scheduling value is (b) 1 b 2 ... b n ) Indicating the level of test schedule priority for each battery, b i The larger the battery, the earlier the battery is tested.
Therefore, the test schedule value obtained by the n groups of storage batteries respectively considering only one type, two types and three types of factors is (b) 1 、b 2 、...、b n )、(b' 1 、b' 2 、...、b' n )、(b″ 1 、b″ 2 、...、b″ n ). The first test schedule value of the battery is b '' i ＝b i *w 1 +b' i *w 2 +b″ i w 3 The storage battery test scheduling value reflects the sequence degree of the storage battery test scheduling, and the higher the scheduling value is, the higher the test is.
In this embodiment, after the first scheduling value is determined, in order to further accurately determine the test scheduling of the storage battery, the storage battery to be tested may be scheduled according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested, where the third attribute set includes the previous time interval of the previous discharge, the deep discharge history performance, the shallow discharge history performance, the power failure, the storage battery capacity attribute, the charge/discharge frequency and the charge/discharge frequency.
Specifically, according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested, the second scheduling value corresponding to the storage battery to be tested is determined through a second scheduling model established in advance, the test scheduling value of each storage battery to be tested is finally obtained, and intelligent scheduling is performed on the storage battery to be tested according to the second scheduling value corresponding to the storage battery to be tested.
It should be noted that, the training process of the second scheduling model is identical to the training process of the first scheduling model, and only the training sample sets are different, which is not described in detail herein.
By the method, reasonable scheduling can be performed according to the test urgency, the fault storage battery can be found timely, waste of test resources is avoided, and the test efficiency is improved.
In addition, the embodiments of the present specification can provide the following advantages:
1. the accuracy of the battery performance judgment is improved by adopting the algorithm based on the scheduling model, and the problems that the battery with good performance is misjudged as a fault battery and the fault battery is misjudged as a battery with good performance due to poor recognition of the traditional scheme are solved.
2. In the aspect of intelligent recommendation of the storage battery, the invention combines the time interval, the deep discharge history performance, the shallow discharge history performance, the power failure fault, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the quantity of the battery, and can reasonably schedule according to the testing urgency degree by a dynamic recommendation algorithm based on element priority, thereby avoiding the defects of high randomness of the traditional scheme, low testing efficiency, incapability of timely detecting the fault battery and the like of the traditional scheme.
3. The application is not only applied to the test arrangement of the storage battery of the communication machine room, but also is applicable to the test arrangement of the battery of the government unit IDC machine room like bank IDC machine room, public security and the like, and has good universality and wide application prospect.
The foregoing is a method for testing and scheduling a storage battery according to an embodiment of the present application, based on which, an embodiment of the present application provides a device for testing and scheduling a storage battery, as shown in fig. 4, the device includes:
an obtaining module 401, configured to obtain an actual discharge amount and a predetermined theoretical discharge amount of a storage battery to be tested;
a first determining module 402, configured to determine a first performance of the battery to be tested according to an actual discharge amount of the battery to be tested and a predetermined theoretical discharge amount;
a second determining module 403, configured to determine, according to the first performance and the first attribute set of the to-be-tested storage battery, a second performance of the to-be-tested storage battery through a first scheduling model that is established in advance;
and the scheduling module 404 is configured to schedule the storage battery to be tested according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested by using a fuzzy comprehensive evaluation method.
The apparatus further comprises:
a third determining module 405, configured to collect a discharge data set of each storage battery to be tested; for each storage battery to be tested, determining a functional relation between the current and time of the storage battery to be tested according to the discharge data set; selecting a functional relation between the current of the storage battery to be tested and time, and determining the root mean square error between the selected functional relation and the functional relation between the current of the rest storage batteries to be tested and time; and determining the theoretical discharge capacity according to a functional relation between the current and time of the storage battery to be tested with the minimum root mean square error.
The first determining module 402 is specifically configured to determine a sum of a ratio between an actual discharge amount of the storage battery to be tested and a predetermined theoretical discharge amount at each collection time; determining the ratio of the sum of the ratio of the actual discharge capacity of the storage battery to be tested to the preset theoretical discharge capacity at each acquisition time to the number of the acquisition times; and determining the ratio of the storage battery to the number of the acquisition moments as the first performance of the storage battery to be tested.
The first set of attributes includes: internal resistance of the storage battery, re-rising highest voltage, floating charge voltage and temperature of the storage battery.
The apparatus further comprises:
a building module 406, configured to obtain historical first performance data, historical first attribute set data, historical second performance data, and a scheduling model to be built of the storage battery; initializing a scheduling model to be established; and taking the historical first performance data and the historical first attribute set data as input, taking the historical second performance data as output, and training the initialized scheduling model to be built to obtain a first scheduling model.
The second set of attributes includes: the time interval from the previous discharge to the present, the deep discharge history performance, the shallow discharge history performance, the power failure fault, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the number of the batteries;
the scheduling module 404 is specifically configured to classify the second performance and the second attribute set of the battery to be tested, and determine at least one evaluation factor set; determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set aiming at each evaluation factor set; determining a fuzzy matrix corresponding to the storage battery to be tested according to an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set; acquiring the weight of each evaluation factor in the evaluation factor set; determining a first scheduling value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested; and according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
The third attribute set comprises the time interval, the deep discharge history performance, the shallow discharge history performance, the power failure, the storage battery capacity attribute, the charge and discharge times and the charge and discharge frequency of the previous discharge;
the scheduling module 404 is further configured to determine, according to the first scheduling value, the second performance, and the third attribute set corresponding to the storage battery to be tested, a second scheduling value corresponding to the storage battery to be tested through a second scheduling model that is established in advance; and according to the second scheduling value corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
The embodiment of the application also provides a non-volatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the storage battery test scheduling method in any of the method embodiments.
Fig. 5 shows a schematic structural diagram of an electronic device according to an embodiment of the present application, and the embodiment of the present application is not limited to the specific implementation of the electronic device.
As shown in fig. 5, the server may include: a processor 502, a communication interface (Communications Interface) 504, a memory 506, and a communication bus 508.
Wherein:
processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508.
A communication interface 504 for communicating with network elements of other devices, such as clients or other servers.
The processor 502 is configured to execute the program 510, and may specifically perform relevant steps in the above-described battery test scheduling method embodiment.
In particular, program 510 may include program code including computer-operating instructions.
The processor 502 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the electronic device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 506 for storing a program 510. Memory 506 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 510 may be specifically operable to cause the processor 502 to:
Acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of a storage battery to be tested;
determining a first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and a preset theoretical discharge capacity;
determining a second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
and according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, scheduling the storage battery to be tested by a fuzzy comprehensive evaluation method.
Optionally, the program 510 may also be operative to cause the processor 502 to:
collecting a discharge data set of each storage battery to be tested; for each storage battery to be tested, determining a functional relation between the current and time of the storage battery to be tested according to the discharge data set; selecting a functional relation between the current of the storage battery to be tested and time, and determining the root mean square error between the selected functional relation and the functional relation between the current of the rest storage batteries to be tested and time; and determining the theoretical discharge capacity according to a functional relation between the current and time of the storage battery to be tested with the minimum root mean square error.
Optionally, the program 510 may also be operative to cause the processor 502 to:
determining the sum of the ratio between the actual discharge capacity of the storage battery to be tested and the preset theoretical discharge capacity at each acquisition moment; determining the ratio of the sum of the ratio of the actual discharge capacity of the storage battery to be tested to the preset theoretical discharge capacity at each acquisition time to the number of the acquisition times; and determining the ratio of the storage battery to the number of the acquisition moments as the first performance of the storage battery to be tested.
Optionally, the program 510 may also be operative to cause the processor 502 to:
the first set of attributes includes: internal resistance of the storage battery, re-rising highest voltage, floating charge voltage and temperature of the storage battery.
Optionally, the program 510 may also be operative to cause the processor 502 to:
acquiring historical first performance data, historical first attribute set data, historical second performance data and a scheduling model to be established of the storage battery; initializing a scheduling model to be established; and taking the historical first performance data and the historical first attribute set data as input, taking the historical second performance data as output, and training the initialized scheduling model to be built to obtain a first scheduling model.
Optionally, the program 510 may also be operative to cause the processor 502 to:
the second set of attributes includes: the time interval from the previous discharge to the present, the deep discharge history performance, the shallow discharge history performance, the power failure fault, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the number of the batteries;
classifying the second performance and the second attribute set of the storage battery to be tested, and determining at least one evaluation factor set; determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set aiming at each evaluation factor set; determining a fuzzy matrix corresponding to the storage battery to be tested according to an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set; acquiring the weight of each evaluation factor in the evaluation factor set; determining a first scheduling value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested; and according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
Optionally, the program 510 may also be operative to cause the processor 502 to:
the third attribute set comprises the time interval, the deep discharge history performance, the shallow discharge history performance, the power failure, the storage battery capacity attribute, the charge and discharge times and the charge and discharge frequency of the previous discharge;
determining a second scheduling value corresponding to the storage battery to be tested through a second scheduling model established in advance according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested; and according to the second scheduling value corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, the present invention is not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some or all of the components in a battery test scheduling apparatus according to embodiments of the invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
Claims (9)
1. A battery test scheduling method, comprising:
acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of a storage battery to be tested;
determining a first performance of the storage battery to be tested according to the actual discharge capacity of the storage battery to be tested and a preset theoretical discharge capacity; the first performance is the ratio between the sum of the ratios of the actual discharge amount of the storage battery to be tested and the preset theoretical discharge amount at each acquisition time and the number of the acquisition times;
Determining a second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, the storage battery to be tested is subjected to scheduling by a fuzzy comprehensive evaluation method;
the method for establishing the first scheduling model specifically comprises the following steps of: acquiring historical first performance data, historical first attribute set data, historical second performance data and a scheduling model to be established of the storage battery; initializing a scheduling model to be established; taking the historical first performance data and the historical first attribute set data as input, taking the historical second performance data as output, and training the initialized scheduling model to be built to obtain a first scheduling model;
according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested, the storage battery to be tested is arranged by a fuzzy comprehensive evaluation method, and the method specifically comprises the following steps:
classifying the second performance and the second attribute set of the storage battery to be tested, and determining at least one evaluation factor set;
Determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set aiming at each evaluation factor set;
determining a fuzzy matrix corresponding to the storage battery to be tested according to an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set;
acquiring the weight of each evaluation factor in the evaluation factor set;
determining a first scheduling value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested;
determining a second scheduling value corresponding to the storage battery to be tested through a second scheduling model established in advance according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested; wherein the second scheduling model building process is consistent with the first scheduling model building process, and the training sample set of the second scheduling model is different from the training sample set of the first scheduling model;
and according to the second scheduling value corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
2. The method according to claim 1, determining a theoretical discharge amount, comprising in particular:
collecting a discharge data set of each storage battery to be tested;
for each storage battery to be tested, determining a functional relation between the current and time of the storage battery to be tested according to the discharge data set;
selecting a functional relation between the current of the storage battery to be tested and time, and determining the root mean square error between the selected functional relation and the functional relation between the current of the rest storage batteries to be tested and time;
and determining the theoretical discharge capacity according to a functional relation between the current and time of the storage battery to be tested with the minimum root mean square error.
3. The method according to claim 2, wherein determining the first performance of the battery to be tested according to the actual discharge amount of the battery to be tested and a predetermined theoretical discharge amount, comprises:
determining the sum of the ratio between the actual discharge capacity of the storage battery to be tested and the preset theoretical discharge capacity at each acquisition moment;
determining the ratio of the sum of the ratio of the actual discharge capacity of the storage battery to be tested to the preset theoretical discharge capacity at each acquisition time to the number of the acquisition times;
And determining the ratio of the storage battery to the number of the acquisition moments as the first performance of the storage battery to be tested.
4. The method of claim 1, the first set of attributes comprising: internal resistance of the storage battery, re-rising highest voltage, floating charge voltage and temperature of the storage battery.
5. The method of claim 1, the second set of attributes comprising: the previous discharge time interval, the deep discharge history performance, the shallow discharge history performance, the power failure fault, the station attribute of the storage battery, the capacity attribute of the storage battery, the charge and discharge times, the charge and discharge frequency, the temperature of the storage battery, the load current and the quantity of the storage battery.
6. The method of claim 1, the third set of attributes comprising time interval since last discharge, deep discharge history performance, shallow discharge history performance, power outage failure, battery capacity attribute, number of charge and discharge, and charge and discharge frequency.
7. A battery test scheduling apparatus comprising:
the acquisition module is used for acquiring the actual discharge capacity and the predetermined theoretical discharge capacity of the storage battery to be tested;
a first determining module, configured to determine a first performance of the storage battery to be tested according to an actual discharge amount of the storage battery to be tested and a predetermined theoretical discharge amount; the first performance is the ratio between the sum of the ratios of the actual discharge amount of the storage battery to be tested and the preset theoretical discharge amount at each acquisition time and the number of the acquisition times;
The second determining module is used for determining the second performance of the storage battery to be tested through a first scheduling model established in advance according to the first performance and the first attribute set of the storage battery to be tested;
the scheduling module is used for scheduling the storage battery to be tested through a fuzzy comprehensive evaluation method according to the second performance, the second attribute set and the third attribute set of the storage battery to be tested;
the method for establishing the first scheduling model specifically comprises the following steps of: acquiring historical first performance data, historical first attribute set data, historical second performance data and a scheduling model to be established of the storage battery; initializing a scheduling model to be established; taking the historical first performance data and the historical first attribute set data as input, taking the historical second performance data as output, and training the initialized scheduling model to be built to obtain a first scheduling model;
the scheduling module is further to:
classifying the second performance and the second attribute set of the storage battery to be tested, and determining at least one evaluation factor set;
determining an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set aiming at each evaluation factor set;
Determining a fuzzy matrix corresponding to the storage battery to be tested according to an evaluation factor value set of the storage battery to be tested under each evaluation factor in the evaluation factor set;
acquiring the weight of each evaluation factor in the evaluation factor set;
determining a first scheduling value corresponding to the storage battery to be tested according to the weight of each evaluation factor in the evaluation factor set and the fuzzy matrix corresponding to the storage battery to be tested;
determining a second scheduling value corresponding to the storage battery to be tested through a second scheduling model established in advance according to the first scheduling value, the second performance and the third attribute set corresponding to the storage battery to be tested; wherein the second scheduling model building process is consistent with the first scheduling model building process, and the training sample set of the second scheduling model is different from the training sample set of the first scheduling model;
and according to the second scheduling value corresponding to the storage battery to be tested, scheduling the storage battery to be tested.
8. An electronic device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
The memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the battery test scheduling method of any one of claims 1-6.
9. A storage medium having stored therein at least one executable instruction that causes a processor to perform operations corresponding to the battery test scheduling method of any one of claims 1-6.
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