CN105807231A - Method and system for storage battery residual capacity detection - Google Patents

Abstract

The invention provides a method for storage battery residual capacity detection. The method comprises the steps of: extracting a plurality of samples from historical data of storage batteries, wherein each sample is data formed by characteristic items including electromotive force, internal resistance and the residual capacity; respectively introducing the extracted a plurality of samples into a preset fuzzy c-means cluster algorithm, carrying out clustering analysis, and obtaining a plurality of clustering central values which are corresponding data formed by the same characteristic items of the samples; determining that the residual capacity of the storage battery is decided by the electromotive force and the internal resistance, and according to the obtained a plurality of clustering central values, obtaining a linear function of the electromotive force and the internal resistance corresponding to the residual capacity; and obtaining the electromotive force and the internal resistance of the storage battery at present, importing the electromotive force and the internal resistance of the storage battery at present into the linear function, and outputting the residual capacity of the storage battery at present. According to the invention, no complex mathematical model is needed, the residual capacity of the storage battery can be detected on line in real time, time and labor are saved, and the working load of calculation is reduced.

Description

A kind of method and system for remaining battery capacity detection

Technical field

The present invention relates to ice storing time technical field, particularly relate to a kind of method for remaining battery capacity detection And system.

Background technology

The volume test of accumulator is affected by several factors, the most accurately measures the residual capacity of accumulator, makees The most not yet solve for a great problem, but carried out a lot of research both at home and abroad, mainly include the research side of following two big classes Method:

First kind method is the residual capacity being tested accumulator by physical modeling method.Main employing is put The several methods such as electric test method, ampere-hour integration method, open-circuit voltage method, densimetry, internal resistance method, but the several method of this class exists Shortcoming is: one, in discharge test method, it is impossible to real-time online is predicted, and need to interrupt battery work at present during test, time-consumingly consumes Power；Two, in ampere-hour integration method, during test, require that accumulator must demarcate state-of-charge initial value, needs accurately to calculate charge and discharge Electrical efficiency and accurately measure electric current, otherwise will result in SOC and calculates error, especially in the feelings that the condition of high temperature and current fluctuation are violent Under condition；Three, in open-circuit voltage method, during test, require that battery status is stable, but battery reach stably required time of repose without Method determines, declines along with cell degradation battery capacity simultaneously, but open circuit voltage variations is inconspicuous so that cannot Accurate Prediction residue Electricity, and the series battery that tradition is used, battery used has been in load state, typically cannot measure open-circuit voltage, On-line measurement can not be realized；Four, in densimetry, need high-precision dense volume sensor during test, but existing market On the trueness error of sensor bigger；Five, in internal resistance method, valve controlling sealed lead battery SOC 50% or 40% with Time upper, owing to internal resistance (or conductance) is not changed in substantially, so that test result is unreasonable, and simultaneously for capacity 80% The above valve controlling sealed lead battery of online use, it is impossible to remove the SOC of on-line checking accumulator according to internal resistance value.

Equations of The Second Kind method is to utilize system identification to judge the residual capacity of accumulator with parameter estimation modeling, i.e. from electric power storage The outside running parameter in pond is started with, the restriction of measurement data in love, using battery as one " black box ", by measuring battery The parameters such as running voltage, electric current, temperature, sum up certain rule and algorithm, simultaneously according to conventional data experience, by model meter Calculate or utilize intelligent algorithm that the residual capacity of accumulator is estimated.Conventional employing Kalman filtering method, fuzzy control With the several method such as neural network, although the several method peripheral parameter in this class is easily measured, and external parameter with Also there is between remaining battery capacity certain regularity, but the construction for mathematical model has the highest requirement.

Therefore, in order to solve the problem that above-mentioned two big class methods produce, need badly a kind of for remaining battery capacity detection Method, it is possible to reduce dependence to mathematical model, the residual capacity of accumulator can be detected by real-time online, and time saving and energy saving, Reduce the workload calculated.

Summary of the invention

Embodiment of the present invention technical problem to be solved is, it is provided that a kind of based on for remaining battery capacity detection Method and system, it is not necessary to set up complicated mathematical model, it is possible to real-time online detects the residual capacity of accumulator, and saves time Laborsaving, reduce the workload calculated.

In order to solve above-mentioned technical problem, embodiments provide a kind of side for remaining battery capacity detection Method, described method includes:

A, from the historical data of accumulator, extract multiple sample；Wherein, each sample standard deviation is electronic for being included by characteristic item The data that gesture, internal resistance and residual capacity are formed；

B, the multiple sample datas extracted all are introduced default Fuzzy C-Means Clustering Algorithm is carried out cluster point Analysis, obtains multiple cluster centre value with sample with same characteristic features item formation corresponding data；

C, determine that the residual capacity of accumulator is determined by electromotive force and internal resistance, and according to the described multiple cluster centres obtained Value, obtains being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

D, the electromotive force obtaining current accumulator and internal resistance, and by the electromotive force of the described current accumulator got and interior In the linear function obtained described in resistance importing, the value of output is the residual capacity of current accumulator.

Wherein, " historical data of accumulator " in described step a is by choosing the form of pulse charge and discharge to plumbic acid storage Battery carries out discharge and recharge and obtains.

Wherein, described step b specifically includes:

B1, algorithm initialization, set the classification number C (2≤C≤n) of cluster, cluster initial centered value P₀, FUZZY WEIGHTED refers to Number m=2, iteration variable l=0, iteration threshold are l_maxWith compare threshold epsilon；Wherein, n is the total number of the plurality of sample；

B2, the degree of membership Matrix dividing U of l+1 iteration of renewal_l+1, for i and k of any number, and if only if apart from model Number d_ikHave during more than zero:

$U_{ik}=\frac{1}{\underset{i=1}{\overset{c}{\Σ}}{\left(\frac{d_{ik}}{d_{jk}}\right)}^{2/(m-1)}}$

For i and r of any number, if making distance norm equal to zero, then there is u_ir=1；When j value is unequal with r Time have u_ij=0.

B3, update cluster centre value P of l+1 iteration by cluster centre computing formula_l+1, as follows:

$P_i=\frac{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m{x}_k}{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m}$

If b4 max | | P_i ^(l+1)-P_i ^(l)| | ＜ ε or iterations l is more than maximum iteration time l_max, stop immediately Computing, otherwise makes iterations l=l+1, is back to step b2 and continues computing；

B5, the degree of membership Matrix dividing U of last iteration and cluster centre value P are exported as parameter, obtain c with Sample has same characteristic features item and forms the cluster centre value of corresponding data.

Wherein, described step c particularly as follows:

Simulate the linear function S=aE+bR corresponding to residual capacity by electromotive force and internal resistance, and obtain described Multiple cluster centre values import in described linear function S=aE+bR, determine that the value of coefficient a, b is respectively a₀、b₀, obtain by electronic Gesture and internal resistance correspond to the linear function S=a of residual capacity₀E+b₀R；Wherein, S is dump energy；E is electromotive force；R is internal resistance； A, b are coefficient.

The embodiment of the present invention additionally provides a kind of system for remaining battery capacity detection, and described system includes:

Sample extraction unit, for extracting multiple sample from the historical data of accumulator；Wherein, each sample standard deviation is served as reasons Characteristic item includes the data that electromotive force, internal resistance and residual capacity are formed；

Fuzzy C-Means Clustering computing unit, for the multiple sample datas extracted all are introduced default Fuzzy C- Means clustering algorithm carries out cluster analysis, obtains multiple cluster centre with sample with same characteristic features item formation corresponding data Value；

Fitting function unit, for determining that the residual capacity of accumulator is determined by electromotive force and internal resistance, and obtains according to described The multiple cluster centre values arrived, obtain being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

Residual capacity acquiring unit, for obtaining electromotive force and the internal resistance of current accumulator, and by described get work as In the linear function obtained described in the electromotive force of front accumulator and internal resistance importing, the value of output is that the residue of current accumulator is held Amount.

Wherein, the historical data of described accumulator is lead-acid accumulator to be carried out charge and discharge by choosing the form of pulse charge and discharge Electricity and obtain.

Implement the embodiment of the present invention, have the advantages that

In embodiments of the present invention, there is nonlinear dependence due to rely on storage battery kinetic potential and internal resistance and residual capacity System, for exporting, is carried out data characteristics by Fuzzy C-Means Clustering Algorithm using electromotive force and internal resistance as input, residual capacity Extract, it is achieved the detection to remaining battery capacity, thus reduce the complexity of mathematical model, reduce the work of calculating Amount, and the residual capacity of accumulator can be detected by real-time online, and time saving and energy saving.

Accompanying drawing explanation

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing In having technology to describe, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is only this Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, according to These accompanying drawings obtain other accompanying drawing and still fall within scope of the invention.

The flow chart of the method for remaining battery capacity detection that Fig. 1 provides for the embodiment of the present invention；

The structural representation of the system for remaining battery capacity detection that Fig. 2 provides for the embodiment of the present invention.

Detailed description of the invention

For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, the present invention is made into one Step ground describes in detail.

As it is shown in figure 1, be in the embodiment of the present invention, it is provided that a kind of for remaining battery capacity detection method, institute The method of stating includes:

Step S1, from the historical data of accumulator, extract multiple sample；Wherein, each sample standard deviation is for be included by characteristic item The data that electromotive force, internal resistance and residual capacity are formed；

Detailed process is, it is contemplated that residual capacity can be caused by battery temp excessive variation to be affected, therefore largely In the middle of data acquisition, the historical data of accumulator is to obtain by choosing the form of pulse charge and discharge accumulator being carried out discharge and recharge , certain time of repose is set simultaneously, for ensureing that in whole charge and discharge process, the temperature of battery is basically unchanged.Accumulator It should be same type of accumulator, such as lead-acid accumulator, selected sample data only includes three feature item data, i.e. Electromotive force, internal resistance and residual capacity.

Step S2, the multiple sample datas extracted all are introduced in default Fuzzy C-Means Clustering Algorithm and gathers Alanysis, obtains multiple cluster centre value with sample with same characteristic features item formation corresponding data；

Detailed process is, the Fuzzy C-Means Clustering Algorithm (Fuzzy C-Means, FCM) preset actually depends on By the process of the continuous interative computation of object function, its purpose make exactly object function in regulation region iterative computation until reach Optimal solution.

First definition sample set is X={x₁, x₂..., x_n, and each sample is containing k=3 characteristic quantity.By sample set Being divided into c Fuzzy Cluster, the normalization constraints arranging Fuzzy C-Means Clustering analysis is:

$\underset{i=1}{\overset{c}{\Σ}}{u}_{ik}=1---\left(1\right)$

In formula (1), u_ikIt is sample X_iBelong to the degree of membership of classification k；

The basic thought of Fuzzy C-Means Clustering is exactly to fuzzy classified matrix U and cluster centre matrix under constraints P calculates so that object function Jm (U, P) is minimum.That is:

$\min \[J_m(U,P)\]=\min \[\underset{k=1}{\overset{n}{\Σ}}\underset{i=1}{\overset{c}{\Σ}}{u}_{ik}^m{\left(d_{ik}\right)}^2\]=\underset{k=1}{\overset{n}{\Σ}}\min \[\underset{i=1}{\overset{c}{\Σ}}{u}_{ik}^m{\left(d_{ik}\right)}^2\]---\left(2\right)$

Then, we can use Lagrange multiplication to solve, and obtains the cluster centre table of Fuzzy C-Means Clustering Reach formula, it only with degree of membership u_ikCorresponding relation is there is with Fuzzy Weighting Exponent m, as follows:

$p_i=\frac{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m{x}_k}{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m}---\left(3\right)$

Therefore, Fuzzy C-Means Algorithm is a dynamic process, the process of calculating by constantly amendment cluster centre and Subordinated-degree matrix, is iterated object function, finally obtains the fuzzy classification of data set.

Conclude Fuzzy C-Means Clustering in conjunction with the above-mentioned cluster centre provided and membership function expression formula, and clustered The concrete calculation procedure of central value is as follows:

Step S21, algorithm initialization, set the classification number C (2≤C≤n) of cluster, cluster initial centered value P₀, fuzzy add Power exponent m=2, iteration variable l=0, iteration threshold are l_maxWith compare threshold epsilon；Wherein, n is the total number of multiple sample；

Step S22, the degree of membership Matrix dividing U of l+1 iteration of renewal_l+1, for i and k of any number, and if only if Distance norm d_ikHave during more than zero:

$U_{ik}=\frac{1}{\underset{j=1}{\overset{c}{\Σ}}{\left(\frac{d_{ik}}{d_{jk}}\right)}^{2/(m-1)}}---\left(4\right)$

For i and r of any number, if making distance norm equal to zero, then there is u_ir=1；When j value is unequal with r Time have u_ij=0.

Step S23, update cluster centre value P of l+1 iteration by cluster centre computing formula_l+1, as follows:

$P_i=\frac{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m{x}_k}{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m}$

If step S24 max | | P_i ^(l+1)-P_i ^(l)| | ＜ ε or iterations l is more than maximum iteration time l_max, immediately Stop computing, otherwise make iterations l=l+1, be back to step S24 and continue computing；

Step S25, the degree of membership Matrix dividing U of last iteration and cluster centre value P are exported as parameter, obtain C has same characteristic features item with sample and forms the cluster centre value of corresponding data.

Step S3, determine that the residual capacity of accumulator is determined by electromotive force and internal resistance, and according to described obtain multiple poly- Class central value, obtains being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

Detailed process is, simulates the linear function S=aE+bR corresponding to residual capacity by electromotive force and internal resistance, and The multiple cluster centre values obtained are imported in linear function S=aE+bR, determines that the value of coefficient a, b is respectively a₀、b₀, obtain by Electromotive force and internal resistance correspond to the linear function S=a of residual capacity₀E+b₀R；Wherein, S is dump energy；E is electromotive force；R is Internal resistance；A, b are coefficient.

Step S4, the electromotive force obtaining current accumulator and internal resistance, and electronic by the described current accumulator got In the linear function obtained described in gesture and internal resistance importing, the value of output is the residual capacity of current accumulator.

Detailed process is, records electromotive force and the internal resistance of current accumulator, can be according to linear function S=a₀E+b₀R, obtains The residual capacity of current accumulator.

In embodiments of the present invention, the application scenarios of the method detected for remaining battery capacity is done furtherly Bright:

(1) using capacity is 60Ah, and model is 12V6-QA-60 and access times are the lead-acid accumulator between 0-100, In the sample collection procedure of historical data, use alternating current-direct current numeral pincers collecting work voltage and loop current.Treat accumulator battery After quitting work and standing 30 minutes, carry out checking discharging test, the actual value of record residual capacity.Therefore, the sample obtained This is as shown in table 1 below:

Table 1:

As can be seen from Table 1, lead-acid accumulator state-of-charge is substantially proportional to its electromotive force, lead-acid accumulator internal resistance with The carrying out of electric discharge and be gradually increased, when being in the electric discharge later stage, its change in value is obvious.

(2) sample data in table 1 is carried out cluster analysis, first FCM is initialized, determine cluster classification number C=9 Being m=2 with FUZZY WEIGHTED index, data initial cluster center gives at random, uses Euclidean distance norm.To initial data by fixed The cluster centre number of justice carries out cluster analysis, and cluster sample produces 9 cluster centres, as shown in table 2 below:

Table 2:

After many experiments, conclusion show that the excursion of this model lead-acid accumulator electromotive force E is 11.92- 12.80V, internal resistance R excursion is 21-36.4m Ω.Therefore electromotive force E is set respectively according to the parameter variation range of accumulator Basic domain [11.92,12.80], the basic domain [21,36.4] of internal resistance R, the basic domain [0,1] of SOC.Therefore, by table 2 two inputs be given, the fuzzy set of an output all have chosen 9 elements.

(3) data in table 2 are substituted in linear function S=aE+bR, permissible function after matching, obtain a=a₀, B=b₀, therefore S=a can be obtained₀E+b₀R, therefore wants to obtain the residual capacity of current accumulator, only need to record current accumulator Electromotive force and internal resistance, can calculate acquisition.

As in figure 2 it is shown, be in the embodiment of the present invention, it is provided that a kind of for remaining battery capacity detection system, institute The system of stating includes:

Sample extraction unit 210, for extracting multiple sample from the historical data of accumulator；Wherein, each sample standard deviation For being included, by characteristic item, the data that electromotive force, internal resistance and residual capacity are formed；

Fuzzy C-Means Clustering computing unit 220, for all introducing default mould by the multiple sample datas extracted Stick with paste in C-means clustering algorithm and carry out cluster analysis, obtain multiple cluster with sample with same characteristic features item formation corresponding data Central value；

Fitting function unit 230, for determining that the residual capacity of accumulator is determined by electromotive force and internal resistance, and according to described The multiple cluster centre values obtained, obtain being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

Residual capacity acquiring unit 240, for obtaining electromotive force and the internal resistance of current accumulator, and gets described In the linear function obtained described in the electromotive force of current accumulator and internal resistance importing, the value of output is that the residue of current accumulator is held Amount.

Wherein, the historical data of accumulator be lead-acid accumulator to be carried out discharge and recharge by choosing the form of pulse charge and discharge and Obtain.

Implement the embodiment of the present invention, have the advantages that

In embodiments of the present invention, there is nonlinear dependence due to rely on storage battery kinetic potential and internal resistance and residual capacity System, for exporting, is carried out data characteristics by Fuzzy C-Means Clustering Algorithm using electromotive force and internal resistance as input, residual capacity Extract, it is achieved the detection to remaining battery capacity, thus reduce the complexity of mathematical model, reduce the work of calculating Amount, and the residual capacity of accumulator can be detected by real-time online, and time saving and energy saving.

It should be noted that in said system embodiment, each included system unit simply enters according to function logic Row divides, but is not limited to above-mentioned division, as long as being capable of corresponding function；It addition, each functional unit Specific name also only to facilitate mutually distinguish, is not limited to protection scope of the present invention.

One of ordinary skill in the art will appreciate that all or part of step realizing in above-described embodiment method is permissible Instructing relevant hardware by program to complete, described program can be stored in a computer read/write memory medium, Described storage medium, such as ROM/RAM, disk, CD etc..

The above disclosed present pre-ferred embodiments that is only, can not limit the right model of the present invention with this certainly Enclose, the equivalent variations therefore made according to the claims in the present invention, still belong to the scope that the present invention is contained.

Claims (6)

1. the method for remaining battery capacity detection, it is characterised in that described method includes:

A, from the historical data of accumulator, extract multiple sample；Wherein, each sample standard deviation is for being included electromotive force, interior by characteristic item The data that resistance and residual capacity are formed；

B, the multiple sample datas extracted all are introduced default Fuzzy C-Means Clustering Algorithm carries out cluster analysis, To multiple cluster centre values with sample with same characteristic features item formation corresponding data；

C, determine that the residual capacity of accumulator is determined by electromotive force and internal resistance, and according to the described multiple cluster centre values obtained, Obtain being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

D, the electromotive force obtaining current accumulator and internal resistance, and electromotive force and the internal resistance of the described current accumulator got are led In the linear function obtained described in entering, the value of output is the residual capacity of current accumulator.

2. the method for claim 1, it is characterised in that " historical data of accumulator " in described step a is to pass through The form choosing pulse charge and discharge carries out discharge and recharge to lead-acid accumulator and obtains.

3. the method for claim 1, it is characterised in that described step b specifically includes:

B1, algorithm initialization, set the classification number C (2≤C≤n) of cluster, cluster initial centered value P₀, Fuzzy Weighting Exponent m= 2, iteration variable l=0, iteration threshold are l_maxWith compare threshold epsilon；Wherein, n is the total number of the plurality of sample；

B2, the degree of membership Matrix dividing U of l+1 iteration of renewal_l+1, for i and k of any number, distance norm d that and if only if_ik Have during more than zero:

$U_{ik}=\frac{1}{\underset{j=1}{\overset{c}{\Σ}}{\left(\frac{d_{ik}}{d_{jk}}\right)}^{2/(m-1)}}$

For i and r of any number, if making distance norm equal to zero, then there is u_ir=1；Have when j value is unequal with r u_ij=0.

B3, update cluster centre value P of l+1 iteration by cluster centre computing formula_l+1, as follows:

$P_i=\frac{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m{x}_k}{\underset{k=1}{\overset{n}{\Σ}}{\left(u_{ik}\right)}^m}$

If b4Or iterations l is more than maximum iteration time l_max, stop computing immediately, otherwise Make iterations l=l+1, be back to step b2 and continue computing；

B5, the degree of membership Matrix dividing U of last iteration and cluster centre value P are exported as parameter, obtain c and sample There is same characteristic features item and form the cluster centre value of corresponding data.

4. the method for claim 1, it is characterised in that described step c particularly as follows:

Simulate the linear function S=aE+bR corresponding to residual capacity by electromotive force and internal resistance, and by described obtain multiple Cluster centre value imports in described linear function S=aE+bR, determines that the value of coefficient a, b is respectively a₀、b₀, obtain by electromotive force and Internal resistance is corresponding to the linear function S=a of residual capacity₀E+b₀R；Wherein, S is dump energy；E is electromotive force；R is internal resistance；a、b For coefficient.

5. the system for remaining battery capacity detection, it is characterised in that described system includes:

Sample extraction unit, for extracting multiple sample from the historical data of accumulator；Wherein, each sample standard deviation is by feature Item includes the data that electromotive force, internal resistance and residual capacity are formed；

Fuzzy C-Means Clustering computing unit, for all introducing default FCM by the multiple sample datas extracted Clustering algorithm carries out cluster analysis, obtains multiple cluster centre value with sample with same characteristic features item formation corresponding data；

Fitting function unit, for determining that the residual capacity of accumulator is determined by electromotive force and internal resistance, and obtains according to described Multiple cluster centre values, obtain being corresponded to the linear function of residual capacity by electromotive force and internal resistance；

Residual capacity acquiring unit, for obtaining electromotive force and the internal resistance of current accumulator, and by the described current storage got In the linear function obtained described in the electromotive force of battery and internal resistance importing, the value of output is the residual capacity of current accumulator.

6. system as claimed in claim 5, it is characterised in that the historical data of described accumulator is by choosing pulse charge and discharge Form lead-acid accumulator is carried out discharge and recharge and obtains.