CN103472397A - Key parameter robust identification method in lead acid battery model empirical formula - Google Patents

Abstract

The invention discloses a key parameter robust identification method in a lead acid battery model empirical formula. The method comprises: first of all, carrying out a plurality of charging experiments on a lead acid battery, and measuring the end voltage, the charging current and the SOC value of the battery during a charging process; establishing a nonlinear optimization problem of robust parameter identification by taking the data obtained from recording in the experiments; solving the problem by using Newton's method of nucleus width adjusting, and obtaining a local optimal solution (usually a global optimal solution ) of the optimization problem, after the optimal solution is obtained, obtaining the key parameters in a model, and accordingly obtaining the empirical formula of the lead acid battery model. The key parameters in the lead acid model empirical formula are obtained by solving the optimization problem which is based on minimum information entropy loss, and poor measurements can be automatically eliminated in the solving process, so that a result with higher robustness can be obtained, the efficiency and precision are also quite high, and the availability of the method is high.

Description

Key parameter robust discrimination method in lead-acid battery model experimental formula method

Technical field

The invention belongs to the Lead-acid Battery Technology field, relate in particular in battery model the discrimination method of key parameter in the experimental formula method.

Background technology

In battery management system, quantitative relationship for clear and definite outside batteries electrical specification and internal state, need to set up mathematical model, thereby calculate the internal states such as SOC, SOH, internal resistance, electromotive force according to external variables such as the voltage of battery, electric current, temperature, as the linear model method, wear the Vernam model method, quadravalence dynamic model method and experimental formula method etc.In the experimental formula method, common are Shepherd model, Unnewehr universal model, Nernst model etc., its expression formula is generally y _k=E ₀-Ri _k+ f (K _i, K ₂, K ₃, z _k) (wherein, y _kthe terminal voltage measured value that means battery, E ₀mean the electromotive force that battery SOC is 100%, R is the internal resistance of cell, i _kbe electric current, f means correction term, for different models, and expression formula difference, z _kthe SOC value that battery charging and discharging is, K _i, K ₂, K ₃the parameter need obtained), the Nonlinear Dynamic static characteristics that these experimental formulas can simulated battery show, but most parameters wherein needs method by experiment to be determined.

Owing in experiment, may having measuring error, and the characteristics of experimental formula method itself, when data acquisition parameters of formula by experiment, need to arrange as much as possible the impact of unreasonable measurement data, thereby make parameters of formula in most of the cases can both use.But in this technical field, still do not have effective method to realize this purpose at present.

Summary of the invention

Goal of the invention: for the problem and shortage of above-mentioned existing existence, the invention provides and propose key parameter robust discrimination method in a kind of lead-acid battery model experimental formula method, the method is by using for reference information science and the existing robust method of estimation of field of power, on the basis of experimental data, by solving an optimization problem based on the loss of minimal information entropy, obtain the key parameter in plumbic acid model experimental formula method, can automatically get rid of bad the measurement in solution procedure, obtain the higher result of robustness.

Technical scheme: for achieving the above object, the present invention is by the following technical solutions: key parameter robust discrimination method in a kind of lead-acid battery model experimental formula method, it is characterized in that: at first, by the lead-acid accumulator test of charging, terminal voltage, charging current and the SOD value of survey record battery in charging process; Using the data of aforementioned record as input, set up the nonlinear optimal problem of robust parameter identification; Adopt this problem of Newton Algorithm into the wide adjustment of core, obtain the locally optimal solution of this optimization problem, this locally optimal solution is the key parameter in lead acid storage battery pool model experimental formula, and then determines the experimental formula that obtains the lead acid storage battery pool model.

Technique scheme is illustrated:

Step 1: lead-acid accumulator is carried out to m group charging experiment, measure the terminal voltage of battery in charging process

charging current

with the SOC value

wherein the measurement of SOC adopts the ampere hour method,

c wherein _rbattery remaining power, C _abe the rated capacity of battery, I is discharge current, then by C _r/ C _acan obtain

and terminal voltage

and charging current can read from the table meter;

Step 2: set up Optimized model as shown in Equation (1), using the data of step 1 record as input:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i+f(K_i,K_2,K_3,{\hat{z}}_i))}^2}{2{\mathrm{\σ}}^2})---\left(1\right)$

In formula, w _ibe the weight of each measurement, σ is that core is wide,

the terminal voltage measured value that means battery, E ₀mean the electromotive force that battery SOC is 100%, R is the internal resistance of cell,

be current measurement value, f means correction term, sOC measured value value while being battery charging and discharging, K _i, K ₂, K ₃to need the parameter obtained;

Step 3: for above-mentioned nothing constraint nonlinear optimal problem, by adding the Newton Algorithm key parameter E of the wide adjustment of core ₀, R, K _i, K ₂, K ₃, concrete grammar is as follows:

(1) the wide and parameter to be identified of initialization core, iterations k=0;

(2) in the k time iteration, under the initial value of and parameter to be identified wide at given core, utilize the optimum solution of the optimization problem above Newton Algorithm, obtain optimum solution;

(3) be less than given threshold value if core now is wide, calculate and finish, the optimum solution now obtained by Newton method is exactly the optimum solution of appeal unconstrained optimization problem; Otherwise it is wide to revise core;

(4) wide according to certain rule adjustment core, and the initial value of the optimum solution of usining now parameter to be identified during as next iteration, return to step (2), re-use Newton Algorithm optimization problem now;

After obtaining optimum solution, obtained the key parameter E in the model ₀, R, K _i, K ₂, K ₃, and then obtained the experimental formula of lead-acid battery model.

Beneficial effect: compared with prior art, the present invention has the following advantages: at first, on the basis of experimental data, by solving an optimization problem based on the loss of minimal information entropy, obtain the key parameter in plumbic acid model experimental formula method, can automatically get rid of bad the measurement in solution procedure, obtain the higher result of robustness; Secondly, the Newton method based on the wide adjustment of core can be obtained the optimum solution of this nonlinear optimal problem usually, and computing velocity has the advantage in theory and practice also than comparatively fast; The 3rd, this method is to original production line and relevant device and have no special requirements, and can on original measuring equipment basis, complete.

The accompanying drawing explanation

The principle of work schematic diagram that Fig. 1 is key parameter robust discrimination method in lead-acid battery model experimental formula method of the present invention.

Embodiment

Below in conjunction with the drawings and specific embodiments, further illustrate the present invention, should understand these embodiment only is not used in and limits the scope of the invention for the present invention is described, after having read the present invention, those skilled in the art all fall within the application's claims limited range to the modification of the various equivalent form of values of the present invention.

At first, lead-acid accumulator is carried out to m group charging experiment, measure the terminal voltage of battery in charging process

charging current

with the SOC value wherein the measurement of SOC adopts the ampere hour method, c wherein _rbattery remaining power, C _abe the rated capacity of battery, I is discharge current, then by C _r/ C _acan obtain and terminal voltage

and charging current

can read from the table meter.

The data that again experimental record obtained, as input, are set up following Optimized model:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i+f(K_i,K_2,K_3,{\hat{z}}_i))}^2}{2{\mathrm{\σ}}^2})$

Wherein, w _ibe the weight of each measurement, σ is that core is wide,

the terminal voltage measured value that means battery, E ₀mean the electromotive force that battery SOC is 100%, R is the internal resistance of cell,

be current measurement value, f means correction term, for different models, and the expression formula difference,

sOC measured value value while being battery charging and discharging, K _i, K ₂, K ₃to need the parameter obtained.

For example, for the Shepherd model, above formula is:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i-K_i{/\hat{z}}_i)}^2}{2{\mathrm{\σ}}^2})$

For Unnewehr universal model, above formula is:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i-K_i{\hat{z}}_i)}^2}{2{\mathrm{\σ}}^2})$

For the Nernst model, above formula is:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i+K_2\ln \left({\hat{z}}_i\right)+K_3\ln (1+{\hat{z}}_i))}^2}{2{\mathrm{\σ}}^2})$

Below take the Shepherd model as example, and above formula is:

$\max \underset{i=1}{\overset{m}{\mathrm{\Σ}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i-K_i{/\hat{z}}_i)}^2}{2{\mathrm{\σ}}^2})$

Nothing constraint nonlinear optimal problem for above-mentioned can adopt the Newton Algorithm that adds as follows the wide adjustment of core:

1) the wide σ of initialization core ⁽⁰⁾with parameter E to be identified ₀, R, K _i, iterations k=0;

2) in the k time iteration, at the wide σ of given core ^(k)(be designated as E with the initial value of parameter to be identified ₀ ^(k), R ^(k), K _i ^(k)) under, utilize the optimum solution of the optimization problem above Newton Algorithm, obtain σ=σ ^(k)the time optimum solution E ₀ ^(k), R ^(k), K _i ^(k)| σ=σ ^(k);

3) if σ ^(k)<, calculate and finish, otherwise carry out step 4;

4) adjust σ ^(k), make σ ^(k+1)=0.1 σ ^(k), until E ₀ ^(k), R ^(k), K _i ^(k)| σ=σ ^(k)hessian battle array positive definite;

5) make E ₀ ^(k+1)=E ₀ ^(k)| σ=σ ^(k), R ^(k+1)=R ^(k)| σ=σ ^(k), K _i ^(k+1)=K _i ^(k)| σ=σ ^(k), progressive rapid 2.

After obtaining optimum solution, obtained the key parameter E in the model ₀, R, K _i, K ₂, K ₃, and then obtained the experimental formula of lead-acid battery model.

Compared with prior art, this method obtains the key parameter in plumbic acid model experimental formula method by solving an optimization problem based on the loss of minimal information entropy, can automatically get rid of bad the measurement in solution procedure, obtain the higher result of robustness, efficiency and precision are also higher, and the availability of method is strong.This method is to original production line and relevant device and have no special requirements, and can on original measuring equipment basis, complete.

Claims (2)

1. key parameter robust discrimination method in a lead-acid battery model experimental formula method is characterized in that: at first, and by the lead-acid accumulator test of charging, terminal voltage, charging current and the SOD value of survey record battery in charging process; Using the data of aforementioned record as input, set up the nonlinear optimal problem of robust parameter identification; Adopt this problem of Newton Algorithm into the wide adjustment of core, obtain the locally optimal solution of this optimization problem, this locally optimal solution is the key parameter in lead acid storage battery pool model experimental formula, and then determines the experimental formula that obtains the lead acid storage battery pool model.

2. key parameter robust discrimination method in lead-acid battery model experimental formula method according to claim 1 is characterized in that comprising the following steps:

Step 1: lead-acid accumulator is carried out to m group charging experiment, measure the terminal voltage of battery in charging process

charging current

with the SOC value wherein the measurement of SOC adopts the ampere hour method,

c wherein _rbattery remaining power, C _abe the rated capacity of battery, I is discharge current, then by C _r/ C _acan obtain and terminal voltage

and charging current

can read from the table meter;

Step 2: set up Optimized model as shown in Equation (1), using the data of step 1 record as input:

$\max \underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{w}_i\exp (-\frac{{({\hat{u}}_i-E_0-R{\hat{i}}_i+f(K_i,K_2,K_3,{\hat{z}}_i))}^2}{2{\mathrm{\&sigma;}}^2})---\left(1\right)$

In formula, w _ibe the weight of each measurement, σ is that core is wide,

the terminal voltage measured value that means battery, E ₀mean the electromotive force that battery SOC is 100%, R is the internal resistance of cell,

be current measurement value, f means correction term,

sOC measured value value while being battery charging and discharging, K _i, K ₂, K ₃to need the parameter obtained;

Step 3: for above-mentioned nothing constraint nonlinear optimal problem, by adding the Newton Algorithm key parameter E of the wide adjustment of core ₀, R, K _i, K ₂, K ₃, concrete grammar is as follows:

(1) the wide and parameter to be identified of initialization core, iterations k=0;

(2) in the k time iteration, under the initial value of and parameter to be identified wide at given core, utilize the optimum solution of the optimization problem above Newton Algorithm, obtain optimum solution;

(3) be less than given threshold value if core now is wide, calculate and finish, the optimum solution now obtained by Newton method is exactly the optimum solution of appeal unconstrained optimization problem; Otherwise it is wide to revise core;

(4) wide according to certain rule adjustment core, and the initial value of the optimum solution of usining now parameter to be identified during as next iteration, return to step (2), re-use Newton Algorithm optimization problem now;

After obtaining optimum solution, obtained the key parameter E in the model ₀, R, K _i, K ₂, K ₃, and then obtained the experimental formula of lead-acid battery model.

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