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Automatic battery parameter identification method

An automatic identification and battery parameter technology, which is applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of parameter divergence and the inability to eliminate abnormal divergent sample data, and achieve the effect of reducing parameter fluctuations and ensuring parameter updates

Active Publication Date: 2021-03-02
GREE ELECTRIC APPLIANCES INC
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] The online identification technical solution disclosed in the prior art has the problem of being unable to eliminate abnormally divergent sample data. Due to the error of the sampling sensor connected to the battery, some sampling data will cause parameters to diverge during the identification process.

Method used

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Embodiment Construction

[0055] In order to facilitate those skilled in the art to understand the present invention, the present invention will be further described in detail below in conjunction with specific embodiments and accompanying drawings.

[0056] Such as figure 1 As shown, the present invention provides a method for automatic identification of battery parameters, comprising the following steps:

[0057] Step 1, the current and voltage sampling sensor connected to the battery collects data, including: U(k), U(K-2), I(K), I(K-1), I(K-2);

[0058] Step 2, calculate the recurrence matrix K(k) according to equations (8), (9), and (10);

[0059] Step 3, calculate the error covariance matrix P(k) according to equations (8), (9), and (10);

[0060] Step 4, recursively update parameters, and obtain model parameters according to equations (12), (13), (14), (15), (16) and (17), and the model parameters include ;

[0061] Step 5, after reaching the preset number of recursions d (d<1000), the extende...

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Abstract

The invention relates to an automatic battery parameter identification method, which comprises the following steps of: establishing a second-order RC equivalent circuit model, and carrying out discrete and differential transformation to obtain an electrical expression of the circuit model; carrying out Laplace transformation on the electrical expression of the circuit model, converting the electrical expression into a z transformation form, carrying out linear transformation, and converting the electrical expression into a time domain discrete equation; converting the time domain discrete equation into a vector form based on a time domain discrete equation; establishing a recursive least square method with a forgetting factor lambda, and performing recursive iteration based on the recursive least square method to calculate a to-be-identified vector; after the recursion frequency d is set to reach the recursion frequency d, obtaining a set of model parameters through a recursion least square method, calculating the SOC of the battery through the model parameters in combination with extended Kalman filtering, and because of a certain linear relation between the SOC and the open-circuit voltage OCV, obtaining the open-circuit voltage OCV through the calculated SOC; and calculating an absolute value of a difference value (delta OVC) between the open-circuit voltage OCV and the open-circuit voltage, and if the absolute value of the difference value (delta OVC) exceeds a set range, performing parameter suppression.

Description

technical field [0001] The invention relates to the technical field of battery detection, in particular to a battery parameter automatic identification method. Background technique [0002] Battery state estimation is the focus of the battery management system. Accurate state estimation is inseparable from battery parameter identification. In this field, battery parameter identification is the identified battery model parameters. Battery model parameters are of great significance to battery state estimation. , The battery parameter identification method includes offline identification and online identification. Offline identification is generally obtained by fitting battery HPPC (pulse discharge) data. Offline identification is simple and easy to implement in engineering, but the parameters obtained by offline identification are a set of fixed values. Offline identification ignores that parameters will be affected by factors such as battery life and discharge rate. influenc...

Claims

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Application Information

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IPC IPC(8): G01R31/3842G01R31/388G01R31/367
CPCG01R31/367G01R31/3842G01R31/388
Inventor 何博宋爱夏雨雨刘兆斌崔桐冉小龙
Owner GREE ELECTRIC APPLIANCES INC
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