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Storage battery state of charge (SOC) estimation method based on extended Kalman filtering (EKF)

An extended Kalman, state of charge technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of large manual labor, low precision, and difficult operation.

Inactive Publication Date: 2015-11-25
SHANDONG ZHIYANG ELECTRIC
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Problems solved by technology

[0004] In the implementation process of the present invention, the prior art at least has defects such as large amount of manual labor, poor real-time performance, difficult operation and low precision.

Method used

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  • Storage battery state of charge (SOC) estimation method based on extended Kalman filtering (EKF)
  • Storage battery state of charge (SOC) estimation method based on extended Kalman filtering (EKF)
  • Storage battery state of charge (SOC) estimation method based on extended Kalman filtering (EKF)

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Embodiment Construction

[0078] The present invention comprises the following steps:

[0079] a. Perform performance test on the battery through staged discharge, and obtain the discharge current and cell voltage data during the discharge test;

[0080] b. Based on the test data obtained in step a, obtain the functional relationship between the open circuit voltage and the state of charge;

[0081] c. Carry out parameter identification based on the test data obtained in step a, and obtain battery model parameters of each discharge stage;

[0082] d. Based on the functional relationship obtained in step b and the battery model parameters of the first discharge stage obtained in step c, the battery SOC is estimated through the EKF algorithm;

[0083] e. Based on the SOC obtained in step d, after temperature compensation is performed, the final SOC is obtained;

[0084] f. Carry out internal resistance test on the battery regularly, and select the battery model parameters under the corresponding discha...

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Abstract

The invention relates to a storage battery state of charge (SOC) estimation method based on extended Kalman filtering (EKF). The method comprises the following steps: performing performance testing on a storage battery through stepped discharge to obtain discharge currents and monomer voltage data in a discharge test process; based on test data obtained from step a, obtaining an open voltage-SOC function relation; based on the test data obtained from the step a, carrying out parameter identification to obtain storage battery model parameters of each discharge phase; based on the function relation obtained from the step b and storage battery model parameters of a first discharge phase, obtained from step c, estimating the SOC of the storage battery through an EKF algorithm; based on the SOC obtained from step d, after temperature compensation is performed, a final SOC is obtained; regularly performing internal resistance testing on the storage battery, and selecting the storage battery model parameters in the corresponding phases in the step c from measured internal resistance values; and obtaining a latest SOC through the step d and step e. The method provided by the invention can accurately and rapidly carry out SOC estimation.

Description

Technical field: [0001] The invention relates to a battery state-of-charge estimation method based on extended Kalman filtering, and relates to the technical field of electric power system batteries. Background technique: [0002] As the last line of defense for reliable power supply, VRLA batteries play an important role in backup power systems. Due to long-term floating charge and lack of maintenance, the performance of the battery will gradually deteriorate with use. The batteries in the power system are used in series, and the performance difference between the batteries will lead to uneven voltage distribution during charging and discharging, so that it is impossible to ensure that each battery can reach the standard charging and discharging, further accelerating the aging of the batteries and reducing the battery life of the whole group. reliability. Therefore, it is very important to master the SOC of each battery, especially the poor battery. [0003] Existing bat...

Claims

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Application Information

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IPC IPC(8): G01R31/36
Inventor 刘国永杨菲张万征
Owner SHANDONG ZHIYANG ELECTRIC
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