A battery model parameter identification method based on multi-innovation recursive Bayesian algorithm

A Bayesian algorithm and parameter identification technology, applied in the field of lithium-ion batteries, can solve problems such as large amount of calculation and premature convergence, and achieve the effect of improving parameter estimation accuracy, high identification accuracy and small error

Active Publication Date: 2021-11-09
NANTONG UNIVERSITY
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Problems solved by technology

Swarm intelligence algorithms, such as particle swarm optimization and its improved algorithms, can be better applied to different working conditions, but there are also problems of large amount of calculation and premature convergence

Method used

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  • A battery model parameter identification method based on multi-innovation recursive Bayesian algorithm
  • A battery model parameter identification method based on multi-innovation recursive Bayesian algorithm
  • A battery model parameter identification method based on multi-innovation recursive Bayesian algorithm

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Experimental program
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Embodiment 1

[0095] see Figure 1 to Figure 9 , In this embodiment, the Panasonic lithium-ion battery NCR-18650B is used as the object of research, the nominal voltage is 3.7V, and the battery capacity is 3400mAh. The battery is charged to the cut-off voltage by constant current charging (0.5C), and the battery is fully charged after standing for 1 hour. The battery works in intermittent constant current discharge mode: discharge for 5 minutes, rest for 30 minutes, discharge current is 3400mA, discharge rate is 1C. This process is repeated until the voltage drops to the discharge cut-off voltage. Test voltage curve and current curve such as Figure 4 shown. The experiment verifies that the multi-innovation recursive Bayesian algorithm can identify each model parameter well, and the parameter estimation value of the algorithm remains relatively stable when the input current has unstable oscillations. In and out, the fluctuation is more obvious at the initial stage of identification, and...

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Abstract

The present invention provides a battery model parameter identification method based on multi-innovation recursive Bayesian algorithm, comprising the following steps: Step 1) measuring the lithium-ion battery terminal voltage and load current within a certain period of time by intermittent constant current discharge method Data, determine the functional relationship of its OCV-SOC by polynomial fitting method; step 2) determine the dual-polarization equivalent circuit model of lithium-ion battery, establish the system equation that represents the battery parameter identification vector and system output relationship; step 3) construct multiple The identification process of the innovation recursive Bayesian algorithm. The beneficial effect of the present invention is: the present invention establishes the ARX model of lithium-ion battery parameter identification, uses the innovation correction technology to correct the result of the previous moment, and introduces the innovation length parameter based on the multi-innovation identification method to overcome bad data The impact on parameter estimation improves the accuracy of parameter estimation. It can be seen from the parameter identification results that this method has high identification accuracy and has engineering value.

Description

technical field [0001] The invention relates to the technical field of lithium-ion batteries, in particular to a battery model parameter identification method based on a multi-innovation recursive Bayesian algorithm. Background technique [0002] With the development of the transportation industry, the shortage of resources, environmental pollution and safety problems are becoming more and more serious, and the new energy industry is emerging, and new energy vehicles are receiving more and more attention. Correspondingly, the energy storage system has become a revolutionary technology to promote the consumption of renewable energy due to its advantages of flexible configuration, fast response, and easy operation and maintenance. Battery energy storage has broad application prospects in the field of new energy access. Lithium-ion batteries have the characteristics of long life, low self-discharge effect and high energy density, and have become the main battery energy storage ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G06N7/00
CPCG01R31/367G06N7/01
Inventor 李俊红李磊顾菊平华亮刘慧霞杨奕李政蒋泽宇
Owner NANTONG UNIVERSITY
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