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A lithium battery online life prediction method based on data fusion and arima model

A technology of life prediction and data fusion, applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., can solve problems such as large prediction errors, inability to capture nonlinear changes, and low prediction accuracy of nonlinear change data, so as to improve accuracy and robustness, realize real-time observation, and improve the effect of life prediction accuracy

Active Publication Date: 2020-12-15
BEIHANG UNIV
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Problems solved by technology

The traditional ARIMA model cannot capture nonlinear changes, and the prediction accuracy of nonlinear change data is not high. It is used to predict the state of health (State of Health, SOH) and remaining useful life (Remaining Useful Life, RUL) of the battery in the later period. Forecast error of

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  • A lithium battery online life prediction method based on data fusion and arima model
  • A lithium battery online life prediction method based on data fusion and arima model
  • A lithium battery online life prediction method based on data fusion and arima model

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Embodiment Construction

[0045] In order to have a further cognition and understanding of the features, purposes and functions of the present invention, the present invention will now be described in more detail in conjunction with specific embodiments and accompanying drawings.

[0046] like image 3 As shown, the present invention provides a lithium battery online life prediction method based on data fusion and ARIMA model, and the specific implementation steps are as follows:

[0047] The first step: Collect the data of equal voltage discharge, charging time interval and battery capacity of lithium battery.

[0048] The data used in the present invention comes from the lithium battery life test data set published by the NASA Failure Prediction Research Center (Prognostics Center of Excellence, PCoE), and the lithium battery data numbered B0005 is used for life prediction.

[0049] Draw the curve of voltage changing with time in the first discharge process (Cycle 1) of B0005 lithium battery, such a...

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Abstract

The invention discloses an online life prediction method for a lithium battery based on data fusion and an ARIMA model. The method comprises the following steps: 1, collecting equal-voltage discharge,charging time interval and battery capacity data of the lithium battery; 2, calculating the fusion weight of a data layer and fusing the data; 3, training and estimating parameters of the ARIMA modeland checking the ARIMA model; 4, predicting RUL and next-period SOH through the ARIMA model according to the data fused in the step 2; and 5, inputting battery state observation data acquired onlinein real time, repeating the steps 2 to 4, and updating the ARIMA prediction model to realize online prediction. According to the method, the service life of the lithium battery is predicted online based on data fusion and the ARIMA model, the service life is predicted more precisely, an online service life prediction function of the lithium battery is realized, and the reliability of the lithium battery of a spacecraft is analyzed.

Description

technical field [0001] The design of the present invention belongs to the field of life prediction and health management (Prognosis and Health Management, PHM), and specifically relates to an online life prediction method of a lithium battery based on data fusion and an ARIMA model. Background technique [0002] Compared with other energy storage devices, lithium batteries have the advantages of high energy density, light weight, and stable discharge. Lithium batteries are used as energy storage devices for spacecraft, which can improve the storage efficiency and stability of spacecraft energy systems, increase payloads, and reduce launch costs. Due to the complexity, large-scale and intelligentization of spacecraft equipment, and the special working environment, after-event maintenance and regular maintenance can no longer meet the requirements. At present, the technical means to maintain the reliable operation of spacecraft mainly rely on health status assessment technolo...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G01R31/392
CPCG01R31/367G01R31/392
Inventor 赵洪博王清赵琦庄忱冯文全
Owner BEIHANG UNIV
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