Lithium battery long-term degradation trend prediction method

A technology of trend forecasting and lithium batteries, applied in design optimization/simulation, computer-aided design, calculation, etc., can solve problems such as time-consuming and cost-consuming, achieve the effect of saving test volume and improving training effect

Active Publication Date: 2021-01-22
BEIHANG UNIV
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Problems solved by technology

At the same time, in order to find out the performance characteristics of the new formula lithium-ion battery, it is necessary to test and measure through a large number of performance test experiments, and the related test process often takes a lot of time and cost

Method used

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  • Lithium battery long-term degradation trend prediction method
  • Lithium battery long-term degradation trend prediction method
  • Lithium battery long-term degradation trend prediction method

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Embodiment Construction

[0037] figure 1 A method for predicting the long-term degradation trend of a lithium battery of the present invention is shown, including:

[0038] By normalizing and smoothing the partial degradation trend curve used for lithium batteries as the original data, the lithium battery samples to be predicted for input to the trained prediction model are obtained; when the prediction model receives the samples to be predicted of lithium batteries, it gives Generate the prediction action corresponding to the initial state of the lithium battery sample to be predicted, and the interactive environment used by the prediction model splices the prediction action corresponding to the initial state to the end of the initial state of the lithium battery sample to be predicted, as the first prediction Trend curve: the interactive environment intercepts the sequence of the first forecast trend curve result equal to the length of a single state as the state at the next moment and inputs it to ...

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Abstract

The invention discloses a lithium battery long-term degradation trend prediction method, which comprises the steps of performing normalization and smoothing processing by taking a partial degradationtrend curve for a lithium battery as original data to obtain a lithium battery to-be-predicted sample used for being input to a trained prediction model; when the prediction model receives the to-be-predicted sample of the lithium battery, generating a prediction action corresponding to the initial state of the to-be-predicted sample of the lithium battery, and splicing the prediction action corresponding to the initial state to the end of the initial state of the to-be-predicted sample of the lithium battery to serve as a first prediction trend curve by the interaction environment used by theprediction model; intercepting a sequence with the length equal to the single state length from the first prediction trend curve result, inputting the sequence into the prediction model as a next moment state, enabling the prediction model to give a prediction action corresponding to the next moment state, and splicing the prediction action corresponding to the next moment state to the end of thenext moment state by the interactive environment, and taking the prediction trend curve as a second prediction trend curve until a final prediction trend curve is obtained.

Description

technical field [0001] The invention relates to battery degradation trend prediction technology, in particular to a lithium battery long-term degradation trend prediction method. Background technique [0002] Fault prediction technology can not only provide decision-making basis for equipment repair, replacement and other maintenance work during the actual use of equipment, but also provide auxiliary decision-making information for the product design process during the equipment performance test stage. For example, for lithium battery research and development enterprises, accelerating the process of improving product performance can occupy more and faster market share. At the same time, in order to find out the performance characteristics of the new formula lithium-ion battery, it is necessary to test and measure through a large number of performance test experiments, and the related test process often takes a lot of time and cost. Therefore, using degradation trend / remaini...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F119/04
CPCG06F30/27G06F2119/04
Inventor 丁宇王超马剑吕琛
Owner BEIHANG UNIV
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