Lithium ion battery remaining useful life prediction method based on fusion algorithm

A lithium-ion battery, life prediction technology, applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., can solve the problem of not mentioning the error compensation of the filtering model, and achieve high accuracy, good stability, and improve prediction accuracy. Effect

Active Publication Date: 2019-08-30
CHONGQING UNIV
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Problems solved by technology

In the first category, the use of data-driven methods to infer or compensate physical models, the use of data-driven methods to estimate predictive measurements of model-based methods, the use of data-driven methods to estimate or adjust the parameters of physical m...

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  • Lithium ion battery remaining useful life prediction method based on fusion algorithm
  • Lithium ion battery remaining useful life prediction method based on fusion algorithm
  • Lithium ion battery remaining useful life prediction method based on fusion algorithm

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Embodiment Construction

[0037] Embodiments of the present invention are described below through specific examples.

[0038] figure 1 It is the overall flowchart of the method of the present invention, as shown in the figure, in this embodiment, the following method steps are adopted:

[0039] Step S1: Obtain open-source battery capacity decay data from the Advanced Life Cycle Engineering Center of the University of Maryland in the United States, select the capacity degradation model (CDM), and determine the RUL prediction model based on one of the optimal control algorithms—particle filter algorithm (PF) parameter;

[0040] Step S2: Utilize the superiority of PF in the process of nonlinear and non-Gaussian capacity degradation, fit the training set data (number of cycles k<160), and iteratively output PF algorithm model parameter filtering estimates and battery capacity attenuation data filtering Estimated value, the estimated value is filtered by model parameters to obtain the initial RUL predicte...

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Abstract

The invention relates to a lithium ion battery remaining useful life (RUL) prediction method based on a fusion algorithm and belongs to the technical field of battery management. The method comprisesthe following steps: S1, acquiring battery capacity attenuation data, and determining parameters of a RUL prediction model based on an optimal control algorithm; S2, fitting data of a training set, iteratively outputting an optimal control algorithm mode parameter filtering estimation value and a battery capacity attenuation data filtering estimation value, and obtaining an initial RUL predicted value by virtue of the model parameter filtering estimated value; S3, based on a difference value between the filtering estimation value of the optimal control algorithm and experimental data, buildingan original error sequence, taking the original error sequence as an input of a neutral network algorithm, performing continuous iteration training on the error sequence, and outputting a predictionresult of the error sequence; and S4, after the data of the training set is used, obtaining a final lithium ion battery RUL prediction result by synthesizing an initial predicted value of the optimalcontrol algorithm and the error sequence prediction result obtained by virtue of the neutral network algorithm.

Description

technical field [0001] The invention belongs to the technical field of battery management and relates to a method for predicting the remaining life of a lithium-ion battery based on a fusion algorithm. Background technique [0002] In recent years, due to its wide application in new energy vehicles and other technological fields, lithium-ion batteries have gradually become a research hotspot in the field of new energy vehicle power batteries due to their high energy density and long cycle life. However, as the battery capacity gradually decays with the increase of the number of cycles, the performance of the battery will deteriorate, and even cause economic losses and personal injuries. Therefore, battery health status monitoring based on lithium battery capacity decay has become an urgent problem to be solved. The remaining battery life can be defined as the number of charge and discharge cycles before the attenuation performance index of the battery reaches the specified ...

Claims

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Application Information

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IPC IPC(8): G01R31/392G01R31/367
CPCG01R31/367G01R31/392
Inventor 冯飞胡晓松杨鑫刘波李可心李云隆李佳承谢翌杨亚联
Owner CHONGQING UNIV
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