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Method for predicting cycle life of lithium battery based on electrochemical thermo-coupling model

A cycle life, electrochemical technology, applied in the direction of electrical digital data processing, design optimization/simulation, special data processing applications, etc., can solve problems that have not been considered, and achieve strong predictive ability, wide application range, and strong applicability Effect

Inactive Publication Date: 2017-09-08
CENT SOUTH UNIV
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Problems solved by technology

The patent with the publication number CN 103336248A discloses a battery degradation model based on collected battery monitoring data to realize the prediction method of lithium-ion battery cycle life. The monitored data are time, discharge voltage, current and battery capacity, without taking into account Effects of Temperature, Depth of Discharge and Discharge Rate on the Life Prediction Model

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  • Method for predicting cycle life of lithium battery based on electrochemical thermo-coupling model
  • Method for predicting cycle life of lithium battery based on electrochemical thermo-coupling model
  • Method for predicting cycle life of lithium battery based on electrochemical thermo-coupling model

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Embodiment 1

[0029] Such as figure 1 Shown, a kind of method based on the prediction lithium battery cycle life of electrochemical-thermal coupling model, it is characterized in that: comprise the following steps:

[0030] Parameter acquisition: First, commercially available soft-pack lithium iron phosphate batteries, with a specification of 13mm×126mm×216mm and a standard capacity of 20.0Ah. Lithium iron phosphate is used as the positive electrode, and carbon mesophase microspheres (MCMB) are used as the negative electrode. The basic physical parameters and electrochemical parameters of this type of battery were obtained by means of product instructions, experimental tests, and literature search, as shown in Table 1.

[0031] Table 1 shows the battery parameters of the electrochemical thermal coupling model

[0032]

[0033] Wherein the symbol description: ε s , ε e are solid phase volume fraction and liquid phase volume fraction respectively, L and r represent thickness and active...

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Abstract

The present invention provides a method for predicting the cycle life of a lithium battery based on the electrochemical thermo-coupling model. The method comprises the following steps: 1) obtaining physical parameters and electrochemical parameters of the lithium battery, and carrying out a charging and discharging cycle test on the battery; 2) using the parameter information obtained in step 1) to establish an electrochemical thermo-coupling model, and carrying out validity verification on the model, wherein the electrochemical thermo-coupled model is a coupling model of a quasi-two-dimensional electrochemical model and a three-dimensional thermal model; 3) verifying the validity of the model; 4) determining the experience life function; and 5) obtaining the final life function. According to the method provided by the present invention, by constructing the electrochemical thermo-coupling multi-physics field model, function fitting is carried out on the simulated life curve, so that the battery life prediction method with fast response, strong forecasting ability and wide application range is obtained.

Description

technical field [0001] The invention relates to a method for predicting the cycle life of a lithium battery based on an electrochemical-thermal coupling model. Background technique [0002] Since the commercialization of lithium-ion batteries, they have been widely used in portable electronic devices, electric vehicles, aerospace and other fields due to their excellent properties such as high energy density, long cycle life, high discharge voltage and low self-discharge rate. [0003] Among many performance indicators, customers are paying more attention to cycle life than ever before. Conventional battery cycle life testing methods have the disadvantages of cumbersome testing procedures, long working hours and high economic costs. Therefore, there are currently two main ideas for the prediction of the cycle life of lithium-ion batteries: 1. Using data-driven methods, such as: neural network, support vector machine, summation autoregressive model, etc. to analyze and model ...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 贾明蒋跃辉李立祥艾燕杜双龙李书国
Owner CENT SOUTH UNIV
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