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Method for estimating SOC of lithium battery by data-driven algorithm considering internal resistance

A data-driven algorithm, lithium battery technology, applied in the direction of measuring electricity, measuring electrical variables, instruments, etc., to achieve the effect of high estimation accuracy and strong real-time performance

Active Publication Date: 2021-05-11
HANGZHOU DIANZI UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

The existing data-driven methods often only consider the three parameters of battery current, voltage, and temperature, but the internal resistance parameters of the battery have a greater impact on the estimation of SOC, and have not been fully considered using data-driven methods to estimate Lithium-ion battery SOC to go

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  • Method for estimating SOC of lithium battery by data-driven algorithm considering internal resistance
  • Method for estimating SOC of lithium battery by data-driven algorithm considering internal resistance
  • Method for estimating SOC of lithium battery by data-driven algorithm considering internal resistance

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Embodiment Construction

[0050] Below in conjunction with the present invention is further explained;

[0051] Such as figure 1 As shown, the method for estimating the SOC of a lithium battery with a data-driven algorithm considering internal resistance includes the following steps:

[0052] Step 1. Data collection

[0053] The Samsung INR 18650-20R lithium-ion battery was charged and discharged at 0°C, 25°C, and 45°C, and the voltage, current, temperature, and internal resistance of the battery were recorded during the test, and the sampling interval was 1s. The current adopts the discharge current under the standard working conditions established by the United States Environmental Protection Agency (EPC, United States Environmental Protection Agency); the lithium-ion battery is discharged through the IT8818B programmable electronic load produced by ITECH; Espec GMC-71 The high and low temperature test chamber can obtain the ambient temperature parameters of the battery; use the HIOKI BT3562 batter...

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Abstract

The invention discloses a method for estimating the SOC of a lithium battery by a data driving algorithm considering internal resistance. The method comprises the following steps: firstly, carrying out a charge-discharge test on the lithium ion battery by using test equipment, measuring voltage, current, temperature and internal resistance data of the battery in different working states, and preprocessing the obtained data; then, building a bidirectional GRU network, wherein one part of processed data serves as a training set to train the network, and the other part of the processed data serves as a test set to evaluate network performance; and finally, in order to improve the performance of the constructed network, optimizing the bidirectional GRU network by using an NAG algorithm. The input of the constructed bidirectional GRU-NAG network is the voltage, the current, the temperature and the internal resistance of the battery, and the output of the constructed bidirectional GRU-NAG network is the residual electric quantity of the battery, so that the method has the advantages of high estimation speed and simple process, and is a data-driven battery residual electric quantity estimation model.

Description

technical field [0001] The invention belongs to the technical field of batteries, and in particular relates to a method for estimating the SOC (State of Charge) of a lithium-ion battery by using a bidirectional GRU (Gated Recurrent Unit)-NAG (Nesterov Accelerated Gradient) algorithm considering internal resistance. Background technique [0002] In recent years, in order to reduce fossil fuel consumption and greenhouse gas emissions, and reduce urban pollution, the number of electric vehicles and hybrid vehicles is increasing. Lithium-ion batteries have been widely used in electric vehicles and hybrid vehicles because of their advantages such as high energy density, long cycle life, low self-discharge capacity, no memory effect, and fast charging speed. BMS (Battery Management System, battery management system) can ensure the safety, durability, reliability and efficiency of electric vehicles, and perform battery management and diagnosis tasks. [0003] The battery's state o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/382
CPCG01R31/382Y02T10/70
Inventor 高明裕张照娓何志伟董哲康林辉品杨宇翔钱志凯
Owner HANGZHOU DIANZI UNIV
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