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Battery RUL prediction method based on battery capacity decline track linear transformation

A trajectory linearization and prediction method technology, applied in the direction of measuring electrical variables, measuring electricity, measuring devices, etc., can solve problems such as consuming large resources and time, save resources and time, improve prediction accuracy and convergence performance, and apply value high effect

Inactive Publication Date: 2019-08-09
SOUTH CHINA UNIV OF TECH
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] However, the classic empirical prediction method and filter prediction method need to analyze the offline aging data of the power battery, which will consume a lot of resources and time

Method used

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  • Battery RUL prediction method based on battery capacity decline track linear transformation
  • Battery RUL prediction method based on battery capacity decline track linear transformation
  • Battery RUL prediction method based on battery capacity decline track linear transformation

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Embodiment

[0035] In this embodiment, the historical capacity data of 1,000 cycles of charging and discharging of a single lithium iron phosphate power battery carried by a certain type of passenger car is selected as the predicted data set, and a battery RUL prediction method based on the linear transformation of the battery capacity decline trajectory is provided. Its flow chart is as figure 1 shown, including the following steps:

[0036] S1. Read the historical capacity data of the power battery. The function curve between the original historical capacity data and the number of discharge cycles is highly nonlinear. Through the Box-Cox transformation, the nonlinear capacity data trajectory is linearized to obtain the Box-Cox transformation coefficient and the Box-Cox transformation coefficient. -History capacity data after Cox transformation; The mathematical expression of described Box-Cox transformation is as shown in formula (1):

[0037]

[0038] where Q max is the historical...

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Abstract

The invention discloses a battery RUL prediction method based on battery capacity decline track linear transformation. The method comprises the following steps: S1, reading historical capacity data ofthe power battery, linearizing a non-linear capacity data track through Box-Cox transformation, and obtaining a Box-Cox transformation coefficient and the historical capacity data subjected to Box-Cox transformation; S2, fitting the historical capacity data subjected to Box-Cox transformation and the corresponding cycle index by using a primary polynomial model; S3, identifying model parameters of the primary polynomial model through a Parameter Estimation tool in Matlab / Simulink; and S4, inputting a set capacity threshold value, predicting the number of cycles reaching the capacity thresholdvalue through the primary polynomial model after parameter updating, and outputting the number of cycles. According to the method, the step of analyzing the offline aging data of the power battery isomitted, and resources and time are greatly saved.

Description

technical field [0001] The invention relates to the field of power battery performance decline prediction, in particular to a method for predicting battery remaining life (RUL) based on linear transformation of battery capacity decline track. Background technique [0002] As the sole power source of electric vehicles, the power battery's performance reliability and stability largely determine the vehicle's power and cruising range. Therefore, the prediction of the performance of electric vehicle power battery has far-reaching significance for the development of electric vehicles. Some irreversible chemical reactions will inevitably occur inside the power battery during the charging and discharging process, resulting in a decrease in the maximum available capacity and maximum output power of the battery, thereby reducing the cruising range and maximum power of the vehicle. Reliable remaining battery life (RUL) prediction is the basis for estimating the cruising range of the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G01R31/367G01R31/392
CPCG01R31/392G01R31/367G06F30/20
Inventor 田晟吕清
Owner SOUTH CHINA UNIV OF TECH
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