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Method and device for predicting SOH of battery

A technology of battery health status and prediction method, which is applied in the directions of measuring devices, measuring electricity, and measuring electrical variables, etc., can solve the problem of low prediction accuracy of battery SOH, achieve the effect of improving exploration ability and development ability, and improving convergence accuracy

Pending Publication Date: 2021-06-08
QINGDAO UNIV
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Problems solved by technology

[0004] The embodiment of the present application provides a battery state of health SOH prediction method and device to help solve the problem of low prediction accuracy of battery SOH in the prior art

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  • Method and device for predicting SOH of battery
  • Method and device for predicting SOH of battery
  • Method and device for predicting SOH of battery

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Embodiment Construction

[0035] In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described The embodiments are only some of the embodiments of the present application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0036] Commonly used data-driven methods for battery health SOH prediction include Gaussian process regression, particle filter, artificial neural network, support vector regression SVR, etc. Compared with other data-driven methods, SVR has a sound theoretical foundation and strong anti-generalization ability, and has unique advantages in...

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Abstract

The embodiment of the invention discloses a battery SOH prediction method and device. The method comprises the following steps: extracting characteristic factors related to battery capacity decline from an original data set to construct a characteristic vector; obtaining a training sample set and a test sample set corresponding to the feature vectors according to the original data set; performing parameter optimization on the support vector regression model through an improved ant lion optimization algorithm to obtain an optimal parameter combination; taking the optimal parameter combination as a parameter of the support vector regression model, and training the support vector regression model through the training sample set; and predicting the test sample set by adopting the trained support vector regression model, and outputting an SOH prediction result. By adopting the technical scheme provided by the embodiment of the invention, the prediction precision of the SOH of the battery can be improved.

Description

technical field [0001] The present application relates to the technical field of batteries, in particular to a battery state of health SOH prediction method and device. Background technique [0002] With the rise of new energy applications, batteries have been widely used in electric vehicles due to their high energy density, high potential, good low temperature performance, low self-discharge rate and long life. However, as the number of times the battery is used increases, the battery will age. If the faulty battery cannot be found and dealt with in time, it may damage the battery energy storage system and affect the safety and stability of the electric vehicle. [0003] As one of the key functions of the battery management system (Battery Management System, BMS), the state of health (State Of Health, SOH) prediction is of great significance to ensure the safe and reliable operation of the battery and reduce the maintenance cost of the battery system. Therefore, improving...

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Application Information

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IPC IPC(8): G01R31/392G01R31/367G06N3/00
CPCG01R31/392G01R31/367G06N3/006
Inventor 王凯李强龙李强孙建瑞赵坤戴吉勇
Owner QINGDAO UNIV
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