Reconfigurable battery pack SOC estimation method based on rest recovery effect
The invention discloses a reconfigurable battery pack SOC estimation method based on a rest recovery effect, and the method comprises the steps: obtaining current data before a battery unit in a reconfigurable battery pack enters a rest state, SOC data when the battery unit enters the rest state, an...
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Format | Patent |
Language | Chinese English |
Published |
26.10.2021
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Abstract | The invention discloses a reconfigurable battery pack SOC estimation method based on a rest recovery effect, and the method comprises the steps: obtaining current data before a battery unit in a reconfigurable battery pack enters a rest state, SOC data when the battery unit enters the rest state, and voltage data within T seconds after the battery unit enters the rest state, and forming an original data set; performing data preprocessing to obtain a data matrix; building a convolutional neural network model to obtain a network model structure; dividing the data matrix into a training set and a test set, wherein the data of the training set is used for network training; evaluating the model by using the test set, outputting a neural network model if a condition is met, otherwise, returning to the previous step; and for the battery unit entering the rest state in the reconfigurable battery pack, collecting current data before the battery unit enters the rest state and voltage data within T seconds after the bat |
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AbstractList | The invention discloses a reconfigurable battery pack SOC estimation method based on a rest recovery effect, and the method comprises the steps: obtaining current data before a battery unit in a reconfigurable battery pack enters a rest state, SOC data when the battery unit enters the rest state, and voltage data within T seconds after the battery unit enters the rest state, and forming an original data set; performing data preprocessing to obtain a data matrix; building a convolutional neural network model to obtain a network model structure; dividing the data matrix into a training set and a test set, wherein the data of the training set is used for network training; evaluating the model by using the test set, outputting a neural network model if a condition is met, otherwise, returning to the previous step; and for the battery unit entering the rest state in the reconfigurable battery pack, collecting current data before the battery unit enters the rest state and voltage data within T seconds after the bat |
Author | CHEN SIZHE CHANG LE ZHANG YUN WANG YULE WANG YU |
Author_xml | – fullname: ZHANG YUN – fullname: CHANG LE – fullname: WANG YULE – fullname: WANG YU – fullname: CHEN SIZHE |
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DocumentTitleAlternate | 一种基于休息恢复效应的可重构电池组SOC估计方法 |
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RelatedCompanies | GUANGDONG UNIVERSITY OF TECHNOLOGY |
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Snippet | The invention discloses a reconfigurable battery pack SOC estimation method based on a rest recovery effect, and the method comprises the steps: obtaining... |
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Title | Reconfigurable battery pack SOC estimation method based on rest recovery effect |
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