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公开(公告)号：US20110191278A1
公开(公告)日：2011-08-04
申请号：US12674647
申请日：2008-08-21
申请人： Hyun-Kon Song , Jeong-ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06N3/08
CPC分类号： G01R31/3651 , G06N7/00
摘要： A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.
摘要翻译： 一种用于估计电池的长期特性的系统包括用于接收作为学习对象的电池的初始特征学习数据和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为用于估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络操作单元，用于从学习数据输入单元接收初始特征学习数据和长期特征学习数据，以允许学习人造神经网络，从测量数据输入单元接收初始特征测量数据并应用 从而从电池的初始特性测量数据计算长期特征估计数据并输出长期特征估计数据。
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公开(公告)号：US20100312733A1
公开(公告)日：2010-12-09
申请号：US12678094
申请日：2008-09-12
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
CPC分类号： H01M10/482 , G01R31/3651 , G01R31/3679 , H01M10/48
摘要： A system includes a learning data input unit for receiving initial and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for long term characteristic estimation; an artificial neural network operation unit for converting the learning data into first and second data structures, allowing an artificial neural network to learn the learning data based on each data structure, converting the measurement data into first and second data structures, and individually applying the learned artificial neural network corresponding to each data structure to calculate and output long term characteristic estimation data based on each data structure; and a long term characteristic evaluation unit for calculating an error of the estimation data of each data structure and determining reliability of the estimation data depending on error.
摘要翻译： 一种系统，包括用于接收作为学习对象的电池的初始和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为长期特性估计对象的电池的初始特性测量数据; 一种用于将学习数据转换为第一和第二数据结构的人造神经网络操作单元，允许人造神经网络基于每个数据结构学习学习数据，将测量数据转换为第一和第二数据结构，以及单独应用所学习的 对应于每个数据结构的人工神经网络，基于每个数据结构计算和输出长期特征估计数据; 以及长期特征评估单元，用于计算每个数据结构的估计数据的误差，并根据误差确定估计数据的可靠性。
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公开(公告)号：US09255973B2
公开(公告)日：2016-02-09
申请号：US12674647
申请日：2008-08-21
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
CPC分类号： G01R31/3651 , G06N7/00
摘要： A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.
摘要翻译： 一种用于估计电池的长期特性的系统包括用于接收作为学习对象的电池的初始特征学习数据和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为用于估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络操作单元，用于从学习数据输入单元接收初始特征学习数据和长期特征学习数据，以允许学习人造神经网络，从测量数据输入单元接收初始特征测量数据并应用 从而从电池的初始特性测量数据计算长期特征估计数据并输出长期特征估计数据。
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公开(公告)号：US08412658B2
公开(公告)日：2013-04-02
申请号：US12678094
申请日：2008-09-12
申请人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
发明人： Hyun-Kon Song , Jeong-Ju Cho , Yeon-Uk Choo , Mi-Young Son , Ho-Chun Lee
IPC分类号： G06N3/08
CPC分类号： H01M10/482 , G01R31/3651 , G01R31/3679 , H01M10/48
摘要： A system includes a learning data input unit for receiving initial and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for long term characteristic estimation; an artificial neural network operation unit for converting the learning data into first and second data structures, allowing an artificial neural network to learn the learning data based on each data structure, converting the measurement data into first and second data structures, and individually applying the learned artificial neural network corresponding to each data structure to calculate and output long term characteristic estimation data based on each data structure; and a long term characteristic evaluation unit for calculating an error of the estimation data of each data structure and determining reliability of the estimation data depending on error.
摘要翻译： 一种系统，包括用于接收作为学习对象的电池的初始和长期特征学习数据的学习数据输入单元; 测量数据输入单元，用于接收作为长期特性估计对象的电池的初始特性测量数据; 一种用于将学习数据转换为第一和第二数据结构的人造神经网络操作单元，允许人造神经网络基于每个数据结构学习学习数据，将测量数据转换为第一和第二数据结构，以及单独应用所学习的 对应于每个数据结构的人工神经网络，基于每个数据结构计算和输出长期特征估计数据; 以及长期特征评估单元，用于计算每个数据结构的估计数据的误差，并根据误差确定估计数据的可靠性。
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