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    System and method for estimating long term characteristics of battery
    4.
    发明授权
    System and method for estimating long term characteristics of battery 有权
    估计电池长期特性的系统和方法

    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

    IPC分类号： G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00 ,  G01R31/36 ,  G06N7/00

    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。

    System and method for estimating long term characteristics of battery
    5.
    发明授权
    System and method for estimating long term characteristics of battery 有权
    估计电池长期特性的系统和方法

    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。

    Redox-active polymers and their applications
    6.
    发明授权
    Redox-active polymers and their applications 有权
    氧化还原活性聚合物及其应用

    公开(公告)号：US08435696B2

    公开(公告)日：2013-05-07

    申请号：US12905398

    申请日：2010-10-15

    申请人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    发明人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    IPC分类号： H01M8/10

    CPC分类号： H01M8/16 ,  H01M4/8807 ,  H01M4/8853 ,  H01M4/9008 ,  Y02E60/527

    摘要： The present invention is directed to a redox-active, conducting polymer energy storage system, said system including an electrode and a counter electrode, wherein the electrode comprises a first conducting polymer and the counter electrode comprises a second conducting polymer, wherein the first conducting polymer is doped by at least one or more first redox-active compounds and/or by a polymer and/or a co-polymer of the one or more first redox-active compounds and the second conducting polymer is doped by at least one or more second redox-active compounds and/or by a polymer and/or a co-polymer of the one or more second redox-active compounds, and wherein there is a potential difference between the dopant for the electrode and the dopant for the counter electrode. In one preferred embodiment, the first or the second redox-active compound is 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS). In another preferred embodiment, an exemplary redox-active compound is a polymerizable derivative of ABTS or a polymer or co-polymer of this monomer.

    摘要翻译： 本发明涉及氧化还原活性导电聚合物储能系统，所述系统包括电极和对电极，其中所述电极包括第一导电聚合物，所述对电极包括第二导电聚合物，其中所述第一导电聚合物 由至少一种或多种第一氧化还原活性化合物和/或通过一种或多种第一种氧化还原活性化合物和第二导电聚合物的聚合物和/或共聚物掺杂至少一个或多个第二 氧化还原活性化合物和/或一种或多种第二种氧化还原活性化合物的聚合物和/或共聚物，并且其中在电极的掺杂剂和对电极的掺杂剂之间存在电位差。 在一个优选的实施方案中，第一或第二氧化还原活性化合物是2,2'-氮杂双（3-乙基苯并噻唑啉-6-磺酸盐）（ABTS）。 在另一个优选的实施方案中，示例性氧化还原活性化合物是ABTS的可聚合衍生物或该单体的聚合物或共聚物。

    SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY
    7.
    发明申请
    SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY 有权
    用于估计电池长期特性的系统和方法

    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。

    REDOX-ACTIVE POLYMERS AND THEIR APPLICATIONS
    8.
    发明申请
    REDOX-ACTIVE POLYMERS AND THEIR APPLICATIONS 有权
    氧化还原活性聚合物及其应用

    公开(公告)号：US20110031440A1

    公开(公告)日：2011-02-10

    申请号：US12905398

    申请日：2010-10-15

    申请人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    发明人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    IPC分类号： H01B1/12

    CPC分类号： H01M8/16 ,  H01M4/8807 ,  H01M4/8853 ,  H01M4/9008 ,  Y02E60/527

    摘要： The present invention is directed to a redox-active, conducting polymer energy storage system, said system including an electrode and a counter electrode, wherein the electrode comprises a first conducting polymer and the counter electrode comprises a second conducting polymer, wherein the first conducting polymer is doped by at least one or more first redox-active compounds and/or by a polymer and/or a co-polymer of the one or more first redox-active compounds and the second conducting polymer is doped by at least one or more second redox-active compounds and/or by a polymer and/or a co-polymer of the one or more second redox-active compounds, and wherein there is a potential difference between the dopant for the electrode and the dopant for the counter electrode. In one preferred embodiment, the first or the second redox-active compound is 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS). In another preferred embodiment, an exemplary redox-active compound is a polymerizable derivative of ABTS or a polymer or co-polymer of this monomer.

    摘要翻译： 本发明涉及氧化还原活性导电聚合物储能系统，所述系统包括电极和对电极，其中所述电极包括第一导电聚合物，所述对电极包括第二导电聚合物，其中所述第一导电聚合物 由至少一种或多种第一氧化还原活性化合物和/或通过一种或多种第一种氧化还原活性化合物和第二导电聚合物的聚合物和/或共聚物掺杂至少一个或多个第二 氧化还原活性化合物和/或一种或多种第二种氧化还原活性化合物的聚合物和/或共聚物，并且其中在电极的掺杂剂和对电极的掺杂剂之间存在电位差。 在一个优选的实施方案中，第一或第二氧化还原活性化合物是2,2'-氮杂双（3-乙基苯并噻唑啉-6-磺酸盐）（ABTS）。 在另一个优选的实施方案中，示例性氧化还原活性化合物是ABTS的可聚合衍生物或该单体的聚合物或共聚物。

    Redox-active polymers and their applications
    9.
    发明授权
    Redox-active polymers and their applications 有权
    氧化还原活性聚合物及其应用

    公开(公告)号：US07838687B2

    公开(公告)日：2010-11-23

    申请号：US11512430

    申请日：2006-08-29

    申请人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    发明人： G. Tayhas R. Palmore ,  Jiangfeng Fei ,  Hyun-Kon Song

    IPC分类号： C07D293/00 ,  C07D417/02

    CPC分类号： H01M8/16 ,  H01M4/8807 ,  H01M4/8853 ,  H01M4/9008 ,  Y02E60/527

    摘要： The present invention provides a monomer comprising the structure: wherein R1 and/or R1′ are selected from the group consisting of MeO, EtO, COF3, SO4H, SO3−, SO3H, H, CHNO4S2F3, C5H4N2O6S2F6, C10H10N4S2, CH3, n-Bu, Cl, NH2, EtN, Br, alkyl, ether, ester, sulfonate, ammonium, carboxylate, phosphonate and any combination thereof, R2 and/or R2′, are selected from the group consisting of EtO, SO3H, H, C10H10N4S2, CH3, Cl, C6H14N2S and any combination thereof, R3 and/or R3′ are selected from the group consisting of CH3, Cl, H and any combination thereof, and R4 and/or R4′ are selected from the group consisting of CH3, H, C2H5, C4H9, C6H5, C8H17, C2H5S, C3H7S, C4H8Br, C10H23N, C20H21N2, C18H25N2, C21H23N2, C31H29N2O2, C22H25N4, C20H25N2, C3H7OS, and any combination thereof.

    摘要翻译： 本发明提供一种包含以下结构的单体：其中R1和/或R1'选自MeO，EtO，COF3，SO4H，SO3-，SO3H，H，CHNO4S2F3，C5H4N2O6S2F6，C10H10N4S2，CH3，n-Bu ，Cl，NH2，EtN，Br，烷基，醚，酯，磺酸盐，铵，羧酸盐，膦酸盐及其任何组合，R2和/或R2'选自EtO，SO3H，H，C10H10N4S2，CH3 ，Cl，C 6 H 14 N 2 S及其任何组合，R 3和/或R 3'选自CH 3，Cl，H及其任何组合，并且R 4和/或R 4'选自CH 3，H， C2H5，C4H9，C6H5，C8H17，C2H5S，C3H7S，C4H8Br，C10H23N，C20H21N2，C18H25N2，C21H23N2，C31H29N2O2，C22H25N4，C20H25N2，C3H7OS及其任意组合。

    SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY
    10.
    发明申请
    SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY 有权
    用于估计电池长期特性的系统和方法

    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

    IPC分类号： G06N3/08 ,  G06F3/048 ,  G01R31/36 ,  G06F19/00

    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。