Lg Chem, Ltd

Brown University

Hyun-Kon Song

Jeong-Ju Cho

Ho-Chun Lee

G Tayhas R Palmore

Mi-Young Son

Yeon-Uk Choo

Jiangfeng Fei

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.

System and method for estimating long term characteristics of battery

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.

Redox-active polymers and their applications

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.

The present invention provides a monomer comprising the structure: wherein Rand/or R' are selected from the group consisting of MeO, EtO, COF, SOH, SO3, SOH, H, CHNOSF, CHNOSF, CHNS, CH, n-Bu, Cl, NH, EtN, Br, alkyl, ether, ester, sulfonate, ammonium, carboxylate, phosphonate and any combination thereof, Rand/or R&#x2032;, are selected from the group consisting of EtO, SOH, H, CHNS, CH, Cl, CHNS and any combination thereof, Rand/or R&#x2032; are selected from the group consisting of CH, Cl, H and any combination thereof, and Rand/or R&#x2032; are selected from the group consisting of CH, H, CH, CH, CH, CH, CHS, CHS, CHBr, CHN, CHN, CHN, CHN, CHNO, CHN, CHN, CHOS, and any combination thereof.

Growing community of inventors

Daejeon, South Korea

Hyun-Kon Song