scholarly journals The energy-storage frontier: Lithium-ion batteries and beyond

MRS Bulletin ◽  
2015 ◽  
Vol 40 (12) ◽  
pp. 1067-1078 ◽  
Author(s):  
George Crabtree ◽  
Elizabeth Kócs ◽  
Lynn Trahey
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Image Position

Abstract

Si-doped high-energy Li1.2Mn0.54Ni0.13Co0.13O2 cathode with improved capacity for lithium-ion batteries

2018 ◽  
Vol 33 (24) ◽  
pp. 4182-4191 ◽  
Author(s):  
Leah Nation ◽  
Yan Wu ◽  
Christine James ◽  
Yue Qi ◽  
Bob R. Powell ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
High Energy ◽  
Si Doped ◽  
Image Position

Abstract

scholarly journals Accuracy improvement of SOC estimation in lithium-ion batteries by ANFIS vs ANN modeling of nonlinear cell characteristics

2021 ◽  
Author(s):  
Mohammad Hassan Amir Jamlouie
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Intelligent System ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Training Data ◽  
Accurate Estimation ◽  
Consumption Pattern ◽  
Load Prediction

Over the last century, the energy storage industry has continued to evolve and adapt to changing energy requirements. To run an efficient energy storage system two points must be considered. Firstly, precise load forecasting to determine energy consumption pattern. Secondly, is the correct estimation of state of charge (SOC). In this project there is a model introduced to predict the load consumption based on ANN implemented by MATLAB. The Designed intelligent system introduced for load prediction according to the hypothetical training data related to two years daily based load consumption of a residential area. For another obstacle which is accurate estimation of SOC, two separate models are provided based on ANN and ANFIS for Lithium-ion batteries as an energy storage system. There are several researches in this regard but in this project the author makes an effort to introduce the most efficient based on the MSE of each performance and as a result the method by ANN is found more accurate.

Elemental analysis of lithium ion batteries

2017 ◽  
Vol 32 (10) ◽  
pp. 1833-1847 ◽  
Author(s):  
Sascha Nowak ◽  
Martin Winter
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Elemental Analysis ◽  
State Of The Art ◽  
Electronic Devices ◽  
Lithium Ion ◽  
Promising Candidate ◽  
Decomposition Products ◽  
Power Sources ◽  
Large Size

Being successfully introduced into the market only 25 years ago, lithium ion batteries are already state-of-the-art power sources for portable electronic devices and the most promising candidate for energy storage in large-size batteries. Therefore, elemental analysis of lithium ion batteries (lithium ion batteries), their components and decomposition products is a fast growing topic in the literature.

Folding Graphene Film Yields High Areal Energy Storage in Lithium-Ion Batteries

ACS Nano ◽  
2018 ◽  
Vol 12 (2) ◽  
pp. 1739-1746 ◽  
Author(s):  
Bin Wang ◽  
Jaegeon Ryu ◽  
Sungho Choi ◽  
Gyujin Song ◽  
Dongki Hong ◽  
...  
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Graphene Film ◽  
Lithium Ion

scholarly journals Multifunctional energy storage composite structures with embedded lithium-ion batteries

2019 ◽  
Vol 414 ◽  
pp. 517-529 ◽  
Author(s):  
Purim Ladpli ◽  
Raphael Nardari ◽  
Fotis Kopsaftopoulos ◽  
Fu-Kuo Chang
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Composite Structures ◽  
Lithium Ion
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