Reprint

Battery Systems and Energy Storage beyond 2020

Edited by
February 2022
338 pages
  • ISBN978-3-0365-3025-3 (Hardback)
  • ISBN978-3-0365-3024-6 (PDF)

This is a Reprint of the Special Issue Battery Systems and Energy Storage beyond 2020 that was published in

Chemistry & Materials Science
Engineering
Physical Sciences
Summary

Currently, the transition from using the combustion engine to electrified vehicles is a matter of time and drives the demand for compact, high-energy-density rechargeable lithium ion batteries as well as for large stationary batteries to buffer solar and wind energy. The future challenges, e.g., the decarbonization of the CO2-intensive transportation sector, will push the need for such batteries even more.

The cost of lithium ion batteries has become competitive in the last few years, and lithium ion batteries are expected to dominate the battery market in the next decade. However, despite remarkable progress, there is still a strong need for improvements in the performance of lithium ion batteries. Further improvements are not only expected in the field of electrochemistry but can also be readily achieved by improved manufacturing methods, diagnostic algorithms, lifetime prediction methods, the implementation of artificial intelligence, and digital twins. Therefore, this Special Issue addresses the progress in battery and energy storage development by covering areas that have been less focused on, such as digitalization, advanced cell production, modeling, and prediction aspects in concordance with progress in new materials and pack design solutions.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
battery energy storage; renewable energy; distribution network; genetic algorithm; particle swarm optimization; electrolyte; additive; interface; pseudocapacitance; intercalation; energy storage; secondary battery; sodium-ion; lithium-ion battery; traction battery; waterjet-based recycling; direct recycling; life cycle assessment; global warming potential; lithium-ion battery; electro-thermal model; smart cell; intelligent battery; neural network; temperature prediction; lithium-ion battery; DRT by time domain data; pulse evaluation; relaxation voltage; online diagnosis; degradation mechanisms; EIS; lead batteries; safety concept; safety battery; battery monitoring; electronic battery sensor; failure modes; failure distribution; failure rates; field battery investigation; safe supply; power supply system; zinc ion batteries; stationary energy storage; polymer binder; solvent; doctor blade coating; manganese dioxide; mixing ratio; electrochemical impedance spectroscopy; SEM+EDX; electrode fabrication; lithium ion battery; AC current injection; bi-directional control; charger; lithium-ion battery cell; volumetric expansion; mechanical degradation; state of charge dependency; cell thickness; mechanical aging; non-uniform volume change; solar photovoltaic energy; redox flow battery; residential load; renewable energy integration; battery sizing; battery efficiency; lithium battery; temperature dependency; ether based electrolyte; insitu deposited lithium-metal electrode; Coulombic efficiency; lithium deposition morphology; Li-ion battery; thermal runaway; model; post-mortem analysis; ecofriendly electrolyte for lithium-ion batteries; increased thermal stability of electrolytes; enhanced electrolyte safety based on high flash point; tributylacetylcitrate; acetyltributylcitrate; electric vehicle battery; disassembly; disassembly planner design; disassembly strategy optimization; lithium-ion battery; battery management system; state monitoring; state-of-charge; digital twin; battery model; battery management system; Doyle-Fuller-Newman model; equivalent circuit model; parameter estimation; lithium-ion batteries; temperature estimation; sensorless temperature measurement; artificial intelligence; artificial neural network; lithium-ion cells; battery thermal management systems; CFD simulations; liquid cooling

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