Computer Aided Engineering of Batteries

Computer Aided Engineering of Batteries [electronic resource] / edited by Shriram Santhanagopalan. - 1st ed. 2023. - XI, 280 p. 1 illus. online resource. - Modern Aspects of Electrochemistry, 62 2197-7941 ; . - Modern Aspects of Electrochemistry, 62 .

Applications of Commercial Software for Lithium-Ion Battery Modeling and Simulation -- In situ Measurement of Current Distribution in Large-format Li-ion Cells -- Mesoscale Modeling and Analysis in Electrochemical Energy Systems -- Development of Computer Aided Design Tools for Automotive Batteries -- Experimental Simulations of Field Induced Mechanical Abuse Conditions -- Abuse Response of Batteries subjected to Mechanical Impact -- Accelerating Battery Simulations by using High Performance Computing and Opportunities with Machine Learning. .

This edited volume, with contributions from the Computer Aided Engineering for Batteries (CAEBAT) program, provides firsthand insights into nuances of implementing battery models in actual geometries. It discusses practical examples and gaps in our understanding, while reviewing in depth the theoretical background and algorithms. Over the last ten years, several world-class academics, automotive original equipment manufacturers (OEMs), battery cell manufacturers and software developers worked together under an effort initiated by the U.S. Department of Energy to develop mature, validated modeling tools to simulate design, performance, safety and life of automotive batteries. Until recently, battery modeling was a niche focus area with a relatively small number of experts. This book opens up the research topic for a broader audience from industry and academia alike. It is a valuable resource for anyone who works on battery engineering but has limited hands-on experience with coding.

9783031176074

10.1007/978-3-031-17607-4 doi


Electric batteries.
Materials.
Computer-aided engineering.
Fuel cells.
Electrochemistry.
Mathematical models.
Engineering--Data processing.
Batteries.
Computer-Aided Engineering (CAD, CAE) and Design.
Fuel Cells.
Electrochemistry.
Mathematical Modeling and Industrial Mathematics.
Data Engineering.

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