This paper focuses on developing a hybrid tool byusing the finite element method (FEM) and the neural networksto improve the electrodes design for Li-ion battery betterperformances ad its lifetime. A design methodology approachbased on a FEM based battery cell model is presented and appliedin conjunction with the design of a neural network to optimizethe electrodes design, in order to increase the usable capacityof a Li-ion battery over a range of charge-discharge currentrates. It can be use for understanding the inter-dependence ofchemical and mechanical degradation and coupling them to developa useful tool to predict battery life. The effect of size, shape,charging and discharging conditions and material properties ofelectrode on the battery output voltage and temperature are analyzed.
|Titolo:||A coupled design optimization methodology for Li-ion batteries in electric vehicle applications based on FEM and neural networks|
|Data di pubblicazione:||2014|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|