Project Description

The objective of the EOBLi (Optimal Lithium Battery Packing) project is to develop a computational tool to facilitate the design of battery banks.

The problem is complex as the design objectives of lithium-ion battery banks compete with each other and are difficult to place in a single mathematical expression. To solve the optimization problem, the EOBLi project uses advanced multi-objective modeling techniques, which with the help of computational intelligence algorithms, allows obtaining the optimal lithium-ion battery bank designs. To obtain the function values, computational simulation software and advanced thermal and lifetime models are used. 

 

A fractal time thermal model for predicting the surface temperature of air-cooled cylindrical Li-ion cells based on experimental measurements (Journal of Power Sources 306, Febrero 2016).
Multi-objective optimal design of lithium-ion battery packs based on evolutionary algorithms (Journal of Power Sources 267, Noviembre 2014).

Project Description

The objective of the EOBLi (Optimal Lithium Battery Packing) project is to develop a computational tool to facilitate the design of battery banks.

The problem is complex as the design objectives of lithium-ion battery banks compete with each other and are difficult to place in a single mathematical expression. To solve the optimization problem, the EOBLi project uses advanced multi-objective modeling techniques, which with the help of computational intelligence algorithms, allows obtaining the optimal lithium-ion battery bank designs. To obtain the function values, computational simulation software and advanced thermal and lifetime models are used. 

 

A fractal time thermal model for predicting the surface temperature of air-cooled cylindrical Li-ion cells based on experimental measurements (Journal of Power Sources 306, Febrero 2016).
Multi-objective optimal design of lithium-ion battery packs based on evolutionary algorithms (Journal of Power Sources 267, Noviembre 2014).