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The principal outcome of the research is to deliver experimental and modelling framework targeted for both EV and next-generation smart grid application developer. The results of the research assist in providing a correct datasheet for a battery cell. It is a result of an experimental framework that is comprised of systematic performance assessment methodology. The method is generic, so it applies to all Li-ion battery cell with necessary adaptation. The research aspires to answer whether the ultimate optimal battery selection from different options is achievable or not. To accomplish the…mehr

Produktbeschreibung
The principal outcome of the research is to deliver experimental and modelling framework targeted for both EV and next-generation smart grid application developer. The results of the research assist in providing a correct datasheet for a battery cell. It is a result of an experimental framework that is comprised of systematic performance assessment methodology. The method is generic, so it applies to all Li-ion battery cell with necessary adaptation. The research aspires to answer whether the ultimate optimal battery selection from different options is achievable or not. To accomplish the goal, both experimentation and modelling approach are employed-each one represents distinct benefits with relative advantages. This is largely possible as an advanced multiphysics modelling method is used. It is complemented by meticulous measurements using the unique isothermal calorimetric technique. Using the developed methodology, it enables to determine how the current input affects the heat flux generation inside a battery cell and how it is possible to find the key performance indicator (KPI) efficiency.
Autorenporträt
Mohammad Rezwan Khan received his PhD from the Department of Energy Technology, Aalborg University, Denmark. He previously worked on MOBI research group, VUB and VITO, Belgium. His current research focuses include various characteristics and optimisations of the battery system.