Cell and Systems Modelling
Syllabus, Master's level, 1KB720
- Code
- 1KB720
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Battery Technology A1F, Chemistry A1F, Technology A1F
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 2 March 2022
- Responsible department
- Department of Chemistry - Ångström
Entry requirements
180 credits, including 100 credits in science/engineering. Participation in Applied Electrochemistry, 10 credits. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Learning outcomes
On completion of the course, the student should be able to:
- construct electrochemical models for simulation of the response in batteries and fuel cells, and identify the most critical parameters for prediction,
- use relevant software to simulate Li-ion battery charge/discharge curves, cell resistance and impedance,
- report on strengths and shortcomings of the finite element methodology and equivalent circuit modelling for battery simulations,
- analyze the performance in batteries by simulation-experiment comparison,
- implement equivalent circuit models to simulate the electrochemical behaviours of battery modules and packs,
- explain how artificial intelligence and machine learning methods can be used in battery simulations.
Content
General construction of physical electrochemical models of cells: simulation of reaction kinetics, mass transport, electric conductivity. Boundary conditions. Integration of materials properties into electrochemical models. Modelling of mass transport. Time dependent 1D, 2D and 3D cell modelling using finite element methodology. Simulation of battery data and correlation with experiment, as applied to Li-ion batteries. Simulation of other battery types than Li-ion and fuel cells. Equivalent electric circuit modelling of battery cells, module and systems. Comparisons of different modelling techniques. Introduction to relevant software (Comsol, Simulink), application of machine learning tools and multi-scale modelling.
Instruction
Lectures, classes and computer laboratory work.
Assessment
Written examination at the end of the course (3 credits). Laboratory course (2 credits).
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.
Reading list
No reading list found.