Description

Lithium-ion batteries have become the key energy storage technologies for various applications, such as electric vehicles, smart grids, or for enhancing renewables’ grid integration. This has become possible due to their superior characteristics in terms of gravimetric and volumetric energy density, efficiency, lifetime etc. Nevertheless, Lithium-ion batteries are highly non-linear energy storage devices with their performance and degradation (lifetime) behavior strongly influenced by the operating conditions (e.g., temperature, load current, number of cycles, idling time etc.). Therefore, to benefit from Lithium-ion batteries’ characteristics, precise knowledge about the performance and degradation behavior must be known at all moments during the lifetime.

This three-day course aims to provide an overview of the status of Lithium-ion batteries’ fundamentals and a deep understanding of their performance and degradation behavior. Different methods for battery performance (electrical) and degradation (lifetime) modeling will be introduced together with suitable parametrization approaches (from datasheet to laboratory experiments), respectively. These models will be subsequently used to introduce various Li-ion battery state-of-charge (SOC) and state-of health (SOH) estimation techniques.

Exemplifications of some of the discussed topics will be made through exercises in Matlab/Simulink. 

Find the detailed course program on PhD Moodle: https://phd.moodle.aau.dk/course/view.php?id=2186 

Prerequisites

Basic electrical engineering knowledge and basic experience with MATLAB/Simulink. 

Form of evaluation

Written individual report with solutions and comments for three exercises, which will be introduced during the course. 

Price

8000 DKK for the Industry and 6000 DKK for PhD students outside of Denmark (VAT-FREE Education)

The Danish universities have entered into an agreement that allows PhD students at a Danish university (except Copenhagen Business School) the opportunity to free of charge take a subject-specific course at another Danish university.
Read more here: https://phdcourses.dk/ 

Questions

hr@energy.aau.dk   

More information

https://www.energy.aau.dk/research/phd   

Course literature

1. Linden’s Handbook of Batteries, 5th edition, McGraw Hill (editor: Kirby Beard) – chapter 17
2. D.-I. Stroe, M. Swierczynski, A.-I. Stroe, S. K. Kær, “Generalized Characterization Methodology for Performance Modelling of Lithium-Ion Batteries,” Batteries 2016, 2, 37. https://doi.org/10.3390/batteries2040037 
3. D.-I. Stroe, M. Świerczyński, A. -I. Stan, R. Teodorescu and S. J. Andreasen, "Accelerated Lifetime Testing Methodology for Lifetime Estimation of Lithium-Ion Batteries Used in Augmented Wind Power Plants," in IEEE Transactions on Industry Applications, vol. 50, no. 6, pp. 4006-4017, Nov.-Dec. 2014, doi: 10.1109/TIA.2014.2321028. 
4. X. Sui, S. He, S. B. Vilsen, J. Meng, R. Teodorescu, D.-I. Stroe, “A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery,” Applied Energy, Volume 300, 2021, 117346, https://doi.org/10.1016/j.apenergy.2021.117346 

A complete list of references will be available one week prior to the course.