2020.10.26-28 PhD course ‘Lithium-Ion Batteries. Fundamentals, Modelling, and State Estimation’

Description: Lithium-ion batteries have become the key energy storage technologies for various applications, such as electric vehicles, microgrids, (nano-)satellites, 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 (electrical) and degradation (lifetime) behavior strongly influenced by the operating conditions (e.g., temperature, load current, number of cycles, idling time etc.). Therefore, in order to benefit from Lithium-ion batteries’ characteristics, precise knowledge about the performance and degradation behavior has to be known at all moments during the lifetime. Thus, this three-day course provides 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 data-sheet 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.


  • Day 1: Energy storage technologies and Lithium-ion batteries – Daniel Stroe (8 hours)
    • Overview of energy storage technologies
    • Lithium-ion battery construction and operation
    • Lithium-ion battery chemistries
    • Performance parameters for Lithium-ion batteries (capacity, resistance, power, efficiency etc.)
    • Influence of operating conditions (e.g., load current/power, temperature etc) on the performance parameters of the Lithium-ion batteries
  • Day 2: Electrical modeling of Lithium-ion batteries – Daniel Stroe & Vaclav Knap (8 hours)
    • Laboratory testing of Lithium-ion batteries for electrical and lifetime modeling
    • Approaches for battery electrical modeling
    • Parametrization of Lithium-ion battery modeling
    • Thevenin-based Lithium-ion battery electrical models
    • Impedance-based Lithium-ion battery models
  • Day 3: Lifetime and state estimation of Lithium-ion batteries – Daniel Stroe, Erik Schaltz, Vaclav Knap (8 hours)
    • Aging mechanisms of Lithium-ion batteries
    • Performance-degradation of Lithium-ion batteries
    • Lifetime modeling approaches for Lithium-ion batteries
    • State-of-Charge and State-of-Health estimation of Lithium-ion batteries

Prerequisites: Fundamental (basic) electrical knowledge, an engineering degree, and Matlab/Simulink and Matlab/Simulink knowledge are strongly recommended. The course language is English.

Form of evaluation: Students are expected to solve a number of exercises and deliver an individual report with solutions and comments.

Course info

  • Organizer: Assoc. Prof. Daniel Stroe, Aalborg University
  • Lecturers: Assoc. Prof. Daniel Stroe, dis@et.aau.dk, Assoc. Prof. Erik Schaltz, esc@et.aau.dk, Aalborg University, Dr. Vaclav Knap, vkn@et.aau.dk, GomSpace
  • ECTS: 3.0
  • Date/Time: 26 – 28 October 2020
  • Location: Aalborg University, Department of Energy Technology, Aalborg, Denmark
  • Registration: https://www.et.aau.dk/phd/

Permanent link to this article: http://batteriselskab.dk/arrangementer/2020-10-26-28-phd-course-lithium-ion-batteries-fundamentals-modelling-and-state-estimation.htm