PhD Courses in Denmark

Welcome to Batteries: from fundamentals to applications (2025)

Description: Batteries play an undeniable role in the green transition, enabling the shift to renewable energy by storing and distributing power from intermittent sources like solar and wind. As demand for cleaner energy grows, trends point towards advancements in battery efficiency, energy density, and sustainability, driving widespread adoption of electric vehicles and stationary battery storage. While pivotal in modern technology, batteries present several significant challenges. One major issue is performance variability, which can be influenced by factors like temperature, usage patterns, and charging rates. Over time, all batteries degrade, losing capacity and efficiency due to electrochemical reactions within the cells. Accurately estimating the state of charge (SOC) is complex, often requiring sophisticated algorithms to provide reliable data, as simple voltage measurements can be misleading. Similarly, assessing the state of health (SOH) is crucial yet challenging; it involves tracking the battery’s aging process and predicting remaining useful life, which is influenced by various environmental and operational conditions. Lifetime prediction is another critical aspect, necessitating comprehensive models that account for all possible degradation mechanisms to ensure reliability and safety. Moreover, the degradation process can lead to issues such as reduced energy density, increased internal resistance, and potential safety hazards like thermal runaway. Balancing these factors while striving for longer-lasting, higher-performing batteries is an ongoing struggle for both researchers, manufacturers, and end-users.

All these aspects will be thoroughly covered in this comprehensive 5-day PhD course designed for beginner and intermediate learners in the field. The course will delve into the complexities of battery performance, degradation mechanisms, SOC and SOH estimation techniques, lifetime prediction models and battery operation in real-life applications. This intensive program aims to provide participants with the knowledge and skills necessary to tackle current challenges and drive future innovations in battery technology.

Key words: Batteries, Performance and Degradation, Electrochemistry, State Estimation, Electro-Thermal Modeling, Stationary Applications

Prerequisites: The participants should have knowledge and competencies comparable to those of an engineer with an MSc in electrical engineering. Furthermore, they should be familiar with MATLAB/Simulink or any other programming software (e.g., Python, C++, etc.) to complete the assignments. It is up to the course participants to decide which software they would like to use to complete the assignments.

Learning objectives: After successfully completing this PhD course, the participants will be able to:

• Identify the most suitable battery chemistry for specific applications, with respect to performance characteristics and lifetime expectations.
• Develop and parametrize battery performance (electrical and thermal) models utilizing battery data sheets and laboratory characterization tests.
• Select the appropriate SOC/SOH estimation algorithm based on the application-specific requirements (e.g., accuracy, computation complexity, etc.).
• Parametrize SOC and SOH algorithms using data obtained from laboratory performance characterization and lifetime testing.
• Understand the relationship between macro-scale battery degradation (e.g., capacity fade, resistance increase etc.) and micro-scale phenomena (e.g., lithium plating, mechanical cracking, SEI layer formation etc.) to inform battery lifetime estimation models.
• Utilize the battery models and state estimation algorithms in real-life battery operation scenarios.

Teaching methods: Lectures with active participation of the participants

Form of evaluation: Each participant should submit an individual report detailing the solution of all the assignments. The assignments are introduced during specific lectures and are to be solved by the course participants after the course. The report should be submitted no later than one month after the course is finished.

Criteria for assessment: To graduate the course, the participants should complete correctly at least 50% of each assignment.

Remarks: 84 hours (preparation based on the provided literature: 10 hours; lectures: 32 hours; solving of assignments: 26 hours; report writing: 16 hours)

Key literature: TBA

Organizer: Associate Professor Daniel-Ioan Stroe, dis@energy.aau.dk

Lecturers: 

Assoc. Prof. Daniel-Ioan Stroe (Section B)

Assoc. Prof. Erik Schaltz (Section D)

Assoc. Prof. Florin Iov (Section B)

Assoc. Prof. Tamas Kerekes (Section B)

Postdoc Yaqi Li (Section E)

Assist. Prof. Søren B. Vilsen (Department of Mathematics)

ECTS: 3.0

Time: 3, 4, 5, 6, 7 November 2025

Place: Aalborg University (Hybrid (AAU Energy in Aalborg & online by Teams))

Zip code: 9220

City: Aalborg

Maximal number of participants: 25

Deadline: 13 October 2025