Battery Modeling, Management and Control
Batterier- modellering, styrning och reglering

EIEN85, 7.5 credits, A (Second Cycle)

Valid for: 2025/26
Faculty: Faculty of Engineering LTH
Decided by: PLED E
Date of Decision: 2025-03-27
Effective: 2025-05-05

General Information

Depth of study relative to the degree requirements: Second cycle, in-depth level of the course cannot be classified
Elective for: E4-el, F4, F4-es, N4, W5
Language of instruction: The course will be given in English

Aim

The course aims to provide students with a comprehensive understanding of battery technology and equip them with the knowledge and skills necessary to work with battery systems in various applications. The course ensures that students have a thorough understanding of battery technology, including its fundamental principles, components, and operation. The course builds the understanding of the designs and implementation of the effective battery management system including state of estimation (state of charge (SOC), state of health (SOH), state of power (SOP), etc.) and thermal management to ensure battery safe and efficient operation. The course enables students to design and implement control algorithms for battery-powered systems in various applications.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

• have a strong grasp of the fundamental principles of battery technology, including electrochemical processes, battery components, and performance metrics and understand how batteries work.
• be capable of developing accurate mathematical models for batteries and using simulation software to predict and analyze battery behaviour under various operating conditions.
•  be able to describe the functions and components of a battery management system (BMS), understand battery measuring, monitoring, state estimation, thermal management and safety control techniques to ensure battery safe and efficient operation effectively.
• master the knowledge and methods of battery testing, analysis and design. They could individually design, plan, and organize the battery test and analyze and present data results.
• be able to describe the functions, components and control methods for different battery applications.

Competences and skills
For a passing grade the student must

• should be proficient in using simulation tools (e.g., MATLAB/Python), know the optimization algorithms and master state estimation methods to create battery models and analyze battery performance.
• should have the competence to design and implement control algorithms and energy management strategies for batteries and their applications.
• should be able to apply their knowledge and skills to practical engineering projects, demonstrating the ability to solve real-world problems related to battery technology.

Judgement and approach
For a passing grade the student must

• be able to participate in discussions and judgement of relevant problems related to battery modeling, simulation, management and control.
• be able to present analysis about batteries both in a written way and orally.

Contents

Lectures and arithmetic exercises

Battery technology, components, and chemistry: battery types and applications, electrochemical reactions in batteries, anode, cathode and electrolyte materials.

Battery modeling: types of battery models (physical model, equivalent circuit model and hybrid model), electrochemical modeling principles, parameter estimation techniques, and model validations.

Battery Testing and Characterization: Battery testing methodologies, evaluation of battery performance and degradation, understanding impedance spectroscopy, and model validation and verification.

Battery management: Functions and components of a BMS, state estimation methods and techniques (SOC, SOH, SOP, and SOE), cell balancing and protection in BMS.

Battery thermal management and battery charging: thermal characteristics of batteries, thermal modeling of batteries, thermal runaway and safety, charging strategies, and optimal charging control.

Applications: Battery applications in electromobility, power systems and distributed energy systems with renewable energy sources (solar, wind, etc.), power electronics control, and energy management strategies for battery applications.

Simulation tasks and laboratory exercises

1. The parameter calibration for battery models with experimental data.
2. Battery SOC/SOH estimation with Kalman filter or machine learning.
3. Grid-connected battery system with power electronics and transformer.

Examination details

Grading scale: TH - (U, 3, 4, 5) - (Fail, Three, Four, Five)
Assessment:

Approved laborations and simulations. Written exam (5 h) with both problem solving and theoretical questions.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Modules
Code: 0125. Name: Written Exam.
Credits: 5.0. Grading scale: TH - (U, 3, 4, 5). Assessment: Approved written exam The module includes: Written exam
Code: 0225. Name: Laboratory and Simulation Exercises.
Credits: 2.5. Grading scale: UG - (U, G). Assessment: Approved laboratory work and written reports. The module includes: Approved laboratory work and written reports.

Admission

Assumed prior knowledge: EIEN75 Power Electronic Control and Design project, ESSF01 Analogue Circuits, ESS030, ESSF20 Physics of Devices, ESSF50 Electrical Engineering (E, W) or MIE012, EIEF35 Electrical Engineering, basic course (M) and FRT010, FRTF05 Automatic Control, Basic Course or FRTF11 Process control (W)
The number of participants is limited to: No

Reading list

• Plett, Gregory L: Battery management systems, Volume I: Battery modeling. Vol. 1. Artech House, 2015.

Contact

Course coordinator: Ferdinand Grimm, ferdinand.grimm@iea.lth.se
Course homepage: https://www.lth.se/iea/utbildning/valfria-kurser-i-lund