Thesis work: 30hp - Modelling Inhomogeneous Degradation in Commercial Li-ion Batteries

Introduction
Thesis work is an excellent way to get closer to Traton and build relationships with industries for the future. Many of today's employees began their Scania/Traton career with their degree project.

Background 
Are you passionate about contributing to electrification and batteries? This master's thesis project aims to develop an advanced three-dimensional electrochemical model of a lithium-ion battery cell based on the Doyle–Fuller–Newman (DFN) framework. The modelling part of the project will be conducted and supported primarily by KTH and the post mortem part will be primarily supported by Traton AB 

Objective 

1. To develop a 3D electrochemical model (P4D) based on the Doyle-Fuller-Newman framework that incorporates spatially distributed parameters representing electrode heterogeneity in an aged Li-ion cell.
2. To integrate OLSA-derived post-mortem data (LLI and LAM) into the model as spatially varying inputs, enabling a realistic representation of degradation across the jellyroll.
3. To correlate model predictions with experimental cycling data at end-of-test (EoT), evaluating whether distributed parameter modelling improves accuracy over conventional lumped models.
4. To quantify the impact of heterogeneous degradation (LLI and LAM) on overall cell performance and local electrochemical behaviour.
5. To assess the feasibility of linking post-mortem measurements with electrochemical model parameters, providing a framework for predictive ageing simulations.
   
   
   

Job description 
This thesis aims to develop an advanced three-dimensional electrochemical model of a lithium-ion battery cell based on the Doyle–Fuller–Newman (DFN) framework. The project will integrate spatially resolved post-mortem data from the OLSA (OCP-based Local SOH Assessment) method to represent heterogeneous degradation — specifically Loss of Lithium Inventory (LLI) and Loss of Active Material (LAM) — across the jellyroll.

The model will be used to investigate the relationship between spatial degradation patterns and overall cell performance at end-of-life, and to evaluate whether distributed-parameter modelling improves predictive accuracy compared to lumped DFN models. The project will be conducted jointly between KTH and Traton AB, combining modelling and post-mortem analysis activities.

Education/program/focus
Indicate education, program or focus: in the final year of a Master’s program in Chemistry, Chemical Engineering, Materials Science and Energy engineering. Indicate any previous experience / interest with modelling and simulations. Experience with R, Python, MATLAB, or COMSOL Multiphysics is highly desirable. Familiarity with Li-ion cell principals and degradation mechanisms is a plus.
Analytical, self-driven, and able to work independently in a research environment

Number of students: 1
Start date for the thesis work: January, 2026
Estimated time required: until June, 2026

Contact persons and supervisors
Traton Supervisor: Aamer Siddiqui, Industrial PhD, Material Technology, Traton SE AB
Academia supervisor: Gian Marco Trippetta, PhD at Applied Electrochemistry KTH, Examiner: Göran Lindbergh Professor, Head of Department of Applied Electrochemistry KTH

Application:
Your application must include a CV, personal letter and transcript.
For questions, please contact Aamer Siddiqui, PhD, aamer.siddiqui@scania.com and Öystein Krogen, PhD, oystein.krogen@scania.com.

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.   

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