Master Thesis

Energy storage system (ESS) based on lithium-ion batteries is one of the most important but expensive and safety-critical components in the electrified powertrain. These batteries have complex nonlinear dynamics and need a battery management system (BMS) with advanced estimation and control algorithms to ensure their optimal performance and long lifetime. In this regard, the systems and control community have shown a lot of research interest in recent years.
The overall goal is to develop a knowledgebase to design adaptive-predictive BMS for optimal utilization of currently available cells to guarantee their long lifetime and safety. The core BMS function is to estimate battery internal state (state-of-charge [SOC], dynamic polarization, state-of-resistance [SoR], State-of-Capacity [SoQ] etc.) using voltage, current, temperature measurements as well as pre-determined cell parameters.
These cell parameters can be estimated under controlled environment using the adequate test methods or framework.


Suitable background
Of students: Two

Description of thesis work


To quickly characterize new cells for basic BMS modelling, a form of system identification framework is needed. This framework will aim at providing relevant stimuli to determine given parameters of the cell in a controlled environment. The framework shall also be able to analyze cell response and provide an estimation of the corresponding cell parameter by minimizing a cost function or an identification error.
The thesis will also consist in collecting data in a lab environment using optimal excitation vectors.
The main tasks are the following:
Develop and propose a system identification framework adapted for cell modeling along with a set of relevant stimuli/excitation.
Collect real cell data using the pre-defined excitation.
Evaluate framework performance against more traditional methods.

Thesis Level: Master

Language: English


Starting date: Spring 2023


Number of students: Two


Tutor


Huang Zhang, Industrial PhD, 0739022691


Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.