THESIS WORKER - ROBUST ESTIMATION OF BATTERY ELECTRODE POTENTIAL
Descripción de la oferta de empleo
All thesis projects are arranged in business-critical areas and therefore you will be able to contribute to our company purpose – providing freedom to move in a safe, sustainable, and personal way – from day one! Background Battery safety and durability is limited by cell internal electro-chemical-thermal conditions related to on-set of degrading side-reactions.
The battery management system (BMS) implements algorithms to keep all the cells in the battery within these “healthy” limits based on primarily cell external electrical and thermal measurements together with empirical models of battery cell characteristics.
The models and measurements enable estimation of internal states and parameters like state-of-charge, power capability, cell capacity, and cell resistance in a computationally efficient way.
However, the limited connection to the underlying electro-chemistry can lead to suboptimal performance due to the large margins needed to keep all cells within their limits in all conditions.
To address this and improve battery performance, advanced battery models describing the electro-chemistry can be used to gain insights into when limiting side-reactions occur.
These models are often based on the Doyle-Fuller-Newman battery model and available in multiple tools, such as Comsol and PyBAMM.
While they offer insight into cell internal dynamics, they are too complex to use on-board a BMS.
In recent years, reduced order models with corresponding state and parameter tracking have been proposed.
This enables BMS functions based on electro-chemical constraints.
Scope In this master thesis we will investigate robust estimation of battery cell electrode potentials that is suitable for implementation in on-board BMS applications.
We will use a combination of models and tests in our battery lab to build an estimator that can handle cell-to-cell variations and changed cell characteristics as the battery ages.
Do you fit the profile You are currently enrolled as a student in the final year of a master’s degree in electrical engineering, physics, applied mathematics, or similar.
You need strong skills in mathematical modelling in suitable programming language (Matlab, Simulink, Python, or similar) and have knowledge in methods of automatic control and optimization.
Electro-chemical modelling and cell knowledge is a merit, but not mandatory.
The work will be conducted on-site at Volvo Cars with access to expertise and our battery lab.
Duration January to June points ECTS (academic credits) if in agreement with your Thesis Advisor in University This thesis is to be conducted by 2 students working in pair.
Be part of the change – apply today! Applications should include the given area and your thoughts and credentials.
We are continuously screening applications and will fill the position as soon as we find a good match.
So do not hesitate to send in your application.
Apply as soon as possible but no later than Please note that due to GDPR applications via email will not be accepted.
If you want more information about the project or simply learn a bit more about the team, please reach out to.
Björn Fridholm at Volvo Cars - Driving change together Volvo Cars’ success is the result of a collaborative, diverse, and inclusive working environment.
Today, we are one of the most well-known and respected car brands, with around employees across the globe.
At Volvo Cars, your career is designed around your skills and aspirations, allowing you to reach your fullest potential.
Detalles de la oferta
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- En todo México
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- 24/10/2024
- 22/01/2025
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