Energy storage systems (ESS) are known to be one of the key sub-systems of an electric vehicle (EV) in which determine a vehicle’s range, power, and speed. Additionally, they strongly impact the total cost of EVs as ESS is one of the most expensive sub-systems. Therefore, ESS efficiency has always been a topic of interest for research and product design.
High number of single Li-ion battery cells are connected to form a battery pack of an ESS. Battery management systems (BMS) are responsible to ensure efficient, safe, and reliable operation of every single cell onboard. To fulfill this goal, a BMS shall have deep and accurate knowledge of battery cells’ behavior to estimate and predict their states. This understanding is based upon how the cells are modelled, and what parameters do the models have.
The complexity of the task increases when the BMS is only provided with limited non-ideal sensor information in occasional time-window opportunities, with limited processing/memory hardware for states estimation. On top of cell voltage, current, and temperature measurements, electrochemical impedance spectroscopy (EIS) measurement capabilities are being introduced within the industry which can further help the BMS to identify the battery model parameters.
This thesis project focuses on proposing a fast, efficient, and accurate BMS algorithm to identify cell model parameters from impedance measurements coming from an EIS device
The selected candidate will be having the qualifications listed as
- Strong educational background in electrical, control, material science, or chemical engineering with adequate knowledge on control theory, nonlinear particle filtering, and system identification;
- High proficiency in MATLAB and Simulink;
- Fluency in English writing and speaking;
- Having self-motivation, researching skills and an independent problem-solving mind.
In addition to the points above, having a background on Li-ion battery modeling would be a merit.
Interested candidates can submit their applications with CV, Cover letter, and Transcripts of University Grades attached. Applications must be submitted through the portal.
For further questions and queries regarding the position, feel free to contact the thesis project supervisor
Description of thesis work
In general, and at major level, the thesis is supposed to be conducted to cover the milestones below
- To develop necessary knowledge on EVs, li-ion battery basics, and impedance spectroscopy through a comprehensive literature review, company knowledge material and training.
- Determination and development of suitable electrothermal battery cell models to be parametrized within the thesis, either in time domain or frequency domain.
- Devising the parameter identification algorithm both in theory, and in BMS simulation platforms available within the company.
- Designing of experiments to verify and validate the proposed algorithm against laboratory, field, or simulated measurements.
Thesis Title: Online Li-ion Battery Parameter Identification Using Electrochemical Impedance Spectroscopy Data
Thesis Level: Master
Starting date: 2024-01-14
Number of students: 2
Dr. Ashkan Pirooz
Control Engineer, +46 73 902 77 35
BMS Software and Controls
Department of Electromobility
Volvo Group Trucks Technology, CampX, Gothenburg, Sweden
Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.