Electrical Engineering

Welcome to the master thesis presentation&nbsp; &nbsp;&nbsp; Hybrid Modeling of High-Voltage Battery Systems for Software Control&nbsp; by Felix Gråhn and Jakob Hogander &nbsp; &nbsp;&nbsp; Conducted at Volvo Cars Corporation supervised by Leonardo Amato&nbsp; &nbsp; &nbsp;&nbsp; Tuesday, February 25, 15:00-16:00, Fredrik Lamms room, Chalmers Electric Power Engineering division&nbsp; &nbsp;&nbsp; Opponents: Arvid Moänge &amp; Philip Liseau &nbsp;&nbsp; Abstract&nbsp; In recent years, electric vehicles have taken up a greater part of the automotive industry. This thesis investigated the potential of using a hybrid approach to modeling the behavior of batteries used in electric vehicles on pack level. Using existing models, both empirical and physics-based, to create a model meant for software control. The aim was to find a way to model the aging of batteries and control the battery pack based on internal electrochemical dynamics but at a lower computational load than that of fully physics-based modeling.&nbsp;
During the project, it was shown that the use of a hybrid model to simulate batteries on pack level is a working method that possesses the ability to control on the basis of physics-based dynamics of the batteries. Using a physics-based controller for fast charging of the battery pack was also shown to decrease fast charging time 18 \% compared to using a fast charging protocol based on testing. This was able to be done without compromising the risks of aging. It was also shown that one can not only use the model to evaluate the performance of aged batteries, but also be able to see the aging effects that a given use of the battery has. The hybrid model was also found to operate on a substantially lower computational load. compared to a fully physical-based model, making it possible to run longer simulations.
Welcome!&nbsp; &nbsp;&nbsp; Felix, Jakob and Torbjörn

Welcome to the master thesis presentation 
Hall E-Smart Palm Sensor for Autonomous&nbsp;Home-Based Hand Rehabilitation by Magdalena Putrym and Rahul Rajagopalan Monday, March 10, 17:00-19:00,&nbsp;
Room 3364 EDIT, Hörsalsvägen 11 Examiner: Emmanuel Dean
Opponents: Joel Trollheden and Hasan Sharineh Abstract
Hand rehabilitation is an important process for restoring functionality and quality of life, targeting injuries such as "avocado hand", with tendon or nerve damage. This thesis presents the design and development of a tactile sensor plate based on Hall-effect sensors, specifically the MLX90393, to supervise home-based hand rehabilitation. The primary goal is to design a sensor plate able to perform precise measurement of force magnitude and direction during rehabilitation exercises, providing real-time feedback to users for effective guidance, and by this, minimising the risk of incorrect movements.
The tactile sensor plate design includes a matrix of 48 Hall-effect sensors, and one Inertial Measurement Unit, embedded within a compact, silicone-coated plate designed for comfort, durability, and ease of&nbsp; cleaning. By collecting sensor data at a sampling rate of 100 Hz, the plate is capable of estimating both&nbsp; normal and shear forces, important for understanding and guiding hand movements. A machine learning Random Forest model was developed to process sensor data and predict applied force parameters. The results demonstrate the sensor plate’s ability to measure force magnitudes and directions with high accuracy, achieving an R2 value of approximately 96% for force prediction in specific test cases.
The research addresses challenges such as hysteresis caused by the silicone layer, calibration for diverse hand sizes, and environmental conditions like magnetic field variations. The system architecture, built on a Raspberry Pi 5 as a main processing unit, opens possibilities for future enhancements, including the&nbsp; integration of additional sensors and improved calibration methods. This study contributes to the field of rehabilitation technology by offering an accessible solution for hand rehabilitation. The proposed system can estimate the applied force making a foundation for supporting guided exercises, allowing a better recovery process, and reducing dependence on physiotherapists. It also aligns with sustainable design principles. Future work will focus on enhancing sensor accuracy, refining the graphical user interface, and expanding the system’s applicability to broader rehabilitation scenarios.
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Welcome!
Magdalena, Rahul and Emmanuel
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Presentation of master thesis

Master thesis presentations at Electrical Engineering

25 February, 2025

15.00-16.00 Felix Gråhn and Jakob Hogander, MPEPO

10 March, 2025

17.00-19.00 Magdalena Putrym and Rahul Rajagopalan, MPSYS