| KEYWORD |
Area Engineering
State of Charge and State of Health Estimation for EV Batteries
Thesis in external company
keywords BATTERY MANAGEMENT SYSTEM (BMS), DATA-DRIVEN MODELLING, ELECTRIC VEHICLES
Reference persons DANIELA ANNA MISUL, EZIO SPESSA
External reference persons MIRETTI Federico
Research Groups PT-ERC
Thesis type APPLIED RESEARCH
Description The first objective of the thesis is to develop a Dual Unscented Kalman Filter for the estimation of both state of charge and state of health of an EV battery cell, based on available experimental data. In a second step, you will explore methods to augment the data available to the filter with a data-driven model, in a hybrid approach.
See also ukf 2024-04-16 06_22_19.pdf
Required skills Matlab/Simulink, fundamentals of thermal machines, fundamentals of energy system control
Notes In the application, include your cv and the list of exams with score
Deadline 16/04/2025
PROPONI LA TUA CANDIDATURA