Power Electronics-Enabled Battery Management Systems for E-Mobility Applications: Energy Storage Systems
Translated title
Power Electronics-Enabled Battery Management Systems for E-Mobility Applications
Author
Term
4. term
Education
Publication year
2025
Submitted on
2025-05-27
Pages
29
Abstract
The adoption of electric vehicles has increased the demand for high performance and long lasting lithium-ion battery packs. This project investigates the development of a battery management system that uses active balancing through power electronic switches. The aim is to improve battery efficiency, safety, and longevity. The proposed method uses an artificial neural network to generate control signals for pulse width modulation of the switches. This enables dynamic management of both the state of charge and temperature across individual battery cells. A battery cell model is developed in MATLAB/Simulink, including state of charge estimation, open circuit voltage estimation, an equivalent circuit model, and a thermal model. These are then made into a modular battery pack model consisting of six cells. The artificial neural network control is trained to minimize deviations in state of charge and temperature, which it then uses to compute modulation signals for controlling the bypass switches. The simulation results show that effective balancing and convergence of both the state of charge and the temperature is done within 2500 seconds. A robustness test that included sensor noise up to ±10% is also made and it confirms the stability of the control. Furthermore, a virtual platform is used to validate the bypass method without involving real batteries. These results highlight the potential of using power electronic switches and a battery management system to improve battery performance, longevity, and efficiency in electric vehicle applications.
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