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Thermal predictive control for electric and hybrid powertrain

Ammar Alaa Mohamed Shebl Ali Salem

Thermal predictive control for electric and hybrid powertrain.

Rel. Stefano Carabelli. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2021

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Abstract:

In the modern era of electric vehicles battery design and management is of a significant importance for electric vehicles performance and development. Specifically, thermal management of battery pack since overheating is a main issue for cooling system design. In this thesis, a model-based design approach is used to design a battery pack as well as the cooling system regardless of cell type. In addition, model accuracy has been proved through an experiment performed using a module composed of 10 Samsung 94Ah cells in series. MATLAB Simulink has been used as a tool for performing analysis and calculations. Comparison was held between two different cells and the one with better thermal behaviour is selected. Furthermore, a battery management strategy implementing a more complicated control algorithm based on prediction of the future battery temperature is applied to avoid battery overheating in extreme situations by applying necessary changes in the inverter.

Relators: Stefano Carabelli
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 61
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/18610
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