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Study and Development of Advanced Core Communication and Memory Management Techniques for Real-Time Battery Electric Vehicle (BEV) Applications

Giuseppe Di Carolo

Study and Development of Advanced Core Communication and Memory Management Techniques for Real-Time Battery Electric Vehicle (BEV) Applications.

Rel. Sarah Azimi, Luca Sterpone. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023

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Abstract:

This thesis focuses on the optimization of electric motor control for battery electric vehicles (BEVs) by leveraging Direct Memory Access (DMA)-based core communications. Various procedures were studied, tested, and compared to determine the most suitable approach to meet the operating specifications of the target study. The first thesis activity involved a comprehensive examination of state-of-the-art data transfer techniques found in the scientific literature with the objective of discerning advantages and disadvantages within the context of hard real-time systems. Simultaneously, an in-depth exploration of the memory modules and communication components of the AURIX™ TriBoard TC399 was conducted, complemented by practical experimentation. The DMA constituted the main focus of the research alongside its configurations, which not only offer enhanced flexibility but also relieve the cores from the burden of data copying at the expense of an increased initial programming overhead. In the concluding part of this work, the acquired knowledge was translated into practical application through the development of C-code programs using the ”Aurix Development Studio” platform. These programs were designed to implement various strategies. The outcomes of these implementations were compared to identify the approach that best aligns with the specified requirements.

Relators: Sarah Azimi, Luca Sterpone
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 72
Subjects:
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/28513
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