Christian Davoli
Data-Driven Approaches for the design of Traction Electrical Motors.
Rel. Maurizio Repetto, Luigi Solimene, Simone Ferrari. Politecnico di Torino, Master of science program in Automotive Engineering, 2024
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (13MB) | Preview |
Abstract
In the last decades, the automotive industry has fostered the integration of electrical machines into vehicle's powertrain. The legislation regarding the environmental pollution is becoming more and more stringent, till to the point in which the classical internal combustion engines will not be compliant anymore. Consequently, Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) are designed depending on the level of integration of the electrical machine in the powertrain. This trend has increased the necessity to design effective electrical machines that are not only efficient but also cost-effective and powerful. Their design is therefore challenging and often requires extensive multi-physics considerations.
For example, high Torque requires higher current, but this also leads to more complex cooling system
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
URI
![]() |
Modify record (reserved for operators) |
