Modelling of Electric Powertrain for Heavy-Duty BEV

Title

Modelling of Electric Powertrain for Heavy-Duty BEV

 Author

Abhay, Nived (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft DC systems, Energy conversion & Storage; TU Delft Electrical Sustainable Energy)

Contributor

Dong, J. (mentor) ORCID 0000-0003-2214-1472
Nouws, Simon (mentor)
Bauer, P. (mentor) ORCID 0000-0002-1171-9972
Rueda, José L. (graduation committee) ORCID 0000-0001-7288-0228

 Degree granting institution

Delft University of Technology

 Date

2020-08-25

 Abstract

The automotive industry plays a crucial role in battling the climate crisis and reducing emissions. Medium-duty and heavy-duty vehicles alone contribute to one-fourth of global emissions in the transport sector and there is a positive trend in the demand for these vehicles. Battery Electric Trucks have the potential to transform the growing logistics industry.

DAF Trucks N.V., one of the largest truck manufacturers in Europe, aims to transition to zero-emission vehicles and advance in this future of electric mobility. This project aims to model the powertrain of their CF Electric model and explore viable options for future designs. The thesis work can be defined in three parts.

The first part of the research focuses on modelling the electric powertrain in MATLAB/Simulink. Here, more focus is given in the calculation of individual motor and inverter losses. These losses are reverse engineered and extracted from the motor drive efficiency map using Particle Swarm Optimisation (PSO) algorithm.

The second part of the project focuses on performing sensitivity analysis to identify the key parameters that have the most influence on the energy efficiency of the Battery Electric Vehicle (BEV). This helps to prioritise and focus on optimisation of these parameters for future models. A comparison is drawn between the percentage change in the range each parameter has with small changes.

Lastly, in the third part of the thesis, different powertrain architectures are studied and modelled to under- stand their influence on the range of the BEV and the challenges involved in implementing such layouts.

 Subject

Battery Electric Vehicles
Modelling
Powertrain
Particle Swarm Optimization
Heavy duty vehicles
Sensitivity Analysis

 To reference this document use:

http://resolver.tudelft.nl/uuid:009a6801-cf71-4490-9046-326113bce762

 Embargo date

2022-08-25

 Part of collection

Student theses

 Document type

master thesis

 Rights

© 2020 Nived Abhay
Files
PDF Nived_Modelling_MScThesis_2020.pdf 13.95 MB
Close viewer