Energy management of electric vehicles: Modelling and performance evaluation
This thesis presents a study on the energy consumption and energy management of three different battery electric vehicles (BEVs): Tesla Model 3 Long Range, Hyundai Kona Electric, and BYD Atto 3. These vehicles were chosen due to their differences in size, weight, and technical features. The goal was...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/440760 |
| Acceso en línea: | https://hdl.handle.net/2117/440760 |
| Access Level: | acceso abierto |
| Palabra clave: | Electric batteries--Mathematical models Electric vehicles--Batteries--Testing Bateries elèctriques--Models matemàtics Vehicles elèctrics--Bateries--Proves Àrees temàtiques de la UPC::Enginyeria elèctrica |
| Sumario: | This thesis presents a study on the energy consumption and energy management of three different battery electric vehicles (BEVs): Tesla Model 3 Long Range, Hyundai Kona Electric, and BYD Atto 3. These vehicles were chosen due to their differences in size, weight, and technical features. The goal was to examine how these characteristics affect energy use under standardised driving conditions. A simulation model was built in MATLAB Simulink using the Energetic Macroscopic Representation (EMR) method, which allows for clear tracking of energy flow and control. The New European Driving Cycle (NEDC) was used for both simulations and real-world driving tests to ensure comparability. The findings showed that vehicle shape and weight play a major role in overall efficiency. More compact and aerodynamic models used less energy, while larger SUV-type vehicles had higher consumption. Regenerative braking also proved effective in recovering energy, especially during high-speed deceleration. The simulation results were very close to real world data, confirming the reliability of the modelling approach. Overall, the research underlines the importance of energy-efficient design and smart control strategies in electric vehicles. The outcomes may help support future development of more sustainable mobility solutions. |
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