Modeling electric Vehicle's and improving battery lifetime using AI tools case study: Postal cars

Area of Science:

• Electrical Engineering
• Automotive Engineering
• Artificial Intelligence

Background:

• Electric vehicle (EV) development necessitates robust design evaluation.
• Simulation models mitigate risks and identify design flaws early.
• MATLAB and Simulink are key tools for EV simulation.

Purpose of the Study:

• To develop and present a simulation model for an electric postal car.
• To analyze the performance of a permanent magnet synchronous motor under a driving cycle.
• To optimize EV battery life and design using AI.

Main Methods:

• Simulated an electric postal car using MATLAB/Simulink.
• Modeled a permanent magnet synchronous electric motor.
• Applied a fuzzy controller for battery management.
• Analyzed torque, traction, resistance, and engine efficiency.

Main Results:

• Calculated required torque, traction, and resistance forces for a driving cycle.
• Determined engine efficiency and energy consumption from the battery.
• Demonstrated the effectiveness of a fuzzy controller in enhancing battery life monitoring.

Conclusions:

• Simulation and AI modeling are crucial for EV design, particularly motor and battery sizing.
• This approach supports environmental goals by reducing carbon emissions.
• The developed model aids in efficient electric postal car design and operation.