Thermal Analysis of PMSM-Driven Electric Vehicle Powertrain – MATLAB Simulink Simulation

Project Objective

Evaluate how electrical loading and drive-cycle demand translate into heat generation and temperature rise in a PMSM-driven EV powertrain, supporting thermal-limit, efficiency and cooling-system studies.

The page is written to help researchers move from a project title to a structured model, a defendable simulation methodology and a clear set of result graphs without claiming fixed performance before the final parameters are selected.

System Architecture and Main Blocks

• Driver and longitudinal vehicle-dynamics model
• Battery/DC source and traction inverter
• PMSM traction motor with torque-speed and efficiency behavior
• Mechanical transmission and wheel-load model
• Copper, iron, switching and conduction loss calculations
• Lumped thermal network for winding, stator, rotor/magnet, inverter and coolant nodes

MATLAB Simulink Methodology

1. Define vehicle mass, road load, gear ratio, motor ratings and drive-cycle speed reference.
2. Calculate inverter and PMSM losses from current, speed, torque and switching conditions.
3. Feed the loss terms into thermal capacitance and thermal-resistance networks.
4. Apply ambient and coolant boundary conditions and simulate over repeated or severe drive cycles.
5. Compare temperatures, losses and efficiency under baseline and improved cooling/control cases.

Recommended Simulation Scenarios

• Urban stop–start drive cycle
• Highway or high-speed operation
• Hill-climb/high-torque demand
• Cooling-flow or ambient-temperature variation
• Motor-sizing and current-limit comparison

Expected Outputs and Performance Metrics

• Vehicle speed and traction torque
• Battery power, inverter power and motor mechanical power
• Copper, iron, switching and conduction losses
• Winding, stator, magnet and inverter temperature
• Efficiency map trajectory and thermal-limit margin

Results should be plotted with labelled axes, units, reference signals and event times. Baseline and proposed-control cases should use the same operating conditions for a fair comparison.

Research Novelty and Extension Options

• Liquid-cooling or oil-spray cooling model
• Temperature-dependent PMSM parameters and demagnetization risk
• Thermal-aware torque derating controller
• Battery–inverter–motor integrated thermal management
• Drive-cycle optimization for energy and temperature reduction

Applications for PhD, Engineering Projects and FYP

• EV thermal-management PhD and master’s research
• Automotive engineering FYP and capstone projects
• PMSM sizing and thermal-limit evaluation
• Electric powertrain efficiency studies
• OEM-oriented model-based design and calibration

Suggested Report Structure

A strong report can include problem definition, literature review, governing equations, system block diagram, parameter table, controller design, simulation cases, result discussion, limitations, proposed novelty and future scope. Screenshots should be accompanied by technical interpretation rather than presented without explanation.