- Overview
- Engineering Solutions (scroll-down for details)
- Range Estimation for Electric Vehicle,
- Size Battery for Electric Vehicle,
- Analyze Thermal Durability for PMSM,
- Motor Inverter Loss Map Generation,
- Estimate Inverter Power Module End of Life,
- Select Gear Ratio for Electric Vehicle, and
- Build Virtual Sensor for BMS.
- Utilities
- Prerequisites
- Setup
Most modern EV are powered by Li-ion based battery chemistry and electric drivetrains with permanent magnet synchronous motors (PMSM) and/or induction motors. Modeling and simulation helps you design vehicles that meet the desired range on the road and perform under all environmental conditions. This project contains Simscape™ based workflows and utilities that help you create different vehicle platforms and analyze their components as well as the overall system.
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Estimate the on-road range of the vehicle. Run drive cycles with different ambient conditions to determine the range of the vehicle with a given capacity. See Workflow/Vehicle/RangeEstimation. |
| Size your high-voltage (HV) battery pack to achieve your desired range. You will learn how to simulate battery packs with different capacities and weights, and compare them based on how these factors affect the range of the vehicle. See Workflow/Battery/BatterySizing. | ![]() |
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Run the thermal test bench over extended duty cycles at multiple coolant sump temperatures to assess winding and magnet thermal margins See Workflow/MotorDrive/ThermalDurability. |
| Generate copper, iron, IGBT, and diode loss maps by sweeping the FOC-controlled PMSM across speed, torque, and temperature points. See Workflow/MotorDrive/GenerateMotInvLoss. |
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Capture IGBT and diode junction temperatures from drive-cycle simulations, apply rainflow cycle counting, and estimate semiconductor lifetime. See Workflow/MotorDrive/GenerateMotInvLoss. |
| Sweep candidate gear ratios over EUDC and US06 cycles on the thermal test bench and compare magnet and winding temperatures to find the best ratio. See Workflow/MotorDrive/GearRatioSelect. | ![]() |
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Train a neural network to predict battery cell temperature from current, voltage, and SOC inputs. A pre-trained model is included for verification. See Workflow/Battery/VirtualSensorNeuralNetModel. |
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You can also launch the BEV Setup App (BEVapp) to select
a template, choose component fidelities, link parameter files, and configure environment, HVAC, and driver settings for your vehicle model. |
- Requires MATLAB® release R2024b or newer.
- Simscape™, Simscape Battery, Simscape Driveline, Simscape Fluids and Simscape Electrical toolboxes
- Clone the project repository.
- Open ElectricVehicleSimscape.prj to get started with the project.
- Requires MATLAB® release R2024b or newer.






