The project supports two ways to configure and load the vehicle model. Choose the one that fits your workflow.
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Preferred way (Preset) — Use the
Preset Picker to browse and
apply a shipped vehicle configuration. Three defaults are available:
VehicleElectric, VehicleElecAux, and
VehicleElectroThermal. Each preset configures the model
references, loads the correct parameters, and opens the model ready to
simulate. No manual configuration needed. Custom configuration — Launch the BEV Setup App ( BEVapp) to select
a template, choose component fidelities, link parameter files, and
configure environment, HVAC, and driver settings.
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In this project, you will learn about the following seven engineering workflows:
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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. |
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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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Build a neural network model to predict battery temperature. This Neural network model takes in battery voltage and current measurements to predict battery temperature. This, when deployed, can help in eliminating some thermal sensors in the battery pack and reduce cost of development. See Workflow/Battery/VirtualSensorNeuralNetModel. |
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Drive units with fixed gear ratio are usually the most cost effective option for battery electric vehicle. To determine an appropriate fixed gear ratio, run a design of experiment (DoE) which covers a range of gear ratios and test cycle parameters. See Workflow/MotorDrive/GearRatioSelect. |
| Learn how to generate a permanent magnet synchronous motor (PMSM) for a system level (electro-thermal) simulation by creating a motor loss map and integrating it into the system level blocks. See Workflow/MotorDrive/GenerateMotInvLoss. |
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Estimate the inverter power module semiconductor device junction temperature variation due to switching and predict the lifetime of the inverter. See Workflow/MotorDrive/InverterLife and Workflow/MotorDrive/ThermalDurability. |
For the full project architecture — folder responsibilities, source-of-truth, config schema, app layers, export flow, component inventory, workflow catalog, drift risks, and extension guides — see Overview/README.md.
R2022b (Feb 2023)
- Initial release — BEV system model with range estimation and battery sizing workflows
R2023a (Oct 2023)
- GitHub Actions CI introduced
- Battery component update
R2023b (Jul 2024)
- Fast running model variant
- Document updates
R2024b (Dec 2025)
- Componentization — models restructured into self-contained packages with shared port interfaces
- Range estimation workflow updated
- PMSM model block and motor drive workflow updates
R2024b Update 2 (Apr 2026) — Latest release
- BEV Setup App — GUI-based vehicle configuration and script export
- JSON config-driven template/fidelity system with presets
- 3 new dummy fidelities for simplified simulations
- Standardized documentation across all 12 components and 7 workflows
- Architecture reference doc with extension guides
- Simscape Battery Electric Vehicle Model — BEV reference model with battery, motor, and vehicle dynamics
- Simscape HEV Series-Parallel — Hybrid electric vehicle model with series-parallel powertrain architecture
- Clone the project repository.
- Open ElectricVehicleSimscape.prj to get started with the project.
- Requires MATLAB® release R2024b or newer.
Copyright 2022 - 2026 The MathWorks, Inc.







