MATLAB, Simulink, and Simscape enable engineers to front-load the development of electric vehicles (EV) through the systematic use of data and models. These products enable you to understand system-level behavior, evaluate design tradeoffs, deploy validated algorithms across the EV lifecycle, and:
- Architect complete EV systems using Model-Based Systems Engineering
- Improve battery safety, longevity, and range
- Enhance powertrain efficiency
- Optimize vehicle thermal management and energy usage
- Accelerate development cycles with data and AI
See How Others Use MATLAB and Simulink for EV Development
Develop System Architecture and Perform System Simulation
Electric vehicles require design and analysis at the vehicle level involving multidomain systems integration. With Powertrain Blockset, Vehicle Dynamics Blockset, and Simscape, you can:
- Quickly get a full EV simulation up and running, with motors, generators, and energy storage components
- Analyze architecture tradeoffs, motor and battery sizing, and control parameter optimization
- Develop custom control features for powertrain, chassis, or vehicle motion controls, then assess their performance using closed-loop vehicle models
- Capture system architecture, detailed design, and implementation details in a single environment with a digital trace across models from different process steps
- Reuse models throughout development from architecture, to analysis, to hardware-in-the-loop (HIL) testing
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Model Batteries and Develop BMS
MATLAB and Simulink let you create equivalent circuit models (ECMs), electrochemical models, and data-driven models for battery cells. You can also:
- Simulate electro-thermal dynamics, hysteresis effects, aging degradation, and thermal runaway of a battery using high‑fidelity or reduced‑order models for EV operating conditions
- Explore architecture trade-offs for cell formats, pack layouts, cooling plate designs, and thermal management strategies
- Develop and verify BMS algorithms across drive cycles, including state estimation (SOC/SOH/SOP), cell balancing, fault protection and mitigation, thermal management, and battery fast charging profile
- Enable BMS software development and certification, including closed-loop desk simulation, code generation, software-in-the-loop (SIL) testing, processor-in-the-loop (PIL), and hardware-in-the-loop testing
- Integrate battery models into EV simulations to assess range, energy usage, and safety margins
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Model Powertrain and Cabin Thermal Systems and Develop Control Algorithms
With MATLAB, Simulink, and Simscape, you can create detailed thermal system models to evaluate component and vehicle-level performance, especially in extreme operating and environmental conditions.
- Develop models of full-vehicle coolant, air, and refrigerant circuits that support real-time simulation
- Develop control algorithms for operating the compressor valves and pumps under different modes
- Monitor component temperatures, power consumption, and heat flows to ensure safe, performant operation even under extreme conditions
- Simulate fuel economy, system derating, aging, and other thermal effects to optimize the system for real-world operating conditions
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Model Traction Motors, Inverters, and Develop Motor Control Software
With Motor Control Blockset and Simscape Electrical, you can aAccelerate development by modeling and simulating motor control systems before hardware testing.
- Model motors and power electronics, such as permanent magnet synchronous motor (PMSM), induction machines, and semiconductor devices, with the right level of fidelity to balance accuracy and simulation speed
- Automate parameter estimation, import finite element analysis (FEA) data for motors, or import SPICE or vendor device data for semiconductors to reduce the initial effort and time required to build accurate models
- Implement sensor-based and sensorless field-oriented control algorithms. Tune current and speed loops using classical control techniques or automated tools like Field Oriented Control (FOC) Autotuner for faster development
- Simulate and verify control algorithms, protection logic and mode transitions through HIL testing before dyno validation to reduce risk and iteration time
- Generate MISRA™-compliant C and HDL code for motor control units (MCUs) and FPGAs directly from Simulink models, with support for AUTOSAR and ISO 26262 certification workflows.
Customer Success
- Eaton: Iterative Approach for Gradual Transition to Model-Based Design in Legacy Motor Controllers (20:48)
- LG Electronics: -Develops ISO 26262–Compliant Power Inverter Control Software with Model-Based Design
- SAIC Motor: Develops Embedded Control System for the Roewe 750 Hybrid Sedan Using Model-Based Design
Deploy, Integrate, and Test Control Algorithms
EV developers increasingly need to comply with safety standards. With MATLAB and Simulink, you can:
- Automatically generate optimized C and HDL code
- Automatically trace requirements, measure quality of code/models, and generate test cases
- Use tools that are pre-qualified for ISO 26262, and comply with an ISO 26262 reference workflow to meet functional safety requirements
- Leverage AUTOSAR Blockset (classic and adaptive) to model AUTOSAR software components, simulate compositions, and import/export ARXML files
- Integrate with CI/CD pipelines, generate code, package for deployment, and automate regression testing
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Use AI and Data-Driven Workflows in EV Development
Integrate AI and reduced‑order modeling (ROM) techniques into modeling, simulation, and deployment workflows. With MATLAB and Simulink, you can:
- Apply AI and ROM to reduce computational complexity of high-fidelity battery, motor, and thermal system models, including for real time HIL testing
- Use virtual sensors to estimate motor and battery temperature, SOC, and SOH—reducing hardware costs
- Detect anomalies and predict failures in batteries and motors with machine learning and predictive maintenance workflows
- Develop optimal energy management and motor control strategies, including reinforcement learning integrated with system level models
- Use point and click apps to prepare data, train models, and validate AI components before deploying to embedded hardware, edge devices, or the cloud
Why MATLAB and Simulink for EV Development?
Simulink integrates with 153+ third-party tools and languages making it a convenient integration platform.
Get the right trade-off between model fidelity and execution speed by picking from a wide range of models.
Lower the barrier to simulation using reference examples, training courses, and documentation.
Speed up development projects by leveraging the expertise of MathWorks Consulting.
Meet compliance and certification standards (ISO 26262, ASPICE, MISRA-C, and more) with Model-Based Design workflows.
Go from concept to deployment within the MATLAB and Simulink environment.
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