Electrification
Powering Electrification with MATLAB, Simulink, and Simscape
Electrical Applications
Engineers use MATLAB and Simulink to develop electrical technologies that help increase reliability, improve efficiency, and mitigate climate change, from motor control and battery management for electric vehicles to integrating renewable energy into the power grid.
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Motor Drives and Traction MotorsDevelop embedded software for motor-inverter systems |
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Renewable Energy and Energy StoragePerform grid-scale integration studies, develop wind and solar farm architecture and control systems |
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Electric Vehicles and TransportationPerform vehicle-level electrical system and control design for electric transportation |
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Battery SystemsDesign battery packs and develop battery management systems |
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Microgrid, Smart Grid, and Charging InfrastructureDevelop network architecture and perform system-level and control system design of power system infrastructure |
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Fuel Cells and ElectrolyzersDevelop architectures and controls for PEM fuel cells and electrolyzers in hydrogen systems |
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Power ConversionDevelop embedded software for high, medium, and low power converter architectures |
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Generation, Transmission, and DistributionConduct bulk power grid analysis and planning for generation, transmission, and distribution systems |
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Building Energy ManagementPerform power system analysis and energy management design for residential and commercial buildings |
 AI for ElectrificationApply artificial intelligence (AI) techniques to the design, control, and operation of power electronic devices and power systems |
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Global Dependence of Engineers and Scientists on MATLAB and Simulink in Electrification
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Model-Based Design for Embedded Control Systems
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Why MATLAB and Simulink for Electrification?
Electrical System Modeling and Simulation
From electrical components to electrical systems
- Start with an expansive library of models and reference examples, from solar cells to PV farms, single IGBTs to grid-tied inverters, a standalone microgrid to large-scale transmission networks, and from a single motor to full electric vehicles
- Include multidomain physical effects (such as heat generation in power converters and air flows in fuel cell compressors) for increased model fidelity
- Tailor models to your needs and strike a balance between model fidelity and simulation speed
- Conduct studies on physical system models with different component-level and system-level configurations, evaluate design trade-offs, and optimize overall system performance
Control Design and Deployment
From fundamental blocks to production code
- Design digital controls in the same environment with the electronic component or electrical system model
- Choose from prebuilt classical or learning-based control algorithm blocks designed for specific applications such as motor controls and battery management system controls
- Automate the tuning process and analyze control system response in time and frequency domains with interactive apps and tools
- Perform rapid control prototyping (RCP) by running desktop control simulations and testing controls on real-time machines
- Generate readable, optimized C/C++ or HDL control code for deployment on common embedded processor targets and FPGA or SoC targets
System Analysis and Testing
From desktop simulation to HIL testing
- Perform system analysis and virtual testing by running desktop simulations of varying parameters, time scales (from milliseconds to hours), and solution scales (from standalone microgrid to interconnected grid networks)
- Simulate normal and fault operating conditions to ensure robust controls and reliable operations of power electronic devices and power systems
- Accelerate the simulation process by using parallel computing or deploying code generated from the model to multicore machines
- Overcome real-hardware infeasibilities and cost barriers by testing controls and operations with HIL testing
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