MATLAB and Simulink for Electrical Technology Development

As an engineer working in the development of electrical engineering technology, you understand the importance of reliability, efficiency, and innovation. Significant developments in electrical technology, from the nineteenth century to the present, have transformed electricity from a mere curiosity into an essential part of daily life. Advanced tools are essential to meet such demands; they enable you to design, simulate, and deploy complex electrical systems with greater accuracy and speed. For instance, integrating renewable energy sources into the power grid requires sophisticated modeling and simulation to ensure stability and efficiency.

MATLAB and Simulink are powerful platforms that provide a comprehensive and integrated ecosystem of tools for electrical engineering technology development. Engineers familiar with traditional methods can use MATLAB and Simulink to work more efficiently, simulate complex systems more accurately, and test real-world scenarios through hardware-in-the-loop simulations.

Key Applications of MATLAB and Simulink in Electrical Technology

Electrical system modeling and simulation

MATLAB and Simulink excel at creating detailed models of electrical systems, which allows you to simulate and analyze their behavior under various conditions. This capability is crucial for designing reliable and efficient power systems, from small-scale circuits to large power grids. Additionally, MATLAB and Simulink provide cost-effective solutions for designing and optimizing electrical systems.

Extensive library of models and reference examples: Leverage a vast selection of prebuilt models and reference examples, from individual solar cells to large photovoltaic farms or from small motors to complete electric vehicle systems. Get started with the shipped examples in MATLAB, Simulink, and Simscape in the initial stages of studies and development.

Incorporating multi-domain physical effects: Integrate a variety of physical phenomena to increase model fidelity and improve the accuracy of your simulations of a couple of physical systems. Simscape simplifies the combination of different physical domains.

Tailoring models for performance and speed: Customize your models to suit the specific needs of your project to strike an ideal balance between model fidelity (accuracy) and simulation speed, which ensures efficient yet detailed simulations.

Optimizing system performance through studies: Conduct comprehensive studies on physical system models by exploring different configurations at both the component and system levels. Evaluate design trade-offs and leverage these insights to optimize the overall performance of your electrical system.

Control design and deployment

MATLAB and Simulink provide tools for designing, testing, and deploying control algorithms to ensure optimal performance and stability. These tools support a wide range of control strategies, including PID, state-space, and adaptive control.

Designing digital controls with integrated models: Develop digital control systems directly within the same environment as that of the electronic component or electrical system model. This allows for seamless integration of control strategies with the underlying system design. We can design various control strategies using the suite of Control System tools available in MATLAB and Simulink.

Prebuilt control algorithm blocks: Select from a range of preconfigured control algorithm blocks, including both classical and learning-based approaches. These blocks are tailored for specific applications, such as motor control systems or battery management systems (BMS) controls, which simplifies the control design process.

Automating control system tuning: Streamline the tuning process using interactive apps and tools to analyze the control system’s response across both time and frequency domains. These tools help fine-tune controllers while ensuring robust system performance.

Rapid control prototyping (RCP): Accelerate the development process by performing rapid control prototyping. Simulate control systems on your desktop and test them on real-time hardware (Speedgoat) to ensure that your designs perform as expected before deployment.

Optimized code generation for deployment: Automatically generate optimized, readable C/C++ or HDL code for deploying control systems to embedded processors, FPGAs, or SoC targets. This ensures that control algorithms are ready for deployment to real-world embedded systems with minimal additional coding effort.

System analysis and testing

MATLAB and Simulink offer comprehensive tools for conducting various analyses, such as power flow, fault analysis, and stability studies. These tools help you identify and address potential issues early on in the design process.

Comprehensive system analysis and virtual testing: Conduct thorough system analysis and virtual testing by running desktop simulations with varying parameters, time scales (ranging from milliseconds to hours), and system scales (from individual microgrids to large interconnected grid networks). Advanced simulation techniques allow for a complete understanding of system behavior under different scenarios.

Simulating normal and fault conditions: Test both normal and fault operating conditions to ensure the robustness of control systems and the reliability of power electronics and power systems. This helps to identify potential weaknesses and ensures that systems perform reliably under all conditions.

Accelerating simulation: Speed up the simulation process by leveraging parallel computing or deploying generated code onto multicore machines. This significantly reduces simulation times and enhances model performance during complex simulations. 

Hardware-in-the-loop (HIL) testing: Overcome the challenges of real hardware limitations and cost by utilizing Hardware-in-the-Loop (HIL) testing. We can leverage Simulink Real-Time and Speedgoat to validate our control designs with real-time HIL simulations.

Key Tools and Features in MATLAB and Simulink for Electrical Technology

Simscape Electrical

A specialized library for electrical systems that includes models for motors, power converters, batteries, and other key components, you create high-fidelity models and perform detailed simulations to optimize system performance while ensuring physical accuracy.

Control system design

The Control System Toolbox, Model Predictive Control (MPC) Toolbox, and Simulink Control Design offer robust capacities for designing and tuning control systems. These tools support the development of robust control algorithms that can be tested and validated through simulation before deployment.

Motor control blocksets

MATLAB and Simulink include specialized blocksets for powertrain and motor control, which enable the design and simulation of complex drive systems. These blocksets provide prebuilt models and components that simplify the development process and enhance simulation accuracy.

AI for Electrification

Reduced order modeling (ROM) 

You can apply reduced order modeling for your physical components or physical systems and use them in your design. By leveraging AI and data-driven methods, we can increase simulation speed while retaining the system’s essential physical behaviors.

Example: Engineers can create a reduced-order model for a Motor Load using Deep Learning in Simulink. 

Predictive maintenance

AI techniques, such as machine learning, can be used for predictive maintenance, which allows you to anticipate and address potential issues before they lead to system failures. MATLAB and Simulink provide tools for developing and deploying predictive maintenance algorithms.

Example: It’s possible to use machine learning models to predict the remaining useful life of electrical components and schedule maintenance accordingly.

Virtual sensors

Virtual sensors estimate critical physical quantities using AI models and real sensor data, without introducing additional costs and physical sensors. MATLAB and Simulink enable the development of AI virtual sensors, which can then be deployed to the production hardware. 

Example: You can develop a virtual sensor to estimate the Battery State of Charge in Simulink, which is a critical information for the vehicle energy management system. 

Energy forecasting

Accurate energy forecasting is essential for managing and mitigating uncertainties and risks of power system operations. MATLAB and Simulink simplify the development of AI-based energy forecasting systems that can predict energy production, consumption, and pricing. 

Example: You can create Machine Learning and Deep Learning models for energy forecasting to improve planning of generation and optimize resources. 

Control strategy

AI can be used to develop high-performance advanced control algorithms for complex, nonlinear, multi-input multi-output systems. MATLAB and Simulink provide tools for designing and testing these algorithms and enabling deployment. 

Example: You can use reinforcement learning to develop Field-Oriented Control of a PMSM motor. 

Conclusion

MATLAB and Simulink are changing the way electrical systems are designed, simulated, and validated. By offering specialized tools and workflows, they are helping electrical engineers optimize system performance, reduce development time, and accelerate innovation.

Featured products

MathWorks® products:

• MATLAB
• Simulink
• Polyspace
• Simscape Electrical
• Control System Toolbox
• Model Predictive Control Toolbox
• Simulink Control Design
• Speedgoat
• Motor control blocksets

Learn more

• Blog: Power Electronics Control Design
  Discover three areas where PECD with Simulink can transform your engineering projects. Reduce project time by 50%, access thousands of electrical modeling components, and build and tune motor control algorithms with ease.
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• Blog: Key Advantages of Using Speedgoat Target Hardware with Simulink
  Dive into the world of R&D as we unveil how the dynamic duo of Simulink and Speedgoat turbocharge testing processes. Learn how their seamless integration ensures precision and real-world replication for groundbreaking innovations.
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• Blog: Why Use Virtual Prototyping for Electric Vehicle Development?
  Learn why virtual prototyping is becoming increasingly essential in electric vehicle development and why MATLAB and SIMULINK are standout tools for this purpose.
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