Introduction: The Importance of Early-Stage Simulation
Early-stage decisions in power converter and motor drive design play a critical role in the time and cost required to meet design criteria. Choices made about circuit topologies, component selection, control strategy, and fault behavior before any hardware is built will define costs, performance, and redesign risk for the entire project.
Digital simulation gives engineers a way to make those decisions, while setting the foundation for effective early-stage power converter and motor drive design.
This white paper shares insights on how MATLAB®, Simulink®, and Simscape Electrical™ provide the necessary environment for early-stage decision making. Each section addresses a specific challenge in early-stage hardware design and discusses how simulation-driven analysis reduces risk before the first prototype is built.
Reducing Risk in Early-Stage Design of Power Converters and Motor Drives
During the initial stages of circuit design for power electronics–based devices such as power converters and motor drives, engineering teams need to use software that provides multiple capabilities to explore the design space. You want to make easy changes to iterate initial concepts, find errors before hardware testing, conduct cost and performance trade‑offs, and explore the circuit as part of a realistic system. Early‑stage design using software with these capabilities ensures fewer design iterations and costly delays when you advance into the hardware implementation phase of the project.
Model‑based, multidomain simulation design empowers engineers to make optimal, informed decisions early in the power converter and motor‑drive design process. By combining simulation, analysis, and design features in a single environment, this approach enables engineers to systematically navigate the full design space. Engineers can conduct trade studies that address multiple and often competing requirements, such as control loop design, dynamic response, thermal effects, power quality, component selection, and fault analysis, all within one platform.
With support for multiple levels of model fidelity and cosimulation capabilities, Simscape Electrical integrates into existing workflows, offering a more comprehensive approach than traditional EDA tools or circuit simulators alone. Engineers can explore topology and architecture options, size components, and conduct targeted trade studies to inform critical decisions at the earliest stages. Vendor‑defined libraries, import tools, and an extensive library of circuit elements, loads, prebuilt converters, and control templates make initial design exploration fast and flexible. Direct integration with MATLAB enables rapid exploration and narrowing of the design space, accounting for a wide range of variables and constraints.
Key performance factors, such as power quality, heat dissipation, system efficiency, and mechanical performance (including motor dynamics), can all be analyzed in a unified environment, with requirements tracking and fault injection capabilities. This integrated approach builds high confidence before moving into detailed design.
How Simscape Electrical Enhances Your Design Process
Simscape Electrical addresses a range of early-stage design challenges through a unified set of capabilities, such as:
- Trade studies, preliminary analysis, and optimization
- Multiple levels of fidelity
- Thermal and mechanical analysis
- Fault injection
- Frequency-based analysis
- Vendor part libraries
- Control loop design
- Requirement traceability
- Cosimulation and model export
Trade Studies, Preliminary Analysis, and Optimization
Simscape Electrical offers two key advantages for systematic converter design and early-stage trade studies. First, its direct integration with MATLAB gives access to scripting, design, and optimization tools for automated design space exploration. Second, engineers have control over simulation detail, from using thermally dependent transistors to abstracting out converters with high-level behavioral models. Together, these features create a unified environment where the level of automation and model fidelity can be tailored to the specific requirements of each project.
MATLAB driven optimization and trade studies leverage Simscape Electrical models to address multiple goals and requirements simultaneously. Objectives such as cost, power quality, or bandwidth can be prioritized and weighted, while hard constraints (like minimum efficiency or required gain/phase margin) are enforced automatically. These constraints are customizable and can be explored individually or collectively to understand their impact on the converter design.
MATLAB supports local, global, and AI-based optimization and provides tools for generating design of experiments to systematically cover the design space.
A key technical advantage for this type of analysis is support for discrete and integer-based optimization, as well as machine learning techniques. This allows the selection of real, off-the-shelf components (such as choosing a standard 1000-ohm resistor instead of an impractical 1004.2 ohms), ensuring the final design is both optimal and manufacturable. Constraints and optimization objectives, whether continuous or discrete, can be used to automate the exploration of architectures, component values, control schemes, and more. MATLAB supports local, global, and AI-based optimization and provides tools for generating design of experiments to systematically cover the design space.
Extensive behavioral models, example projects, and control templates accelerate the construction of exploratory models, abstracting unnecessary details to facilitate meaningful analysis and comparison in the early design stages. This approach enables high-quality decisions that account for the full set of system requirements, increasing the likelihood of design success. Importantly, these same methods can be applied to more mature designs for fine-tuning and further optimization.
Diagram of a three-phase high-power converter design and analysis workflow.
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Multiple Levels of Fidelity: Streamlining Model Creation and Maintenance
The flexible modeling capabilities of Simscape Electrical enable engineers to address specific design criteria while abstracting unnecessary details. This user-customizable flexibility means both system-level and detailed design decisions can be made within the same workflow. For example, you might analyze a power distribution system for cost and efficiency without modeling low-level control loops, or evaluate gate drive resistance to explore the trade-off between efficiency and EMI. Simscape Electrical libraries include prebuilt models at various fidelity levels, along with numerous examples and templates to quickly assemble simulations tailored to your task.
At its core, Simscape Electrical scales from detailed transistor models with thermally dependent parameters and complex nonlinearities up to high-level behavioral models that can abstract even the control loop of a converter. Common fidelity levels include:
- Detailed nonlinear switches (SPICE-like models)
- Switched linear devices (preserving switching effects and losses, but ignoring turn-on dynamics)
- Average models (focusing on higher-order system dynamics, including discontinuous mode)
This approach applies not only to transistors but also to batteries, motors, ICs, and more. The ability to select the appropriate fidelity is critical for building useful models with the available data, supporting iterative design even when some details are unknown. It also streamlines model creation, maintenance, and simulation by abstracting unnecessary complexity.
Detailed schematic of a gate driver.
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Thermal and Mechanical Analysis: Evaluate Losses and Cooling Strategies
Packaging and layout are critical considerations in converter design. Simscape Electrical provides detailed loss calculations at every level of fidelity. For traditional transistor models, both switching and conduction losses are always calculated. When using piecewise linear models for faster simulation, losses can be populated from vendor-provided tables or auto-generated by Simscape from detailed switch models, including soft-switching scenarios. Average and behavioral models can incorporate efficiency maps to ensure accurate thermal behavior and circuit efficiency.
Simscape Electrical provides detailed loss calculations at every level of fidelity.
While understanding thermal losses and efficiency is essential, a complete system perspective is often needed to ensure effective heat extraction. Simscape Electrical supports traditional thermal modeling approaches such as Cauer and Foster networks, enabling simulation of conductive, convective, and radiative heat transfer within the thermal domain. These models can include advanced details like liquid and two-phase cooling, as well as heat exchangers, allowing designers to evaluate heat extraction strategies while considering the additional power demands of active cooling systems.
Mechanical components, such as motors and solenoids, can also be modeled at multiple fidelity levels. These range from simple lumped parameter models to detailed, nonlinear models imported from FEA tools, capturing effects like spatial harmonics and saturation. Thermal behavior can be included as needed, supporting comprehensive analysis of both electrical and mechanical aspects.
Built-In, Proactive Fault Injection
Simscape Electrical features built-in tools for fault modeling, injection, and analysis. Individual components include predefined faults, while dedicated fault blocks allow users to inject open circuits or shorts at any point in the system. Faults can be triggered by simulation criteria, user input, or specific simulation times. Because the simulation environment recognizes these behaviors as faults, all fault scenarios are managed through a dedicated fault window, enabling systematic and thorough virtual fault assessment. This capability can be scaled up to support virtual failure modes and effects analysis (FMEA) when required.
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Frequency-Based Analysis for Electrical Performance and Control Characteristics
Simscape Electrical supports frequency-based analysis alongside time-domain simulation, essential for studying power quality, input impedance, noise rejection, and control loop design. When using prebuilt converter blocks from the Simscape Electrical library, analytical frequency responses and transfer functions are readily available, as average models are derived and integrated under the hood. These capabilities extend to all custom-modeled topologies, regardless of fidelity, using built-in frequency response analysis tools. This eliminates the need for manual small-signal analysis or average model derivation.
Frequency response data can be integrated with control and optimization algorithms or used with system identification tools to generate reduced-order time-domain models, with no manual mathematical analysis required.
Frequency analysis of a boost converter.
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Vendor Parts: Integrating Models from Hitachi, Infineon, Wolfspeed, and Other Vendors
Simscape Electrical supports vendor-defined component modeling through several integration methods:
- Datasheet-based modeling: Parameters from vendor datasheets can be structured to configure predefined component blocks when vendor-supplied simulation models are unavailable and datasheet values are sufficient for system-level analysis.
- Parameter extraction from simulation: Vendor SPICE models can be simulated to extract key parameters, such as switching losses, capacitance profiles, and thermal characteristics, which then populate lookup tables for behavioral models.
- SPICE netlist import: Simscape Electrical can import detailed vendor device models using SPICE netlists that include nonlinearities and parasitics.
Simscape Electrical includes component data from manufacturers such as Hitachi, Infineon, and Wolfspeed and provides tools to build representative models for any discrete device given appropriate vendor data. This ensures consistent, verified modeling across electrical, thermal, and control domains.
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Control Loop Design: Optimizing Control Bandwidth from the Start
Simulink supports classical and advanced control approaches, including model predictive control and machine learning. It enables concurrent control design and optimization, allowing engineers to address competing criteria and achieve highly optimized performance.
Simulink supports loop design in both the S and Z domains, with standard visualizations such as Bode, Nyquist, and step response plots, and tools for pole-zero analysis and placement. Traditional control criteria can be combined with additional quantitative performance measures, enabling, for example, a controller to be tuned for stability and bandwidth while also limiting current overshoot during startup.
Simulink supports loop design in both the S and Z domains, with standard visualizations such as Bode, Nyquist, and step response plots, and tools for pole-zero analysis and placement.
Simulink also offers a range of control strategies, from robust and fuzzy logic controllers to advanced motor drive techniques (for example, phase-locked loops, Clarke and Park transforms, field-oriented control, direct torque control, and BLDC commutation). For utility and grid-connected systems, Simulink provides tools for maximum power point tracking, inverter resource management, admittance-based stability, grid-forming, and more.
Integrating model predictive controllers in field-oriented control for enhancing electric motor control.
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Requirements Traceability: ISO 26262 and IEC 61508 Compliance
Requirements traceability is essential for structured hardware design workflows, especially under standards such as ISO 26262 and IEC 61508, which mandate tracking from requirements to implementation. Missing a requirement early can lead to costly rework at later stages.
Simscape Electrical, integrated with the Simulink product family, supports comprehensive requirements management and verification. Engineers can link circuit models directly to textual requirements and perform formal requirements–based testing, supporting compliance and validation against defined specifications.
This unified environment enables traceability across modeling, simulation, and testing, linking requirements to design artifacts, simulation results, and test coverage. This approach supports design reviews, certification processes, and change impact analysis, ensuring robust, standards-compliant design from concept through implementation.
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Cosimulation and Model Export for HIL Testing
Simscape Electrical fits into existing hardware design workflows, which often include EDA and layout tools for final design file generation. To support this integration, MathWorks offers cosimulation and model export capabilities, enabling adoption across many design environments.
Plant models can be exported to C and HDL/Verilog code for hardware-in-the-loop (HIL) testing of power systems and converters.
Simscape Electrical supports cosimulation with circuit simulation tools such as PSpice® and SIMetrix, allowing engineers to leverage the strengths of different platforms simultaneously. This capability extends to integration with multiphysics engines and EDA tools for higher-fidelity modeling, such as FEA analysis, when needed.
On the export side, plant models can be exported to C and HDL/Verilog code for hardware-in-the-loop (HIL) testing of power systems and converters. These models can also be exported for use in EDA tools, integrating with SystemVerilog and allowing models created in Simscape Electrical to run within EDA environments.
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Conclusion
Reducing risk in early-stage power converter and motor drive design comes down to visibility and seeing the consequences of design decisions before they become expensive, irreversible, or unsafe. The workflows described in this paper demonstrate how a model-based, multidomain simulation environment helps engineers explore more ideas, validate assumptions earlier, and converge on robust designs with greater confidence. With MATLAB, Simulink, and Simscape Electrical they can use vendor-accurate components to conduct trade studies; thermal, fault, and mechanical analysis; frequency-based evaluation; and control loop development.
