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EMC-informed Adaptive Frequency Sweep

Authored by: Sayantan Das, SDE II


In the realm of Electromagnetic Interference (EMI) and Electromagnetic Compatibility (EMC) simulations, frequency-domain analysis plays a pivotal role in identifying resonant behavior, coupling paths, and compliance margins. Systems under test often exhibit sharp resonances, abrupt notches, and other rapidly varying features that demand close scrutiny across a wide frequency span.

Why Adaptive Frequency sweep (AFS)?

Traditionally, engineers have relied on Discrete Frequency Sweeps (DFS), a strategy that employs uniformly spaced frequency points spanning the band of interest. While straightforward, this method carries a major trade-off: either you risk missing critical spectral features with coarse resolution, or you consume excessive computational resources with a dense sweep.

This is where traditional Adaptive Frequency Sweep (AFS) steps in as a smarter, more efficient alternative. Rather than marching blindly through frequencies at fixed intervals, AFS intelligently selects the frequency points for solution. It zooms in around regions where the response changes rapidly—like resonance peaks—and skips quickly through flat regions. Thus, AFS delivers a faster and more insightful analysis, capturing critical dynamics with optimal use of simulation resources. 

The AFS methodology involves a few key stages: initial point selection, solving, and data acquisition, next frequency selection and convergence checking, as depicted below, where a simplified AFS flow is demonstrated.

Seeding AFS – Role of initial points

In AFS, initial frequency points seed the algorithm by providing a baseline response that guides the entire adaptive process. Thoughtful selection helps the algorithm target critical regions early, improving both speed and accuracy. However, using too many initial points can burden the simulation right from the start, undermining the efficiency that AFS aims to achieve. In contrast, too few initial points may cause the algorithm to overlook important resonance peaks entirely.  Therefore, the placement of initial frequency points in AFS is a strategic decision that can shape the entire sweep. 

System response-Guided Seeding Strategy for AFS

Relying on an arbitrary number or distribution of the initial points makes the entire AFS algorithm inconsistent and, at times, unreliable. A more effective approach is to select initial points based on prior knowledge of the system’s approximate behavior. In other words, predicting the resonant frequencies beforehand and using them as initial points. This way, we move from random seeding to response-informed initialization, laying the groundwork for a smarter, faster, and more accurate frequency sweep. 

In the context of EMI-EMC simulations, predicting resonances in advance—without performing a full electromagnetic (EM) analysis—is inherently challenging. These resonances often arise from complex interactions within the PCB layout and components, enclosure geometry, and unintended parasitics, making them difficult to estimate using intuition alone. 

Compliance-scope leverages EMC-specific knowledge by using the more predictable low- to mid-frequency behavior to guide the selection of initial points for the adaptive frequency sweep, enabling a more focused and efficient AFS.

  • At lower frequencies, resonances are primarily influenced by discrete components on the PCB—such as capacitors, inductors, and nonlinear elements. 
  • As the frequency increases into the mid-band range, cable-related resonances begin to dominate due to their length, routing, and termination characteristics.

To account for the combined effects of all these elements, a circuit-level simulation is performed, emulating the complete EMI test setup—including the PCB, connected cables, and the LISN (Line Impedance Stabilization Network). This simulation helps to locate the resonance peaks across the frequency spectrum, more accurately in the low to mid frequency region a priori. These frequencies are fed as initial points to the AFS algorithm.

Improved Accuracy

The following example illustrates a representative Bulk Current Injection (BCI) laboratory setup, demonstrating that traditional AFS technique fails to detect low-frequency resonances, particularly those occurring below 10 MHz. In contrast, an initial-point selection strategy informed by prior circuit-level simulations effectively captures these critical features with higher accuracy, thereby improving the reliability of the frequency-domain analysis.

Key Insights

The EMC response-informed Adaptive Frequency Sweep (AFS) strategy ensures critical low- and mid-frequency resonances, often missed by conventional adaptive sweeps, are accurately captured without excessive computational cost. Leveraging deep expertise in EMI-EMC, Compliance-Scope employs an advanced AFS framework that surpasses traditional general-purpose Electromagnetic Solvers in both accuracy and speed. Our solution uniquely integrates domain knowledge to intelligently guide the sweep process, delivering unmatched performance in simulation fidelity and efficiency. This makes our AFS a game-changer for industry-grade EMI-EMC workflows, where precision, speed, and regulatory confidence are critical.

© 2025 SimYog Technologies Pvt. Ltd. – All Rights Reserved.

Revolutionizing PCB EMC Analysis with Smart Net Selection

Authored by: Krishnan Ramaswami, CTO


EMC analysis of a Printed Circuit Board (PCB) can be an overwhelmingly complex process, especially as designs grow in density and intricacy. Traditionally, importing an ODB (Open Database) file brings in all the nets and components, meaning engineers are often confronted with hundreds of connections and components, many of which are not directly relevant to the task at hand. This leads to inefficient workflows, lengthy simulation times, and bloated use of computing resources. But what if you could focus solely on what matters most? That’s where the new Smart Net Selection feature steps in, transforming the way engineers handle PCB connectivity.

What is Smart Net Selection?

Smart Net Selection is a cutting-edge tool designed to streamline the process of net selection during the ODB import stage. Instead of bringing in every single net and component, Smart Net Selection empowers users to zero in on relevant connections, dramatically reducing project scope and complexity.

At the heart of Smart Net Selection is an intuitive, interactive graph-based UI. Users can pick a starting node—such as an integrated circuit (IC) or connector—and immediately view all the nets connected to that node. By simply clicking through related nets, users can trace paths of interest, extending selection only to those nodes and components critical for their analysis. Once the ideal connection path is defined, only these nets and associated components are imported for further work.

Key Benefits

The Smart Net Selection feature was engineered to address several major pain points PCB designers and analysts encounter while doing EMC simulation:

  • Reduced Number of Nets: By limiting the imported nets to only those that are vital, the number of mesh elements generated in your simulation drops significantly. This directly translates to quicker, more manageable analysis.
  • Faster Setup: With fewer components to model, setup times are dramatically shortened, getting your project off the ground faster.
  • Connectivity Verification: The step-by-step, visual selection process makes it easier to trace and verify PCB connectivity, providing an opportunity to catch missed or incorrect connections early in the workflow.

Real-World Impact: An 18-Layer Board Case Study

Let’s look at a concrete example. Our team recently faced the challenge of analyzing an 18-layer board featuring 479 nets and 618 components. Utilizing conventional import methods, the simulation demanded nearly two hours of solve time per frequency and consumed a hefty 120 GB of memory. For high-stakes projects with tight deadlines and finite resources, this was far from ideal.

Top view and Bottom view of the 18-Layer PCB

Enter Smart Net Selection. By interactively selecting only the 20 relevant nets, the number of imported components dropped to just 52. The result? Solve time fell to a mere 13 minutes per frequency, and memory consumption dropped to 30 GB—a fraction of the original resource needs.

Conclusion

Smart Net Selection marks a significant leap forward in PCB EMC analysis efficiency. By empowering engineers to select only those nets and components that truly matter, this feature helps accelerate results, conserve computational resources, and bolster analysis efficacy. Whether you’re aiming to optimize complex multi-layer boards or just streamline your workflow, Smart Net Selection is poised to become an indispensable tool in your design process.

Ready to see how Smart Net Selection can revolutionize your PCB analysis? Give it a try and experience the future of efficient design today. Download Compliance-Scope® 

 

© 2025 SimYog Technologies Pvt. Ltd. – All Rights Reserved.