With the rapid advancement of the semiconductor industry, new power electronic devices are continuously emerging, creating a growing demand for accurate and efficient device modeling. This has posed significant challenges in developing specialized modeling tools. To address these challenges, this paper presents the development of a lightweight and dedicated device modeling tool based on open-source simulation code, specifically leveraging the SPICE3f5 simulation kernel.
The simulation module is designed to integrate seamlessly with existing SPICE-based workflows. By analyzing the input equivalent circuit using SPICE syntax, we export relevant interfaces to the SPICE3f5 source code, enabling the simulation engine to process custom models efficiently. This approach ensures compatibility while maintaining flexibility for future enhancements.
To facilitate communication between the user interface and the simulation core, an API was developed by compiling the SPICE3f5 source into a dynamic link library (DLL). This allows the tool to interact with the simulation engine through well-defined functions, as detailed in Table 1.
Parameter extraction plays a crucial role in device modeling. The model parameters must be accurately extracted from the netlist input provided by the user. A two-step parsing process is implemented: first, the netlist is pre-processed to retain only the valid simulation data, and second, component parameters and instantiated subcircuits are extracted and stored in structured data formats. This enables efficient and repeatable simulations with parameter adjustments.
For visualizing simulation results, a graphical display module was developed. It includes a Smith impedance chart, which is essential for high-frequency circuit analysis. The Smith chart is composed of constant resistance and reactance circles, and the drawing logic involves normalizing values and scaling them according to the display requirements.
In addition to the Smith chart, the tool supports zooming and panning features, allowing users to focus on specific regions of the graph. These functions are implemented using memory device contexts (DCs) and bitmaps, ensuring smooth and efficient rendering even after multiple zoom operations. The ability to restore previous views makes it easier to navigate complex simulations.
This work introduces an object-oriented design approach to device modeling, enhancing modularity and reusability. It significantly reduces the development cycle and cost of creating custom device models, offering valuable insights for future tool development in specialized modeling applications.
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