new features

capacitive effects for EMC analysis


InCa3D 3.1 version opens the doors for higher frequency simulations. Computations take into account the capacitive effects for EMC analysis of power electronics systems.

Find critical parasitic capacitances!

Parasitic capacitance matrix between regions, values in pF

InCa3D provides all the elements of the capacitance matrix between conductors, possibly separated by dielectrics. Now, it’s possible to find where are the most critical capacitive couplings!

 

 

Perform global computations

Global models composed of these parasitic capacitances and resistive-inductive behaviors of the structure are achievable in the InCa3D environment;

 

 

 

 

 

Compute common-mode currents

Study inside parasitic capacitances the common-mode currents which can be responsible of EMC failures in power electronics devices;

 

 

 

 

 

Identify resonances

Analyze resonance frequency of the system in the “Conductor impedances” application by plotting 2D curves of equivalent impedances;

 

 

 

 

 

Develop RLC macro models

Extract accurate equivalent RLC circuits in SPICE or VHDL-AMS languages. Now is possible to include all the parasitic effects of interconnections into circuit-level time-domain simulations.

 

 

 

 

 

Easy, accurate and high-quality PCBs simulation with the Gerber import

  • Import of Gerber files describing both layers and vias
  • A dedicated working context with the possibility to discard useless information in order to simplify the geometry

Accelerate your simulation with the new FMM solver

  • Speeding-up simulations and especially dealing with more and more complex structures
  • Based on the state-of-the-art Adaptive Multi-Level Fast Multipole Method (AMLFMM) algorithms
  • Many other algorithms for complex conductor’s meshing and physics definition

Advance your design by coupling InCa3D to GOT-It optimization tool

  • Advanced algorithms for the automatic searching of the best configuration
  • Possibility to screen the relative importance of the parameters and determine the most influential ones, in order to possibly reduce the model complexity and size
  • Research of the optimum configuration allowing to reach one or several objectives by respecting constraints
  • Robustness study of the optimized configuration