Automating PSIM with Hyperstudy vs Scripting
Altair EmployeeThe primary goal of this article is to highlight the advantages of Altair HyperStudy over making scripts to process data produced by PSIM. This article does not delve into the implementation details of a script or a Hyperstudy file. If you are not familiar with these yet, please refer below for the Hyperstudy and here for the PSIM integration into Compose.
To better illustrate these advantages, we will use a buck converter in PSIM, as shown in the schematic below.
Task
The task that has to be implemented is to choose which LC filter we should use, depending on our application and load (R). So, we are going to plot the output voltage (Vout) for different values of L, C, R.
LSpace: 10e-6 – 90e-6 H, 5 values
CSpace: 10e-6 – 50e-6 F, 5 values
RSpace: 1 – 10 Ohm, 5 values
You can find all the files attached in this article.
The scripts are .oml files. However, you can write them in Python, but first you should visit the article here.
Scripting – Altair Compose
The implementation code provided below plots the output voltage for every combination of L, C, and R, totaling 125 combinations.
It is evident that post-processing the output data is challenging and time-consuming. Finding the optimal combination that meets your application's requirements (such as ripple, overshoot, and output voltage) can be particularly difficult.
Hyperstudy
In HyperStudy, the implementation is much simpler. We define the bounds for each decision variable,
and Hyperstudy runs the simulation for every combination of L, C,R
The last but not the least, a very useful advantage of using of Hyperstudy instead of scripting is its post – processing tools like Data Sources Tool, which can help us plot and debug every voltage and current measurement defined in the PSIM schematic separately for every simulation run. In our case, we can plot the output voltage (Vout).
Furthermore, there are a lot of similar tools like 3D scatter and Linear Effects tool which may be useful depending on our application.
Conclusions
This task took me about 8 hours longer in Compose than in HyperStudy. It's important to consider that we may have more decision variables and a more complex objective function.
In conclusion, using HyperStudy offers several advantages:
Time-saving: You can save a significant amount of time.
No programming skills required: You don't need to have programming skills.
Meaningless labor abstracted: You can add your own scripts - the set up is handled by Hyperstudy.
Improved data post-processing: You can post-process data more effectively and easily.
Consistent time investment: The time required remains the same regardless of the problem's complexity.