https://github.com/dyk-team/dc_resistance_network

KCL and KVL for the bridge circuit
https://github.com/dyk-team/dc_resistance_network

bridge-circuit circuit current kirchhoff-voltage-law kirchoff-current-law least-sqaure-method least-square-fit least-square-regression linear-equations ltspice matrix-equations ohms-law overdetermined python scipy-library voltage

Last synced: about 2 months ago
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KCL and KVL for the bridge circuit

• Host: GitHub
• URL: https://github.com/dyk-team/dc_resistance_network
• Owner: DYK-Team
• Created: 2024-04-08T15:56:08.000Z (9 months ago)
• Default Branch: master
• Last Pushed: 2024-11-14T23:28:32.000Z (about 2 months ago)
• Last Synced: 2024-11-15T00:28:02.998Z (about 2 months ago)
• Topics: bridge-circuit, circuit, current, kirchhoff-voltage-law, kirchoff-current-law, least-sqaure-method, least-square-fit, least-square-regression, linear-equations, ltspice, matrix-equations, ohms-law, overdetermined, python, scipy-library, voltage
• Language: Python
• Homepage: https://dykplus.wordpress.com/
• Size: 332 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
For more details refer to the file "Report.pdf". 

In this educational project, we demonstrate the application of Python for solving DC resistance networks using matrix equations (Circuit_1.py). Students learn how to model and analyse these networks by formulating their governing equations into a system of linear equations, leveraging Python’s computational capabilities to efficiently solve for unknowns such as currents and voltages. The calculations performed in Python are further validated through LTspice simulations, providing a practical comparison between theoretical results and simulated circuit behaviour.

An important aspect of the project is the exploration of overdetermined systems of linear equations, which arise when there are more equations than unknowns (Circuit_2.py). Students are introduced to techniques for handling such systems, including the use of least-squares approximation to find the best-fit solution. This provides an opportunity to discuss the mathematical principles and practical implications of overdetermined systems in real-world applications.

By integrating Python programming, matrix algebra, and LTspice simulations, this project offers a comprehensive educational resource. Students gain hands-on experience with computational tools while deepening their understanding of electrical network analysis and the broader mathematical concepts underpinning circuit behaviour. All Python scripts and LTspice simulation files are included, enabling students to replicate and expand upon the presented examples.