verg1lio/XangoER
Nov 2024 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
Control SystemsElectrical EngineeringEmbedded SystemsSimulation3D modelingalgorithm development
Iago Silva
PROFILE
Iago Silva
Contributed to the verg1lio/XangoER repository by developing two core features over a two-month period. Delivered Pulse Width Modulation support for the Motor class, enhancing the digital twin powertrain simulation’s realism through inverter switch state definitions and PWM signal generation using Python. Collaborated with multiple contributors to update simulation examples, improving onboarding and validation of control strategies. Later, implemented a battery optimization and 3D visualization module, enabling calculation of battery pack dimensions, weight, and energy capacity, with interactive data visualization via Plotly. Focused on control systems, embedded systems, and data visualization, the work strengthened simulation fidelity and accelerated design cycles.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
818
Activity Months2
Your Network
16 peopleWork History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for verg1lio/XangoER highlighting a new battery design capability and visualization features. Key deliverable: Battery Optimization and 3D Visualization Module with calculations for battery pack dimensions, weight, and energy capacity, plus a Plotly-based visualization. No major bugs fixed this period.
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for verg1lio/XangoER highlighting a new battery design capability and visualization features. Key deliverable: Battery Optimization and 3D Visualization Module with calculations for battery pack dimensions, weight, and energy capacity, plus a Plotly-based visualization. No major bugs fixed this period.
January 2026
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered PWM support for the Motor class in the verg1lio/XangoER digital twin powertrain simulation, enhancing realism and configurability of motor drive models. The feature introduces inverter switch state definitions, PWM signal generation based on modulated voltages, new parameters and methods, and updated simulation examples. This work strengthens the platform’s digital twin fidelity and enables faster validation of control strategies for powertrain projects.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered PWM support for the Motor class in the verg1lio/XangoER digital twin powertrain simulation, enhancing realism and configurability of motor drive models. The feature introduces inverter switch state definitions, PWM signal generation based on modulated voltages, new parameters and methods, and updated simulation examples. This work strengthens the platform’s digital twin fidelity and enables faster validation of control strategies for powertrain projects.
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
3D modelingControl SystemsElectrical EngineeringEmbedded SystemsSimulationalgorithm developmentbattery optimizationdata visualization
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