evtolpy is a Python-based modeling framework for sizing, performance analysis, and mission-level simulation of electric vertical takeoff and landing (eVTOL) aircraft. The software evaluates vehicle aerodynamics, rotorcraft performance, subsystem masses, battery requirements, and mission energy consumption using an extensible set of physics-based methods combined with empirical mass regressions.

License: MIT License

The framework is mission-driven: given a vehicle configuration and a sequence of flight segments, evtolpy computes shaft power, electric power, and energy for each segment; iteratively updates vehicle mass properties; and converges on a consistent maximum takeoff weight (MTOW). The tool supports comparative studies across aircraft architectures, propulsion layouts, battery technologies, and mission definitions.

The evtolpy simulator accepts JSON-based inputs describing aircraft geometry (e.g., wingspan, fuselage dimensions, rotor diameter), aerodynamic and drag-related properties, propulsion system characteristics (e.g., rotor count, thrust and power coefficients, efficiency parameters), mission definitions (e.g., segment speeds, durations, and vertical profiles), battery cell and pack properties (e.g., specific energy, accessible energy fraction, pack integration factor), and relevant environmental conditions such as air density and atmospheric viscosity. A complete list of input parameters is provided in the sample-inputs directory.

This repository also includes source code implementing the Autonomous Battery Units (ABU) concept introduced in the AIAA SciTech Forum 2026 paper
“Autonomous Battery Units as an Enabling Technology for Urban Air Mobility.”

• Mission-based energy and power simulation
• Iterative aircraft sizing loop for MTOW, battery mass, and structural and subsystem mass estimation
• Aerodynamic and rotor performance models based on NASA’s NDARC rotorcraft design database
• Configurable inputs for geometry, aerodynamics, propulsion, environment, and battery characteristics
• Modular Python package suitable for research, teaching, and early-stage conceptual design of eVTOL aircraft

• Python 3.x
• matplotlib

• analysis: Analysis scripts and study workflows
• docs: Framework documentation and methodology notes
• evtol: Core Python package
• references: Supporting reference materials and technical sources
• sample-inputs: Example configuration files for testing and demonstrations
• tests: Package unit tests
• README.md: This document

Analysis scripts are organized by study type within the analysis/ directory. Each analysis follows a similar workflow consisting of a logging step followed by a plotting step.

The simulator is driven by a JSON input file that defines both the aircraft configuration and mission parameters. In the examples below, test-all.json specifies vehicle geometry, aerodynamic and propulsion properties, battery characteristics, and the sequence of mission segments. Users may modify this file to define custom aircraft configurations and mission profiles. This JSON file serves as the primary input to the evtolpy simulator.

cd analysis/mission-segment-energy/src
python log_mission_segment_energy.py ../cfg/test-all.json ../log/
python plt_mission_segment_energy.py ../log/mission-segment-energy.csv ../plt/

cd analysis/mission-segment-power/src
# Follow similar logging and plotting steps as above

cd analysis/mission-segment-weight/src
# Follow similar logging and plotting steps as above

cd analysis/mission-segment-abu-analysis/src
# Follow similar logging and plotting steps as above

This repository may be cited using the following BibTeX entry:

@software{evtolpy2026,
  author = {Nguyen, Khoa D. and Hogge, Dylan and Riris, John and Sarojini, Darshan and Denby, Bradley},
  title  = {evtolpy: A Design and Simulation Framework for eVTOL Aircraft},
  url    = {https://github.com/starbelt/evtolpy},
  year   = {2026}
}

The most recent publication introducing evtolpy and the ABU framework was presented at the AIAA SciTech Forum 2026 and may be cited as:

@inproceedings{nguyen2026autonomous,
  title     = {Autonomous Battery Units as an Enabling Technology for Urban Air Mobility},
  author    = {Nguyen, Khoa D. and Hogge, Dylan and Riris, John and Sarojini, Darshan and Denby, Bradley},
  booktitle = {AIAA SciTech 2026 Forum},
  year      = {2026},
  doi       = {},
  url       = {}
}