Metadata-Version: 2.4
Name: fastsim
Version: 3.1.0
Classifier: Programming Language :: Python :: 3
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Requires-Dist: pandas>=2.1.2
Requires-Dist: polars~=1.4
Requires-Dist: plotly~=6.0
Requires-Dist: numpy>=1.18
Requires-Dist: typing-extensions~=4.12
Requires-Dist: pyyaml>=6.0
Requires-Dist: msgpack>=1.2.1
License-File: LICENSE
License-File: NOTICE
Summary: Tool for modeling vehicle powertrains
Author-email: NLR/BEST/CIMS/TETA Group <fastsim@nlr.gov>
Requires-Python: >=3.10, <3.16
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Homepage, https://www.nlr.gov/transportation/fastsim

<img src="docs/assets/fastsim-icon.svg" height="250">

<div style="height: 2rem;"></div>

The Future Automotive Systems Technology Simulator (**FASTSim**) is an open-source vehicle powertrain simulation tool for evaluating the efficiency and performance of on-road vehicles.
Developed by the National Laboratory of the Rockies (NLR), it provides fast, credible estimates of powertrain performance and energy consumption.
FASTSim models powertrain technologies from conventional internal-combustion vehicles to hybrids, plug-in hybrids, and battery electric vehicles, and has been used to simulate light-duty passenger vehicles, two-wheelers, and a wide variety of medium- and heavy-duty vehicles.

FASTSim is designed for rapid analysis, making it practical to run many
simulations and compare technology scenarios across vehicle classes and use
cases. It occupies a practical middle ground between basic efficiency assumptions and detailed component/control models, balancing accuracy, runtime speed,
and input burden for large scenario sweeps. FASTSim outputs are a core layer in other NLR tools, including:
- [RouteE](https://www.nlr.gov/transportation/route-energy-prediction-model):
  an energy prediction tool and energy-aware routing engine
- [T3CO](https://www.nlr.gov/transportation/t3co):
  a medium- and heavy-duty vehicle total cost of ownership assessment tool
- [ADOPT](https://www.nlr.gov/transportation/adopt):
  a technology-driven consumer choice and vehicle market adoption model

FASTSim models conventional vehicles, hybrids, plug-in hybrids,
battery electric vehicles, and fuel-cell electric vehicles over a set of
standard regulatory drive cycles. You can also define custom vehicles and custom drive cycles to simulate any on-road vehicle over realistic scenarios.

For detailed documentation on FASTSim, including usage, background, and modeling philosophy, see https://natlabrockies.github.io/fastsim.

For a collection of prebuilt vehicle models, see the [FASTSim Vehicle Database](https://github.com/NatLabRockies/fastsim-vehicles).

# Installation

FASTSim is available as a package for use in
[Python 3.10 through 3.15](https://www.python.org).

In an active Python environment, run:

```bash
pip install fastsim
```

This installs the latest FASTSim release as a Python package.

For more detailed instructions, including compilation of FASTSim from source, see the
[Installation](https://natlabrockies.github.io/fastsim/installation)
page of
[FASTSim's documentation](https://natlabrockies.github.io/fastsim).

## Usage

For instructions on using FASTSim to simulate on-road vehicle performance, see the
[User Guide](https://natlabrockies.github.io/fastsim/user-guide)
section of
[FASTSim's documentation](https://natlabrockies.github.io/fastsim).

