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https://github.com/romainsacchi/carculator
Prospective environmental and economic life cycle assessment of vehicles made blazing fast.
https://github.com/romainsacchi/carculator
Last synced: 12 days ago
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Prospective environmental and economic life cycle assessment of vehicles made blazing fast.
- Host: GitHub
- URL: https://github.com/romainsacchi/carculator
- Owner: romainsacchi
- License: bsd-3-clause
- Created: 2019-06-07T11:42:08.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-02-11T11:29:13.000Z (9 months ago)
- Last Synced: 2024-06-11T18:12:59.843Z (5 months ago)
- Language: Python
- Homepage: http://carculator.psi.ch
- Size: 128 MB
- Stars: 47
- Watchers: 8
- Forks: 14
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-blazingly-fast - carculator - Prospective environmental and economic life cycle assessment of vehicles made blazing fast. (Python)
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README
# ``carculator``
Prospective environmental and economic life cycle assessment of vehicles made blazing fast.
A fully parameterized Python model developed by the [Technology Assessment group](https://www.psi.ch/en/ta) of the
[Paul Scherrer Institut](https://www.psi.ch/en) to perform life cycle assessments (LCA) of passenger cars and light-duty vehicles.
See [the documentation](https://carculator.readthedocs.io/en/latest/index.html) for more detail, validation, etc.
See our [examples notebook](https://github.com/romainsacchi/carculator/blob/master/examples/Examples.ipynb) as well.
## Table of Contents
- [Background](#background)
- [What is Life Cycle Assessment](#what-is-life-cycle-assessment)
- [Why carculator](#why-carculator)
- [Install](#install)
- [Usage](#usage)
- [As a Python library](#as-a-python-library)
- [As a web app](#as-a-web-app)
- [Support](#support)
- [Maintainers](#maintainers)
- [Contributing](#contributing)
- [License](#license)
## Background
### What is Life Cycle Assessment?
Life Cycle Assessment (LCA) is a systematic way of accounting for environmental impacts along the relevant phases of the life of a product or service.
Typically, the LCA of a passenger vehicle includes the raw material extraction, the manufacture of the vehicle, its distribution, use and maintenance, as well as its disposal.
The compiled inventories of material and energy required along the life cycle of the vehicle is characterized against some impact categories (e.g., climate change).
In the research field of mobility, LCA is widely used to investigate the superiority of a technology over another one.
### Why ``carculator``?
``carculator`` allows to:
* produce [life cycle assessment (LCA)](https://en.wikipedia.org/wiki/Life-cycle_assessment) results that include conventional midpoint impact assessment indicators as well cost indicators
* ``carculator`` uses time- and energy scenario-differentiated background inventories for the future, based on outputs of Integrated Asessment Model [REMIND](https://www.pik-potsdam.de/research/transformation-pathways/models/remind/remind).
* calculate hot pollutant and noise emissions based on a specified driving cycle
* produce error propagation analyzes (i.e., Monte Carlo) while preserving relations between inputs and outputs
* control all the parameters sensitive to the foreground model (i.e., the vehicles) but also to the background model
(i.e., supply of fuel, battery chemistry, etc.)
* and easily export the vehicle models as inventories to be further imported in the [Brightway2](https://brightwaylca.org/) LCA framework
or the [SimaPro](https://www.simapro.com/) LCA software.
``carculator`` integrates well with the [Brightway](https://brightwaylca.org/) LCA framework.
``carculator`` was built based on work described in [Uncertain environmental footprint of current and future battery electric vehicles by Cox, et al (2018)](https://pubs.acs.org/doi/abs/10.1021/acs.est.8b00261).
## Install
``carculator`` is at an early stage of development and is subject to continuous change and improvement.
Three ways of installing ``carculator`` are suggested.
We recommend the installation on **Python 3.7 or above**.
### Installation of the latest version, using conda
conda install -c romainsacchi carculator
### Installation of a stable release from Pypi
pip install carculator
## Usage
### As a Python library
Calculate the fuel efficiency (or ``Tank to wheel`` energy requirement) in km/L of petrol-equivalent of current SUVs for the driving cycle WLTC 3.4
over 800 Monte Carlo iterations:
```python
from carculator import *
import matplotlib.pyplot as plt
cip = CarInputParameters()
cip.stochastic(800)
dcts, array = fill_xarray_from_input_parameters(cip)
cm = CarModel(array, cycle='WLTC 3.4')
cm.set_all()
TtW_energy = 1 / (cm.array.sel(size='SUV', year=2020, parameter='TtW energy') / 42000) # assuming 42 MJ/L petrol
l_powertrains = TtW_energy.powertrain
[plt.hist(e, bins=50, alpha=.8, label=e.powertrain.values) for e in TtW_energy]
plt.xlabel('km/L petrol-equivalent')
plt.ylabel('number of iterations')
plt.legend()
```
Compare the carbon footprint of electric vehicles with that of rechargeable hybrid vehicles for different size categories today and in the future
over 500 Monte Carlo iterations:
```python
from carculator import *
cip = CarInputParameters()
cip.stochastic(500)
dcts, array = fill_xarray_from_input_parameters(cip)
cm = CarModel(array, cycle='WLTC')
cm.set_all()
scope = {
'powertrain': ['BEV', 'PHEV'],
}
ic = InventoryCalculation(cm)
results = ic.calculate_impacts()
data_MC = results.sel(impact_category='climate change').sum(axis=3).to_dataframe('climate change')
plt.style.use('seaborn')
data_MC.unstack(level=[0, 1, 2]).boxplot(showfliers=False, figsize=(20, 5))
plt.xticks(rotation=70)
plt.ylabel('kg CO2-eq./vkm')
```
For more examples, see [examples](https://github.com/romainsacchi/carculator/blob/master/examples/Examples.ipynb).
## As a Web app
``carculator`` has a [graphical user interface](https://carculator.psi.ch) for fast comparisons of vehicles.
## Support
Do not hesitate to contact the development team at [[email protected]](mailto:[email protected]).
## Maintainers
* [Romain Sacchi](https://github.com/romainsacchi)
* [Chris Mutel](https://github.com/cmutel/)
## Contributing
See [contributing](https://github.com/romainsacchi/carculator/blob/master/CONTRIBUTING.md).
## License
[BSD-3-Clause](https://github.com/romainsacchi/carculator/blob/master/LICENSE). Copyright 2023 Paul Scherrer Institut.