carculator_truck
Prospective environmental and economic life cycle assessment of medium and heavy duty vehicles.
A fully parameterized Python model developed by the Technology Assessment group of the Paul Scherrer Institut to perform life cycle assessments (LCA) of medium and heavy duty trucks. Based on the Life Cycle Assessment tool for passenger vehicles carculator.
See the documentation for more detail, validation, etc.
The model has been introduced and detailed in a publication to the journal Environmental Science and Technology.
[1] Sacchi R, Bauer C, Cox BL. Does Size Matter? The Influence of Size, Load Factor, Range Autonomy, and Application Type on the Life Cycle Assessment of Current and Future Medium and Heavy-Duty Vehicles. Environ Sci Technol 2021. https://doi.org/10.1021/acs.est.0c07773.
How to install?
For the latest version, using conda::
conda install -c romainsacchi carculator_truck
or for a stable release, from Pypi::
pip install carculator_truck
What does it do?
carculator_truck allows to model vehicles across:
- different conventional and alternative powertrains: diesel, compressed natural gas, hybrid-diesel, plugin hybrid, electric, fuel cell
- different gross weight cateogries: 3.5t, 7.5t, 18t, 26t, 32t, 40t and 60t
- different fuel pathways: conventional fuels, bio-based fuels (biodiesel, biomethane), synthetic fuels (Fischer-Tropsch-based synthetic diesel, synhtetic methane)
- different years: from 2000 to 2050. Technological progress at the vehicle level but also in the rest of the world energy system (e.g., power generation) is accounted for, using energy scenario-specific IAM-coupled ecoinvent databases produced by premise.
- Inventories can be imported into Brightway2 and SimaPro 9.x..
The energy model of carculator_truck considers the vehicle aerodynamics, the road gradient and other factors.
It also considers varying efficiencies of the transmission and engine at various load points for each second
of the driving cycle.
The energy model and the calculated tank-to-wheel energy consumption is validated against the simulation software
VECTO.
Benefits of hybrid powertrains are fully conidered: the possibility to recuperate braking energy as well as efficiency gains from engine
downsizing is accounted for.
Global warming potential impacts per ton-km for a 40-t truck, across different powertrain technologies,
using an urban driving cycle.
How to use it?
See the notebook with examples.
Support
Do not hesitate to contact the development team at carculator@psi.ch.
Maintainers
Contributing
See contributing.
License
BSD-3-Clause. Copyright 2020 Paul Scherrer Institut.
1 maintainer
Metadata
1 maintainer
Release files for carculator-truck 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| carculator_truck-0.5.0.tar.gz | 63.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| carculator_truck-0.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 124.7 kB
Release files / carculator_truck-0.5.0.tar.gz
| Download URL | carculator_truck-0.5.0.tar.gz |
|---|---|
| Size | 63.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
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Release files / carculator_truck-0.5.0-py3-none-any.whl
| Download URL | carculator_truck-0.5.0-py3-none-any.whl |
|---|---|
| Size | 61.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.20
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