wltp: generate WLTC gear-shifts based on vehicle characteristics

JupyterLab for WLTP Development Status Integration-build status cover-status Documentation status Latest Version in PyPI Downloads Issues count Code Style

release:1.0.0.dev9
date:2019-08-08 16:44:35
documentation:https://wltp.readthedocs.org/ (build-date: Aug 09, 2019)
source:https://github.com/JRCSTU/wltp
live-demo:https://mybinder.org/v2/gh/JRCSTU/wltp/master?urlpath=lab/tree/Notebooks/README.md
pypi-repo:https://pypi.python.org/pypi/wltp
keywords:UNECE, automotive, car, cars, driving, engine, fuel-consumption, gears, gearshifts, rpm, simulation, simulator, standard, vehicle, vehicles, wltc, nedc
Copyright:2013-2019 European Commission (JRC-IET)
License:EUPL 1.1+

A python package to generate the gear-shifts of Light-duty vehicles running the WLTP driving-cycles, according to UNECE’s GTRs.

_images/wltc_class3b.png

Figure 1: WLTP cycle for class-3b Vehicles

Attention

This wltp python project is still in alpha stage, in the send that its results are not “correct” by the standard, and no WLTP dyno-tests should rely currently on them.

Some of the known deficiencies are described in these places:

  • In the Changes.
  • Presented in the diagrams of the Tests, Metrics & Reports section.
  • Imprinted in the test_wltp_db test-case which automatically compares, on each build, the mean RPMs & Gears of this program against Heinz’s phase-1a (end of 2014) MSAccess, for a pre-determined set of Heinz-db vehicles. Currently, genrated mean-RPMs differ from Heinz-db < 0.5% and gears < 5% for a 1800-step class-3 cycle.

Glossary

WLTP
The Worldwide harmonised Light duty vehicles Test Procedure, a GRPE informal working group
UNECE
The United Nations Economic Commission for Europe, which has assumed the steering role on the WLTP.
GRPE
UNECE Working party on Pollution and Energy - Transport Programme
GTR
GTRs
Any of the Global Technical Regulation documents of the WLTP .
GS Task-Force
The Gear-shift Task-force of the GRPE. It is the team of automotive experts drafting the gear-shifting strategy for vehicles running the WLTP cycles.
WLTC
The family of pre-defined driving-cycles corresponding to vehicles with different PMR. Classes 1,2, 3a & 3b are split in 2, 4, 4 and 4 parts respectively.
Unladen mass
UM or Curb weight, the weight of the vehicle in running order minus the mass of the driver.
Test mass
TM, the representative weight of the vehicle used as input for the calculations of the simulation, derived by interpolating between high and low values for the CO2-family of the vehicle.
Downscaling
Reduction of the top-velocity of the original drive trace to be followed, to ensure that the vehicle is not driven in an unduly high proportion of “full throttle”.
pandas-model
The container of data that the gear-shift calculator consumes and produces. It is implemented by wltp.pandel.Pandel as a mergeable stack of JSON-schema abiding trees of strings and numbers, formed with sequences, dictionaries, pandas-instances and URI-references.
JSON-schema
The JSON schema is an IETF draft that provides a contract for what JSON-data is required for a given application and how to interact with it. JSON Schema is intended to define validation, documentation, hyperlink navigation, and interaction control of JSON data. You can learn more about it from this excellent guide, and experiment with this on-line validator.
JSON-pointer
JSON Pointer(RFC 6901) defines a string syntax for identifying a specific value within a JavaScript Object Notation (JSON) document. It aims to serve the same purpose as XPath from the XML world, but it is much simpler.