routee.powertrain 2.0.1

RouteE-Powertrain is a tool for predicting energy usage over a set of road links.

Overview

RouteE-Powertrain is a Python package that allows users to work with a set of pre-trained mesoscopic vehicle energy prediction models for a varity of vehicle types. Additionally, users can train their own models if "ground truth" energy consumption and driving data are available. RouteE-Powertrain models predict vehicle energy consumption over links in a road network, so the features considered for prediction often include traffic speeds, road grade, turns, etc.

The typical user will utilize RouteE's catalog of pre-trained models. Currently, the catalog consists of light-duty vehicle models, including conventional gasoline, diesel, hybrid electric (HEV), plugin hybrid electric (PHEV) and battery electric (BEV). These models can be applied to link-level driving data (in the form of pandas dataframes) to output energy consumption predictions.

Users that wish to train new RouteE models can do so. The model training function of RouteE enables users to use their own drive-cycle data, powertrain modeling system, and road network data to train custom models.

Quickstart

RouteE Powertrain is available on PyPI and can be installed with pip:

pip install pip --upgrade
pip install routee.powertrain

If pip is unavailable, use pip3:

pip3 install pip --upgrade
pip3 install routee.powertrain

(For more detailed instructions, see here)

Then, you can import the package and use a pre-trained model from the RouteE model catalog:

import pandas as pd
import routee.powertrain as pt

# Query for a specific model
print(pt.query_available_models(make="chevrolet", model="bolt", year=2017))

# Load a pre-trained model
model = pt.load_model("chevrolet/bolt_bev/2017/rf_c3326385/v1")

# Inspect the model to see what it expects for input
print(model)

# Predict energy consumption for a set of road links
links_df = pd.DataFrame(
    {
        "distance": [0.1, 0.2, 0.3], # miles
        "speed_mph": [30, 40, 50], # mph
        "grade_percent": [-5.0, 0.0, 5.0], # percent
    }
)

energy_result = model.predict(links_df)

Upgrading from v1

RouteE Powertrain 2.0 is a breaking release. It was previously published as nrel.routee.powertrain; it is now routee.powertrain, and the import path changed to match:

pip uninstall nrel.routee.powertrain
pip install routee.powertrain

-import nrel.routee.powertrain as pt
+import routee.powertrain as pt

Model names, the model file format, and much of the Model API changed as well. See the migration guide for the full list, and CHANGELOG.md for everything in 2.0.0.

Custom v1 .json models can be converted in place:

routee-powertrain convert-v1 MyModel.json out/ --make toyota --model camry --year 2016