| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: Heavy truck drive cycle |
| tags: |
| - time-series |
| - automotive |
| - electric-vehicles |
| - energy |
| - tabular |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: data.csv |
| --- |
| |
| # Heavy truck drive cycle |
|
|
| 3,831 seconds of driving logged once a second from a diesel heavy truck (15 to 32 tonnes): 58 km over about 14 hours, |
| with three stops of half an hour or more in between. It is the data behind the |
| [electric truck battery sizing app](https://huggingface.co/spaces/prteek/electric-truck-battery-sizing), which replays |
| it as if the truck were electric to see what battery and charger it would need. |
| Code: [github.com/prteek/real-world-vehicle-simulation](https://github.com/prteek/real-world-vehicle-simulation). |
|
|
| Rows are logged only while the truck is running: a jump in `time_s` larger than a second is a stop. |
|
|
| | column | content | |
| |---|---| |
| | `time_s` | seconds since the start of the log (gaps are stops) | |
| | `speed_kph` | vehicle speed [km/h]; 255 means no reading | |
| | `engine_torque_nm` | net engine torque [N·m]; negative when the engine is driven | |
| | `overall_gear_ratio` | overall torque ratio from the engine to the transmission output | |
| | `transmission_output_speed_rpm` | transmission output shaft speed [rpm] | |
| | `accelerator_pedal_pct` | accelerator pedal position [%] | |
| | `vehicle_mass_kg` | estimated vehicle mass [kg] | |
| | `road_grade_pct` | road grade [%], averaged | |
|
|
| Power at the wheels is engine torque × overall gear ratio × transmission output speed. Brake power is not logged; the |
| code estimates it as what is left after road load, grade and inertia whenever the driver is off the accelerator and |
| slowing down. |
|
|
| ## Road load (`road_load.json`) |
| |
| The road-load model, frozen: power [W] = `rolling` × mass × g × cos(grade) × speed + `aero` × speed³ (speed in m/s, |
| grade = `road_grade_pct` / 100). It was fitted by least squares on the whole 428 km log this stretch came from, on the |
| moments the truck was driving rather than braking (R² 0.74 on a held-out 30%); the stretch alone is too uniform in |
| speed to separate the two terms. |
| |
| ```python |
| import json, pandas as pd |
| from huggingface_hub import hf_hub_download |
|
|
| log = pd.read_csv(hf_hub_download("prteek/drive-cycle", "data.csv", repo_type="dataset")) |
| road_load = json.load(open(hf_hub_download("prteek/drive-cycle", "road_load.json", repo_type="dataset"))) |
| ``` |
| |
