Examples
Examples
Try the starting example
- Comparable full-to-full legs JSON [distance km,fuel consumed L]
- [[200,10],[300,12]]
- Usable scenario fuel (L)
- 15
- Distance-weighted observed consumption (L/100 km)
- 4.4
- Scenario range at aggregate consumption (km)
- 340.909091
- Range at worst observed leg efficiency (km)
- 300
- Range at best observed leg efficiency (km)
- 375
Try another scenario
- Comparable full-to-full legs JSON [distance km,fuel consumed L]
- [[200,10],[300,12]]
- Usable scenario fuel (L)
- 12
- Distance-weighted observed consumption (L/100 km)
- 4.4
- Scenario range at aggregate consumption (km)
- 272.727273
- Range at worst observed leg efficiency (km)
- 240
- Range at best observed leg efficiency (km)
- 300
Calculation method
Calculation method
Distance-weighted observed consumption (L/100 km)
100*sum(fuel)/sum(distance).
Scenario range at aggregate consumption (km)
usableFuel*sum(distance)/sum(fuel).
Range at worst observed leg efficiency (km)
usableFuel*min(distance/fuel).
Range at best observed leg efficiency (km)
usableFuel*max(distance/fuel).
Symbols and units
- a
- Comparable full-to-full legs JSON [distance km,fuel consumed L]
- b
- Usable scenario fuel (L)
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Calculation steps and notation
sum(list) adds all entries in the list.
Assumptions & limits
Assumptions & limits
- Observed full-to-full consumption log; range is conditional on repeating supplied observations, not guaranteed reserve, road, weather or fuel-availability guidance. Supported limits: 1..1000 legs with distance,fuel>0; usable fuel>=0; refueling method consistent.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.