Stop trusting manufacturer lab tests. We run actual aerodynamic physics and live weather data to show you the truth.
No black boxes. No manufacturer bias. Here's exactly how our algorithm turns raw physics into the number you see.
We compute drag force, rolling resistance, and drivetrain losses from actual vehicle specs. No guessing.
Air density changes with temperature. We adjust the physics formula dynamically if you input a city.
A machine-learning bridge cross-references the math with real-world highway tests. Physics is dominant — ML only nudges.
Manufacturer figures (EPA, WLTP) are obtained under controlled lab conditions optimized for the test — constant temperature, smooth road, no accessories, specific speed cycles. Our algorithm models real-world highway conditions, which is why our estimate is almost always lower — and more accurate.
Five primary parameters per vehicle: weight_kg, cx (drag coefficient), frontal_area_m2, battery_net_kwh, and tire_width_mm. From these we calculate aerodynamic drag, rolling resistance, and drivetrain losses.
Cold air is denser, increasing aerodynamic drag. Cold temps also raise battery internal resistance and force the cabin heater. We ping OpenWeatherMap for your city's live temperature, recalculate air density (ρ) and apply a thermal penalty.
RealEVRange Estimate ÷ Manufacturer Claim × 100.
85%+ = Relatively honest. 75–84% = Moderate gap. Below 75% = Significant overstatement.