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How we know the number is real.

A GPS dyno is only worth trusting if its accuracy can be checked. Every figure below is generated from the same benchmark that gates each release — controlled synthetic recovery, real repeated road sessions, raw signal quality, outlier honesty, and a committed precision history. Nothing here is a mock-up.

01

The math is controlled

Fig. 01 source: committed benchmark
A known synthetic engine curve recovered by Powertora within about a Powertora-second of the truth.

We build a known engine curve, simulate a protocol pull and coast-down with a GPS-noise model calibrated from real RaceBox and Dragy hardware, then run the full production pipeline and score the recovered curve against the truth. Across 30 noise seeds and four engine shapes (smooth, cam-step, intake-ripple, fine texture) peak power lands within about ±1.3 PS — so the recovery is measured against ground truth, not asserted.

02

Real runs repeat

Fig. 02 source: committed benchmark
Three road runs each for a Honda EP1 and FK2, with the merged curve and its confidence band.

No ground truth exists for a real car, so precision is repeatability. Here are the last three road runs for a naturally-aspirated EP1 and a turbo FK2 — the faint lines are individual pulls, the bold line is the merged result, and the shaded band is its measured run-to-run scatter. The EP1 session holds to ~1.3% (±0.8 PS at the peak); the noisier turbo FK2 to ~2.8% — and the band widens exactly where the runs actually disagree.

03

25 Hz signal, honestly filtered

Fig. 03 source: committed benchmark
Raw 25 Hz GPS speed samples versus the Kalman-smoothed estimate the pipeline uses.

A power curve is only as good as the speed trace behind it. This is a real pull: every raw 25 Hz GPS sample (dots) and the zero-phase Kalman estimate the pipeline differentiates for acceleration (line). High sample rate plus a physics-aware smoother is what turns raw Doppler speed into a clean curve — without rounding away real engine features.

04

Bad data is dropped, not hidden

Fig. 04 source: committed benchmark
A wheelspin pull detected as an outlier and excluded from the merged result.

A merge only helps if a bad pull can’t poison it. When a run falls sustainedly below the consensus — wheelspin, a missed shift, a lift — it is flagged and excluded from the average rather than quietly dragging the number down. (Illustrative: a synthetic wheelspin dip injected into one of three runs.)

05

Tracked on every change

Fig. 05 source: committed benchmark
Committed precision history across algorithm versions.

Accuracy isn’t a launch-day claim — it’s a committed benchmark. Every change to the pipeline is scored against the synthetic suite and the real fixtures before it ships, and the result is appended to a committed history. Precision is engineered and watched over time, not asserted once.

The method, in one line

Synthetic engines prove the math is controlled; real fixtures prove it repeats; the committed history proves it stays that way. Power is crank-equivalent by measured loss, metric PS, DIN-corrected — the honest number, with its uncertainty shown.

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