{"id":186,"date":"2026-05-17T15:10:44","date_gmt":"2026-05-17T15:10:44","guid":{"rendered":"https:\/\/milaracing.nexalance.com\/technology\/"},"modified":"2026-06-08T19:37:27","modified_gmt":"2026-06-08T17:37:27","slug":"technology","status":"publish","type":"page","link":"https:\/\/milaracing.nexalance.com\/fr\/technology\/","title":{"rendered":"Technology"},"content":{"rendered":"
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\n Home<\/a>\n \/<\/span>\n Technology<\/span>\n<\/div>\n\n
\n\n \n
\n
\n
\u2014 Inside Quasar<\/div>\n

One algorithm.Two sensor systems.Zero guesswork.<\/em><\/h1>\n

A real-time grip model that reads what your tires are doing \u2014 internally, externally, and contextually \u2014 and turns five raw signals into a single number you can ride by.<\/p>\n <\/div>\n

\n \n \n \n \n \n <\/radialgradient>\n <\/defs>\n \n \n QUASAR<\/text>\n \n \n \n TT<\/text>\n TTPMS \u00b7 INTERNAL<\/text>\n \n \n \n \n IR<\/text>\n IR \u00b7 SURFACE<\/text>\n \n \n \n \n IMU<\/text>\n 6-AXIS IMU \u00b7 LEAN<\/text>\n \n \n \n \n BLE<\/text>\n APP \u00b7 BLE 5.2<\/text>\n \n <\/svg>\n <\/div>\n <\/div>\n\n \n
\n
\n
0Hz<\/span><\/div>
Sensor sample rate<\/div><\/div>\n
\u00b10.2\u00b0C<\/span><\/div>
Thermal accuracy<\/div><\/div>\n
\u00b10.05bar<\/span><\/div>
Pressure accuracy<\/div><\/div>\n
<12ms<\/span><\/div>
End-to-end latency<\/div><\/div>\n <\/div>\n <\/div>\n\n \n
\n
\n
01 \u00b7 Architecture<\/div>\n

From rubber to display in twelve milliseconds.<\/em><\/h2>\n

Quasar splits the work across three physical units: sensors inside and on the tire, the Quasar device on the bike, and the firmware that fuses everything into a single score.<\/p>\n <\/div>\n

\n
\n
01 \u00b7 Sensors<\/div>\n <\/svg>\n

Inside & on the tire<\/h4>\n

TTPMS valve-stem units read pressure and internal air temperature. IR sensors aimed at the contact patch read surface temperature 1000 times per second.<\/p>\n

\n
Radio<\/span>BLE 5.2<\/span><\/div>\n
Power<\/span>CR2032 \u00b7 18mo<\/span><\/div>\n
Range<\/span>3m LoS<\/span><\/div>\n <\/div>\n <\/article>\n
Transmit<\/span>
<\/div><\/div>\n
\n
02 \u00b7 Quasar device<\/div>\n <\/svg>\n

On the handlebar<\/h4>\n

ARM Cortex M4 receives all sensor streams, runs the T-Grip fusion algorithm locally, and renders the live display \u2014 no cloud, no app required.<\/p>\n

\n
CPU<\/span>STM32F405 \u00b7 168MHz<\/span><\/div>\n
Display<\/span>1.69\" LCD<\/span><\/div>\n
Ingress<\/span>IP67<\/span><\/div>\n <\/div>\n <\/article>\n
Sync<\/span>
<\/div><\/div>\n
\n
03 \u00b7 Companion app<\/div>\n <\/svg>\n

iOS & Android<\/h4>\n

Optional. Configures tire compounds, records session telemetry, and reviews past rides with full data export.<\/p>\n

\n
Compat<\/span>iOS 14+ \u00b7 Android 9+<\/span><\/div>\n
Export<\/span>CSV \u00b7 GPX \u00b7 MAT<\/span><\/div>\n
Storage<\/span>Local \u00b7 no cloud<\/span><\/div>\n <\/div>\n <\/article>\n <\/div>\n <\/section>\n\n \n
\n
\n
02 \u00b7 Signals<\/div>\n

What the device reads.Five inputs. One truth.<\/em><\/h2>\n

Every signal is sampled at 1000Hz, filtered with a Kalman estimator, and timestamp-aligned within \u00b11ms before the fusion stage.<\/p>\n <\/div>\n

\n
SIG\u00b701<\/span>SIG\u00b702<\/span>SIG\u00b703<\/span>SIG\u00b704<\/span>SIG\u00b705<\/span><\/div>\n
<\/div>\n
\u2193 T-Grip Score<\/div>\n <\/div>\n
\n
\n
SIG \u00b7 01<\/span><\/svg><\/div>\n

Internal pressure<\/h4>\n

TTPMS \u00b7 Valve stem<\/p>\n

Direct measurement from inside the tire chamber. Detects slow leaks, temperature-driven pressure rise, and out-of-range conditions before they reach the rider's senses.<\/p>\n

\n
Range<\/span>0.5 \u2013 5.5 bar<\/span><\/div>\n
Accuracy<\/span>\u00b10.05 bar<\/span><\/div>\n
Resolution<\/span>0.01 bar<\/span><\/div>\n <\/div>\n <\/article>\n
\n
SIG \u00b7 02<\/span><\/svg><\/div>\n

Temp\u00e9rature interne du pneu<\/h4>\n

TTPMS \u00b7 Air chamber<\/p>\n

Tire chamber air temperature. The bulk-thermal proxy \u2014 slow to change, but what tells the algorithm whether the carcass has reached operating window.<\/p>\n

\n
Range<\/span>-20 \u2013 120 \u00b0C<\/span><\/div>\n
Accuracy<\/span>\u00b10.5 \u00b0C<\/span><\/div>\n
Refresh<\/span>4 Hz<\/span><\/div>\n <\/div>\n <\/article>\n
\n
SIG \u00b7 03<\/span><\/svg><\/div>\n

Surface temperature<\/h4>\n

IR \u00b7 Non-contact thermal<\/p>\n

Infrared reading of the actual tread surface where rubber meets road. Reacts within 50ms \u2014 fast enough to catch the difference between a flick and a sustained lean.<\/p>\n

\n
Range<\/span>-40 \u2013 200 \u00b0C<\/span><\/div>\n
Accuracy<\/span>\u00b10.2 \u00b0C<\/span><\/div>\n
Refresh<\/span>1000 Hz<\/span><\/div>\n <\/div>\n <\/article>\n
\n
SIG \u00b7 04<\/span><\/svg><\/div>\n

Lean angle<\/h4>\n

6-axis IMU \u00b7 Gyro + accelerometer<\/p>\n

On-board inertial measurement unit estimates real-time roll angle. Combined with grip score, drives the adaptive red-line indicators on the display.<\/p>\n

\n
Range<\/span>0 \u2013 65 \u00b0<\/span><\/div>\n
Accuracy<\/span>\u00b10.5 \u00b0<\/span><\/div>\n
Refresh<\/span>200 Hz<\/span><\/div>\n <\/div>\n <\/article>\n
\n
SIG \u00b7 05<\/span><\/svg><\/div>\n

Tire profile model<\/h4>\n

Calibrated \u00b7 per compound<\/p>\n

Pre-loaded compound profiles for 47 OEM and aftermarket tires. Each profile maps temperature\/pressure\/load to expected friction coefficient \u2014 the baseline against which live signals are compared.<\/p>\n

\n
Profiles<\/span>47 compounds<\/span><\/div>\n
Updates<\/span>Quarterly OTA<\/span><\/div>\n
Custom<\/span>App-configurable<\/span><\/div>\n <\/div>\n <\/article>\n <\/div>\n <\/section>\n\n \n
\n
\n
03 \u00b7 Pipeline<\/div>\n

Five signals.One number.<\/em><\/h2>\n

The T-Grip fusion algorithm doesn't average. It weights \u2014 dynamically \u2014 based on which signal carries the most predictive value in the current riding condition. The model adapts every millisecond.<\/p>\n <\/div>\n

\n
01<\/div>

Acquire<\/h4>

Five sensor streams arrive over BLE 5.2 with sequence numbers and timestamps.<\/p>2 ms<\/span><\/div>\n

<\/svg><\/div>\n
02<\/div>

Filter<\/h4>

Kalman filter rejects outliers, smooths high-frequency noise, reconstructs missing samples.<\/p>3 ms<\/span><\/div>\n

<\/svg><\/div>\n
03<\/div>

Align<\/h4>

All signals interpolated to a common 1000Hz timestamp grid within \u00b11ms tolerance.<\/p>1 ms<\/span><\/div>\n

<\/svg><\/div>\n
04<\/div>

Fuse<\/h4>

Weighted-confidence model combines signals with the compound profile to estimate friction.<\/p>4 ms<\/span><\/div>\n

<\/svg><\/div>\n
05<\/div>

Render<\/h4>

T-Grip score (0\u2013100), color zone, and lean-angle limit are pushed to the display.<\/p>2 ms<\/span><\/div>\n <\/div>\n

\n
Total \u00b7 12 ms<\/div>\n
End-to-end latency<\/div>\n <\/div>\n <\/section>\n\n \n
\n
\n
04 \u00b7 The T-Grip model<\/div>\n

Signification du score.<\/em><\/h2>\n

Le T-Grip est un score de 0 \u00e0 100 repr\u00e9sentant la confiance en temps r\u00e9el dans tes pneus. En dessous de 50, tu es en dehors de la zone de s\u00e9curit\u00e9. Au-dessus de 80, tu es dans la fen\u00eatre de fonctionnement optimale. Les zones de couleur traduisent cela en un langage visuel lisible en un coup d'\u0153il, plein angle, \u00e0 200 km\/h.<\/p>\n <\/div>\n

\n
\n
Grip en direct \u00b7 Exemple de lecture<\/div>\n
\n
0\u201345<\/div>\n
45\u201375<\/div>\n
75\u201395<\/div>\n
95+<\/div>\n <\/div>\n
<\/div><\/div>\n
82<\/div>
T-Grip \u00b7 Zone id\u00e9ale<\/div><\/div>\n
\n
Cold 22<\/div>\n
Warm 58<\/div>\n
Ideal 92<\/div>\n
Hot 100<\/div>\n <\/div>\n <\/div>\n
\n
\n
Zone froide<\/h5>

\u00c9vitez l'angle \u2013 faites chauffer les pneus d'abord<\/p><\/div>0 \u2013 45<\/span><\/article>\n

Zone chaude<\/h5>

Fais chauffer les pneus progressivement<\/p><\/div>45 \u2013 75<\/span><\/article>\n

Zone id\u00e9ale<\/h5>

Fen\u00eatre de fonctionnement \u2013 attaque librement<\/p><\/div>75 \u2013 95<\/span><\/article>\n

Hot zone<\/h5>

Reduce intensity \u2014 cooling needed<\/p><\/div>95 \u2013 100<\/span><\/article>\n <\/div>\n

\n
Update rate<\/div>
10 Hz on display<\/div><\/div>\n
Confidence<\/div>
95% predictive accuracy<\/div><\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/section>\n\n \n
\n
\n
05 \u00b7 Hardware<\/div>\n

Built in Turin.Tested everywhere.<\/em><\/h2>\n <\/div>\n
\n
\"Quasar<\/div>
Main unit<\/div>

Quasar \u00b7 IP67 alloy housing<\/h4><\/div><\/article>\n
\"Quasar<\/div>
Display<\/div>

1.69\" LCD \u00b7 240\u00d7280<\/h4><\/div><\/article>\n
\"TTPMS<\/div>
Sensor \u00b7 01<\/div>

TTPMS \u00b7 18-month battery<\/h4><\/div><\/article>\n
\"IR<\/div>
Sensor \u00b7 02<\/div>

IR \u00b7 1000Hz thermal<\/h4><\/div><\/article>\n <\/div>\n <\/section>\n\n \n
\n
\n
06 \u00b7 Honestly compared<\/div>\n

Against the alternatives.<\/em><\/h2>\n <\/div>\n
\n
Capability<\/div>\n
Quasar<\/div>\n
Standard TPMS<\/div>\n
Track-only telemetry<\/div>\n\n
Internal pressure<\/div>\n
Yes<\/span><\/div>\n
Yes<\/span><\/div>\n
Yes<\/span><\/div>\n\n
Temp\u00e9rature interne du pneu<\/div>\n
Yes<\/span><\/div>\n
No<\/span><\/div>\n
Yes<\/span><\/div>\n\n
Surface temperature (IR)<\/div>\n
Yes \u00b7 1000Hz<\/span><\/div>\n
No<\/span><\/div>\n
Pro tier only<\/span><\/div>\n\n
Real-time grip score<\/div>\n
Yes \u00b7 T-Grip<\/span><\/div>\n
No<\/span><\/div>\n
Post-session only<\/span><\/div>\n\n
Adaptive lean limit<\/div>\n
Yes<\/span><\/div>\n
No<\/span><\/div>\n
No<\/span><\/div>\n\n
Compound profiles<\/div>\n
47 compounds<\/span><\/div>\n
N\/A<\/span><\/div>\n
8 compounds<\/span><\/div>\n\n
Setup time<\/div>\n
< 5 min<\/span><\/div>\n
~15 min<\/div>\n
2+ hours<\/span><\/div>\n\n
Wiring required<\/div>\n
None<\/span><\/div>\n
Optional<\/div>\n
Bike-side ECU<\/span><\/div>\n\n
Price range<\/div>\n
CHF 299 \u2013 CHF 499<\/strong><\/div>\n
CHF 80 \u2013 CHF 200<\/div>\n
CHF 2,000+<\/div>\n <\/div>\n <\/section>\n\n \n
\n
\n
07 \u00b7 Deeper still<\/div>\n

For the engineers.<\/em><\/h2>\n <\/div>\n
\n
\n How does the IR sensor avoid being fooled by sunlight or road heat?<\/summary>\n
\n

The IR sensor uses dual-wavelength differential pyrometry. It samples two adjacent infrared bands and subtracts the ambient radiation component, isolating the tread's emissive signature regardless of solar load or hot tarmac underneath.<\/p>\n

Calibration \u00b7<\/b> Two-point per compound \u00b7 Reflectivity coefficient 0.93 \u00b1 0.02 for carbon-black rubber compounds<\/div>\n <\/div>\n <\/details>\n
\n What happens if a sensor fails or runs out of battery mid-ride?<\/summary>\n
\n

The T-Grip algorithm degrades gracefully. If a single signal drops out, the remaining four are reweighted automatically and a confidence indicator on the display reflects the reduced certainty. You always know when the system is operating at less than full accuracy.<\/p>\n

Failure modes \u00b7<\/b> Graceful degradation \u00b7 Confidence display ranges 60% (one signal lost) to 30% (three signals lost)<\/div>\n <\/div>\n <\/details>\n
\n How is the algorithm validated?<\/summary>\n
\n \n

Every firmware release is validated against a reference dataset of 12,400 laps collected with the Honda LCR Castrol MotoGP team across 28 track configurations and seasonal conditions. New compound profiles undergo on-track validation before being released to production firmware.<\/p>\n

Validation set \u00b7<\/b> 12,400 reference laps \u00b7 28 circuits \u00b7 Predictive accuracy 95% within \u00b10.05 friction coefficient<\/div>\n \n <\/div>\n <\/details>\n
\n Can I export the raw data?<\/summary>\n
\n

Yes. The companion app exports session data as CSV (human-readable), GPX (mapping software), or MAT (MATLAB \/ Octave \/ Python). All signals are timestamped at native sample rate; no downsampling. Storage is local \u2014 your data never leaves your device.<\/p>\n

Formats \u00b7<\/b> CSV \u00b7 GPX \u00b7 MAT \u00b7 BIN (raw) \u00b7 Avg session size 24 MB \/ hour<\/div>\n <\/div>\n <\/details>\n
\n What's the firmware update cadence?<\/summary>\n
\n \n

Quarterly major releases. Monthly bugfix patches. New compound profiles roll out as tire manufacturers release new generations. All updates are free for the life of the device \u2014 there are no premium tiers behind a paywall.<\/p>\n

Distribution \u00b7<\/b> OTA via app \u00b7 Average payload 1.4 MB \u00b7 Rollback supported \u00b7 No cloud auth required<\/div>\n \n <\/div>\n <\/details>\n <\/div>\n <\/section>\n\n \n
\n
Specs without a ride are noise.<\/div>\n

See the numbers under your tires.<\/em><\/h2>\n

The fastest way to understand the technology is to feel the difference on your next ride.<\/p>\n

\n Boutique Kits Quasar \u2192<\/span><\/a>\n Talk to an engineer<\/a>\n <\/div>\n <\/section>\n\n<\/section>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Home \/ Technology \u2014 Inside Quasar One algorithm.Two sensor systems.Zero guesswork. A real-time grip model that reads what your tires are doing \u2014 internally, externally, and contextually \u2014 and turns five raw signals into a single number you can ride by. QUASAR TT TTPMS \u00b7 INTERNAL IR IR \u00b7 SURFACE IMU 6-AXIS IMU \u00b7 LEAN […]<\/p>\n","protected":false},"author":0,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-186","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/pages\/186","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/types\/page"}],"replies":[{"embeddable":true,"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/comments?post=186"}],"version-history":[{"count":4,"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/pages\/186\/revisions"}],"predecessor-version":[{"id":543,"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/pages\/186\/revisions\/543"}],"wp:attachment":[{"href":"https:\/\/milaracing.nexalance.com\/fr\/wp-json\/wp\/v2\/media?parent=186"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}