#automotive

US vehicle data as an API, built on the official NHTSA datasets. Decode any VIN into make, model, year, trim, body class, engine, drivetrain, fuel type and assembly plant. Browse the full catalogue of vehicle makes and the models offered for any make and year. Then pull the safety record for a vehicle: open recalls with the affected component, the manufacturer summary, consequence and remedy; owner complaints flagging crashes, fires, injuries and deaths; and the official NCAP crash-test star ratings (overall, frontal, side and rollover). Real government data, no key needed upstream. Ideal for car marketplaces, dealer tools, VIN-lookup widgets, insurance and recall-check apps.

api.oanor.com/nhtsa-api

Turbocharger and boost engineering maths as an API, computed locally and deterministically — the pressure-ratio, charge-air and airflow numbers a tuner, engine builder or motorsport engineer sizes forced induction with. The pressure-ratio endpoint gives the compressor pressure ratio = absolute manifold pressure ÷ ambient = (atmospheric + boost) ÷ atmospheric, so 10 psi at sea level is a 1.68 ratio — the x-axis of every compressor map, which climbs at altitude where ambient pressure is lower. The charge-air endpoint shows why an intercooler matters: compressing air heats it (T₂ = T₁ × (1 + (PR^0.2857 − 1)/efficiency)), and hot air is less dense, so the real gain is the charge density ratio = pressure ratio × (T₁/T_charge), not the pressure ratio alone — 10 psi at 70 % compressor efficiency makes ~93 °C and a 1.37 density ratio with no intercooler, rising toward 1.6 once an intercooler claws back the heat, and the estimated power gain tracks the density. The airflow endpoint gives the engine mass airflow ≈ displacement × (rpm/2) × volumetric efficiency × charge density, in lb/min — the y-axis of the compressor map you plot against the pressure ratio to land in the efficient island and avoid surge or choke. Everything is computed locally and deterministically, so it is instant and private. Ideal for engine-tuning and turbo-sizing tools, dyno and data-logging apps, and motorsport calculators. Pure local computation — no key, no third-party service, instant. Sizing estimates — verify on a dyno. 3 compute endpoints. For engine displacement and compression use an engine API; for shop compressed air a compressor API.

api.oanor.com/turbo-api

Air-fuel ratio and lambda maths for engine tuning as an API, computed locally and deterministically — the lambda, AFR and mixture numbers a tuner, ECU developer or motorsport engineer dials fuelling in with. The lambda endpoint turns a measured air-fuel ratio into lambda (the AFR divided by the fuel's stoichiometric AFR — 14.7 for gasoline) and the equivalence ratio φ = 1/lambda, classifying the mix as rich, stoichiometric or lean: a gasoline AFR of 13.0 is lambda 0.88, an 11.6 % rich mixture, the sort used at wide-open throttle for power and a cooler, safer burn. The afr endpoint runs it the other way — pick a target lambda and it gives the AFR the wideband should read — and because the AFR number is fuel-specific (E85's stoichiometric AFR is about 9.8, not 14.7) it always works from the right fuel, which is why pros tune in lambda when switching fuels. The mixture endpoint links the air the engine breathes to the fuel the injectors must add: give an air mass and a target lambda and it returns the fuel mass (or vice-versa), the heart of how an ECU sizes fuelling from measured airflow. Built-in stoichiometric ratios for gasoline, E10, E85, ethanol, methanol, diesel, LPG, propane, methane/CNG and hydrogen, or pass your own. Everything is computed locally and deterministically, so it is instant and private. Ideal for engine-tuning and dyno tools, ECU and standalone-management apps, motorsport and data-logging utilities. Pure local computation — no key, no third-party service, instant. 3 compute endpoints. For engine displacement and power use an engine API; for chemical reaction stoichiometry a stoichiometry API.

api.oanor.com/airfuel-api

Quarter-mile drag-strip maths as an API, computed locally and deterministically — the classic empirical estimates a racer, tuner or car enthusiast uses to relate a car's power and weight to its performance. The et endpoint gives the predicted elapsed time and trap speed from flywheel horsepower and race weight using the standard formulas — ET = 5.825 × (weight ÷ hp) raised to the one-third, trap speed = 234 × (hp ÷ weight) raised to the one-third — so a 3,000 lb car with 300 hp is predicted to run about 12.6 seconds at 109 mph, assuming a competent launch and decent traction. The horsepower endpoint runs it in reverse: because trap speed is set by power-to-weight and barely by the launch, hp ≈ weight × (trap ÷ 234) cubed is a popular way to estimate flywheel power straight off a timeslip. The power-to-weight endpoint gives the ratio that actually decides acceleration — in horsepower per pound, horsepower per ton and watts per kilogram, the cleanest cross-unit figure — with a performance class from commuter through hot hatch and supercar to hypercar, because a light 200 hp car can beat a heavy 400 hp one. Everything is computed locally and deterministically, so it is instant and private. Ideal for drag-racing and tuner apps, car-spec and comparison tools, automotive enthusiasts and motorsport dashboards. Pure local computation — no key, no third-party service, instant. Empirical estimates assuming a good launch and traction — not a timeslip. 3 compute endpoints. For aerodynamic drag use a drag API; for gearing use a gear-ratio API.

api.oanor.com/quartermile-api

Tire maths as an API, computed locally and deterministically — the size, pressure and speedometer numbers a driver, fitter or fleet manager works out before fitting a tyre. The size endpoint turns a P-metric spec into the real dimensions: overall diameter = rim + 2 × the sidewall (section width × aspect ratio), so a 225/45R17 stands about 25 inches tall, rolls a 78-inch circumference and turns roughly 808 times a mile — the numbers behind fitment, gearing and clearance. The pressure endpoint gives the hot pressure from a cold pressure and the temperature change, because pressure tracks absolute temperature (P2/P1 = T2/T1), about +1 psi per 10 °F — so 32 psi set cold at 70 °F reads ~34.6 after warming to 100 °F, and drops on a cold morning, which is what trips the warning light. The speedo-error endpoint gives the speedometer error and true speed from a tyre-size change: a taller tyre makes the speedo read low, so actual speed = indicated × new diameter ÷ old — go up 4 % and 60 on the dial is really 62.5. Everything is computed locally and deterministically, so it is instant and private. Ideal for tyre-shop and fitment apps, fleet and 4x4 build tools, speedo-recalibration calculators, and automotive sites. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 compute endpoints. Estimates — always set pressure cold to the placard.

api.oanor.com/tire-api

Vehicle-suspension maths as an API, computed locally and deterministically — the spring and frequency numbers a racer, tuner or chassis engineer sets a car up with. The wheel-rate endpoint converts a spring rate to the rate the wheel actually feels: wheel rate = spring rate × motion ratio², where the motion ratio is the spring's travel per unit of wheel travel — a 200 lb/in spring at a 0.7 motion ratio gives a 98 lb/in wheel rate, because the spring's leverage softens it. The frequency endpoint gives the ride (natural) frequency at a corner, f = (1/2π)·√(wheel rate × g ÷ corner sprung weight), the number that really sets the ride: luxury cars run about 0.5–1.2 Hz, sporty street 1.2–1.7, race cars 2 Hz and up. The spring-rate endpoint inverts it — the spring rate needed to hit a target frequency for a corner weight and motion ratio — so you can pick the frequency for the car's job and get the spring straight out. Everything is computed locally and deterministically, so it is instant and private. Ideal for motorsport and tuning apps, chassis-setup and corner-balancing tools, suspension-design calculators, and engineering study aids. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 compute endpoints. Estimates — real ride also depends on damping and tyres.

api.oanor.com/suspension-api

Window-tint maths as an API, computed locally and deterministically — the net VLT numbers an installer or car owner picks a film by. The catch with tint is that visible light transmission multiplies through layers: factory automotive glass already passes only about 70–80 % of light, so a film’s rated VLT is not what you end up with. The vlt endpoint multiplies it out — net % = the product of each layer’s VLT ÷ 100 — so a 35 % film on 78 % factory glass nets 27.3 %, a 5 % limo film on the same glass nets 3.9 %, and you can stack several layers in one call; it also describes how dark that looks, from near-clear down to blackout. The required endpoint runs it backwards: to land on a target net VLT through known glass you need a film of target ÷ glass × 100, so hitting a 35 % net on 78 % glass takes a 44.9 % film — and it flags the impossible case where the target is lighter than the bare glass already allows. Everything is computed locally and deterministically, so it is instant and private. Ideal for auto-tint, detailing, glass and automotive app developers, film-selection and compliance tools, and shop software. Pure local computation — no key, no third-party service, instant. Legal limits vary by jurisdiction — check local law. Live, nothing stored. 2 compute endpoints.

api.oanor.com/windowtint-api

Tyre-size geometry as an API, computed locally and deterministically. The dimensions endpoint parses a metric tyre code such as 205/55R16 — or separate width, aspect ratio and rim values — into its full geometry: the sidewall height (width·aspect/100), the overall diameter (rim·25.4 + 2·sidewall) in millimetres and inches, the rolling circumference, and the revolutions per kilometre and per mile; a 205/55R16 works out to a 112.75 mm sidewall and a 631.9 mm (24.88 in) outside diameter. The compare endpoint takes an original and a replacement size and computes the speedometer error and ground-clearance change of swapping between them: because the speedometer is calibrated to the original rolling diameter, a larger tyre makes it read low, so true speed = indicated · OD_new/OD_old, and a tyre that is 2 % bigger means an indicated 100 is really about 102 km/h. Staying within ±3 % keeps the error and clearance change small. Tyre codes use the metric P-metric/Euro-metric form. Everything is computed locally and deterministically, so it is instant and private. Ideal for automotive, tyre-shop, fitment, car-enthusiast, fleet and vehicle-spec app developers, plus-sizing and speedo-error tools, and garage software. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 2 endpoints. This is metric tyre geometry; for fuel economy use a fuel-economy API.

api.oanor.com/tiresize-api

Vehicle-braking physics as an API, computed locally and deterministically. The stopping-distance endpoint computes the total distance to stop a vehicle as the sum of the reaction distance the vehicle travels during the driver's reaction time, v·t, and the braking distance v²/(2·μ·g) — which grows with the square of speed, so doubling the speed quadruples the braking distance — from the speed, the tyre-road friction coefficient, the reaction time and the road grade, along with the deceleration and the time to stop. The braking-force endpoint computes the braking force F = m·a and the deceleration of a vehicle, either from a stop-in-a-given-distance (a = v²/2d) or from the friction coefficient (a = μ·g), with the kinetic energy that must be dissipated as heat. The skid-speed endpoint reconstructs the speed at the start of a skid from the skid-mark length, v = √(2·μ·g·d), a lower-bound estimate used in accident reconstruction. Speed is in km/h by default (also m/s or mph), mass in kg and distances in m; dry asphalt has μ ≈ 0.7, wet ≈ 0.4 and ice ≈ 0.1. Everything is computed locally and deterministically, so it is instant and private. Ideal for automotive, driving-safety, fleet, telematics and accident-reconstruction app developers, stopping-distance and forensic tools, and physics education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is vehicle braking; for general kinematics use a kinematics API and for an object on a slope an inclined-plane API.

api.oanor.com/brake-api

Internal-combustion engine maths as an API, computed locally and deterministically. The displacement endpoint computes an engine's swept volume from the bore, the stroke and the number of cylinders, V = (π/4)·bore²·stroke per cylinder, in cubic centimetres, litres and cubic inches, and classifies the bore-to-stroke geometry as oversquare, square or undersquare. The compression endpoint relates the compression ratio and the clearance volume, CR = (swept + clearance)/clearance — give the clearance to get the ratio or the ratio to get the clearance — and, with a boost pressure, estimates the effective compression ratio of a forced-induction engine. The power-to-weight endpoint computes the power-to-weight ratio in horsepower per tonne, kilowatts per tonne and watts per kilogram, the weight per horsepower, and, with a displacement, the specific output in horsepower per litre. Bore and stroke are in millimetres, volumes in cc, weight in kilograms and power in horsepower or kilowatts. Everything is computed locally and deterministically, so it is instant and private. Ideal for automotive, motorsport, motorcycle and engine-builder app developers, build-spec and tuning tools, and mechanical education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is engine geometry and tuning; for EPA fuel-economy data use a fuel-economy API and for tyre sizes a tyre-calculator API.

api.oanor.com/engine-api

Trailer-towing weight maths as an API, computed locally and deterministically. The tongue endpoint computes the tongue (hitch) weight as a percentage of the loaded trailer weight and reports the recommended 10–15 % range — too little tongue weight is the main cause of trailer sway. The capacity endpoint computes the maximum trailer weight a tow vehicle can pull, GCWR − curb weight − payload (the passengers and cargo in the vehicle), and checks a proposed trailer against it with the margin remaining. The payload endpoint computes the vehicle payload still available once the trailer is hitched, GVWR − curb weight − tongue weight, since the tongue weight presses down on the tow vehicle and counts against its payload rating. Everything is computed locally and deterministically, so it is instant and private. Ideal for RV, caravan, trailer and fleet apps, tow-vehicle matching and load-planning tools, and automotive calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Guidance only — follow the manufacturer's ratings. 3 endpoints. This is trailer-towing weights; for tyre size and rolling circumference use a tyre API.

api.oanor.com/towing-api

Tyre, wheel and drivetrain maths as an API. The tire endpoint parses a metric tyre size such as 205/55R16 into all its real dimensions — section width, aspect ratio, sidewall height, rim and overall diameter in millimetres and inches, rolling circumference, and revolutions per kilometre and per mile. The compare endpoint takes an original and a replacement tyre size and works out the change in overall diameter and the resulting speedometer and odometer error — so you know how much faster you are really going than the dial shows after a tyre change. The gear endpoint computes a gear ratio from ring and pinion tooth counts, or the road speed from engine RPM, total gear ratio and tyre size. Everything is computed locally and deterministically, so it is instant and private. Ideal for automotive and motorsport apps, tyre shops and fitment tools, modding and restomod planning, and vehicle configurators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is tyre and drivetrain maths; for vehicle specifications by VIN use a vehicle-database API.

api.oanor.com/tirecalc-api

Official US vehicle fuel-economy data as an API, powered by FuelEconomy.gov — the joint US EPA and Department of Energy resource behind the fuel-economy window sticker on every car, SUV and truck sold in the United States since 1984. Browse the catalogue step by step — model years, then makes, then models, then the engine/transmission trims (each carrying the vehicle id you need for the detail call) — and pull a vehicle's complete fuel-economy record: city, highway and combined MPG, fuel type, engine (number of cylinders and displacement), transmission, EPA vehicle class and drivetrain, the estimated annual fuel cost, tailpipe CO2 emissions in grams per mile, the barrels of petroleum consumed per year and the estimated five-year fuel-cost saving (or extra spend) versus an average new vehicle. Ideal for car-shopping and comparison tools, total-cost-of-ownership and emissions calculators, fleet management and sustainability reporting. The data is authoritative, official EPA/DOE test data and is public domain; it covers US-market light-duty vehicles. Vehicle ids come from the trims endpoint, reached via the year -> make -> model -> trim chain.

api.oanor.com/fueleconomy-api

Decode any Vehicle Identification Number (VIN) into a full, structured vehicle specification — make, manufacturer, model, year, trim, series, body class, vehicle type, drive type, doors, engine (cylinders, displacement, horsepower, configuration and primary/secondary fuel), transmission style, gross vehicle weight rating and the manufacturing plant (country, city, state, company). Partial VINs with wildcards are supported and an optional model year improves accuracy. The API also lists every vehicle make (optionally for a vehicle type such as car, truck or motorcycle) and all models for a given make and year. Backed by the official NHTSA vPIC database, with clean, predictable JSON and no raw-data wrangling. Every endpoint accepts input via the query string or the request body. Ideal for automotive marketplaces, insurance and fleet tools, dealer and parts catalogues, and vehicle-registration flows.

api.oanor.com/vehicledb-api

Decode any Vehicle Identification Number (VIN) into make, model, year, body class, engine, fuel type, drivetrain and plant — and browse vehicle makes and models by type and year. Powered by the official NHTSA vPIC database.

api.oanor.com/cars-api