PsiWings/ Kyte Series/ X1

Current development · Grade 9

Kyte X1. Understand the energy of flight.

Kyte X1 is the first experimental aircraft in the PsiWings research program. Its primary objective is to create a reliable relationship between aircraft configuration, flight condition, electrical power consumption, and real-world endurance — before we make any bigger claims.

Generation

Verb

Understand

Program stage

Build → Bench

Target output

First flight-energy dataset

— Primary research question

Why does an aircraft
consume the energy it does?

This is not a rhetorical question. It is the specific problem Kyte X1 exists to attack — not with claims, but with instrumentation, flight tests, and a growing dataset.

CHAPTER 01

— Research objectives

Four things Kyte X1 must be able to answer.

OBJ.01

Measure real power

Voltage, current, temperature, RPM — sampled fast enough to see the instantaneous behaviour of the aircraft, not just averaged trends.

OBJ.02

Understand flight state

Airspeed, altitude, climb rate, attitude, wind, payload. Every environmental factor becomes a variable — not an excuse for the numbers.

OBJ.03

Model from first principles

Physics-based equations first — P = f(V, m, ρ, config). Then fit them to real flight data, and note exactly where the model still lies.

OBJ.04

Compare & iterate

Every flight begins with a prediction and ends with a post-flight review. The delta between them is where the next experiment starts.

CHAPTER 02

— Instrumentation

What Kyte X1 measures.

— Sensor axis

Kyte X1 v0.1

— Signals

12 8 sensed · 4 derived

— Sample rates

100 · 50 · 10 Hz

— Telemetry

433 MHz LoRa on-board SD

Side-view exploded diagram of Kyte X1 showing eight numbered sensor callouts: pitot, GNSS, IMU, barometer, motor tach, bus shunt, battery BMS, and ESC temperature — FIG. 02 · Side-view · Eight sensors, eight callouts SENSOR SUITE

Kinematics · how the aircraft moves

6 signals

AirspeedPitot

V_asm/s

PositionGNSS

lat · londegrees

AttitudeIMU

φ θ ψdegrees

AltitudeBarometer

hm AGL

—

Climb ratederived

ḣm/s

—

Wind estimatederived

V_wm/s

Propulsion · where the energy goes

4 signals

Motor tachHall sensor

ωrpm

Bus currentShunt

Iamps

Battery voltageBMS

Vvolts

—

Instant powerderived

P = V·Iwatts

Thermal · how the aircraft feels

2 signals

Battery temperatureBMS thermistor

T_bat°C

ESC temperatureinternal probe

T_esc°C

—

CHAPTER 03

— Powertrain

Where the energy flows.

Every joule of battery energy must travel through four conversions before it becomes flight. Each conversion costs a percentage. This diagram shows exactly where the losses are — measured individually, so the biggest opportunity to improve is always visible.

Sankey-style energy flow diagram: 100 J of battery energy narrows through ESC (96 J), motor (81 J), and propeller (63 J), with losses of 4 J heat, 15 J winding losses, and 18 J propeller slip peeling off downward — FIG. 03 · Energy flow · 100 J battery → 63 J flight 63% END-TO-END EFFICIENCY

Where every 100 joules go

63%to flight

63 JFlight · thrust × distance
18 JPropeller · slip & tip vortex
15 JMotor · winding & friction
4 JESC · switching heat

— Research finding

The propeller is the largest single point of loss — and the one with the most physics still worth studying.

Battery and ESC losses have well-established engineering solutions. Motor efficiency is a mature discipline. But propeller aerodynamics — especially at these Reynolds numbers — is where a young engineer can still find real questions to answer.

CHAPTER 04

— Research relationships

The relationships Kyte X1 sets out to quantify.

One aircraft — six directions to ask questions in. Each axis below is a physical variable that changes how much energy the aircraft consumes. Each has a shape that first-principles physics predicts. The research is measuring how far reality actually deviates from that prediction.

Compass-rose diagram of Kyte X1 at center with six radial axes labelled AIRSPEED · CLIMB RATE · WIND · STATE OF CHARGE · PAYLOAD · DISTANCE, each showing a miniature expected curve at its endpoint — FIG. 04 · Six variables · Six curves · One aircraft FLIGHT ENVELOPE

— The research question

Every gap between the predicted curve and the measured curve is a new engineering question worth flying.

— Potential output

The first PsiWings
flight-energy dataset.

Sampled at high rate. Annotated by flight condition. Cross-referenced with wind and payload. Released internally as the foundation for Kyte X2. Not a paper yet — but a real, honest, useful dataset.

Next: Kyte X2 · Predict → See the four-year roadmap