By Emrik Joner
Wing Flying Product Page
When building a drone, one of the first steps is choosing the right motor. To get the best performance, it is essential to test multiple motors and select the most efficient one for your design. There are plenty of motors on the market, including many varieties of electric motors that are specifically built for use in drone design. In this article, we will focus solely on electric motors, touching on the following topics:
Note: We will be using the Series thrust stand to gather motor and propeller data for this article.
Before getting into the principle of the brushless mechanism, let’s first take a look at it’s components.
Electromagnets and Permanent Magnets:
A conductive wire coiled around a metallic base will not act like a magnet, but when a current flows through the wire, it will induce it to behave as a magnet would. This is commonly referred to as an electromagnet. If a negative current flows through that same wire, the magnet now has the opposite effect, it would attract another magnet instead of pushing it away.
The parts seen on the inner circle of figure 3 are the electromagnets, while on the outer circle we have the permanent magnets. To turn on the motor, you activate one of the electromagnets by delivering an electric current to its coils. This will make the rotor start to spin as the permanent magnet experiences repulsion from the like-electromagnet and tries to align with an opposite permanent magnet on the stator.
This will only make it spin for a short period of time as the electromagnet and opposite permanent magnet align. The next step is to power another electromagnet to keep the rotation from stopping, followed by the next electromagnet, and the next, and so on.
By delivering a three-phase current at a given frequency, the motor will spin at a speed equal to the frequency of that signal. The throttle on a drone’s controller is used for changing the motor’s speed, with a higher throttle input sending a higher frequency signal to the drone. The Electronic Speed Controller (ESC) controls the signal delivery to adjust the motor’s speed according to the throttle’s input.
An ESC or Electronic Speed Controller controls the electric motor by delivering electric signals that are translated into changes in speed or even a reversal of the rotation. It uses direct current coupled with a switch system to achieve an alternate three-phase current. This output current can then be modified by changing the rate at which the switches open and close in the circuit.
Brushless ESCs need information on the current position of the rotor to be able to start the motor and choose a direction for the rotation. To determine its position, the ESC uses information from the last unpowered electromagnet to measure its induction. This induction varies depending on where the closest permanent magnet is and the closer it is to the electromagnet, the stronger is the magnetic field induced.
The throttle is used to vary the speed of the motor. To do so, the ESC has to adjust the switching frequency based on the throttle’s signal. There are several signal delivery protocols with different performances, the most common ones being Oneshot, Multishot and Dshot.
The difference between them is the frequency of the signals delivered. Shorter frequencies allow a faster reaction time. Furthermore, the Dshot protocol is different from the two others because it sends a digital signal instead of an analog signal. This makes the signal more reliable since it is less sensitive to electrical noise and is more precise with its higher resolution.
Further reading: List of Brushless Motor Manufacturers
Every brushless motor is made of two main parts, a stator and a rotor. The stator is static, it does not move, and it holds the electromagnets. The rotor is the rotating component that holds the permanent magnets. There are two types of Brushless DC motors: Inrunner and outrunner models.
For inrunner motors, the rotor rotates 'inside' the stator, or further inwards relative to the motor casing. Outrunner motors have the opposite set-up as the rotor rotates 'outside' of the stator or further outwards, see figure 6. Both models have their pros and cons.
When comparing an inrunner and an outrunner of the same size, it is easy to see that the diameter on which the forces are applied is different. This happens because the electromagnets take a lot more space than the rotor carrying the permanent magnets. If the electromagnets are located inside, the diameter is bigger compared to if they are located on the outside (figure 6).
In addition to size, the consequence for the motor’s performances are also important to consider. A larger diameter means more torque because the force is applied further from the center of rotation, while a smaller diameter would be better for high RPM. Thus inrunners run best at high speed but generate less torque while outrunners work best with larger propellers because they can output more torque, but spin at slower speed.
Brushless Motors in the Drone Industry:
For the reasons described above, eVTOLs often use outrunners for vertical thrust due to their high torque. Inrunners are more commonly used for ducted fan jets or fixed wing aircraft and for horizontal movements requiring high RPM. This is easy to understand through the Kv value of a motor, also known as its RPM/Volt value.
This value determines at which speed the motor will spin if 1 V is sent through it. Therefore, an inrunner typically has a higher Kv value than an outrunner of the same size because, as stated above, the inrunner has a smaller rotor which spins faster for the same voltage. You will often see the Kv value displayed first when browsing brushless motors.
Further reading: Why You Should Test Your Drone's Motors and Propellers
When talking about the performance of a drone, we often think about the flight time. Unfortunately, the most advanced battery technologies can’t compete with gas motors in terms of the weight/energy ratio. The only solution is to carefully select the electrical components that will use the battery charge most efficiently.
Many factors can optimize the energy consumption of a battery. One of these factors is the motor’s efficiency. A higher efficiency helps increase the weight/energy ratio, thus getting higher performance from the motor and the drone itself. Testing a motor is crucial to be aware of the differences between a manufacturer’s specifications and the motor’s quality. To demonstrate this idea, we present a comparison of two similar BLDC motors with different price ranges.
To compare the motors' performance, we used the RCbenchmark Series thrust stand. It is capable of measuring thrust, torque, voltage, current, RPM and efficiency. The data acquisition is done using the RCbenchmark software. The two motors tested are Ts of Kv and Kv respectively. Both motors spin the same 7-inch propeller with a pitch of 4.
The first graph in figure 7 displays the efficiency of both motors compared to the throttle. The second graph shows the efficiency at specific speeds. Clearly, the smaller Kv motor requires more throttle to run efficiently. It won’t achieve the same efficiency as the Kv motor in this set-up with the same propeller. The efficiency range is also better on the Kv motor, meaning the motor keeps a high efficiency at both low and top speed.
On the other hand, the smaller motor can operate at higher speed and would probably be more efficient with a smaller propeller. A drone used for transport would use a smaller motor to be able to stay idle and stable at low speed.
To get a full comparison, we would need to know the purpose of the drone and the RPM it will operate at. It is possible that the Kv motor is more efficient with a different propeller suited for a different function. Only through testing can we find out.
Finally, let’s talk about what to look for when choosing a motor. The most important characteristic is motor Kv, which describes the rotation speed you get for the power input to the motor. A motor with Kv will spin at rotations per minute for every volt sent to the motor.
Size is closely related to the Kv. A wide and large motor will often have higher torque but lower Kv and use a bigger propeller, while a thin but longer motor will have high Kv, low torque and would be best suited for a small propeller. This makes sense when you consider that a larger motor operates at lower RPM while a small motor operates at relatively high RPM.
The maximum power of a motor is also something to take into consideration. Exceeding the motor's power restriction would result in the motor heating up and thus drastically lowering its efficiency or even damaging it. The brand can also change a motor's performance. For the same Kv value, a motor from one brand may perform better than others. That’s why you should test your motor before building a drone around it.
Further reading: How to Calculate Brushless Motor Kv and Motor Poles
As a general rule, it is wise to use the smallest (lightest) motor possible without being in danger of overpowering and overheating it. The reason for this is to reduce the excess weight of a motor that is larger than needed. We have compiled alist of large motor manufacturers with products suitable for heavy-lift and manned drone operations.
UAVs combine aerospace engineering, embedded systems, AI (for autonomy), and network communications—all while needing to meet safety and regulatory standards. Here’s why structured prep is vital:
Demonstrate Technical Versatility
UAV teams are often cross-functional, involving mechanical, electrical, software, and aerospace disciplines.
Employers will probe if you can integrate flight dynamics, sensor data processing, and robust software architectures.
Master Real-Time Control & Safety
Drones operate in dynamic environments, requiring stable flight controllers and quick response to external disturbances.
Interviews often check your ability to design fail-safes, handle sensor failures, and ensure flight stability.
Showcase Automation & Autonomy
As UAVs become more autonomous, your knowledge of path planning, obstacle avoidance, and vision-based navigation can be decisive.
Prepare for questions on algorithms, from Kalman filters to AI-based detection.
Emphasise Communication & Collaboration
UAV development isn’t siloed—frequent collaboration with testers, pilot operators, and regulatory bodies is typical.
Your ability to explain complex flight software or hardware constraints to diverse teams is key.
Adapt to Rapid Evolution
Drone technology moves quickly, with new sensors, better batteries, and evolving government regulations.
Candidates who show an eagerness to learn and adapt stand out.
With thorough preparation across flight control, embedded software, aerial robotics, and safety best practices, you’ll be better equipped to impress in UAV interviews. Next, let’s step through 15 coding questions relevant to UAV roles.
Question: Write embedded C/C++ code that implements a PID controller for regulating the pitch angle of a quadcopter.
What to focus on:
Variables for pitch setpoint, current pitch, error terms,
Summing P, I, D components,
Handling integral windup, ensuring real-time constraints.
Question: Show how you’d fuse accelerometer and gyroscope data to estimate a UAV’s orientation, possibly using a complementary filter.
What to focus on:
IMU raw data handling,
Weighted combination of gyro integration vs. accelerometer stability,
Implementation details (time delta, filter constants).
Question: Implement a finite state machine in C/C++ that transitions a UAV through states: IDLE, TAKEOFF, TRAVEL, HOLD, LAND, based on external triggers.
What to focus on:
Clear transitions and triggers,
Handling emergency overrides,
Code structure for maintainability.
Question: Given a MAVLink data packet, demonstrate code that extracts the message ID, payload, and checks the CRC before passing the data to higher-level logic.
What to focus on:
MAVLink packet format (start byte, length, msg ID, checksum),
Byte-level parsing,
Error detection and handling.
Question: Write code that calculates each motor’s throttle output from pitch, roll, yaw, and collective throttle inputs.
What to focus on:
Summation logic: motor 1 = throttle + pitch_correction + roll_correction - yaw_correction, etc.,
Normalisation or clamping outputs to valid [min, max] range,
Handling potential motor saturations.
Question: Parse an NMEA sentence (e.g., GGA) in C and extract latitude, longitude, and fix quality.
What to focus on:
String tokenisation,
Converting ASCII to float,
Checking data validity or partial sentences.
Question: Demonstrate how to log sensor data (IMU, barometer) in real-time to an SD card. Emphasise minimal overhead and data integrity.
What to focus on:
Buffered writes,
Handling potential brown-out or partial writes,
Timestamping each record from a stable clock.
Question: Implement a simple tracking algorithm (e.g., a colour blob or optical flow) for a drone’s downward camera.
What to focus on:
OpenCV usage (if high-level environment) or custom filtering,
Real-time constraints (frame rate, memory usage),
ROI updates or robust centroid detection.
Question: Write pseudocode that adjusts PID gains in flight based on battery voltage or weight changes to maintain stable flight.
What to focus on:
Monitoring battery voltage changes,
Mapping these changes to gain scheduling,
Smooth transitions vs. abrupt changes in control loop.
Question: Demonstrate a method (in Python or C) for a UAV to broadcast telemetry over a mesh network protocol to ground stations or other UAVs.
What to focus on:
Packet structure, addressing,
Handling dynamic node joins/leaves,
Potential reliability or retry strategies.
Question: Write microcontroller code that captures PWM input from an RC receiver channel to decode user commands.
What to focus on:
Timer/capture registers,
Calculating pulse width, mapping to servo range,
Handling noise or glitch filtering.
Question: Code a function that checks CPU usage, sensor status, battery, and motor currents, then sets a “system healthy” flag if all are within thresholds.
What to focus on:
Data structure for health checks,
Update frequency,
Communication if not healthy (LED blink, error log).
Question: Implement a basic A* algorithm for a drone operating in 2D ground plane (assuming altitude is fixed), returning waypoints around obstacles.
What to focus on:
Occupancy grid or cost map,
Heuristic function (Manhattan or Euclidean),
Constructing final path from closed set.
Question: Outline code that triggers an emergency landing if the RC signal is lost for more than 3 seconds, using barometer and IMU for stable descent.
What to focus on:
Detecting signal loss,
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Gradual throttle cut while maintaining level attitude,
Possibly using GPS for a slow auto-home or direct descent.
Question: Show pseudocode for a simple Kalman filter that combines barometer altitude with vertical acceleration from an IMU to get smoother altitude readings.
What to focus on:
Predict step (acceleration integration),
Update step (barometric measurement),
Covariance updates.
With these coding exercises, you’ll demonstrate your ability to handle sensor data, flight control logic, communication protocols, and navigation. Next, we’ll cover 15 system design scenarios that test higher-level UAV architecture and integration.
Scenario: You’re creating a quadcopter autopilot system from scratch. Outline the major software modules (sensor drivers, state estimation, flight control, failsafe, telemetry).
Key Points to Discuss:
Module boundaries (e.g., sensor fusion separate from attitude control),
Data flows between modules,
Real-time scheduling, priority for control loops.
Scenario: A UAV must communicate live telemetry to a ground control station (GCS). Explain how you’d design the link, message protocol, and GCS UI.
Key Points to Discuss:
Wireless link type (Wi-Fi, 4G, proprietary RF),
Message packaging (MAVLink or custom),
GCS software features (map display, parameter tuning, mission planning).
Scenario: You have 10 drones operating in a formation. Discuss how you’d coordinate collision avoidance, communication, and distributed planning.
Key Points to Discuss:
Communication topology (mesh vs. central coordinator),
Real-time obstacle sharing,
Formation control algorithms (leader-follower, consensus-based).
Scenario: A startup wants a drone delivering small packages in urban areas. Outline the system from route planning, package handling, to safe landing.
Key Points to Discuss:
Geofencing around restricted airspace,
Computer vision or IR sensors for landing site detection,
Integration with a backend for scheduling, updates, track & trace.
Scenario: Design a UAV that takes off vertically but transitions to fixed-wing flight. How do you manage transitions and control surfaces?
Key Points to Discuss:
Two flight modes (multirotor vs. fixed wing), blending control laws,
Motor arrangement or tilt-rotor mechanism,
Minimising instability during transition states.
Scenario: You have a drone with multiple payloads (camera, LiDAR). Propose how to manage power distribution and ensure flight time doesn’t degrade severely.
Key Points to Discuss:
Battery capacity, power rails, current monitoring,
Possibly dynamic load shedding or prioritised power usage,
Heat dissipation for high-power sensors.
Scenario: You need to store flight logs for post-flight analysis. How do you handle multi-source data (IMU, GPS, camera) in a synchronised manner?
Key Points to Discuss:
Timestamps from a unified clock,
Buffering data on SD card or offloading mid-flight to ground,
Overcoming potential file corruption if power is lost suddenly.
Scenario: A drone must detect obstacles in front using stereo cameras or a depth sensor. Outline your approach to real-time processing and avoidance commands.
Key Points to Discuss:
Depth map generation or object detection (e.g., YOLO),
Reaction logic (stop/hover, path re-planning),
Handling latencies or false positives.
Scenario: Design a system for OTA (Over The Air) firmware updates of a drone fleet. Discuss security, rollback, and reliability.
Key Points to Discuss:
Secure bootloader, signature checks,
Partial downloads with resume,
Automatic rollback if new firmware fails at boot.
Scenario: A drone operates beyond visual range. How do you ensure safe, stable flight and regulatory compliance (e.g., detect-and-avoid, real-time telemetry)?
Key Points to Discuss:
Redundant comm links (LTE, satcom?),
Automated sense-and-avoid systems (ADS-B if manned-aircraft integration),
Logging flight data for authority review.
Scenario: A drone can swap payloads (thermal camera, multispectral sensor). Propose how you detect and initialise each payload’s driver at runtime.
Key Points to Discuss:
Physical interface (power, data bus: USB, SPI?),
Autodetect via ID pins or a small EEPROM,
Software modular approach for driver loading, calibration routines.
Scenario: You have 50 drones, each sending telemetry to a cloud service. Design the architecture for real-time monitoring, historical data storage, and alerting.
Key Points to Discuss:
Message broker (MQTT, AMQP),
Database schema for flight logs, events,
Scalable front-end to visualise all drones on a map, with alerts on anomalies.
Scenario: A high-end UAV has two flight controllers for redundancy. Explain how they share sensor data and decide which controller is active if a fault occurs.
Key Points to Discuss:
Synchronising sensor readings, voting or master-slave arrangement,
Health checks, heartbeat signals,
Automatic switchover logic if the master fails.
Scenario: If the drone loses GPS signal mid-flight, propose a system that uses IMU, barometer, and vision to return home or perform a controlled descent.
Key Points to Discuss:
Inertial navigation and relative positioning,
Possibly memorising takeoff location or searching for a known landmark,
Decision thresholds for landing vs. continuing flight.
Scenario: Outline how you’d set up hardware-in-the-loop testing plus real flight tests to certify a UAV’s flight stack.
Key Points to Discuss:
HIL test environment with sensors simulated,
Gradual approach: bench test, tethered flight, open test field,
Logging and documentation for regulatory or internal QA compliance.
These system design scenarios demonstrate your ability to architect complete UAV solutions that integrate sensors, controllers, software modules, and safety measures. Finally, let’s end with interview tips to help you excel.
Revisit Flight Dynamics & Control
Refresh your knowledge of quadcopter or fixed-wing equations of motion, PID controllers, and extended/unscented Kalman filters for state estimation.
Employers expect clarity on how you’d handle real-time feedback loops.
Highlight Practical Projects
If you’ve built or programmed a drone, mention your firmware design, sensor calibration, or flight tests.
Videos or GitHub repos showcasing stable flight or creative UAV tasks can impress.
Understand Key Protocols
MAVLink, CAN, or custom serial protocols are common for UAV communication.
Show you can parse and handle them in code, integrate with ground station software.
Stress Reliability & Safety
Drones can pose risk to property/people. Demonstrate your approach to fail-safes, e-stop logic, sensor fallback, and compliance with local air regulations.
If relevant, mention flight logs or analytics for post-flight checks.
Master Sensor Fusion
UAVs rely on multiple sensors: IMU, GPS, barometer, magnetometer, cameras.
Emphasise knowledge of multi-sensor filtering, outlier rejection, and error handling.
Show Collaboration Skills
UAV projects often require cross-disciplinary collaboration: mechanical frames, electronics, software, regulatory.
Mention times you integrated feedback from mechanical or business teams, or performed user acceptance tests.
Explain Real-World Constraints
Battery life, payload weight, environment hazards (wind, obstacles), and data link reliability.
Employers appreciate design choices that address these constraints effectively.
Stay Current on UAV Trends
Drone deliveries, VTOL systems, swarm AI, 4G/5G connectivity, LiDAR-based autonomy.
Discuss how new sensor or battery tech might impact your designs or approach.
Ask Intelligent Questions
Inquire about the company’s test flight framework, sensor choices, or integration pipeline.
Reflect genuine interest and help you gauge if the environment suits your interests.
Project Confidence & Problem-Solving
UAVs can encounter unpredictable field issues.
Employers value candidates who remain calm under pressure, adapt quickly, and systematically troubleshoot flight anomalies.
By combining robust technical grounding, real-world UAV experiences, and an adaptive mindset, you’ll demonstrate readiness to tackle the complex challenges in UAV development.
In the UAV industry, innovation moves at breakneck pace—blending robotics, aerodynamics, IoT communications, and AI. As you prepare for UAV job interviews, revisiting fundamentals (like flight control, sensor fusion, and safety measures) while practising hands-on coding and system architecture is invaluable. The 30 questions presented here will help hone your understanding of UAV development’s intricacies, from real-time embedded code to high-level swarm coordination.
When you’re ready to find new opportunities in this exciting sector, visit www.uavjobs.co.uk for UK roles at start-ups, large aerospace companies, or research labs. With thorough preparation, you’ll be well‑positioned to seize emerging opportunities and help shape the future of unmanned flight—whether for delivery, inspection, emergency response, or next‑generation passenger drones.
Good luck—and may your UAV interviews take off smoothly!
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