Update: Karan 2018-11-16

Problem Statement: Characterizing aerodynamic forces on quadcopters flying in close proximity due to their respective downwash.

I will be using some acronyms in my posts and will list them once: CF – crazyflie (the smallest quad we have – until now); MQ – miniquad; LQ – large quad.

1. Quick summary

A quick summary of what I have done till now, to have a connection and not suddenly start with this week’s updates:

  • Conducted proximity flight experiments with different pairs of quads (CF-CF, LQ-CF, LQ-MQ). When I say LQ-MQ experiment, it means that LQ was at the bottom and MQ at the top.
  • Collected data for each experiment.
  • Wrote a script to obtain the forces experienced by the quads and their variation with vertical and horizontal separation.

Here are some sample plots of aerodynamic forces vs separation for LQ-MQ experiments:

These plots may seem like a random point cloud with no meaning, and this is what I have been struggling with over the past 3 weeks. The following methods were tried to mitigate this and get a trend:

  • Simulated dummy forces to confirm that there is nothing wrong with the script. A spring force was added in the simulator and a plot made for its data. The plot showed a clear trend and hence it was verified that there was nothing wrong in the script.
  • Moving average: Noise could be one factor leading to randomness and the belief is that a moving average can essentially cancel out the randomness. This did not help – I still get a meaningless point cloud.
  • Filtering based on horizontal separation: All the data points with a horizontal separation greater than the sum of radii of the 2 quads were removed to only keep the data in which there was an overlap between the 2 quads in top view. This again did not give any results for a single experiment, but when data for multiple experiments was plotted together, there was some trend that could be observed. See plot below for LQ-MQ experiment:

2. This week’s updates

For this week, the following was work was done:

  • Analyzed data to get aerodynamic forces on the top vehicle. It experiences “near zero” forces. These forces are less than 5% of the weight and hence can be neglected (maybe I can include these in the future for better control). The forces on the bottom vehicle though are of the order of 10% or more of the vehicle weight. Sample plot shown below for LQ-MQ experiment.


  • Conducted time of flight tests for the miniquad with various payloads. The miniquad weighs 150 g. Here are the flight times with a fully charged 800 mAh (2S) battery for various payloads:
    • 0 g – 270 s
    • 50 g – 213 s
    • 100 g – 169 s
    • We weren’t able to sustain the flight for a 150 g payload. This turned out to be a voltage drop issue which was rectified this week. The issue was as follows:
      • The battery voltage dropped to about 5.2 V for a fully charged 2S battery.
      • This reduced the maximum power output to a point beyond which the motors could not produce enough thrust to even hover.
      • Miniquad crashed.
  • The rectification was achieved by using a higher capacity battery – a fully charged 1600 mAh battery (weight – 90 g). This doubles the current capacity and can provide enough power to the motors even with the voltage drop
    • Now the voltage dropped to 6.7 V
    • The miniquad could hover sustainably for a lot more time.
3. Planned work for next week:
  • Theoretically estimate downwash flow velocities for the quadrotors using actuator disk model. Use this to get an estimate of forces on the bottom vehicle.
  • Finalize BOM (Bill of Materials) for miniquad v2.0 and order the necessary components.
4. Plan for next 30 days:
  • Conduct MQ-LQ experiments. (note the reversed order).
  • Analyze the log files of the above experiments.
  • Characterize torque disturbances. These are very likely to be more harmful than force disturbances, in terms of stability of the bottom quad.
  • Conduct more experiments with a smaller step size for ‘richer’ data.
  • Analyze frequency content of the disturbances and see if it correlates with anything (RPM of motors, etc.).