Power-Output-Testing

Code repository for pilot power output testing and thrust determination.

Serial Port Setup

Follow these steps to set up the system using the serial port:

1. Clone the repository.
2. Open MATLAB and Arduino IDE.
3. Plug in the Arduino into your machine.
4. Connect the Arduino to COM3 (or another port, adjusting the code accordingly).
5. Open Arduino_Power_Code.ino in the Arduino IDE.
6. Under Tools, ensure that Board is set to Arduino Uno, and under Port, make sure it is set to COM3.
7. Upload Arduino_Power_Code.ino to the Arduino.
8. Open SerialPortCode.m in MATLAB.
9. Configure the duration in SerialPortCode.m to be approximately 2 minutes, depending on the test (add 5 seconds for safety).
10. Once SerialPortCode.m is started, enter the data file name (format: initials_#.txt), and when ready, press the space bar to start recording data.

Run the test by starting the code before starting to pedal.

Moment of Inertia Calculation

To find the moment of inertia (MOI) of the test rig:

1. Set up using the serial port as described above.
2. Monitor the live plot for any erroneous indications.
3. Plug data from the trainer ('Record' field) .csv into modelTrainerData.m to get MOI and torqueFriction (table input also supported).

Data Structures

Data from Onland Testing is available in OnlandTesting in OnlandTestingData.mat

OnlandTesting = 

  struct with fields:

    CG: [1×3 struct]
    CJ: [1×2 struct]
    KB: [1×3 struct]
    MC: [1×3 struct]
    MD: [1×3 struct]
    NQ: [1×3 struct]

OnlandTesting.CG(1) =

  struct with fields:

       trainerData: [122×5 table]
       arduinoData: [406×1 double]
    trainerResults: [122×4 table]
    arduinoResults: [406×4 table]
               MOI: 4.0138
         TORQFRICT: 7.0816

OnlandTesting.CG(1).arduinoResults =

  406×4 table

     times      rpm      torque    power 
    _______    ______    ______    ______

          0         0    19.916    41.983
    0.65446    91.678    19.619    110.09

       :         :         :         :   

     119.81    229.24    4.9603    119.82

OnlandTesting.CG(1).trainerResults =

  122×4 table

    times     rpm      torque    power
    _____    ______    ______    _____

       0          0         0       0 
       1     12.241    5.4607       7 

      :        :         :         :  

     121     316.16    7.0374     233 

• trainerData and arduinoData contain data directly from their respective data sources.
• trainerResults and arduinoResults contain processed data in table format, including times, rpm, torque, and power, according to modelTrainerData and deriveValues, respectively.

A binary for water testing will be added once complete

Scripts and Functions

• Arduino_Power_Code.ino Arduino code to read button presses and send activation states to MATLAB through serial communication.

• SerialPortCode.m MATLAB code to read serial data from Arduino using the serialport object, collect and visualize data, and save it to a file.

• derivative.m MATLAB function to compute the derivative of discrete x and y data using various methods.

• deriveValues.m MATLAB function to calculate derived parameters (rpm, torque, power) from revolution times data.

• modelTrainerData.m MATLAB function to process trainer data, compute relevant torque-related parameters, and train a torque model based on linear regression.

• readDataFolder.m MATLAB function to read data from files in subfolders of a specified directory to a struct.

• rpmGen.m MATLAB function to convert revolution times to rpm and time stamps.

• PowerAnalysis.m MATLAB script for loading, processing, and analyzing data from Onland Testing, including visualizing raw data and derived values.

• makeBinaryFiles.m MATLAB script to read data from folders, calculate MOI and torqueFriction, process data from the trainer and Arduino, and save the processed data as a binary .mat file.

• Onland Analysis MATLAB script for performing aggregate analysis on data collected during Onland Power Testing from Arduino.

Notes

• modelTrainerData.m requires the Statistics and Machine Learning Toolbox.
• deriveValues.m requires the Signal Processing Toolbox
• To reference functions in another folder, you can use the following snippet:

oldpath = path;
% assuming your script is in another folder
path(oldpath,'..\Functions')
% your code
path(oldpath)

Model

flowchart TD
    A[Trainer] --> B(Power)
    A--> C(Angular Velocity)
    C --> D(Torque)
    B --> D
    C --> E(Angular Acceleration)
    D --> |fitlm| F(Linear Fit Params: MOI & Frictional Torque)
    E --> |fitlm| F

    G[Arduino] --> H(RPM)
    H --> |processing| I(Torque)
    F --> I
    I --> J(Power)
    H --> J

Loading

Figures

Average Power:

	Trial1	Trial2	Trial3
CG	159.7118	153.3534	174.1082
CJ	93.6738	64.7137	0
KB	174.0862	198.166	191.7826
MC	93.3015	83.7175	94.5097
MD	156.2198	110.1545	121.4405
NQ	103.6824	121.1665	111.4725

Peak Power:

	Trial1	Trial2	Trial3
CG	229.7978	280.6831	279.8394
CJ	339.9596	202.9147	0
KB	553.5193	541.1092	233.8113
MC	402.8491	255.8057	430.8718
MD	1136.1656	118.3475	260.4775
NQ	248.0476	315.1827	564.8355