BLDC Motor configuration

All BLDC motors are handled with the BLDCMotor class. This class implements:

• BLDC FOC algorithm
• Motion control loops
• Monitoring
• User communication interface

Step 1. Creating the instance of the BLDC motor

To instantiate the BLDC motor we need to create an instance of the BLDCMotor class and provide it the number of pole pairs of the motor.

//  BLDCMotor(int pp, (optional R))
//  - pp  - pole pair number
//  - R   - phase resistance value - optional
BLDCMotor motor = BLDCMotor(11 , 10.5);

Pole pair number

If you are not sure what your pole_paris number is. The library provides an example code to estimate your pole_paris number in the examples find_pole_pairs_number.ino.

Phase resisatnce

If you know in advance your motor's phase resistance value R, we suggest you to provide it to the library. The library will then calculate the voltage values internally and the user will be dealing only with currents. But this is an optional feature.

Step 2. Linking the sensor

Once when you have the motor defined and the sensor initialized you need to link the motor and the sensor by executing:

// link the sensor to the motor
motor.linkSensor(&sensor);

Method linkSensor is able to link the motor to any sensor implemented in this library. The sensor will be used to determine electrical position of the motor for the FOC algorithm as well as for the motion control loops of velocity and position. See the position sensor docs for more info!

Linking is not necessary when using the openloop motion control.

Step 3. Linking the driver

Once when you have the motor defined and the driver initialized you need to link the motor and the driver by executing:

// link the driver to the motor
motor.linkDriver(&driver);

The BLDCMotor class expect to receive a BLDCDriver class instance, implemented by default with classes BLDCDriver3PWM and BLDCDriver6PWM. The driver deals with all the hardware specific operations related to specific microcontroller architecture and driver hardware. See the bldc driver docs for more info!

Step 4. Linking the current sense

If you have a current sensor current_sense you can link it to the motor using:

// link the current sensor to the motor
motor.linkCurrentSense(&current_sense);

This linking step is only necessary if you have a current sense supported by this library. See the current sense docs for more info!

Step 5. Configuration paramters

If you choose not to set some of the configuration parameters they will take values defined in the defaults.h file. Check the library source code to dig deeper.

Step 5.1 PWM Modulation type

There are four types of Field Oriented Control modulation types implemented for BLDC motors:

• Sinusoidal PWM modulation
• Space Vector PWM modulation
• Block commutation - beneficial for current control applications
  • Trapesoidal 120
  • Trapesoidal 150

You can set them by changing the motor.foc_modulation variable:

// choose FOC modulation
// FOCModulationType::SinePWM; (default)
// FOCModulationType::SpaceVectorPWM;
// FOCModulationType::Trapezoid_120;
// FOCModulationType::Trapezoid_150;
motor.foc_modulation = FOCModulationType::SpaceVectorPWM;

Sinusoidal PWM and Space vector commutation patters will produce sinusoidal currents and smooth operation but block commutation will be faster to execute, therefore more suitable for higher velocities. It is suggested to use the Trapesoidal 120 commutation with Hall sensors. Other commutation patterns will work as well but this one will have the best performance.

FOC currents torque control requirements

FOC torque control requires sinusoidal currents therefore please use either Sinusoidal PWM or Space vector PWM

For more information about the theory of these approaches please and source code implementation check the FOC implementation docs or visit the digging deeper section.

Step 5.2 Sensor and motor aligning parameters

The voltage used for the motor and sensor alignment set the variable motor.voltage_sensor_align:

// aligning voltage [V]
motor.voltage_sensor_align = 3; // default 3V

If your sensor is an encoder and if it has an index pin, you can set the index search velocity value by set the variable motor.velocity_index_search:

// incremental encoder index search velocity [rad/s]
motor.velocity_index_search = 3; // default 1 rad/s

Step 5.3 Position sensor offset

For some applications it is convenient to specify the sensor absolute zero offset, you can define it by changing the parameter motor.sensor_offset:

// sensor offset [rad]
motor.sensor_offset = 0; // default 0 rad

This parameter can be changed in real-time.

Step 5.3 Motor phase resistance

Motor phase resistance is an optional parameter which is not very important for current based torque modes, but if the voltage mode is used and if user specifies the motor.phase_resistance (either in constructor or in the setup() function) the library will allow user to work with current value and it will calculate the necessary voltages automatically. In the setup function you can change this parameter by setting:

// motor phase resistance [Ohms]
motor.phase_resistance = 2.54; // Ohms - default not set

Working with currents instead of voltages is better in may ways, since the torque of the BLDC motor is proportional to the current and not voltages and especially since the same voltage value will produce very different currents for different motors (due to the different phase resistance). Once when the phase resistance is provided the user will be able to set current limit for its BLDC motor instead of voltage limit which is much easier to understand.

It is important to say that once you specify the phase resistance value, you will most probably have to retune the velocity motion control and angle motion control parameters, due to the reason that the voltages and currents values are in different orders of magnitude. The rule of thumb is to divide all the P, I and D gains with the motor.phase_resistance value. That will be a good staring point.

Finally, this parameter is suggested to be used if one whats to switch in real time in between voltage (voltage mode) and current based (DC current and FOC current) torque control strategies. Since in this way all the torque control loops will have current as input (target value) the user will not have to change the motion control parameters (PID values).

Phase resistance can be changed in real-time if needed.

Step 5.4 Torque control mode

There are 3 different torque control modes implemented in the Arduino SimpleFOClibrary:

• Voltage mode
• DC current
• FOC current

DC current and FOC current require current sensing and are controlling current and limiting the real current the motor is drawing, whereas voltage mode approximates the motor current and does not use any current sensing. Read more in torque control docs.

The torque mode can be set by changing the motor attribute torque_controller.

// set torque mode to be used
// TorqueControlType::voltage    ( default )
// TorqueControlType::dc_current
// TorqueControlType::foc_current
motor.torque_controller = TorqueControlType::foc_current;

Step 5.5 Motion control parameters

There are 3 different closed loop control strategies implemented in the Arduino SimpleFOClibrary:

• Torque control loop
• Velocity motion control
• Position/angle motion control

Additionally SimpleFOClibrary implements two open loop control strategies as well:

• Velocity open-loop control
• Position open-loop control

You set it by changing the motor.controller variable.

// set motion control loop to be used
// MotionControlType::torque      - torque control 
// MotionControlType::velocity    - velocity motion control
// MotionControlType::angle       - position/angle motion control
// MotionControlType::velocity_openloop    - velocity open-loop control
// MotionControlType::angle_openloop       - position open-loop control
motor.controller = MotionControlType::angle;

Important!

This parameter doesn't have a default value and it has to be set before real-time execution starts.

Each motion control strategy has its own parameters and you can find more about them on motion control docs.

Here is the list of all the motion control configuration parameters:

// set control loop type to be used
motor.controller = MotionControlType::angle;

// controller configuration based on the control type 
motor.PID_velocity.P = 0.2;
motor.PID_velocity.I = 20;
motor.PID_velocity.D = 0.001;
// jerk control it is in Volts/s or Amps/s
// for most of applications no change is needed 
motor.PID_velocity.output_ramp = 1e6;

// velocity low pass filtering time constant
motor.LPF_velocity.Tf = 0.01;

// angle loop controller
motor.P_angle.P = 20;
motor.P_angle.I = 0; // usually set to 0  - P controller is enough
motor.P_angle.D = 0; // usually set to 0  - P controller is enough
// acceleration limit
motor.P_angle.output_ramp = 1e6;

// motion control limits
// angle loop velocity limit
motor.velocity_limit = 50;
// either voltage limit
motor.voltage_limit = 12; // Volts -  default driver.voltage_limit
// or current limit - if phase_resistance set
motor.current_limit = 12; // Amps -  default 0.5 Amps

Step 5.6 Configuration done - motor.init()

Finally the configuration is terminated by running init() function which prepares all the hardware and software motor components using the configured values.

// initialize motor
motor.init();

Step 6. Align motor and all the sensors - Field Oriented Control init

After the position sensor, current sense, driver and the motor are configured, and before we can start the motion control we need to align all hardware components in order to initialize the FOC algorithm. This is done in the scope of the funciton motor.initFOC()

// align sensor and start FOC
motor.initFOC();

Can be skipped for openloop control!

If no sensor is attached this function will not really do anything, but you can still call it if necessary or more convenient.

This function does several things:

• Checks/modifies position sensor direction in respect to the motor’s direction
• Searches for encoder index if necessary
• Finds the motor electrical offset in respect to the position sensor
• Checks/modifies current sense pinout and gains signs if one available to make sure it aligned with the driver

This function is a final check function and it will disable your motor and display you a message what is wrong. (when using the monitoring ). If everything is well configured, after the call of this function FOC is ready and our setup is done!

The alignment procedure will have to move your motor several times and might not be desirable behavior, therefore for most of the position sensors (except encodes) and current senses, this alignment procedure can be skipped by following the steps 6.1 an 6.2.

Step 6.1 Skip alignment - position sensor

If you are using absolute sensors such as magnetic sensors or hall sensors, once you have done the alignment procedure and once you have the motor’s zero electrical offset sensor direction you no longer need the full calibration sequence. Therefore, to the motor.initFOC() you can provide the sensor offset zero_electric_offset and sensor direction sensor_direction to avoid alignment procedure:

// align sensor and start FOC
//motor.initFOC(zero_electric_offset, sensor_direction);
motor.initFOC(2.15, Direction::CW);

The same can be done by using the motor parameters:

// align sensor and start FOC
motor.zero_electric_offset  = 2.15; // rad
motor.sensor_direction = Direction::CW; // CW or CCW
motor.initFOC();

You can find these values by running the find_sensor_offset_and_direction.ino example.

More generally, if you know any of these two values make sure to provide and the iniFOC will skip that part of the calibration. For example, for encoder sensors the zero electrical offset changes all the time but the sensor direction will stay the same so you can provide it and skip a large part of the calibration sequence.

Step 6.2 Skip alignment - current sense

For the current sensors it is as well possible to avoid the calibration procedure an that is done by specifying the curren sense flag called skip_align:

current_sense.skip_align  = true; // default false

But make sure that all of your gains are well set and all of your ADC pins are aligned to the driver/motor phases. For more information about the alignment please visit the current sense docs.

Step 7. Real-time motion control

The real-time motion control of theArduino SimpleFOClibrary is realized with two functions:

• motor.loopFOC() - low level torque control
• motor.move(float target) - high level motion control

The function loopFOC() behavior directly depends of the torque control mode usd. If used in volatge mode it gets the current motor angle from the sensor, turns it into the electrical angle and transforms the q-axis U_q voltage command motor.voltage_q to the appropriate phase voltages u_a, u_b and u_c which are set then set to the motor. Whereas if it is used in DC of FOC current modes it additionally reads the current sensor and runs the closed loop current control.

// Function running the low level torque control loop
// it calculates the gets motor angle and sets the appropriate voltages 
// to the phase pwm signals
// - the faster you can run it the better Arduino UNO ~1ms, Bluepill ~ 100us
motor.loopFOC();

Can be skipped for openloop control!

This function will have no effect if the motor is run in open loop!

This function is execution time is critical both in the voltage mode and in current control modes. Therefore it is very important that the motor.loopFOC() function is executed as fast as possible.

Rule od thumb: execution time

The faster you can run this function the better, here is approximative loops execution time using different torque modes.

MCU	Voltage mode	DC current	FOC current
Arduino UNO	~ 700 us	~ 1.2 ms	~ 1.5 ms
Esp32	~ 100 us	~ 200 us	~ 300 us
Bluepill	~ 200 us	~ 500 ms	~ 700 us
Nucleo	~ 100 us	~ 150 us	~ 200 us

Finally, once we have a way to set the torque command (current i_q or voltage u_q) to the motor using the FOC algorithm we can proceed to the motion control. And this is done with motor.move() function.

// Function executing the motion control loops configured by the motor.controller parameter of the motor. 
// - This function doesn't need to be run upon each loop execution - depends of the use case
//
// target  Either torque, angle or velocity based on the motor.controller
//         If it is not set the motor will use the target set in its variable motor.target
motor.move(target);

The move() method executes the motion control loops of the algorithm. If is governed by the motor.controller variable. It executes either pure torque loop, velocity loop or angle loop.

It receives one parameter float target which is current user defined target value.

• If the user runs velocity loop or velocity open-loop, move function will interpret target as the target velocity.
• If the user runs angle loop or angle open-loop, move will interpret target parameter as the target angle.
• If the user runs the torque loop, move function will interpret the target parameter as either voltage u_q or current i_q (if phase resistance provided).

The target parameter is optional and if it is not set, the target value will be set by the public motor variable motor.target. The equivalent code would be:

motor.target = 2;
motor.move();

Step 7.1 Motion control downsampling

For many motion control applications it will make sense run multiple torque control loops for each motion control loop. This can have a great impact on the smoothness and can provide better high-speed performance. Therefore this library enables a very simple downsampling strategy for the move() function which is set using the parameter motor.motion_downsample:

// downsampling value
motor.motion_downsample = 5; // - times (default 0 - disabled)

The downsampling strategy works in a very simple way, even though the motor.move() is called in each arduino loop it will only be executed each motor.motion_downsample calls. This parameter si optional and can be configured in real time.

BEWARE: Motion control impact

Different values of the downsampling might require a bit of tuning of motion parameters.

And that is it, you have your complete Field Oriented Controlled BLDC motor with motion control.

User interaction

SimpleFOClibrary implements two types of real-time user interaction:

• Monitoring functionality
• Motor commands

Digging deeper

For more theoretical explanations and source code implementations of the FOC algorithm and the motion control approaches check out the digging deeper section.

Example code

A simple BLDC motor torque control using voltage based on the FOC algorithm.

/**
 * Torque control example using voltage control loop.
 */
#include <SimpleFOC.h>

// BLDC motor instance
BLDCMotor motor = BLDCMotor(11);
// driver instance
BLDCDriver3PWM driver = BLDCDriver3PWM(9, 5, 6, 8);
// sensor instance
MagneticSensorI2C sensor = MagneticSensorI2C(AS5600_I2C);

void setup() { 
  
  // initialize encoder sensor hardware
  sensor.init();
  // link the motor to the sensor
  motor.linkSensor(&sensor);

  // driver config
  // power supply voltage [V]
  driver.voltage_power_supply = 12;
  driver.init();
  // link driver
  motor.linkDriver(&driver);

  // aligning voltage
  motor.voltage_sensor_align = 3;
  
  // choose FOC modulation
  motor.foc_modulation = FOCModulationType::SpaceVectorPWM;

  // set torque mode
  motor.torque_controller = TorqueControlType::voltage;
  // set motion control loop to be used
  motor.controller = MotionControlType::torque;

  // initialize motor
  motor.init();
  // align sensor and start FOC
  motor.initFOC();

  _delay(1000);
}

// target voltage to be set to the motor
float target_voltage = 2;

void loop() {

  // main FOC algorithm function
  motor.loopFOC();

  // Motion control function
  motor.move(target_voltage);
}