What Is Sensorless Brushless Motor Control?

Sensorless brushless motor control eliminates the need for physical speed or position sensors in electric motors by using algorithms that analyze voltage and current feedback to estimate rotor position and speed. Sensorless brushless motor control enhances cost-effectiveness and reliability, especially in harsh environments, making it useful in electric vehicles, drones, industrial automation, consumer electronics, and other sectors.

Field-oriented control (FOC), a widely utilized approach in motor control systems, is known for its precise torque and speed regulation. Sensorless FOC, therefore, combines the precise control of FOC with the practical advantages of sensorless observers. The block diagram below shows an example of sensorless FOC architecture that includes the inner current control, outer speed control, coordinate transformations, and space vector generator, as well as a sensorless observer to estimate rotor speed and position.

Understanding sensorless brushless motor control is essential for harnessing its capabilities in cost-sensitive applications. Developing and fine-tuning these algorithms is a complex process, and accurate modeling and simulation are needed to ensure effective implementation. Through detailed simulations, engineers can address the challenges of sensorless control, ensuring optimized motor performance and efficiency for their motor control applications.

To minimize development time, Simulink^® offers prebuilt blocks and reference examples designed for implementing sensorless brushless motor control; depending on their application, engineers can choose from these options:

• The flux observer (FO) uses the motor’s magnetic flux characteristics to estimate the rotor position, providing a method that is inherently synchronized with the motor’s physical properties and thus offers precise control. Its performance is closely tied to the accuracy of motor parameters, highlighting the importance of accurate motor modeling.
• The sliding mode observer (SMO) excels in environments with high levels of noise, offering robust estimations of the rotor’s position by dynamically adjusting its operation to maintain performance across different conditions. While its tuning process is intricate and time consuming, the precision it offers makes this extra attention to detail worthwhile for sensorless brushless motor control systems.
• The extended EMF (EEMF) observer enhances back-EMF estimation techniques, offering improved performance in medium- to high-speed applications for both types of PMSM: surface-mount (SPMSM) and interior permanent magnet (IPMSM). Due to their saliency, IPMSMs’ position information depends not only on EMF but also on stator inductance. By including both EMF and saliency, EEMF accurately captures rotor position and speed, making it suitable for sensorless brushless motor control systems, applicable to both SPMSM and IPMSM.
• For initial position estimation and low speeds, where back-EMF is nearly zero, the pulsating high-frequency observer (PHFO) ensures accurate estimations for IPMSM by leveraging the motor’s saliency. It achieves this through high-frequency signal injection, a highly effective yet complex technique.

Simulink provides reference examples that demonstrate the use and integration of the blocks, streamlining the modeling and simulation process for building motor control algorithms. For further information on motor control solutions using MATLAB^® and Simulink, see Motor Control Blockset™ and Simscape Electrical™.