Estimation of Angular Velocity for Brushless DC Motors Using Particle Filter Considering Misalignment of Hall Sensors and Rotor Magnetic Poles

The angular velocities of brushless DC (BLDC) motors are estimated based on hall sensor signals. However, the estimation performance deteriorates owing to the misalignment of the Hall sensors and the magnetic poles of the rotors. To improve estimation performance, the proposed method designed a particle filter. For this design, this study analyzed the probability distribution of angular velocity observed using Hall sensors. Considering the influence of the misalignment, the probability distribution is expressed using a probability density function with a variable of motor’s angular velocity. The proposed method considers the probability density function on a design of likelihood in particle filter algorithm. Numerical simulations confirmed that the proposed method reduced errors by approximately 80% compared with a particle filter that does not consider misalignment.