Title :
Improving the Dynamic Stiffness in a Self-Sensing BLDC Machine Drive Using Estimated Load Torque Feedforward
Author :
Darba, Araz ; D´haese, Pieter ; De Belie, Frederik ; Melkebeek, Jan A.
Author_Institution :
Dept. of Electr. Energy Syst. & Autom., Ghent Univ., Ghent, Belgium
Abstract :
This paper presents a load torque estimation method for self-sensing brushless dc drives. Torque ripples in brushless dc machines can be reduced using load torque information. This method uses the terminal voltage, the virtual neutral point voltage, and the dc bus current of the machine. The algorithm uses the variation of successive back electromotive force (back EMF) samples to estimate the rotor speed. The rotor position is estimated by defining an intermediate function of estimated speed and back EMF samples. An estimate of acceleration is used to estimate load torque. The load torque information is used for increasing the dynamic stiffness of the drive. The mathematical background is given and discussed, and the simulations and the experimental results prove the performance of the proposed method.
Keywords :
DC machines; brushless machines; drives; electric potential; estimation theory; feedforward; rotors; virtualisation; DC bus current; back EMF; back electromotive force; brushless DC machines; load torque estimation method; load torque feedforward; load torque information; rotor position; rotor speed; self-sensing BLDC machine drive; self-sensing brushless DC drives; terminal voltage; torque ripples; virtual neutral point voltage; Commutation; Equations; Estimation; Load modeling; Mathematical model; Rotors; Torque; Back electromagnetic force (back EMF) zero crossing; estimation method; permanent-magnet brushless dc (BLDC) machine; self-sensing control;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2015.2399623