Title :
A kriging assisted direct torque control of brushless DC motor for electric vehicles
Author :
Xiang Liu ; Chengbin Ma ; Mian Li ; Min Xu
Author_Institution :
Inst. of Automotive Eng., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Torque is one of the most important control factors for a vehicle´s motion. Compared with internal combustion engine, electric motors can have a more accurate torque feedback. It is possible for EVs that are driven by electric motors to have better vehicle dynamic control performance. In EVs, direct torque control of the permanent magnet synchronous motor has been studied. However, because of non-ideal back EMF, direct torque control of brushless DC motors, which is different from that of permanent magnet synchronous motors, has not been widely used up to now. In this paper, a new method using kriging to calculate back EMF in real-time is presented. Kriging prediction can approximate the response of unobserved points based on information from observed points. With motor speed and rotor position as inputs, kriging prediction calculates back EMF as an output. Motor torque is then calculated using back EMF and three phase currents. Using kriging, motor torque can be directly estimated and be used as a feedback to the motor´s controller. With this novel method, motor torque can be well controlled and the speed response is satisfactory.
Keywords :
brushless DC motors; electric potential; electric vehicles; machine control; position control; rotors; statistical analysis; torque control; velocity control; brushless DC motor; electric vehicles; internal combustion engine; kriging assisted direct torque control; motor speed; nonideal back EMF; permanent magnet synchronous motor; rotor position; Brushless DC motors; Permanent magnet motors; Synchronous motors; Torque; Torque control;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022349