TY - GEN
T1 - Model Predictive Torque Control of Switched Reluctance Motor Drive
AU - Bhavana, Gantasala
AU - Narasimharaju, B. L.
AU - Reddy, P. Vijaya Vardhan
AU - Babu, K. Vijay
N1 - Funding Information:
This research work is supported by IMPRINTIIC. 1 Science and Engineering Reseach Board (SERB) research funded project IMP/2019/000295, IMPRINT-India, Govt. of. India
Funding Information:
Acknowledgement: This research work is supported by IMPRINT-IIC.1 Science and Engineering Reseach Board (SERB) research funded project IMP/2019/000295, IMPRINT-India, Govt. of. India
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - A comparative study between conventional torque control methods and model predictive torque control (MPTC) of an 8/6 configuration switched reluctance motor (SRM) drive is presented in this paper. For extending the SRM application to higher speeds, the algorithm is designed by maintaining low torque ripple and considering the dynamic response of controller. The cost-function based online optimization of drives, replace non-linear controllers and heuristic switching table. The cost function is built with torque and stator current constraints. The principle of the predictive control method is explained, and the system mathematical description is derived. The results are verified for conventional control techniques and model predictive torque control applied to a 4kW switched reluctance motor under different operating conditions using MATLAB/Simulink. The obtained simulation results exhibit that the proposed model predictive torque control of an 8/6 SRM performance is satisfactory and can be used for electric vehicular applications.
AB - A comparative study between conventional torque control methods and model predictive torque control (MPTC) of an 8/6 configuration switched reluctance motor (SRM) drive is presented in this paper. For extending the SRM application to higher speeds, the algorithm is designed by maintaining low torque ripple and considering the dynamic response of controller. The cost-function based online optimization of drives, replace non-linear controllers and heuristic switching table. The cost function is built with torque and stator current constraints. The principle of the predictive control method is explained, and the system mathematical description is derived. The results are verified for conventional control techniques and model predictive torque control applied to a 4kW switched reluctance motor under different operating conditions using MATLAB/Simulink. The obtained simulation results exhibit that the proposed model predictive torque control of an 8/6 SRM performance is satisfactory and can be used for electric vehicular applications.
UR - https://www.scopus.com/pages/publications/85126644853
UR - https://www.scopus.com/pages/publications/85126644853#tab=citedBy
U2 - 10.1109/ICEPES52894.2021.9699742
DO - 10.1109/ICEPES52894.2021.9699742
M3 - Conference contribution
AN - SCOPUS:85126644853
T3 - 2021 IEEE 2nd International Conference on Electrical Power and Energy Systems, ICEPES 2021
BT - 2021 IEEE 2nd International Conference on Electrical Power and Energy Systems, ICEPES 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Electrical Power and Energy Systems, ICEPES 2021
Y2 - 10 December 2021 through 11 December 2021
ER -