TY - GEN
T1 - Surrogate-Based Optimization of Firing Angles for Switched Reluctance Motor
AU - Anvari, Bahareh
AU - Kaya, Mine
AU - Englebretson, Steven
AU - Hajimirza, Shima
AU - Toliyat, Hamid A.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/28
Y1 - 2018/8/28
N2 - In this work, optimal firing angles of Switched Reluctance Motors (SRMs) are explored by surrogatebased optimization in order to minimize the torque ripple. Surrogate-based optimization is facilitated via Neural Networks (NNs) which are regression tools capable of learning complex multi-variate functions. Flux and torque calculations of a nonlinear 16/20 SRM are evaluated with a NN, and consequently the computation time is expedited by replacing the look-up tables of flux and torque with the surrogate NN model. An optimization algorithm is proposed to discover optimal firing angle objects to minimize the 16/20 SRM torque ripple for a certain electrical load requirement. The resulting optimal firing angles are also represented by simple NN models to expedite online control. Comprehensive simulation and experimental results are provided to validate the theoretical findings.
AB - In this work, optimal firing angles of Switched Reluctance Motors (SRMs) are explored by surrogatebased optimization in order to minimize the torque ripple. Surrogate-based optimization is facilitated via Neural Networks (NNs) which are regression tools capable of learning complex multi-variate functions. Flux and torque calculations of a nonlinear 16/20 SRM are evaluated with a NN, and consequently the computation time is expedited by replacing the look-up tables of flux and torque with the surrogate NN model. An optimization algorithm is proposed to discover optimal firing angle objects to minimize the 16/20 SRM torque ripple for a certain electrical load requirement. The resulting optimal firing angles are also represented by simple NN models to expedite online control. Comprehensive simulation and experimental results are provided to validate the theoretical findings.
UR - http://www.scopus.com/inward/record.url?scp=85053856048&partnerID=8YFLogxK
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U2 - 10.1109/ITEC.2018.8450092
DO - 10.1109/ITEC.2018.8450092
M3 - Conference contribution
AN - SCOPUS:85053856048
SN - 9781538630488
T3 - 2018 IEEE Transportation and Electrification Conference and Expo, ITEC 2018
SP - 359
EP - 365
BT - 2018 IEEE Transportation and Electrification Conference and Expo, ITEC 2018
T2 - 2018 IEEE Transportation and Electrification Conference and Expo, ITEC 2018
Y2 - 13 June 2018 through 15 June 2018
ER -