Proceedings of the 2nd International Conference on Electrical and Electronic Engineering (EEE 2019)

The Design of BP Neural Network Modeling for Switched Reluctance Motor

Authors
Dong-kai Qiao, Mei-qing Cai, Guo-le Li
Corresponding Author
Mei-qing Cai
Available Online July 2019.
DOI
https://doi.org/10.2991/eee-19.2019.28How to use a DOI?
Keywords
Switched reluctance motor, DSP TMS320LF2407, BP network, Flux linkage characteristic
Abstract
The model parameters of 8/6 poles switched reluctance motor (SRM) were determined through using the measured magnetization curve and the establish BP neural network model, selecting Sigmoid function as the hidden layer activation function and using gradient descent method to train the network. The simulated results show that the motor flux linkage model established has a good convergence rate, higher accuracy and generalization ability. It is significant to improve the reliable running and high precision speed control of SRM motor.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2nd International Conference on Electrical and Electronic Engineering (EEE 2019)
Part of series
Advances in Engineering Research
Publication Date
July 2019
ISBN
978-94-6252-754-6
ISSN
2352-5401
DOI
https://doi.org/10.2991/eee-19.2019.28How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Dong-kai Qiao
AU  - Mei-qing Cai
AU  - Guo-le Li
PY  - 2019/07
DA  - 2019/07
TI  - The Design of BP Neural Network Modeling for Switched Reluctance Motor
BT  - 2nd International Conference on Electrical and Electronic Engineering (EEE 2019)
PB  - Atlantis Press
SP  - 164
EP  - 168
SN  - 2352-5401
UR  - https://doi.org/10.2991/eee-19.2019.28
DO  - https://doi.org/10.2991/eee-19.2019.28
ID  - Qiao2019/07
ER  -