Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive
Abstract The development of a sensorless induction motor drive is elaborated in this paper with a unique feature of online estimation of equivalent circuit parameters (ECPs) during its running condition. The cases like temperature rise of the motor, change in drive speed due to sudden changes in its...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-10-01
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| Series: | Journal of Electrical Systems and Information Technology |
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| Online Access: | https://doi.org/10.1186/s43067-022-00060-3 |
| _version_ | 1798028543730384896 |
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| author | Tista Banerjee Jitendra Nath Bera |
| author_facet | Tista Banerjee Jitendra Nath Bera |
| author_sort | Tista Banerjee |
| collection | DOAJ |
| description | Abstract The development of a sensorless induction motor drive is elaborated in this paper with a unique feature of online estimation of equivalent circuit parameters (ECPs) during its running condition. The cases like temperature rise of the motor, change in drive speed due to sudden changes in its loading, or even in supply voltage are the sources of error in accurate ECPs evaluation. The indirect field-oriented control (IFOC) scheme is adopted in its controller to deal with these challenges. The drive controller is designed with a model reference adaptive system (MRAS) having two models—one is the plant model to estimate the ECPs during running conditions while the other one is the reference model. The H-G diagram method is utilized in the reference model to estimate the reference ECPs (ECPR) before starting without the need of performing any physical tests on the motor. During the transition period of the drive, the feedback signal is fed to the reference model to generate the ECPR. The technique of the backpropagation algorithm with an artificial neural network (BPANN) is utilized in the plant model while its weight and gain parameters are tuned with the reference ECPs. The Adam rule is utilized for fast convergence of the BPANN weights during the transition period while stator temperature and speed feedback enhance the overall accuracy in ECPs. A discrete-time low-frequency signal injection-based resistance assessment and sensorless speed estimation method to determine inductances are adopted for minimizing the ECPs errors. The results from MATLAB-based simulation and a hardware prototype using a DSPIC microcontroller with different running conditions show the efficacy of the proposed algorithm. |
| first_indexed | 2024-04-11T19:09:59Z |
| format | Article |
| id | doaj.art-9a8562b7602e407384785b0c4d2c67f8 |
| institution | Directory Open Access Journal |
| issn | 2314-7172 |
| language | English |
| last_indexed | 2024-04-11T19:09:59Z |
| publishDate | 2022-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Electrical Systems and Information Technology |
| spelling | doaj.art-9a8562b7602e407384785b0c4d2c67f82022-12-22T04:07:39ZengSpringerOpenJournal of Electrical Systems and Information Technology2314-71722022-10-019113010.1186/s43067-022-00060-3Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor driveTista Banerjee0Jitendra Nath Bera1Department of Applied Physics, University of CalcuttaDepartment of Applied Physics, University of CalcuttaAbstract The development of a sensorless induction motor drive is elaborated in this paper with a unique feature of online estimation of equivalent circuit parameters (ECPs) during its running condition. The cases like temperature rise of the motor, change in drive speed due to sudden changes in its loading, or even in supply voltage are the sources of error in accurate ECPs evaluation. The indirect field-oriented control (IFOC) scheme is adopted in its controller to deal with these challenges. The drive controller is designed with a model reference adaptive system (MRAS) having two models—one is the plant model to estimate the ECPs during running conditions while the other one is the reference model. The H-G diagram method is utilized in the reference model to estimate the reference ECPs (ECPR) before starting without the need of performing any physical tests on the motor. During the transition period of the drive, the feedback signal is fed to the reference model to generate the ECPR. The technique of the backpropagation algorithm with an artificial neural network (BPANN) is utilized in the plant model while its weight and gain parameters are tuned with the reference ECPs. The Adam rule is utilized for fast convergence of the BPANN weights during the transition period while stator temperature and speed feedback enhance the overall accuracy in ECPs. A discrete-time low-frequency signal injection-based resistance assessment and sensorless speed estimation method to determine inductances are adopted for minimizing the ECPs errors. The results from MATLAB-based simulation and a hardware prototype using a DSPIC microcontroller with different running conditions show the efficacy of the proposed algorithm.https://doi.org/10.1186/s43067-022-00060-3IFOCParameter estimationSpace vector modulationH-G diagramBPANNAdam |
| spellingShingle | Tista Banerjee Jitendra Nath Bera Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive Journal of Electrical Systems and Information Technology IFOC Parameter estimation Space vector modulation H-G diagram BPANN Adam |
| title | Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive |
| title_full | Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive |
| title_fullStr | Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive |
| title_full_unstemmed | Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive |
| title_short | Online equivalent parameter estimation using BPANN controller with low-frequency signal injection for a sensorless induction motor drive |
| title_sort | online equivalent parameter estimation using bpann controller with low frequency signal injection for a sensorless induction motor drive |
| topic | IFOC Parameter estimation Space vector modulation H-G diagram BPANN Adam |
| url | https://doi.org/10.1186/s43067-022-00060-3 |
| work_keys_str_mv | AT tistabanerjee onlineequivalentparameterestimationusingbpanncontrollerwithlowfrequencysignalinjectionforasensorlessinductionmotordrive AT jitendranathbera onlineequivalentparameterestimationusingbpanncontrollerwithlowfrequencysignalinjectionforasensorlessinductionmotordrive |