Self-tuning control of a switched-reluctance motor drive with shaft position sensor

Tandon, P.; Rajarathnam, A.V.; Ehsani, M.

doi:10.1109/28.605742

Cited by 36 publications

(9 citation statements)

References 6 publications

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“…Moreover, [5] also indicates that the copper loss varies significantly with different turn on and turn off angles while the iron loss doesn't change very much. [6] presents an online search method of turn off angles and current limit in order to achieve the best efficiency with off line turn-on angle . [7] demonstrates that by experiments the turn-on angle mainly determines the output power while the turn-off angle mainly determines the efficiency., Then an online control method is presented to adjust both the turn on angle and turn off angle.…”

Section: Introductionmentioning

confidence: 99%

Optimal calculation method for control of switched reluctance motor

Peng

Lin

et al. 2015

2015 IEEE Transportation Electrification Conference and Expo (ITEC)

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In this paper, the optimization problem for switched reluctance motor (SRM) is discussed and the convex optimization method is applied to calculate SRM control parameters instead of parameter sweeping. An optimal approach to calculate the maximum torque at each speed is presented. Also, a method to optimize control parameters is presented to minimize the copper loss for the given speed and torque. Simulation shows that the proposed optimal method is much faster than conventional parameter sweeping method with acceptable calculation errors.I.

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Section: Introductionmentioning

confidence: 99%

Optimal calculation method for control of switched reluctance motor

Peng

Lin

et al. 2015

2015 IEEE Transportation Electrification Conference and Expo (ITEC)

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“…At each time step, in compliance with a sensorless implementation, actual measurements of SRM electromechanical quantities are used to provide the input variables in, An and AB, while B and w are the outputs of the ANN. magnitude, the turn-on angle and the turn-off angle [22], [23]. In this paper, in order to compare simulation and experimental results, obtained by a drive with a fixed turn-off angle of about 1 4 5 O , the same option was adopted.…”

Section: Srm Dynamic Identification With Annmentioning

confidence: 99%

Position sensorless control of a SRM drive using ANN-techniques

Bellini

Filippetti²,

Franceschini³

et al.

Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242)

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Absfrucr-Nowadays speed-sensorless electromechanical drives are feasible for many applications. The elimination of the mechanical transducer increases reliability, reducing costs. As far as synchronous machine drives are concerned this issue is critical since the rotor position is fundamental to derive the proper switching sequence. If a SRM is used as actuator, different sensorless techniques have been proposed, essentially based on the rotor position detection by reluctance variation.Being the SRM a highly non-linear machine, it is an ideal candidate for the application of Artificial Neural Networks (ANNs).In this paper, a t first the results of a mixed closed loop scheme for the sensorless identification of a SRM drive are presented. A radial basis function ANN has been used, since it is well suited to simulate a non-linear system in a wide operating area. Then the proposed ANN is applied within a standard control scheme as a position sensor. Simulation results show the effectiveness of the proposed method, since a good agreement is reached with experimental results obtained from a SRM drive with a standard position sensor.

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“…This indicates that maximum productivity of the SRM does not necessitate storage of substantial magnetic energy in the core which contributes to a poor power quality. Therefore effectiveness of maximum torque per ampere control routines [8], [9] is also justified from this point of view. In order to understand the process of force generation in SRM study of the components of the flux density is crucial.…”

Section: Phase Excitationmentioning

confidence: 99%

Investigation of electromagnetic force components in SR machines: design and control issues

Edrington

Kaluvagunta

Joddar

et al.

38th IAS Annual Meeting on Conference Record of the Industry Applications Conference, 2003.

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this paper presents the results of an investigation on components of the electromagnetic force in the airgap of an 8/6 Switched Reluctance Machine (SRM). Using Maxwell stress method variations of radial and tangential force components with respect to saliency of the machine and saturation effects have been studied. Access to distribution of the force components acting on the rotor and stator enables us to provide a more accurate picture of the torque generation and vibration in this family of electric machines. Furthermore, distribution of magnetic forces under multiphase excitation has been studied in details. Our findings show that bipolar excitation of SRM phases, resulting in a short flux path magnetic circuit, favors its efficiency and power quality while generating slightly higher torque with less pulsation. This is a significant improvement especially for automotive current intensive applications where the difference in price of power electronics components can be justified. An experimental, 2kW, 42 Volts, 8/6 SRM drive which has been designed and manufactured in our energy system laboratory was targeted for this study. In addition to our extensive Finite Element(FE) analysis, experimental work is being carried out on our motor to validate some of the findings of this investigation. 0-7803-7883-0/03/$17.00

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Self-tuning control of a switched-reluctance motor drive with shaft position sensor

Cited by 36 publications

References 6 publications

Optimal calculation method for control of switched reluctance motor

Optimal calculation method for control of switched reluctance motor

Position sensorless control of a SRM drive using ANN-techniques

Investigation of electromagnetic force components in SR machines: design and control issues

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