The paper presents an automatic parameter identification procedure for linear permanent magnet synchronous motors. The electrical parameters of a test machine are estimated by identification tests performed through the inverter. The method employs the available feedback signals that are needed by the control. The stator resistance and machine inductances are estimated through signal injection at standstill. The permanent magnets' flux-linkage identification instead requires carriage movement. Subsequently, the inverter nonlinearity characteristics are identified, again at standstill, through a flux-observer. The proposed self-commissioning process requires only the nameplate data of the machine and no datasheet information of the power electronic devices is needed. The developed techniques can be used both with and without a position sensor. The complete process is automatic and safe to run on its own and requires least intervention from the operator. © 2018 IEEE.

Identification of Linear Permanent Magnet Synchronous Motor Parameters and Inverter Non-Linearity Effects

Zanchetta P.
;
2018-01-01

Abstract

The paper presents an automatic parameter identification procedure for linear permanent magnet synchronous motors. The electrical parameters of a test machine are estimated by identification tests performed through the inverter. The method employs the available feedback signals that are needed by the control. The stator resistance and machine inductances are estimated through signal injection at standstill. The permanent magnets' flux-linkage identification instead requires carriage movement. Subsequently, the inverter nonlinearity characteristics are identified, again at standstill, through a flux-observer. The proposed self-commissioning process requires only the nameplate data of the machine and no datasheet information of the power electronic devices is needed. The developed techniques can be used both with and without a position sensor. The complete process is automatic and safe to run on its own and requires least intervention from the operator. © 2018 IEEE.
2018
9781538649411
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1372880
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