Winding Resistance Estimation Research Articles

Sensorless DTC of BDFRG using LMS algorithm for wind energy conversion systems

This paper presents a new sensorless speed and secondary winding resistance estimation technique for brushless doubly fed reluctance generator (BDFRG) using least mean square (LMS) algorithm. Detailed mathematical derivation of the algorithm is explained and simulation results in MATLAB Simulink are shown for sensorless direct torque control (DTC) of BDFRG using LMS algorithm. A comparison to traditional speed estimation technique for BDFRG using primary winding flux linkage formula in stationary frame is then held to show the advantages of this proposed technique over the traditional method of speed estimation. Power electronics of the drive system is also simulated to consider effect of harmonics injected by electronic switches on both algorithms.

Sensorless DTC of BDFRG using LMS algorithm for wind energy conversion systems

This paper presents a new sensorless speed and secondary winding resistance estimation technique for brushless doubly fed reluctance generator (BDFRG) using least mean square (LMS) algorithm. Detailed mathematical derivation of the algorithm is explained and simulation results in MATLAB Simulink are shown for sensorless direct torque control (DTC) of BDFRG using LMS algorithm. A comparison to traditional speed estimation technique for BDFRG using primary winding flux linkage formula in stationary frame is then held to show the advantages of this proposed technique over the traditional method of speed estimation. Power electronics of the drive system is also simulated to consider effect of harmonics injected by electronic switches on both algorithms.

A Novel Current Injection-Based Online Parameter Estimation Method for PMSMs Considering Magnetic Saturation

This paper studies the online parameter estimation of permanent magnet synchronous motor (PMSM) with the consideration of magnetic saturation and proposes a novel current injection method to estimate parameters, including winding resistances, dq-axis inductances, and rotor flux. During the current injection, the inductances will vary due to magnetic saturation, neglecting which will cause great estimation error especially in the inductance estimation. This paper proposes to use simplified equations to model the self- and cross-saturation effects during the current injection. By incorporating this saturation model into the PMSM steady-state equations, the varying dq-axis inductances due to magnetic saturation as well as the rotor flux can be accurately estimated. In addition, the estimation of winding resistance is independent of other parameters and does not get affected by the magnetic saturation. The proposed approach is validated through both the numerical and experimental studies on a laboratory interior PMSM.

Influence of Nonideal Voltage Measurement on Parameter Estimation in Permanent-Magnet Synchronous Machines

This paper investigates the influence of nonideal voltage measurements on the parameter estimation of permanent-magnet synchronous machines (PMSMs). The influence of nonideal voltage measurements, such as the dc bus voltage drop, zero shift in the amplifier, and voltage source inverter nonlinearities, on the estimation of different machine parameters is investigated by theoretical and experimental analysis. For analysis, a model-reference-adaptive-system-based estimator is first described for the parameter estimation of the q-axis inductance, stator winding resistance, and rotor flux linkage. The estimator is then applied to a prototype surface-mounted PMSM to investigate the influence of nonideal voltage measurement on the estimation of various machine parameter values. It shows that, at low speed, the inverter nonlinearity compensation has significant influence on both the rotor flux linkage and winding resistance estimations while, at high speed, it has significant influence only on the winding resistance estimation and has negligible influence on the rotor flux linkage estimation. In addition, the inverter nonlinearity compensation will not influence the q-axis inductance estimation when it is under id = 0 control. However, the dc bus voltage drop due to the load variation and zero shift in the amplifier will significantly influence the q-axis inductance estimation.

A Novel Flux Linkage Measurement Method for Linear Switched Reluctance Motors

The magnetic characteristics of a linear switched reluctance motor (LSRM) are important in its performance prediction and verification. Owing to the complicated magnetic paths, the measurement of the flux linkage for this type motor has drawn many researchers' attentions. In this paper, a new flux linkage measurement method for LSRMs is proposed to obtain the flux linkage characteristics of LSRMs using an online winding resistance estimation technique. Both the theoretical derivation and the actual implementation of the proposed method are addressed in this paper. In comparison with the search coil scheme and the static resistor scheme, experimental results confirm the validity and accuracy of this method. In short, the proposed method is simple, effective, and easy to be implemented. It is a practical solution for flux linkage measurement of LSRMs and other motors.

A Remote and Sensorless Stator Winding Resistance Estimation Method for Thermal Protection of Soft-Starter-Connected Induction Machines

This paper proposes a remote and sensorless stator winding resistance estimation method for thermal protection of soft-starter-connected induction motors. By changing the gate drive signals of the thyristors in the soft starter, a small adjustable dc bias can be intermittently injected to the motor for the estimation of the stator winding resistance. Based on online and continuous monitoring of the stator winding resistance, the stator winding temperature can be monitored using only motor voltage and current. In addition, the torque pulsation caused by the injected dc bias is analyzed. It can also be controlled under an acceptable level by adjusting the level of the injected dc signal. The influence of cable resistance is also studied, and a compensation method is proposed. The proposed method has been verified by experimental results from two induction motors. The proposed stator resistance estimation method can provide remote, sensorless, and accurate thermal protection for soft-starter-connected induction motors.

DSP-Based Automated Error-Reducing Flux-Linkage-Measurement Method for Switched Reluctance Motors

The switched reluctance motor (SRM) has received considerable attention from researchers for its many inherent advantages, and thus, it has become a popular research topic in the field of variable-speed drives as well as servo drives. Research on SRMs mainly includes their design, modeling and performance analysis, control, as well as applications. However, for verification of design, performance prediction, as well as development of a high-performance sensorless control algorithm, accurate measurement of the magnetic characteristics of the SRM is most critical. Hence, one of the most important problems in the field of SRMs is a practical and accurate instrumentation system for the measurement of the SRM magnetic characteristics. This paper first describes an accurate and fully automated digital method for the measurement of the magnetic characteristic of SRMs, which includes online offset-error removal and winding resistance estimation. In this method, a digital-signal-processor-based virtual instrumentation for measurement of flux linkage is developed. Then, the results of the measurement conducted on a four-phase SRM are presented. The accuracy of the measurement system is verified by comparing with that found via a magnetic analyzer. Finally, the various sources of errors and their contributions to the errors are discussed. The scheme can also be used, in general, for transformers or inductors.

An online stator winding resistance estimation technique for temperature monitoring of line-connected induction machines

A new technique for stator resistance (R/sub s/)-based thermal monitoring of small line-connected induction machines is proposed in this paper. A simple device is developed for injecting a small DC signal into line-connected induction machines for estimation of R/sub s/. The proposed DC injection device is capable of intermittently injecting a controllable DC bias into the motor with very low power dissipation. Experimental results under motor startup, load variation, and abnormal cooling conditions verify that the proposed technique provides an accurate estimate of R/sub s/ that is capable of responding to the changes in the motor thermal characteristics, resulting in reliable thermal protection. The proposed technique is a very practical method for thermal protection of small line-connected induction machines that can be implemented with low cost in a motor condition monitoring system.

Flux linkage measurement method for switched reluctance motors and inductor/transformers using a real-time DSP system

The switched reluctance motor (SRM) has received considerable attention from researchers for its many inherent advantages, and thus has become a popular research topic in the field of variable-speed drives as well as servo drives. The research on SRMs mainly includes its design, modelling and performance analysis, control, as well as applications. However, for verification of design, performance prediction and development of a high-performance sensorless control algorithm, accurate measurement of the magnetic characteristics of the SRM is most critical. Hence, one of the most important problems in the field of SRMs is a practical and accurate instrumentation system for the measurement of the SRM magnetic characteristics. This paper first describes an accurate, fully automated digital method for the measurement of the magnetic characteristics of SRMs, including on-line offset error removal and winding resistance estimation. In this method, a digital signal processor-based virtual instrumentation for measurement of flux linkage is developed. Then the results of measurement conducted on a four-phase SRM are presented. The accuracy of the measurement system is verified by comparing it with that found via a magnetics analyzer. Finally, the various sources of errors are discussed and their contributions to the errors are quantified. The scheme can also be used in general for transformers or inductors