Optimisation of the FE Model Based on the No-Load Test Measurement for Estimating Electromagnetic Parameters of an Induction Motor Equivalent Circuit Including the Rotor Deep-Bar Effect
Round 1
Reviewer 1 Report
This paper proposes a new optimization approach for electromagnetic parameter identification for induction motors based on a FEM model that is optimized by means of no load test measurements. In the work, the rotor deep-bar effect is also taken into account. With the help of the optimized FEM-model, a load curve test can be applied in simulation, which allows to estimate the main machine parameters. This simplifies the identification procedure, since the application of the load curve test can cause difficulties in practical implementations. Experiments performed on an industrial induction machine prove the accuracy and simplicity of the discussed identification approach.
The authors provide a thorough state-of-the-art and motivate their work clearly. Theoretical background about the used machine model and identification approaches are shown in detail, which provides the necessary knowledge for the reader. The experimental set-up as well as the performed experiments are described thoroughly and validate the presented approach. Nevertheless, the paper needs to be improved significantly in terms of structure and English language, since it describes the work in a complicated and confusing way (see list of comments below). Moreover, more information about the optimization strategy and the genetic algorithm are required to provide a detailed understanding. The reviewer therefore suggests major revision, because after these issues have been addressed, the paper presents a valuable work and is worth to be published.
Comments:
line 133: In another paper ...
line 137 - 148: Please reformulate for better comprehension. It is useful to refer in this paragraph directly to the sections of the paper, e.g. "Section 2 shows the mathematical model of the induction motor that is used for parameter estimation".
line 167: Is it possible to show the air gap inductance L_{1, \delta} in the equivalent circuits for better comprehension?
line 172: Please give a reason or reference why this inductance cannot be evaluated by the inverse Laplace transform.
line 173: By putting (3) do you refer to equation 3 or reference 3? Please specify this.
line 180: Is it possible to show Z_2 in the equivalent circuits?
line 190: ... analytical procedure shown in Equation (3) and (4) ...
line 280 prosperties --> properties
line 308: Better write: ... within the relatively wide interval of [0.005 Nms/rad 0.025 Nms/rad] ...
line 343: interval [0.3 mm 0.6 mm]
line 347: Please check if the reference should link to Table 3 instead of Table 1.
section 5: This section is very long and contains a lot of content. It might be better to use sub-sections in order to structure the text more, e.g. into a subsection called "Optimization process of the FEM-model" and "Validation of the identified parameters". This might help the reader to separate the different experiments and will improve the comprehension a lot.
line 373: Is the reference to equation 6 correct?
Figure 4: When you refer to the motor inductance, do you mean L_1?
line 378 - 384: The identification of the torque-versus-slip characteristic fits better into chapter 2, where the identification of the inductance-frequency-characteristic was explained. It would be beneficial for the structure of the paper to put it into a new subsection with the number 2.3.
line 385: The optimization described here is based on a manual tuning process of the FEM model parameters. Is there a better way, e.g. rules, to tune these parameters automatically? Can you say 1-2 sentences about this in this section or in the conclusions/outlook?
line 433: Can you say more about the genetic algorithms that were used? What were the exact algorithms, used settings and the procedure?
Author Response
The authors really appreciate the Reviewer valuable comments and contribution in improving the revised paper. Thank you very much for your insightful review.
The corrections of the paper text were performed according to suggestions of the Reviewer. Therefore in this document, we do not refer to the Reviewer comments on the suggested corrections.
Please reformulate for better comprehension. It is useful to refer in this paragraph directly to the sections of the paper, e.g. "Section 2 shows the mathematical model of the induction motor that is used for parameter estimation".
The paragraph was reformulated. At first, the main contributions of the paper are listed in bullet point. Then the concisely descriptions of the individual paper sections and appendices are included.
Is it possible to show the air gap inductance L_{1, \delta} in the equivalent circuits for better comprehension?
Is it possible to show Z_2 in the equivalent circuits?
The Laplace-domain inductance L1δ(p) and the Laplace-domain rotor impedance Z2(p) are shown in the Induction Motor (IM) equivalent circuit presented in Figure 1b. Additionally the relationship between the Laplace-domain inductance and the magnetizing inductance Lμ = L1δ(p = 0) is included in the revised paper.
Please give a reason or reference why this inductance cannot be evaluated by the inverse Laplace transform.
Form the work of Paszek and Kaplon: “The operational inductance is a transcendent function of the differential operator p and a meromorphic function with an infinite number of negative, real zeroes pn but is not directly applicable for the calculation of the dynamic transients at variable rotational speed.”
The argumentation or adequate reference for the lack of possibility of the inverse transformation of a Laplace transform including the Laplace-domain inductance L1δ(p) should be placed undoubtedly in the paper. In the revised paper, the sentence:
“The inductance L1δ(p) is a certain type of the IM transfer function but cannot be directly used in the analysis of IM transients since the inverse transformation of a Laplace transform including this inductance is not possible.”
is replaced by the following sentence:
“The inductance L1δ(p) is a certain type of the IM transfer function but cannot be directly used in the analysis of IM transients [17].”
[17] Paszek, W.; Kaplon, A. Induction machine with anisotropic multilayer rotor modelling the electromagnetic and the electrodynamic states of a symmetrical machine with deep bar cage in solid iron rotor core. Electromagn. Fields Electr. Eng. 1988, 205–210.
This section is very long and contains a lot of content. It might be better to use sub-sections in order to structure the text more, e.g. into a subsection called "Optimization process of the FEM-model" and "Validation of the identified parameters". This might help the reader to separate the different experiments and will improve the comprehension a lot.
In the revised manuscript, Section 5 is composed of the two sub-sections: 5.1. Optimization process of the FE-model and 5.2. Validation of the electromagnetic parameter estimation for the IM space-vector model.
When you refer to the motor inductance, do you mean L_1?
The y-axis labels of the following figures 4, 5 and 6 were defined imprecisely. The figures 4, 5 and 6 present inductance frequency characteristics L1(ω2). The axis labels of this figures were modified.
The identification of the torque-versus-slip characteristic fits better into chapter 2, where the identification of the inductance-frequency-characteristic was explained. It would be beneficial for the structure of the paper to put it into a new subsection with the number 2.3.
The description of the torque-versus-slip frequency curve determination employing the measurement conducted under the Load Curve Test (LCT) is included in the sub-section 2.3 of the revised manuscript. The equation for electromagnetic torque and rotor flux calculations are formulated based on complex RMS values in the revised version of the paper.
The optimization described here is based on a manual tuning process of the FEM model parameters. Is there a better way, e.g. rules, to tune these parameters automatically? Can you say 1-2 sentences about this in this section or in the conclusions/outlook?
The sub-section 5.1 of the revised manuscript is complemented by the following information:
“The study results presented in Section 4 demonstrate the approximate linearity between the specified FE-model parameters and the x-axis or y-axis components of the SC space vector. For this reason, the results of the FE-analysis conducted for two different settings of the selected FE-model parameter enables estimating the variability of the x-axis or y-axis components of the SC space vector as a function of the studied parameter. This property can be conveniently used in determining the FE-model parameters which provide the requested conformity between the SC space vector components obtained from the measurement and the optimised FE-model”
We hope this information clearly describes the rule that can be used for determining the FE-model parameters under the optimisation process.
Can you say more about the genetic algorithms that were used? What were the exact algorithms, used settings and the procedure?
The genetic algorithm is briefly described in Appendix D of the revised manuscript. The information on the software, evaluation function, settings and genetic operators are included.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Please view the attachment
Comments for author File: Comments.pdf
Author Response
The authors really appreciate the Reviewer valuable comments and contribution in improving the revised paper. Thank you very much for your review.
First, the organization and follow of the introduction section could be improved. To be specific, clearly articulating the problem to solve, assumptions and main contributions in bullet point form would greatly help the readers. Moreover, adding another paragraph at the end of the introduction section to describe the section arrangement of the paper would also be helpful.
The paragraph was reformulated. According to your suggestions the research problem is articulated, the main contributions of the paper are listed in bullet point. Then the concisely descriptions of the individual paper sections and appendices are included.
Second, the modeling and characterization using lumped parameter models and conventional measurement techniques are presented with sufficient details. However, it seems that the modeling procedure in the ANSYS software has not been discussed with sufficient details. Showing some more details on mesh creation and modeling process will be helpful to improve the reproducibility of the analysis for interested readers in the future.
The revised manuscript is complemented by the two additional appendices. Appendix B briefly describes the modelling procedure of the tested induction motor with the use of ANSYS Maxwell software. The second Appendix which is added in the revised paper includes the information on the genetic algorithm concerning the software, evaluation function, settings and genetic operators.
Third, providing a step by step instruction list on how to use the proposed method to analyze other motors would be helpful. This would improve the scalability of the proposed method.
The manuscript presents the optimization technique for the Finite Element (FE) model of Induction Motors (IM). The optimized FE-model is intended for use in the estimation process of electromagnetic parameters for the IM equivalent circuit including the rotor deep-bar effect. As regards the considered phenomenon – the skin effect – the proposed technique for the FE-model optimisation should be valid for every IM, regardless of its rating power or voltage. However, the studies including experimental validations need to be done to confirm this.
At this stage of studies, the other types of motors, e.g. synchronous motors, have not been investigated. These types of motors can be subjected to the future studies.
Last but not least, there are some typos that need to be fixed. For example, the phrase “Load Curve Test” in line 15 is abbreviated as “LTC”, which should be “LCT”. The leading sentence of line 76 should also be corrected. It would be ideal to proof read the paper and fix the flow of certain sentences
We did our best to eliminate all the typos from the paper. The paper also went through linguistic corrections.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Dear authors,
Thank you for your thorough revision of the paper. The quality of the paper was increased significantly and the work is now worth to be published.
Best regards
Author Response
Dear Reviewer,
one more time thank you very much for your insightful review and contribution in improving the manuscript.
Best regards,
Authors
