Algebraic Speed Estimation for Sensorless Induction Motor Control: Insights from an Electric Vehicle Drive Cycle

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Authors present algebraic estimator of the speed of IM for EV application. The idea of algebraic estimator is novel, but the presentation of the functionality has some gaps. The results are compared to conventional MRAS sensorless controller on  UDDS speed command that is used as an EPA-standard procedure for vehicle testing, which is OK, but details of estimator performance during transitions are missing. This will be in my opinion main drawback of the method in case of high performace drive control

I have several comments/questions to the authors:

1) The fact that you are targeting EV shouold be mentiond in paper titel

2) Instead of inclueding well known equation of vehicle (chapter 3) I would recomend to show more figures proving stability and robustnes of the speed estimator

3) I am missing some sensitivity analysis of proposed estimator to IM parameter deviation such as Rr, Lm, Uuvw

4) The reseting algorithm should be explained in more detail. Sensitivity of proposed estimator to DC offset on current resp. voltage is missing in the paper

5)There is LC filter connected between IM and VSI in Fig. 9. Which I suppose is filtering voltage for measurement, however there are no such filters in real drive. Can you explain how will the estimator work under pulse width modulated voltage or how does it deal with inverter nonlinearities

6) Some speed detail during speed transition should be added 

7( Can you compare proposed estimator with MRAS estimator from the point of view of computational burden?

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Article review: Algebraic Speed Estimation for Sensorless Induction Motor Control Minor and controversial comments: 1. Chapters cannot begin with diagrams, formulas and results (chapter 2), it is not very elegant - please correct it. 2. The diagrams are ambiguous - in Fig. 1 you use alpha/beta in the transformation and at the output of these blocks small a and b (these are phase signals a, b, c sometimes A, B, C) - please standardize in the article and mark the stationary system as alpha/beta, not ab. 3. The same applies to the formulas and the rest of the article (Greek alpha and Beta, not ab) 4 the marking M is incomprehensible - in the literature, inductance is marked as LM, not M... please correct or provide the source of such marking of the motor parameters (if there are LR and LS, it should be Lm) 5. chapter 2.1.4 and 3 starts with a diagram 6. no punctuation after patterns Note on the results 7. The waveforms of the measured and estimated speed during t = 600 seconds are shown. It is impossible to assess the quality of the estimation in the low speed range and in the field weakening range. It is necessary to add additional analyzes and results for ultra-low speeds, medium and high speeds over short time intervals with variable load torque. This is how sensorless drives are evaluated. 8. The MRAS estimator in Fig. 9 is called MRAS CC (see cited literature) 9 please compare MRAS CC with your solution but within 1-3 seconds for different speeds. Interesting article, but requires additions. Congratulations!

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The article titled "Algebraic Speed Estimation for Sensorless Induction Motor Control" proposes a novel algebraic estimation strategy to accurately estimate rotor speed in sensorless induction motor (IM) control systems. The authors address the challenges associated with sensorless rotor speed estimation, such as filtering distortions, tuning complexities, and sensitivity to IM model mismatch. They introduce an algebraic estimator with single-parameter tuning and inherent filtering capabilities, aiming to simplify the control system while maintaining accuracy and reliability.

Summary of the Article:

The article begins by highlighting the significance of sensorless control strategies in mission-critical applications like electric vehicles (EVs). It reviews existing techniques and their limitations, emphasizing the need for improved methods. The authors then introduce the algebraic methodology, drawing from previous works, to develop a robust and efficient estimator for sensorless IM control. They present a detailed description of the proposed strategy, including its theoretical foundations, practical implementation considerations, and experimental validation.

Key Contributions:

Development of Algebraic Estimation Strategy: The article proposes an algebraic estimator tailored for sensorless IM control, combining concepts from previous research with new innovations. The estimator offers single-parameter tuning, inherent filtering, and adaptability to practical implementation requirements.

Experimental Validation: The authors conduct experiments using a laboratory setup to emulate a small-scale EV powertrain. They evaluate the performance of the algebraic estimator under realistic conditions, demonstrating its effectiveness in achieving accurate rotor speed estimation.

Comparison and Analysis: The article compares the proposed algebraic strategy with existing sensorless techniques, particularly focusing on its advantages in simplicity, robustness, and performance. The authors provide insights into the strengths and limitations of their approach, paving the way for further research and development.

Conclusion:

"Algebraic Speed Estimation for Sensorless Induction Motor Control" offers a promising solution to the challenges of sensorless IM control. The algebraic estimator, with its simplicity and effectiveness, holds potential for practical applications in various industries, including electric vehicles and renewable energy systems. The article contributes valuable insights and methodologies to the field of motor control, stimulating further exploration and innovation in this area. In my opinion, the reviewed manuscript is ready for publication.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thanks for your work. You have dealt with my comments. The proposed speed estimator results are clearly presented and the results are well discussed.

Reviewer 2 Report

Comments and Suggestions for Authors

my comments were taken into account.