A Life Prediction Model of Flywheel Systems Using Stochastic Hybrid Automaton

Round 1

Reviewer 1 Report

it is necessary to add to the work a comparison with real experiments (if this is possible in this case).

You need to slightly modify 'Conclusion' and write more about the results.

Author Response

Reviewer 1

Comments and Suggestions for Authors:

1. it is necessary to add to the work a comparison with real experiments (if this is possible in this case).

Response:

Experiments are going to be conducted on our further work under the fund supports and help from labs of China Academy of Space Technology. We are scheduling to take advantage of the data acquired from the accelerated testing experiments and temperature cycling experiments on the stage of development, attempting to find out the information available for the prediction of useful life. It is a meaningful and significant work even though it will take long time and big cost to carry out the experiment and get the experiment data. We have just drafted the rough scheme and yet to have a test. We will verify and improve the supposed prediction model through the experiments.

2. You need to slightly modify 'Conclusion' and write more about the results.

Response:

Considering of reviewer’s comment, we have rewritten the conclusion, where more remarks are added on the main results.

Reviewer 2 Report

1.      The modern flywheel energy storage systems use active magnetic bearings to achieve ultra-high rotational speeds, since the storage energy depends on the square of the angular speed. These systems have a back-up safety system consistent with a ball or oil bearings in case of the power supply failure of active magnetic bearings.
Moreover, in the modern flywheels, the self-powered smart sensors provide on-line health monitoring of the flywheel and predicted algorithms allow to prevent failure in advance.
2.      The literature review is lack of flywheel systems review, where some examples with fault diagnostics/monitoring for advanced flywheel supported with magnetic bearings:
a.       Analytical method for design and thermal evaluation of a long-term flywheel energy storage system, By: Sokolov, Maksim A.; Jastrzebski, Rafal P.; Saarakkala, Seppo E.; et al., Conference: International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) Location: Capri, ITALY Date: JUN 22-24, 2016, 2016 INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS, ELECTRICAL DRIVES, AUTOMATION AND MOTION (SPEEDAM)  Pages: 270-275   Published: 2016.
b.      A Sensor-Fault Tolerant Control Method of Active Magnetic Bearing in Flywheel Energy Storage System, Yu, J., Zhu, C., 2016 IEEE Vehicle Power and Propulsion Conference, VPPC 2016 – Proceedings, 7791595
3.      Therefore, according to my first comment, how proposed work refer to the actual state of the art into this topic. Additional comments are welcome.
4.      How is the present paper different from these previous results? The contribution and motivation of the paper need to be clearly stated.
5.      The paper needs motivation (some gap in earlier designs or the assumptions that are not satisfied or something else). Needs to be clarified.
6.      Moreover, the systems models are derived under many assumptions that were made and they need justification.
7.      Abstract should overview obtained results and paper claims in a consistent way.
8.      Introduction. The literature overview of what is done in the manuscript does not look professional. Authors just say, paper by paper, what is done in every single manuscript (this is what students usually in their coursework do), the Authors should provide some expert view - analyse and compare the results in cited papers.
9.      The conclusion should be completely rewritten and supported by the data.
10.  Conclusions do not support any of the earlier claims.

Author Response

Reviewer 2

Comments and Suggestions for Authors:

The modern flywheel energy storage systems use active magnetic bearings to achieve ultra-high rotational speeds, since the storage energy depends on the square of the angular speed. These systems have a back-up safety system consistent with a ball or oil bearings in case of the power supply failure of active magnetic bearings.
Moreover, in the modern flywheels, the self-powered smart sensors provide on-line health monitoring of the flywheel and predicted algorithms allow to prevent failure in advance. 

and
2. The literature review is lack of flywheel systems review, where some examples with fault diagnostics/monitoring for advanced flywheel supported with magnetic bearings:
a. Analytical method for design and thermal evaluation of a long-term flywheel energy storage system, By: Sokolov, Maksim A.; Jastrzebski, Rafal P.; Saarakkala, Seppo E.; et al., Conference: International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) Location: Capri, ITALY Date: JUN 22-24, 2016, 2016 INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS, ELECTRICAL DRIVES, AUTOMATION AND MOTION (SPEEDAM) Pages: 270-275 Published: 2016.
b. A Sensor-Fault Tolerant Control Method of Active Magnetic Bearing in Flywheel Energy Storage System, Yu, J., Zhu, C., 2016 IEEE Vehicle Power and Propulsion Conference, VPPC 2016 – Proceedings, 7791595

 

Response :

Thanks for reviewer’s comment.

As suggested by the reviewer, we have investigated and cited a few more literatures with more discussions in the introduction (highlighted in the revised manuscript).

Just as the reviewer pointed out, there are modern flywheel systems using active magnetic bearings. They have safety and on-line health manager systems. Literature b. proposed a sensor-fault tolerant control method for the Active Magnetic Bearing. These modern flywheels will play an important role on future spacecraft.

Literature a. presents a analytical method of designing and evaluating the flywheel system from the thermal point of view. It gives recommendations to reach a point of better system utilization while maintaining its reliability and life expectancy on system design considerations.

While, to the best of the authors’ knowledge, traditional machinery flywheels are still served as one kind of the vital actuators allocated in the developing and arranged spacecrafts in two coming decade. Their reliability and lifetime play the decisive role for the Attitude Control Systems and still deserves further investigation. That is why this study focuses on the traditional machinery flywheels.

This paper focus on the model study of lifetime prediction of Flywheel Systems considering the following affecting aspects: running environments, configurations and work modes.

Therefore, according to my first comment, how proposed work refer to the actual state of the art into this topic. Additional comments are welcome.

and
4. How is the present paper different from these previous results? The contribution and motivation of the paper need to be clearly stated. 

and
5. The paper needs motivation (some gap in earlier designs or the assumptions that are not satisfied or something else). Needs to be clarified. 

and

Introduction. The literature overview of what is done in the manuscript does not look professional. Authors just say, paper by paper, what is done in every single manuscript (this is what students usually in their coursework do), the Authors should provide some expert view - analyse and compare the results in cited papers.

Response:

We reply to above several comments together. Existing works are of great help for learning the failure mechanism of a flywheel. While they mostly focus on the failure factor of either burst failure or accumulated performance degradation. Generally speaking, the lifetime of FS commonly ends in the above two forms. How to integrate the two failure forms and explore the interactions when executing the life prediction is a challenge.

Lifetime of FS is affected not only by the failure of a single flywheel but also by its configuration, running environment and work modes.

In case of the failure of one single flywheel, the allocation of FS changes and a discrete state transformation happens. At the same time, continuous state change occurs. For certain configuration with identical flywheels, the life of one single flywheel is varied from the other for its different workload. During long time running, accumulated stress will consequently have an impact on the performance of one single flywheel, which cannot be neglected. Besides, due to changed work modes and running environment, wear and tear will degrade the performance and hence result in the end of FS life.

In consideration of the above influence factors, we need to seek a method to build a prediction model and describe the dynamic relation of lifetime with influence factors. Therefore, we introduce the Stochastic Hybrid Automaton(SHA) method, which can describe all the above related factors as well as discrete state transformation and continuous state variation.

All the above have been added in the Introduction (highlighted in the revised manuscript).

 

Moreover, the systems models are derived under many assumptions that were made and they need justification.

Response:

The Monte Carlo simulations are carried out on following circumstance: running environment, different configurations and changed work modes. There are no specific assumptions.

Abstract should overview obtained results and paper claims in a consistent way.

Response:

Referred to the reviewer’s comment, we have rewritten the abstract where the obtained results are further emphasized and consistent with the claims in the paper (highlighted in the revised manuscript).

The conclusion should be completely rewritten and supported by the data. 

and
10. Conclusions do not support any of the earlier claims.

Response :

Considering of reviewer’s comment, we have rewritten the conclusion, where the main results and claims in the paper are summarized, and more remarks on the results are added.

Round 2

Reviewer 2 Report

Thank you for improving your paper.