Online Voltage and Degradation Value Prediction of Lead Acid Battery Using Gaussian Process Regression

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors used IoT as a voltage monitoring system for lead-acid batteries. A predictive model using Gaussian Process Regression (GPR) was applied. There are many questions to be addressed before the level of the paper can be further assessed.

1. The labeling of references in the text is very confusing, starting with [24]. Some expressions, for example, in pages 3-5, “The research conducted by [reference]” are not appropriate.

2. Figure 7-9 are not clear, which may be exported by the screenshot method.

3. The authors should explain how the model correlates with the decay of lead-acid batteries.

4. Lead-acid batteries can usually be deeply charged and discharged for 400 cycles, with a stable lifespan of 2 years. How can 5 hours monitoring data work to predict the battery performance with only voltage and temperature sensors?

Comments on the Quality of English Language

 Extensive editing of English language required.

Author Response

Dear Reviewer, 

Thank you for your insightful comments and suggestions. We really appreciate it. 

Here we submit our response to answer your comments. 

Please kindly check it.

Best regards,

Nico Surantha

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors,

the topic is interesting. However, please specify and review to improve the manuscript:

- It is necessary to broader overview of the topic and also analyze more related references to the topic (state of the art). So that, provide key contribution of the research in comparison with previous publications.

- The presentation of the manuscript is not good. Figures all are not proper located.

- Section III. Results and discussion. Please hightlight the contributing results to support the research questions and comparison with other methods.

 

Author Response

Dear Reviewer, 

Thank you for your insightful comments and suggestions. We really appreciate it. 

Here we submit our response to answer your comments. 

Please kindly check it.

Best regards,

Nico Surantha

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study investigates how IoT and machine learning methods can be utilized to enhance the maintenance and cost-efficiency of lead acid batteries by enabling real-time monitoring and predictive capabilities. The topic is both pertinent and carries substantial importance within the context of battery-related concerns. However, there is a need for improvement and further development.

1 1)      The article is poorly written, with significant repetition of sentences and even entire paragraphs.

2 2)      I appreciated the "related work" section, but it lacks a connection to the presented work by clarifying your contribution.

3 3)      There is no interpretation provided for figures 3 through 9.

4 4)      It's essential to verify the time axis for figures 4, 5, and 6.

5 5)      Also, please further improve the presentation of figures.

6 6)      The conclusion is overly lengthy.

7 7)      Since the paper is an applied research paper, I recommend presenting the "Materials and Methods" section with specific details about the case study, including the considered data points (N observations), features (D features), and the input matrix X.

8 8)      You mentioned that "In this case study, P.T. XYZ has not fully leveraged the potential of IoT technology for monitoring and Machine Learning for predicting future voltage and degradation values." Please clarify what you mean by "fully leveraged the potential of IoT."

9 9)      If the company has its own approach, I recommend comparing the two approaches to demonstrate the effectiveness of IoT utilization in this application.

Author Response

Dear Reviewer, 

Thank you for your insightful comments and suggestions. We really appreciate it. 

Here we submit our response to answer your comments. 

Please kindly check it.

Best regards,

Nico Surantha

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have addressed the comments in the revised version.

Comments on the Quality of English Language

Minor editing of English language required.

Reviewer 2 Report

Comments and Suggestions for Authors

It is accepted with this revised version