The Vertical Force Estimation Algorithm Based on Smart Tire Technology
, Bo Li 1,2,*, Zhenqiang Quan 1, Shaoyi Bei 1,*, Guodong Yin 3, Jinfei Guo 1, Xinye Zhou 1 and Xiao Han 2
Round 1
Reviewer 1 Report
- The paper includes an interesting study on the shape and length of the contact patch and its relationship with vertical load, pressure, speed and wear. How ever, it is necessary to include and compare with other previous studies and it is important to clarify the experimental validation of the simulated results and how to include this development in a real intelligent tire.
Comments for author File: 
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Author Response
Author Response File: 
Author Response.docx
Reviewer 2 Report
The indication of the corresponding authors is seen to be incorrect. line 11
Well structured introduction. The initial perception may be that its too long.
line 7 p 7: Taking this as an example. It would have brought the writers choice of choosing these ranges of N and later speeds to better in context if the tire manufacturer specs were given to see at which percentage limits these tests were executed.
The font conversions for the formulas for example eq. 1 and 2 (p13) is not correct, and may be corrected throughout the paper.
p15 line 34 Just check the formula do not know if it was edited due to saving it to PDF.
A well written article.
Although the results were almost to what was expected it was good to see that the prediction models could be developed and evaluated.
Author Response
Author Response File: Author Response.docx
Reviewer 3 Report
I personally do not agree with the term 'intelligent' tire technology but I recommend 'smart', because intelligent means 'learning'.
The summary presents the main aspects of the article.
The introduction gives a brief overview of some articles in the field, with advantages and disadvantages.
The second section presents the schematic diagram of the tire model structure in Fig.1. But the finite element model is not convincingly presented. This presentation needs to be improved through both mathematical and graphical relationships. The same goes for model and sensor positioning material and for the \verification of the tire finite element model.
The paper must present the mathematical relations on the basis of which the simulation was made, otherwise the results have no value.
All the figs. from 7 to 22 must be described in detail.
The paper mixes the notion of neural network with that of genetic algorithms without making a detailed individual description of each, which makes the approach unclear.
The paper does not describe how to develop the neural network or how to apply the genetic algorithm. Without a clear description of them, the paper cannot be used by readers and has no use value.
In the end, it is not clear how the results in 5.4 are based on previous theory.
Detailed discussions of results and methods are needed.
Certain contributions claimed at the end of the paper are not demonstrated in the content of the paper, such as: software, validation, mathematical relations for the formal analysis, what resources were used.
Author Response
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The reviewed document has clearly been improved and contains an interesting and well structured study. From my point of view, it can be publish as it is.
Reviewer 3 Report
The authors responded satisfactorily to the comments.
