Framework for the Sustainable Modeling of Electric Truck Fleet Usage

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript presents a generic simulation, TraPodSim for evaluating important parameters of a fleet of eTrucks, and other vehicles with different types of engines by considering the regional geography, transportation routes, technical specifications, etc. It considers 20 physical metrics for describing each vehicle's operation, enabling customers to evaluate fleet requirements as well as analyze the use of charging stations. The study has many emerging applications for better transportation modeling as a decision-making tool for companies in transforming their transportation businesses as per the new rules and requirements.

My comments are as below:

- A good literature study is undertaken, however, the research gap is to be included at the end of the State-of-the-art section. 

- Artificial intelligence, machine learning, fog, and edge computing are creating a big footprint in all fields including eMobility. It is recommended to add such relevant references and their descriptions, such as https://doi.org/10.3390/wevj15020039, https://doi.org/10.3390/en17051148.

- Are the charging stations considered private, public or owned by transporters? The pros and cons of these categories may influence in selection of charging stations. Please add a comment on that.

- Similarly, the condition/capacity of the road, etc also influences in selecting better routes.

- Choosing the stochastic approach, what kind of challenges might have to be faced? Please add.

- The novelty of the work missing and needs to be highlighted.

- Text in figures is not readable. Please update it. Similarly, the significance of different colors should be written somewhere.

- MDPI template format needs to be followed for the manuscript.

Comments on the Quality of English Language

Moderate edit required

Author Response

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding corrections highlighted in file.

Comment 1. - A good literature study is undertaken, however, the research gap is to be included at the end of the State-of-the-art section. Response. - We agreed with this comment. This recommendation is implemented by adding a new paragraph at the end of the State-of-the-art section (highlighted in red in file).

Comment 2.  Artificial intelligence, machine learning, fog, and edge computing are creating a big footprint in all fields including eMobility. It is recommended to add such relevant references and their descriptions, such as https://doi.org/10.3390/wevj15020039, https://doi.org/10.3390/en17051148. Response.  The first link refers to the article: Chougule, S.B.; Chaudhari, B.S.; Ghorpade, S.N.; Zennaro, M. Exploring Computing Paradigms for Electric Vehicles: From Cloud to Edge Intelligence, Challenges and Future Directions. World Electr. Veh. J. 2024, 15, 39. https://doi.org/10.3390/wevj15020039
The authors of this article consider the issues of applying new information technologies such as Edge Intelligence to control the movement of Electric Vehicles. Unfortunately, we do not see a direct connection between these problems and those discussed in our article. We are primarily interested in methods for assessing the physical performance of the Electric Vehicles fleet. We do not deal with the issues of applying information technologies.
The second link refers to the article: Madziel, M. Energy Modeling for Electric Vehicles Based on Real Driving Cycles: An Artificial Intelligence Approach for Microscale Analyses. Energies 2024, 17, 1148. https://doi.org/10.3390/en17051148
We are grateful to the reviewer for the reference to this article. We are interested in the issues of assessing the electricity consumption of Electric Vehicles. Although the proposed article studies the processes at the micro level, and the simulation model considers only one intersection, we have included a reference to this article in our work.

Comment 3. - Are the charging stations considered private, public or owned by transporters? The pros and cons of these categories may influence in selection of charging stations. Please add a comment on that. Response. As a commentary to Figure 1, five spatial arrangements of charging stations are described in detail, which can belong to all types of owners noted in the reviewer's question. The charging stations that can be used within the simulated scenario are assigned by the user of the model before its launch. When it is necessary to charge a car in the model, a specific charging station is selected only taking into account the remaining energy and the distance to it. This fact is now specifically noted in the article.

Comment 4. - Similarly, the condition/capacity of the road, etc also influences in selecting better routes. Response. The reviewer correctly notes that all these factors influence the selection of the best routes. Descriptions of planned routes are entered into the model in the form of Planned routes input data (see Figure 2). TraPodSim has a simplified Route Planning program (Yatskiv et al., 2022) that allows the user to define physically feasible routes for trips during the simulated day. It is assumed that one of the commercial packages will be used to select the optimal routes taking into account all the factors noted by the reviewer, the data from which will be fed into the TraPodSim system.

Comment 5. - Choosing the stochastic approach, what kind of challenges might have to be faced? Please add. Response. The authors have extensive experience in applying statistical methods in simulation and in other articles describe five groups of random factors that can influence the simulated processes of cargo transportation using Electric Vehicles. The authors do not see any fundamental problems in specifying distribution laws for some input parameters of the model. The main problems are related to the perception of the simulation results by the end users of the model who have no experience in applying statistical methods. It is easier for such users to explain the simulation results of a specific daily scenario than the meaning of a dozen empirical distributions presented using confidence intervals or histograms. The authors briefly reported on the features of applying the deterministic and stochastic approaches in the Conclusions of this article.

Comment 6. - The novelty of the work missing and needs to be highlighted. Response. The authors thank the reviewer and added text about novelty to the Introduction.

Comment 7. - Text in figures is not readable. Please update it. Similarly, the significance of different colors should be written somewhere. Response. The figures have been enlarged. A legend has been added to Figure 5 to indicate the colours.

 Comment 8. MDPI template format needs to be followed for the manuscript. Response, Everything was checked and adjusted.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1. the authors in the reviewed article used the newly developed TraPodSim computer system to compare electric and internal combustion powered delivery vehicles. They did this based on an analysis of actual van trip data. Based on the simulation results obtained using this system, they showed that the available evaluation indicators form a set of information to plan the transport strategy of a given transport company. However, they also pointed out that the practical use of TraPodSim requires long-term cooperation between the transport company and the software developer. This is a drawback. 

2.In my opinion, the authors have carefully traced and compared the literature on the issue. They have shown why it is important to plan transport and to compare vehicles powered by electric or combustion engines. According to the authors, this is since the charging infrastructure for delivery vehicles is not yet sufficient, which entails higher transport costs. 

3 Finally, they stand by their earlier opinion:

The conclusions developed are interesting above all for decision-makers of transport companies, as they indicate the possibility of solving practical problems related to the analysis of the feasibility of electric or combustion-powered trucks.  I therefore believe that the reviewed article should be published.

I have a minor comment on the readability of Figure 5: I would ask that it be made larger. It would then be easier to analyze.

 

Author Response

Thank you very much for review of manuscript. 

Comments 1. the authors in the reviewed article used the newly developed TraPodSim computer system to compare electric and internal combustion powered delivery vehicles. They did this based on an analysis of actual van trip data. Based on the simulation results obtained using this system, they showed that the available evaluation indicators form a set of information to plan the transport strategy of a given transport company. However, they also pointed out that the practical use of TraPodSim requires long-term cooperation between the transport company and the software developer. This is a drawback.

Response 1. The need for cooperation between the transport company and the software developer in this situation should be considered as a special type of limitation of the application of the TraPodSim system. This product is not offered to the client for independent use, but is a working tool with which a service of the Modeling and Simulation as a Service (MSaaS) type is performed (see section 6 of our article). The authors' experience shows that even with a good user interface, a transport company specialist who does not have special training in the field of simulation will not be able to develop and test a complex model.

Comments 2. Finally, they stand by their earlier opinion: The conclusions developed are interesting above all for decision-makers of transport companies, as they indicate the possibility of solving practical problems related to the analysis of the feasibility of electric or combustion-powered trucks.  I therefore believe that the reviewed article should be published. I have a minor comment on the readability of Figure 5: I would ask that it be made larger. It would then be easier to analyze.

Response 2. Figure 5 was re-created by the authors.

Reviewer 3 Report

Comments and Suggestions for Authors

This study presents an intriguing proposal for a novel eTruck fleet and validates its effectiveness using a simulation approach.

 

Section 3's description of the TradPodSim modeling system lacks clarity. I recommend enhancing this section with a detailed flowchart for better understanding. Additionally, could you clarify how truck charging times are incorporated into the simulation model?

 

The formatting of Figure 2 needs improvement to enhance visual clarity and information conveyance.

 

Figure 3 requires additional information to be comprehensible. It is currently challenging to decipher the content and implications of this figure.

 

Regarding the two cases presented, how do they represent varied real-world traffic conditions? It is crucial to demonstrate that the simulation approach can accurately replicate real traffic scenarios.

 

Are the input data mentioned in Section 4.1 gathered from actual field observations?

 

Some recent and relevant studies may be reviewed. For example, see: Multi‐Depot Pickup and Delivery Problem with Resource Sharing. Journal of Advanced Transportation, 2021(1), 5182989. 

Comments on the Quality of English Language

none

Author Response

Thank you very much for taking the time for review this manuscript. 

Comment 1. Section 3's description of the TradPodSim modeling system lacks clarity. I recommend enhancing this section with a detailed flowchart for better understanding. Additionally, could you clarify how truck charging times are incorporated into the simulation model?

Response 1. The TraPodSim system and its detailed block diagram are described in the paper (Yatskiv et al., 2022). The authors do not want to repeat the text from that paper in this paper. The total charging time for the entire working day is shown in the “Charging duration, h” column in Figure 3, as well as in all tables with the simulation results. Table 4 shows that 161 kWh/h is used as the “Charging speed, kWh/h”. In Case 1, the charging time for each cycle was 12.6 minutes (see section 4.1 of our paper). For Case 2, at the end of section 5.2 it is written: In the experiments with the model, when charging the battery in L/U points, the charge level was brought to 50%, and when charging at an external station – to 80%. The charging time was calculated by dividing the required amount of energy by the charging rate of 161 kWh/h.

Comment 2. The formatting of Figure 2 needs improvement to enhance visual clarity and information conveyance.

Response 2. The authors increased the size of Figure 2.

Comment 3. Figure 3 requires additional information to be comprehensible. It is currently challenging to decipher the content and implications of this figure.

Response 3. The authors have increased the size of Figure 3. The table accurately describes the indicators that are the standard results of modeling the operation of each eTruck during the day.

Comment 4. Regarding the two cases presented, how do they represent varied real-world traffic conditions? It is crucial to demonstrate that the simulation approach can accurately replicate real traffic scenarios.

Response 4. The main objective of the simulation in both Cases was to obtain and compare the main physical performance indicators of eTrucks and Diesels. The driving conditions are not of fundamental importance. The main requirement is that these conditions are the same for all groups of compared vehicles. In Case 1, the average speed of the vehicles on the approximately 14 km long section between two route points depended on the time of day in accordance with real statistics. In Case 2, the average speed of the vehicles did not change during the day, but all vehicles accurately reproduced the route shown in Fig. 7.

Comment 5. Are the input data mentioned in Section 4.1 gathered from actual field observations?

Response 5.  These data were prepared based on sources (eEconic, 2023) and (Actros-2543, 2023). The authors assume that the data in these sources were verified by the manufacturer of eTrucks through field observations.

Comment 6. Some recent and relevant studies may be reviewed. For example, see: Multi‐Depot Pickup and Delivery Problem with Resource Sharing. Journal of Advanced Transportation, 2021(1), 5182989. 

Response 6. Thank you very much for the article, the article is an example of applying a complex mathematical model to solve a specific logistics problem, but it is not related to the application of simulation to analyze the physical performance of a fleet of eTrucks. For this reason, it was not mentioned in the literature review shown in section 2 of our article.

 

Reviewer 4 Report

Comments and Suggestions for Authors

The study is devoted to solving a relevant problem – planning the movement of electric trucks. In the abstract, the authors provide the article essence; briefly describe the problem state, research methods, and results. The title of the article and keywords adequately reflect the article content.

In the introduction, the authors provide a rationale for the relevance of the topic in the context of solving the sustainability problem, as well as the simulation modelling method used for the study. The second section is devoted to an overview of studies by different authors devoted to similar topics. In the third section, the authors describe the TraPodSim modelling system, including its characteristics, purpose, and application concept. Sections 4 and 5 are devoted to the description and analysis of two cases: a shuttle transport model and a model of using electric and diesel trucks on a real road network. Section six contains prospects for creating a structure for sustainable modelling of the use of an electric truck fleet. In the final section, the authors summarize the results obtained.

The article has been prepared in accordance with the instructions for authors, corresponds to the topic it studies and publishes. Figures and tables that are of sufficient quality support theoretical and practical conclusions. The list of references reflects the article topic. In our opinion, the article corresponds to the topic of "improving the operation of an electric truck fleet" and corresponds to the Preliminary Study type.

Comment.

Despite the relevance and timeliness of the study, there are some comments:

1. In our opinion, insufficient scientific validity, for example, the authors should more clearly formulate the purpose and objectives of the study, indicate its structure and differences from the works carried out by other authors, and also confirm how the adequacy of the conclusions presented in the article can be assessed. In our opinion, the adequacy of the model in the article is not proven, since the results of its verification and validation are not provided.

2. Despite a detailed consideration of two model options, it is unclear why and how these options were chosen, and the choice of parameters for conducting a model experiment and assessing the efficiency of using the truck fleet is also unclear. It is necessary to provide the results of the experiment planning.

3. The authors provided only 30 literary sources, of which only an insignificant part are scientific articles written in the last 5 years, and the other part are either links to descriptions of electric truck models or to descriptions of modelling systems. This area of science is developing quite quickly, so it would be interesting to learn in more detail what studies in this area have been carried out in recent years.

Comments for author File: Comments.pdf

Author Response

Thank you very much for taking the time to review this manuscript. Please. find detail responses below.

Comments 1. In our opinion, insufficient scientific validity, for example, the authors should more clearly formulate the purpose and objectives of the study, indicate its structure and differences from the works carried out by other authors, and also confirm how the adequacy of the conclusions presented in the article can be assessed. In our opinion, the adequacy of the model in the article is not proven, since the results of its verification and validation are not provided.

Response 1. At the end of the Introduction, the authors added a text explaining the scientific novelty of the study, which consists in applying a mesoscopic approach to constructing and using models using the TraPodSim system. The obtained results are difficult to compare with the works of other authors, since each of the authors solves their own specific problems in the field of simulation modeling.
Both models presented in the work were subject to verification and validation. Section 4.1 mentions an analytical spreadsheet model, with the help of which the calculation results were obtained that almost perfectly coincide with the simulation results. The model was validated by demonstrating it to logistics specialists, who set the task of studying the options for organizing transportation between the logistics center and the VW plant. The second model was verified by analyzing the log files that are generated each time the model is run on AnyLogic. The model can be easily validated by observing the animation of the movement of vehicles against the background of the road network shown in Fig. 6. Also, the diagrams shown in Fig. 9 and 10, allow you to see the position of each vehicle at any time.

Comments 2. Despite a detailed consideration of two model options, it is unclear why and how these options were chosen, and the choice of parameters for conducting a model experiment and assessing the efficiency of using the truck fleet is also unclear. It is necessary to provide the results of the experiment planning.

Response 2. The main objective of the modeling in both examples was to obtain and compare the main physical performance indicators of eTrucks and Diesels. The driving conditions are not of fundamental importance. The main requirement is that these conditions are the same for all groups of compared vehicles. In Case 1, the model variants were clearly determined by the stated task of studying the options for organizing transportation between a logistics center and a VW plant. In Case 2, a transport network was selected that is typical for the use of eTrucks in medium-distance transportation. The scheme shown in Fig. 8 is the result of planning a series of experiments aimed at solving the stated task.

Comments 3. The authors provided only 30 literary sources, of which only an insignificant part are scientific articles written in the last 5 years, and the other part are either links to descriptions of electric truck models or to descriptions of modelling systems. This area of science is developing quite quickly, so it would be interesting to learn in more detail what studies in this area have been carried out in recent years.

Response 3. This work of the authors is not a review article. The list of references includes only those sources, the information from which was used as initial data or the content of which directly or indirectly influenced the choice of the method for solving the problem of assessing the physical indicators of the use of the fleet of eTrucks or Diesels, set in the study.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have reworked on the manuscript and addressed all my queries and comments. 

No further suggestions.

Reviewer 3 Report

Comments and Suggestions for Authors

The paper is well-revised.

Comments on the Quality of English Language

The paper writing is fine.