Control Unit for Battery Charge Management in Electric Vehicles (EVs)

Round 1

Reviewer 1 Report

Dear authors,

Thank you, authors, for allowing me to read your manuscript.  I appreciate the effort you have put into this work.

This article describes the design of a control unit for efficient battery charge management in electric vehicles (EVs). The design objective of the system is to manage the charging performance of a pair of lithium-ion battery blocks in EVs, the main battery powering the vehicle and the auxiliary battery powering the ancillary equipment. In this paper, we design and analyse the controller protocol that controls and regulates the battery charging process in electric vehicles to achieve optimal performance. This proposed system improves the battery charging process and protects the main battery from capacity reduction, thus extending the range of the electric vehicle. We propose a specific protocol for an electrical circuit that reproduces the structure of the electric vehicle battery charging system.

The control system improves the charging efficiency of the auxiliary battery by 4.5%. The theoretical simulation matches the experimental values in the simulation test at 98.4%.

In the article, there is no detection of plagiarism. The topic of the article is topical. The article is well structured. The article has a decent level of English language.

I recommend the next editor for articles:

·         The article does not follow the MDPI template (indented text, headings, etc.)

·         In Fig. 7 has poor quality (the text is hard to read)

·         In the article, I miss some of the authors' innovation, motivation, and goals and why this particular publication/presented method/technology is better than another. I recommend adding to the introduction. Your work will then be better understood and highlighted for the reader.

·         Which software environment/language is used in Arduino? Add more information to the article.

Your work is solid; a minor revision could significantly contribute to our field. 

I look forward to seeing the revised manuscript.

Author Response

The article does not follow the MDPI template (indented text, headings, etc.)

R: We have adapted text to MDPI template

• In Fig. 7 has poor quality (the text is hard to read)

R: Text has been rewritten to make it legible

• In the article, I miss some of the authors' innovation, motivation, and goals and why this particular publication/presented method/technology is better than another. I recommend adding to the introduction. Your work will then be better understood and highlighted for the reader.

R: The following paragraphs have been added at the end of the Introduction

In this paper, we propose a new method to manage the charging process of a dual battery block for battery electric vehicles, which powers an electric vehicle and services the ancillary equipment. The charging process optimizes the energy transfer to the auxiliary battery while the vehicle runs, depending on driving conditions. To this goal, the charging control system equips a specific software that selects when the main battery charges the auxiliary one to avoid an excessive discharge rate while powering the vehicle.

This paper represents a contribution to the state of the art of dual battery electric vehicle power management since it develops a new method to optimize the management of the power source for vehicle powering and ancillary equipment service.

Previous works deal with power management in fuel cell hybrid electric vehicles, applying Model Predictive Control (MPC) and Deep Reinforcement Learning (DRL) [9-10]; this paper, however, deals with a dual lithium battery power system, which represents an innovative situation regarding the powering of EVs, because the traditional configuration uses a single battery for vehicle power and ancillary equipment service, or a lead-acid battery for this latter use. Power battery use as the power source for vehicle motion and auxiliary battery charging represents a novelty in the electric vehicle power system configuration. Besides, power management optimization also means an innovation in the state of the art.

• Which software environment/language is used in Arduino? Add more information to the article.

R: Arduino has its own programming language. This is known by people working with Arduino. On the other hand, in the first line after Experimental implementation subsection headline it is written We start the process using an Arduino code

Reviewer 2 Report

In this paper, a dual-battery pack charge management control system for electric vehicles (EVs) is designed, and the theoretical simulation of this control system is in high agreement with the experimental results, which verifies the effectiveness of the proposed scheme and helps to extend the range of EVs. However, the following problems must be solved before being accepted.

1. The introduction part needs to better clarify the background significance of the research, explain the advantages and innovations of the control system relative to the existing programmes, and the reference part should be supplemented with some relevant and up-to-date literature, reflecting the research frontiers. It is suggested to add relevant references for support:

[1] Jia C, He H, Zhou J, Li J, Wei Z, Li K. Learning-based model predictive energy management for fuel cell hybrid electric bus with health-aware control[J] . . Applied Energy, 2024;355:122228.

[2] Jia C, Zhou J, He H, Li J, Wei Z, Li K, et al. A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal and health-constrained awareness. energy. 2023;271:127105.

2. The derivation of some formulas in the theoretical foundations section needs to be explained in more detail in order to enhance readability.

3. There are some instances of redundancy or unrefined language throughout the text that need to be revised.

4. The structural arrangement of the thesis needs to be further optimised, the articulation between different parts is not compact enough and the overall coherence needs to be improved.

5. The results and discussion section needs to analyse the data more fully and explore possible sources of error and influencing factors.

6. The conclusion section could more clearly summarise the main innovations of the study, rather than just repeating the experimental results.

7. The simulation section lacks justification for the choice of parameters and needs to be supplemented with relevant justifications.

Medium level of English

Author Response

1. The introduction part needs to better clarify the background significance of the research, explain the advantages and innovations of the control system relative to the existing programmes, and the reference part should be supplemented with some relevant and up-to-date literature, reflecting the research frontiers. It is suggested to add relevant references for support:

[1] Jia C, He H, Zhou J, Li J, Wei Z, Li K. Learning-based model predictive energy management for fuel cell hybrid electric bus with health-aware control[J] . . Applied Energy, 2024;355:122228.

[2] Jia C, Zhou J, He H, Li J, Wei Z, Li K, et al. A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal and health-constrained awareness. energy. 2023;271:127105.

R: The following paragraphs have been added at the end of the Introduction

In this paper, we propose a new method to manage the charging process of a dual battery block for battery electric vehicles, which powers an electric vehicle and services the ancillary equipment. The charging process optimizes the energy transfer to the auxiliary battery while the vehicle runs, depending on driving conditions. To this goal, the charging control system equips a specific software that selects when the main battery charges the auxiliary one to avoid an excessive discharge rate while powering the vehicle.

This paper represents a contribution to the state of the art of dual battery electric vehicle power management since it develops a new method to optimize the management of the power source for vehicle powering and ancillary equipment service.

Previous works deal with power management in fuel cell hybrid electric vehicles, applying Model Predictive Control (MPC) and Deep Reinforcement Learning (DRL) [9-10]; this paper, however, deals with a dual lithium battery power system, which represents an innovative situation regarding the powering of EVs, because the traditional configuration uses a single battery for vehicle power and ancillary equipment service, or a lead-acid battery for this latter use. Power battery use as the power source for vehicle motion and auxiliary battery charging represents a novelty in the electric vehicle power system configuration. Besides, power management optimization also means an innovation in the state of the art.

Suggested references have been included and reference list renumbered.

2. The derivation of some formulas in the theoretical foundations section needs to be explained in more detail in order to enhance readability.

R: We have added some explanation to Equations 5 and 6, which in our opinion are the ones that need more detail. We hope to have fulfilled your requirement

3. There are some instances of redundancy or unrefined language throughout the text that need to be revised.

R: We have passed the manuscript to a professional English Editor, which has revised the text and made the corresponding amendments. These amendments have been incorporated to the new version of the manuscript

4. The structural arrangement of the thesis needs to be further optimised, the articulation between different parts is not compact enough and the overall coherence needs to be improved.

R: With due respect, we would like to know what is wrong with the article structure since other reviewers think the paper is well structured. Thank you in advance for your help

5. The results and discussion section needs to analyse the data more fully and explore possible sources of error and influencing factors.

R: We have added the following paragraphs at the end of the Results section, right before CONCLUSIONS

We observe a good matching between experimental data and simulation results in the evolution of the auxiliary battery voltage, with a slight gap at the acceleration and normal driving mode (constant speed). The gap does not represent a significant deviation in the battery voltage determination, around 0.8%, which we attribute to the uncertainties in determining the battery voltage by the measuring unit (1%). We check that the gap deviation is lower than the experimental band error, which justifies the existing gap.

The gap vanishment at the deceleration mode corresponds to a transition state where time at simulation and the experimental test is not evolving; thus, the values match. This situation is attributed to a mathematical singularity in the battery voltage determination during simulation since the voltage determination responds to a step function during the transition state. For the experimental tests, the voltage suffers a sudden increase for the near null transient time; therefore, the gap disappears. The reader can notice that for the non-transient state, the gap maintains the differential value observed for the acceleration and normal driving mode.

Regarding the main battery, the gap between experimental data and simulation results is identical, 0.8%, for the acceleration and normal driving mode. The same justification for the auxiliary battery voltage evolution applies.

We observe, however, that simulation results and experimental data show a diverging trend during the last normal driving and first deceleration period; we attribute this behavior to the recovery energy system, which operates with a time delay due to capacitive effects. On the other hand, the difference in battery voltage between simulation prediction and experimental results is of 0.9%, within the uncertainty band error.

6. The conclusion section could more clearly summarise the main innovations of the study, rather than just repeating the experimental results.

R: The two following paragraphs have been added at the CONCLUSIONS section

The paper is introducing a new type of lithium battery dual block that can power a vehicle and its ancillary equipment. The device is operated by a control system that is specifically designed to allow for independent operation of both the main power battery and the auxiliary one.

The proposed control system represents an innovation in the battery electric vehicle power management with a dual battery block, contributing to optimizing the performance of the power battery. As a result, the electric vehicle can increase the driving range because of a more effective use of the available energy.

We hope this addition fulfils your requirements.

7. The simulation section lacks justification for the choice of parameters and needs to be supplemented with relevant justifications.

R: We base the simulation study on theoretical analysis, where battery voltage evolution depends on the driving dynamic conditions, especially on the vehicle speed. Therefore, the vehicle speed is the key parameter for the simulation study.

Reviewer 3 Report

Use the acrnoym's full form before mentioning the acronym for the first time.

Please mention the type of EV. PHEV/HEV. BEVs don't usually use the power from Regenerative braking in the powertrain itself. It is unclear. 

Will a integral equation not be a better choice to calculate discharge current? Eq-21

Where is the said electric circuit built? In simulation or hardware? What is the simulation environment. details of the build are a must. line 346.

general justification in line 399 for picking this particular module is not enough. 

A physical picture could be included along with fig 11.

Again in line 485, unclear about the coding environment. 
Pay attention to grammar. 

OK

Author Response

Use the acrnoym's full form before mentioning the acronym for the first time.

R: We have detected the following undefined acronyms, which have been defined in the new version.

Internal combustion engine (ICE). 2^nd line, paragraph 6^th, Introduction section

If there is anything else we have omitted, please let us know. Thank you.

Please mention the type of EV. PHEV/HEV. BEVs don't usually use the power from Regenerative braking in the powertrain itself. It is unclear. 

R: We deal with battery electric vehicles (full electric). We have included a mention to this type in the Abstract and Introduction. On the other hand, BEVs use regenerative braking as stated in the following references among others:

[1] Xu, G., Li, W., Xu, K., & Song, Z. (2011). An intelligent regenerative braking strategy for electric vehicles. Energies, 4(9), 1461-1477.

[2] Guo, J., Wang, J., & Cao, B. (2009, June). Regenerative braking strategy for electric vehicles. In 2009 IEEE Intelligent Vehicles Symposium (pp. 864-868). IEEE.

Will an integral equation not be a better choice to calculate discharge current? Eq-21

R: The integral function is not necessary, a logarithm one gives enough accuracy

Where is the said electric circuit built? In simulation or hardware? What is the simulation environment. details of the build are a must. line 346.

R: The electric circuit is hardware. We built an experimental model to verify the simulation (see first paragraph of Materials section). All details are mentioned in the Materials section.

general justification in line 399 for picking this particular module is not enough.

R: Sorry, the version the editor sent to us don’t have line number; therefore, we cannot identify what you are mentioning. Could you please tell us the phrase or paragraph you are referring to?. Thank you.

A physical picture could be included along with fig 11.

R: We are sorry but the assembling is no longer available

Again in line 485, unclear about the coding environment. 

R: The coding environment reflects the battery charging process according to the built experimental electric circuit. If you need further explanation, please tell us what.

Pay attention to grammar.

R: We have passed the manuscript to a professional English Editor, which has revised the text and made the corresponding amendments. These amendments have been incorporated to the new version of the manuscript

Round 2

Reviewer 2 Report

The author has made sufficient revisions to the suggestions provided, demonstrating a correct scientific attitude. The revised article is logical and well-organized, and it is recommended to accept!

English proficiency above average