Intrinsic Characteristics of Forward Simulation Modeling Electric Vehicle for Energy Analysis
Round 1
Reviewer 1 Report
Objective: A detailed study of modeling and simulation of the EV is presented considering the forward method
Results: Table 3 compares autonomy with the simulation of a more accurate model from the Matlab/Simulink library and also with [14], a reference used for validation of the model.
Novelty is limited.
The main contributions are mentioned.
Recommendations:
1) The design of the parameters for the PID and LQR control for the considered process needs to be detailed.
Line 227: In non-dynamic models or resistive models, the simplest test performed on a battery is a constant current charge/discharge test, where cells are discharged and charged to and from 0% and 100% state of charge at a constant current, as shown in Fig. 9.
2) Mention that in reality a deep discharge is avoided (generally less than 20%).
Figure 10. Simplified battery module.
3) Mention the voltage source with v(t)
Line 237: Limit power p_max, this block prevents the power from exceeding the limits imposed and is calculated with Eq. (10).
4) Where is this block presented? The power of who?
Figure 17. State of charge at the end of the driving cycle (UDDS cycle).
5) Present SOC variation for proposed model, model from the Matlab/Simulink library and [14].
Line 392 : There is a greater difference is in the autonomy, the highest being the model developed in this study.
6) Present an explanation of the greater difference (about 4 times greater) in the autonomy obtained with the proposed model compared to the model from the Matlab / Simulink library and [14] (where the degree of autonomy is comparable).
Line 397: The study focuses on the development process of the vehicle model by the forward method, but not on developing a model that improves the consumption autonomy of the EV.
7) Reformulate; not the model, but the control for optimizing the operation of the EV can increase its performance. The model gives the estimation accuracy etc.
References
8) Avoid lumped references (see [3,9]); include a brief critical comment for each.
9) Revise the paper carefully
Ambiguous phrases; see for example:
Line 165: Nevertheless, the PID controller has a shorter response time, therefore, specifically for this study, a PID controller is used together with 2 saturations for the values in percentage of the accelerator and brake pedal, in the results section it is shown that the error between the target speed and the real speed is minimal if the gains of the PID controller.
Line 162: It is verified by developing the two types of controllers (Fig. 6), it is observed (Fig. 7) that
Line 237: Limit power p_max, this block prevents the power from exceeding the limits imposed and is calculated with Eq. (10).
Line 394: Nevertheless, considering environmental conditions (temperature, atmospheric pressure, etc.) and energy management, while in [14] an AUTONOMIE simulator is used, models developed with greater precision.
Ambiguous phrases due to editing errors; see for example:
Line 38: There are multiple models of EVs, some of them can be seen in [3-9] that, depending on the required detail of each component, the model can be stationary, quasi-stationary or dynamic => There are multiple models of EVs, some of them can be seen in [3-9], which, depending on the required detail of each component, can be stationary, quasi-stationary or dynamic [10].
Line 158: Other than the PID controller, there are others such as the pole location controller, linear quadratic regulator (LQR) and observer-based controller (OBC) all of which seek to adjust the throttle position with a uniform movement, maintain the desired speed vehicle. => In addition to the PID controller, there are others, such as the pole location controller, the square linear controller (LQR) and the observer-based controller (OBC), all of which seek to adjust the position of the damper with a uniform motion to maintain the desired speed of the vehicle.
See others in Conclusions.
Minor editing errors; see for example:
In figure 2: drivecycle => driving cycle;
Figure 5 shows a control diagram with a PID Controller.
Etc.
Author Response
Please see the attachment
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper is interesting and well-written. Authors provided detailed description of developed model and proved its validity.
There are, however, details worth addressing:
- Authors stated that presented method can more accurately estimate energy consumption of the EV (in conclusions) - does this statement refer to comparison to other described methods or suggests improvement of the forward method itself?
- Discrepancy in autonomy value is only mentioned, but not explained - are there multiple methods of calculating this value that could result in such difference?
- I would suggest language check - especially prepositions.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
The aim of the paper is to provide a detailed description about the forward modeling method. The emphasis is on the development process rather than creating a better models than the already existing ones. The created model is implemented in Matlab/Simulink and compared to two existing models.
However authors aim to give a clear and detailed description of the modelling methodology, the paper is not well written.
The style of the paper needs to be improved. Lots of sentences are long and contain grammatical errors (e.g. line 217-222, 278-280, 377-386, etc.). Sometimes words are missing or the sentence seems unfinished (e.g. page 5, line 168. "if the gains of the PID controller." -are what?) These mistakes makes it hard to understand what the authors want to express.
In Section 2, the results and conclusion sections do not need to be mentioned again at the end of the first paragraph. (line 87-88)
Some equations are poorly formatted, please use the "·" symbol in Eq. (13),(14),(15).
Eq. (4) - "Edisponible" is used instead of Eavaliable
Eq. (6) and (7) are the same. To make difference between the operating mode of the motor, use different variables (probably G is different?)
Eq. (9) - Tme is used instead of Tem, TLoss is not defined, FTF is the total force (FTf)?
Eq(15) - according to the text, this equation is the slope resistance (Frp), but it seems that it is the total resistance. The equation for Frp is missing.
Figure 10: Baterry -> Battery
Figure 11. Sprug Mass ->Sprung Mass
page 12, line 314: what is the difference between the two Ffrsuij variables?
Table 3 last column: kwh -> kWh
Questions:
- The battery is modeled by a simple resistive model. Is the voltage source representing the open circuit voltage constant? According to Figure 9, it depends on the SOC.
- In the conclusions the authors write that "The results of the forward method can more accurately estimate the energy consumption of the E". Is there any reference value (or real value) that the results can be compared to? How is the accuracy measured?
- What is the reason behind the greater difference between the autonomy of the different models? In the conclusion it is stated, that the developed model can better estimate the energy consumption than other more precise models. It seems a bit contradicting, as one can expect a precise model to perform better overall.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
The article presents a simulation of the components of an EV used to transfert the power from the battery to the EV speed in order to match a target speed profile. The use of the UDDS cycle for to model the driver behavior, as well as the use of the PID controller are well justified. A detailed explanation of the force transfer through mathematical formulas and graphs is given. The results and the simulation applied to a particular EV shows some outputs through time such as the EV SoC. Let me add a few suggestions. Figures 17 to 20 are not interpreted. A few words on the link between the parameters or some remarks could be a plus. Some fixed parameter values are not given, such as the coefficients used to by the PID controller of equation 1, or the efficiency map of the electric motor of equation 5. A few words could be added to explain the difference between the values obtained for the three models in Table 3. Also, from my point of view, the reasons of the high difference of values between the energy consumed and the autonomy is not clear. Some sentences are long and could be shortened into several ones such as « The simulation of the vehicle is avoided by the multibody modeling of each sub-model of the components (suspension, tire, frame), when performing this type of modeling it is emphasized to obtain results of the vehicle's own dynamics to optimize these mechanical components and analyze their behavior in different scenarios, although it could also be useful to develop the mutibody model to incorporate lateral displacements where, from the vehicle, output data would be obtained such as the movement of the steering system, traction, braking, position of the frame and not only the feedback of the speed of the EV as occurs in longitudinal dynamics. » (page 15) Please correct some typo: « in the results section it is shown that the error between the target speed and the real speed is minimal if the gains of the PID controller » (page 5); uniform E_available(eq. 3) and E_disponible (eq. 4) if they indeed have the same meaning (page 6); « depends of » (line 188); uniform T_emand (eq. 5, 6, 7) and T_me (eq. 9) if they indeed have the same meaning (page 7); uniform F_Tf (line 177) and F_TF (eq. 9) if they indeed have the same meaning; « Baterry » -> Battery in Figure 10; « There is a greater difference is in the autonomy » line 392.Author Response
Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors revised.
Reviewer 3 Report
The paper has been amended according to the review. The quality of the paper improved significantly. The paper can be accepted in present form.
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
The manuscript entitled “Intrinsic characteristics of forward simulation modeling electric vehicle for energy analysis” was submitted by Jurado and coauthors. They perform a simulation process of the electric vehicle by the "forward" method, highlighting their intrinsic characteristics through a theoretical study with a mathematical model, complemented with a simulation in MATLAB-Simulink. Please address the following comments.
According to my understanding, the introduction and abstract sections are too long. Even the introduction section is divided into three sub-sections. I will suggest revising it. Similarly, in the abstract, there is no need to mention the literature reviewer. It can be reduced.
Can the authors explain why they choose specific models mentioned in section 2.2.1?
Regarding controllers, please include this study to enhance the scope (A comparative study of controllers for optimal speed control of the hybrid electric vehicle, 10.1109/INTELSE.2016.7475142).
Please improve the quality of the figures. It is difficult to comprehend the axis. Especially, Figures #1, 10. Similarly, please correct typos and mistakes throughout the manuscript. E.g., units in the figure 3 legends, inconsistency in using units ‘seconds’ and ‘s’, Table 2, etc.,
Reviewer 2 Report
Recommendations
1) Present the novelty and the main contributions at the end of the introduction (in a clear and punctual manner, using a bulleted list).
The authors states that, ‘’In summary, the objective is to estimate the energy consumption of the EV 237 throughout a driving cycle but not to estimate the aging of each battery cell or the degradation of the performance of the system over time. Thus, it is more feasible to use the equivalent electrical model for battery.’’
On the other hand, the objective of the proposed forward method is to accurately estimate the autonomy of an electric vehicle whose energy source is a battery pack.
So, the model used for the battery influences the estimation accuracy.
2) Include autonomy estimation data using a simplified model (like the one used) and a more accurate model (for example, the one included in Matlab). Mention the obtained results in a Table. Discuss and compare them in the discussion section.
The energy analysis of EV is presented, but an estimate of the autonomy of an electric vehicle using the proposed method is not detailed and discussed in the paper, except for some comments in the conclusions section: ‘’One of the aims of this study is to validate the simulation of the EV developed by the forward method, therefore, only the benefits of the Ford Focus vehicle and values considered by the authors are considered. The simulation is validated based on [6], where the autonomy simulation tool and the test results of the Argonne Research Center are used to simulate and validate the Ford Focus electric vehicle model under different driving cycles (UDDS, HWFET, US06) estimating based on the results of energy consumption a discrepancy of 0.5 – 4%.’’
3) Include a discussion section where you can compare the results obtained in this paper and [6] on energy consumption and the autonomy of an electric vehicle.
4) The conclusions section is not an abstract; present in a clear and punctual manner (using a bulleted list) the main findings (qualitative and quantitative assessments of the results presented).
Minor editing errors and ambiguous phrases; see for example
Line 417: where the autonomie simulation tool
Etc.
Line 105 : To fill the gaps in the available literature, this study highlights all these intrinsic characteristics and even a model is developed and the load state is estimated at the end of the cycle, where the model is able to use any driving cycle to develop each component more complex integrating the simulation chain.
Line 109 : This way, a theoretical study of the mathematical model of each of the components involved is carried out, such as driving cycle, driver model, power train and multibody vehicle model, being able to develop complex electric vehicle architectures from this information. not only focusing on the development of power train elements but also incorporating real driving cycles taken through a GPS and importing them into the simulation for a more accurate and real energy analysis, estimating autonomy and energy consumption of the elements at each moment electric vehicle auxiliaries.
Line 342 : Through the simulation carried out in Matlab considering in more detail all the parameters and forces that act on the EV, various results can be obtained to estimate the energy of the vehicle at the end of the imposed driving cycle, it is observed in Fig.13 as the profile of the electric vehicle is almost exactly equal to the input speed profile (UDDS) through the driver model, the PID controller converts the error into signals for the accelerator and brake pedal that its representation is observed in detail throughout the driving cycle as seen in Fig. 14.
Etc.
5) Revise the paper carefully using short and clear sentences.
12 references from the last 3 years are included (but none from 2021).
6) Include several references from the last 3 years to highlight the timeliness of the study.
