Investigation of the Wheel Power and State of Charge of Plug-In Hybrid Electric Vehicles (PHEVs) on a Chassis Dynamometer in Various Driving Test Cycles

Response to Reviewer 1 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Questions for General Evaluation

Reviewer’s Evaluation

Response and Revisions

Does the introduction provide sufficient background and include all relevant references?

Yes

We already revised please see an attached file.

Are all the cited references relevant to the research?

Yes

We already revised please see an attached file.

Is the research design appropriate?

Yes

We already revised please see an attached file.

Are the methods adequately described?

Yes

We already revised please see an attached file.

Are the results clearly presented?

Yes

We already revised please see an attached file.

Are the conclusions supported by the results?

Yes

We already revised please see an attached file.

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: The objectives of the experiment were vague, no testable scientific hypotheses (e.g. quantitative relationship between SOC consumption and driving cycles) were presented, and only ‘analytical performance’ was described, which needs to be supplemented with testable relationships.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised.

      The study also aims to quantitatively compare the maximum and average sustained wheel power of the PHEV's powertrain across the high-load (US06) and moderate-load (NEDC) driving cycles, particularly focusing on the powertrain’s ability to meet peak demand in a charge-sustaining (CS) model  and to quantify and compare the resulting state of charge (SOC) and wheel horse power operational modes of the chassis dynamometer under the US06 NEDC and EPA driving cycles.

Comments 2: The full paper does not quantify the contribution of brake energy return to SOC, which is a key aspect of PHEV energy management. For example, is there a need to analyse the potential for energy recovery potential in the highway segment when SOC plummeted by 59.95% in the EPA Highway test?

Response 2: Agree. We have, to emphasize this point in article.

The analysis yields three critical findings regarding the relationship between driving cycle and net energy use.

    First, the EPA Highway cycle demonstrates the highest net energy efficiency, exhibiting the lowest rate of SOC depletion over distance. This outcome confirms that steady-state cruising, which minimizes gross energy expenditure against rolling resistance and aerodynamic drag, is intrinsically efficient. This performance occurs despite literature estimates suggesting minimal regenerative opportunity in motorway conditions, the test shows SOC around 22.6 %.  

     Second, the aggressive US 06 cycle, which presents the greatest gross kinetic energy available for recovery due to high speeds and sharp decelerations, paradoxically records the highest net energy consumption. The vehicle experienced a substantial 36.9 % of SOC depletion over just 12.8 kilometers. This energy imbalance highlights a severe operational constraint where the extreme instantaneous power required for rapid acceleration far outweighs the energy that can be recuperated during aggressive braking events, often due to limitations imposed by battery discharge rates and maximum motor output capacity.  

Third, the NEFZ cycle, characterized by variation of speed by high stop-and-go elements inherent to urban driving, aligns most closely with conditions that maximize the fraction of dissipated kinetic energy that can be recovered. While its net depletion rate remains high compared to the NEFZ SOC  63.1% for ΔSOC/km, this environment provides the theoretically optimal physical scenario for testing and maximizing regenerative blending effectiveness.

Table 1 Summarize results

Analysis of the net electrical energy consumption, quantified by the State of Charge (SOC) depletion, observed in a Plug-in Hybrid Electric Vehicle (PHEV) when subjected to three distinct standardized regulatory driving cycles the aggressive US 06, the mixed-mode New European Driving Cycle (NEFZ), and the steady EPA Highway Fuel Economy Test (HWFET). The analysis focuses on interpreting the potential for and limitations of kinetic energy recovery via regenerative braking systems across these dynamic profiles.

US 06 driving conditions

The analysis yields three critical findings regarding the relationship between driving dynamism and net energy use.

First, the EPA Highway cycle demonstrates the highest net energy efficiency, exhibiting the lowest rate of SOC depletion over distance. This outcome confirms that steady-state cruising, which minimizes gross energy expenditure against rolling resistance and aerodynamic drag, is intrinsically efficient. This performance occurs despite literature estimates suggesting minimal regenerative opportunity in motorway conditions, often around 18% of useful motor energy.  

     Second, the aggressive US 06 cycle, which presents the greatest gross kinetic energy available for recovery due to high speeds and sharp decelerations, paradoxically records the highest net energy consumption. The vehicle experienced a substantial 77.4% SOC depletion over just 12.8 kilometers. This energy imbalance highlights a severe operational constraint where the extreme instantaneous power required for rapid acceleration far outweighs the energy that can be recuperated during aggressive braking events, often due to limitations imposed by battery discharge and maximum motor charge capacity.  

     Third, the NEFZ cycle, characterized by high stop-and-go driving characteristic  elements inherent to urban driving, aligns most closely with conditions that maximize the fraction of dissipated kinetic energy that can be recovered (studies show up to 70% recovery potential in urban settings). While its net depletion rate remains high compared to the HWFET (5.74% of ΔSOC/km), this environment provides the theoretically optimal physical scenario for testing and maximizing regenerative blending effectiveness.

Using an industry average PHEV battery capacity of approximately 10.7 kWh, it is possible to calculate the net energy consumption per kilometer. The US 06 cycle, with its high ΔSOC of 77.4% over 12.8 km, reveals an exceptionally high net energy consumption by approximately 647 Wh/km). Conversely, the EPA Highway cycle, with its 40.05% depletion over 26.4 km, consumes only about 164 kW/km. The approximately four-fold difference in net energy consumption between the US 06 and EPA Highway cycles demonstrates that the US 06 profile demands vastly higher instantaneous power delivery, stressing the battery and motor limits during both discharge and attempted charge, likely contributing to increased ohmic losses (I2R). This necessary step of converting the relative percentage drop to absolute power demand clarifies the severity of the energy expenditure in aggressive driving.

NEFZ

The NEFZ (or NEDC) is a mixed cycle intended to represent typical usage, encompassing both urban stop-and-go elements (ECE-15 phases) and extra-urban driving (EUDC). Key dynamic characteristics include a low average speed (33.6 km/h) and a high proportion of idling time (the combined NEDC features 24% idle time), which favors repeated, low-to-medium-power regenerative braking events.  

The NEFZ cycle resulted in a moderate total depletion (63.1%) over a short distance (11.0 km), yielding a high consumption rate of 5.74% ΔSOC/km. Academic literature supports that such urban and suburban conditions offer a high yield for regenerative braking, potentially representing up to 70% of useful motor energy. However, the high observed net energy consumption suggests that while the road load fraction of kinetic energy recovered may be high, the cumulative energy cost of overcoming vehicle inertia and rolling resistance during the frequent acceleration phases (which account for 36.9% of the NEFZ cycle ) still results in substantial battery drain. The engineering priority in this driving environment shifts from maximizing recovery power as in US 06 to minimizing overall parasitic losses during every acceleration event.  

EPA highway

The EPA Highway Fuel Economy Driving Schedule (HWFET) simulates steady cruising conditions, with the observed test registering an average speed of 77.7 km/h and a maximum speed of 96.6 km/h. This profile is characterized by minimal acceleration or deceleration, resulting in low vehicle dynamism.  

EPA highway cycle yielded the lowest total SOC depletion 40.05% and crucially, the lowest consumption rate at 1.52% ΔSOC/km, despite covering the longest distance 26.4 km. This superior net efficiency is attributed not to high energy recovery, but to the high inherent thermodynamic and mechanical efficiency of constant-speed operation, where energy is expended primarily against predictable drag forces. This observation strongly aligns with powertrain studies confirming that motorway conditions limit regenerative opportunity to approximately 18%. For highway driving, the PHEV is optimized to minimize losses rather than focus on maximizing recuperation.   Steady State, minimal dynamism ΔSOC of 40.54 % over 26.4km, reveals an exceptionally high net energy consumption approximately 164 kW/km. Conversely, the EPA Highway cycle has approximately four-fold difference in net energy consumption between the US 06 and EPA Highway cycles demonstrates that the US 06 profile demands vastly higher instantaneous power delivery, stressing the battery and motor limits during both discharge and attempted charge, likely contributing to increased ohmic losses (I2R). This necessary step of converting the relative percentage drop to absolute power demand clarifies the severity of the energy expenditure in aggressive driving.

Comments 3: The calculation of SOC consumption rates is not clear, and it is recommended that an error analysis or repeatability validation be provided to improve data reliability.

Response 3: Agree. We have, accordingly, done emphasize this point.

The clarity of the State-of-Charge (SOC) consumption rate calculation and the need for data reliability validation. We have taken the following steps to clarify our methodology and address data reliability

1. Clarification of SOC Data Acquisition

SOC Measurement: The State-of-Charge (SOC) data was recorded directly from the vehicle's Battery Management System (BMS) via the OBD-II port using a high-resolution logging tool, Battery metrics.

Resolution: The logging frequency was set to 10 Hz (10 data points per second), providing a high-fidelity record of the SOC during the test conditions.

Data Source Reliability, The OBD-II data stream represents the vehicle's internal, real-time assessment of its SOC, which is calculated and provided by the calibrated Battery Management System (BMS). This method minimizes external measurement errors.

        2. Calculation of SOC Consumption Rate

The SOC consumption rate (RSOC​) was calculated over a defined time interval (Δt) using the following formula

Where SOCt1​​ and SOCt2​​ are the SOC values recorded by Battery metrics at time t1​ and t2​, respectively.

The raw 10 Hz data form OBD was processed to remove noise, and the consumption rate was typically averaged over the full duration of the test run to provide a stable metric

Table 2 Repeatability time

This analysis evaluates the consistency of the Plug-in Hybrid Electric Vehicle (PHEV) Energy Management System (EMS). The assessing the standard deviation (STDEV) of the final State of Charge (SoC) across four repeat tests for the US06, NEFZ, and EPA Highway driving cycles. The use of a high-resolution OBD system, capable of resolving SOC to provides a robust basis for differentiating true system variance from measurement noise.

     3. Analysis of Test Repeatability

US06 Driving Cycle

The US06 cycle, characterized by high-speed, high-acceleration transients and significant power demand, demonstrated the highest level of SOC management repeatability. The low mean SOC of suggests the vehicle was operating near its lower SoC buffer limit, yet the Standard Deviation (STDEV) was exceptionally low at US06 driving condition.

This low variance indicates that under maximum-demand conditions, the EMS operates with minimal ambiguity. The high current draw likely provides a clear signal, and the system is tightly constrained by a performance-critical control strategy, resulting in highly consistent battery utilization and regeneration profiles across all four runs allowing 95% of confidential.

NEFZ Driving Cycle

The NEFZ (New European Driving Cycle equivalent) exhibited the highest data variability, with a Standard Deviation of around an average SOC of . The NEFZ cycle is characterized by multiple low-to-medium speed accelerations, decelerations, and idle periods, representing frequent mode transitions between the engine and motor.

The significantly higher is hypothesized to stem from the cumulative effect of minor, inherent inconsistencies in the EMS decision-making at these lower power demands and transitional states. Factors contributing to this variability may include.

Thermal Dithering, small variations in ambient or component temperature at the start of each run, which disproportionately influence engine start/stop decisions or auxiliary load demand HVAC, cooling pumps during low-power segments.

State Transition Tolerance, the EMS often employs a tolerance band for battery power requests in charge-sustaining mode. The NEFZ cycle frequently skirts the edges of these control boundaries, allowing for greater run-to-run divergence in the precise timing of mode switching, which accumulates in the final SOC value.

EPA Highway Driving Cycle

The EPA Highway driving cycle, representing a more prolonged, steady-state high-speed cruising profile, yielded a moderate Standard Deviation of (Average SOC).

The variance, while lower than NEFZ, is higher than US06. This is attributed to the integration of low-magnitude, continuous errors over the cycle's long duration. During steady-state operation, the engine and motor are primarily balancing accessory loads and aerodynamic drag. Minor fluctuations in load from external factors—such as minute speed corrections on the chassis dynamometer or continuous variation in auxiliary system power consumption (e.g., A/C compressor cycling, belt-driven accessories) are integrated over time, leading to the observed deviation.

2. Addressing Measurement Resolution and Reviewer Comments

The data definitively demonstrates that the observed repeatability error is not an artifact of the measurement system. With The OBD resolution of the smallest recorded standard deviation (US06) is an order of magnitude larger than the measurement floor. This confirms that the variance is a genuine characteristic of the PHEV's control system performance in response to the specific kinematic demands of each cycle, exacerbated by subtle environmental and initial state variations across the repeated tests.

In conclusion, the repeatability of the final SOC is highly correlated with the dynamic nature of the driving cycle. The EMS exhibits best performance consistency under maximum-demand conditions (US06), while the frequent, low-power transitions of the NEFZ cycle introduce the greatest cumulative variance. Further research should focus on isolating the specific control parameters responsible for the NEFZ cycle's high to improve overall PHEV system robustness.

Comments 4: The full text is confusingly formatted in figures and tables, recheck the pdf and revise it figure by figure.

Response 4: Agree. We have, accordingly, revised this point in full paper.

5. Additional clarifications

5.1 This manuscript describes a study of wheel power and state of charge (SOC) of hybrid vehicles in tests conducted on a chassis dynamometer (rolling road) under three testing protocols, namely, one American and two European, and realistic driving conditions. Therefore, the title is slightly misleading, i.e., the word‘European’ should be deleted. We rename the title to “Investigation of the Wheel Power and State of Charge of Plug-in Hybrid Electric Vehicles (PHEVs) on a Chassis Dynamometer in Various Driving Test Cycles” .

5.2  We change between ‘NEFZ’ and ‘NEDC’ and back again; the former is the German abbreviation, the latter the English. We selected consistently use the English abbreviation.

(2) The inconsistent use of capitalization for definitions of acronyms and abbreviations, as well as for domain specific terminology.

(3) We revised a tendency to define abbreviations and acronyms multiple times across the manuscript.

(4) A mixing up of terminology and definitions where the authors refer to the car operating in electic vehicle mode as ‘electric power (EV)’, which makes it seem that ‘electric power’ is the definition of the abbreviation ‘EV’, which of course, it is not. Similarly, ‘engine power (ICE)’ and ‘hybrid power (HEV)’ are used. It is far better to use phrases such as ‘power in EV mode’ or ‘power (EV mode).  

Response to Reviewer 2 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files. US06 is a US driving test cycle, not a European driving test cycle. I already change delete the word ‘European’ to optimization title.

2. Questions for General Evaluation

Reviewer’s Evaluation

Response and Revisions

Does the introduction provide sufficient background and include all relevant references?

Yes improved

[Please give your response if necessary. Or you can also give your corresponding response in the point-by-point response letter. The same as below]

Are all the cited references relevant to the research?

Yes/ improved

Is the research design appropriate?

Yes/Can be improved/Must be improved/Not applicable

Are the methods adequately described?

Yes/Can be improved/Must be improved/Not applicable

Are the results clearly presented?

Yes/Can be improved/Must be improved/Not applicable

Are the conclusions supported by the results?

Yes

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: The abstract effectively summarizes your methodology and findings, but consider adding a brief statement about the practical implications of your results for PHEV users or manufacturers.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised.

Abstract: The purpose of this study is to monitor the battery performance of plug-in hybrid electric vehicles (PHEVs) on a chassis dynamometer using the US06, NEDC, and EPA highway driving cycles. The chassis dynamometer simulates vehicle operation and driving conditions and allows for precise simulation of pre-defined driving cycles, including simulations of acceleration, deceleration, stopping, and re-acceleration on the road. In the case of the US06 driving cycle, the results for ( EV mode) compared with energy consumption during electric testing revealed a consistent decrease in the SOC (state of charge) due to the rapid response of the electric motor distribution to the changing power, as well as electric power fluctuations during driving conditions. Under the NEDC driving cycle, the test results for electric power (EV) compared with energy consumption during electric testing revealed that the SOC gradually decreased at the start of the test due to low driving speeds. Towards the end, at around 800 seconds, an increase in driving speed resulted in a noticeable drop in SOC. The electric power varied during the driving cycle in this test due to the motor's rapid response to changes in power distribution while driving. For the EPA Highway driving cycle test, the test results for electric power (EV) compared with energy consumption during continuous electric testing indicated a gradual decrease in the SOC at first due to low driving speeds. As the driving speed increased after about 300 seconds, the SOC rapidly decreased. Because of the motor's quick response to changes in the power distribution while driving, the electric power varied according to the driving cycle.

Comments 2: In the introduction, you've provided a thorough literature review. Consider adding a paragraph that more explicitly identifies the research gap your study addresses to strengthen the justification for your work.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have revised as below text.

Most research has been predictive or focused on comparing driving at various temperatures, with no relevant studies found in Thailand. Therefore, the objectives of this research study are to examine the performance suitability of PHEVs to understand the power accessibility of plug-in hybrid vehicles using a chassis dynamometer and to analyse the horsepower net energy changes of the internal combustion engine, and the battery's state of charge in simulated scenarios on a chassis dynamometer as an alternative to conventional fuel use.

Already revise in paper

Comments 3: The experimental methodology is well-described, but the figures could benefit from higher resolution. Figure 1 and 2 appear somewhat pixelated, which might reduce clarity in the final publication.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have revised as below figure.

Figure 1. Experimental Diagram

Figure 2. Experimental PHEV test rig

Comments 4: Your results are presented logically for each driving cycle, but consider adding a comparative analysis section that directly contrasts the three driving cycles to highlight key differences in PHEV performance across these standardized tests.

Response 4: Thank you for pointing this out. We agree with this comment. Therefore, I/we have revised.

     State of Charge (SOC) Depletion and Energy consumption. The most significant difference lies in the total SOC consumption across the three tests, directly reflecting the energy demand of each cycle.

EPA Highway, experienced the highest energy consumption, with an SOC drop of ≈60% (from ≈100% to ≈40%). The sustained high speed and power required for highway driving result in continuous, high-rate battery use and limited regenerative opportunity, leading to the largest overall reduction in electric range.

NEFZ showed an intermediate SOC consumption 39.69%. While the test duration is the longest, the lower average speed and repeated cycles suggest the demand is less power-intensive per unit of time than the highway or aggressive cycles, resulting in a more moderate total energy draw.

US06 consumed the least amount of energy, with an SOC drop of 59.56%. Despite the aggressive nature of the cycle (high peaks in power and speed), its shorter total duration 600 seconds is the primary reason for the lowest total SOC consumption. This highlights that while the instantaneous power demand is high, the overall time spent drawing power is limited.

Implication for PHEV System Operation. The different cycles underscore the varying roles of the electric powertrain in real-world driving

High-speed cycles (EPA Highway) necessitate a high and continuous energy output, rapidly draining the battery. The text notes the engine workload accounted for 61% of the operation in HEV mode for this cycle, indicating that the PHEV would rely heavily on the internal combustion engine (ICE) for sustained high-speed travel once the battery is depleted.

Comments 5; The conclusion effectively summarizes your findings, but could be strengthened by discussing limitations of the current study and suggesting specific directions for future research.

Response 5: Thank you for pointing this out. We agree with this comment. Therefore, we have revised.

Key Findings

The experimental results across the three standardized driving cycles (US06, NEDC, and EPA Highway) consistently demonstrated a clear relationship between vehicle speed, driving cycle demands, and battery performance in the plug-in hybrid electric vehicle (PHEV).

Across all three test cycles, the electric motor exhibited a rapid and dynamic response to fluctuations in the energy supply during driving. This rapid response confirms the system’s ability to instantaneously meet the varying power demands encountered under diverse driving conditions (urban highway, and US06).

The rate of battery state of charge (SOC) depletion was directly correlated with the intensity and duration of high-speed periods.

In the US06 driving cycle test, the high-demand profile led to a continuous decrease in the SOC due to the sustained rapid energy expenditure.

In the NEDC (urban/moderate) and EPA Highway cycles, the SOC was depleted gradually at lower speeds but underwent a sharp, noticeable drop, directly corresponding to phases where driving speeds significantly increased (e.g., around 800 seconds in NEDC and 300 seconds in EPA Highway).

Consistency in EV power variation: For all tested cycles, the electric power output consistently varied in accordance with the profile of the respective driving cycle, confirming that the vehicle's control system efficiently utilized electric power to follow the target speed.

Limitations of this Study

Based on the described experimental methodology, the following limitations should be considered when interpreting the results: 

Limited vehicle scope, Only one specific PHEV model was evaluated in this study. The derived efficiency characteristics and SOC behavior may not be generalizable to other PHEV architectures, battery capacities, or energy management strategies implemented by different manufacturers.

Dynamometer-only testing: Experiments were conducted solely on a chassis dynamometer. While this ensures a controlled and repeatable environment, it inherently omits real-world influences such as road grade, wind resistance, thermal effects from varying ambient temperatures, and driver-specific variations, which can significantly impact actual PHEV performance.

Lack of comparative detail, although the methodology included comparisons of ICE, HEV, and EV data, the tests focused almost exclusively on the EV mode (electric power and SOC changes). There is a lack of a detailed, quantitative analysis and a discussion of the observed differences and efficiency trade-offs between the internal combustion engine (ICE) and hybrid electric vehicle (HEV) operating modes under these cycles .  

         Future Work Study Limitations overcoming, the limitations of the present study, es-pecially the scope of vehicles, testing conditions, and the comparison in detail, lead to the clear way forward in future research in this field. It is possible to strategically plan future research to address these limitations, which will substantiate the existing results and expand them. Limited vehicle scope future work with the variety of vehicles focused on one Plug-in Hybrid Electric Vehicle (PHEV) model, it is possible to address this limitation with the help of a large-scale, multi-vehicle test program. Research directions in the future should contain a minimum of three different PHEV architectures which differ in battery size, motor arrangement (series or parallel) and manufacturer-specific Energy Management Strategies (EMS). This would allow a comparative sensitivity analysis to reveal what observed efficiency and State-of-Charge (SOC) behaviors are generic and what are unique to different designs, leading to more generalized conclusions about the performance of PHEVs. Dynamometer only testing       

      Future Work: The artificial but controlled character of chassis dynamometer testing is an issue that can be resolved by introducing much on-road testing in the laboratory work. In subsequent studies, the results of the dynamometer would be compared to the data gathered on the same cars that would be used in the real-world driving scenario (RWD). This involves the deployment of Portable Emission Measurement Systems (PEMS) and data loggers to capture the variables such as road grade, real time thermal management information, and the ambient temperatures. The laboratory and field data would be combined to form correction factors or high-fidelity simulation models that would perfectly reflect the real world operational factors that affect PHEV efficiency. Deficiency in Comparative Detail Future Work: To conquer the major concern of the present study, namely the Electric Vehicle (EV) mode, future work needs to include detailed, quantitative energy balance and efficiency breakdown of all three operating modes, namely EV, Internal Combustion Engine (ICE), and Hybrid Electric Vehicle (HEV). This requires the total energy consumption of each mode in terms of the tank-to-wheel energy consumption to be calculated and discussed using the same drive cycles. Comparative data in future research must be applied to develop measurable efficiency trade-off matrix to determine the best duty cycles or thresholds to switch EV to ICE or HEV mode and achieve the maximum total energy savings or CO2 reduction.

Comments 6;

Consider adding a brief discussion on the practical implications of your findings for PHEV design optimization or usage patterns for drivers seeking to maximize electric range.

Response 6: Thank you for pointing this out. We agree with this comment. Therefore, we have revised.

Practical implications for PHEV optimization and usage: These findings offer direct guidance for PHEV design and driver behavior. Designs should be optimized to focus on high-speed efficiency and regeneration.

The EPA Highway results (60% SOC use) show that the electric range is severely com-promised at sustained high speeds. PHEV designers should focus on minimizing aerodynamic and rolling resistance to preserve the electric range on the highway. Enhancing the regenerative braking efficiency is also critical, especially in the US06 and NEDC cycles, where deceleration events are frequent. Optimal battery charging control during regeneration is key to maximizing energy recovery in these dynamic scenarios.

The Driver Usage Pattern Maximizes EV Mode in Urban Settings

Electric use for city driving (like under the NEDC test conditions) should be prioritized. Since lower-speed urban cycles are less demanding on the battery per distance covered compared with highway cycles, drivers seeking to maximize their electric range should save their battery charge for low-speed, stop-and-go driving conditions.

Aggressive acceleration (as in US06) should be minimized. Although the US06 test has the lowest total SOC use due to its short duration, the high instantaneous power peaks stress the battery and can reduce overall system efficiency. Smooth acceleration and deceleration are essential for maximizing the electric range in daily driving.

Comments on the Quality of English Language

Regarding the English language quality:

•            Several sentences throughout the manuscript would benefit from restructuring for clarity and flow

•            There are instances of awkward phrasing and grammatical errors that should be addressed

•            The paper would benefit from a thorough copy-editing by a native English speaker

•            Some technical terminology is inconsistently applied throughout the text

•            Long, complex sentences could be broken into shorter ones for improved readability

Thank you for pointing this out. We agree with this comment. Therefore, we have revised.  send manuscript to revise with MDPI author service.

 The certificate is shown below.