Adaptive λ-Control Strategy for Plug-In HEV Energy Management Using Fast Initial Multiplier Estimate
Round 1
Reviewer 1 Report
1. The order of references is out of order. It is suggested to reorder them. The selected references are old and cannot reflect the current research status. It is recommended to cite more articles within 5 years. Such as,[ Sustainability, 2022, 14(10): 6320], [Sustainability, 2022, 14(3): 1214]
2. Fig. 2 is compressed. The numerical value labels block each other in Fig. 6 and Fig. 7. The font in Figure 9 should not be hollow. Should line 368 start a new line.
3. “The amount of fuel consumed is around 2.33L per 100km for a battery balance of around –70.80% for 10 mixed cycles (best offline results is: 2.1L is for a battery balance of around –70.2%). The amount of fuel consumed is around 2.87L per 100km for a battery balance of around –70.11% for 6 WLTC cycles (best offline result 2.7L is for a battery balance of around –69.8%).” How do you get the fuel consumption? Why is the battery balance negative?
Author Response
Dear reviewer,
Thank you for your valuable comments on our work.
Please find attached our responses to your questions.
Best regards
Author Response File: 
Author Response.docx
Reviewer 2 Report
The paper decribes an attempt at optimizing energy usage and strategy on board a plug-in hybrid-electric vehicle through complex algorithms, of which I am not in the position to assess the significance. A few question marks arise however at the first sight.
-the vehicle model seems extremely simplified: aerodynamic drag, road grade, and rolling resistance are not even mentioned.
-no details at all are given about the type of vehicle and its typical mission profile. Is it a passenger car? A light commercial vehicle? A three-wheeler? The only hint comes from the overall vehicle weight (1155 kg) which appears extremely low for a plug-in HEV.
-description of the algorithms is extremely complex and probably understandable only with a solid background of control theory. Simpler descriptions should be given as well.
-the strategy requires the drive cycle to be known, at least approximately (which is a shortcoming on its own). The NEDC cycle is therefore selected as a reference. The NEDC however is now considered obsolete since it is not representative of real-life vehicle use: why not select another, more realistic cycle?
-regenerative braking is completely ignored, although it plays a major role in determining overall vehicle efficiency, and requires specific management to be integrated in the powertrain strategies (see Sandrini, G.; Chindamo, D.; Gadola, M. (2022) Regenerative Braking Logic That Maximizes Energy Recovery Ensuring the Vehicle Stability. Energies 2022, 15(16), 5846 for instance).
-the results are deemed "good" although this seems to remain a subjective statement.
Apart from the above considerations, the English language should be revised, and the significance of captions and text sentences referring to the figures should be very carefully checked.
Author Response
Dear reviewer,
Thank you for your valuable comments on our work.
Please find attached our responses to your questions.
Best regards
Author Response File: Author Response.docx
