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An Investigation of Driver Brake Pedal Stroke Input on Regenerated Braking Energy in Electric Vehicles via Dynamic Programming

Yıl 2025, Cilt: 16 Sayı: 3, 687 - 695
https://doi.org/10.24012/dumf.1655409

Öz

The rising popularity of electric vehicles increases the need for advanced techniques to improve driving efficiency. One such method is regenerative braking, which captures kinetic energy from the wheels—energy that would otherwise be lost as in traditional braking systems. In this study, a fully electric vehicle model which is three degrees of freedom was created with a fixed pedal-feel brake pedal and electric motors on both axles. The brake torque produced by pedal stroke input in different braking scenarios was allocated to the electric motors on the front and rear axles via dynamic programming in MATLAB/Simulink. It was compared to the case where the distribution ratio is fixed. More energy was gained with dynamic programming compared to the fixed allocation, and it is concluded that the duration of pressing the pedal and the repetition of pressing are effective parameters on energy recovery.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

122M994.

Kaynakça

  • [1] E. Labeye, M. Hugot, C. Brusque, and M. A. Regan, "The electric vehicle: A new driving experience involving specific skills and rules, "Transportation Research Part F: Traffic Psychology and Behaviour”, vol. 37, pp. 27–40, Feb. 2016.
  • [2] Miri, I., Fotouhi, A., and Ewin, N., "Electric vehicle energy consumption modelling and estimation—A case study," International Journal of Energy Research, vol. 45, no. 1, pp. 501-520, Jan. 2021.
  • [3] G. A. Chandak and A. A. Bhole, "A review on regenerative braking in electric vehicle," 2017 Innovations in Power and Advanced Computing Technologies (i-PACT), pp. 1-5, 2017.
  • [4] J. Zhiming, R. Dianbo, S. Baoyu, C. Shumei, and S. Gang, “The research of regenerative braking control strategy for advanced braking force distribution,” in 2009 Fifth International Conference on Natural Computation, vol. 6, Aug. 2009, pp. 458–462. IEEE
  • [5] Bogineni, J., & Nakka, J. (2022, January). Battery and supercapacitor performance analysis during regenerative braking in electric vehicles. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 108-112). IEEE.
  • [6] W. J. Melis and O. Chishty, “Fully regenerative braking and improved acceleration for electrical vehicles,” Int. J. Sustain. Energy Dev. (IJSED), vol. 2, no. 1, pp. 75–80, 2013.
  • [7] P. S. Shenil, “Novel regenerative braking controllers for electric vehicle driven by BLDC motor,” in 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2021.
  • [8] W. Jiang, R. Zheng, G. Zhang, Z. Zhu, W. Wang, C. Li, and Q. Tong, “Optimal torque distribution strategy for electric vehicles with electro-hydraulic compound braking system,” in 2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI), Oct. 2023, pp. 1–6. IEEE.
  • [9] W. Xu, H. Chen, H. Zhao, and B. Ren, “Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system,” Mechatronics, vol. 57, pp. 95–108, 2019.
  • [10] D. H. Kim, J. M. Kim, S. H. Hwang, and H. S. Kim, “Optimal brake torque distribution for a four-wheel-drive hybrid electric vehicle stability enhancement,” Proc. Inst. Mech. Eng., Part D: J. Automob. Eng., vol. 221, no. 11, pp. 1357–1366, 2007.
  • [11] G. BhaskarRao, N. Mounika, K. Chandana, A. DileepKumar, G. AshokBabu, and S. HimaVarshini, "Control strategy for regenerative braking in electric vehicles," International Journal of Scientific Research in Engineering and Management, 2023, doi: 10.55041/ijsrem18484
  • [12] D. Kim, J. SooEo, and K.-K. K. Kim, "Parameterized energy-optimal regenerative braking strategy for connected and autonomous electrified vehicles: A real-time dynamic programming approach," IEEE Access, 2021. DOI: 10.1109/access.2021.3098807
  • [13] B. Liu, L. Li, X. Wang, and S. Cheng, "Hybrid electric vehicle downshifting strategy based on stochastic dynamic programming during regenerative braking process," IEEE Transactions on Vehicular Technology, 2018. [Online]. Available: DOI: 10.1109/TVT.2018.2815518.
  • [14] J. Zhang, Y. Yang, D. Qin, C. Fu, and Z. Cong, "Regenerative braking control method based on predictive optimization for four-wheel drive pure electric vehicle," IEEE Access, vol. 9, pp. 1-10, 2021. DOI: 10.1109/ACCESS.2020.3046853.
  • [15] C. Qiu, G. Wang, M. Meng, and Y. Shen, “A novel control strategy of regenerative braking system for electric vehicles under safety critical driving situations,” Energy, vol. 149, pp. 329–340, Apr. 2018, doi:10.1016/j.energy.2018.02.046.
  • [16] U. Caliskan and V. Patoglu, "Efficacy of haptic pedal feel compensation on driving with regenerative braking," IEEE Transactions on Haptics, vol. 13, no. 1, pp. 175-182, 2020.
  • [17] Rajamani, R.: Vehicle Dynamics and Control. Springer, New York (2012)
  • [18] Regulation No 13 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of vehicles of categories M, N and O regarding braking, (OJ L 257 30.9.2010, p. 1) [Online]. Available: https://op.europa.eu/s/y1QM
  • [19] E. Dincmen, B. Güvenç, "A control strategy for parallel hybrid electric vehicles based on extremum seeking," Vehicle System Dynamics, vol. 50, pp. 199-227, 2012, doi: 10.1080/00423114.2011.577224.
  • [20] O. Ergun, N. O. Cayci, E. Dincmen, and I. Istif, "Optimum torque distribution during regenerative braking in a fully electrical vehicle via dynamic
  • [21] programming," in 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Oct. 2023, pp. 1-6

An Investigation of Driver Brake Pedal Stroke Input on Regenerated Braking Energy in Electric Vehicles via Dynamic Programming

Yıl 2025, Cilt: 16 Sayı: 3, 687 - 695
https://doi.org/10.24012/dumf.1655409

Öz

The rising popularity of electric vehicles increases the need for advanced techniques to improve driving efficiency. One such method is regenerative braking, which captures kinetic energy from the wheels—energy that would otherwise be lost as in traditional braking systems. In this study, a fully electric vehicle model which is three degrees of freedom was created with a fixed pedal-feel brake pedal and an electric motor on the front and rear axles. The brake torque produced by pedal stroke input in different braking scenarios was allocated to the electric motors on the front and rear axles via dynamic programming in MATLAB/Simulink. It was compared to the case where the distribution ratio is fixed. More energy was gained with dynamic programming compared to the fixed allocation, and it is concluded that the duration of pressing the pedal and the repetition of pressing are effective parameters on energy recovery.

Proje Numarası

122M994.

Kaynakça

  • [1] E. Labeye, M. Hugot, C. Brusque, and M. A. Regan, "The electric vehicle: A new driving experience involving specific skills and rules, "Transportation Research Part F: Traffic Psychology and Behaviour”, vol. 37, pp. 27–40, Feb. 2016.
  • [2] Miri, I., Fotouhi, A., and Ewin, N., "Electric vehicle energy consumption modelling and estimation—A case study," International Journal of Energy Research, vol. 45, no. 1, pp. 501-520, Jan. 2021.
  • [3] G. A. Chandak and A. A. Bhole, "A review on regenerative braking in electric vehicle," 2017 Innovations in Power and Advanced Computing Technologies (i-PACT), pp. 1-5, 2017.
  • [4] J. Zhiming, R. Dianbo, S. Baoyu, C. Shumei, and S. Gang, “The research of regenerative braking control strategy for advanced braking force distribution,” in 2009 Fifth International Conference on Natural Computation, vol. 6, Aug. 2009, pp. 458–462. IEEE
  • [5] Bogineni, J., & Nakka, J. (2022, January). Battery and supercapacitor performance analysis during regenerative braking in electric vehicles. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 108-112). IEEE.
  • [6] W. J. Melis and O. Chishty, “Fully regenerative braking and improved acceleration for electrical vehicles,” Int. J. Sustain. Energy Dev. (IJSED), vol. 2, no. 1, pp. 75–80, 2013.
  • [7] P. S. Shenil, “Novel regenerative braking controllers for electric vehicle driven by BLDC motor,” in 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2021.
  • [8] W. Jiang, R. Zheng, G. Zhang, Z. Zhu, W. Wang, C. Li, and Q. Tong, “Optimal torque distribution strategy for electric vehicles with electro-hydraulic compound braking system,” in 2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI), Oct. 2023, pp. 1–6. IEEE.
  • [9] W. Xu, H. Chen, H. Zhao, and B. Ren, “Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system,” Mechatronics, vol. 57, pp. 95–108, 2019.
  • [10] D. H. Kim, J. M. Kim, S. H. Hwang, and H. S. Kim, “Optimal brake torque distribution for a four-wheel-drive hybrid electric vehicle stability enhancement,” Proc. Inst. Mech. Eng., Part D: J. Automob. Eng., vol. 221, no. 11, pp. 1357–1366, 2007.
  • [11] G. BhaskarRao, N. Mounika, K. Chandana, A. DileepKumar, G. AshokBabu, and S. HimaVarshini, "Control strategy for regenerative braking in electric vehicles," International Journal of Scientific Research in Engineering and Management, 2023, doi: 10.55041/ijsrem18484
  • [12] D. Kim, J. SooEo, and K.-K. K. Kim, "Parameterized energy-optimal regenerative braking strategy for connected and autonomous electrified vehicles: A real-time dynamic programming approach," IEEE Access, 2021. DOI: 10.1109/access.2021.3098807
  • [13] B. Liu, L. Li, X. Wang, and S. Cheng, "Hybrid electric vehicle downshifting strategy based on stochastic dynamic programming during regenerative braking process," IEEE Transactions on Vehicular Technology, 2018. [Online]. Available: DOI: 10.1109/TVT.2018.2815518.
  • [14] J. Zhang, Y. Yang, D. Qin, C. Fu, and Z. Cong, "Regenerative braking control method based on predictive optimization for four-wheel drive pure electric vehicle," IEEE Access, vol. 9, pp. 1-10, 2021. DOI: 10.1109/ACCESS.2020.3046853.
  • [15] C. Qiu, G. Wang, M. Meng, and Y. Shen, “A novel control strategy of regenerative braking system for electric vehicles under safety critical driving situations,” Energy, vol. 149, pp. 329–340, Apr. 2018, doi:10.1016/j.energy.2018.02.046.
  • [16] U. Caliskan and V. Patoglu, "Efficacy of haptic pedal feel compensation on driving with regenerative braking," IEEE Transactions on Haptics, vol. 13, no. 1, pp. 175-182, 2020.
  • [17] Rajamani, R.: Vehicle Dynamics and Control. Springer, New York (2012)
  • [18] Regulation No 13 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of vehicles of categories M, N and O regarding braking, (OJ L 257 30.9.2010, p. 1) [Online]. Available: https://op.europa.eu/s/y1QM
  • [19] E. Dincmen, B. Güvenç, "A control strategy for parallel hybrid electric vehicles based on extremum seeking," Vehicle System Dynamics, vol. 50, pp. 199-227, 2012, doi: 10.1080/00423114.2011.577224.
  • [20] O. Ergun, N. O. Cayci, E. Dincmen, and I. Istif, "Optimum torque distribution during regenerative braking in a fully electrical vehicle via dynamic
  • [21] programming," in 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Oct. 2023, pp. 1-6
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Teorisi ve Dinamiği
Bölüm Makaleler
Yazarlar

Nurettin Okan Çayci 0009-0002-0060-531X

Erkin Dinçmen 0000-0002-3234-281X

İlyas İstif 0000-0003-0792-249X

Proje Numarası 122M994.
Erken Görünüm Tarihi 30 Eylül 2025
Yayımlanma Tarihi 5 Ekim 2025
Gönderilme Tarihi 12 Mart 2025
Kabul Tarihi 25 Ağustos 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 16 Sayı: 3

Kaynak Göster

IEEE N. O. Çayci, E. Dinçmen, ve İ. İstif, “An Investigation of Driver Brake Pedal Stroke Input on Regenerated Braking Energy in Electric Vehicles via Dynamic Programming”, DÜMF MD, c. 16, sy. 3, ss. 687–695, 2025, doi: 10.24012/dumf.1655409.
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