Research Article
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Development of controller based on lungs performance optimization algorithm for hybrid energy storage systems of electric vehicles

Year 2024, Volume: 13 Issue: 3, 948 - 955, 15.07.2024
https://doi.org/10.28948/ngumuh.1449613

Abstract

Electric vehicles (EVs) have the potential to replace fossil fuel vehicles with advantages such as energy-saving capabilities and lack of exhaust pollution. However, pure electric vehicles still face limitations such as poor energy consumption, long charging times, and short battery range. Therefore, the use of hybrid energy storage systems (HESS) in EVs is becoming widespread. In this study, a new controller design was realized using the lungs performance-based optimization (LPO) algorithm and the energy consumption demands of EV HESS were optimized thanks to the designed system. The performance results of the proposed system were compared with other EV HESS management systems in the literature, and it was concluded in this study that the proposed LPO-based system is much superior to previous methods, typically reducing energy consumption by %21.86.

References

  • K. Jorgensen, “Technologies for electric, hybrid and hydrogen vehicles: Electricity from renewable energy sources in transport,” Utilities Policy, 16 (2), pp. 72–79, 2008, doi: 10.1016/j.jup.2007.11.005.
  • N. Omar et al., “Standardization work for BEV and HEV applications: critical appraisal of recent traction battery documents,” Energies, 5 (1), 138–156, 2012, do i: 10.3390/en5010138.
  • F. Hacker, R. Harthan, and F. Matthes, “Environmental impacts and impact on the electricity market of a large scale introduction of electric cars in Europe-Critical Review of Literature,” 4, 2009.
  • J. Martínez-Lao, F. G. Montoya, M. G. Montoya, and F. Manzano-Agugliaro, “Electric vehicles in Spain: An overview of charging systems,” Renewable and Sustainable Energy Reviews, 77, 970–983, 2017, doi: 10.1016/j.rser.2016.11.239.
  • A. Mahmoudzadeh Andwari, A. Pesiridis, S. Rajoo, R. Martinez-Botas, and V. Esfahanian, “A review of battery electric vehicle technology and readiness levels,” Renewable and Sustainable Energy Reviews, 78, 414–430, 2017, doi: 10.1016/j.rser.2017.03.138.
  • R. S. Sankarkumar and R. Natarajan, “Energy management techniques and topologies suitable for hybrid energy storage system powered electric vehicles: An overview,” Int Trans Electr Energ Syst, 31 (4), 2021, doi: 10.1002/2050-7038.12819.
  • I. Azizi and H. Radjeai, “A new strategy for battery and supercapacitor energy management for an urban electric vehicle,” Electr Eng, 100 (2), pp. 667–676, 2018, doi: 10.1007/s00202-017-0535-1.
  • F. Cheruiyot and D. Segera, “A Master-Slave Salp Swarm Algorithm Optimizer for Hybrid Energy Storage System Control Strategy in Electric Vehicles,” Journal of Energy, 2022, pp. 1–20, 2022, doi: 10.1155/2022/1648433.
  • R. Bousmaha, R. M. Hamou, and A. Amine, “Optimizing connection weights in neural networks using hybrid metaheuristics algorithms:,” International Journal of Information Retrieval Research, 12 (1), pp. 1–21, 2021, doi: 10.4018/IJIRR.289569.
  • D. M. Bu and C. Zhu, “Research on the Optimum Continuous Mileages under the Pure Electric Mode of Plug-In Hybrid Electric Vehicles,” AMM, 672–674, pp. 1179–1182, 2014, doi: 10.4028/www.scientific.net/AMM.672-674.1179.
  • J. Li et al., “Dual-loop online intelligent programming for driver-oriented predict energy management of plug-in hybrid electric vehicles,” Applied Energy, 253, p. 113617, 2019, doi: 10.1016/j.apenergy.2019.113617.
  • H. Zhou, F. Wei, and L. Sun, “Development Status of Electric Vehicles,” JAEV, 2 (1), pp. 531–534, 2004, doi: 10.4130/jaev.2.531.
  • S. Lu, K. A. Corzine, and M. Ferdowsi, “A New Battery/Ultracapacitor Energy Storage System Design and Its Motor Drive Integration for Hybrid Electric Vehicles,” IEEE Trans. Veh. Technol., 56 (4), pp. 1516–1523, 2007, doi: 10.1109/TVT.2007.896971.
  • H. Yu, R. Lu, T. Wang, and C. Zhu, “Battery/ultra-capacitor Hybrid Energy Storage System Used in HEV,” JAEV, 8 (1), pp. 1351–1356, 2010, doi: 10.4130/jaev.8.1351.
  • K. Gokce and A. Ozdemir, “A rule based power split strategy for battery/ultracapacitor energy storage systems in hybrid electric vehicles,” Int. J. Electrochem. Sci, 11 (2), 1228–1246, 2016.
  • E. Schaltz, A. Khaligh, and P. O. Rasmussen, “Influence of battery/ultracapacitor energy-storage sizing on battery lifetime in a fuel cell hybrid electric vehicle,” IEEE Trans. Veh. Technol., 58, (8), 3882–3891, 2009, doi: 10.1109/TVT.2009.2027909.
  • Q. Zhang, W. Deng, S. Zhang, and J. Wu, “a rule based energy management system of experimental battery/supercapacitor hybrid energy storage system for electric vehicles,” Journal of Control Science and Engineering, 1–17, 2016, doi: 10.1155/2016/6828269.
  • R. Carter, A. Cruden, and P. J. Hall, “Optimizing for efficiency or battery life in a battery/supercapacitor electric vehicle,” IEEE Trans. Veh. Technol., 61 (4), 1526–1533, 2012, doi: 10.1109/TVT.2012.2188551.
  • M. Pipicelli, B. Sessa, F. De Nola, A. Gimelli, and G. Di Blasio, “Assessment of battery–supercapacitor topologies of an electric vehicle under real driving conditions,” Vehicles, 5 (2), 424–445, 2023, doi: 10.3390/vehicles5020024.
  • J. P. Trovão and C. H. Antunes, “A comparative analysis of meta-heuristic methods for power management of a dual energy storage system for electric vehicles,” Energy Conversion and Management, 95, 281–296, 2015, doi: 10.1016/j.en conman.2015.02.030.
  • K. Ye, P. Li, and H. Li, “Optimization of Hybrid Energy Storage System Control Strategy for Pure Electric Vehicle Based on Typical Driving Cycle,” Mathematical Problems in Engineering, 1–12, 2020, doi: 10.1155/2020/1365195.
  • M. Ghasemi, M. Zare, A. Zahedi, P. Trojovský, L. Abualigah, and E. Trojovská, “Optimization based on performance of lungs in body: Lungs performance-based optimization (LPO),” Computer Methods in Applied Mechanics and Engineering, 419, 116582, 2024, doi: 10.1016/j.cma.2023.116582.
  • R. Wang and S. M. Lukic, “Dynamic programming technique in hybrid electric vehicle optimization,” in 2012 IEEE International Electric Vehicle Conference, Greenville, SC, USA: IEEE, pp. 1–8, 2012. doi:10.1 109/IEVC.2012.6183284.

Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi

Year 2024, Volume: 13 Issue: 3, 948 - 955, 15.07.2024
https://doi.org/10.28948/ngumuh.1449613

Abstract

Elektrikli araçlar, enerji tasarrufu yetenekleri ve egzoz kirliliğinin olmaması gibi avantajlarla fosil yakıtlı araçların yerini alma potansiyeline sahiptir. Ancak, saf elektrikli araçlar hâlâ kötü enerji tüketimi, uzun şarj süreleri ve kısa batarya menzili gibi kısıtlamalarla karşı karşıyadır. Bu nedenle elektrikli araçlarda hibrit enerji depolama sistemlerinin kullanılması yaygınlaşmaktadır. Bu çalışmada, akciğer performansına dayalı optimizasyon algoritması kullanılarak yeni bir kontrolör tasarımı gerçekleştirilmiş ve elektrikli araçların hibrit enerji depolama sistemlerinin enerji tüketim talepleri tasarlanan sistem ile optimize edilmiştir. Önerilen sistemin performans sonuçları literatürdeki diğer enerji yönetim sistemleri ile karşılaştırılmış ve bu çalışma ile önerilen sistemin önceki yöntemlerden çok daha üstün olduğu, tipik olarak ise enerji tüketimini %21.86 oranında düşürdüğü sonucuna ulaşılmıştır.

References

  • K. Jorgensen, “Technologies for electric, hybrid and hydrogen vehicles: Electricity from renewable energy sources in transport,” Utilities Policy, 16 (2), pp. 72–79, 2008, doi: 10.1016/j.jup.2007.11.005.
  • N. Omar et al., “Standardization work for BEV and HEV applications: critical appraisal of recent traction battery documents,” Energies, 5 (1), 138–156, 2012, do i: 10.3390/en5010138.
  • F. Hacker, R. Harthan, and F. Matthes, “Environmental impacts and impact on the electricity market of a large scale introduction of electric cars in Europe-Critical Review of Literature,” 4, 2009.
  • J. Martínez-Lao, F. G. Montoya, M. G. Montoya, and F. Manzano-Agugliaro, “Electric vehicles in Spain: An overview of charging systems,” Renewable and Sustainable Energy Reviews, 77, 970–983, 2017, doi: 10.1016/j.rser.2016.11.239.
  • A. Mahmoudzadeh Andwari, A. Pesiridis, S. Rajoo, R. Martinez-Botas, and V. Esfahanian, “A review of battery electric vehicle technology and readiness levels,” Renewable and Sustainable Energy Reviews, 78, 414–430, 2017, doi: 10.1016/j.rser.2017.03.138.
  • R. S. Sankarkumar and R. Natarajan, “Energy management techniques and topologies suitable for hybrid energy storage system powered electric vehicles: An overview,” Int Trans Electr Energ Syst, 31 (4), 2021, doi: 10.1002/2050-7038.12819.
  • I. Azizi and H. Radjeai, “A new strategy for battery and supercapacitor energy management for an urban electric vehicle,” Electr Eng, 100 (2), pp. 667–676, 2018, doi: 10.1007/s00202-017-0535-1.
  • F. Cheruiyot and D. Segera, “A Master-Slave Salp Swarm Algorithm Optimizer for Hybrid Energy Storage System Control Strategy in Electric Vehicles,” Journal of Energy, 2022, pp. 1–20, 2022, doi: 10.1155/2022/1648433.
  • R. Bousmaha, R. M. Hamou, and A. Amine, “Optimizing connection weights in neural networks using hybrid metaheuristics algorithms:,” International Journal of Information Retrieval Research, 12 (1), pp. 1–21, 2021, doi: 10.4018/IJIRR.289569.
  • D. M. Bu and C. Zhu, “Research on the Optimum Continuous Mileages under the Pure Electric Mode of Plug-In Hybrid Electric Vehicles,” AMM, 672–674, pp. 1179–1182, 2014, doi: 10.4028/www.scientific.net/AMM.672-674.1179.
  • J. Li et al., “Dual-loop online intelligent programming for driver-oriented predict energy management of plug-in hybrid electric vehicles,” Applied Energy, 253, p. 113617, 2019, doi: 10.1016/j.apenergy.2019.113617.
  • H. Zhou, F. Wei, and L. Sun, “Development Status of Electric Vehicles,” JAEV, 2 (1), pp. 531–534, 2004, doi: 10.4130/jaev.2.531.
  • S. Lu, K. A. Corzine, and M. Ferdowsi, “A New Battery/Ultracapacitor Energy Storage System Design and Its Motor Drive Integration for Hybrid Electric Vehicles,” IEEE Trans. Veh. Technol., 56 (4), pp. 1516–1523, 2007, doi: 10.1109/TVT.2007.896971.
  • H. Yu, R. Lu, T. Wang, and C. Zhu, “Battery/ultra-capacitor Hybrid Energy Storage System Used in HEV,” JAEV, 8 (1), pp. 1351–1356, 2010, doi: 10.4130/jaev.8.1351.
  • K. Gokce and A. Ozdemir, “A rule based power split strategy for battery/ultracapacitor energy storage systems in hybrid electric vehicles,” Int. J. Electrochem. Sci, 11 (2), 1228–1246, 2016.
  • E. Schaltz, A. Khaligh, and P. O. Rasmussen, “Influence of battery/ultracapacitor energy-storage sizing on battery lifetime in a fuel cell hybrid electric vehicle,” IEEE Trans. Veh. Technol., 58, (8), 3882–3891, 2009, doi: 10.1109/TVT.2009.2027909.
  • Q. Zhang, W. Deng, S. Zhang, and J. Wu, “a rule based energy management system of experimental battery/supercapacitor hybrid energy storage system for electric vehicles,” Journal of Control Science and Engineering, 1–17, 2016, doi: 10.1155/2016/6828269.
  • R. Carter, A. Cruden, and P. J. Hall, “Optimizing for efficiency or battery life in a battery/supercapacitor electric vehicle,” IEEE Trans. Veh. Technol., 61 (4), 1526–1533, 2012, doi: 10.1109/TVT.2012.2188551.
  • M. Pipicelli, B. Sessa, F. De Nola, A. Gimelli, and G. Di Blasio, “Assessment of battery–supercapacitor topologies of an electric vehicle under real driving conditions,” Vehicles, 5 (2), 424–445, 2023, doi: 10.3390/vehicles5020024.
  • J. P. Trovão and C. H. Antunes, “A comparative analysis of meta-heuristic methods for power management of a dual energy storage system for electric vehicles,” Energy Conversion and Management, 95, 281–296, 2015, doi: 10.1016/j.en conman.2015.02.030.
  • K. Ye, P. Li, and H. Li, “Optimization of Hybrid Energy Storage System Control Strategy for Pure Electric Vehicle Based on Typical Driving Cycle,” Mathematical Problems in Engineering, 1–12, 2020, doi: 10.1155/2020/1365195.
  • M. Ghasemi, M. Zare, A. Zahedi, P. Trojovský, L. Abualigah, and E. Trojovská, “Optimization based on performance of lungs in body: Lungs performance-based optimization (LPO),” Computer Methods in Applied Mechanics and Engineering, 419, 116582, 2024, doi: 10.1016/j.cma.2023.116582.
  • R. Wang and S. M. Lukic, “Dynamic programming technique in hybrid electric vehicle optimization,” in 2012 IEEE International Electric Vehicle Conference, Greenville, SC, USA: IEEE, pp. 1–8, 2012. doi:10.1 109/IEVC.2012.6183284.
There are 23 citations in total.

Details

Primary Language Turkish
Subjects Electrical Machines and Drives
Journal Section Research Articles
Authors

Aydın Boyar 0000-0002-3680-855X

Yasin Kabalcı 0000-0003-1240-817X

Ersan Kabalcı 0000-0002-7964-9368

Early Pub Date June 25, 2024
Publication Date July 15, 2024
Submission Date March 9, 2024
Acceptance Date May 30, 2024
Published in Issue Year 2024 Volume: 13 Issue: 3

Cite

APA Boyar, A., Kabalcı, Y., & Kabalcı, E. (2024). Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(3), 948-955. https://doi.org/10.28948/ngumuh.1449613
AMA Boyar A, Kabalcı Y, Kabalcı E. Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi. NOHU J. Eng. Sci. July 2024;13(3):948-955. doi:10.28948/ngumuh.1449613
Chicago Boyar, Aydın, Yasin Kabalcı, and Ersan Kabalcı. “Elektrikli araçların Hibrit Enerji Depolama Sistemleri için akciğer performansına Dayalı Optimizasyon Algoritması Temelli kontrolör geliştirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13, no. 3 (July 2024): 948-55. https://doi.org/10.28948/ngumuh.1449613.
EndNote Boyar A, Kabalcı Y, Kabalcı E (July 1, 2024) Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13 3 948–955.
IEEE A. Boyar, Y. Kabalcı, and E. Kabalcı, “Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi”, NOHU J. Eng. Sci., vol. 13, no. 3, pp. 948–955, 2024, doi: 10.28948/ngumuh.1449613.
ISNAD Boyar, Aydın et al. “Elektrikli araçların Hibrit Enerji Depolama Sistemleri için akciğer performansına Dayalı Optimizasyon Algoritması Temelli kontrolör geliştirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13/3 (July 2024), 948-955. https://doi.org/10.28948/ngumuh.1449613.
JAMA Boyar A, Kabalcı Y, Kabalcı E. Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi. NOHU J. Eng. Sci. 2024;13:948–955.
MLA Boyar, Aydın et al. “Elektrikli araçların Hibrit Enerji Depolama Sistemleri için akciğer performansına Dayalı Optimizasyon Algoritması Temelli kontrolör geliştirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, vol. 13, no. 3, 2024, pp. 948-55, doi:10.28948/ngumuh.1449613.
Vancouver Boyar A, Kabalcı Y, Kabalcı E. Elektrikli araçların hibrit enerji depolama sistemleri için akciğer performansına dayalı optimizasyon algoritması temelli kontrolör geliştirilmesi. NOHU J. Eng. Sci. 2024;13(3):948-55.

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