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

Aydın Boyar , Yasin Kabalcı , Ersan Kabalcı

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.

Keywords

Electric vehicle, Hybrid energy storage systems, Metaheuristic algorithm, Optimization

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

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.

Keywords

Elektrikli araç, Hibrit enerji depolama sistemi, Meta sezgisel algoritma, Optimizasyon

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