Control of pre and post transmission parallel hybrid vehicles with fuzzy logic method and comparison with other power systems

Yıl 2020, , 2269 - 2286, 21.07.2020

Tolga Kocakulak , Hamit Solmaz

https://doi.org/10.17341/gazimmfd.709101

Cited By: 10

Öz

In this study, modeling of pre-transmission parallel hybrid, post- transmission parallel hybrid, serial hybrid and conventional vehicle structures in Matlab / SIMULINK environment. Average fuel consumption values for different driving cycles were obtained on the vehicle models created and compared. The power, gear range and regenerative brake control of the parallel hybrid vehicle were provided by the control algorithm developed by the fuzzy logic method. Transfer functions representing the vehicle's power system have been created for all vehicle structures. Rolling, acceleration and aerodynamic forces acting on the vehicle are included in the model. The torque / speed and specific fuel consumption map of the 1.8 liter “ZR-FXE” gasoline engine was used in the internal combustion engine model. In the electric motor model, the torque / speed and efficiency map of the “Ashwoods / Elmo-D576” brand electric motor was used. A 7-speed DCT transmission is used in all vehicle structures. The vehicle uses a 5 kWh energy capacity, lium ion battery pack. The battery model was created with the equivalent circuit method Rint method. It was determined that the lowest average fuel consumption values for US06, FTP75, NEDC, EUDC driving cycles were obtained as 5.73, 4, 3.96 and 4.18 L / 100 km with the pre-transmission parallel hybrid vehicle structure controlled by fuzzy logic method. In the ECE15 driving cycle, it was determined that the serial hybrid vehicle structure has the lowest average fuel consumption with a value of 3.62 L / 100 km. In the ECE15 driving cycle, where regenerative braking use is most effective, it has been observed that the series, pre-transmission parallel and post transmission parallel hybrid vehicle structures save 14.22%, 11.5% and 9.95% respectively.

Anahtar Kelimeler

Parallel hybrid vehicle, pre and post transmission, power system, serial hybrid vehicle, fuzzy logic control strategy

Ön ve son iletimli paralel hibrit araçların bulanık mantık yöntemi ile kontrolü ve diğer güç sistemleri ile karşılaştırılması

Öz

Bu çalışmada, ön iletimli paralel hibrit, son iletimli paralel hibrit, seri hibrit ve konvansiyonel araç yapılarının Matlab/SIMULINK ortamında modellemesi yapılmıştır. Oluşturulan araç modelleri üzerinde farklı sürüş çevrimleri için ortalama yakıt tüketim değerleri elde edilerek karşılaştırması yapılmıştır. Paralel hibrit aracın güç, vites kademe ve rejeneratif fren kontrolü bulanık mantık yöntemi ile geliştirilen kontrol algoritması ile sağlanmıştır. Tüm araç yapıları için, aracın güç sistemini temsil eden transfer fonksiyonları oluşturulmuştur. Araca etki eden yuvarlanma, ivme ve aerodinamik kuvvetleri modele dahil edilmiştir. İçten yanmalı motor modelinde 1,8 litre “ZR-FXE” benzinli motora ait tork/devir ve özgül yakıt tüketimi haritası kullanılmıştır. Elektrik motor modelinde “Ashwoods/Elmo-D576” marka elektrik motorunun tork/devir ve verim haritasından faydalanılmıştır. Bütün araç yapılarında 7 ileri DCT şanzıman kullanılmıştır. Araçta 5 kWh enerji kapasiteli, liyum iyon batarya paketi kullanılmıştır. Eşdeğer devre yöntemi Rint metodu ile batarya modeli oluşturulmuştur. US06, FTP75, NEDC, EUDC sürüş çevrimleri için en düşük ortalama yakıt tüketimi değerlerinin bulanık mantık yöntemi ile kontrol edilen ön iletimli paralel hibrit araç yapısıyla 5,73, 4, 3,96 ve 4,18 L/100 km olarak elde edildiği belirlenmiştir. ECE15 sürüş çevriminde 3,62 L/100 km değeri ile seri hibrit araç yapısının en düşük ortalama yakıt tüketimine sahip olduğu tespit edilmiştir. Rejeneratif fren kullanımının en etkili olduğu ECE15 sürüş çevriminde, seri, ön iletimli paralel ve son iletimli paralel hibrit araç yapılarında sırasıyla % 14,22, % 11,5 ve % 9,95 oranında tasarruf sağladığı görülmüştür.

Anahtar Kelimeler

Paralel hibrit araç, ön ve son iletim, seri hibrit, bulanık mantık kontrol stratejisi, güç sistemi modeli

Kaynakça

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