Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy


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Kocakulak T., Solmaz H., Sahin F.

JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2021 (ESCI) identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Doi Number: 10.2339/politeknik.932448
  • Journal Name: JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI
  • Journal Indexes: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Keywords: Fuzzy logic, energy saving, rule-based control strategy, modeling, parallel hybrid, ENERGY MANAGEMENT, ELECTRIC VEHICLES, TORQUE
  • Gazi University Affiliated: Yes

Abstract

In this study, a model of a pre-transmission parallel hybrid vehicle was created in MATLAB/Simulink environment. A torque control strategy has been developed for the hybrid vehicle on the created model. The hybrid vehicle's torque control is provided by fuzzy logic and conventional rule-based control strategies. The control strategies of the hybrid vehicle have been developed based on four input parameters: accelerator and brake pedal position, battery state of charge and the operating mode of the electric motor. The regenerative braking system of the pre-transmission parallel hybrid vehicle has been provided with a fuzzy logic control strategy in both vehicle structures. In the fuzzy logic torque split controller, a control algorithm has been created in which the safety, performance and fuel consumption values of the vehicle meet at the optimum point. Under different driving cycle conditions, the effects of control strategies on engine operating points have been examined and average fuel consumption values have been obtained. In the control of the parallel hybrid vehicle with fuzzy logic method, it has been obtained that it provides 12.87%, 6.62%, 2.27% and 6.23% fuel savings under FTP-75, NEDC, EUDC and ECE-15 driving cycle conditions, respectively. It has been observed that the vehicle cannot provide sufficient performance in US06 driving cycle conditions with the use of conventional rule-based control strategy.