چكيده به لاتين
Recently, the use of clean and renewable energies has been rapidly increasing. For this reason, vehicle research is also focused on using clean and renewable fuels to reduce emissions and global warming. In hybrid vehicles, two or more energy sources are used simultaneously to provide the power and traction of cars. For example, a hybrid vehicle can include a battery, supercapacitor, and fuel cells as a power supply. As a result, there are challenges in using energy sources, such as designing an energy management system, implementing a stable control system, the correctness of the dynamic equations, and dealing with noise and ripple. First, in this thesis, the dynamic equations of the hybrid system, including fuel cell, battery, and supercapacitor, will be reviewed. Then, to supply the requested power of the vehicle, an intelligent algorithm based on the type-2 fuzzy algorithm is used to effectively divide the requested power between the fuel cell, battery, and supercapacitor energy sources. Also, an observer-based adaptive fuzzy control method is designed for the hybrid vehicle so that it can provide the desired power of the energy management system while dealing with noise and uncertainties. The methods employed in this thesis are carried out to optimally supply the requested power, reduce costs, and increase the lifespan of the vehicle's hybrid system. Finally, to show the effectiveness of the proposed method, a hybrid tramway model is used in the simulations. The results of the simulation illustrate the proper performance of the tram. The requested power is well-supplied, the tram is stable and well-controlled, and the output voltage of the hybrid system is adjusted correctly.
