Abstract:

Based on the complex structure of electric hybrid car and uncertainty in driving force structure of electric hybrid car, different strategies have been presented for optimal management of energy based on smart methods. In this study by the decision making nature of fuzz logic, a movement map for Parallel Hybrid Electric Vehicle (PHEV) is made based on the required path. In a parallel hybrid car, recharging control of battery and auxiliary torque of electric engine are used as the key points of movement. Based on the disadvantages of pure electric car, to increase the life of battery and its easy use, we need a movement strategy balancing the battery charge for a movement path. If the battery is charged at no load by the combustion engine, NOx emission is increased and the battery charge is not good and adequate for HEV performance under no-load condition by the energy retrieval power and combustion engine. For a movement structure, it is hard to define the conversion point between the motor performance and generator performance exactly. By a drive strategy based on crisp methods, the battery charge is sensitive to the moving samples of driver, path condition and load conditions. Using fuzzy control strategy to control varied non-linear systems is very suitable and it is robust against the changes of components of sub-systems and inexact measurements. New York City Cycle (NYCC) is considered to perform simulation. As shown in paper, the fuzzy control strategy can keep the charge stage of batteries at good range.