چكيده به لاتين
The gradual reduction in oil reserves and increasing of energy consumption in recent decades and the problem of air pollution have led the automotive industry to find a solution to reduce transportation dependence on fossil fuels. One of the technologies that make a significant improvement in the overall energy conversion efficiency of the Powertrain system is the hybridization of conventional vehicles. In a hybrid car, there are two sources of power to supply the required power of vehicle, including electric and combustion engine. The control strategy determines the share of electric and combustion engine to supply the required power of the vehicle. In this study, a fuzzy logic control strategy is used to reduce fuel consumption and increase vehicle efficiency. This type of controller is efficient for certain operating conditions. In this study, the performance of the designed fuzzy logic control strategy for a plug-in hybrid electric vehicle (PHEV) is investigated by means of hardware-in-the-loop (HIL) testing using model-based design (MBD) method. To design and test the control strategy, the MBD method has been used. Using the MBD method, the problems related to the coding of the control algorithm and the compiler can be completely solved and the project can be completed in a short time. HIL testing is one of the model-based design steps; It can be used to check memory and speed problems, input and output software, real-time execution scheduling. Also, with the design of a software filter, the amount of noise due to the increase of electronic board sampling frequency and environmental disturbances is significantly reduced and the results of HIL and software simulation are close to each other. The vehicle model used in this study is a PHEV model based the backward-and-forward model in the Advisor software, which is prepared to perform HIL testing. The electronic board used, is an Arduino board, which has sufficient capabilities according to the desired requirements.
