the Design of artificial neural network based power split controller for hybrid electric vehicle
In this paper the work represent the design flow of artificial neural network (ANN) for the parallel hybrid electric vehicle using the dynamic programming strategy, for the better fuel economy and power for the real time driving condition. In this paper the artificial neural network for the parallel hybrid electric vehicle is first trained from the input/output data generated by a dynamic programming. The power spilt between electric motor (EM) and internal combustion engine (ICE) an is prescribe by using this artificial neural network controller. One input layer is used and one output layer is used with 2 hidden layers. For the training of the data the numpy-library is used and matlab-simulink is used for the implementation. The trained data is used. The data is tasted on three driving cycle named NEDC, US06 and FTP-75 for both the thermal and hybrid vehicles.
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