Dual-mode hybrid vehicle neurocontrol

Now most of the hybrid vehicle control strategies are aiming at the optimal fuel economy and driving cycle must be pre-known. Changing driving condition will influence the optimal results greatly. Therefore, a neural network controller (NNC) is proposed, which can improve fuel efficiency and the battery´s SOC of a dual-mode hybrid vehicle in most driving conditions. The controller is trained through genetic algorithm to optimize the weights of the network. By using different driving cycle in the NNC training, this controller can be well functioned in variety conditions. The proposed NNC is testified through the hardware-in-loop simulation.