Neural network and efficiency-based control for dual-mode hybrid electric vehicles

Now hybrid electric vehicle (HEV) control strategies are mainly aiming at the optimal fuel economy. The performance of most control strategies depends on the driving cycle pre-known. Changing driving condition will influence the optimal results greatly. Therefore, a neural network controller (NNC) is proposed for a dual-mode hybrid vehicle, which can improve fuel efficiency and maintain battery's state of charge (SOC) in most driving conditions. The NNC combined with an efficiency-based strategy can further reducing vehicle fuel consumption by improving the transmission efficiency. The proposed NNC is testified through the hardware-in-the-loop simulation. The test results show that, the control strategy combined neural network and efficiency-based strategy can reduce vehicle fuel consumption and control the battery SOC in a reasonable range. The control strategy has good prospects in the controller design for dual-mode HEVs.