网联混合动力汽车能量优化控制

Energy management strategy is one of the core technologies of hybrid electric vehicles, which determines the fuel economy and emission performance of the vehicle. Aiming at the problem that the existing energy management strategies of hybrid electric vehicles are all developed based on the fixed operating conditions without considering the actual road driving conditions, proposes a hierarchical energy control method for hybrid electric vehicles in the connected environment based on the road trcoffic in formation and surrounding vehicle in formation obtained by intelligent transportation system (ITS) and dedicated short range communication (DSRC) technology. Road traffic information and model predictive control algorithm are utilized to predict the optimal velocity of vehicle in the upper controller. The lower controller is designed to follow the optimal velocity by using target vehicle velocity information obtained in the upper controller, and uses the fuzzy neural network control algorithm to optimize the torque distribution between the engine and the motor to reduce fuel consumption. The simulation results show that, compared with the traditional energy management strategy, the proposed method can avoid the vehicle stopping at the red light effectively, so that the fuel consumption rate of the vehicle is reduced by 34.88%, and the emission of HC, CO, and NO_x are reduced by 10.59%, 66.19%, and 1.05%, respectively, which improves the fuel economy and emission performance of hybrid electric vehicles.