Energy Management Strategy Considering Speed Feature Recognition and Cabin Noise Constraint for Hybrid Commercial Vehicles

摘要

The fuel economy and ride comfort of range-extender electric vehicles are closely related to the adopted energy management strategy (EMS). The appropriate EMS with noise constraints can not only effectively reduce fuel consumption, but improve ride comfort during vehicle travel. To this end, an EMS was proposed in this paper in which an adaptive equivalent consumption minimization method was developed considering the noise level in the driving cabin based on vehicle speed feature recognition so that the vehicle fuel economy and ride comfort can be optimized simultaneously through a calibratable cost function. The linear state of charge reference trajectory based on the route information, which could be obtained by a mileage-indication knob equipped in the cockpit, was employed to determine the start-stop of the range-extender. The proposed strategy was verified on the road in a light-duty range-extender electric van. The results were compared with those obtained from the conventional equivalent consumption minimization strategy and a dynamic equivalent consumption minimization strategy. The experimental results indicated that the proposed strategy could reduce the vehicle fuel consumption by 3.28 % and 1.40 %, respectively, on an urban-suburban integrated route. Moreover, the ride comfort indicated by the noise level in the driving cabin was better as well.