Research On Adaptive Equivalent Fuel Consumption Minimum Strategy For Hybrid Electric Vehicle Based On Speed Forecast

Against the background of energy shortages and environmental pollution,the development of the automobile industry tends to energy conservation and emissions reduction,and various types of new energy vehicles have emerged.Among them,plug-in hybrid electric vehicles(PHEV)have been widely studied because it takes into account the pollution-free of pure electric vehicles(EV)and the long driving range of traditional fuel vehicles.How to distribute the two power sources reasonably is the key to improving overall fuel economy.This paper takes a plug-in hybrid electric vehicle as the research object,and aims to improve the fuel economy under the low battery maintenance state.The future vehicle speed prediction method and the equivalent fuel consumption minimum strategy are combined to formulate an energy management strategy.The specific research content is as follows:(1)According to the configuration characteristics of a plug-in hybrid electric vehicle,the backward simulation software ADVISOR is used to build the vehicle component model in the MATLAB/Simulink environment,and the rule-based motor-assisted energy management strategy is established.The simulation verified that the built vehicle model can meet the requirements of power and economy.(2)Using neural network theory,a vehicle speed prediction model based on RBF neural network was established,and the spread parameters and the duration of historical speed duration under single-step prediction and multi-step prediction of the model were studied,and the best spread parameters and the duration of historical vehicle speed determined.Then,the prediction sequence of vehicle speed is decomposed by wavelet packet transform,and the prediction results of four RBF-NN predictors are reconstructed to achieve the prediction of future vehicle speed,which improves the accuracy of vehicle speed prediction to a certain extent.(3)According to the Pontryagin’s minimum principle(PMP),an energy management strategy based on the equivalent fuel consumption minimum strategy(ECMS)was established,and the influence of the constant equivalent factor on the change of battery SOC was studied.In view of the adaptability of the equivalent factor in working conditions,the self-adaptive adjustment method of the equivalent factor(EF)was studied,and the ECMS strategy based on the feedback regulation of SOC error is established.In order to solve the problem of regulation lag in equivalent factor regulation with constant period,a method of adjusting equivalent factor regulation period based on SOC error feedback was proposed,and an adaptive ECMS strategy with variable regulation period based on SOC feedback was established.(4)The vehicle speed in the adjustment period is predicted by the RBF-NN speed prediction model based on wavelet packet,and then the optimal equivalent factor satisfying the battery SOC constraint is calculated by using the ECMS,which is used as the equivalent factor in the actual driving.The simulation of the comprehensive cycle condition verifies that the adaptive-ECMS based on speed prediction established in this paper improves the power maintenance and fuel economy compared with the motor assisted energy management strategy.