Research On Control Strategy Of Hybrid Electric Vehicle Considering Different Road Spectrum And Driving Style

In recent years,with the introduction of China's National Sixth Emission Regulations,various automobile companies are facing severe challenges.As a product of the transition from traditional fuel vehicles to pure electric vehicles,hybrid vehicles have no geographical scope under the existing technical conditions.And the advantages of environmental temperature impact has become a hot research topic,and the quality of its energy management strategy directly affects vehicle emissions and fuel consumption.The formulation of vehicle control strategy has become an indispensable part.The current control strategy mainly focuses on the identification of the driving road spectrum without considering the driver's driving style and intention to influence the whole vehicle.The spectrum and the driver's driving style and the control strategy of the intent recognition are of great significance.The research conte nt of this paper is as follows:Firstly,the principle of particle swarm optimization algorithm is expounded and improved.Four typical functions are selected to use PSO algorithm,AFSA algorithm and MPSO algorithm for optimization calculation.The results show that the MPSO algorithm has excellent performance and the other two algorithms are improved.Then the MP-means algorithm is optimized by MPSO algorithm and compared with K-means algorithm.The results show that the improved clustering algorithm is better.The self-driving method was used to obtain the passenger vehicle road spectrum data of Jinan City.The 19 characteristic parameters were used to describe the data.The principal component analysis method was used to reduce the data.Then the K-MPSO clustering algorithm was used to cluster the road spectrum segments into The third category,the final synthesis of typical passenger car road spectrum in Jinan.In analyzing the operating conditions of the car and the driver's influence on the fuel economy of the vehicle,the driver's driving style is divided into aggressive,ordinary and calm;for the emergency of driving,the acceleration intention is divided into slow acceleration and normal acceleration.Emergency acceleration,which is divided into slow braking,normal braking and emergency braking.Based on AVL Cruise software,a parallel hybrid passenger car model was built.Then,a rule-based control strategy was established and simulated under the NEDC,Hangzhou and Jinan road spectra,and the threshold parameters of Jinan road spectrum were established.On this basis,the driver driving style and intention identification control strategy based on Jinan City was established and compared with the rule-based control strategy.The result showed that fuel economy improved by 16.79%.