Research On Two-Speed AMT Shifting Strategy Of Pure Electric Commercial Vehicles Based On Driving Intention And Working Condition Recognition

Facing the challenges of energy crisis and environmental problems,various countries are actively supporting and promoting new energy vehicles.Pure electric vehicles,with their simple structure,low energy consumption,convenient production and other characteristics,have attracted the attention of governments.In the context of the rapid development of logistics and transportation industry,pure electric commercial vehicles equipped with automatic transmission have won the favor of consumers.However,the performance of commercial vehicles is closely related to the shift strategy of automatic transmission.How to formulate shift strategy to improve the comprehensive performance of vehicles has become the focus of current research.This paper takes pure electric commercial vehicle as the research object and conducts a comprehensive shift strategy based on driving intention and working condition recognition.The main research contents are as follows:(1)Based on the basic parameters and performance indicators of pure electric commercial vehicle,a longitudinal dynamics model of vehicle is established.The model parameters of each component of vehicle power transmission system are determined by parameter matching calculation.The two gear ratios of transmission are optimized by using particle swarm optimization algorithm.(2)The influence of driving intention change and working condition change on vehicle performance is analyzed.Fuzzy control algorithm is used to identify driving intention,and the identification simulation results are analyzed to verify the accuracy of driving intention identification.Extended Kalman filter algorithm(EKF)is used to identify vehicle mass under working condition.Based on mass identification,EKF combined with dynamics method is used to identify road slope,and the identification results are simulated and analyzed to prove that EKF algorithm can accurately identify vehicle mass and road slope with small fluctuation error.(3)The shift factors are analyzed,and the traditional shift rules based on power performance and economy performance are formulated and used as the evaluation criteria for the shift rule modification.The gear operation corresponding to each different driving intention is analyzed,and the gear decision based on driving intention recognition is formulated.The correctness of gear decision is verified by selecting simulation conditions.According to the different vehicle mass and road slope change,the uphill shift strategy and downhill shift strategy are formulated.The accuracy of shift decision is proved by setting simulation conditions.(4)A pure electric commercial vehicle model and a shift control strategy model are established by using a joint simulation mode.Based on the working condition priority principle,a comprehensive shift strategy based on driving intention and working condition recognition is formulated.On this basis,a coupling working condition is designed and formulated.A coupling working condition simulation task is set up,and the effectiveness of the comprehensive shift strategy is verified by comparing and analyzing with the traditional power performance and economy performance shift rules.