Research On Mode Switching Sequence Control Of Planetary Gear Multi-Mode Hybrid Power System

In recent years,the new energy vehicle industry has developed vigorously,the hybrid vehicle market has achieved great progress,and the demand for technology upgrades has become increasingly urgent.The planetary multi-mode hybrid vehicle has the advantages of precise division of working modes and efficient power coupling.The planetary electromechanical coupling device uses the node connection relationship of the planetary gear train and the clutch state switching to divide many working modes,and reasonably allocates the working modes according to different operating conditions,so that the power components of the hybrid system work at the best time to achieve high efficiency and energy saving.So it is an important issue for the planetary hybrid power system to solve the optimal match between the working mode and the road condition.This paper takes the complex mode switching problem of planetary array electromechanical coupling system as the research object,based on the global optimization method considering the mode switching rules,and relying on the National Natural Science Foundation of China project “Planetary array multi-mode hybrid power system molecular topology synthesis and synergy Optimal Methodology Study”,the following studies were carried out:(1)Global power flow optimization of planetary row hybrid power system based on dynamic programming(DP).In this thesis,the single-row multi-mode hybrid system configuration is taken as the research object.Aiming at the complex configuration and various modes of the planetary row hybrid system,the hybrid vehicle model selfconstruction method is introduced to establish the state space expression of the system in each working mode,supplemented by the construction of vehicle dynamics and mathematical models of each power source component of the system,which provides a basis for the calculation and expression of system power flow in the subsequent DP algorithm optimization process.And based on the main-sub-mode switching rules,the mode switching penalty is introduced,and the objective function model of the DP algorithm of the planetary array hybrid electric vehicle is built,and the power flow optimization algorithm of the planetary array multi-mode hybrid system considering the mode switching rules is established.(2)Mode switching sequence map extraction based on learning vector quantization network clustering(LVQ).Taking the urban cycle working condition(UDDS)and the expressway circulating working condition(HWFET)as the global optimization road test parameters,respectively use the DP algorithm for global optimization for comparative analysis,and then select the UDDS & HWFET composite working condition with wider coverage as the system working mode switching sequence Distribution map extraction basis.Based on the system operating point distribution diagram under compound working conditions,using the LVQ neural network clustering method,the distribution data of the operating mode points is used as the input quantity,and the original data type of the input quantity is used as the category mark to drive the power demand state of the system under the main mode The spatial clustering is divided into 4 driving sub-mode regions,and the mode switching sequence diagram in the driving main mode is obtained.Through clustering training,the initial five main sub-modes of the single-row multi-mode hybrid system are simplified to the driving main sub-mode,auxiliary braking main sub-mode,and parking charging mode that meet the urban and high-speed road conditions,which greatly simplifies the planetary row hybrid system mode switching rules.(3)Simulation of mode switching sequence control of planetary row hybrid electric vehicle based on Simulink & AMESim co-simulation environment.Taking the mode switching sequence diagram of single-row multi-mode hybrid power system as the energy management rule,the equivalent fuel consumption minimum(ECMS)real-time optimization control algorithm is introduced,the DP-ECMS real-time energy management strategy considering mode switching rules is established,and the idea of discrete ECMS(D-ECMS)is introduced to improve the computational efficiency of realtime energy management optimization algorithm and meet the real-time energy management requirements of planetary row hybrid system.Build a vehicle controller model based on Simulink software and a vehicle power flow model based on AMESim software,and use DP-ECMS as a real-time energy management strategy.The cosimulation results prove that the comprehensive energy consumption result and the DP global optimization result of the single-row multi-mode hybrid electric vehicle using the DP-ECMS control strategy under the UDDS & HWFET composite working condition increase by 5.53%,which is in line with the expected goal.The comprehensive energy consumption under the WLTC operating condition has a slight increase compared with the compound operating condition,which proves that the matching of the operating condition and the mode switching sequence can maximize the energy consumption potential of the hybrid power system.