Study On Modeling And Energy Management Strategy For Parallel Heavy-duty Hybrid Electric Vehicle

In order to solve the increasingly acute energy shortage and environmental pollution problems,hybrid electric vehicles that combine the advantages of traditional internal combustion engine vehicles and electric vehicles have gradually become the focus of attention.In the development of hybrid electric vehicles,how to build a mathematical model of the vehicle and design a reasonable energy management strategy is very important.To ensure the vehicle dynamic performance and fuel economy improvement,this thesis develops the modeling and energy management strategies for the hybrid power system,with taking the self-designed hybrid electric vehicle transmission structure as the research object.The following is the main content of this thesis.First,this thesis establishes the simulation model of hybrid electric vehicle on MATLAB/Simulink.Based on the hybrid electric vehicle equipped with a new type of power coupling device and analysis of structural characteristics,a simulation model of hybrid electric vehicle's power system is built by using the experimental modeling method.The model of hybrid electric vehicles includes the vehicle models,engine models,motor models,battery models,automatic transmission models,and driver models,etc.Secondly,an energy management strategy based on logic threshold algorithm is designed in this thesis.In the logic threshold energy management strategy,the engine torque and its limit curves,battery state of charge and its upper and lower limits,vehicle demand torque are selected as logic threshold parameters.Based on the division of the optimal working range of the engine and the battery and the analysis of the working mode of the hybrid electric vehicle,the energy distribution rules for each working mode have been formulated.The controller model according to logic threshold energy management strategy has been built in Stateflow.The simulation experiments of hybrid electric vehicle are carried out based on the vehicle components models and the designed controller model.The simulation results turns out that the energy management strategy designed based onthe new hybrid transmission structure is effective.Then,an energy management strategy based on dynamic programming algorithm is designed in this thesis.Multi-stage decision-making problem of energy distribution in hybrid electric vehicles is transformed into multiple single-stage decision problems with the least amount of fuel consumption under certain constraints.The energy management strategy using dynamic programming algorithms is set up in this thesis.The optimal torque distribution strategy is found by using the dynamic programming algorithm.The objective function of the system is established in view of the vehicle fuel consumption function and battery state of charge penalty function.The optimal theoretical fuel economy and system optimal control law of the vehicle are obtained by using the dynamic programming algorithm to solve the equations.Finally,an energy management strategy based on fuzzy logic algorithm is designed,and the energy of the system is rationally allocated using double fuzzy controllers.The required torque of the vehicle,the state of charge of the battery,and the rate of throttle opening,the value of throttle opening are determined as the input variables of the double fuzzy controller respectively.The output torque coefficient of the engine is obtained by modifying the output of the fuzzy controller using a proportional factor.The double fuzzy controller is built in fuzzy toolbox according to the energy management strategies of logic thresholds and dynamic programming algorithm.Through the comparison and analysis of the simulation results of three different energy management strategies designed in this paper,it shows that the energy management strategy based on fuzzy logic algorithm designed in this paper can effectively reduce the fuel consumption of hybrid electric vehicles,and at the same time,the stability of the nuclear power state is guaranteed in the simulation process.