Study On Parameter Matching And Optimization Simulation Of Double Speed Motor For Electric Vehicle

From the perspective of environmental protection,economy and technology,pure electric truck as a clean,efficient and intelligent commercial vehicle,can effectively solve the increasingly serious energy problems and environmental problems,it is also an ideal alternative to fuel cars.Studies have shown that pure electric truck powertrain parameters reasonable matching and optimization design is crucial promotion for automobile economy and power performance,especially pure electric vehicle battery problems have not been fundamentally solved,which not only can give full play to the pure electric truck various performance,but also can promote the development of the auto industry.This thesis relies on the Sichuan Provincial Science and Technology Department to support the project "pure electric truck integrated key technology research and demonstration(five high-end)"(project number: 2016GZ0020).Pure electric truck is the research object in this thesis.First of all,through the analysis of the advantages and disadvantages,which exist in today’s power system structure of pure electric vehicle and different layout forms,and the various factors which influence the layout,this thesis proposes a dynamic system general layout plan for the research object,and analyzes key components of the dynamic system including batteries and drive motor.Secondly,above parts characteristics analysis,formulate dynamic system parameters preliminary matching process and preliminary match a double-base speed motor.Match initial values of rated parameters for high base speed and low base speed based on the matching degree between the high frequency region and the high efficiency region.Match the peak parameters for high base speed and low base speed by the base speed ratio matching method.Thirdly establish a new evaluation function through a weighted manner by taking the driving distance and energy consumption rate as dual objective functions.According to mileage maximization target,preliminary matching parts and vehicle constraints,use particle swarm optimization(PSO algorithm),which has the advantages of simple implementation,fast convergence and less required parameters,to optimize parameters.For the double goals that longest driving distance and lowest energy consumption,determine the optimization variables and the optimization constraint,finding the best parameter combination,to achieve the optimization of power performance and fuel economy.Finally,according to the contact between the parts and components,establish the simulation model in the ADVISOR,comparing and analyzing the optimized hundred kilometers travel distance and energy consumption with preliminary matching parameters,to validate the rationality and accuracy of the optimization scheme.This research has theoretical and practical significance in the field of parameter matching and optimization of double speed motor for electric vehicle.