Design And Optimiazaion Of Double-salient Flux Memory Motor Based On Dynamic Magnetic Network Model

With the increasing critical world energy crisis and environmental pollution issues,electric vehicles(EVs),which exhibit high efficiency and zero emissions,have gradually replaced traditional fuel vehicles and become a new trend of the development of the automotive industry.As the crucial component of electric vehicles,the drive system faces many challenges such as different operating environments and complex working conditions.Flux control memory motor(FCMM)is a new type of permanent magnet motor that adopts low coercivity permanent magnet as magnetic source.It possesses the ability to regulate the air gap magnetic field online.During the operation,FCMM not only inherits the advantage of high power density and high efficiency from permanent magnet motor,but also has excellent driving characteristics with flexible mode and wide speed range.Therefore,there is broad application prospect for FCMM in the field of electric drive for vehicles.This paper proposes a multi-mode optimization design method based on variable magnetic network for FCMM,and takes a double salient flux memory motor(DSFM)as the research example to verify the design method,where the special working principle,multi-mode operation and assessment of PM magnetization state are considered specially.In this regard,the accurate modeling of the magnetic network,the multi-objective optimization and the uncertainty analysis will systematically carry out in the following.Overall,the main research works of this paper can be summarized as following aspects:(1)The background and significance of the subject research are introduced systematically,the current research status of memory motors is presented,and the existing multi-objective design optimization methods are discussed.(2)A novel DSFM motor with simple topology is proposed.The motor topology and operating principles are presented.And the motor dimensional parameters,permanent magnets and windings are designed based on the corresponidng design experience of traditional double salient pole motors.(3)The dynamic magnetic network of DSFM motor is established,where the online magnetic regulation characteristic is fully considered and the relationship between core field distribution and PM magnetization state is explored.Finally,the prediction results of the model are verified by the finite element method(FEA).(4)Based on the dynamic magnetic network,a multi-objective optimization framework is constructed to optimize DSFM motor.Two operation modes of DSFM motors are defined,and the key structural parameters are optimized by setting the average output torque,torque ripple in flux-strengthened mode,and iron loss in fluxweakening mode as design objectives.(5)A robust optimization method based on the dynamic magnetic network model is proposed,where the influence of the unpredictable parameters fluctuation on the motor performance is considered.In the algorithm,the concept of the primary processing success rate is defined,and it is added to the multi-objective optimization framework as a restriction.Finally,the optimization results are compared with deterministic optimization to determine the final prototyped design.(6)The prototype is processed and the test platform is established.The no load back electromotive force(Back-EMF)of different operation modes and dynamic characteristics of the motor are measured to verified optimization results.