Multiple Models Switching Control Based On PMSM Of Pure Electronic Vehicles

Because of the energy conservation and environment protection characters of the pure electric vehicles,the trend of replacing the traditional vehicles has already been emerged.How-ever,though the varieties of pure electric cars are numerous,the core techniques—such as motor control,there still exists many shortages because of its deficiency of the development experi-ence comparing with the traditional vehicles.This thesis mainly concerns about the topic of PMSM controlling with the technique of mutiple models adaptive control.Therefore,the speed governing performance of PMSM has been improved in the perturbated situation.This thesis focuses on that how to govern the speed with high accuracy,especially the large scale of unmolded dynamic case.The core method will be the multiple models switching control,which concludes the following aspects:(1)Comparing the linear model using the id = 0 field oriented method and the original strong coupled nonlinear model.The results indicate that the nonlinear model will reflect the running state more comprehensively and exactly instead of being independent on the "id = 0".However,in this essay,we didn't take the simple and less complicated ways,and we designed a nonlinear controller directly.(2)In the 'parameter known,case,we designed a nonlinear controller basing on the back-stepping method,and every state value can converge to its individual equlibriums,and each of the equlibriums are equals to the anticipant working point which was carefully designed.(3)If there exists many unknown parameters,generally,we should use some adaptive the-ories.On the other hand,the convergence speed will slow down if the gap is too large between initial parameters and real parameters.In the multiple models switching control,the issue above will be well overcomed by the parallel calculating of multiple estimators.Furthermore,we are unable to control the system by using a single controller,if the plant is perturbed by some input signals.The conclusion of this thesis are:the supervisor in this system will always provides a optimized controller,and make the state of the plant detectable—at least bounded.(4)We will discuss the simulation problems by three cases,they are:the ideal case(no parameter error and perturbation);the parameter error case;the pertubated case.The results of the simulation verify the detectable property of this essay successfully.Multiple models switching control has developed over twenty years till now.Even though it is improved and perfect in linear systems,there are still some challenges in the nonlinear control field.