Study On Iron Loss Identification And Compensation Method For Induction Motor

Motor control systems characterized with high-speed and high-efFiciency are needed in centrifugal equipment and electric vehicles.As an important part of the model parameters and motor losses,iron loss has an impact on the flux observation,parameter identification,real-time torque and speed control,and efficiency optimal control performance to some extent.Using appropriate models to quantify the impact of iron loss,and then proposing corresponding improvements for different applications are the hot topics of modem motor control and detection technology.The adaptive observer is one of the most common and effective methods for single-parameter real-time identification and compensation.The power of components in the equivalent circuit can be easily estimated by using the full-order state knowledge.To test the performance of models and observers with the iron loss changing,a variety of iron loss resistance perturbations are assumed.Based on this,simulation tests for various models and compensation methods are performed.It is an attempt to identify the iron loss and its equivalent parameter using an observer so as to provide references for improving control accuracy and motor operating efficiency of the speed control system.The mam work is summarized as follows:(1)Three types of motor equivalent models related to iron loss are studied.They are the parallel model,series model and the conventional model simplified from the two models.The three models are analyzed and tested under the empirical perturbation assumption of the iron loss resistance,and their respective advantages and disadvantages are summarized.(2)Based on the parallel model and series model,the adaptive observers and fixed-value compensation observers are established respectively.Based on the conventional model,the observer ignoring iron loss is established.These observers are tested and compared under the same conditions as the model tests.The observation errors and the iron loss estimation errors introduced by different models and compensation methods are obtained.(3)In view of the simplicity of the series model and the easiness of observer designing,the adaptive observer based on series model is selected as the research object.Considering the analytical and design strategy of the traditional adaptive observer,the observer is designed based on performance indicators such as parameter sensitivity,dynamic tracking performance,and noise sensitivity.The results show that the iron loss can be qualitatively estimated by the observer.However,the adaptive observer based on the parallel model is difficult to analysis and design,and the identification result of observer based on the series model is greatly influenced by the parameter deviation and noise.With the accurate description of the iron loss resistance,the series model can effectively replace the complex parallel model to estimate the iron loss accurately through error compensation.Under a variety of iron loss parameter compensation methods,replacing the conventional model with a series model can improve observation and control accuracy to some extent.