Thermal–structure coupling analysis and multi-objective optimization of motor rotor in MSPMSM

With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses, which leads to instability and inefficiency.In this paper, the mechanical–temperature field coupling analysis is conducted to analyze the relationship between the temperature field and structure, and multi-objective optimization of a rotor is performed to improve the design reliability and efficiency. Firstly, the temperature field is calculated by the 2 D finite element model of MSPMSM and the method of applying the 2 D temperature result to the 3 D finite element model of the motor rotor equivalently is proposed. Then the thermal–structure coupling analysis is processed through mathematic method and finite element method(FEM),in which the 3 D finite element model is established precisely in a way and approaches the practical operation state further. Moreover, the impact produced by the temperature and structure on the mechanical strength is analyzed in detail. Finally, the optimization mathematical model of the motor rotor is established with Sequential Quadratic Programming-NLPQL selected in the optimization scheme. Through optimization, the strength of the components in the motor rotor increases obviously and satisfies the design requirement, which to a great extend enhances the service life of the MSPMSM rotor.

A multi-objective antidisturbance robust filter for SINS/GPS navigation systems

Purpose-A full-order multi-objective anti-disturbance robust filter for SINS/GPS navigation systems with multiple disturbances is designed.Generally,the unmodeled dynamics,the external environmental disturbance and the inertial apparatus random drift may exist simultaneously in an integrated navigation system,which can be classified into three type of disturbances,that is,the Gaussian noise,the norm bounded noise and the time correlated noise.In most classical studies,the disturbances in integrated navigation systems are classified as Gaussian noises or norm bounded noises,where the Kalman filtering or robust filtering can be employed,respectively.While it is not true actually,such assumptions may lead to conservative results.The paper aims to discuss these issues.Design/methodology/approach-The Gaussian noises,the norm bounded noises and the time correlated noises in the integrated navigation system are considered simultaneously in this contribution.As a result,the time correlated noises are augmented as a part of system state of the integrated navigation system error model,the relative integrated navigation problem can be transformed into a full-order multi-objective robust filter design problem for systems with Gaussian noises and norm bounded disturbances.Certainly,the errors of the time correlated noises are estimated and compensated for high precision navigation purpose.Sufficient conditions for the existence of the proposed filter are presented in terms of linear matrix inequalities(LMIs)such that the system stability is guaranteed and the disturbance attenuation performance is achieved.Findings-Simulations for SINS/GPS integrated navigation system given show that the proposed full-order multi-objective anti-disturbance filter,has stronger robustness and better precision when multiple disturbances exist,that is,the present algorithm not only can suppression the effect of white noises and norm bounded disturbance but also can estimate and compensate the modeled disturbance.Originality/value-The proposed algorithm has stronger anti-disturbance ability for integrated navigation with multiple disturbances.In fact,there exist multiple disturbances in integrated navigation system,so the proposed scheme has important significance in applications.

Accelerometer Bias and Star Sensor Installation Error Joint Calibration for the SINS/CNS Integrated Navigation System Using Attitude Maneuver

The integrated strap-down inertial nav igation system/olelestial navigation system(SINS/CNS)i an important autonomous navigation method with efective concealment and high predision.Both accelerometer biss and star ensor installation error ame important factors that aflect the performanoe of this mavigation system,which needl to be calibratexd and compensatedl.A new acelerometer bias and star sensor installation error joint calibration method for the SINS/CNS integrated navigation system i propoeed.In this newly propoeed method,the installation error of star sensor is augmented to the state vector,and the star vector,nadir angle,horkzontal poeition error and velbcity error ame ueed a8 measurementa to calbrate the two errors mentioned above.Simulations show that both accelerometer bias and star sensor installation enror an be calibratedl efectively.