Biblio

Permanent magnet synchronous motors (PMSM) are widely used in the shafts of industrial robots. The quality consistency of PMSM, derived from both the wide range of operating temperature and inherent uncertainties, significantly influences the application of the PMSM. In this paper, the mechanism of temperature influence on the PMSM is analyzed with the aid of the digital model, and the quantitative relationship between the main PMSM feature, the cogging torque, and the temperature is revealed. Then, the NdFeB remanence in different temperature levels was measured to obtain its temperature coefficient. The finite element method is used to simulate PMSM. The qualitative and quantitative conclusions of cogging torque drop when the temperature rises are verified by experiments. The magnetic performance data of the magnetic tiles of 50 motors were randomly sampled and the cogging torque simulation was carried out under the fixed ambient temperature. The results show that the dispersion significantly increases the stray harmonic components of the cogging torque.

Application of computational intelligence methods in data analysis and optimization problems can allow feasible and optimal solutions of complicated engineering problems. This study demonstrates an intelligent analysis scheme for determination of optimal operating condition of an internal combustion engine. For this purpose, an artificial neural network learning model is used to represent engine behavior based on engine data, and a metaheuristic optimization method is implemented to figure out optimal operating states of the engine according to the neural network learning model. This data analysis scheme is used for adjustment of optimal engine speed and fuel rate parameters to provide a maximum torque under Nitrous oxide emission constraint. Harris hawks optimization method is implemented to solve the proposed optimization problem. The solution of this optimization problem addresses eco-friendly enhancement of vehicle performance. Results indicate that this computational intelligent analysis scheme can find optimal operating regimes of an engine.

Spin-transfer torque magnetoresistive random-access memories (STT-MRAMs) are gradually superseding conventional SRAMs as last-level cache in System-on-Chip designs. Their manufacturing process includes trimming a reference resistance in STT-MRAM modules to reliably determine the logic values of 0 and 1 during read operations. Typically, an on-chip trimming routine consists of multiple runs of a test algorithm with different settings of a trimming port. It may inherently produce a large number of mismatches. Diagnosis of such a sizeable volume of errors by means of existing memory built-in self-test (MBIST) schemes is either infeasible or a time-consuming and expensive process. In this paper, we propose a new memory fault diagnosis scheme capable of handling STT-MRAM-specific error rates in an efficient manner. It relies on a convolutional reduction of memory outputs and continuous shifting of the resultant data to a tester through a few output channels that are typically available in designs using an on-chip test compression technology, such as the embedded deterministic test. It is shown that processing the STT-MRAM output by using a convolutional compactor is a preferable solution for this type of applications, as it provides a high diagnostic resolution while incurring a low hardware overhead over traditional MBIST logic.

A novel efficiency-shifting radial-axial hybrid permanent magnet synchronous motor that can realize two high-efficiency regions at low and high speeds is developed to extend the maximum driving distance and track the reference speed more accurately for electric vehicle application. The motor has two stators, which are radial and axial, to rotate one shared rotor. The rotor employs two combined topologies, i.e., inner surface-inset-mounted and outer V-shaped interior-mounted. For both outer and inner permanent magnets, Nd-Fe-B, having the remanent flux density of 1.23 T and coercivity of 890 kA/m, is used. The simulation result shows that the designed motor exhibits not only high maximum torque of 400 Nm and the maximum speed of 18,000 rpm but also two high-efficiency regions of 97.6 % and 92.0 % at low and high speed, respectively. Lastly, the developed motor shows better performance than corresponding separated radial and axial permanent magnet motor.

This paper presents a study and analysis of flux linkage performance on 12/8 pole doubly salient permanent magnet machine in square envelope conventional. Analyzed model was using a finite element method. The investigated model was constructed by changing the size of the structure as the main parameters of the speed 500 rpm, PM coercivity 910 kA/m, PM remanence 1.2 T, copper loss 30 W, turns per coil 45, and stator side length 100 mm. The study and analysis of flux linkage, induced voltage, and torque are also included in this paper.

The NEREIDA wave generation power plant installed in Mutriku, Spain is a multiple Oscillating Water Column (OWC) plant. The power takeoff consists of a Wells turbine coupled to a Doubly Fed Induction Generator (DFIG). The stalling behavior present in the Wells turbine limits the generated power. This paper presents the modeling and a Harmony Search Algorithm-based airflow control of the OWC. The Harmony Search Algorithm (HSA) is proposed to help overcome the limitations of a traditionally tuned PID. An investigation between HSA-tuned controller and the traditionally tuned controller has been performed. Results of the controlled and uncontrolled plant prove the effectiveness of the airflow control and the superiority of the HSA-tuned controller.

This paper presents an analytical method for predicting the electromagnetic performance in permanent magnet (PM) machine with the spoke-type rotor (STR) and a proposed hybrid rotor structure (HRS), respectively. The key of this method is to combine magnetic field analysis model (MFAM) with the magnetic equivalent circuit model. The influence of the irregular PM shape is considered by the segmentation calculation. To obtain the boundary condition in the MFAM, respectively, two equivalent methods on the rotor side are proposed. In the STR, the average flux density of the rotor core outer-surface is calculated to solve the Laplace's equation with considering for the rotor core outer-surface eccentric. In the HRS, based on the Thevenin's theorem, the equivalent parameters of PM remanence BreB and thickness hpme are obtained as a given condition, which can be utilized to compute the air-gap flux density by conventional classic magnetic field analysis model of surface-mounted PMs with air-gap region. Finally, the proposed analytical models are verified by the finite element analysis (FEA) with comparisons of the air-gap flux density, flux linkage, back-EMF and electromagnetic torque, respectively. Furthermore, the performance that the machine with the proposed hybrid structure rotor can improve the torque density as explained.

To decouple the multi-axis motion in the 6 degrees of freedom magnetically levitated actuators (MLAs), this paper introduces a numerical method to model the force and torque distribution. Taking advantage of the Gaussian quadrature, the concept of coil node is developed to simplify the Lorentz integral into the summation of the interaction between each magnetic node in the remanence region and each coil node in the coil region. Utilizing the coordinate transformation in the numerical method, the computation burden is independent of the position and the rotation angle of the moving part. Finally, the experimental results prove that the force and torque predicted by the numerical model are rigidly consistent with the measurement, and the force and torque in all directions are decoupled properly based on the numerical solution. Compared with the harmonic model, the numerical wrench model is more suitable for the MLAs undertaking both the translational and rotational displacements.

This paper develops a model for Wells turbine using Xilinx system generator (XSG)toolbox of Matlab. The Wells turbine is very popular in oscillating water column (OWC) wave energy converters. Mostly, the turbine behavior is emulated in a controlled DC or AC motor coupled with a generator. Therefore, it is required to model the OWC and Wells turbine in real time software like XSG. It generates the OWC turbine behavior in real time. Next, a PI control scheme is suggested for controlling the DC motor so as to emulate the Wells turbine efficiently. The overall performance of the system is tested with asquirrel cage induction generator (SCIG). The Pierson-Moskowitz and JONSWAP irregular wave models have been applied to validate the OWC model. Finally, the simulation results for Wells turbine and PI controller have beendiscussed.

The manufacturing process of electrical machines influences the geometric dimensions and material properties, e.g. the yoke thickness. These influences occur by statistical variation as manufacturing tolerances. The effect of these tolerances and their potential impact on the mechanical torque output is not fully studied up to now. This paper conducts a sensitivity analysis for geometric and material parameters. For the general approach these parameters are varied uniformly in a range of 10 %. Two dimensional finite element analysis is used to simulate the influences at three characteristic operating points. The studied object is an internal permanent magnet machine in the 100 kW range used for hybrid drive applications. The results show a significant dependency on the rotational speed. The general validity is studied by using boundary condition variations and two further machine designs. This procedure offers the comparison of matching qualitative results for small quantitative deviations. For detecting the impact of the manufacturing process realistic tolerance ranges are used. This investigation identifies the airgap and magnet remanence induction as the main parameters for potential torque fluctuation.

With the application and promotion of electric vehicles, vehicle security problems caused by actuator reliability have become increasingly prominent. Firstly, the paper analyses and sums motor failure modes and their effects of permanent magnet synchronous motor (PMSM) , which is commonly used on electric vehicles. And then design a hierarchical structure of the vehicle control strategies and the corresponding algorithms, and adjust based on the different failure modes. Finally conduct simulation conditions in CarSim environment. Verify the control strategy and algorithm can maintain vehicle stability and reduce the burden on driver under motor failure conditions.