Additive manufacturing has many advantages over traditional manufacturing methods and has been increasingly used in medical, aerospace, and automotive applications. The flexibility of additive manufacturing technologies to fabricate complex geometries from copper, polymer, and ferrous materials presents unique opportunities for new design concepts and improved machine power density without significantly increasing production and prototyping cost. Topology optimization investigates the optimal distribution of single or multiple materials within a defined design space, and can lead to unique geometries not realizable with conventional optimization techniques. As an enabling technology, additive manufacturing provides an opportunity for machine designers to overcome the current manufacturing limitation that inhibit adoption of topology optimization. Successful integration of additive manufacturing and topology optimization for fabricating magnetic components for electrical machines can enable new tools for electrical machine designers. This article presents a comprehensive review of the latest achievements in the application of additive manufacturing, topology optimization, and their integration for electrical machines and their magnetic components.

This study presents a method to mitigate and alleviate the effects produced by a turn-to-turn short in a fault tolerant permanent magnet synchronous motor with single-layer concentrated windings. The rotor magnets are capable of inducing a high voltage across the fault contact point; this voltage has the potential to generate a high circulating current that promotes the rapid propagation of the fault due to the thermal stress created by the increased localized fault power losses. The scope of this study is for applications where postfault operation is desired, even if it means operating at reduced power capacity and lower speeds. Upon quick detection of a fault, the proposed technique can be used to decelerate the propagation of the fault and extend the machine's postfault life span. The technique consists of a magnetic field-weakening strategy at speeds below nominal, to reduce the voltage induced in the faulted portion. The concept is validated through finite element analysis, modeling, and experimental data. It is demonstrated that the proposed technique reduces the fault current magnitude and winding temperature.

Different faults in permanent magnet synchronous machines (PMSMs) cause various and independent changes to the machine magnetic flux distribution, which affect the machine parameters and performance. These changes are reflected in the machine flux linkages and can be estimated from the machine voltages. In this paper, we continue the work of Haddad et al., where a method was proposed to detect and separate three types of faults in PMSMs: 1) static eccentricity; 2) demagnetization; and 3) turn-to-turn short circuit. The method proposed here is based on using the change in the commanded d- and q-axis voltages, while the machine is operating at steady state, for fault detection and separation. Simulation tests using finite element analysis (FEA) software (MAGSOFT-Flux2D) were performed under healthy and the tested fault conditions on a three-phase ten-pole fractional-slot concentrated-winding PMSM. An analytical method is proposed to estimate the commanded voltages at any operating condition, and a classification algorithm is implemented for fault detection and classification. Experimental tests were carried out and compared with FEA. The effects of the variation in the operating speed and temperature were simulated and tested to validate the detection method under different operating conditions.

A significant portion of faults experienced by electrical machines are caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation and without expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of stator insulation with simple equipment is proposed. Accelerated lifetime testing was performed by exposing the stator of an electric machine to high temperatures. An Extended Kalman Filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using expensive or special technology.

This paper presents a simplified experimental method to accurately estimate the parameters of a permanent magnet synchronous machine. It accounts for the self and cross saturation effects over the entire operation range of the machine. Experimentally, the procedure is performed only using the components typically used in a traction drive system, such as current sensors, a position encoder, a DC link voltage sensor and a digital signal processor. AC voltage sensors, analog filtering hardware and additional measuring equipment are not required. With fewer components, the method is suitable for machine commissioning in the field. Therefore, the process of characterization is no longer confined to a laboratory environment. The method was experimentally verified using a 10-kW SmCo and a 125-kW NdFeB interior permanent magnet machine.

Improving the efficiency, as well as reducing size of electrical machines, can reduce the amount and types of pollutants we emit into our environment; however, manufacturing realities often bottleneck the production of new low-cost and highly efficient motor designs. Additive manufacturing technologies provide flexibility to overcome limitations of the subtractive and powder metallurgical processes. In this paper, the magnetic characteristics of 3D printed iron silicon samples are compared with prototype soft magnetic composite material. Binder jet printing technology is used to prepare the iron silicon samples and its magnetic properties are experimentally extracted. It is shown that magnetic permeability of the 3D printed sample is higher than prototype soft magnetic composite.