Hairpin windings are gaining increasing popularity in recent years due to their advantages in improving electrical machine performance while reducing manufacturing time and costs. Their geometrical features introduce new challenges and opportunities on thermal management. In particular, spray cooling is increasingly being used, since hairpin windings open up regular and accurately defined gaps in the end-windings compared to the traditional random windings. To date, technical literature on the effectiveness of spray cooling with hairpin windings is lacking, with no practical guidelines available to researchers. In this article, taking an existing hairpin-wound stator, a test rig is developed to investigate the cooling ability of different spray cooling setups on the end-windings. Three types of commercial spray nozzles are chosen to carry out a series of experiments, varying the oil flow rate, pressure, outlet velocity, and number of nozzles. The winding temperature and heat transfer coefficients are presented and discussed. Furthermore, the efficiency of spray cooling is reviewed based on the experimental results. Finally, suggestions on designing similar cooling setups and increasing the cooling efficiency are also provided.

For the propose of increasing the reliability in hostile environment, techniques of fault diagnosis have been reported for three-phase voltage source inverter (VSI). Based on the average current Park's Vector method, this paper proposes a fuzzy-based fault diagnosis method for the VSI in the three-phase permanent-magnet synchronous motor drive. By utilizing the phase current information, the fault symptom variables are calculated by using the average current Park's Vector method. The fuzzy logic approach is applied to process the fault symptom variables and get the faulty information of power switches. Compared with other fuzzy logic methods, the fuzzy logic design, fuzzy inputs and fuzzy rules are different. The proposed fault diagnosis method can detect and locate not only the single or multiple open-circuit faults but also the intermittent faults in power switches, which can improve the reliability of the motor drive system. The effectiveness of the proposed method is validated by both simulation and experiments.

Electrical machines and drives keep moving away from traditional technologies such as brushed machines and wound field machines towards lighter, ‘easier to maintain’ machines. A very interesting aspect is that certain transport applications, especially the aerospace industry, still favour the classical wound field machine for its main generating system such as the Boeing 787. This paper focuses on investigating this particular trend by presenting a detailed overview of historical power generation systems on aircraft. This paper compares the current state of the art of wound field machines with other generator families. The results of this analysis are then projected into the needs of the electrical power generation and distribution system on aircraft. While power density is a major objective for any aerospace application, however the extra benefits associated with wound field systems are still essential in modern aircraft. The paper then focuses on the main challenges for improving power density of wound field machines. Recommendations, opportunities and improvements related to wound field machines are discussed. In conclusion, if robust designs for higher speed wound field generators were consolidated, it would be very probable that these classical machines might still be implemented on future MEA platforms.

Sensorless machine drives in vehicle traction frequently experience rapidly-changing load disturbance and demand fast speed dynamics. Without gain-scheduling or compensation, conventional Quadrature Phase-Locked-Loop (Q-PLL) is unable to accurately estimate the rotor position and speed for these systems. In this paper, a Third Order Nonlinear Extended State Observer (TNESO) is proposed for position and speed estimation for sensorless Interior Permanent Magnet Synchronous Motor (IPMSM) drives. TNESO has the power of nonlinear feedback and takes the advantages of fast convergence and disturbance rejection. An optimized parameter configuration method is deployed to extend the disturbance observation bandwidth of TNESO. Both the steady state and transient performance of TNESO are verified through the experimental tests. In comparison with the performance of conventional Q-PLL scheme, the proposed ESO is proved to be capable of delivering higher precision of position and speed estimation against rapidly varying disturbance in wide operating range.

While the electromagnetic aspects of hairpin windings are actively being investigated and discussed in recent literature, including the design rules together with the loss calculation and reduction techniques, the thermal performance and modeling aspects have received less attention to date. In hairpin windings, the conductors (pins) are comparatively larger and arranged as separate components in parallel within the slot. In contrast, conductors randomly overlap and contact each other for traditional random windings. The differences in the aforementioned winding physical characteristics result in a different methodology to develop the thermal network. This article presents a 3-D lumped parameter thermal network (LPTN) approach for an oil-spray cooled hairpin winding, which includes the slot thermal model configuration, the end-winding connections, together with different methodologies of analyzing the end-winding sprayed oil characteristics. The aforesaid thermal model captures unique features related to the winding technology and cooling mechanism, such as the nonuniform end-winding temperature caused by the uneven oil-spray cooling effects. Finally, taking an existing propulsion drive hairpin stator and a bespoke-designed test setup, the presented steady-state thermal modeling approach is experimentally validated covering various experimental tests, including different spray conditions.

In practice, sensorless drive systems of interior permanent magnet synchronous motors (IPMSMs) are usually working in highly utilized conditions where fast changing uncertain loads, inverter losses, magnetic saturation and other disturbance exist. These issues could reduce the performance and stability, which become the main vulnerability of sensorless drives. Linear extended state observer (LESO) or Q-PLL is conventionally adopted to estimate the speed and position. Without compensation or adaptive methods, fast changing uncertainties cannot be observed thoroughly. In this paper, a third order super-twisting extended state observer (STESO) is proposed to enhance the dynamic performance of position and speed estimation for IPMSM. Utilizing the high-order extended state and super-twisting algorithm, fast convergence and disturbance estimation can be achieved in STESO. The effectiveness and stability of STESO are analyzed and an optimized parameter selection method is presented. Comparative experimental results between the LESO and STESO verify the effectiveness and improvement of the proposed STESO against rapid speed and load variations.