Abstract Magnetic-geared permanent magnet (MGPM) electrical machine is a new type of machine by incorporating magnetic gear into PM electrical machine, and it may be in operation with low-speed, high-torque and direct-driven. In this paper, three types of MGPM machines are present, and a quantitative comparison among them is performed by finite element analysis (FEA). The magnetic field distribution, stable torque and back EMF are obtained at no-load. The results show that three types of MGPM machine are suitable for different application fields respectively according to their own advantages, such as high torque and back EMF, which form an important foundation for MGPM electrical machine research.
The advance of MEMS-based inertial sensors successfully expands their applications to small unmanned aerial vehicles (UAV), thus resulting in the challenge of reliable and accurate in-flight alignment for airborne MEMS-based inertial navigation system (INS). In order to strengthen the rapid response capability for UAVs, this paper proposes a robust in-flight alignment scheme for airborne MEMS-INS aided by global navigation satellite system (GNSS). Aggravated by noisy MEMS sensors and complicated flight dynamics, a rotation-vector-based attitude determination method is devised to tackle the in-flight coarse alignment problem, and the technique of innovation-based robust Kalman filtering is used to handle the adverse impacts of measurement outliers in GNSS solutions. The results of flight test have indicated that the proposed alignment approach can accomplish accurate and reliable in-flight alignment in cases of measurement outliers, which has a significant performance improvement compared with its traditional counterparts.