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This article proposes a position detection method for a multi-to-one wireless power transmission (WPT) system for the first time and applies it to the position detection of a spherical motor. The traditional contact detection system has high friction resistance and poor rotor positioning accuracy. Although some noncontact measurement systems are not directly connected to the rotor, the structure or calculation of the measurement system is more complicated. To solve the abovementioned problems, this article proposes two structural topologies, which are evenly arranged on the upper part of the rotor and the receiving coil is placed on the rotor shaft. When the motor rotor rotates along with the three motion states of yaw, spin, and tilt, the receiving and multitransmitting coils will have an angular offset. The rotor position is obtained by a method of accurately estimating the mutual inductance. This method avoids complicated finite element calculations and saves a lot of time. Finally, the experiment verifies the above analysis and compares the data with the microelectromechanical system three-degree-of-freedom attitude detection method. This article provides insights into the position detection of spherical motors. This method simplifies the previous measurement system and obtains higher positioning accuracy. [ABSTRACT FROM AUTHOR]

This article proposes a rotor attitude estimation (RAE) method for spherical motors using the multiobject Kalman kernel correlation filter (MKKCF) algorithm in monocular vision. A permanent magnet spherical motor (PMSpM) is adopted as the research object, and a monocular area scan camera is equipped in the RAE system with a visual feature component mounted on top of the rotor output shaft. In the proposed MKKCF algorithm, the Kalman filter is used to enhance the robustness and accuracy of KCF tracker for each object. To simplify the proposed algorithm verification, a one-object tracking comparison is conducted among the KCF algorithm, the fast discriminative scale space tracking (FDSST) algorithm, and the Kalman KCF algorithm, and the results show that Kalman KCF tracker is more applicable for RAE. In addition, an RAE test bench is developed, and the MKKCF-based RAE method and the micro-electro-mechanical system (MEMS) (MPU9250) method are compared when estimating the rotor attitude. To set a benchmark, the contact rotor position measurement with encoders is used. The comparison results indicate that the MKKCF-based RAE method works with higher accuracy than the MEMS method. Finally, a closed-loop PMSpM control experiment is conducted by using the proposed MKKCF-based RAE method, and the practicability of the proposed method is proved. [ABSTRACT FROM AUTHOR]

This paper proposes a monolayer Halbach array based permanent magnet spherical motor (PMSpM) using cubic permanent magnets (PM). The research aims to provide a fast computing model to calculate the magnetic field for this PMSpM, which helps for future PMSpM optimization and control study. Three thickness equivalence principles are provided and compared for cubic PMs. The magnetic scalar potential is introduced, and the spherical harmonics expansion is implemented for rotor magnetic field analysis. Engineering revision is used to reduce the Legendre function deviation in polar angle direction. Torques and forces are deduced using the Lorentz force law, and relatively simple models of this PMSpM for both magnetic fields and torques are acquired. In addition, a prototype motor has been developed, and the analytic results of air-gap flux density and torque are compared with their finite element simulation and experimental results, which are proved consistent. It is concluded that the fundamental component of the spherical harmonics can be used to present the magnetic field model, which uses fewer integrals than the Biot-Savart law based solution, and the modeling results of the magnetic field flux density, forces and torques are in line with the expectations. The analytic models are proved correct. [ABSTRACT FROM AUTHOR]