Axial-flux permanent-magnet (AFPM) motors are a kind of important motor with compact structure, high power density and high torque density. In this review, the progress of AFPM motors and their key technologies are analyzed and described, with emphasis on the topological structures, design and optimization methods and control techniques. Based on these analyses, the main findings of the review are the following: (1) the yokeless and segment armature (YASA)-type motors have great potential for development; (2) the multi-objective optimization design theories can be integrated and applied to optimize the design of AFPM motors; and (3) optimal control and sensorless control have important value in improving system reliability and reducing cost. Finally, highlights and prospects are provided for further advancing AFPM motors.
The rapid development of automated vehicle technology requires reasonable test scenarios and comprehensive evaluation methods. This paper proposes an evaluation method for automated vehicles combining subjective and objective factors. First, we propose a method for automatically generating test scenarios and for batch testing autonomous vehicles. Then, the use of the target layer, total index layer, and index layer of automated vehicles is proposed to establish a more comprehensive evaluation system for automated vehicles. Specifically, the analytic hierarchy process (AHP, subjective) and improved criteria importance though intercriteria correlation (CRITIC, objective) methods are used to determine the weight of the indicators, and a two-level fuzzy comprehensive (subjective and objective) evaluation method is adopted to comprehensively evaluate the performance of the automated vehicles. Finally, the effectiveness of the proposed evaluation method combining subjective and objective factors is verified through virtual simulations and real-world experiments. Through a combination of subjective and objective methods, improved results can be obtained for safety, efficiency, economy, intelligence, and comfort tests.
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