Development of A Flux-Enhancing Dual-Mechanical-Port Electric Machine For Far-Sea Hybrid Unmanned Surface Vehicles

Due to the advantages of high integration, no mechanical contact between the two ports, and various operating modes, the dual-mechanical-port electric machines have broad application prospects in far-sea hybrid unmanned surface vehicles. However, this type of electric machine has disadvantages, such as low power density, lack of efficient analytical methods, and speed overshoot and oscillation when switching between different operating modes. To solve the above problems, we integrate the “flux enhancing technology” into the topology design of this novel electric machine. This project proposes a novel flux-enhancing dual-mechanical-port electric machine, the corresponding electromagnetic field analytical modeling method, and an online self-learning control strategy, which can effectively improve the power density, design and optimization efficiency, and dynamic performance of this type of electric machine. This project: 1) aims to investigate the flux-enhancing structures and operating mechanism of this type of electric machine, so its design theory can be completed; 2) proposes a hybrid electromagnetic field modeling method based on the magnetic reluctance network and harmonic modeling method and further combines it with the multi-objective algorithm to form the structural optimization criteria for this type of electric machines; 3) explores the control strategy based on the online neural network to achieve a smooth control switching process to satisfy the various operating modes requirement of the proposed electric machine. Finally, a test bench will be set up to verify the effectiveness of the proposed machine topology. This project’s conduction can help solve the bottleneck problems that restrict the performance of dual-mechanical-port electric machines and is expected to provide a theoretical basis and technical support for unmanned surface vehicles sailing toward the far sea.