Thermal analysis calculation is an indispensable checking process in the design of the high-speed permanent magnet synchronous machine (HSPMSM) with the active magnetic bearings, due to its high loss density and non-contact support mode. The finite element method (FEM) is applied for visual global temperature distribution. Because the thermal analysis is a complex problem reflected the interaction among the electromagnetic field, temperature field, and fluid field, so it cannot be solved independently, and a multi-physical field simulation based on magneto-thermal-fluid coupled iterative solution is proposed. An electromagnetism (EM) model is established to solve electromagnetic loss and the computational fluid dynamics (CFD) software is used to simulate convective condition, both the results are applied to the thermal analysis of motor. The data interaction is bidirectional and transfers in the form of a field, and the interaction during the EM model, the CFD model, and thermal analysis is fully considered to guarantee high accuracy. Finally, two prototypes of 30-kW 60000 r/min magnetically suspended HSPMSMs have been developed. The experimental results of back-to-back towing test validate the accuracy of the proposed multi-physical field simulation.INDEX TERMS Back-to-back motor towing experiment, cooling design, electromagnetic-thermal-fluid coupling analysis, high-speed permanent magnet motor, magnetic bearings, multi-physics analysis, thermal analysis.
In order to find an algorithm to get a better optimization result of high-speed rotor supported by magnetic bearing in BLDCM, we presented a multiple objective optimization results which included three algorithms' in this paper. They are the local Sequential Quadratic Program (SQP) algorithm, the global Genetic Algorithm (GA) and the combined optimization strategy algorithm which combines GA and SQP. The parametric optimization model of a 100 kW BLDCM supported by magnetic bearings was constituted with software ANSYS and an effective connection between software ANSYS and iSIGHT was used to execute the whole optimization process. To insure the best performance, mass and strength were chosen as the optimization goals, meanwhile, the static strength, dynamic modal, shape and magnetic force of the rotor subassembly were used as the main constrains. Six main dimensions of the subassembly were optimized. The optimization results indicated that the GA can get a higher optimization precision than the other two algorithms and the SQP was not effective in the optimization of magnetic suspended motor rotor subassembly. The GA's optimization result made the mass decrease 7.62 percent with the safe factor is 3.15. The 100 kW BLDCM supported by magnetic bearings was designed and fabricated; the multiple objective optimization results were verified by the prototype.
The correlation degree between nodes of urban traffic network is the basis of sub-area division, and the signal coordination control in sub-area is very effective to improve the traffic efficiency of road network. In this paper, based on the study of unsaturated traffic state, the paper first analyzes the shortcomings of the existing correlation degree model, and constructs a comprehensive correlation degree model to measure the relationship between the two nodes by considering the factors of section spacing, section flow, signal period, traffic flow dispersion and queue length. Through VISSIM simulation experiment, the examples of 15 sections of 10 nodes are compared with the classical Whitson model and the merging index. The sub-region based on the DBSCAN algorithm is more close to reality, which can provide a good basis for the signal coordination strategy.
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