Optimal operation region of super-high-speed electrical air compressor in fuel cell system for working stability under multiple-time scale excitation. (3rd June 2021) - Hu, Donghai; Hou, Wenshuo; Hu, Leli; Yang, Lei; Yang, Qingqing; Zhou, Jiaming
Abstract: As an important component of fuel cell systems, the operational stability of compressors powered by super-high-speed permanent magnet synchronous motors (SHSPMSMs) significantly affects the comprehensive performance of fuel cells. Under relatively low-frequency excitation, as the difference between excitation and natural frequencies is in the range of an order gap, multi-time scales are generated in a super-high-speed electrical air compressor (SHSEAC), and thereby lead to the generation of complex nonlinear vibrations. Moreover, the stiffness softening effect due to high-speed operation leads to additional instability phenomena. In this study, a multi-time scale-based instability mechanism of a SHSEAC was examined under the stiffness softening effect. The mathematical model of a SHSEAC was first established by considering the load and electromagnetic excitation. Then, by considering load excitation as a slow variable, the operation regions of the system are accurately classified based on the bifurcation theory and Routh–Hurwitz criterion. Numerical simulations are developed to determine the optimal operation region and investigate the effects of the excitation frequency amplitude and order gap on the transition of the system to instability. The results indicate that under multi-time scales, the excitation amplitude classifies the operation region into three categories: optimal operation region, progressive instability region, and absolute instability region. Furthermore, stiffness softening effect will cause optimal operation region to be gradually eroded, increasing probability of instability. Highlights: A multi-time scale model of the high-speed PMSM driven compressor is established. The optimal operation region of the high-speed PMSM driven compressor under multi-time scales is determined. The effectiveness of the proposed method is verified by experiment.