This page has only limited features, please log in for full access.
Stable operation of fuel cell air compressions is constrained by rotating surge in low flowrate conditions. In this paper, a diagnosis criterion based on wavelet transform to solve the surge fault is proposed. First of all, the Fourier transform was used to analyze the spectral characteristics of the outlet flowrate. Before wavelet transform was used, the data are standardized. This step eliminated the influence of the flowrate’s absolute value. Then, the wavelet coefficients under characteristic frequencies were extracted. Finally, the diagnosis criterion’s threshold, which indicates the surge occurrence, was defined from the perspective of safety margin. The criterion threshold alerted a surge only 1 s after it occurred. The analysis results show that the criterion meets with the expectation, and it can be used for the control of anti-surge valve.
Su Zhou; Jie Jin; Yuehua Wei. Research on Online Diagnosis Method of Fuel Cell Centrifugal Air Compressor Surge Fault. Energies 2021, 14, 3071 .
AMA StyleSu Zhou, Jie Jin, Yuehua Wei. Research on Online Diagnosis Method of Fuel Cell Centrifugal Air Compressor Surge Fault. Energies. 2021; 14 (11):3071.
Chicago/Turabian StyleSu Zhou; Jie Jin; Yuehua Wei. 2021. "Research on Online Diagnosis Method of Fuel Cell Centrifugal Air Compressor Surge Fault." Energies 14, no. 11: 3071.
The purpose of this research is to develop a representative driving cycle for fuel cell logistics vehicles running on the roads of Guangdong Province for subsequent energy management research and control system optimization. Firstly, we collected and preliminarily screened the 42-day driving data of a logistics vehicle through the remote monitoring platform, and determined the vehicle characteristic signal vector for analysis. Secondly, the principal component analysis method is used to reduce the dimensionality of these characteristic parameters, avoiding the linear correlation between them and increase the comprehensiveness of the upcoming clustering. Next, the dimensionality-reduced data are fed to a clustering machine. K-means clustering method is used to gather the segmented road sections into highway, urban road, national highway and others. Finally, several segments are chosen in accordance to the occurrence possibility of the four types of road conditions, minimizing the deviation with the original data. By joining the segments and using a moving average filtering window, a typical driving cycle for this fuel cell logistics vehicle on a fixed route is constructed. Some statistical methods are done to validate the driving cycle.The effectiveness analysis shows the driving cycle we constructed has a high degree of overlap with the original data. This positive result provides a solid foundation for our follow-up research, and we can also apply this method to develop other urban driving cycles of fuel cell logistics vehicle.
Su Zhou; Jie Jin; Yuehua Wei. A Driving Cycle for a Fuel Cell Logistics Vehicle on a Fixed Route: Case of the Guangdong Province. World Electric Vehicle Journal 2021, 12, 5 .
AMA StyleSu Zhou, Jie Jin, Yuehua Wei. A Driving Cycle for a Fuel Cell Logistics Vehicle on a Fixed Route: Case of the Guangdong Province. World Electric Vehicle Journal. 2021; 12 (1):5.
Chicago/Turabian StyleSu Zhou; Jie Jin; Yuehua Wei. 2021. "A Driving Cycle for a Fuel Cell Logistics Vehicle on a Fixed Route: Case of the Guangdong Province." World Electric Vehicle Journal 12, no. 1: 5.