Theoretical Loss Model Research Articles

Effects of Geometry of Plenum Chamber on Losses in the Bleed System of an Axial Compressor

To study how the geometry of the plenum chamber in the bleed system of an axial compressor influences the losses therein and to establish a theoretical loss model for this system, a 1.5-stage axial compressor with a bleed system is studied numerically by means of computational fluid dynamics (CFD). The results show that losses in the bleed system occur mainly in the axisymmetric bleed slot and plenum chamber, accounting for ca. 85% of the total loss. For a bleed system with a vertical axisymmetric slot, the loss is more sensitive to the radial height than to the axial width of the plenum chamber. A loss model for each part of the bleed system is established via theoretical analysis, and then, a model of the overall bleed system is established by combining these submodels. The predictions of the theoretical loss model agree well with the CFD results: the maximum prediction error for the coefficient of the stagnation pressure loss in the bleed system is −1.38%, and the average prediction error is −0.8%. This loss model can be used when designing the geometry of a bleed system.

Energy performance prediction of the centrifugal pumps by using a hybrid neural network

It is of great significance to rapidly and accurately predict the energy performance of centrifugal pumps for the macro-control of the entire electric power system. However, some challenges are encountered, for example, the numerical simulation requires huge computing resources and calculating time, the theoretical loss model needs to improve the prediction accuracy, etc. Based on the multiple geometrical parameters and operation conditions, a hybrid neural network is proposed to predict the energy performance (i.e. the head, power and efficiency) of centrifugal pumps, where the theoretical loss model is incorporated into the back propagation neural network and then the neural network structure is optimized by automatically determining the node number of hidden layers. When compared with the experiments, the energy performance is well predicted by using the hybrid neural network with the mean-square-error (MSE) for the head, power and efficiency of 0.0062, 8.4E-4, 0.020, respectively. Besides, by considering the theoretical loss model, the hybrid neural network demonstrates a dramatic decrease in the head MSE and the efficiency MSE when compared with the original neural network. Furthermore, the hybrid neural network performs much better than the traditional linear regression in a wide flow-rate range for multiple centrifugal pumps.

PWM Switched Capacitor-Based Cell-Level Power Balancing Converter Utilizing Diffusion Capacitance of Photovoltaic Cells

This paper proposes a novel pulsewidth modulation cell-level diffusion charge redistribution (DCR) converter based on a switched capacitor converter (SCC) utilizing diffusion capacitance of photovoltaic (PV) cells for PV modules under partial shading. Although a discrete inductor and capacitor are additionally necessary, Joule losses associated with switching operations can be reduced compared to the conventional capacitorless DCR converter. First, ac impedance measurement for a PV cell with 125 × 125 mm was performed, and the diffusion capacitance values were measured to be approximately 6.0 mF at its maximum power point voltage of 0.574 V. Second, the theoretical loss model was derived based on the detailed analysis, and it revealed that an optimal duty cycle achieving the lowest Joule loss was dependent on shading conditions. Third, a dual maximum power point tracking (MPPT) algorithm that controls duty cycles of not only the DCR converter, but a front-end boost converter is also proposed. With the dual MPPT control, the DPP converter operates at its optimal duty cycle to minimize the Joule loss while the boost converter seeks the MPP. The experimental results demonstrated that the maximum power significantly increased, thanks to the DCR converter, and that both the DCR and boost converters operated with respective optimal duty cycles.