A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares. Issue 1 (24th January 2018)

• Record Type: Journal Article
• Authors: Li, Xu; Yang, Chuanlei; Wang, Yinyan; Wang, Hechun
• Is Part Of: Royal Society open science. Volume 5:Issue 1(2018)
• Publication Date: 2018-01-24
• Subjects: diesel engine -- variable geometry compressor -- performance prediction -- PLS model; Science -- Periodicals; 500
• DOI: 10.1098/rsos.171468
• Languages: English
• ISSNs: 2054-5703

Abstract

Abstract : To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.