A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least...

Area of Science:

• Automotive Engineering
• Thermodynamics
• Computational Fluid Dynamics

Background:

• Turbocharged diesel engines require precise control over intake air flow for optimal performance.
• Variable-geometry compressors (VGCs) enhance intake air flow range but present prediction challenges due to variable diffuser vane angles (DVAs).
• Accurate performance prediction is crucial for integrating VGCs effectively into engine models.

Purpose of the Study:

• To develop a novel and accurate prediction model for variable-geometry compressor (VGC) performance.
• To establish a polynomial relationship between VGC performance parameters, relative speed, and diffuser vane angle (DVA).
• To demonstrate the superiority of the proposed model over existing prediction methods.

Main Methods:

• A prediction model was developed using an elliptical equation to fit VGC speed lines (pressure ratio and efficiency maps).
• Partial least-squares (PLS) regression was employed, incorporating coefficients from the elliptical equation to model the relationship with relative speed and DVA.
• The maximal polynomial order was investigated to balance fit accuracy and model complexity.

Main Results:

• The developed model demonstrated acceptable prediction accuracy for VGC performance.
• Validation against sample data confirmed the model's reliability.
• Comparative analysis showed the new model outperformed look-up table and back-propagation neural network (BPNN) methods.

Conclusions:

• The proposed elliptical equation and PLS-based model offers a novel and effective solution for VGC performance prediction.
• This model is more suitable than look-up tables and BPNNs for VGC performance prediction under similar conditions.
• The model can enhance the accuracy of thermodynamic models for turbocharged diesel engines.