A reduced-order model of twin-entry nozzleless radial turbine based on flow characteristics

Jiangshan Wei, Yingxian Xue, Mingyang Yang, Kangyao Deng, Cuicui Wang and Xintao Wu

Energy, 2021, vol. 214, issue C

Abstract: Twin-entry radial turbine has evident advantages on energy recovery of internal combustion engine because of better utilization of exhaust pulse energy. One-dimensional performance prediction plays an important role in automobile industry because of the cost-effective feature. However, as twin-entry turbine is confronted by out-of-phase pulses, to capture the flow distortion by twin-entry turbine model is challenging, especially under partial admission conditions. This paper establishes a reduced-order parallel-rotor model for performance prediction of twin-entry nozzleless radial turbine based on internal flow characteristics. Firstly, twin-entry turbine experiment and 3D simulation are applied to analyze the different flow features under partial admission conditions. The flow distortions in the spanwise and circumferential directions are both demonstrated. Based on these flow characteristics, a reduced-order twin-entry turbine model with parallel rotor passages is established for predicting the rotor at distorted flow field. Finally, the model is carefully validated against the results of CFD. The results show that satisfied consistency can be obtained and the maximum discrepancy of turbine performance is 3.8% and the performance difference and flow distortion under partial admissions can be captured, thus prove the credibility of the model. This investigation provides a reliable methodology for performance prediction and behavior analysis of twin-entry turbine.

Keywords: Reduced-order model; Twin-entry turbine; Parallel rotor passage; Performance prediction; Partial admission (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:214:y:2021:i:c:s0360544220319976

DOI: 10.1016/j.energy.2020.118890

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