کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1731868 1521459 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling and extrapolating mass flow characteristics of a radial turbocharger turbine
ترجمه فارسی عنوان
مدل سازی و استخراج ویژگی های جریان جرمی توربین توربوشارژر شعاعی
کلمات کلیدی
خصوصیات جریان جرمی توربین توربو شارژر رادیال، درجه واکنش عملکرد فوق العاده تجزیه و تحلیل رگرسیون
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی


• A physical based turbine model of mass flow characteristics is proposed.
• Existing turbine mass flow models are reviewed and summarized.
• Comparative analyses of the deduced model and existing models are conducted.
• Interpolating and extrapolating abilities of the deduced model are evaluated.

Since the turbocharger turbine plays an important role in determining the engine performance, how to model and extrapolate mass flow characteristics of the turbocharger turbine is very important especially when only a narrow range of turbine data is provided by manufacturers. In this paper, a new mass flow model is proposed based on the physical model of a radial turbine simplified as two nozzles in series. With the ideal nozzle flow equation applied on the turbine stator, the mass flow rate through the turbine can be expressed with three fitted coefficients which have clear physical meanings. Existing empirical and partly empirical models of turbine mass flow characteristics are reviewed and compared with the deduced model in the Matlab software. The results show that considering the number of fitted coefficients and the modeling accuracy, the deduced model performs well in regression analyses conducted with experimental data tested from three radial turbines of different sizes. Also interpolating and extrapolating performances of this new model can match the turbine model in the GT-Power commercial software. Thus this new model is sufficiently robust to model and extrapolate mass flow characteristics of the radial turbocharger turbine at off design operating conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 87, 1 July 2015, Pages 628–637
نویسندگان
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