2015
DOI: 10.4271/2015-01-1288
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A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers

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Cited by 15 publications
(9 citation statements)
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“…By substituting equation (7) and c pa = kR=(k À 1) into equation (17), C 2 is obtained as 18can be modified as…”
Section: No Cross Flow Takes Place Throughout the Compres-mentioning
confidence: 99%
See 1 more Smart Citation
“…By substituting equation (7) and c pa = kR=(k À 1) into equation (17), C 2 is obtained as 18can be modified as…”
Section: No Cross Flow Takes Place Throughout the Compres-mentioning
confidence: 99%
“…For instance, Wahlstrom and Eriksson 6 replaced the inverse proportional function with an ellipse function. Canova et al 7 proposed a relationship between the JK model empirical coefficients and compressor geometry parameters, such as rotor diameter, Trim, and area/radius (A/R) ratio. Apart from c-based models, a neural network approach 8 was also investigated, which was later shown by Paul and Kolmanovsky 9 to be not very effective in predicting mass flow rate.…”
Section: Introductionmentioning
confidence: 99%
“…Canova developed a Δ P c,loss model using a semi-empirical correlation with respect to the blade Mach number and the Trim of the compressor. 7 However, this approach required a large compressor data set for parameter identification. Simpler control-oriented models 1,2,9,21,22 use a first-order dynamic to represent the compressor power.…”
Section: Introductionmentioning
confidence: 99%
“…Canova et.al. 7 proposed another correlation between η t and the expansion ratio (ER), with coefficients being a function of the TC geometry parameters and rotational speed, among others. Unfortunately, this approach required a large data set for identification, and the application for VGT systems was not discussed.…”
Section: Introductionmentioning
confidence: 99%
“…The under-fitting phenomenon may occur if the structure is too simple and the quantity of nodes is too less; on the other hand, although the prediction capability of the neural network may improve to some extent by increasing its structural complexity and the number of nodes, its generalization ability may degrade, i.e., over-fitting phenomenon may occur; • Curve fitting method (empirical, semi-empirical, or mean value models). This method is widely used for predicting the working characteristics of compressors, mainly owing to its simpler and much more compact model structure than their theoretical counterparts, as well as their satisfactory predictive and extrapolation ability [3,6,[16][17][18][19][20][26][27][28][29]. The curve fitting method can be further divided into two sub-categories: Some studies directly fit the relationship between the rotational speed, mass flow rate, pressure ratio, and isentropic efficiency with appropriate functions; while some researchers utilize suitable functions to fit the relationship between Because the ultimate purpose of this paper is to find a compressor model that is most suitable for the modeling of marine two-stroke diesel engine used for the marine engineering simulator, which has a relatively high requirement on both simulation speed and predictive accuracy, so only the empirical models developed with the curve fitting method are compared and analyzed in this paper owing to their simplicity, superior time-efficiency, and satisfactory predictive ability.…”
mentioning
confidence: 99%