This paper presents a comparative study of different methods of identifying and modelling a 2.2KW cage induction machine. It includes the semi-empirical (classical), analytical, equivalent scheme and an iterative method which uses the... more
This paper presents a comparative study of different methods of identifying and modelling a 2.2KW cage induction machine. It includes the semi-empirical (classical), analytical, equivalent scheme and an iterative method which uses the results of the classical method. The reasoning and demonstration that leads to the equations used for the calculation are also included in this work. The experimental approach, the schematics of the set-ups and the data obtained during the experimental tests are also included. The calculation is been done in the MATLAB environment. One of the methods used showed the existence of an electrical defect in the machine, so the results calculated in this paper are those of a defective machine. Key words: induction machine, ASM, identification, defect.
A parametric model predicting the performance of a solid polymer electrolyte, proton exchange membrane (PEM) fuel cell has been developed using a combination of mechanistic and empirical modeling techniques. This paper details the... more
A parametric model predicting the performance of a solid polymer electrolyte, proton exchange membrane (PEM) fuel cell has been developed using a combination of mechanistic and empirical modeling techniques. This paper details the empirical analysis which yielded the parametric coefficients employed in the model. A 28 run experiment covering a range of operating currents (50 to 300 ASF), temperatures (328 to 358 K), oxygen partial pressures (0.6 to 3.1 atm abs.) and hydrogen partial pressures (2.0 to 3.1 aim abs.) was conducted. Parametric equations for the activation overvoltage and the internal resistance of the fuel cell were obtained from linear regression. The factors to be employed in the linear regression had been previously determined through a mechanistic analysis of fuel cell processes. Activation overvoltage was modeled as a function of the operating temperature, the product of operating temperature, and the logarithm of the operating current, and the product of operating temperature and the logarithm of the oxygen concentration at the catalyst reaction sites. The internal resistance of the fuel cell was modeled as a function of the operating temperature and the current. Correlation of the empirical model to experimental data was very good. It is anticipated that the mechanistic validity yielded by the coupling of mechanistic and empirical modeling techniques will also allow for accurate predictive capabilities outside of the experimental range. A mechanistic model defining the factors most likely to influence fuel cell performance has been described previously. I'2 The performance of a fuel cell (output voltage) was defined as a function of the thermodynamic potential, the activation overvoltage, and the ohmic overvoltage, with mass transport losses being incorporated in each of the three terms V = E + ~ot + ~lohm~ [1]
