Batman University

About: Batman University is a education organization based out in Batman, Turkey. It is known for research contribution in the topics: Diesel fuel & Diesel engine. The organization has 300 authors who have published 810 publications receiving 10346 citations. The organization is also known as: Batman Üniversitesi.

Optimal PID Controller Design of DC-DC Buck Converter using Whale Optimization Algorithm

Abstract: This paper presents a novel design method to determine optimal proportional-integral-derivative (PID) controller parameters of a DC-DC buck converter using the whale optimization algorithm (WOA). The simplicity of the proposed algorithm provides fast and high quality tuning of optimum PID controller parameters effectively. The performance of the proposed WOA-based PID controller is validated using a time domain performance index. From simulation results, the proposed method compared to the genetic algorithm was found more efficient in improving the transient response of Buck converter.

Determination of thermodynamic properties of an alternative refrigerant (R407c) using artificial neural network

Abstract: Thermodynamic analysis of the refrigeration systems is too complex because of thermodynamic properties equations of working fluids, involving the solution of complex differential equations. To simplify this complex process, this paper proposes a new approach (artificial neural network, ANN) to determine of thermodynamic properties of an environmentally friendly alternative refrigerant (R407c) for both saturated liquid-vapor region (wet vapor) and superheated vapor region. Instead of complex rules and mathematical routines, ANNs are able to learn the key information patterns within multidimensional information domain. Therefore, reducing the risk of experimental uncertainties and also removing the need for complex analytic equations requiring long computational time and efforts. R^2 values - which are errors known as absolute fraction of variance - in wet vapor region are 0.999706, 0.999949, 0.999909, 0.999988 and 0.999836 for specific volume, enthalpy, entropy, viscosity and thermal conductivity for training, respectively. Similarly, for superheated vapor, they are: 0.99992, 1, 0.99998, 0.99995 and 0.99996 for training data, respectively. Promising thermodynamics property results have been obtained for R407c within acceptable errors. PVTx properties predicted are in valid region for working conditions of the refrigeration systems in case of use to computer simulation programs.