Performance comparison of Honey Bee Mating Optimization algorithms for Fuel Cell operating parameters

Fuel cells are emerging as a promising source of green energy that emit electrical energy with almost no pollutants. Fuel cell technology highlights a vital role in the evolution of alternative energy which can be applied for all future applications such as automobile, stationary power plants and to power up devices like mobiles and laptops. One of the most attractive fuel cell types is the polymer electrolytic membrane fuel cells (PEMFCs) due to its ability to operate at low temperature conditions, low corrosion, low weight and quick start-up, which widens its area of applications. There are many operating parameters of PEMFC such as temperature, pressure, flow rate, voltage etc. affecting the overall system efficiency in PEMFC. Controlling the operating parameters of PEMFC is important as it affects the performance, lifetime, working and the response times. In this project, we are focusing on optimization of PEM Fuel Cell. Among these different parameters two are considered to optimize: Flow rate and Pressure. For this optimization problem, different algorithms are compared in this project and the one that best optimizes PEMFC parameters is selected after simulation and analysis. Finally, genetic algorithm is implemented into which holds advantage and from this, selected algorithms are also included into GA. Since, GA is a powerful and dependable innovation to optimize fuel cell stack model. A review of recent research indicates that GAs and other computational intelligence techniques are likely to dominate PEMFC modeling efforts in the future. And the outcome is confirmed to be effective.