A Novel development of soft computing based hybrid power point tracking controllers for hydrogen vehicle application with new wide source DC-DC converter

Abstract

From the present power generation scenario, most of the power production companies are focusing on renewable energy systems because their merits are easy to install, more reliable power sources, free from atmospheric pollution, and better adaptable to all weather conditions. In this article, a Polymer Electrolyte Membrane Fuel Cell (PEMFC) module is selected in the first objective to produce constant and continuous power to the hydrogen-based electrical vehicle systems. This fuel module provides fast power production and gives good energy density. However, the demerits of this module are more current production and low-level voltage generation. A new single-switch DC-DC circuit is introduced in the second objective of this work for optimizing the current levels of the fuel module thereby reducing the source power loss of the proposed system. Here, another problem of the fuel module is nonlinear power production which is linearized by proposing the Cuckoo Search Optimization (CSO)-based Adaptive Network-based Fuzzy Inference System (ANFIS) in the third objective to extract the maximum voltage from the fuel module. The merits of this introduced Maximum Power Point Tracking (MPPT) Controller are better tracking speed, low-level disturbances in the consumer load power, high robustness, more sustainability, and easy operation. The entire proposed system is investigated by selecting the MATLAB Simulink tool. The introduced converter circuit is analyzed by selecting the programmed DC supply.

Keywords

• Booster circuit
• Better MPPT dynamic response
• Efficiency of MPP
• High reliability
• Fewer disturbances at MPP
• Quick fuel stack response