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Given the uncertainties associated with proton-exchange membrane fuel cell systems and relatively low efficiency of the fuel cell stacks for low-power applications, designing a high-efficiency maximum power point tracking (MPPT) controller for the fuel cell electric vehicles is an important and also technically challenging issue. For this purpose, in this article, aiming to develop a high-efficiency and low cost battery charger, a novel self-tuning type-2 fuzzy MPPT controller is presented. The main task of the controller is to provide the better performance and regulate the switching duty cycle of the used power converter under the system's uncertainty conditions in order to dynamically extract the maximum power from the fuel cell system and maintain the battery at its highest possible state of charge while protecting it from overcharging. For the sake of computational efficiency, an improved invasive weed optimization algorithm, called elitist invasive weed optimization (EIWO), is also presented to tune the type-2 fuzzy set parameters, whose improvement is demanding due to the limited human experience and knowledge. All data processing and simulations are conducted in the MATLAB software. Finally, the performance of the proposed MPPT controller is examined through using experimental tests with a prototype device. Image 1 • A novel self-tuning type-2 Fuzzy controller is proposed to extract MPPT from PEMFC stack. • An improved optimization algorithm is developed to optimize controller parameters. • Developed controller dictates the duty cycle of the converter and the cooling fans speed. • Validations of proposed controller are carried out via simulation/experimental results. [ABSTRACT FROM AUTHOR]