A fuel cell is an electrochemical energy conversion device that uses fuel to generate electricity. It basically converts the chemical energy of reactants directly into electricity without combustion. In a Proton Exchange Membrane Fuel Cell (PEMFC), the reactants, hydrogen and oxygen, are fed into the two electrodes, anode and cathode, respectively. A reaction takes place at each electrode and produces electricity, as well as water, and heat as the by-products. In order to maximize performance of a fuel cell, many factors can be considered for tuning and control. Temperature management is one of these factors.

A thermal-fluid model of a PEMFC has been developed as part of this work to predict the temperature responses to changes in input during operation. A control method was designed based on the thermal-fluid model to maintain a consistent operating temperature which allows optimization of the fuel cell performance.

A 6 kW Nedstack PEMFC stack model was developed using MATLAB and Simulink. A conventional PID controller was used to control the thermal response of the PEMFC system. Additionally, a Fuzzy Logic Controller (FLC) was also developed to explore further performance optimization of the PEMFC in comparison to the baseline results provided by the PID controller. The FLC was designed and tested for preliminary results to be ready for future expansion and adjustments. Both control methods had two input variables: air flow rate (manipulated variable) and current (disturbance variable). The output was set to be the stack temperature which is directly related to the performance of the PEMFC.

Results show that manipulating the air flow rate plays an important role in controlling the stack temperature, with an inversely proportional relationship. During nominal operation, the temperature of the stack at steady state is relatively high. However, when increasing the air flow rate, the stack temperature decreases. Other factors and disturbances may affect the stack temperature which justify the implementation of a controller. A PID and a Fuzzy-logic controller are utilized. The models show promising results opening the door to many additional possibilities for investigations better to understand the behavior of the thermal response of the fuel cell, especially in the case of using a fuzzy logic controller for such a system.

Date of publication

Summer 8-27-2020

Document Type




Persistent identifier


Committee members

Mohammad Abu Rafe Biswas, Ph.D., Nael Barakat, Ph.D., Chung Hyun Goh, Ph.D.


M - Mechanical Engineering