Engineering Applications of Predictive Control Algorithms for Thermal Management of Fuel Cell Systems

<div class="section abstract"><div class="htmlview paragraph">The advancement of clean energy technology has resulted in the emergence of fuel cells as an efficient and environmentally friendly energy conversion device with a diverse range of potential applications, including those in the fields of transportation and power generation. Among the challenges facing fuel cell technology, thermal management represents a significant technical hurdle. The advancement of innovative thermal management methods and system design is imperative to address issues such as high waste heat. In light of the above, this paper presents a methodology for the application of fuel cell thermal management predictive control algorithms in engineering, with a particular focus on fuel cell engine systems that have been implemented in fuel cell cars. This paper proposes a thermal management control method based on a model predictive control algorithm for proton exchange membrane fuel cell systems. The objective of the methodology is to predict and adjust the thermal management strategy in real time, in accordance with the operational status of the fuel cell and environmental fluctuations. The study employed both bench tests and vehicle tests for the purpose of analyzing the control effect. The results demonstrate that the key technical indicators, including the temperature difference between the stack inlet and outlet and the stack inlet temperature, are in alignment with the system target requirements. The algorithm is capable of accurately predicting the temperature trend and achieving more precise temperature control, thereby markedly enhancing the efficiency and stability of the fuel cell. Consequently, this algorithm offers novel insights and methodologies for optimizing the fuel cell thermal management strategy and provides a new framework for addressing the thermal management challenges of fuel cell vehicles.</div></div>