Hydrogen is attracting attention as a good energy-storage medium for renewable energy. Among hydrogen production technologies using renewable energy, water electrolysis is drawing attention as a key technology for green hydrogen production using renewable energy. In particular, polymeric electrolyte membrane water electrolysis systems have several advantages compared to other types of water electrolysis technologies, such as small size and mass, high efficiency, low operating temperature, and low power consumption. However, until now, proton-exchange membrane (PEM) water electrolysis systems have not been reliable. In this study, system failure diagnosis techniques were presented among the various methods for improving reliability. We developed PEM water electrolysis stack models and system models to predict the performance of the system and analyze the dynamic properties using MATLAB/Simulink^® 2018a, which have been validated under various conditions. The developed dynamic characteristic simulation model applies hardware-in-the-loop simulation (HILS) technology to configure experimental devices to interact in real-time. The developed PEMWE HILS system accepts signals that control the system, operates the experimental setup and simulation model in real-time, and diagnoses the system’s failure based on the results.

With an increase in global warming, battery electric vehicles (BEVs), which are environmentally friendly, have been rapidly commercialized to replace conventional vehicles with internal combustion engines. Unlike traditional internal combustion engine vehicles, the powertrain system of BEVs operates with high efficiency, resulting in lower heat generation. This poses a challenge for cabin heating under low-temperature conditions. Conversely, under high-temperature conditions, the operating temperature of a high-voltage battery (HVB) is lower than the ambient air temperature, which makes cooling through ambient air challenging. To overcome these challenges, in this study, we proposed an integrated thermal management system (ITMS) based on a heat pump system capable of stable thermal management under diverse climatic conditions. Furthermore, to assess the ability of the proposed ITMS to perform thermal management under various climatic conditions, we integrated a detailed powertrain system model incorporating BEV specifications and the proposed ITMS model based on the heat pump system. The ITMS model was evaluated under high-load-driving conditions, specifically the HWFET scenario, demonstrating its capability to perform stable thermal management not only under high-temperature conditions, such as at 36 °C, but also under low-temperature conditions, such as at −10 °C, through the designated thermal management modes.

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are a new trend for the vehicle industry, due to the environmental regulations of the internal combustion engine (ICE) and pollutant emission of transportation. However, despite being very promising, the durability of the battery, due to overheating, is still an obstacle. In particular, electric vehicle batteries are manufactured with high voltage and high capacity to ensure power and energy efficiency. For this reason, a high temperature is generated in the system, which reduces the battery performance and life cycle. In this study, three different layouts, based on a direct contact air-cooled system, are designed to compare and improve the cooling performance. Further, a battery cooling test is conducted to verify the designed model. The results show that the spoiler model reduces the maximum battery temperature by (about) 16%, and effectively improves the temperature distribution of the battery cell by (about) 65%, when compared with a conventional cooling method without a spoiler.

In this study, transient responses of a polymer electrolyte fuel cell system were performed to understand the effect of sensor fault signal on the temperature sensor of the stack and the coolant inlet. We designed a system-level fuel cell model including a thermal management system, and a controller to analyze the dynamic behavior of fuel cell system applied with variable sensor fault scenarios such as stuck, offset, and scaling. Under drastic load variations, transient behavior is affected by fault signals of the sensor. Especially, the net power of the faulty system is 45.9 kW. On the other hand, the net power of the fault free system is 46.1 kW. Therefore, the net power of a faulty system is about 0.2 kW lower than that of a fault-free system. This analysis can help in understanding the transient behavior of fuel cell systems at the system level under fault situations and provide a proper failure avoidance control strategy for the fuel cell system.