Today, the laws of traditional thermodynamics are facing challenges when science is growing rapidly toward the microscale-world, even quantum hypothesis. In this work, the thermodynamics of nano-confinement and quantu...Today, the laws of traditional thermodynamics are facing challenges when science is growing rapidly toward the microscale-world, even quantum hypothesis. In this work, the thermodynamics of nano-confinement and quantum thermodynamics are summarized to illustrate their developments at the microscales.展开更多
The real-time model-based control of polymer electrolyte membrane(PEM)fuel cells requires a computationally efficient and sufficiently accurate model to predict the transient and long-term performance under various op...The real-time model-based control of polymer electrolyte membrane(PEM)fuel cells requires a computationally efficient and sufficiently accurate model to predict the transient and long-term performance under various operational conditions,involving the pressure,temperature,humidity,and stoichiometry ratio.In this article,recent progress on the development of PEM fuel cell models that can be used for real-time control is reviewed.The major operational principles of PEM fuel cells and the associated mathematical description of the transport and electrochemical phenomena are described.The reduced-dimensional physics-based models(pseudo-twodimensional,one-dimensional numerical and zero dimensional analytical models)and the non-physics-based models(zero-dimensional empirical and data-driven models)have been systematically examined,and the comparison of these models has been performed.It is found that the current trends for the real-time control models are(i)to couple the single cell model with balance of plants to investigate the system performance,(ii)to incorporate aging effects to enable long-term performance prediction,(iii)to increase the computational speed(especially for one-dimensional numerical models),and(iv)to develop data-driven models with artificial intelligence/machine learning algorithms.This review will be beneficial for the development of physics or nonphysics based models with sufficient accuracy and computational speed to ensure the real-time control of PEM fuel cells.展开更多
基金National Natural Science Foundation of China (21878296)Beijing Municipal Natural Science Foundation (20B10125)National Key Projects for Fundamental Research and Development of China (2019YFA0705600) for the financial support。
文摘Today, the laws of traditional thermodynamics are facing challenges when science is growing rapidly toward the microscale-world, even quantum hypothesis. In this work, the thermodynamics of nano-confinement and quantum thermodynamics are summarized to illustrate their developments at the microscales.
基金This work received financial support from Toyota Motor Engineering&Manufacturing North America,Inc.,Toyota Motor Manufacturing Canada,and Natural Sciences and Engineering Research Council of Canada through a Collaborative Research and Development Grant with the project number of CRDPJ 543945-19.
文摘The real-time model-based control of polymer electrolyte membrane(PEM)fuel cells requires a computationally efficient and sufficiently accurate model to predict the transient and long-term performance under various operational conditions,involving the pressure,temperature,humidity,and stoichiometry ratio.In this article,recent progress on the development of PEM fuel cell models that can be used for real-time control is reviewed.The major operational principles of PEM fuel cells and the associated mathematical description of the transport and electrochemical phenomena are described.The reduced-dimensional physics-based models(pseudo-twodimensional,one-dimensional numerical and zero dimensional analytical models)and the non-physics-based models(zero-dimensional empirical and data-driven models)have been systematically examined,and the comparison of these models has been performed.It is found that the current trends for the real-time control models are(i)to couple the single cell model with balance of plants to investigate the system performance,(ii)to incorporate aging effects to enable long-term performance prediction,(iii)to increase the computational speed(especially for one-dimensional numerical models),and(iv)to develop data-driven models with artificial intelligence/machine learning algorithms.This review will be beneficial for the development of physics or nonphysics based models with sufficient accuracy and computational speed to ensure the real-time control of PEM fuel cells.
