Grants and Contributions:
Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)
Electrochemical devices play an important role in the drive towards a sustainable energy environment: energy storage (batteries, fuel cells, supercapacitors), hydrogen production, electro-incineration of wastewater or carbon sequestration. These devices are integrated within a system that includes power conversion equipment, controllers and an electrical grid.
Operationally, energy storage devices, electrolyzers and electroincinerators have different performance metrics and end user requirements but a similar mathematical model structure. Information gained from analyzing one system can be applied to the other systems with only minor changes to the modeling procedure. In this proposal we focus on improved models and an improved design methodology for energy storage devices.
An accurate quantitative analysis of device performance, in an application environment, is currently not attainable due to gaps in our understanding of physical processes occurring at an interface which is not fully accounted for in existing mathematical models. A mathematical model that is derived from first principles and is computationally efficient to simulate is required in so far as
• predicting the electrical, mechanical and thermal properties of the device, for an arbitrary excitation condition.
• exploring new manufacturing or material systems that could lead to increased performance or functionality, lower cost, the use of low toxicity materials, lower weight, safer operation and longer operating lifetimes.
• determining the role of electrolyte type and concentration, electrode surface impurities, surface morphology and structural deformations on device characteristics.
• designing controllers for the power conversion equipment.
The objective of this proposal, over the longer term, is six-fold: to develop a modeling methodology that can incorporate new physics and is expandable, to determine a discretization scheme and numerical method that ensures speed of convergence and stability, to develop experimental voltammetry and impedance spectroscopy emulation tools that produce results that can be compared to experimental results, to develop system identification tools that can be used to establish transport and thermodynamic coefficients for systems with built in uncertainty, to develop a model order reduction method that retains unobservable state variables but that leads to a model that can be embedded within commercial circuit simulators and shorten simulation execution times and to develop an in-situ real time diagnostic tool that can monitor the state of health of an electrochemical system using a reduced order model.
The impact of this technology is a reduction in life cycle costs, the development of new simulation tools that can be used to investigate different design scenarios and a reduced time to design new systems and to train technicians and engineers.