Collaborative Research: Model Reformulation for Lithium-ion Batteries -- Parameter Estimation and Dynamic Optimization

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CBET-0828002SubramanianThe PIs will pursue a wide range of activities in modeling, parameter estimation and dynamic optimization of Lithium-ion batteries. While physics-based models have been widely developed and studied for these systems, the rigorous models have not been employed for parameter estimation or dynamic optimization of operating conditions. This is an unexplored area requiring model reformulation and approximations for efficient simulation of coupled partial differential equations. Along these lines, this is an in-depth analysis of model reformulation to facilitate (1) parameter estimation for understanding capacity fade of Lithium-ion batteries and (2) dynamic optimization technique to optimize the usability and efficiency of future power sources.Research ObjectivesSpecific research objectives include:* Reformulated efficient physics-based models for Lithium-ion batteries: reformulate and develop efficient models by careful analysis and analytical/approximate methods for rigorous numerical models with the aid of various advanced mathematical methods including analytical solution of banded matrix equations, decoupling coupled equations, etc.* Prediction of capacity fade in Lithium-ion batteries by keeping track of the change of transport and kinetic parameters with cycle numbers.* Optimum operating conditions: develop, validate, and implement ideal operating conditions to minimize utilization loss and maximize energy efficiency (and hence reduce the specific weight) of Lithium-ion batteries by performing dynamic optimization on reformulated-efficient models.Intellectual Merit* The reformulated physics-based models for Lithium-ion batteries will have CPU times two orders-of-magnitude lower than the current state-of-the-art.* The reformulated models are more amenable for parameter estimation and dynamicoptimization while the current state-of-the-art transport phenomena models are computationally inefficient.* The work will help predict and understand capacity fade in Lithium-ion batteries by tracking changes in the parameters with cycles. This will help design better batteries for the future. The proposed work will optimize the operating conditions of batteries for high energy and utilization efficiency.Broader Impacts* The model reformulation technique will be applicable for a wide range of engineering problems like monolith reactors, fuel cells, bioreactors, etc. Training and development of a wide range of battery/fuel cell professionals, ranging from engineers and researchers to educators. Crucial to maintaining national preeminence in the field.* Increased participation of under-represented groups in engineering research. Dissemination of results through peer-reviewed research articles, presentations and website for research modules will have an impact on student and research community worldwide.* Develop user-friendly modules to aid experimental researchers in modeling electrochemical power sources.* A new addition to the existing graduate course that trains the students in model reformulation of electrochemical power sources.