Simulation Techniques for Design and Evaluation of Safe and Reliable Energy Storage Systems
Abstract
The Power Electronic Power Distribution System (PEPDS) program requires multiple areas of science and technology for modeling and simulation as tools for design and analysis. Previous ONR-sponsored research at Temple University s Electric Vehicle Safety Lab (EVSL) and Dynamical Systems Lab (DSLab) has provided several components required for the modeling and simulation of advanced energy storage systems under combined electrical, mechanical, and thermal loading. The research was divided into three main components, including 1-mechanical, 2-electrical/electrochemical, and 3-combined mechanical/electrical specifications and modeling. This proposal aims to create advanced high fidelity and fast simulation techniques for design and evaluation of safe energy storage systems, such as Lithium-ion Batteries (LIBs) in Navy PEPDS. We will build on our previous studies to develop multi-physics models of the cells, takinginto account effects of mechanical loading, state of charge, temperature, and dynamic loads. The models will combine the cells mechanical and electrical responses to predict their behavior in cases of impacts and mechanical shocks and deformations. Further, we will develop interpretable machine learning dynamic models of the batteries to discover governing equations of the cells for mechanical safety, state-of-charge, and state-of-health estimations. These equations will allow for health monitoring and management of batteries under normal use or aggressive applications. To develop safe, cost efficient and lightweight systems, it is important to understand the complexities in the mechanical response of lithium-ion battery packs and the interactions with their electrochemical performance. This knowledge will allow design of optimized protective structures and mitigating countermeasures. Development of a high-fidelity model for battery cellsDevelopment of a multi-scale modeling techniqueMulti-physics modeling for crash applicationsDevelopment of a damage detection algorithm Data-Driven Modeling:Investigating effects of shock
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 24, 2023
- Source ID
- N000142312612
Entities
People
- Elham Sahraei
Organizations
- Office of Naval Research
- Temple University
- United States Navy