NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020!

CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including:
-What is the future for engineering analysis and simulation?
-Where will it lead us in the next decade?
-How can designers and engineers realize its full potential?
What are the business, technological, and human enablers that will take past successful developments to new levels in the next ten years?

Resource Abstract

Physically developing and performing trials on new battery compositions and cooling strategies is an expensive and resource intensive process that only large funded organizations and laboratories have the facilities to perform successfully. In this paper, we would like to address how simulation would assist in minimizing the research, analysis, and experiments to analyze the behavior of battery systems where there is a need for strongly coupled resolution of flow, heat transfer, electrochemistry and stress due to expansion and contraction during operation to provide the best possible prediction to maintain the integrity of the system and identifying potential problems at an early stage. Now, introducing aging mechanisms into this creates a complex but realistic model which is predictive of the battery pack’s performance for a real world driving cycle.



This paper presents a case study for a commercial light weight sports EV which considers the multiphysics aspects of pack: electrochemistry, thermal, stress and aging mechanisms. Firstly, the cell is characterized and then the pack level cooling is developed to achieve the required range based on an aggressive drive cycle. Finally, we will demonstrate the performance of a full system level simulation to capture various interactions such as control on pack level integration.



Different approaches are used for modeling of lithium-ion batteries and their aging. The most realistic cell models are physics ones which simulate mostly single aging effects such as SEI growth, lithium plating, electrolyte decomposition, and corrosion of electrodes, etc. However, these models are very slow and complex to parameterize. Therefore, they are not suitable for aging prediction on a long-time scale hence an empirical aging model would be suitable. For an aging prediction a lot of different aging factors must be accounted for - e.g. temperature, storage voltage and time for calendar aging and, in addition, cycle depth, SOC range, current rate and charge throughput for cycle aging considering both calendar and cyclic aging. This paper presents a case study for a commercial light weight sports EV. Firstly, the cell is characterized and then the pack level cooling is developed to reach the achieve the required range based on an aggressive drive cycle.



In all, it is becoming more vital to analyze packs and modules through simulation to capture the complexity of the management of thermal, stress and aging of cells at the component and system level.