From Atoms to Wheels: The Role of Multi-Scale Modeling in the Future of Transportation Electrification

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The entropy coefficient of a battery cell is the property that governs the amount of reversible heat that is generated during operation. In this work, we propose an extension of the Multi-Species, Multi-Reaction (MSMR) model to capture the entropy coefficient of a large format lithium-ion battery cell. We utilize the hybridized time-frequency domain analysis (HTFDA) method using a multi-functional calorimeter to probe the entropy coefficient of a large format pouch type lithium-ion battery with a NMC 811 cathode and a graphite anode. The measured entropy coefficient profile of the battery cell is deconvoluted into an entropy coefficient for each active material, which is then estimated using an extension of the MSMR model. Finally, we extend the entropy of a material to individual entropy for each gallery as treated by the model.

Section: Resultsmentioning

confidence: 99%

Quantifying the Entropy and Enthalpy of Insertion Materials for Battery Applications Via the Multi-Species, Multi-Reaction Model

Garrick,

Koch,

Choi

et al. 2024

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“…Prior to manufacturing the battery cell, battery models can be utilized to drive design by linking the performance requirements of a battery cell in a particular system to the electrode and material level design choices during the development phase. 1 After a battery has been implemented into the target system, battery models are developed to predict the physical state of a battery and track degradation dynamics to optimize performance, efficiency, and long-term health. 2 Battery Management Systems (BMS) sustain safe battery operating conditions, manage thermal loads, and perform fault detection during operation to detect scenarios that lead to undesired events.…”

mentioning

confidence: 99%

Perspective—Moving Next-Generation Phase-Field Models to BMS Applications: A Case Study that Confirms Professor Uzi Landau’s Foresight

Telmasre,

Concepción,

Kolluri

et al. 2024

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Physics-based electrochemical models play a prominent role in the model-based analysis, virtual engineering, and Battery Management Systems (BMS) of lithium-ion and next-generation batteries. In this paper, we demonstrate the rich physics of phase-field models and convey their potential in BMS applications. Our phase-field model-based optimization framework predicts an impulse-like control profile to reduce capacity degradation. This work was partially inspired by the pulse-charging protocol proposed by Professor Landau in his 2006 work [B. K. Purushothaman and U. Landau, J Electrochem Soc, 153(3), A533 (2006)]. An open-source framework is shared for predicting the (im)pulse protocol reported in this paper.

“…The large format battery cells used in this study were from the GMC Hummer EV Pickup electric vehicle as reported in our previous work. [46][47][48] The cells used here have a capacity of 101.8 Ah at a C/3 discharge rate. The cell is built with a stacking construction with alternating cathodes and anodes with separators placed in between.…”

Section: Methodsmentioning

confidence: 99%

“…Silicon and other high-capacity anode materials undergo significant volume change [19][20][21][22][23] during lithiation, [24][25][26] which can ultimately impact the performance of the battery pack and electric vehicle due to the engineering changes that must be made to account for the silicon volume change. Additionally, a desire exists to increase the speed 27 at which battery cell designs move from concept to production reality. To that end, using virtual methods to drive cell and system level changes for electric vehicles and grid storage becomes critical, and in turn, quantifying the impact of lithiation induced volume changes in any battery cell active material is necessary to drive the virtualization of the design and prototyping phase for electric vehicle development.…”

Section: Background and Introductionmentioning

confidence: 99%

Modeling Rate Dependent Volume Change in Porous Electrodes in Lithium-Ion Batteries

Garrick,

Fernandez,

Koch

et al. 2024

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Automotive manufacturers are working to improve individual cell, module, and overall pack design by increasing the performance, range, and durability, while reducing cost. One key piece to consider during the design process is the active material volume change, its linkage to the particle, electrode, and cell level volume changes, and the interplay with structural components in the rechargeable energy storage system. As the time from initial design to manufacture of electric vehicles decreases, design work needs to move to the virtual domain; therefore, a need for coupled electrochemical-mechanical models that take into account the active material volume change and the rate dependence of this volume change need to be considered. In this study, we illustrated the applicability of a coupled electrochemical-mechanical battery model considering multiple representative particles to capture experimentally measured rate dependent reversible volume change at the cell level through the use of an electrochemical-mechanical battery model that couples the particle, electrode, and cell level volume changes. By employing this coupled approach, the importance of considering multiple active material particle sizes representative of the distribution is demonstrated. The non-uniformity in utilization between two different size particles as well as the significant spatial non-uniformity in the radial direction of the larger particles is the primary driver of the rate dependent characteristics of the volume change at the electrode and cell level.