Publications

© 2019 The Electrochemical Society. An experimental study of the module-to-module thermal runaway (TR) propagation in a multi-modular battery pack is presented here. During the experiment a cell in one of the modules is triggered by heating to study both cell-to-cell and module-to-module propagation. In order to understand the mechanism and gain insight into the thermal hazards of a battery pack system, the thermal characteristics of the cells in different modules are analyzed in detail. Although the TR-propagations are all triggered from the side next to the heater, the results indicate that the thermal characteristics of the modules vary in different phases. The upward direction of burning flame and heat flow highlight the importance of design considerations in a multi-modular battery pack.

A mixed mode solid electrolyte interphase (SEI) growth model is presented that includes both the influence of the kinetics of the solvent reduction reaction at the SEI/electrode interface and diffusion of the solvent through the SEI layer. The governing equations are solved numerically to predict the solvent concentration profile, the SEI layer thickness, and the capacity loss. Capacity loss predictions are fitted to two sets of experimental data from the literature. The high quality of the fits demonstrates that the mixed mode model provides a useful description of the capacity loss in the cell due to the growth of the SEI layer on the anode under constant voltage storage condition. Also, analytical expressions are presented for SEI growth for both the combined kinetics/diffusion mode (mixed mode model) and the limit of a fast solvent reduction reaction (diffusion limited mode model) as a function of cell characteristics.

Six experiments are presented to validate the testing methods given in TR-propagation regulation (TF5) being developed by The Electrical Vehicle Safety - Global Technical Regulation (EVS-GTR). The novel testing methods in TF5 draft are present here and used on six different battery packs exposed to thermal runaway. The characteristics of the thermal runaway propagation of the EV battery packs with different designs are investigated. Some of the experiments use the same sample with different heater powers. The result indicated that heater power does not affect the maximum temperature very much, but rather the propagation time. The feasibility of the test approach is demonstrated by the test results. However, the repeatability of the test approach requires improvement.

Alkaline-based metal-air batteries require a low-resistance, bifunctional oxygen electrode to perform fast oxygen reduction and oxygen evolution reactions (ORR/OER) during discharging and charging cycles, respectively. However, achieving good ORR/OER bifunctionality with single materials has proven challenging. Here we report a composite material as a bifunctional oxygen electrode for ORR and OER. The composite oxygen electrode consists of an ORR-active 20 wt% Pt/C and an OER-active perovskite La0.6Sr0.4CoO3-$δ$ (LSCO). The study focuses on identifying the optimal LSCO:Pt/C ratio through electrochemical DC voltammetry techniques. The results show that the addition of Pt/C into the LSCO catalyst greatly enhances the ORR activity, due to Pt/C s superior ORR capabilities, while LSCO retains good OER performance, which is known to be poor for Pt/C. The optimal LSCO:Pt/C ratio among the seven compositions studied is found to be 60:40 (wt%) and is tested for stability through using a square-wave potentiostatic method. Overall, this study demonstrates a synergetic effect between LSCO and Pt/C, with each one contributing towards one of the electrode reactions in a positive manner.

In this work, a perovskite-structured and oxygen-deficient oxide, La0.6Sr0.4CoO3-$δ$ (LSCO), has been investigated as a model bifunctional thin-film oxygen electrode for alkaline metal-air cells. The rotating disk electrode (RDE) configuration in combination with common electrochemical techniques such as linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS) were applied to characterize the behavior of the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) taking place on LSCO in 0.1 M KOH solution. The results show that the oxygen electrocatalysis process in LSCO follows a multistep charge-transfer pathway. A physics-based, generalized electrochemical model, encompassing two sequential 2e- steps with HO2- as an intermediate species and one parallel 4e- step, has been established to account for the multistep charge-transfer behavior with very satisfactory results, yielding a series of important electrode kinetic transfer coefficients and exchange current densities for the elementary electrochemical reactions considered. Finally, LSCO is found to be a better oxygen electrode for OER than ORR.

Oriented one-dimensional nanostructures have been of substantial interest as electrodes for lithium-ion batteries due to the better performance both in terms of initial capacity and lower capacity fade compared to powder pressed electrodes. This paper focuses on a model driven approach to understanding the relationship between the morphology of these oriented nanostructures to the performance of the battery. The Newman-type P2D modeling technique is applied to a porous electrode made up with solid continuous cylinders that extends from the current collectors to separator. TiO2 columnar nanostructures of varying heights were synthesized using the aerosol chemical vapor deposition (ACVD) and their performance as electrodes in a lithium-ion battery was measured. This electrochemical transport model was validated with the experimental data. This model was used to understand the role of transport parameters, including the diffusivity of lithium in the TiO2 and the electronic conductivity of the TiO2 columns, and structural parameters, including the height of the columns and the porosity of the electrode, on the areal capacity of a lithium ion battery at different rates of discharge. The model enables for the prediction of optimized structural parameters of one-dimensional electrodes tailored to the desired application of lithium and sodium-ion batteries.

This paper presents a mathematical model developed for predicting the temperature-pressure behavior and gas generation inside 18650 LCO/Graphite cells with a DMC (Dimethyl Carbonate) electrolyte. The cell was modeled using oven heating conditions, and the analysis was done at time intervals around the venting event. The paper also presents the thermodynamic property table for DMC, as extracted from different resources and calculated using various assumptions. The model was developed by deriving the energy balance for an unsteady-flow control volume and applying the isentropic flow equations corresponding to the venting of gas. The results show that the model fails to predict the pressure measured experimentally when no gas is generated inside. When adding the gas generation due to pre-venting reactions occurring, the model can predict the pressure profile measured experimentally.

In this work, a reduced-order-modeling(ROM) approach is introduced to simulate a battery system with multiple cells. The ROM is described by only two state variable equations and several explicit expressions.While running a stand-alone pseudo-2D (P2D) model by the nonlinear state variable modeling (NSVM) algorithm at a specified current, several parameters can be estimated through the NSVM procedure; and with these parameters, the cell voltage under additional current perturbations can be computed approximately by the ROM. This modeling scheme was tested for a 24P battery module in a co-simulation process: the stand-alone P2D model is solved at the battery-average current to estimate certain parameters to share with its ROM, then the ROM is implemented to evaluate the voltage response of each cell at its respective cell current. The ROM shows excellent accuracy and a much higher speed than the full-order-model with P2D models used for each cell. © The Author(s) 2017. Published by ECS.

The finite element method (FEM) was used in our nonlinear state-variable method (NSVM) presented recently (J. Electrochem. Soc., 164, E3001 (2017)). The details of the application of the FEM to solve the lithium ion pseudo-2D (P2D) model equations using the NSVM are presented here for several control modes (constant current, voltage, power, or load). Validation of the method was performed by comparison to rigorous full-ordermodels and experimental data. The FEM based NSVM shows excellent performance, and the estimated cell parameters are determined with a high confidence level. (C) The Author(s) 2017. Published by ECS. All rights reserved.