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LIB Technology Symposium
Large Lithium Ion Battery Technology & Application (LLIBTA)
Monday, June 15 to Wednesday, June 17, 2015
Engineering Track

Advanced Automotive Battery Conferences

AABC 2015 – LIB Technology Symposium - Engineering Track


Session 1B (joint session with Chemistry Track session 1B):

"Posters + 8" Presentations

Venkat Srinivasan
Session Chairman:
Venkat Srinivasan, Batteries for Advanced Transportation Technologies (BATT) Electrochemical Technologies Group, Lawrence Berkeley National Laboratory


Dr. Venkat Srinivasan is Head of the Energy Storage and Distributed Resources Department at the Lawrence Berkeley National Lab. He also serves as the Acting Director of the Batteries for Advanced Transportation Technologies (BATT) Program and Deputy Director of the recently announced Energy Storage Hub, titled Joint Center for Energy Storage Research (JCESR). Dr. Srinivasan's research interest is in developing the next-generation batteries for use in vehicle and grid applications. At present, he has projects focused on studying the degradation and performance limitations in advanced lithium-ion cathode and anode materials and on developing high power, low-cost flow batteries for use in stationary energy-storage applications. Dr. Srinivasan received his PhD from the University of South Carolina in Chemical Engineering in 2000. His thesis topic included various aspects in electrochemical capacitors and the nickel hydroxide electrode.

  1. LIBS as a Chemical Diagnostic Tool of Li-Ion Battery Raw Materials and Fabricated Components
    Steve Barnett, Applied Spectra, Inc
    Laser Induced Breakdown Spectroscopy (LIBS) is a well-established, elemental analysis technique that uses a short laser pulse to rapidly analyze the composition of any solid sample. In the current study, we demonstrate this technique for the analysis of raw Li-ion battery materials, components and fabricated cells. LIBS was used to monitor major element composition and check impurity of raw materials for cathode and anode, ensuring consistent quality of incoming materials before the component fabrication. We present 2D and 3D elemental mapping by LIBS for Li-ion battery structures such thin film electrolytes, cathodes, and anodes. Fluorine imaging is utilized to map PVDF binder distribution in graphite anodes and NMC cathodes, enabling an assessment of binder homogeneity during the manufacturing process of the anodes and cathodes. We also present rapid analysis of key elemental ratios in the solid state electrolyte LLZO pellets prepared under different conditions and show how the difference in these ratios lead to different electrochemical behavior. The results presented demonstrate the ability to chemically analyze and image different types of Li‐ion battery device structures across different length‐scales (nano‐, meso‐ and macro‐scale) by LIBS. The high flexibility, sensitivity and inherent in situ capabilities of this technique make LIBS the ideal tool for in‐line inspection after critical Li ion battery process steps to ensure process stability and to control quality of the fabricated components. This chemical diagnostic capability is expected to improve the yield and performance of the current Li ion batteries to make the product more economically competitive and drive the faster adoption cycle of Electric Vehicles (EVs).
  2. Novel Noncarbonate Electrolytes for Silicon Anodes
    Gang Cheng, Lead Scientist, Wildcat Discovery Technologies
    Wildcat Discovery Technologies is developing novel electrolyte additives and noncarbonate solvent formulations that yield improved solid electrolyte interphase (SEI) layers on silicon alloy anodes. The large volumetric changes in silicon during charge/discharge cycles result in mechanical disruption of conventional SEI’s leading to rapid capacity fade as the cell cycles. Novel additives are demonstrated to improve cycle life of silicon based materials by forming less brittle, more mechanically robust SEI passivation layers. Since propylene carbonate (PC) is not expected to form an effective SEI layer, the additives are tested with PC to determine their efficacy. Wildcat’s high throughput electrolyte formulation, cell assembly, and test capabilities enable the evaluation of hundreds of additives in a very short timeframe.

    Once effective SEI additives are identified in a PC-based formulation, other non-SEI forming solvents can be evaluated. Since the additives are effective without solvent participation in SEI formation, solvents can be considered that may not be reductively stable on the anode – and also opens the possibility to more oxidatively stable or less flammable solvents. Wildcat has evaluated hundreds of combinations of noncarbonate solvents with its initial silicon anode SEI additives. This presentation will focus on the results of the additive improvement to cycle life in NMC//Si full cells, and illustrate the opportunities for novel solvent combinations.

  3. Ion Chromatography Coupled with High-Resolution Mass Spectrometry for the Analysis of Anionic Degradation Products Obtained from Surface Deposits on Lithium-Ion Battery Anodes
    Chris Pohl, Vice President, Chromatography Chemistry, Chromatography & Mass Spectrometry Division, ThermoFisher Scientific
    This presentation will summarize work our team has done using gradient anion exchange ion chromatography with a conductivity detector coupled with high resolution mass spectrometry for the analysis of anionic degradation products obtained from surface deposits on lithium ion battery anodes.  Gradient ion exchange ion chromatography enables separation of complex mixtures of inorganic anions and organic anions based on size, charge charge and hydrophobicity properties.  Using IC on samples containing complex mixtures of anionic species can help in the elucidation of chemical structures of unknown components.  The use of high resolution mass spectrometry provides high confidence analyte identification while use of ion chromatography provides confirmatory information about ionizable functional groups.  Together these two techniques provide a powerful new tool in the analysis of anionic degradation products in lithium ion batteries.  Compound classes and specific compounds that were found in these anode wash samples included:
    • Solvent degradation products such as methyl carbonate
    • Ubiquitous anionic contaminants such as chloride and sulfate
    • Electrolyte breakdown products such as fluoride phosphate and pyrophosphate
    • Organic acids derived from degradation of the anode
    • Ionic materials derived from reactions between various ion classes found in the samples including: sulfate esters, phosphate esters and fluorophosphate esters
  4. The Effect of Impurity Profile on Cycling Behavior of Electrolytes Containing LiFSI
    Krzysztof Pupek, Principal Process R&D Chemist, Argonne National Laboratory
    There is growing interest in lithium bis (fluorosulfonyl)imide (LiFSI ) as an alternative to LiPF6 and as an additive to electrolytes used in lithium-ion cells. LiFSI has attracted attention because it is reported to have higher ionic conductivity, better high temperature stability, and enhanced stability toward hydrolysis, Also, LiFSI additive to electrolytes can bring benefits of improved storage properties and reduced gas evolution in the cells. However, numerous publications report aluminum current collector corrosion in electrolytes formulated with LiFSI. This corrosion is presumably due to impurities in the material.
    We conducted comparative study of several commercial samples of LiFSI to assess effect of impurity profile on electrochemical performance of the materials. Ion chromatography was used for chemical analyses and LMN//graphite CR2032 cells for corrosion, cycle life and calendar life evaluation. Comprehensive data from these tests will be presented at the meeting.
  5. Estimating Degradation of a Lithium-Ion Battery under Storage and Arbitrary Cycling – Some Examples
    Jayant Sarlashkar, Staff Engineer, Engine, Emissions, and Vehicle Research Division, Southwest Research Institute
    Lithium-ion (and more generally, rechargeable electrochemical) batteries, routinely undergo charge-discharge cycles and their performance degrades with use. Estimation of degradation of battery performance is of great general interest regardless of the field of application. The main conclusion of the work reported here is that the degradation of a battery, subjected to an arbitrary (cyclic) loading pattern, can be estimated by a composite statistical model superposing effect of lapse of time (calendar or storage aging) and of repeated charge and discharge (cycle or fatigue aging). It is shown that the degradation due to time can be modeled hierarchically as an exponential (or power) form in time with the characteristic time (and the exponent of the power form) as function of state-of-charge and temperature. It is also shown that the degradation due to a “simple cycle” can be modeled hierarchically as a linear form in number of simple cycles with the slope as function of the amplitude, bias, and frequency of the cycle, and the temperature. A proprietary algorithm is used to decompose arbitrary charge-discharge pattern into constituent “simple cycles” and to aggregate degradation due to the constituent cycles and storage. Composite degradation models were developed from storage and simple cycling experiments on two Lithium-ion batteries from two suppliers. The batteries differed with respect to chemistry, packaging, and intended application. The composite models were validated on three arbitrary charge/discharge patterns. The preliminary results are encouraging – for the cases tested, the estimated degradation was within 5% (absolute) of the measured counterpart. The expected uses of the model include real-time estimation of battery degradation, sizing of battery for a given application subject to life expectancy, estimation of battery warranty costs, and emulation of battery degradation for HIL testing.
  6. Material Characterization Needs for Battery Multi-Physics Modeling and Simulation
    Ramesh Rebba, Lead CAE Engineer, Global Battery Systems Engineering, General Motors
    Modeling and simulation of lithium ion battery cells and packs is a key business driver for accelerating the development time of electrified vehicles. Thermal cooling concepts for improved battery life and desired storage energy density can be studied using computer aided engineering tools. General Motors had teamed up with Department of Energy, NREL, ANSYS and ESim as part of CAEBAT project, to commercialize a tool that implements multi-scale multi-domain physics-based models for Li-ion batteries. Significant computational efficiencies are achieved using reduced order models of battery system behavior. Continued success in this area requires accurate and reliable model input materials such as open circuit potentials of blended electrodes, electronic conductivities, Lithium transport properties in electrodes and electrolyte, particle size distribution as well as reaction rates. Input measurement uncertainties, vast unstructured literature data and model form errors impact the simulation predictions. Standard material characterization techniques are not yet developed and fully adopted in the industry. Some of the lessons in mathematical model validation of electro-thermal behavior of cells and challenges in model parameterization will be discussed in the poster. The poster and presentation will address the key issues that analysts and product managers deal with:
    • What is the state-of-art for lithium ion battery electrochemical modeling?
    • How can industry access these models and tools for cell selection and battery pack design?
    • How do we quantify the confidence in the model predictions?
    • How to characterize model inputs and material properties for electrodes?
    • Develop standards for direct experimental measurement of lithium transport properties versus numerical calibration of parameters
  7. Integrated Multiscale Multiphysics Modeling of Safety Response in Lithium-Ion Batteries; Focus on Prismatic Wound Cell Behaviors
    Gi-Heon Kim, Principal Researcher, Team Lead, Energy Storage Modeling, Hydrogen and Transportation Systems Center, National Renewable Energy Laboratory
    Scale-up of lithium-ion battery raises the complexity of interactions among the physicochemical processes occurring in intricate geometries across wide range time and length scales. The entangled interplays critically affect the violent failure response of these batteries under safety incidents. In support of U.S. Department of Energy, National Renewable Energy Laboratory has developed a modeling framework providing modular architecture, facilitating flexible integration of multiphysics components. Interdisciplinary constitutive models are integrated to properly simulate the response of a battery developing various safety incident causes. The model is used to evaluate the impact of the chemical/thermal/electrical design characteristics, operational/environmental conditions, and type and nature of faults at cell and pack levels.
  8. Development of Multifunctional Batteries for EVs
    Jiang Fan, President, American Lithium Energy Corporation
    Energy density, cost, and safety are three highly correlated factors in EV batteries. A battery consisting of a high energy density cells does not necessarily lead to a high energy density and low-cost battery because a high efficiency thermal system and strong container may be required to mitigate safety concerns, which not only diminish the battery specific energy density but also increase the cost. Therefore, it is advantageous to develop an EV battery that is optimized at higher level, i.e. vehicle level.

    ALE, an advanced lithium ion battery company located in San Diego County, is developing a multifunctional battery for EV applications together with workers at the University of California at San Diego, University of California at Merced, and Columbia University. In this project, the battery functionality is extended beyond the power source of the electric vehicle. Specifically, the battery will replace some non-critical parts in the electric vehicle to serve both as a power source and as a means to mitigate crush or impact. This approach can effectively enhance the battery specific energy density and decrease the cost in view of the reduction of the weight and cost at the electric vehicle level. As a result, an electric vehicle with 300 miles range at a very competitive cost may be feasible.

    This presentation will start with the review of battery weight vs. the EV weight and their ranges for the major brands, and then illustrates the considerations to develop a multifunctional EV battery at the cell and battery levels. Actual cell performance and abuse tolerance as well as computer simulation results will be presented to demonstrate the feasibility of this novel approach.

    Acknowledgements: Drs. Qiao Yu and Shirley Meng, UCSD, Dr. Xi Chan, Columbia University and Dr. Yan Bao Ma from UCM are greatly acknowledged for sharing some of their results; Program manager Dr. John Lemmon and fellow Dr. Dawson Cagle from ARPA-E are greatly appreciated for their support and guidance.

  9. Modeling, Testing, and Verification of Multifunctional Impact-Resistant Structural Batteries
    Waterloo Tsutsui, Ph.D. Student and Graduate Researcher, School of Aeronautics and Astronautics, Purdue University
    We are in the process of developing multifunctional impact-resistant structural batteries for electric vehicles (EVs). The battery system not only stores electricity for vehicle propulsion but also reduces impact forces for the EVs getting into crash loading conditions, thus decreasing the impact shock to the vehicle occupants and mitigating the risk of bodily injury. Parab et al. (2014) demonstrated the fundamental mechanism of impact energy dissipation with the pulverization of a sand particle in the granular load chain, where the pulverized sand particle interrupted the transmission of impact loads and forced the rearrangement of the remaining grains. Our research extended the concept of granular load chains to the battery cell arrangement with the use of sacrificing cells that effectively limit the impact load propagation speed, thus isolating the mechanical impact shocks. Based on this concept, we propose Granular Battery Assembly (GBA). In the development of GBA, the mechanics of cylindrical lithium-ion battery cells and surrounding sacrificing structures as well as the interactions between these components were exploited for their structural application. More specifically, we conducted finite element modeling, testing, and verification of models at both the cell and pack levels. We foresee the results of our research to cause a paradigm shift in EV design since we can place the GBA system directly in the crash zone for both a) safety improvement due to its impact shock absorption capability and b) driving range improvement due to the added battery capacity in the crash zone. Safety and driving range are some of the key topics that contribute to the high market penetration of EVs for today’s increasing need for sustainable energy in transportation. This study aims at this high-level objectives by focusing on the impact mechanics of battery cells and packs.

    Presentation Outline

    • Introduction/Motivation
    • Overview of Design Concepts
    • Experimental and Numerical Analysis
      • Cell-Level Analysis
      • Pack-Level Analysis
    • Conclusion
  10. Coupling of Mechanical Behavior of Lithium Ion Cells to Electrochemical-Thermal Models for Battery Crush
    Ahmad Pesaran, Energy-Storage Group Manager, National Renewable Energy Laboratory
    Propagation of failure in lithium ion batteries during field-events or under abuse is a strong function of the mechanical response of the different components in the battery. Whereas thermal and electrochemical models that capture the abuse response of batteries have been developed and matured over the years, the interaction between the mechanical behavior and the thermal response of these batteries is not very well understood. With support from Department of Energy NREL has made progress in coupling mechanical, thermal and electrochemical lithium ions models to predict the initiation and propagation of short circuit under external crush in a cell. The challenge with cell crush simulation is to estimate the magnitude and location of the short. To address this, the model includes an explicit representation of each individual component such as the active material, current collector, separator, etc., and predicts their mechanical deformation under different crush scenario. Initial results show reasonable agreement with experiments. In this presentation, the versatility of the approach for use with different design factors, cell formats and chemistries is explored using examples.