Sandia National Laboratories has been conducting studies on performance of laboratory and commercial lithium-ion and other types of electrochemical cells using inductive models [1]. The objectives of these investigations are: (1) To develop procedures and techniques to rapidly determine performance degradation rates while these cells undergo life tests; (2) To model cell voltage and capacity in order to simulate cell performance characteristics under variable load and temperature conditions; (3) To model rechargeable battery degradation under charge/discharge cycles and many other conditions. The inductive model and methodology are particularly useful when complicated cell performance behaviors are involved, which are often difficult to be interpreted from simple empirical approaches. We find that the inductive model can be used effectively: (1) To enable efficient predictions of battery life; (2) To characterize system behavior. Inductive models provide convenient tools to characterize system behavior using experimentally or analytically derived data in an efficient and robust framework. The approach does not require detailed phenomenological development. There are certain advantages unique to this approach. Among these advantages is the ability to avoid making measurements of hard to determine physical parameters or having to understand cell processes sufficiently to write mathematical functions describing their behavior. We used artificial neural network for inductive modeling, along with ancillary mathematical tools to improve their accuracy. This paper summarizes efforts to use inductive tools for cell and battery modeling. Examples of numerical results will be presented. One of them is related to high power lithium-ion batteries tested under the U.S. Department of Energy Advanced Technology Development Program for hybrid vehicle applications. Sandia National Laboratories is involved in the development of accelerated life testing and thermal abuse tests to enhance the understanding of power and capacity fade issues and predict life of the battery under a nominal use condition. This paper will use power and capacity fade behaviors of a Ni-oxide-based lithium-ion battery system to illustrate how effective the inductive model can interpret the cell behavior and provide predictions of life. We will discuss the analysis of the fading behavior associated with the cell performance and explain how the model can predict cell performance.
This document describes a general protocol (involving both experimental and data analytic aspects) that is designed to be a roadmap for rapidly obtaining a useful assessment of the average lifetime (at some specified use conditions) that might be expected from cells of a particular design. The proposed experimental protocol involves a series of accelerated degradation experiments. Through the acquisition of degradation data over time specified by the experimental protocol, an unambiguous assessment of the effects of accelerating factors (e.g., temperature and state of charge) on various measures of the health of a cell (e.g., power fade and capacity fade) will result. In order to assess cell lifetime, it is necessary to develop a model that accurately predicts degradation over a range of the experimental factors. In general, it is difficult to specify an appropriate model form without some preliminary analysis of the data. Nevertheless, assuming that the aging phenomenon relates to a chemical reaction with simple first-order rate kinetics, a data analysis protocol is also provided to construct a useful model that relates performance degradation to the levels of the accelerating factors. This model can then be used to make an accurate assessment of the average cell lifetime. The proposed experimental and data analysis protocols are illustrated with a case study involving the effects of accelerated aging on the power output from Gen-2 cells. For this case study, inadequacies of the simple first-order kinetics model were observed. However, a more complex model allowing for the effects of two concurrent mechanisms provided an accurate representation of the experimental data.
The technical and economic feasibility of applying used electric vehicle (EV) batteries in stationary applications was evaluated in this study. In addition to identifying possible barriers to EV battery reuse, steps needed to prepare the used EV batteries for a second application were also considered. Costs of acquiring, testing, and reconfiguring the used EV batteries were estimated. Eight potential stationary applications were identified and described in terms of power, energy, and duty cycle requirements. Costs for assembly and operation of battery energy storage systems to meet the requirements of these stationary applications were also estimated by extrapolating available data on existing systems. The calculated life cycle cost of a battery energy storage system designed for each application was then compared to the expected economic benefit to determine the economic feasibility. Four of the eight applications were found to be at least possible candidates for economically viable reuse of EV batteries. These were transmission support, light commercial load following, residential load following, and distributed node telecommunications backup power. There were no major technical barriers found, however further study is recommended to better characterize the performance and life of used EV batteries before design and testing of prototype battery systems.
Electrical and chemical measurements have been made on 18650-size lithium-ion cells that have been exposed to calendar and cycle life aging at temperatures up to 70 C. Aging times ranged from 2 weeks at the highest temperature to several months under more moderate conditions. After aging, the impedance behavior of the cells was reversed from that found originally, with lower impedance at low state of charge and the total impedance was significantly increased. Investigations using a reference electrode showed that these changes are primarily due to the behavior of the cathode. Measurements of cell impedance as a function of cell voltage reveal a pronounced minimum in the total impedance at approximately 40--50% state-of-charge (SOC). Chemical analysis data are presented to support the SOC assignments for aged and unaged cells. Electrochemical impedance spectroscopy (EIS) data have been recorded at several intermediate states of charge to construct the impedance vs. open circuit voltage curve for the cell. This information has not previously been available for the LiNi{sub 0.85}Co{sub 0.15}O{sub 2} cathode material. Structural and chemical analysis information obtained from cell components removed during postmortems will also be discussed in order to reveal the true state of charge of the cathode and to develop a more complete lithium inventory for the cell.
The authors have developed a model for the probabilistic behavior of a rechargeable battery acting as the energy storage component in a photovoltaic power supply system. Stochastic and deterministic models are created to simulate the behavior of the system components. The components are the solar resource, the photovoltaic power supply system, the rechargeable battery, and a load. One focus of this research is to model battery state of charge and battery capacity as a function of time. The capacity damage effect that occurs during deep discharge is introduced via a non-positive function of duration and depth of deep discharge events. Because the form of this function is unknown and varies with battery type, the authors model it with an artificial neural network (ANN) whose parameters are to be trained with experimental data. The battery capacity loss model will be described and a numerical example will be presented showing the predicted battery life under different PV system use scenarios.
Valve-Regulated Lead-Acid (VRLA) batteries continue to be employed in a wide variety of applications for telecommunications and Uninterruptible Power Supply (UPS). With the rapidly growing penetration of Internet services, the requirements for standby power systems appear to be changing. For example, at last year's INTELEC, high voltage standby power systems up to 300-vdc were discussed as alternatives to the traditional 48-volt power plant. At the same time, battery reliability and the sensitivity of VRLAs to charging conditions (e.g., in-rush current, float voltage and temperature), continue to be argued extensively. Charge regimes which provide 'off-line' charging or intermittent charge to the battery have been proposed. Some of these techniques go against the widely accepted rules of operation for batteries to achieve optimum lifetime. Experience in the telecom industry with high voltage systems and these charging scenarios is limited. However, GNB has several years of experience in the installation and operation of large VRLA battery systems that embody many of the power management philosophies being proposed. Early results show that positive grid corrosion is not accelerated and battery performance is mantained even when the battery is operated at a partial state-of-charge for long periods of time.