Jake Christensen

Identifying Capacity Limitations in the Li/Oxygen Battery Using Experiments and Modeling

The Li/oxygen battery may achieve a high practical specific energy as its theoretical specific energy is 11,400 Wh/kg Li assuming Li 2 O 2 is the product. To help understand the physics of the Li/oxygen battery we present the first physics-based model that incorporates the major thermodynamic, transport, and kinetic processes. We obtain a good match between porous-electrode experiments and simulations by using an empirical fit to the resistance of the discharge products (which include carbonates and oxides when using carbonate solvents) as a function of thickness that is obtained from flat-electrode experiments. The experiments and model indicate that the discharge products are electronically resistive, limiting their thickness to tens of nanometers and their volume fraction in one of our discharged porous electrodes to a few percent. Flat-electrode experiments, where pore clogging is impossible, show passivation similar to porous-electrode experiments and allow us to conclude that electrical passivation is the dominant capacity-limiting mechanism in our cells. Although in carbonate solvents Li 2 O 2 is not the dominant discharge product, we argue that the implications of this model, (i.e., electrical passivation by the discharge products limits the capacity) also apply if Li 2 O 2 is the discharge product, as it is an intrinsic electronic insulator.

Electrochemical Model Based Observer Design for a Lithium-Ion Battery

Batteries are the key technology for enabling further mobile electrification and energy storage. Accurate prediction of the state of the battery is needed not only for safety reasons, but also for better utilization of the battery. In this work we present a state estimation strategy for a detailed electrochemical model of a lithium-ion battery. The benefit of using a detailed model is the additional information obtained about the battery, such as accurate estimates of the internal temperature, the state of charge within the individual electrodes, overpotential, concentration and current distribution across the electrodes, which can be utilized for safety and optimal operation. Based on physical insight, we propose an output error injection observer based on a reduced set of partial differential-algebraic equations. This reduced model has a less complex structure, while it still captures the main dynamics. The observer is extensively studied in simulations and validated in experiments for actual electric-vehicle drive cycles. Experimental results show the observer to be robust with respect to unmodeled dynamics as well as to noisy and biased voltage and current measurements. The available state estimates can be used for monitoring purposes or incorporated into a model based controller to improve the performance of the battery while guaranteeing safe operation.

Experiments on and Modeling of Positive Electrodes with Multiple Active Materials for Lithium-Ion Batteries

We adapt a previously developed lithium-ion mathematical model to treat multiple types of active materials in a single electrode; our model treats both direct (galvanostatic) and alternating (impedance) currents. We compare our simulations to experimental data from coin cells built with two positive-electrode materials (compositions based on Li y Ni 0.80 Co 0.15 Al 0.05 O 2 and Li y Mn 2 O 4 ) mixed in five different molar ratios and develop a model parameter set that qualitatively matches both the galvanostatic and impedance data. We found that to match the behavior of the high rate discharge curves and the impedance data (which showed a similar width of the positive-electrode kinetic arc for any composition containing Li y Mn 2 O 4 ), multiple types of electronic connections between the active material and the conductive matrix were required. Our experiments showed that at high powers the specific energy from an electrode with pure Li y Mn 2 O 4 exceeded that from an electrode with pure Li y Ni 0.80 Co 0.15 Al 0.05 O 2 , while at low specific powers the Li y Ni 0.80 Co 0.15 Al 0.05 O 2 electrode had a higher specific energy. Mixing these active materials combined power and energy characteristics. We discuss other applications in which a mixed active-material electrode may be beneficial. For example, combining a sloped-potential system with a flat-potential system may assist in electrode state-of-charge determination.

Optimal charging strategies in lithium-ion battery

There is a strong need for advanced control methods in battery management systems, especially in the plug-in hybrid and electric vehicles sector, due to cost and safety issues of new high-power battery packs and high-energy cell design. Limitations in computational speed and available memory require the use of very simple battery models and basic control algorithms, which in turn result in suboptimal utilization of the battery. This work investigates the possible use of optimal control strategies for charging. We focus on the minimum time charging problem, where different constraints on internal battery states are considered. Based on features of the open-loop optimal charging solution, we propose a simple one-step predictive controller, which is shown to recover the time-optimal solution, while being feasible for real-time computations. We present simulation results suggesting a decrease in charging time by 50% compared to the conventional constant-current / constant-voltage method for lithium-ion batteries.

Modeling, estimation, and control challenges for lithium-ion batteries

Increasing demand for hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV) has forced battery manufacturers to consider energy storage systems that are better than contemporary lead-acid batteries. Currently, lithium-ion (Li-ion) batteries are believed to be the most promising battery system for HEV, PHEV and EV applications. However, designing a battery management system for Li-ion batteries that can guarantee safe and reliable operation is a challenge, since aging and other performance degrading mechanisms are not sufficiently well understood. As a first step to address these problems, we analyze an existing electrochemical model from the literature. Our aim is to present this model from a systems & controls perspective, and to bring forth the research challenges involved in modeling, estimation and control of Li-ion batteries. Additionally, we present a novel compact form of this model that can be used to study the Li-ion battery. We use this reformulated model to derive a simple approximated model, commonly known as the single particle model, and also identify the limitations of this approximation.

State estimation of a reduced electrochemical model of a lithium-ion battery

Batteries are the key technology for enabling further mobile electrification and energy storage. Accurate prediction of the state of the battery is needed not only for safety reasons, but also for better utilization of the battery. In this work we present a state estimation strategy for a detailed electrochemical model of a lithium-ion battery. The benefit of using a detailed model is the additional information obtained about the battery, such as accurate estimates of the state of charge within the individual electrodes, overpotential, concentration and current distribution across the electrodes, which can be utilized for safety and optimal operation. We propose an observer based on a reduced set of partial differential-algebraic equations, which are solved on a coarse spatial grid. The reduced model has a less complex structure, while still capturing the main dynamics. The observer is tested in experiments for actual electric-vehicle drive cycles. Experimental results show the observer to be robust with respect to unmodeled dynamics, as well as to noisy and biased voltage and current measurements. The available state estimates can be used for monitoring purposes, or incorporated into a model based controller to improve the performance of the battery while guaranteeing safe operation.

Stitching h-BN by atomic layer deposition of LiF as a stable interface for lithium metal anode

Selective atomic layer deposition of LiF on h-BN as an interfacial layer enables stable cycling of Li metal anodes. Defects are important features in two-dimensional (2D) materials that have a strong influence on their chemical and physical properties. Through the enhanced chemical reactivity at defect sites (point defects, line defects, etc.), one can selectively functionalize 2D materials via chemical reactions and thereby tune their physical properties. We demonstrate the selective atomic layer deposition of LiF on defect sites of h-BN prepared by chemical vapor deposition. The LiF deposits primarily on the line and point defects of h-BN, thereby creating seams that hold the h-BN crystallites together. The chemically and mechanically stable hybrid LiF/h-BN film successfully suppresses lithium dendrite formation during both the initial electrochemical deposition onto a copper foil and the subsequent cycling. The protected lithium electrodes exhibit good cycling behavior with more than 300 cycles at relatively high coulombic efficiency (>95%) in an additive-free carbonate electrolyte.

Approximations for Partial Differential Equations Appearing in Li-Ion Battery Models

Li-ion based batteries are believed to be the most promising battery system for HEV/PHEV/EV applications due to their high energy density, lack of hysteresis and low self-discharge currents. However, designing a battery, along with its Battery Management System (BMS), that can guarantee safe and reliable operation, is a challenge since aging and other mechanisms involving optimal charge and discharge of the battery are not sufficiently well understood. In a previous article [1], we presented a model that has been studied in [2]–[5] to understand the operation of a Li-ion battery. In this article, we continue our work and present an approximation technique that can be applied to a generic battery model. These approximation method is based on projecting solutions to a Hilbert subspace formed by taking the span of an countably infinite set of basis functions. In this article, we apply this method to the key diffusion equation in the battery model, thus providing a fast approximation for the single particle model (SPM) for both variable and constant diffusion case.Copyright

Overview of LiO2 Battery Systems, with a Focus on Oxygen Handling Requirements and Technologies

The reactions of Li and O2 to form Li2O2, and of Li, O2, and H2O to form LiOH·H2O, have exceptional energy content but are adversely affected by components of air such as CO2 (for both cases) and H2O (for the Li2O2 case). Hence, a method is required to supply O2 while excluding contaminants. In this chapter we focus on O2 supply for both a closed system (in which tanks store pure O2 at pressures up to 350 bar) and an open system (in which CO2 and possibly H2O are removed through a series of unit operations). In particular, we consider the implications of the O2 supply method on the specific energy and energy density at the system level, as well as other system attributes such as cost. For the closed (tank) system we find that with the use of a carbon fiber tank, for the reaction forming Li2O2, the specific energy is twice that of a comparison cell (one pairing Li metal with an advanced intercalation metal oxide), but the energy density is about 30 % lower. For the reaction forming LiOH·H2O, the specific energy is about 40 % above that of a Li/metal oxide cell, but the energy density is 50 % lower. A unique challenge for the closed system is the need for high-pressure compression. An open system may be enabled through the combined use of several gas separation steps (including a membrane and solid adsorption) as well as a compressor to drive the air. The required purity of an O2 supply stream remains unclear, but for a reduction of CO2 and H2O to levels of 1 ppm, the mass and volume of the O2 supply equipment for the open system is comparable to that of the closed system. A unique challenge for the open system is safely charging in closed environments where the O2 emitted does not quickly dissipate. For both types of systems, handling any volatile cell components (e.g., solvents) may be a challenge (for the closed system they may enter the high-pressure O2 tanks, while in the open system they may be lost to the atmosphere), and potential technologies to address volatiles are not included in this analysis. We encourage Li/O2 researchers to investigate sets of nonvolatile materials that may improve the robustness of the cell chemistry to the presence of air contaminants.

Engineering stable interfaces for three-dimensional lithium metal anodes

Atomic layer deposition enables stable cycling of Li metal in a three-dimensional lithium host. Lithium metal has long been considered one of the most promising anode materials for advanced lithium batteries (for example, Li-S and Li-O2), which could offer significantly improved energy density compared to state-of-the-art lithium ion batteries. Despite decades of intense research efforts, its commercialization remains limited by poor cyclability and safety concerns of lithium metal anodes. One root cause is the parasitic reaction between metallic lithium and the organic liquid electrolyte, resulting in continuous formation of an unstable solid electrolyte interphase, which consumes both active lithium and electrolyte. Until now, it has been challenging to completely shut down the parasitic reaction. We find that a thin-layer coating applied through atomic layer deposition on a hollow carbon host guides lithium deposition inside the hollow carbon sphere and simultaneously prevents electrolyte infiltration by sealing pinholes on the shell of the hollow carbon sphere. By encapsulating lithium inside the stable host, parasitic reactions are prevented, resulting in impressive cycling behavior. We report more than 500 cycles at a high coulombic efficiency of 99% in an ether-based electrolyte at a cycling rate of 0.5 mA/cm2 and a cycling capacity of 1 mAh/cm2, which is among the most stable Li anodes reported so far.