Towards Better Understanding of Failure Modes in Lithium-Ion Batteries: Design for Safety

In this digital age, energy storage technologies become more sophisticated and more widely used as we shift from traditional fossil fuel energy sources to renewable solutions. Specifically, consumer electronics devices and hybrid/electric vehicles demand better energy storage. Lithium-ion batteries have become a popular choice for meeting increased energy storage and power density needs. Like any energy solution, take for example the flammability of gasoline for automobiles, there are safety concerns surrounding the implications of failure. Although lithium-ion battery technology has existed for some time, the public interest in safety has become of higher concern with media stories reporting catastrophic cellular phone- and electric vehicle failures. Lithium-ion battery failure can be dangerously volatile. Because of this, battery electrochemical and thermal response is important to understand in order to improve safety when designing products that use lithium-ion chemistry. The implications of past and present understanding of multi-physics relationships inside a lithium-ion cell allow for the study of variables impacting cell response when designing new battery packs. Specifically, state-of-the-art design tools and models incorporate battery condition monitoring, charge balancing, safety checks, and thermal management by estimation of the state of charge, state of health, and internal electrochemical parameters. The parameters are well understood for healthy batteries and more recently for aging batteries, but not for physically damaged cells. Combining multi-physics and multi-scale modeling, a framework for isolating individual parameters to understand the impact of physical damage is developed in this work. The individual parameter isolated is the porosity of the separator, a critical component of the cell. This provides a powerful design tool for researchers and OEM engineers alike. This work is a partnership between a battery OEM (Johnson Controls, Inc.), a Computer Aided Engineering tool maker (ANSYS, Inc.), and a university laboratory (Advanced Manufacturing and Design Lab, University of Wisconsin-Milwaukee). This work aims at bridging the gap between industry and academia by using a computer aided engineering (CAE) platform to focus battery design for safety

A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle‐adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries.

The safety assurance is very important for the unmanned aerial vehicle lithium ion batteries, in which the state of charge estimation is the basis of its energy management and safety protection. A new equivalent modeling method is proposed for the mathematical expression of different structural characteristics, and an improved reduce particle-adaptive Kalman filtering model is designed and built, in which the incorporate multiple featured information is absorbed to explore the optimal representation by abandoning the redundant and abnormal information. And then, the multiple parameter identification is investigated that has the ability of adapting the current varying conditions, according to which the hybrid pulse power characterization test is accommodated. As can be known from the experimental results, the polynomial fitting treatment is carried out by conducting the curve fitting treatment and the maximum estimation error of the closed-circuit-voltage is 0.48% and its state of charge estimation error is lower than 0.30% in the hybrid pulse power characterization test, which is also within 2.00% under complex current varying working conditions. The iterate calculation process is conducted for the unmanned aerial vehicle lithium ion batteries together with the compound equivalent modeling, realizing its adaptive power state estimation and safety protection effectively

An accurate time constant parameter determination method for the varying condition equivalent circuit model of lithium batteries.

An accurate estimation of the state of charge for lithium battery depends on an accurate identification of the battery model parameters. In order to identify the polarization resistance and polarization capacitance in a Thevenin equivalent circuit model of lithium battery, the discharge and shelved states of a Thevenin circuit model were analyzed in this paper, together with the basic reasons for the difference in the resistance capacitance time constant and the accurate characterization of the resistance capacitance time constant in detail. The exact mathematical expression of the working characteristics of the circuit in two states were deduced thereafter. Moreover, based on the data of various working conditions, the parameters of the Thevenin circuit model through hybrid pulse power characterization experiment was identified, the simulation model was built, and a performance analysis was carried out. The experiments showed that the accuracy of the Thevenin circuit model can become 99.14% higher under dynamic test conditions and the new identification method that is based on the resistance capacitance time constant. This verifies that this method is highly accurate in the parameter identification of a lithium battery model

Modelling, Aging and Optimal Operation of Lithium-ion Batteries

Energy storage has a big role to play in power systems across the world in order to integrate increasing amounts of intermittent renewable sources of energy. Among the different storage technologies, lithium-ion batteries exhibit favourable characteristics that make them suitable for power system applications. However, commercial success of lithium-ion battery based storage is limited not only for grid applications but also for electric vehicles. This is due to three inter-related factors - safety, price-performance ratio and lifetime, which largely offset the advantages that these batteries offer and impede their adoption for potential applications. Any improvement in these factors is tied to better understanding of the functioning and of the limits of these batteries. This work is an attempt to further this understanding using modelling and experimental means, such that the behaviour of these batteries can be predicted over their lifetime, and their operation can be optimized. The contributions of this thesis are three-fold, as described in the following paragraphs. A battery model that is not only able to accurately estimate the electrochemical but also the thermal behaviour of a lithium ion battery is important in order to keep track of performance and safety indices. To this end, a physics based pseudo 2D electrochemical-thermal model of a lithium iron phosphate battery is developed. Parameters for this model are determined through primary information from manufacturer, literature studies and experimental data analysis. The developed model accurately predicts the electrochemical and thermal behaviour of the battery for both charging and discharging conditions for a wide range of current rates. Heat generation in the cell is investigated using the validated model and the important role of reversible heat and the dominant role of graphite electrode is highlighted. The model is extended to determine thermal behaviour of module, pack and study different thermal management systems. Given that battery performance degrades over time, long-term accelerated aging tests are used to quantify calendar and cycle aging in commercial lithium nickel manganese cobalt oxide batteries. Capacity and impedance measurements, electrochemical impedance spectroscopy as well as post-mortem analysis are used to study aging. Calendar aging is analysed as a function of temperature and storage state of charge. In general, low temperatures and low states of charge cause less degradation in the battery. Considerable influence of the periodic characterization process on the calendar aging results is noticed. Cycle aging is analysed as a function of temperature, current rate, depth of discharge and state of charge. In general, fast aging in batteries is observed when they are operated at low temperatures, high current rates and around high states of charge. The effects of local potentials at the two electrodes and staging behaviour of graphite in causing capacity fade and increase in the resistances of the cell are elucidated. Finally, the integration of storage in power systems is investigated. Technically, lithium-ion batteries are found to be suitable for a variety of applications in power systems both at utility scale as well as for home storage. Their economic feasibility is however debatable and dependent on local market conditions. To optimally use batteries in power system applications, an accurate degradation model that takes into account the complex, non-linear dependence of battery aging on operating parameters is developed. A mixed integer linear program is formulated, which produces an optimal charge-discharge schedule for the energy storage when trading in electricity markets. This program optimizes the operation of battery systems considering the twin objectives of maximizing revenue from market transactions and minimizing degradation. Such a multi-objective approach yields a Pareto-front of feasible operating strategies putting onus on a decision maker to choose a desirable operational strategy for implementation

Advanced Diagnostics for Lithium-ion Batteries: Decoding the Information in Electrode Swelling

Lithium-ion batteries exhibit mechanical expansion and contraction during cycling, consisting of a reversible intercalation-induced expansion and an irreversible expansion as the battery ages. Prior experimental studies have shown that mechanical expansion contains valuable information that correlates strongly with cell aging. However, a number of fundamental questions remain on the usability of the expansion measurement in practice. For example, it is necessary to determine whether the expansion measurements provide information that can help the estimation of the electrode state of health (eSOH), given limits on data availability and sensor noise in the field. Furthermore, the viability of using expansion for cell diagnostics also needs more investigation considering the broad range of aging conditions in real-world applications. This dissertation focuses on the experimental and modeling study of the expansion measurements during aging in order to assess its ability in helping battery diagnostics. To this end, mechanistic voltage and expansion models based on the underlying physics of phase transitions are developed. For the first time, the identifiability of eSOH parameters is explored by incorporating the expansion/force measurement. It is shown that the expansion measurements enhance the estimation of eSOH parameters, especially with a limited data window, since it has a better signal-to-noise ratio compared to the voltage. Moreover, the increased identifiability is closely related to the phase transitions in the electrodes. A long-term experimental aging study of the expansion of the graphite/NMC pouch cells is conducted under a variety of conditions such as temperature, charging rate, and depth of discharge. The goals here are to validate the results of the identifiability analysis and record the reversible and irreversible expansion correlated with capacity loss for informing the electrochemical models. Firstly, the advantages of the expansion concerning the eSOH identifiability are confirmed. Secondly, the results of the expansion evolution reveal that the features in the reversible expansion are an excellent indicator of health and, specifically, capacity retention. The expansion feature is robust to charge conditions. Namely, it is mostly insensitive to the hysteresis effects of the various initial state of charge, and it is detectable at higher C-rates up to 1C. Additionally, the expansion feature occurs near the half-charged point and therefore diagnostics can be performed more often during naturalistic use cases. Thus, the expansion measurement facilitates more frequent capacity checks in the field. Furthermore, an electrochemical and expansion model suitable for model-based estimation is developed. In particular, a multi-particle modeling approach for the graphite electrode is considered. It is demonstrated that the new model is able to capture the peak smoothing effect observed in the differential voltage at higher C-rates above C/2. Model parameters are identified using experimental data from the graphite/NMC pouch cell. The proposed model produces an excellent fit for the observed electric and mechanical swelling response of the cells and could enable physics-based data-driven degradation studies at practical charging rates. Finally, a fast-charging method based on the constant current constant voltage (CC-CV) charging scheme, called CC-CVησT (VEST), is developed. The new approach is simpler to implement and can be used with any model to impose varying levels of constraints on variables pertinent to degradation, such as plating potential and mechanical stress. The capabilities of the new CC-CVησT charging are demonstrated using the physics-based model developed in this dissertation.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169953/1/pmohtat_1.pd

Contributions on DC microgrid supervision and control strategies for efficiency optimization through battery modeling, management, and balancing techniques

Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC. Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinàmica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues. A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix càrrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un ràpid equilibrat del SOC evitant sobrecompensar el desequilibri. Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinàmica ràpida de la cel·la, amb un model físic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessària per a aconseguir els límits de OCV després de la pèrdua de liti ciclable en la reacció secundària. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC. Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinàmica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues. A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix càrrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un ràpid equilibrat del SOC evitant sobrecompensar el desequilibri. Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinàmica ràpida de la cel·la, amb un model físic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessària per a aconseguir els límits de OCV després de la pèrdua de liti ciclable en la reacció secundària. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.This dissertation presents a set of equipment, models and control strategies, that have been developed with the final goal of improving the operation of a DC microgrid. Two control strategies are proposed to improve the efficiency of the DC-DC converters that interface the microgrid’s power units with the DC bus. The first strategy is centralized Bus Voltage Optimization Control, which manages the power of the microgrid’s Battery Energy Storage System to make the bus voltage follow the optimum voltage dynamic reference that minimizes the converters’ losses. The second control strategy is Online Optimization of Switching Frequency, which consists in locally operating each converter at its optimum switching frequency, again minimizing power losses. The two proposed optimization strategies have been validated in simulations. Moreover, a new converter-based active balancing topology has been proposed and its control strategy has been designed. This equalizer topology consists of a single DC-DC converter that performs cell-to-cell charge transfer employing power routing via controlled switches. The control strategy of the equalizer has been designed to achieve rapid SOC balancing while avoiding imbalance overcompensation. Its performance has been validated in simulation. Finally, a simple degradation model of an NMC battery cell with graphite negative electrode is proposed. The model combines the simplicity of an equivalent circuit model, which explains the fast dynamics of the cell, with a physical model of the Solid-Electrolyte Interphase (SEI) layer growth process, which predicts the capacity loss and the internal resistance rise in the long term. The proposed model fine-tunes the capacity loss prediction by accounting for the incorporation of unused lithium reserves of both electrodes into the cyclable lithium range to reach the OCV limits after the side reaction has consumed cyclable lithium. The SEI degradation model can be used to perform predictive control of batteries oriented toward extending their lifetime