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<p> In the pursuit to enable the rapid charging of lithium-ion batteries, lithium plating at the anode  poses one of the most significant challenges. Additionally, the heat generation that accompanies  high rate battery operation in conjunction with non-uniform cooling and localized heating at tabs  is known to result in thermal inhomogeneity. Such thermal anomalies in the absence of proper  thermal management can instigate accelerated degradation in the cell. This work seeks to elucidate  the link between thermal gradients and lithium plating in lithium-ion batteries using a combined  experimental and simulation-based approach. First, we experimentally characterize the lithium  plating phenomenon on graphite anodes under a wide variety of charging rates and temperatures  to gain mechanistic insights into the processes at play. An in operando detection method for the  onset of dendritic lithium plating is developed. Lithium plating regimes are identified as either  nucleate or dendritic, which exhibit vast differences in reversibility. An operando method to  quantify lithium stripping based on the rest phase voltage plateau is presented. Next, a model is  employed to provide fundamental insights to the thermo-electrochemical interactions during  charging in scenarios involving an externally imposed in-plane and inter-electrode thermal  gradient. The relative importance of in-plane vs. inter-electrode thermal gradients to charging  performance and cell degradation is necessary to inform future cell design and cooling systems for  large-format cells, which are crucial for meeting the energy requirements of applications like  electric vehicles. While in-plane thermal gradients strongly influence active material utilization,  the lithium plating severity was found to be very similar to an isothermal case at the same mean  temperature. By contrast, inter-electrode thermal gradients cause a shifting on the solid phase  potential at each electrode during charging, related to the increase or decrease in overpotential due  to local temperature variation. An experiment is then performed on a commercial multi-layer  pouch cell, in which it was found that applied thermal gradients provide a slight reduction in  lithium plating severity and degradation rate when compared to an isothermal cell at the same  mean temperature. The presence of a thermal gradient causes heterogeneous lithium plating  deposition within the cell, with colder regions experiencing higher quantities of plating and larger  thermal gradients leading to more severe heterogeneity.   </p>

The accurate and reliable estimation of the State-of-Charge (SOC) and State-of-Health (SOH) of Li-ion batteries is paramount to the safe and reliable operation of any electrified vehicle. Not only is accuracy and reliability necessary, but these estimation techniques must also be practical and intelligent since their use in real world applications can include noisy input signals, varying ambient conditions and incomplete or partial sequences of measured battery data. To that end, a novel framework, utilizing deep learning techniques, is considered whereby battery modelling and state estimation are performed in a single unified step. For SOC estimation, two different deep learning techniques are used with experimental data. These include a Recurrent Neural Network with Long Short-Term Memory (LSTM-RNN) and a Deep Feedforward Neural Network (DNN); each one possessing its own set of advantages. The LSTM-RNN achieves a Mean Absolute Error (MAE) of 0.57% over a fixed ambient temperature and a MAE of 1.61% over a dataset with ambient temperatures increasing from 10°C to 25°C. The DNN algorithm, on the other hand, achieves a MAE of 1.10% over a 25°C dataset while, at -20°C, a MAE of 2.17% is obtained. A Convolutional Neural Network (CNN), which has the advantage of shared weights, is used with randomized battery usage data to map raw battery measurements directly to an estimated SOH value. Using this strategy, average errors of below 1% are obtained when using fixed reference charge profiles. To further increase the practicality of this algorithm, the CNN is trained and validated over partial reference charge curves. SOH is estimated with a partial reference profile with the SOC ranging from 60% to 95% and achieves a MAE of 0.81%. A smaller SOC range is then used where the partial charge profile spans a SOC of 85% to 95% and a MAE of 1.60% is obtained. Finally, a fused convolutional recurrent neural network (CNN-RNN) is used to perform combined SOC and SOH estimation over constant charge profiles. This is performed by feeding the estimated SOH from the CNN into a LSTM-RNN, which, in turn, estimates SOC with a MAE of less than 0.5% over the lifetime of the battery. / Thesis / Doctor of Philosophy (PhD)

This study has two parts. In the first part we develop a computational approach to the solution of an inverse modelling problem concerning the material properties of electrolytes used in Lithium-ion batteries. The dependence of the diffusion coefficient and the transference number on the concentration of Lithium ions is reconstructed based on the concentration data obtained from an in-situ NMR imaging experiment. This experiment is modelled by a system of 1D time-dependent Partial Differential Equations (PDE) describing the evolution of the concentration of Lithium ions with prescribed initial concentration and fluxes at the boundary. The material properties that appear in this model are reconstructed by solving a variational optimization problem in which the least-square error between the experimental and simulated concentration values is minimized. The uncertainty of the reconstruction is characterized by assuming that the material properties are random variables and their probability distribution estimated using a novel combination of Monte-Carlo approach and Bayesian statistics. In the second part of this study, we carefully analyze a number of secondary effects such as ion pairing and dendrite growth that may influence the estimation of the material properties and develop mathematical models to include these effects. We then use reconstructions of material properties based on inverse modelling along with their uncertainty estimates as a framework to validate or invalidate the models. The significance of certain secondary effects is assessed based on the influence they have on the reconstructed material properties. / Thesis / Doctor of Philosophy (PhD)

One of the questions arising as regards to structured materials is how one can compute their cluster concentrations. Specifically, we are interested in deriving the concentrations of the micro-structures in the NMC (Nickel-Manganese-Cobalt) layer of the cathodes of Li-ion batteries. A simulated annealing approach has been used lately for detecting the structure of the whole lattice which is computationally heavy. Here we propose a mathematical model, called cluster approximation model, in the form of a dynamical system for describing the concentrations of different clusters inside the lattice. However, the dynamical system is hierarchical which requires to be truncated. Truncation of the hierarchical system is performed by the nearest-neighbor closure scheme. Also, a novel framework is proposed for an optimal closure of the dynamical system in order to enhance the accuracy of the model. The parameters of the model are reconstructed by the least square approach as a constrained optimization problem by minimizing the mismatch between the experimental data and the model outputs. The model is validated based on the experimental data on a known Li-ion battery cathode and different approximation schemes are compared. The results clearly show that the proposed approach significantly outperforms the conventional method. / Thesis / Master of Science (MSc)

Li-ion battery technologies have transformed the consumer electronics and electric vehicles landscape over the last few decades. Single-crystal cathode materials with controllable physical properties including size, morphology, and crystal facets can aid researchers in developing relationships between physical characteristics, chemical properties, and electrochemical performance. High-voltage LiNi_0.5Mn_1.5O₄ (LNMO) materials are desirable as cathodes due to their low cost, low toxicity, and high capacity and energy density making them promising to meet increasing consumer demands for battery materials. However, transition metal dissolution, interfacial instability, and capacity fading plague these materials when paired with graphite, limiting their commercial capability. Furthermore, variation in Ni/Mn ordering can lead to complex multiphase co-existence and changes in Mn oxidation state and electrochemical performance. These properties can be adjusted during synthesis using a facile and tunable molten salt synthesis method. This dissertation focuses on the investigation of chemical and structural heterogeneities of LNMO prepared under different synthetic conditions at different length scales. In Chapter 2, the influences of molten salt synthesis parameters on LNMO particle size, morphology, bulk uniformity, and performance are evaluated revealing the difficulty of reproducible cathode synthesis. We utilize the X-ray nanodiffraction technique throughout this work, which provides high-resolution structural information. We develop a method to measure and relate lattice strain to phase distribution at the tens of nanometers scale. In Chapter 3, mapping lattice distortions of LNMO particles with varying global Mn oxidation states reveals inherent structural defects and distortion heterogeneities. In Chapter 4, we examine lattice distortion evolution upon chemical delithiation, Mn dissolution behaviors, and evaluate the chemical delithiation method as a means to replicate electrochemical cycling conditions. We further investigate lattice distortion spatially via in situ nanodiffraction during battery cycling in Chapter 5, illustrating the capabilities of the measurement to provide practical understanding of cathode transformations. From intra-particle to electrode materials level, heterogeneities that arise in cathode materials can dictate performance properties and degradation mechanisms and are necessary for researchers to understand for the improvement of Li-ion battery systems. The development of the nanodiffraction measurements aids in our understanding of inherent and dynamic materials chemical and structural heterogeneities. / Doctor of Philosophy / The invention of rechargeable Li-ion batteries in the 1990s has undeniably revolutionized modern civilization. Cell phones, laptops, grid energy storage, and electric vehicles have become fundamental fixtures of the 21st century. As technologies improve and requirements for advanced renewable energy storage have increased, researchers have sought to design longer lasting, faster charging, and more lightweight batteries. Modifying and finding new positive electrode materials is one way to improve the capabilities of modern batteries as their properties are governed by fundamental chemistry. High-voltage LiNi_0.5Mn_1.5O₄ (LNMO) is one such material that can allow for fast charging and high energy storage capacity, but its commercialization is hindered by complex physical and chemical properties, which can limit its lifetime in batteries. Large, particles with well-defined shapes are desirable to improve the stability of the materials; however, understanding their defects and structural heterogeneities is vital to continued optimization and requires advanced characterization techniques. In this dissertation, we characterize the physical phases and chemical properties of LNMO samples prepared under different conditions resulting in different particle shapes, sizes, and chemical distributions. An advanced X-ray nanodiffraction technique is used to measure phase distributions within individual particles while lab-based analytical techniques and electrochemical testing can determine bulk properties and battery performance of materials. Overall, the aim of this work is to develop techniques to measure structural and chemical heterogeneities of cathode materials at different length scales and to understand how they influence properties and performance in batteries. This work provides valuable insights into the inherent and dynamic properties of high-voltage electrode materials useful to advance our understanding of how these materials fail and to aid researchers in creating design principles to develop stable, high-performing future generations of rechargeable batteries.

The wide applications of energy storage systems in consumer electronics, electric vehicles, and grid storage in the recent decade has created an enormous market globally. The electrochemical flow system has many applications in Li-ion battery recycling and energy storage system design. First, research work on a scalable electrochemical flow system is presented to effectively restore the lithium concentration in end-of-life Li-ion cathode materials. An effective recycling process for end-of-life lithium-ion batteries could relieve the environmental burden and retrieve valuable cathode battery materials. The design is validated in a static configuration with both cathode loose powder and cathode electrode sheet. Materials with comparable electrochemical performance to virgin cathode materials are produced after post heat treatment. Second, research contributions in sulfur-based flow battery systems for long-duration energy storage are presented. Sulfur-based redox flow batteries are promising due to their high theoretical capacity, low cost, and high abundance. The speciation of aqueous sulfur solutions with different nominal concentrations, sulfur concentrations, and pH are studied by Raman spectroscopy. Next, a promising aqueous manganese catholyte to couple with the sulfur anolyte for a full flow battery is investigated. Test protocols and quantification metrics for the catholyte are developed. The stability of the catholyte, including self-discharge rate and precipitation rate, is measured via ex-situ characterizations. The electrochemical performance of the catholyte is investigated and optimized via in-situ experiments. The reaction pathway for the precipitation of catholyte is discussed and several mitigation strategies are proposed. Finally, a semi-solid sodium-sulfur flow battery is developed. The electrochemical performance of the sodium-sulfur battery is studied first in a static configuration at an intermediate temperature (150°C). Then a Na-S semi-solid flow cell is assembled and cycled under the two-aliquots and three-aliquots intermittent flow. / Doctor of Philosophy / The market of energy storage systems has been expanding dramatically in recent years due to their wide applications in portable electronics, electric vehicles, and large-scale grid storage. First, the research on the development of an electrochemical flow system in the Li-ion batteries (LIB) recycling process is presented. The improper disposal of end-of-life LIBs will generate flammable hazardous waste. Recycling spent LIBs could ease the environmental burden and replenish valuable resources such as lithium, cobalt, and nickel, and reduce the cost of battery manufacturing. In this study, an electrochemical flow system is designed to restore the end-of-life cathode materials in LIBs. The design has the potential to scale up and is validated with a static configuration. The recycled materials show comparable electrochemical performance to virgin battery cathode materials. Life cycle analysis shows that the recycling process consumes less energy and is more environmentally friendly. Second, the research contribution in sulfur-based flow battery systems for long-duration energy storage is presented. The aqueous sulfur solutions with different nominal concentrations, sulfur concentrations, and pH are studied by Raman spectroscopy. Next, a promising aqueous manganese catholyte to couple with the sulfur anolyte for a full redox flow battery is investigated. The chemical stability of the catholyte, including self-discharge rate and precipitation rate, is measured via ex-situ characterizations. The electrochemical performance of the catholyte is studied and optimized via in-situ experiments. The reaction mechanisms for the precipitation of aqueous manganese solutions are discussed. Finally, a semi-solid sodium-sulfur (Na-S) flow battery is developed. The electrochemical performance of the sodium-sulfur battery is studied first in a static cell at intermediate temperature. Then a Na-S semi-solid flow cell is demonstrated and cycled under the two-aliquots and three-aliquots intermittent flow.

Li-ion batteries (LIBs) have achieved remarkable success in electric vehicles (EVs), consumer electronics, grid energy storage, and other applications thanks to a wide range of electrode materials that meet the performance requirements of different application scenarios. Cathodes are an essential component of LIBs, which governs the performance of commercial LIBs. Layered transition metal oxide, i.e., LiNixCoyMn1-x-yO2 (NMC), is one family of cathodes that are widely applied in the prevailing commercial LIBs. With increasing demand for high energy density, the development of layered oxide cathodes is towards high Ni content because Ni redox couples majorly contribute to the battery capacity. Meanwhile, the battery community has been making tremendous efforts to eliminate Co in layered cathodes due to its high cost, high toxicity, and child labor issues during Co mining. However, these Ni-rich Co-free cathodes usually suffer from low electrochemical and structural stability. Several strategies are adopted to enhance the stability of Ni-rich Co-free cathodes, such as doping, coating, and synthesizing single crystal particles. However, the design principles and synthesis mechanisms of these approaches have not been fully understood. Herein, we design and synthesize stable Ni-rich and low/no-Co layered oxide cathodes by manipulating the chemical and structural properties of cathode particles. Our studies reveal the cathode formation mechanisms and shed light on the cathode design through complementary synchrotron microscopic and spectroscopic characterization methods. In Chapter 1, the motivation for LIB research is introduced from the perspective of its indispensable role in achieving carbon neutrality. We then comprehensively introduce the status of LIBs at present, including assessing their sustainability, worldwide supply chain and manufacturing, and cathode materials. Subsequently, we focus on the Co-free layered oxide cathodes and discuss their structure, limitations, and strategies to address the challenges. Finally, we discuss single crystal Ni-rich layered oxide cathodes and the challenges and strategies associated with their synthesis. In Chapter 2, we investigate the dopant redistribution, phase propagation, and local chemical changes of layered oxides at multiple length scales using a multielement-doped LiNi0.96Mg0.02Ti0.02O2 (Mg/Ti-LNO) as a model platform. We observed that dopants Mg and Ti diffuse from the surface to the bulk of cathode particles below 300 °C long before the formation of any layered phase, using a range of synchrotron spectroscopic and imaging diagnostic tools. After calcination, Ti is still enriched at the cathode particle surface, while Mg has a relatively uniform distribution throughout cathode particles. Our findings provide experimental guidance for manipulating the dopant distribution upon cathode synthesis. In Chapter 3, we synthesized Mn(OH)2-coated single crystal LiNiO2 (LNO) and used it as the platform to monitor the Mn redistribution and the structural and chemical evolution of the LNO cathode. We use in situ transmission X-ray microscopy (TXM) to track the Mn tomography inside the LNO particle and Ni oxidation state evolution at various temperatures below 700 °C. We further reveal chemical and structural changes induced by different extents of Mn diffusion at ensemble-averaged scale, which validates the results at the single particle scale. The ion diffusion behavior in the cathode is highly temperature dependent. Our study provides guidance for ion distribution manipulation during cathode modification. In Chapter 4, we successfully fabricated a surface passivation layer for NMC particles via a feasible quenching approach. A combination of bulk and surface structural characterization methods show the correlation of surface layer with bulk chemistry including valence state and charge distribution. Our design enables high interfacial stability and homogeneous charge distribution, impelling superior electrochemical performance of NMC cathode materials. This study provides insights into the cathode surface layer design for modifying other high-capacity cathodes in LIBs. In Chapter 5, we use statistical tools to identify the significance of multiple synthetic parameters in the molten salt synthesis of single crystal Ni-rich NMC cathodes. We also create a prediction model to forecast the performance of synthesized single crystal Ni-rich NMC cathodes from the input of synthetic parameters with relatively high prediction accuracy. Guided by the models, we synthesize single crystal LiNi0.9Co0.05Mn0.05O2 (SC-N90) with different particle sizes. We find large single crystals show worse capacity and cycle life than small single crystals especially at high current rates due to slower Li kinetics. However, large single crystal has higher thermal stability potentially because of smaller specific surface area. The findings of particle size effect on the performance provide insights into size engineering while developing next-generation single crystal Ni-rich NMC cathodes. The statistical and prediction models developed in this study can guide the molten salt synthesis of Ni rich cathodes and simplify the optimization process of synthetic parameters. Chapter 6 summarizes our efforts on the novel design and fundamental understanding of the state-of-the-art cathodes. We also provide our future perspectives for the development of LIBs. / Doctor of Philosophy / Lithium-ion batteries (LIBs) have been studied for decades and are widely applied in electronics and vehicles because of their high energy density and long lifetime. With the increasing demand for higher energy density, particularly in electric vehicles, the development of Ni-based layered oxide cathode materials has been focused on increasing the Ni content. Meanwhile, decreasing or eliminating Co has become a consensus due to its high cost, toxicity, and human rights issues during mining. Enhancing the stability of these Ni-rich and low/no-Co layered oxide cathodes is challenging yet crucial to their practical applications. Herein, we design and synthesize multiple Ni-rich and low/no-Co layered cathodes through ion distribution engineering and structure modification at various length scales. We also investigate the dopant redistribution, phase propagation, and local chemical changes during layered oxides cathode formation through a combination of complementary characterization methods at different length scales. In addition, we provide guidance for synthesis optimization by statistical correlations and performance prediction models with the input of synthetic conditions. Overall, this dissertation provides insights into the design and synthesis principles of Ni-rich low/no-Co layered oxide cathode, which can facilitate the transition to a sustainable future with next-generation LIBs.

This work reports the experimental and numerical study of the thermal management of Li-ion battery packs under the context of electric vehicle (EV) or hybrid EV (HEV) applications. Li-ion batteries have been extensively demonstrated as an important power source for EVs or HEVs. However, thermal management is a critical challenge for their widespread deployment, due to their highly dynamic operation and the wide range of environments under which they operate. To address these challenges, this work developed several experimental platforms to study adaptive thermal management strategies. Parallel to the experimental effort, multi-disciplinary models integrating heat transfer, fluid mechanics, and electro-thermal dynamics have been developed and validated, including detailed CFD models and lumped parameter models. The major contributions are twofold. First, this work developed actively controlled strategies and experimentally demonstrated their effectiveness on a practical sized battery pack and dynamic thermal loads. The results show that these strategies effectively reduced both the parasitic energy consumption and the temperature non-uniformity while maintaining the maximum temperature rise in the pack. Second, this work established a new two dimensional lumped parameter thermal model to overcome the limitations of existing thermal models and extend their applicable range. This new model provides accurate surface and core temperatures simulations comparable to detailed CFD models with a fraction of the computational cost. / Ph. D.