The increased deployment for renewable energy sources to mitigate the climate crisis has accelerated the need to develop efficient energy storage devices. Batteries are at the top of the list of the most in-demand devices in the current decade. Nowadays, research is in full swing to develop a battery that meets the needs of today’s renewable energy systems, which are intermittent by nature. Within the framework of improving the performance of batteries, there are parameters in the composition of the battery that play an important role in its performance: electrode materials, electrolytes, separators, and other factors. The key to battery development is the manufacture of electrode materials with optimal properties. Two-dimensional (2D) materials have led to advances in this field, firstly, using graphite as the anode in lithium-ion batteries (LIBs). However, when using the standard graphite as the anode for sodium-ion batteries (NIBs), the large ionic size and energetic instability of Na+ limit intercalation, resulting in a low storage capacity. Therefore, other 2D materials with large interlayer spacing need to be identified for use as electrodes. In this dissertation, our approach is focus on optimizing anode electrode materials by in situ conversion of 2D materials to obtain hybrid materials. These hybrids materials will synergistically improve the performance of LIBs and NIBs by combining the advantages of individual 2D materials. Starting with converted Ti0.87O2 nanosheets to the TiO2/TiS2 hybrid nanosheets. Then, taking advantage of the properties of MXene, we developed hybrid electrodes based on MXenes by converted V2CTx MXene into V2S3@C@V2S3 heterostructures. Finally, we boosted the redox kinetics and cycling stability of Mo2CTx MXene by using a laser scribing process to construct a multiple-scale Mo2CTx/Mo2C-carbon (LS-Mo2CTx) hybrid material.

This paper examines the possibility of adding a photovoltaic(PV) power station to an already planned wind park in terms of profitability. At this time, southern Sweden’s grid is facing a number of challenges and is hurting economic development. Hybrid parks have showed to be able to tackle some of those challenges. This study has used a two-scaled methodology to analyse which solar PV size is the optimal to be co-located to the wind park of 24MW[Office1] . The results show that the 21MW size is the ideal one. In addition, to complement the findings, an analysis has been conducted to determine which battery size would be the optimal size to be added to the hybrid system. The results showed that a 1MW/1MWh battery storage would be the ideal size, however, it is possible that a 5MW/MWh battery storage might produce better results if peak shaving is included. All the scenarios in this study have been analysed in terms of IRR.

Together with electrification of the transportation sector and the introduction of renewable energy in the electricity grid, the demand for lithium-ion batteries is increasing. As a result of this emerging need, large-scale battery manufacturing is a promising and developing industry. Currently, there exist a challenge for lithium-ion battery manufacturers to ensure supply of the desired material and to guarantee operation in a sustainable manner. The material included in a battery cell possess unique characteristics, has high criticality, and experience limited availability, which has resulted in an un- certain business environment with high complexity. Hence, the aim of this thesis is to investigate how unique material characteristics affect the purchasing environment and can be considered to obtain a sustainable inbound supply chain for lithium-ion battery manufacturers. The study is based on the following research question; How can purchasing of critical direct material for lithium-ion battery manufacturers support a sustainable inbound supply chain?

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This study characterizes production-line defects in lithium-ion batteries' anode, cathode, and separators. Lithium-ion batteries demand has increased tremendously in the last decades due to their use in various applications, including electric vehicles, portable electronics, and energy storage systems. Therefore, characterizing defects in these batteries is crucial to understand their performance and reliability. This study uses scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) analysis to identify and analyze defects in the battery components. The major critical defects encountered in the study are impurities, contaminations, agglomerates, point defects, line defects, and more. This study helps improve the quality and reliability of lithium-ion batteries by providing guidelines to analyze and address essential deficiencies during the manufacturing process. / Denna studie karakteriserar produktionslinjedefekter i litiumjonbatteriers anod, katod och separatorer. Efterfrågan på litiumjonbatterier har ökat enormt under de senaste decennierna på grund av deras användning i olika applikationer, inklusive elfordon, bärbar elektronik och energilagringssystem. Därför är det avgörande att karakterisera defekter i dessa batterier för att förstå deras prestanda och tillförlitlighet. Denna studie använder svepelektronmikroskopi (SEM) och energidispersiv röntgenspektroskopi (EDS) analys för att identifiera och analysera defekter i batterikomponenterna. De största kritiska defekterna som påträffats i studien är föroreningar, föroreningar, agglomerat, punktdefekter, linjedefekter med mera. Denna studie hjälper till att förbättra kvaliteten och tillförlitligheten hos litiumjonbatterier genom att tillhandahålla riktlinjer för att analysera och åtgärda väsentliga brister under tillverkningsprocessen

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A process, called carbon nanotube templated microfabrication (CNT-M) makes high aspect ratio microstructures out of a wide variety of materials by growing patterned vertically aligned carbon nanotubes (VACNTs) as a framework and then infiltrating various materials into the frameworks by chemical vapor deposition (CVD). By using the CNT-M procedure, a partial Si infiltration of carbon nanotube frameworks results in porous three dimensional microscale shapes consisting of silicon-carbon nanotube composites. The addition of thin silicon shells to the vertically aligned CNTs (VACNTs) enables the fabrication of robust silicon nanostructures with edibility to design a wide range of geometries. Nanoscale dimensions are determined by the diameter and spacing of the resulting silicon/carbon nanotubes while microscale dimensions are controlled by the lithographic patterning of CNT growth catalyst. The characterization and application of the new silicon nanomaterial, silicon-carbon core-shell nanotube (Si/CNT) composite, is investigated thoroughly in the dissertation.The Si/CNT composite is used as thin layer chromatography (TLC) separations media with precise microscale channels for fluid flow control and nanoscale porosity for high analyte capacity. Chemical separations done on the CNT-M structured media outperform commercial high performance TLC media resulting from separation efficiency and retention factor. The Si/CNT composite is also used as an anode material for lithium ion batteries. The composite is assembled into cells and tested by cycling against a lithium counter electrode. This CNT-M structured composite provides an effective test bed for studying the effects of geometry (e.g. electrode thickness, porosity, and surface area) on capacity and cycling performance. A combination of high gravimetric, volumetric, and areal capacity makes the composite an enabling materials system for high performance Li-ion batteries.Last, a thermal annealing to the Si/CNT composite results in the formation of silicon carbide nanowires (SiCNWs). This combination of annealing and Si/CNTs yields a unique fabrication approach resulting in porous three dimensional silicon carbide structures with precise control over shape and porosity.

The research presented in this thesis focuses on developing new functional polymeric materials that can conduct ions, H+, or OH- or Li+. The motivation behind this work was to understand the similarities and/or differences in the structure property relationships between polymer membranes and the conductivity of H+ and OH- ions, and between polymer membranes and the anhydrous conductivity of H+ and Li+ ions. This understanding is critical to developing durable polymer membranes with high H+, OH- and Li+ ion conductivity for proton exchange membrane fuel cells (PEMFCs), alkaline anion exchange membrane fuel cells (AAEMFCs) and lithium ion batteries respectively. Chapter 1 describes the basic functioning of PEMFCs, AAEMFCs and lithium ion batteries, the challenges associated with each research topic, and the fundamental mechanisms of ion transport. The proton conducting properties of poly(4-vinyl-1H-1,2,3-triazole) were investigated on a macroscopic scale by impedance spectroscopy and microscopic scale by solid state MAS NMR. It was found that proton conductivity is independent of molecular weight of the polymer, but influenced by orders of magnitude by the presence of residual dimethylformamide. To improve the mechanical properties of otherwise liquid-like 1H-1,2,3-triazole functionalized polysiloxane homopolymers, hybrid inorganic-organic proton exchange membranes (PEMs) containing 1H-viii 1,2,3-triazole grafted alkoxy silanes were synthesized, using sol-gel chemistry. This method enabled self-supporting membranes having proton conductivity comparable to uncrosslinked homopolymers. One of the biggest challenges with AEMs for use in AAEMFCs is finding a cationic polyelectrolyte that is chemically stable at elevated temperatures in high pH environment. Novel triazolium ionic salts were developed, having greater chemical stability under alkaline conditions compared to existing imidazolium ionic salts. However, the chemical stability of triazolium cations was not sufficient for AAEMFC applications. Excellent chemical stability of (C5H5)2Co+ in 2 M NaOH at 80°C over 30 days was demonstrated and polymerizable vinyl functionalized cobaltocenium monomers were synthesized. This work paves the way for future development of AEMs containing cobaltocenium moieties to facilitate hydroxide ion transport. Polymers containing covalently attached cyclic carbonates were synthesized and doped with lithium triflate and their lithium ion conductivities were investigated. The findings highlight the importance of high charge carrier density and flexibility of the polymer matrix to achieve high lithium ion conductivity. These results are similar to the key factors influencing anhydrous proton transport.

This thesis focuses on the development of oxidatively stable cathode and electrolyte materials for sodium-based battery systems. This is primarily achieved through the use of solid-state nuclear magnetic resonance (ssNMR) and pulsed-field gradient (PFG) NMR spectroscopy. ssNMR is used to diagnose the primarily failure mode of the NaOB. It is found through a combined 23Na and 19F study that the main discharge product of the cell, NaO2, oxidizes both the carbon and polyvinylidene fluoride (PVDF) binder of the cathode to produce parasitic Na2CO3 and NaF. In a subsequent study, Ti4O7-coated carbon paper cathodes are implemented in an attempt to stabilize NaO2. The 23Na triple quantum magic angle spinning (3QMAS) and 1H to 23Na dipolar heteronuclear multiple quantum correlation (23Na{1H} D-HMQC) experiments are used to diagnose the failure modes of carbon-coated, and Ti4O7-coated cathodes. It is found that electrochemically formed NaO2 is significantly more stable in Ti4O7-coated cathodes, leading to longer lifetime NaOBs. Oxidatively stable electrolyte materials are also examined. Lithium and sodium bis(trifluoromethansulfonyl)imide (TFSI) in adiponitrile (ADN) electrolytes exhibit extreme oxidative resistance, but are unusable in modern cells due to Al corrosion by TFSI, and spontaneous ADN degradation by Li and Na metal. PFG NMR is used to investigate the transport properties of LiTFSI in ADN as a function of LiTFSI concentration. By measuring the diffusion coefficient of Li+ and TFSI as a function of diffusion time (Δ), diffusional behaviour is encoded as a function of length scale to study the short- and long-range solution structure of the electrolyte. It is found that at high concentrations, LiTFSI in ADN transports Li+ primarily through an ion-hopping mechanism, in contrast to the typical vehicular mechanism observed at low concentrations. This suggests significant structural changes in solution at high concentrations. The NaTFSI in ADN analogue is examined for its electrochemical properties in Na-ion and Na-O2 batteries. It is found that the oxidative resistance of ADN to Na metal is significantly increased at high concentrations, leading to reversible Na deposition and dissolution in cyclic voltammetry (CV) experiments. Linear sweep voltammetry (LSV) and chronoamperometry (CA) experiments on Al current collectors show that Al corrosion by TFSI is similarly suppressed at high concentration. This culminates in high concentration NaTFSI in ADN being able to reversibly intercalate Na3V2(PO4)2F3 (NVPF) cathodes in SIB half-cells for multiple cycles. The knowledge gained from exploring oxidatively stable cathode and electrolyte materials can be used in tandem for the development of a longer lifetime, more oxidatively stable, NaOB in the future. / Thesis / Doctor of Philosophy (PhD) / The continued development of rechargeable batteries is paramount in reducing the world’s reliance on fossil fuels, as they allow for the storage of electrical energy produced by renewable sources. This work primarily examines sodium-based batteries systems, such as the sodium-oxygen battery (NaOB) and sodium-ion battery (SIB), which are possible alternatives to the currently used lithium-ion battery (LIB) system. In order to produce energy, NaOBs produce sodium superoxide (NaO2) during the discharge process, which is formed on the carbon cathode. However, NaO2 is inherently unstable to carbon materials, causing degradation of the battery overtime. Ti4O7 is investigated as a stable coating material in NaOBs, used to coat the carbon cathode to make the system more stable to NaO2 degradation. The degradation processes in NaOBs are characterized by solid state nuclear magnetic resonance (ssNMR) spectroscopy, which uses strong superconducting magnets to probe the magnetic properties of, and consequently identify, the chemical species formed within the battery. It is found that the addition of the Ti4O7 coating inhibits NaO2 degradation, producing longer lifetime NaOBs. Subsequently, both Li-bis(trifluoromethansulfonyl)imide (LiTFSI), and NaTFSI, in adiponitrile (ADN) electrolytes are examined for their use in LIBs and SIBs, respectively. Electrolytes facilitate stable ion transport within the cell, and ADN electrolytes specifically allow for the use of higher voltage cathode materials, which can result in a higher energy density battery. The transport properties of LiTFSI in ADN electrolytes are studied by a pulsed-field gradient (PFG) NMR technique, that allows for the measurement of the rate of ion transport in the electrolyte. It is found that the mechanism of ion transport significantly depends on electrolyte concentration, which suggests significant changes to the electrolyte solution structure at high concentration. The electrochemical ramifications of this are studied for the NaTFSI in ADN electrolyte in SIBs. It is found that the electrolyte becomes substantially more stable at high concentrations, leading to more favourable charging and discharging behaviours when tested in SIBs. The work presented in this thesis illustrates the development of more stable, longer lifetime, batteries over a number of cell chemistries, using a variety of NMR and electrochemical characterization techniques.

Recently, lithium-ion batteries (LIBs) have achieved wide acceptance for various energy storage applications, such as electric vehicles (EVs) and smart grids. As a vital component in EVs, the performance of lithium-ion batteries in the last few decades has made significant progress. The development of a robust battery management system (BMS) has become a necessity to ensure the reliability and safety of battery packs. In addition, state of charge (SOC) estimation and thermal models with high-fidelity are essential to ensure efficient BMS performance. The SOC of a LIB is an essential factor that should be reported to the vehicle’s electronic control unit and the driver. Inaccurate reported SOC impacts the reliability and safety of the lithium-ion battery packs (LIBP) and the vehicle. Different algorithms are used to estimate the SOC of a LIBP, including measurement-based, adaptive filters and observers, and data-driven; however, there is a gap in feasibility studies of running these algorithms for multi-cell LIBP on BMS microprocessors. On the other hand, temperature sensors are utilized to monitor the temperature of the cells in LIBPs. Using a temperature sensor for every cell is often impractical due to cost and wiring complexity. Robust temperature estimation models can replace physical sensors and help the fault detection algorithms by providing a redundant monitoring system. In this thesis, an accurate SOC estimation and thermal modeling for lithium-ion batteries (LIBs) are presented using deep neural networks (DNNs). Firstly, two DNN-based SOC estimation algorithms, including a feedforward neural network (FNN) enhanced with external filters and a recurrent neural network with a long short-term memory layer (LSTM), are developed and benchmarked versus an extended Kalman filter (EKF) and EKF with recursive least squares filter (EKF-RLS) SOC estimation algorithms. The execution time of EKF, EKF-RLS, FNN, and LSTM SOC estimation algorithms with similar accuracy was found to be 0.24 ms, 0.25 ms, 0.14 ms, and 0.71 ms, respectively. The DNN SOC estimation algorithms were also demonstrated to have lower RAM use than the EKFs, with less than 1 kB RAM required to run one estimator. The proposed FNN and LSTM models are also used to predict the surface temperature of different lithium-ion cells. These DNN models are shown to be capable of estimating temperature with less than 2 ⁰C root mean square error for challenging low ambient temperature drive cycles and just 0.3 ⁰C for 4C rate fast charging conditions. In addition, a DNN model which is trained to estimate the temperature of a new battery cell, is found to still have a very low error of just 0.8 ⁰C when tested on an aged cell. Finally, an integrated physics, and neural network-based battery pack thermal model (LP+FNN) is developed and used to detect and identify different thermal faults of a LIBP. The proposed fault detection and identification method is validated using various thermal faults, including fan system failure, airflow lower and higher than setpoint, airflow blockage of submodule and temperature sensor reading faults. The proposed method is able to detect different cooling system faults within 10 to 35 minutes after fault occurrence. In addition, the proposed method demonstrated being capable of detecting temperature sensor reading offset and scale faults of ±3 ⁰C and ±0.15% or more, respectively with 100% accuracy. / Thesis / Doctor of Philosophy (PhD)