Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2011 / The purpose of this thesis was to design and develop a measurement system that would allow accurate measurement of individual cell voltages in a series cell stack. The system was initially proposed to be used in conjunction with an active cell balancer. This would allow for the efficient equalising of cells as well as provide detailed information on the cell stack and how the stack operates over time. Having a system that measures voltages accurately, with which the active cell balancer can be controlled would allow for peak cell lifetime and performance. Current battery management systems are large, complex and inefficient and a new way of battery management had to be investigated. To accurately measure individual cells in a series stack, the high common mode voltage must be negated. Different techniques that are currently used to create galvanic isolation were reviewed; circuits were designed and were simulated to find the most suitable design. The traditional methods used to create galvanic isolation did not provide adequate results. The methods were too inefficient and not accurate enough to be used. The methods that had the required accuracy were too complicated to connect in a useable system. This led to the investigation of integrated circuits created to measure voltages in large cell stacks. An integrated circuit from Linear Technology was chosen and a system was built. A system was thus designed that fulfilled the most desirable design specifications while delivering excellent results. The system allowed accurate, individual voltages to be measured in the presence of high common mode voltages. Accuracies and measurement time were well below the required system specification. Power consumption was high, but different component choice will lower power consumption to within specification. Excellent results were obtained overall with most, although not all results well below the design specifications. By including current measurements, as well as other technologies such as wireless communication, USB connectivity and a better data processor, this system will be at the forefront of current battery management technology.

Battery research has been going full steam and with that the search for alternative anodes. Among many proposed electrode materials, little attention has been given to phosphorus. Phosphorus boasts the third highest gravimetric charge capacity and the highest volumetric charge capacity of all elements. Because of that, it would be an attractive battery anode material were it not for its poor cyclability with significant capacity loss immediately after the first cycle. This is known to be the consequence of considerable volume changes of phosphorus during charge/discharge cycles. In this work, we propose circumventing this issue by mixing amorphous red phosphorus with carbon nanotubes. By employing a non-destructive sublimation-deposition method, we have synthesized composites where the synergetic effect between phosphorus and carbon nanotubes allow for an improvement in the electrochemical performance of battery anodes. In fact, it has been shown that carbon nanotubes can act as an effective buffer to phosphorus volumetric expansions and contractions during charging and discharging of the half-cells [1]. By modifying the synthesis parameters, we have also been able to change the degree of crystallinity of the phosphorus matrix in the composites. In fact, the less common phase of red phosphorus, named fibrous phosphorus, was obtained, and that explains some of the varying electrochemical performances observed in the composites. Overall, it is found that a higher surface area of amorphous phosphorus allows for a better anode material when using single-walled carbon nanotubes as fillers.

Abstract: TEM is one of the most powerful technologies for material research. In-situ TEM is a TEM technique that allows us to study samples in real-time. Researchers can focus on one area and change the conditions under the electron beam to acquire much more data from the material than conventional TEM techniques. In this research, we use the in-situ TEM technique to observe the rechargeable aqueous zinc-ion batteries which have been considered as a promising candidate for next-generation batteries. We established the platform for the aqueous battery system and studied the charge and discharge processes for both cathode and anode materials in rechargeable aqueous zinc-ion batteries for the first time. Besides, we also combined low-dose TEM techniques to observe the HRTEM images of the electrode materials to probe the change on the surface of the cathode materials and the mechanism of dendrite growth in rechargeable aqueous zinc-ion batteries.

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A Denial of Service (DoS) attack is an incident in which the user is deprived of the services of a resource he is expected to have. With the increasing reliance on mobile devices like laptops and palmtops, a new type of DoS attack is possible that attacks the batteries of these devices, called "sleep deprivation attacks". The goal of sleep deprivation attacks is to rapidly drain the battery of the mobile devices, rendering the device inoperable long before the expected battery lifetime, thus denying the service the user expects from the mobile device. The purpose of this research is to investigate these types of attacks so that proper defense mechanisms can be put in place before the attacks become a more sophisticated and potent force. This research presents three different possible methods that can be adopted by an attacker to drain the battery of a device i.e. malignant attacks, benign attacks and network service request attacks. These attacks are implemented on a variety of mobile computing platforms like palmtops and a laptop and the corresponding results are presented. Finally, a mathematical model is presented that estimates the battery life of a device based on its power consumption in various power management states and expected usage. This model can also be used to predict the impact of a DoS attack on the battery life of the device under attack. / Master of Science

Within the framework of this thesis, three innovative electrochemical devices have been studied. A part of the work is devoted to an already existing device, laminates which are debonded by the application of a voltage. This type of material can potentially be used in a wide range of applications, including adhesive joints in vehicles to both reduce the total weight and to simplify the disassembly after end-of-life, enabling an inexpensive recycling process. Although already a functioning device, the development and tailoring of this process was slowed by a lack of knowledge concerning the actual electrochemical processes responsible for the debonding. The laminate studied consisted of an epoxy adhesive, mixed with an ionic liquid, bonding two aluminium foils. The results showed that the electrochemical reaction taking place at the releasing anode interface caused a very large increase in potential during galvanostatic polarization. Scanning electron microscopy images showed reaction products growing out from the electrode surface into the adhesive. These reaction products were believed to cause the debonding through swelling of the anodic interface so rupturing the adhesive bond. The other part of the work in this thesis was aimed at innovative lithium ion (Li‑ion) battery concepts. Commercial Li-ion batteries are two-dimensional thin film constructions utilized in most often mechanically rigid products. Two routes were followed in this thesis. In the first, the aim was flexible batteries that could be used in applications such as bendable reading devices. For this purpose, nano-fibrillated cellulose was used as binder material to make flexible battery components. This was achieved through a water-based filtration process, creating flexible and strong papers. These paper-based battery components showed good mechanical properties as well as good rate capabilities during cycling. The drawback using this method was relatively low coulombic efficiencies believed to originate from side-reactions caused by water remnants in the cellulose structure. The second Li-ion battery route comprised an electrochemical process to coat carbon fibers, shown to perform well as negative electrode in Li-ion batteries, from a monomer solution. The resulting polymer coatings were ~500 nm thick and contained lithium ions. This process could be controlled by mainly salt content in the monomer solution and polarization time, yielding thin and apparently pin-hole free coatings. By utilizing the carbon fiber/polymer composite as integrated electrode and electrolyte, a variety of battery designs could possibly be created, such as three-dimensional batteries and structural batteries. / <p>QC 20130403</p>

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)