A NOVEL MODELING AND STATE OF CHARGE ESTIMATION SCHEME FOR LITHIUM-ION BATTERIES

Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.

A Comparison of the Impacts of Lithium Extraction and Lithium Recycling Processes

Lithium is used in the cathode and electrolyte of rechargeable batteries in many portable electronics and electric vehicles, and is thus seen as a critical component of modern technology (Gruber et al., 2011). Electric vehicles are promoted as a way to reduce carbon emissions associated with the transportation sector, which accounts for 14.3% of anthropogenic greenhouse gas emissions (OECD International Transport Forum, 2010). However, the sustainability of lithium procurement will influence the overall environmental impact of this proposed “green” solution. It is estimated that 66% of the world’s lithium resource is contained in natural brines, 24% in pegmatites, and 8% in sedimentary rocks such as hectorite clays (Gruber et al., 2011). It has been shown that “[r]ecycling of lithium from Li-ion batteries may be a critical factor in balancing the supply of lithium with future demand” (Gruber et al., 2011). In an attempt to quantify energy and materials consumption associated with production of a unit of useful lithium compounds, industry reports and peer-reviewed scientific literature concerning lithium mining and lithium recycling were reviewed and compared. Other aspects of sustainability, such as waste or by-products produced in the production of a unit of useful lithium, were also explored. Thus, this paper will serve to further the evaluation of the comparative environmental consequences associated with lithium production via extraction versus recycling. Efficiencies must be made in both processes to maximize productivity while minimizing ecological harm.

U, FE, AND LI ISOTOPE RATIOS IN THE MINERALIZED AND BARREN AREAS OF THE KOMBOLGIE BASIN

The Paleo- to Meso-Proterozoic Jabiluka unconformity related uranium mine is located within the Alligator River Uranium Field, found in the Northern Territories, Australia. The uranium ore is hosted in the late middle Paleoproterozoic Cahill Formation, which is unconformably overlain by a group of unmetamorphosed conglomerates known as the Kombolgie subgroup. The Kombolgie subgroup provided the source for oxidized basinal brines, carrying U as the mobile form U(VI), which interacted with reducing lithologies in the Cahill formation, thus reducing U(VI) to the solid U(IV), and leading to the precipitation of uraninite (UO2). In order to characterize fluid interaction with the ore body and compare that to areas without mineralization, several isotopic tracers were studied on a series of clay samples from drill core at Jabiluka as well as in barren areas throughout the ARUF. Among the potential tracers, three were selected: U (redox sensitive and recent fluid mobilization), Fe (redox sensitive), and Li (fractionated by hydrothermal fluids and adsorption reactions). δ238U values were found to be closely linked to the mineralogy, with samples with higher K/Al ratios (indicating high illite and low chlorite concentrations) having higher δ238U values. This demonstrates that 235U preferentially absorbs onto the surface of chlorite during hydrothermal circulation. In addition, δ234U values lie far from secular equilibrium (δ234U of 30‰), indicating there was addition or removal of 234U from the surface of the samples from recent (<2.5Ma) interactions of mobile fluids. δ57Fe values were found to be related to lithology and spatially to known uranium deposits. Decreasing δ57Fe values were found with increasing depth to the unconformity in a drill hole directly above the ore zone, but not in drill holes in the barren area. Similarly to δ238U, δ7Li is found to correlate with mineralogy, with higher δ7Li values associated with samples with more chlorite. In addition, higher δ7Li values are found at greater depth throughout the basin, indicating that the direction of the mineralizing fluid circulation was upwards from the Cahill formation to the Kombolgie subgroup.