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.

Genetic architecture and sexual conflict in the life history of Drosophila

Because males and females of a species express many homologous traits, sex-specific selection on these traits can shift the opposite sex away from its phenotypic optimum. This mode of sexually antagonistic selection, known as intralocus sexual conflict (IaSC), arises when the evolution of sexual dimorphism is constrained by the two sexes sharing a common gene pool. As IaSC has been historically overlooked, many outstanding questions remain. For example, what is its contribution in maintaining genetic variation for fitness in populations? What characters underlie this variation in fitness? How does the selection history of the population influence the standing genetic variation? I used the model organism Drosophila melanogaster to attempt to resolve some of these questions. The first part of my Master’s project involved assessing the detectability of sexually antagonistic alleles in populations at different stages of adaptation to the laboratory. For the second part of my Master’s project, I looked for evidence of conflict during the development of body size, a well-known sexually dimorphic trait. While the first part of my thesis proved inconclusive, the second part revealed a surprising source of sexual conflict in pre-adult stages of D. melanogaster.