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.

Examination of the Effect of Time Delay on Fragmentation

The main objective of blasting is to produce optimum fragmentation for downstream processing. Fragmentation is usually considered optimum when the average fragment size is minimum and the fragmentation distribution as uniform as possible. One of the parameters affecting blasting fragmentation is believed to be time delay between holes of the same row. Although one can find a significant number of studies in the literature, which examine the relationship between time delay and fragmentation, their results have been often controversial. The purpose of this work is to increase the level of understanding of how time delay between holes of the same row affects fragmentation. Two series of experiments were conducted for this purpose. The first series involved tests on small scale grout and granite blocks to determine the moment of burden detachment. The instrumentation used for these experiments consisted mainly of strain gauges and piezoelectric sensors. Some experiments were also recorded with a high speed camera. It was concluded that the time of detachment for this specific setup is between 300 and 600 μs. The second series of experiments involved blasting of a 2 meter high granite bench and its purpose was the determination of the hole-to-hole delay that provides optimum fragmentation. The fragmentation results were assessed with image analysis software. Moreover, vibration was measured close to the blast and the experiments were recorded with high speed cameras. The results suggest that fragmentation was optimum when delays between 4 and 6 ms were used for this specific setup. Also, it was found that the moment at which gases first appear to be venting from the face was consistently around 6 ms after detonation.