Mark Bowkett

Comparative analysis of failure detection methods of composites materials’ systems

ABSTRACT This paper presents a review and analysis of current non-destructive failure detection methods of composite materials and a brief outline of the build of a bamboo bicycle which has been used as a development platform and test bed for the initial development of a novel and practical non-destructive failure detection solution, which has future compatibility for carbon-fibre (CF)-based bicycles. The paper begins by presenting the current market condition of composite materials and in particular, CF and CF-reinforced plastic, and then follows onto failure modes and proceeds to investigate a comprehensive range of failure detection methods.

Review and analysis of failure detection methods of composites materials systems

This paper presents a review and analysis of failure detection methods of composites materials systems and development and application of a bamboo bicycle. The paper begins by presenting the current market condition of composites materials and in particular, carbon fibre and carbon fibre reinforced plastic (CFRF). The work proceeds to investigate the failure detection methods that have been applied to develop a carbon fibre bicycle with reference to a bamboo bicycle.

Design and implementation of an open circuit voltage prediction mechanism for lithium-ion battery systems

This paper describes an open circuit voltage (OCV) prediction technique for lithium cells. The work contains an investigation to examine the charge and mixed state relaxation voltage curves, to analyse the potential for the OCV prediction technique in a practical system. The underlying principal of the technique described in this paper employs a simple equation paired with a polynomial to predict the equilibrated cell voltage after a small rest period. The polynomial coefficients are devised by the use of curve fitting and system identification techniques. The practical work detailed in this paper was conducted at the Centre for Automotive and Power System Engineering (CAPSE) battery laboratories at the University of South Wales. The results indicate that the proposed OCV prediction technique is highly effective and may be implemented with a simple battery management system.

Design and implementation of OCV prediction mechanism for PV-lithium ion battery system

This paper describes the design and implementation of an open circuit voltage (OCV) prediction mechanism for Li-ion based battery systems. This approach involves the development of a simulation model incorporating Li-ion cells, modules and later the PV-battery system. The simulation model is used to analyse the effect of the prediction mechanism and is validated with the experimental data obtained through the tests conducted at the Centre for Automotive and Power System Engineering (CAPSE) battery laboratories, at the University of South Wales. This approach could be used for controller development, to improve operational quality and performance with an appropriate BMS system design that makes use of the technique. To prove that the technique works in a real world system the prediction mechanism has been built into a BMS currently being developed in the CAPSE labs.

Failure Detection of Composites with Control System Corrective Response in Drone System Applications

The paper describes a novel method for the detection of damage in carbon composites as used in drone frames. When damage is detected a further novel corrective response is initiated in the quadcopter flight controller to switch from a four-arm control system to a three-arm control system. This is made possible as a symmetrical frame is utilized, which allows for a balanced weight distribution between both the undamaged quadcopter and the fallback tri-copter layout. The resulting work allows for continued flight where this was not previously possible. Further developing work includes improved flight stability with the aid of an underslung load model. This is beneficial to the quadcopter as a damaged arm attached to the main body by the motor wires behaves as an underslung load. The underslung load works are also transferable in a dual master and slave drone system where the master drone transports a smaller slave drone by a tether, which acts as an underslung load.

Enhanced OCV prediction mechanism for a stand-alone PV-lithium ion renewable energy system

This paper aims to improve the estimation of state of charge (SoC) of the battery component for a small-scale photovoltaic stand-alone system through the use of a simple summing equation, at a set measurement interval. The system uses a predefined parameter to accurately predict the open-circuit voltage (OCV) of a cell at a much reduced measurement time of 5 minutes, while maintaining a maximum prediction error of less than 1%SoC. A simulation model has been provided that allows measurement of the cell voltage and current for prediction of the equilibrated OCV. The simulation can be used for single cell, modules and battery packs which use lithium-based technologies. Validation of the model has been performed using experimental data from tests conducted at the Centre for Automotive and Power System Engineering (CAPSE) laboratories, at the University of South Wales. An application has been proposed for this work, which includes a photovoltaic module for energy generation to power an illuminated advertizing sign. The energy is stored in a lithium-based battery model which uses a combination of a battery management system and remote monitoring for real-time data acquisition.

Advanced EIS Techniques for Performance Evaluation of Li-ion Cells

Abstract This paper provides an advanced electrochemical impedance spectroscopy (EIS) technique for improving the state of charge and state of health estimation of Li-ion cells. This advanced technique is derived from various tests and experimental studies conducted in the CAPSE labs at the University of South Wales. The results indicate that the technique is very accurate compared to other methods such as coulomb counting and OCV prediction method.