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Item Open Access A Paradigm Shift Toward Zero Accident(Cranfield University, 2017-09-22 08:36) Soltani, AmirmasoudPresented at the "Future of Transportation" World Conference, July 2017, Cologne, Germany.Item Open Access Battery thermal management system design, modelling and optimisation(Cranfield University, 2018-10-22 10:41) valerio Morganti, Manlio3 Minute Thesis presented at the Cranfield Doctoral Network Annual Event 2018. The growth of the electric vehicle market has led to an increase in the diffusion of batteries. Batteries are energy storage devices subject to uneven heat generation, having unisotropic thermal properties and being forced to comply with tight temperature range requirements (-10°C to 40°C), to avoid aging and permanent performance drop at low temperatures and safety concerns at high temperatures. In addition to that, the temperature gradient across a battery pack, across a module and across a single cell, needs to be monitored in order to prevent a battery life shortening. In such scenario, literature lacks of medium-fidelity coupled-physics models that can simulate both the electrical and the thermal behaviour of the battery cells at a low computational cost. In addition, no systematic methodology for battery thermal management design is currently available. The aim of this work is to provide a battery thermal management design procedure based on a coupled-physics model of a single cell that can be scaled up to a module and a pack model. The proposed simulation library allows the quick implementation of thermal models of different cell chemistries and geometries. A single cell model is then used to populate a whole module model. More modules populate a pack model. The use of a multi-physics simulation tool keeps computational costs much lower than a full-scale finite-element-method-based software. In order to ensure the reliability of results, models are validated against a single-module test rig. A liquid indirect thermal management is taken as case study. Different scenarios and options are examined and optimal solutions are proposed in each case. Objectives are minimisation of weight, cost, volume and energy consumption and operating temperature ranges and temperature gradients are taken as constraints. This methodology is lean, flexible and can be adapted to different vehicle classes reducing development time and costs.Item Open Access Distributed gas sensing using microstructured optical fibres(Cranfield University, 2018-10-22 10:51) Bremner, James3 Minute Thesis presented at the Cranfield Doctoral Network Annual Event 2018. With a global warming potential 34 times that of CO2, as well as an explosion hazard, methane monitoring is of interest. Current technology requires the placement of a large number of sensors to cover an area. We propose a distributed technique to allow the use of a single measurement device to cover multiple sampling sites. Tunable Diode Laser Spectroscopy has been combined with optical fibre coupling of gas cells to permit a large number of cells to be interrogated simultaneously. Techniques to multiplex a number of TDLS cells together have been developed including time-division-multiplexing, Optical Time Domain Reflectometry and use of multiple fibres, each with its own detector.Range Resolved Interferometry (RRI) is an interferometric signal processing technique that has been used for position sensing and vibrometry. The principle of operation is the sinusoidal modulation of the emission wavelength of a diode laser which is input into an interferometer. The signal is demodulated to give amplitude information within each interferometer. Signals from different interferometers can be distinguished based on the optical path length difference, enabling interrogation of all measurement channels simultaneously.Here, a combination of RRI and absorption spectroscopy is performed to multiplex two gas cells arranged to form two interferometers and to recover gas concentrations from the two cells independently. The configuration is two 1m path length single-pass gas cells connected via different lengths of optical fibre in a nested Mach-Zehnder interferometer along with a common reference arm. The two gas cells were filled with different concentrations of methane. A distributed feedback diode laser was modulated with a ramp and sinusoidal wave form. The ramp sweeps the laser emission frequency across a methane absorption line at 1651nm, while the sinusoidal modulation generates interference patterns.RRI was used to recover the amplitude from the two gas cells and thereby the concentration of methane.Item Open Access How accurate is state of charge as a predictor of remaining useful work? (ICLSB 2019)(Cranfield University, 2021-05-13 09:21) Auger, Daniel; Munisamy, Srinivasan; Fotouhi, AbbasPresentation given at ICLSB 2019. Abstract follows: It is well known that lithium sulfur cells have a distinctive open-circuit voltage profile: at high states of charge there is a €˜high plateau€™, starting at around 2.35 V, and at low states of charge there is a flatter €˜low plateau€™ at near constant voltage. This presentation will discuss the implications this profile might have for the prediction of the work that cell is capable of doing before it is fully discharged, which is vital for real-world applications. This presentation will introduce a family of techniques that has been developed for the creation of low-complexity dynamic models [1,2] and their application in state estimation algorithms embedded within real-life battery management systems using extended Kalman filters, unscented Kalman filters and particle filters [3,4] or adaptive neuro-fuzzy inference systems (ANFIS) [5]. So far, algorithms for management of lithium-sulfur have all been based on state of charge, rather than €˜remaining energy€™. In a practical application, the real information the end user needs is an answer to the question €˜how much work can I still do?€™ The work done by a cell is the product of the terminal voltage and the current delivered to the load, and a Coulomb-based metric, dependent on current alone, is only a proxy for this. In this presentation, we explore the question €˜how accurate is state of charge as a predictor of remaining useful work?€™ In this presentation, the title question is addressed, both using theoretical and simulation studies comparing a lithium-ion cell [6] from the literature with a model of development-grade industrial lithium sulfur cell [1] and through the analysis of experimental data collected from the same lithium-sulfur cell. In the theoretical studies, it is observed that with low currents, state of charge is a good predictor of remaining useful work in both the lithium-ion cell and the lithium-sulfur one, but that where the remaining useful work predictions for the lithium-ion cell are least accurate at the mid-discharge point, the remaining useful work predictions for the lithium-sulfur cell were least accurate near to the transition between the high and low plateau. The results of the theoretical analysis were supported by an analysis of the experimental data. From these results, no significant motivation was been identified for refactoring estimation algorithms in terms of state of energy. At the time this abstract is prepared, work to consider the accuracy of prediction of remaining useful work at higher loads is underway, and the results of this will also be presented at the conference. [1] Propp K, Marinescu M, Auger DJ, O'Neill L, Fotouhi A, Somasundaram K, Offer GJ, Minton G, Longo S, Wild M & Knap V (2016) Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries, Journal of Power Sources, 328 (October) 289-299. Dataset/s: 10.17862/cranfield.rd.c.3292031 [2] Fotouhi A, Auger DJ, Propp K, Longo S, Purkayastha R, O'Neill L & Walus S (2017) Lithium-Sulfur cell equivalent circuit network model parameterization and sensitivity analysis, IEEE Transactions on Vehicular Technology, 66 (9) 7711-7721. [3] Propp K, Auger DJ, Fotouhi A, Longo S & Knap V (2017) Kalman-variant estimators for state of charge in lithium-sulfur batteries, Journal of Power Sources, 343 (March) 254-267. Dataset/s: 10.17862/cranfield.rd.3834057 [4] Knap V, Auger DJ, Propp K, Fotouhi A & Stroe D-I (2018) Concurrent real-time estimation of state of health and maximum available power in lithium-sulfur batteries, Energies, 11 (2133) 1-23. [5] Fotouhi A, Auger D, Propp K & Longo S (2018) Lithium-sulfur battery state-of-charge observability analysis and estimation, IEEE Transactions on Power Electronics, 33 (7) 5847-5859. [6] Antaloae C, Marco J & Assadian F (2012) A novel method for the parameterization of a Li-ion cell model for EV/HEV control applications. IEEE Transactions on Vehicular Technology, 61(9), 3881€“3892. https://doi.org/10.1109/TVT.2012.2212474