Evaluating the impact of V2G services on the degradation of batteries in PHEV and EV

Many researchers and industry observers claim that electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) could provide vehicle-to-grid (V2G) bulk energy and ancillary services to an electricity network. This work quantified the impact on various battery characteristics whilst providing such services. The sensitivity of the impact of V2G services on battery degradation was assessed for EV and PHEV for different battery capacities, charging regimes, and battery depth of discharge. Battery degradation was found to be most dependent on energy throughput for both the EV and PHEV powertrains, but was most sensitive to charging regime (for EVs) and battery capacity (for PHEVs). When providing ancillary services, battery degradation in both powertrains was most sensitive to individual vehicle battery depth of discharge. Degradation arising from both bulk energy and ancillary services could be minimised by reducing the battery capacity of the vehicle, restricting the number of hours connected and reducing the depth of discharge of each vehicle for ancillary services. Regardless, best case minimum impacts of providing V2G services are severe such as to require multiple battery pack replacements over the vehicle lifetime. © 2013 Elsevier Ltd.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

Hybrid-electric propulsion for aircraft

Against a background of increasing energy demand and rising fuel prices, hybrid-electric propulsion systems (HEPS) have the potential to significantly reduce fuel consumption in the aviation industry, particularly in the lighter sectors. By taking advantage of both Electric Motor (EM) and Internal Combustion Engine (ICE), HEPS provide not only a benefit in fuel saving but also a reduction in take-off noise and the emission levels. This research considers the design and sizing process of a hybrid-electric propulsion system for a single-seat demonstrator aircraft, the experimental derivation of the ICE map and the EM parameters. In addition to the experimental data, a novel modeling approach including several linked desktop PC software packages is presented to analyze and optimize hybrid-electric technology for aircraft. Further to the analysis of a parallel hybrid-electric, mid-scale aircraft, this paper also presents a scaling approach for a 20 kg UAV and a 50 tonne inter-city airliner. At the smaller scale, two different mission profiles are analyzed: an ISR mission profile, where the simulation routine optimizes the component size of the hybrid-electric propulsion system with respect to fuel saving, and a maximum duration profile; where the flight endurance is determined as a function of payload weight. At the larger scale, the performance of a 50 tonne inter-city airliner is modeled, based on a hybrid-electric gas-turbine, assuming a range of electric boost powers and battery masses.

Soil mix technology for integrated remediation and ground improvement: From laboratory work to field trials

Relatively new in the UK, soil mix technology applied to the in-situ remediation of contaminated land involves the use of mixing tools and additives to construct permeable reactive in-ground barriers and low-permeability containment walls and for hot-spot soil treatment by stabilisation/ solidification. It is a cost effective and versatile approach with numerous environmental advantages. Further commercial advantages can be realised by combining this with ground improvement through the development of a single integrated soil mix technology system which is the core objective of Project SMiRT (Soil Mix Remediation Technology). This is a large UK-based R&D project involving academia-industry collaboration with a number of tasks including equipment development, laboratory treatability studies, field trials, stakeholder consultation and dissemination activities. This paper presents aspects of project SMiRT relating to the laboratory treatability study work leading to the design of the field trials. © 2012 American Society of Civil Engineers.

An integrated 2-D model of a lithium ion battery: The effect of material parameters and morphology on storage particle stress

An integrated 2-D model of a lithium ion battery is developed to study the mechanical stress in storage particles as a function of material properties. A previously developed coupled stress-diffusion model for storage particles is implemented in 2-D and integrated into a complete battery system. The effect of morphology on the stress and lithium concentration is studied for the case of extraction of lithium in terms of previously developed non-dimensional parameters. These non-dimensional parameters include the material properties of the storage particles in the system, among other variables. We examine particles functioning in isolation as well as in closely-packed systems. Our results show that the particle distance from the separator, in combination with the material properties of the particle, is critical in predicting the stress generated within the particle. © 2012 Springer-Verlag.