Electric vehicle capacity forecasting model with application to load levelling

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

The implausibility of ‘usual care’ in an open system: sedation and weaning practices in Paediatric Intensive Care Units (PICUs) in the United Kingdom (UK).

Background
The power of the randomised controlled trial depends upon its capacity to operate in a closed system whereby the intervention is the only causal force acting upon the experimental group and absent in the control group, permitting a valid assessment of intervention efficacy. Conversely, clinical arenas are open systems where factors relating to context, resources, interpretation and actions of individuals will affect implementation and effectiveness of interventions. Consequently, the comparator (usual care) can be difficult to define and variable in multi-centre trials. Hence outcomes cannot be understood without considering usual care and factors that may affect implementation and impact on the intervention.

Methods
Using a fieldwork approach, we describe PICU context, ‘usual’ practice in sedation and weaning from mechanical ventilation, and factors affecting implementation prior to designing a trial involving a sedation and ventilation weaning intervention. We collected data from 23 UK PICUs between June and November 2014 using observation, individual and multi-disciplinary group interviews with staff.

Results
Pain and sedation practices were broadly similar in terms of drug usage and assessment tools. Sedation protocols linking assessment to appropriate titration of sedatives and sedation holds were rarely used (9 % and 4 % of PICUs respectively). Ventilator weaning was primarily a medical-led process with 39 % of PICUs engaging senior nurses in the process: weaning protocols were rarely used (9 % of PICUs). Weaning methods were variably based on clinician preference. No formal criteria or use of spontaneous breathing trials were used to test weaning readiness. Seventeen PICUs (74 %) had prior engagement in multi-centre trials, but limited research nurse availability. Barriers to previous trial implementation were intervention complexity, lack of belief in the evidence and inadequate training. Facilitating factors were senior staff buy-in and dedicated research nurse provision.

Conclusions
We examined and identified contextual and organisational factors that may impact on the implementation of our intervention. We found usual practice relating to sedation, analgesia and ventilator weaning broadly similar, yet distinctively different from our proposed intervention, providing assurance in our ability to evaluate intervention effects. The data will enable us to develop an implementation plan; considering these factors we can more fully understand their impact on study outcomes.

Can the scaling behavior of electric conductivity be used to probe the self-organizational changes in solution with respect to the ionic liquid structure? The case of [C8MIM][NTf2]

Electrical conductivity of the supercooled ionic liquid [C8MIM][NTf2], determined as a function of temperature and pressure, highlights strong differences in its ionic transport behavior between low and high temperature regions. To date, the crossover effect which is very well known for low molecular van der Waals liquids has been rarely described for classical ionic liquids. This finding highlights that the thermal fluctuations could be dominant mechanisms driving the dramatic slowing down of ion motions near Tg. An alternative way to analyze separately low and high temperature dc-conductivity data using a density scaling approach was then proposed. Based on which a common value of the scaling exponent [gamma] = 2.4 was obtained, indicating that the applied density scaling is insensitive to the crossover effect. By comparing the scaling exponent [gamma] reported herein along with literature data for other ionic liquids, it appears that [gamma] decreases by increasing the alkyl chain length on the 1-alkyl-3-methylimidazolium-based ionic liquids. This observation may be related to changes in the interaction between ions in solution driven by an increase in the van der Waals type interaction by increasing the alkyl chain length on the cation. This effect may be related to changes in the ionic liquid nanostructural organization with the alkyl chain length on the cation as previously reported in the literature based on molecular dynamic simulations. In other words, the calculated scaling exponent [gamma] may be then used as a key parameter to probe the interaction and/or self-organizational changes in solution with respect to the ionic liquid structure.

A Parametric Study Of A Turbogenerator On A Diesel-Electric Hybrid Bus

The fuel consumption of automotive vehicles has become a prime consideration to manufacturers and operators as fuel prices continue to rise steadily, and legislation governing toxic emissions becomes ever more strict. This is particularly true for bus operators as government fuel subsidies are cut or removed.

In an effort to reduce the fuel consumption of a diesel-electric hybrid bus, an exhaust recovery turbogenerator has been selected from a wide ranging literature review as the most appropriate method of recovering some of the wasted heat in the exhaust line. This paper examines the effect on fuel consumption of a turbogenerator applied to a 2.4-litre diesel engine.

A validated one-dimensional engine model created using Ricardo WAVE was used as a baseline, and was modified in subsequent models to include a turbogenerator downstream, and in series with, the turbocharger turbine. A fuel consumption map of the modified engine was produced, and an in-house simulation tool was then used to examine the fuel economy benefit delivered by the turbogenerator on a bus operating on various drive-cycles.

A parametric study is presented which examined the performance of turbogenerators of various size and power output. The operating strategy of the turbogenerator was also discussed with a view to maximising turbine efficiency at each operating point.

The performance of the existing turbocharger on the hybrid bus was also investigated; both the compressor and turbine were optimised and the subsequent benefits to the fuel consumption of the vehicle were shown.

The final configuration is then presented and the overall improvement in fuel economy of the hybrid bus was determined over various drive-cycles.

A Reliability Assessment Approach For Integrated Transportation and Electrical Power Systems Incorporating Electric Vehicles

With the increasing utilization of electric vehicles (EVs), transportation systems and electrical power systems are becoming increasingly coupled. However, the interaction between these two kinds of systems are not well captured, especially from the perspective of transportation systems. This paper studies the reliability of integrated transportation and electrical power system (ITES). A bidirectional EV charging control strategy is first demonstrated to model the interaction between the two systems. Thereafter, a simplified transportation system model is developed, whose high efficiency makes the reliability assessment of the ITES realizable with an acceptable accuracy. Novel transportation system reliability indices are then defined from the view point of EV’s driver. Based on the charging control model and the transportation simulation method, a daily periodic quasi sequential reliability assessment method is proposed for the ITES system. Case studies based on RBTS system demonstrate that bidirectional charging controls of EVs will benefit the reliability of power systems, while decrease the reliability of EVs travelling. Also, the optimal control strategy can be obtained based on the proposed method. Finally, case studies are performed based on a large scale test system to verify the practicability of the proposed method.

Battery modelling methods for electric vehicles - a review

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are rapidly gaining popularity as a means of de-carbonization in the transport sector in tackling sustainable energy supply and environment pollution problems. To build a proper battery model is essential in predicting battery behaviour under various operating conditions for avoiding unsafe battery operations and developing proper controlling algorithms and maintenance strategies. This paper presents a comprehensive review of battery modelling methods. In particular, the mechanism and characteristics of Li-ion batteries are presented, and different modelling methods are discussed. Considering that equivalent electric circuit models (EECMs) are the most widely used, a detailed analysis of the modelling procedure is presented.

Synchronous Islanding Control in the Presence of Hydro-electric Generation

This paper introduces a novel load sharing algorithm to enable island synchronization. The system model used for development is based on an actual system for which historical measurement and fault data is available and is used to refine and test the algorithms performance and validity. The electrical system modelled is selected due to its high-level of hydroelectric generation and its history of islanding events. The process of developing the load sharing algorithm includes a number of steps. Firstly, the development of a simulation model to represent the case study accurately - this is validated by way of matching system behavior based on data from historical island events. Next, a generic island simulation is used to develop the load sharing algorithm. The algorithm is then tested against the validated simulation model representing the case study area selected. Finally, a laboratory setup is described which is used as validation method for the novel load sharing algorithm.

UK publicly funded Clinical Trials Units supported a controlled access approach to share individual participant data but highlighted concerns

OBJECTIVES: Evaluate current data sharing activities of UK publicly funded Clinical Trial Units (CTUs) and identify good practices and barriers.

STUDY DESIGN AND SETTING: Web-based survey of Directors of 45 UK Clinical Research Collaboration (UKCRC)-registered CTUs.

RESULTS: Twenty-three (51%) CTUs responded: Five (22%) of these had an established data sharing policy and eight (35%) specifically requested consent to use patient data beyond the scope of the original trial. Fifteen (65%) CTUs had received requests for data, and seven (30%) had made external requests for data in the previous 12 months. CTUs supported the need for increased data sharing activities although concerns were raised about patient identification, misuse of data, and financial burden. Custodianship of clinical trial data and requirements for a CTU to align its policy to their parent institutes were also raised. No CTUs supported the use of an open access model for data sharing.

CONCLUSION: There is support within the publicly funded UKCRC-registered CTUs for data sharing, but many perceived barriers remain. CTUs are currently using a variety of approaches and procedures for sharing data. This survey has informed further work, including development of guidance for publicly funded CTUs, to promote good practice and facilitate data sharing.

Turing’s Menagerie: Talking Lions, Virtual Bats, Electric Sheep and Analogical Peacocks: Common Ground and Common Interest are Necessary Components of Engagement

This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein’s argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that–for some people at least–it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.