Speed Sensorless Induction Motor Drive Control for Electric Vehicles

Fast diminishing fossil fuel resources, deterioration in air quality and concerns for environmental protection, continuously promote the interest in the research and development of Alternative Energy Vehicles (AEVs). Traction motor drive is an integral part and common electric propulsion system in all kinds of AEVs. It plays an utmost significant role in the development of electrified transport industry. Application of Induction Motor (IM) drive is not only limited to the domestic and industrial applications but also has an ubiquitous influence in the modern electrified transport sector. IM is characterized by a simple and rugged structure, operational reliability, low maintenance, low cost, ability to operate in a hostile environment and high dynamic performance. However, IM is one of the widely accepted choices by Electric Vehicles (EVs) manufacturer. At present, Variable speed IM drive is almost replacing the traditional DC motor drive in a wide range of applications including EVs where a fast dynamic response is required. It became possible after the technological advancement and development in the field of power switching devices, digital signal processing and recently intelligent control systems have led to great improvements in the dynamic performance of traction drives. Speed Sensorless control strategies offer better system’s reliability and robustness and reduce the drive cost, size and maintenance requirements. Sensorless IM drives have been applied on medium and high speed applications successfully. However, instability at low speed and under different load disturbance conditions are still a critical problem in this research field and has not been robustly achieved. Some application such as traction drives and cranes are required to maintain the desired level of torque down to low speed levels with uncertain load torque disturbance conditions. Speed and torque control is more important particularly in motor-in-wheel traction drive train configuration EVs where vehicle wheel rim is directly connected to the motor shaft to control the speed and torque. The main purpose of this research is to improve the dynamic performance of conventional proportional-integral controller based model reference adaptive system (PI-MRAS) speed observer by using several speed profiles under different load torque disturbance conditions, which is uncertain during the whole vehicle operation apart from the vehicle own load. Since, vehicle has to face different road conditions and aerodynamic effects which continuously change the net load torque effect on the traction drive. This thesis proposes different novel methods based on the fuzzy logic control (FLC) and sliding mode control (SMC) with rotor flux MRAS. Numerous simulations and experimental tests designed with respect to the EV operation are carried out to investigate the speed estimation performance of the proposed schemes and compared with the PI-MRAS speed observer. For simulation and experimental purpose, Matlab-Simulink environment and dSPACE DS-1104 controller board are used respectively. The results presented in this thesis show great performance improvements of the proposed schemes in speed estimation & load disturbance rejection capability and provide a suitable choice of speed sensoless IM drive control for EVs with cost effectiveness

Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice

Routinely collected data in hospital Electronic Medical Records (EMR) is rich and abundant but often not linked or analysed for purposes other than direct patient care. We have created a methodology to integrate patient-centric data from different EMR systems into clinical pathways that represent the history of all patient interactions with the hospital during the course of a disease and beyond. In this paper, the literature in the area of data visualisation in healthcare is reviewed and a method for visualising the journeys that patients take through care is discussed. Examples of the hidden knowledge that could be discovered using this approach are explored and the main application areas of visualisation tools are identified. This paper also highlights the challenges of collecting and analysing such data and making the visualisations extensively used in the medical domain. This paper starts by presenting the state-of-the-art in visualisation of clinical and other health related data. Then, it describes an example clinical problem and discusses the visualisation tools and techniques created for the utilisation of these data by clinicians and researchers. Finally, we look at the open problems in this area of research and discuss future challenges

Toward an improved representation of middle atmospheric dynamics thanks to the ARISE project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions

Climate simulations for 1880-2003 with GISS modelE

We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. The greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds.Comment: 44 pages; 19 figures; Final text accepted by Climate Dynamic

The COGs (context, object, and goals) in multisensory processing

Our understanding of how perception operates in real-world environments has been substantially advanced by studying both multisensory processes and “top-down” control processes influencing sensory processing via activity from higher-order brain areas, such as attention, memory, and expectations. As the two topics have been traditionally studied separately, the mechanisms orchestrating real-world multisensory processing remain unclear. Past work has revealed that the observer’s goals gate the influence of many multisensory processes on brain and behavioural responses, whereas some other multisensory processes might occur independently of these goals. Consequently, other forms of top-down control beyond goal dependence are necessary to explain the full range of multisensory effects currently reported at the brain and the cognitive level. These forms of control include sensitivity to stimulus context as well as the detection of matches (or lack thereof) between a multisensory stimulus and categorical attributes of naturalistic objects (e.g. tools, animals). In this review we discuss and integrate the existing findings that demonstrate the importance of such goal-, object- and context-based top-down control over multisensory processing. We then put forward a few principles emerging from this literature review with respect to the mechanisms underlying multisensory processing and discuss their possible broader implications

Synthesis of 2-azidoethyl α-d-mannopyranoside orthogonally protected and selective deprotections

4 páginas, 1 figura, 2 esquemas.We present the synthesis of a fully orthogonally protected mannosyl glycoside 1 and the corresponding methods for selective deprotections. Mannosyl glycoside 1 contains a functionalized linker at the anomeric position to allow for the attachment of carbohydrate units to scaffolds in order to prepare carbohydrate multivalent systems.We would like to thank FIS (PI030093), for financial supportPeer reviewe

Spatiotemporal Receptive Field Properties of a Looming-Sensitive Neuron in Solitarious and Gregarious Phases of the Desert Locust

Desert locusts (Schistocerca gregaria) can transform reversibly between the swarming gregarious phase and a solitarious phase, which avoids other locusts. This transformation entails dramatic changes in morphology, physiology, and behavior. We have used the lobula giant movement detector (LGMD) and its postsynaptic target, the descending contralateral movement detector (DCMD), which are visual interneurons that detect looming objects, to analyze how differences in the visual ecology of the two phases are served by altered neuronal function. Solitarious locusts had larger eyes and a greater degree of binocular overlap than those of gregarious locusts. The receptive field to looming stimuli had a large central region of nearly equal response spanning 120° × 60° in both phases. The DCMDs of gregarious locusts responded more strongly than solitarious locusts and had a small caudolateral focus of even further sensitivity. More peripherally, the response was reduced in both phases, particularly ventrally, with gregarious locusts showing greater proportional decrease. Gregarious locusts showed less habituation to repeated looming stimuli along the eye equator than did solitarious locusts. By contrast, in other parts of the receptive field the degree of habituation was similar in both phases. The receptive field organization to looming stimuli contrasts strongly with the receptive field organization of the same neurons to nonlooming local-motion stimuli, which show much more pronounced regional variation. The DCMDs of both gregarious and solitarious locusts are able to detect approaching objects from across a wide expanse of visual space, but phase-specific changes in the spatiotemporal receptive field are linked to lifestyle changes