Filtyp
This paper forms part of a broader study on the design and optimisation of a high speed switched reluctance motor (SRM) for hybrid-electrical automotive traction applications. The main focus of this particular paper is to explain the design optimisation methodology followed. Furthermore, the main aim of the motor design is to push the power density of the SRM as high as possible. This leads to num
The growth of electromobility emphasizes the need for good charging solutions. Electric vehicles can be charged either while standing still (static charging) or while in movement (dynamic charging) by using electric road systems (ERSs). In both cases, significant power levels are used to transfer energy to the vehicles, thus requiring a thermal design that is able to handle the losses generated wh
Thermal design of electric traction machines for high performance HEV drivetrains is a challenging task. Unlike conventional HEV traction machines, these machines are subject to continuous operation at or near their thermal limits during race-track driving, and so thermal management is of paramount importance to the mass and size of the machine. This article presents the main challenges related to
This paper forms part of a broader study on the design optimization of a high speed switched reluctance motor for automotive traction applications. Due to the high speed operation and resulting high electrical frequency, it is of extreme importance that the different loss components of this motor are accurately calculated. In this study, several effects are observed that influence the accurate mea
This paper forms part of a broader study on the design of an unconventional, high speed, switched reluctance machine (SRM), for automotive traction applications making use of soft magnetic composite (SMC) material. The aim is to have this machine operate at a fundamental frequency of up to 4 kHz. Another characteristic is that switched reluctance machines tend to be operated in deep saturation a l
Conductive Electric Road Systems (ERS) appear as a promising solution for the electrification of transportation, particularly for heavy vehicles and long distance trips, but also for light vehicles. Significant research efforts are currently devoted to the development of conductive ERS systems, with up to 4 pilot test sites with different technologies in operation only in Sweden. This article asse
Transport electrification in Sweden is moving at a fast pace. Grid impact studies from EVs predominantly consider low-voltage grids. However, as the share of electric cars is rapidly increasing, potential grid impact at higher voltage levels needs to be considered. This paper presents a probabilistic approach to generate aggregated charging profiles for home charging at a sub-transmission grid lev
This article presents the first thermal experiments conducted on a novel cooling concept applied to a high speed switched reluctance machine topology for traction applications. By circulating the coolant in between the coils and the stator poles the winding and the stator iron are virtually thermally decoupled. A test motorette is used to demonstrate the potential of the cooling concept at current
Vassiliki “Betty” Smocovitis has done a thorough and admirable job in highlighting the complex history the Modern Synthesis (MS) or the Evolutionary Synthesis (ES) as she prefers to call it. Her interesting contribution should hopefully increase awareness that the history of evolutionary biology is important even for researchers today who are mainly interested in solving practical questions of mor
Purpose: To demonstrate the feasibility and accuracy of chemical shift–encoded imaging of the fatty acid composition (FAC) of human bone marrow adipose tissue at 7 T, and to determine suitable image-acquisition parameters using simulations. Methods: The noise performance of FAC estimation was investigated using simulations with a range of inter-echo time, and accuracy was assessed using a phantom
Background: Resuscitative endovascular balloon occlusion of the aorta (REBOA) is an emerging and potentially life-saving procedure, necessitating qualified operators in an increasing number of centres. The procedure shares technical elements with other vascular access procedures using the Seldinger technique, which is mastered by doctors not only in endovascular specialties but also in trauma surg
The present Multi-view stereo (MVS) methods with supervised learning-based networks have an impressive performance comparing with traditional MVS methods. However, the ground-truth depth maps for training are hard to be obtained and are within limited kinds of scenarios. In this paper, we propose a novel unsupervised multi-metric MVS network, named M 3 VSNet, for dense point cloud reconstruction w
Wood is a porous, hygroscopic material that can take up water both within cell walls (cell-wall water) and in the macrovoid structure (capillary water). Therefore, moisture transport in wood occurs through multiple pathways and phases of water, that is, both cell-wall water, liquid water, and water vapor can be transported through the material structure. The amount of water in wood is quantified b
The advent of deep learning has yielded powerful tools to automatically compute gradients of computations. This is because training a neural network equates to iteratively updating its parameters using gradient descent to find the minimum of a loss function. Deep learning is then a subset of a broader paradigm; a workflow with free parameters that is end-to-end optimisable, provided one can keep t
This article extends the optimal covariance steering (CS) problem for discrete time linear stochastic systems modeled using moment-based ambiguity sets. To hedge against the uncertainty in the state distributions while performing covariance steering, distributionally robust risk constraints are employed during the optimal allocation of the risk. Specifically, a distributionally robust iterative ri
Aim: The aim of the study was to explore the work conditions that influence the opportunities for professional development of specialist nurses in surgical care. Design: A qualitative descriptive design was used. Methods: With a purposeful sampling procedure, 14 specialist nurses in surgical care were included. Four focus-group interviews were conducted during November to December 2021 and deducti
We investigate the problem of risk averse robot path planning using the deep reinforcement learning and distributionally robust optimization perspectives. Our problem formulation involves modelling the robot as a stochastic linear dynamical system, assuming that a collection of process noise samples is available. We cast the risk averse motion planning problem as a Markov decision process and prop
An integration of distributionally robust risk allocation into sampling-based motion planning algorithms for robots operating in uncertain environments is proposed. We perform non-uniform risk allocation by decomposing the distributionally robust joint risk constraints defined over the entire planning horizon into individual risk constraints given the total risk budget. Specifically, the determini
Paperboard is a thin and lightweight material made of cellulose fibers and it is an important component in packaging material where it provides stiffness and rigidity. The scope of this work is the development of continuum models, and its numerical treatments, for simulating the processes of converting paperboard into packages. The thesis begins with a general introduction to paperboard and a revi
