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This paper presents a novel optimization strategy for fitting the Jiles-Atherton (JA) hysteresis model to experimental stator yoke core loss measurements and locked-rotor IPMSM calculations. The first study aims to identify a single set of JA model parameters that track sample core losses at different magnetization levels at a given frequency: the analytical model is compared with finite element m
Situation awareness in driving involves detection of events and environmental changes. Failure in detection can be attributed to the density of these events in time, amongst other factors. In this research, we explore the effect of temporal proximity, and event duration in a change detection task during driving in VR. We replicate real-world interaction events in the streetscape and systematically
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
We present the building blocks of an energy-efficient on-chip platform for neural network applications based on III-V semiconductor nanowires and nanopillar arrays. These will work as emitting and detecting neurosynaptic nodes for spiking nanocircuits, as light sensors that emulate navigational properties of insect vision systems.
Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks. While in the past, robot programs were often written statically and tuned manually, the current, faster transition times call for robust, modular and interpretable solutions that also allow a robotic system to learn how to perform a task. We propose the method Behavior-based Bayesian Optimizatio
