An N-port system model for multiwinding transformer based multilevel converters in DC-autotransformer configuration

This paper proposes a time-domain modelling approach for a multi-winding transformer-based multilevel DC/DC converter. Within previous research, multi-winding transformers have been modeled using cantilever models. These models, while simple, have no direct intuitive interpretation. Furthermore, they do not include currents circulating within each individual module and external load currents affecting only some of the modules at the same time. In this paper, a DC/DC converter model that includes the transformer as N-port network with magnetization and stray inductance and conduction losses is proposed. The model is verified using simulations showing both accurate predictions of both, circulating currents within each module and load currents affecting multiple modules

A DC-Autotransformer based Multilevel Inverter for Automotive Applications.

This paper proposes a novel multilevel inverter for automotive applications. The topology consists of a modular DCDC converter and a tap selector, where the DC-DC converter provides several DC-output levels and the tap selector produces an AC signal by choosing different DC-output signals from the DC-DC converter. To produce the DC-levels, the DC-DC converter consists of a modular structure where the modules are connected in series. The novelty is that the modules are connected both, magnetically in the AC-domain and electrically in the DCdomain. Due to the usage of low power switches in the modules, the proposed structure provides high efficiency. Furthermore, the DC-DC converter is capable of self-balancing its modules and thus does not require large capacitors which yields a high power density. A prototype of the proposed converter is built and simulation, as well as experimental results, are used to verify the findings

Going further with smaller EVs: System-level battery range, emissions and charging infrastructure analysis

Electric vehicles are a necessary part of a zero-carbon future. However, one in five motorists worldwide depend on small petrol motorcycles for their transport needs — vehicles for which no satisfactory low-carbon substitute exists. Meanwhile, the rise in electric car ownership is not reducing GHG emissions as much as often thought, due to the significant emissions from producing ever-larger batteries. Both problems can be solved by uncovering the mechanisms of long distance EV travel, beyond battery range, where the interaction with recharging infrastructure governs vehicle performance. This study develops a new model for journeys involving multiple run-recharge cycles and introduces a novel metric for EV performance — Day Range. Not only does this allow a direct comparison between a wide variety of vehicle and infrastructure options but, by further manipulating the formulae, high level trends can be observed and specific quantitative guidelines extracted. In vehicle design, a strong emphasis on efficiency and recharge rates can drastically reduce both in-use and embodied energy while matching the touring performance of a conventional, resource intensive, heavy battery car. Meanwhile, the recharging network can be developed to better support this lower energy use. Taking the example of the UK motorway network, charge rates up to only 100kW should be installed with the focus instead falling on reliably reducing chargepoint intervals at least as far as the existing target of 28 miles, and ideally much further. In doing so, required battery capacity can be reduced from the 60kWh+ currently seen as necessary to as little as 25kWh. The resulting vehicles not only consume less energy in motion but emit far less greenhouse gases during manufacture and will cost less to produce, allowing a much wider uptake of electric vehicles than possible under the existing, energy intensive battery vehicle touring paradigm

A Sphere Decoding Algorithm for Multistep Sequential Model Predictive Control

This paper investigates the combination of two model predictive control concepts, sequential model predictive control and long-horizon model predictive control for power electronics. To achieve sequential model predictive control, the optimization problem is split into two subproblems: The first one summarizes all control goals which linearly depend on the system inputs. Sequential model predictive control generally requires to obtain more than one solution for the first subproblem. Due to the mixed-integer nature of finite control set model predictive control power electronics a special sphere decoder is therefore proposed within the paper. The second subproblem consists of all those control goals which depend nonlinearly on the system inputs and is solved by an exhaustive search. The effectiveness of the proposed method is validated via numerical simulations at different scenarios on a three-level neutral point clamped permanent magnet synchronous generator wind turbine system and compared to other long-horizon model predictive control methods

A Comprehensive Review on Planar Magnetics and the Structures to Reduce the Parasitic Elements and Improve Efficiency

Due to the need for highly efficient and compact power electronic converters to operate at higher frequencies, traditional wire-wound magnetics are not suitable. This paper provides a comprehensive review of planar magnetic technologies, discussing their advantages as well as associated disadvantages. An extensive review of the research literature is presented with the aim of suggesting models for planar magnetics. Several strategies are proposed to overcome the limitations of planar magnetics, including winding conduction loss, leakage inductance, and winding capacitance. The goal of this study is to provide engineers and researchers with a clear roadmap for designing planar magnetic devices

Variable Switching Point Model Predictive Control for DC-Link Voltage Regulation of Back-to-Back Converters

In this paper, a novel control method for back-toback converters used in grid-to-motor connections is explored. To increase the robustness of low DC-link capacitances, a control method based on variable switching point model predictive control is proposed. While previous model predictive control methods for the back-to-back converter selected a certain switching state to fulfill all control goals, we use the switching time in addition to the switching state in order to minimise deviations from the target voltage. Choosing a variable switching point provides an additional degree of freedom to the control framework and allows the system to cope with the large number of control variables. In this case, the variable switching point is used to minimize the effects of low DC-link capacitances on the system. This can either be achieved by selecting a switching point that yields low DClink capacitor charging or by selecting a switching point that aims to keep the DC-link voltage close to the reference. The proposed method is verified through numerical simulations and hardware-in-the-loop (HIL) experiments and compared to existing approaches. The results show that it is possible to control the DClink using only the switching point of the converter

Multi-active bridge based DC-link balancing of three-level NPC inverters

A common topic in multilevel converter research is the question of DC-link capacitor voltage balancing. For the three-level neutral point clamped converter the balancing is difficult due to the nonlinear nature of the DC-link capacitor voltages. Previous papers solved this problem using sophisticated controllers or additional circuitry connected in parallel to the load. Those solutions however restrict the performance of the output voltage since the controller has to provide a trade-off between output voltage performance and DC-link balancing while the load-connected balancing circuit puts limitations on the applied modulation scheme. In this paper, we connect a multi-active bridge circuit to the DC-link of the converter to overcome this problem. The proposed method is independent of the modulation scheme of the neutral point clamped converter and allows to use of all possible switching states to control the output voltage without taking the effect on the DC-link balance into account. The efficiency of the proposed method is verified using experimental results

Thermal design of superconducting cryogenic rotor: Solutions to conduction cooling challenges

This paper describes the design and testing of the first cryogenic rotor based on conductively cooled superconducting stacked tape pseudo bulks used in a rotating machine with various magnetisation methods. The rotor design demanded a number of unusual features and constraints that required novel, innovative solutions that may be applicable in other designs. The aim of this work is not to create a complete design manual, rather, to suggest some ideas that could be useful to others who are looking to solve similar problems. The outline of the proposed design is followed by a detailed description of the key systems and their interactions. Several innovative design characteristics are discussed, including calculation of liquid cryogenic cooling. Finally, experimental thermal results indicate that the design calculations are reliable and provide reaffirmation of the overall success of the design

Wa-LiD: A new LiDAR simulator for waters

A simulator (Wa-LiD) was developed to simulate the reflection of LiDAR waveforms from water across visible wavelengths. The specific features of the simulator include (i) a geometrical representation of the water surface properties, (ii) the use of laws of radiative transfer in water adjusted for wavelength and the water’s physical properties, and (iii) modelling of detection noise and signal level due to solar radiation. A set of simulated waveforms was compared with observed LiDAR waveforms acquired by the HawkEye airborne and GLAS satellite systems in the near-infra red or green wavelengths and across inland or coastal waters. Signal-to-noise ratio (SNR) distributions for the water surface and bottom waveform peaks are compared with simulated and observed waveforms. For both systems (GLAS and HawkEye), Wa-LiD simulated SNR conform to the observed SNR distributions

PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs

We motivate the design and implementation of a platform-neutral compute intermediate language (PENCIL) for productive and performance-portable accelerator programming