Inverter Design for SiC-based Electric Drive Systems with Optimal Redundant States Control of Space Vector Modulation

The need for inverters with ever increasing power density and efficiency has recently become the driving factor for research in various fields. Increasing the operating voltage of the whole drive system and utilizing newly developed SiC power switches can contribute towards this goal. Higher operating voltage allows the design of drives with lower current, which leads to lower copper losses in cables and machine, while SiC switches can drastically increase the inverter efficiency. Offshore renewable power generation, such as tidal power, is a typical application where the increase of operating voltage can be highly beneficial. The ongoing electrification of transportation calls also for high power electric powertrains with high power density,where SiC technology has key advantages.In the first part of the thesis, suitable control schemes for inverters in synchronous machine drive systems are derived. A properly designed Maximum Power Point Tracking algorithm for kite-based tidal power systems is presented. The speed and torque of this new tidal power generation system varies periodically and the inverter control needs to be able to handle this variable power profile. Experimental verification of the developed control is conducted on a 35 kVA laboratory emulator of the tidal power generation unit.Electric drives using multilevel inverters are studied afterwards. Multilevel inverters use multiple low-voltage-rated switches and can operate at higher voltage than standard two-level inverters. The Neutral Point Clamped (NPC) converter is a commonly used multilevel inverter topology for medium voltage machine drives. However, the voltage balancing of its dc-side capacitors and the complexity of its control are still issues that have not been effectively solved. A new method for the optimal utilization of the redundant states in Space Vector pulse-width-Modulation (SVM) is proposed in this thesis in order to control its dc-link voltages. Experimental verification on a 4-kV-rated prototype medium-voltage PMSM drive with 5-level NPC converters is conducted in order to validate the effectiveness of the proposed control technique.Low switching and conduction losses are typical characteristics of SiC switches that can be utilized to build inverters with high power density, due to the increased efficiency and smaller form-factor. Due to the above, SiC power modules have been particularly attractive for the automotive industry. The design approach of 2-level automotive inverters has been studied in this project. Moreover, a new design approach for the cooling system of automotive inverters has been developed in this thesis, which fine-tunes the inverter heatsink utilizing standard legislated test routines for electric vehicles. Multiple conjugate-heat-transfer (CHT) computation results showcase the iterative optimization procedure on a test-case 250 kW (450 A) automotive SiC inverter.Finally, the experimental testing of high power machine drives in order to verify the control and the hardware design is an important step of the development process. Thus, the performance of the prototype 450 A SiC 2-level inverter has been been experimentally validated in a power hardware-in-the-loop (P-HIL) set-up that emulates an automotive drive system. Several challenges have been addressed with respect to the accurate modelling of the motor and the control of the circulating power in the system. A new control technique utilizing the redundant states of the SVM has been developed for this set-up to effectively suppress the zero-sequence current to 3.3 % of the line current at rated power

DeViT: Decomposing Vision Transformers for Collaborative Inference in Edge Devices

Recent years have witnessed the great success of vision transformer (ViT), which has achieved state-of-the-art performance on multiple computer vision benchmarks. However, ViT models suffer from vast amounts of parameters and high computation cost, leading to difficult deployment on resource-constrained edge devices. Existing solutions mostly compress ViT models to a compact model but still cannot achieve real-time inference. To tackle this issue, we propose to explore the divisibility of transformer structure, and decompose the large ViT into multiple small models for collaborative inference at edge devices. Our objective is to achieve fast and energy-efficient collaborative inference while maintaining comparable accuracy compared with large ViTs. To this end, we first propose a collaborative inference framework termed DeViT to facilitate edge deployment by decomposing large ViTs. Subsequently, we design a decomposition-and-ensemble algorithm based on knowledge distillation, termed DEKD, to fuse multiple small decomposed models while dramatically reducing communication overheads, and handle heterogeneous models by developing a feature matching module to promote the imitations of decomposed models from the large ViT. Extensive experiments for three representative ViT backbones on four widely-used datasets demonstrate our method achieves efficient collaborative inference for ViTs and outperforms existing lightweight ViTs, striking a good trade-off between efficiency and accuracy. For example, our DeViTs improves end-to-end latency by 2.89$\times$ with only 1.65% accuracy sacrifice using CIFAR-100 compared to the large ViT, ViT-L/16, on the GPU server. DeDeiTs surpasses the recent efficient ViT, MobileViT-S, by 3.54% in accuracy on ImageNet-1K, while running 1.72$\times$ faster and requiring 55.28% lower energy consumption on the edge device.Comment: Accepted by IEEE Transactions on Mobile Computin

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Journal of Telecommunications and Information Technology, 2018, nr 3

kwartalni

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Business process modelling in ERP implementation literature review

Business processes are the backbone of any Enterprise Resource Planning (ERP) implementation. Business process modelling (BPM) has become essential for modern, process driven enterprises due to the vibrant business environments. As a consequence enterprises are dealing with a substantial rate of organizational and business processes change. Business process modelling enables a common understanding and analysis of the business processes, which is the first step in every ERP implementation methodology (blueprint phase). In order to represent enterprise processes models in an accurate manner, it is paramount to choose a right business process modeling technique and tool. The problem of many ERP projects rated as unsuccessful is directly connected to a lack of use of business process models and notations during the blueprint phase. Also, blueprint implementation phase is crucial in order to fit planned processes in an organization with processes implemented in the solution. However, business analysts and ERP implementation professionals have substantial difficulties to navigate through a large number of theoretical models and representational notations that have been proposed for business process modeling (BPM). As the availability of different business process modeling references is huge, it is time consuming to make review and classification of all modeling techniques. Therefor, in reality majority of ERP implementations blueprint documents have no business process modeling included in generating blueprint documents. Choosing the right model comprise the purpose of the analysis and acquaintance of the available process modelling techniques and tools. The number of references on business modelling is quit large, so it is very hard to make a decision which modeling notation or technique to use. The main purpose of this paper is to make a review of business process modelling literature and describe the key process modelling techniques. The focus will be on all business process modeling that could be used in ERP implementations, specifically during the blueprint phase of the implementation process. Detailed review of BPM (Business process modeling) theoretical models and representational notations, should assist decision makers and ERP integrators in comparatively evaluating and selecting suitable modeling approaches

A conceptual framework for capability sourcing modeling

Companies need to acquire the right capabilities from the right source, and the right shore, at the right cost to improve their competitive position. Capability sourcing is an organizing process to gain access to best-in-class capabilities for all activities in a firm's value chain to ensure long-term competitive advantage. Capability sourcing modeling is a technique that helps investigating sourcing alternative solutions to facilitate strategic sourcing decision making. Our position is applying conceptual models as intermediate artifacts which are schematic descriptions of sourcing alternatives based on organization's capabilities. The contribution of this paper is introducing a conceptual framework in the form of five views (to organize all perspectives) and a conceptualisation (to formulate a language) for capability sourcing modelling