Design, Modelling and Verification of Distributed Electric Drivetrain

The electric drivetrain in a battery electric vehicle (BEVs) consists of an electric machine, an inverter, and a transmission. The drivetrain topology of available BEVs, e.g., Nissan Leaf, is centralized with a single electric drivetrain used to propel the vehicle. However, the drivetrain components can be integrated mechanically, resulting in a more compact solution. Furthermore, multiple drivetrain units can propel the vehicle resulting in a distributed drive architecture, e.g., Tesla Model S. Such drivetrains provide an additional degree of control and topology optimization leading to cheaper and more efficient solutions. To reduce the cost, the drivetrain unit in a distributed drivetrain can be standardized. However, to standardize the drivetrain, the drivetrain needs to be dimensioned such that the performance of a range of different vehicles can be satisfied. This work investigates a method for dimensioning the torque and power of an electric drivetrain that could be standardized across different passenger and light-duty vehicles. A system modeling approach is used to verify the proposed method using drive cycle simulations. The laboratory verification of such drivetrain components using a conventional dyno test bench can be expensive. Therefore, alternative methods such as power-hardware-in-the-loop (PHIL) and mechanical-hardware-in-the-loop (MHIL) are investigated. The PHIL test method for verifying inverters can be inexpensive as it eliminates the need for rotating electric machines. In this method, the inverter is tested using a machine emulator consisting of a voltage source converter and a coupling network, e.g., inductors and transformer. The emulator is controlled so that currents and voltages at the terminals resemble a machine connected to a mechanical load. In this work, a 60-kW machine emulator is designed and experimentally verified. In the MHIL method, the real-time simulation of the system is combined with a dyno test bench. One drivetrain is implemented in the dyno test bench, while the remaining are simulated using a real-time simulator to utilize this method for distributed drivetrain systems. Including the remaining drivetrains in the real-time simulation eliminates the need for a full-scale dyno test bench, providing a less expensive method for laboratory verification. An MHIL test bench for verification of distributed drivetrain control and components is also designed and experimentally verified

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Exploring the Design of Highly Energy Efficient Forestry Cranes using Gravity Compensation

Although most mechanized forestry work relies heavily on cranes for handling logs along the supply chain, there has been little research on how to improve cranes design. In addition, the available research has mainly focused on improving current designs, so there is a lack of application of modern methods for designing cranes with improved efficiency. This paper analyzes how a mechanical engineering design method, known as gravity compensation, can be used to make a new generation of highly energy efficient forestry cranes. To introduce this design approach, a standard forwarder crane with two booms is used as a model system on which to apply gravity compensation concepts. The design methodology follows a procedure based on physics and mathematical optimization, with the objective of minimizing the energy needed to move the crane by using gravity compensation via counterweights. To this end, we considered to minimize mechanical power, because this quantity relates to how fuel and hydraulic fluid are converted into mechanical motion. This analysis suggests that using gravity compensation could reduce energy consumption due to crane work by 27%, at the cost of increasing the crane total mass by 57%. Thus, the original crane mass of 559 kg increases to 879 kg after applying gravity compensation with counterweights. However, overall reductions in energy consumption would depend on both the crane work and the extraction distance. The greater the extraction distance, the lower the total savings. However, energy consumption savings of around 2% could be achieved even with an extraction distance of 1 km. From a design perspective, this study emphasized the need to consider gravity compensation in the design philosophy of forestry cranes, not only for its ability to minimize energy consumption, but also due to all the inherited properties it provides. This initial study concludes that designing cranes with a combination of gravity compensation concepts could yield a new generation of highly energy efficient cranes with energy savings exceeding those reported here

Exploring the Design of Highly Energy Efficient Forestry Cranes using Gravity Compensation

Although most mechanized forestry work relies heavily on cranes for handling logs along the supply chain, there has been little research on how to improve cranes design. In addition, the available research has mainly focused on improving current designs, so there is a lack of application of modern methods for designing cranes with improved efficiency.This paper analyzes how a mechanical engineering design method, known as gravity compensation, can be used to make a new generation of highly energy efficient forestry cranes. To introduce this design approach, a standard forwarder crane with two booms is used as a model system on which to apply gravity compensation concepts. The design methodology follows a procedure based on physics and mathematical optimization, with the objective of minimizing the energy needed to move the crane by using gravity compensation via counterweights. To this end, we considered to minimize mechanical power, because this quantity relates to how fuel and hydraulic fluid are converted into mechanical motion.This analysis suggests that using gravity compensation could reduce energy consumption due to crane work by 27%, at the cost of increasing the crane total mass by 57%. Thus, the original crane mass of 559 kg increases to 879 kg after applying gravity compensation with counterweights. However, overall reductions in energy consumption would depend on both the crane work and the extraction distance. The greater the extraction distance, the lower the total savings. However, energy consumption savings of around 2% could be achieved even with an extraction distance of 1 km.From a design perspective, this study emphasized the need to consider gravity compensation in the design philosophy of forestry cranes, not only for its ability to minimize energy consumption, but also due to all the inherited properties it provides. This initial study concludes that designing cranes with a combination of gravity compensation concepts could yield a new generation of highly energy efficient cranes with energy savings exceeding those reported here

OpenZmeter: An Efficient Low-Cost Energy Smart Meter and Power Quality Analyzer

Power quality and energy consumption measurements support providers and energy users with solutions for acquiring and reporting information about the energy supply for residential, commercial, and industrial sectors. In particular, since the average number of electronic devices in homes increases year by year and their sensitivity is very high, it is not only important to monitor the total energy consumption, but also the quality of the power supplied. However, in practice, end-users do not have information about the energy consumption in real-time nor about the quality of the power they receive, because electric energy meters are too expensive and complex to be handled. In order to overcome these inconveniences, an innovative, open source, low-cost, precise, and reliable power and electric energy meter is presented that can be easily installed and managed by any inexperienced user at their own home in urban or rural areas. The system was validated in a real house over a period of two weeks, showing interesting results and findings which validate our proposal

Volume 3 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 8: Pneumatics Group 9 | 11: Mobile applications Group 10: Special domains Group 12: Novel system architectures Group 13 | 15: Actuators & sensors Group 14: Safety & reliabilit

Adaptive Sliding Mode Contouring Control Design Based on Reference Adjustment and Uncertainty Compensation for Feed Drive Systems

Industrial feed drive systems, particularly, ball-screw and lead-screw feed drives are among the dominating motion components in production and manufacturing industries. They operate around the clock at high speeds for coping with the rising production demands. Adversely, high-speed motions cause mechanical vibrations, high-energy consumption, and insufficient accuracy. Although there are many control strategies in the literature, such as sliding mode and model predictive controls, further research is necessary for precision enhancement and energy saving. This study focused on design of an adaptive sliding mode contouring control based on reference adjustment and uncertainty compensation for feed drive systems. A combined reference adjustment and uncertainty compensator for precision motion of industrial feed drive systems were designed. For feasibility of the approach, simulation using matlab was conducted, and results are compared with those of an adaptive nonlinear sliding model contouring controller. The addition of uncertainty compensator showed a substantial improvement in performance by reducing the average contour error by 85.71% and the maximum contouring error by 78.64% under low speed compared to the adaptive sliding mode contouring controller with reference adjustment. Under high speed, the addition of uncertainty compensator reduced the average and absolute maximum contour errors by 4.48% and 10.13%, respectively. The experimental verification will be done in future. Keywords:    Machine tools, Feed drive systems, contouring control, Uncertainty dynamics, Sliding mode control

Analysis and optimization of material flow inside the system of rotary coolers and intake pipeline via discrete element method modelling

There is hardly any industry that does not use transport, storage, and processing of particulate solids in its production process. In the past, all device designs were based on empirical relationships or the designer's experience. In the field of particulate solids, however, the discrete element method (DEM) has been increasingly used in recent years. This study shows how this simulation tool can be used in practice. More specifically, in dealing with operating problems with a rotary cooler which ensures the transport and cooling of the hot fly ash generated by combustion in fluidized bed boilers. For the given operating conditions, an analysis of the current cooling design was carried out, consisting of a non-standard intake pipeline, which divides and supplies the material to two rotary coolers. The study revealed shortcomings in both the pipeline design and the cooler design. The material was unevenly dispensed between the two coolers, which combined with the limited transport capacity of the coolers, led to overflowing and congestion of the whole system. Therefore, after visualization of the material flow and export of the necessary data using DEM design measures to mitigate these unwanted phenomena were carried out.Web of Science117art. no. 184