Modeling Warp in Corrugated Cardboard Based on Homogenization Techniques for In-Process Measurement Applications

A model for describing warp—characterized as a systematic, large-scale deviation from the intended flat shape—in corrugated board based on Kirchhoff plate theory is proposed. It is based on established homogenization techniques and only a minimum of model assumptions. This yields general results applicable to any kind of corrugated cardboard. Since the model is intended to be used with industrial data, basic material properties which are usually not measured in practice are summarized to a few parameters. Those parameters can easily be fitted to the measurement data, allowing the user to systematically identify ways to reduce warp in a given situation in practice. In particular, the model can be used both as a filter to separate the warp from other surface effects such as washboarding, and to interpolate between discrete sample points scattered across the surface of a corrugated board sheet. Applying the model only requires height measurements of the corrugated board at several known (not necessarily exactly predetermined) locations across the corrugated board and acts as an interpolation or regression method between those points. These data can be acquired during production in a cost-efficient way and do not require any destructive testing of the board. The principle of an algorithm for fitting measured data to the model is presented and illustrated with examples taken from ongoing measurements. Additionally, the case of warp-free board is analyzed in more detail to deduce additional theoretical conditions necessary to reach this state

Model-based Range Prediction for Electric Cars and Trucks under Real-World Conditions

The further development of electric mobility requires major scientific efforts to obtain reliable data for vehicle and drive development. Practical experience has repeatedly shown that vehicle data sheets do not contain realistic consumption and range figures. Since the fear of low range is a significant obstacle to the acceptance of electric mobility, a reliable database can provide developers with additional insights and create confidence among vehicle users. This study presents a detailed, yet easy-to-implement and modular physical model for both passenger and commercial battery electric vehicles. The model takes consumption-relevant parameters, such as seasonal influences, terrain character, and driving behavior, into account. Without any a posteriori parameter adjustments, an excellent agreement with known field data and other experimental observations is achieved. This validation conveys much credibility to model predictions regarding the real-world impact on energy consumption and cruising range in standardized driving cycles. Some of the conclusions, almost impossible to obtain experimentally, are that winter conditions and a hilly terrain each reduce the range by 7–9%, and aggressive driving reduces the range by up to 20%. The quantitative results also reveal the important contributions of recuperation and rolling resistance towards the overall energy budget

Field-ready implementation of linear economic model predictive control for microgrid dispatch in small and medium enterprises

The increasing share of distributed renewable energy resources (DER) in the grid entails a paradigm shift in energy system operation demanding more flexibility on the prosumer side. In this work we show an implementation of linear economic model predictive control (MPC) for flexible microgrid dispatch based on time-variable electricity prices. We focus on small and medium enterprises (SME) where information and communications technology (ICT) is available on an industrial level. Our implementation uses field devices and is evaluated in a hardware-in-the-loop (HiL) test bench to achieve high technological maturity. We use available forecasting techniques for power demand and renewable energy generation and evaluate their influence on energy system operation compared to optimal operation under perfect knowledge of the future and compared to a status-quo operation strategy without control. The evaluation scenarios are based on an extensive electricity price analysis to increase representativeness of the simulation results and are based on the use of historic real-world measurements in an existing production facility. Due to real-world restrictions (imperfect forecast knowledge, implementation on field hardware, power fluctuations), between 72.2% and 85.5% of the economic optimum (rather than 100%) is reached. Together with reduced operation cost, the economic MPC implementation on field-typical industrial ICT leads to an increased share of renewable energy demand

Determination of the NOx Loading of an Automotive Lean NOx Trap by Directly Monitoring the Electrical Properties of the Catalyst Material Itself

Recently, it has been shown that the degree of loading of several types of automotive exhaust aftertreatment devices can be directly monitored in situ and in a contactless way by a microwave-based method. The goal of this study was to clarify whether this method can also be applied to NOx storage and reduction catalysts (lean NOx traps) in order to obtain further knowledge about the reactions occurring in the catalyst and to compare the results with those obtained by wirebound NOx loading sensors. It is shown that both methods are able to detect the different catalyst loading states. However, the sensitivity of the microwave-based method turned out to be small compared to that previously observed for other exhaust aftertreatment devices. This may limit the practical applicability of the microwave-based NOx loading detection in lean NOx traps

SAW RFID-Tags for Mass-Sensitive Detection of Humidity and Vapors

One-port surface acoustic wave (SAW) devices with defined reflector patterns give characteristic signal patterns in the time domain making them identifiable and leading to so-called RFID-Tags. Each sensor responds with a burst of signals, their timed positions giving the identification code, while the amplitudes can be related to the analyte concentration. This paper presents the first combination of such a transducer with chemically sensitive layer materials. These include crosslinked polyvinyl alcohol for determining relative humidity and tert-butylcalix[4]arene for detecting solvent vapors coated on the free space between the reflectors. In going from the time domain to the frequency domain by Fourier transformation, changes in frequency and phase lead to sensor responses. Hence, it is possible to measure the concentration of tetrachloroethene in air down to 50 ppm, as well as 1% changes in relative humidity

Advanced Sensor Technologies for Cryogenic Liquid Propellant Flow Phenomena

Sensors for various fluid physical quantities play a vital role in the management of cryogenic liquid propellants (hydrogen, oxygen, methane), used worldwide in launchers such as the European Ariane rockets. In addition, measurement devices are particularly central in all basic scientific fluid experimentation, investigating for instance liquid sloshing, free liquid surface movement, boiling or bubble formation. The results of these experiments in microgravity and on ground enable the efficient design of present-day cryogenic launcher (upper) stages and (as possible future applications) of long-term orbital propellant storage facilities, in-orbit refuelling stations and interplanetary cryogenic propulsion. These utilizations call for sensor technology to efficiently perform propellant mass gauging, determine fill-levels, temperature fields, phase change quantities and bubble formation in a nonintrusive fashion. An overview of various candidate cryogenic sensor technologies currently investigated by the authors is provided. Tomographic techniques based on sound waves and electrostatic fields are discussed with respect to their applicability in cryogenic liquids, potential applications areas, engineering challenges and corresponding validation tests. Fibre-optic technologies for visual observations and large scale, high resolution distributed temperature measurements are presented with first results of their validation in cryogenic liquids. New and improved insights into cryogenic liquid propellant behaviour are possible, as is shown based on experimental applications

Automotive Catalyst State Diagnosis Using Microwaves

The state of catalysts plays a key role in automotive exhaust gas aftertreatment. The soot or ash loading of Diesel particulate filters, the oxygen loading degree in three-way catalysts, the amount of stored ammonia in SCR catalysts, or the NOx loading degree in NOx storage catalysts are important parameters that are today determined indirectly and in a model-based manner with gas sensors installed upstream and/or downstream of the catalysts. This contribution gives an overview on a novel approach to determine the catalyst state directly by a microwave-based technique. The method exploits the fact that the catalyst housing acts as a microwave cavity resonator. As “sensing” elements, one or two simple antennas are mounted inside the catalyst canning. The electrical properties of the catalyst device (ceramic honeycomb plus coating and storage material) can be measured. Preferably, the resonance characteristics, e.g., the resonance frequencies, of selected cavity modes are observed. The information on the catalyst interior obtained in such a contactless manner is very well correlated with the catalyst state as will be demonstrated for different exhaust gas aftertreatment systems