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The purpose of this article is to provide insight of a new simple forecasting method based on a state-estimation algorithm known as the Kalman filter. While the accuracy of such algorithm is not comparable to state-of-the-art forecasting algorithms for PV-power production it does not require any internet connection, eyefish cameras or time intensive training. The algorithm was tested with several months of real high-resolution data with adequate results for the intended applications. The minimization of the necessary spinning reserve on a PV-diesel hybrid system to increase the solar fraction and reduce diesel consumption.
In recent years, significant progress was made on switched-capacitor DCDC converters as they enable fully integrated on chip power management. New converter topologies overcame the fixed input-to-output voltage limitation and achieved high efficiency at high power densities. SC converters are attractive to not only mobile handheld devices with small input and output voltages, but also for power conversion in IoTs, industrial and automotive applications, etc. Such applications need to be capable of handling high input voltages of more than 10V. This talk highlights the challenges of the required supporting circuits and high voltage techniques, which arise for high Vin SC converters. It includes level shifters, charge pumps and back-to-back switches. High Vin conversion is demonstrated in a 4:1 SC DCDC converter with an input voltage as high as 17V with a peak efficiency of 45 %, and a buckboost SC converter with an input voltage range starting from 2 up to 13V, which utilizes a total of 17 ratios and achieves a peak efficiency of 81.5 %. Furthermore a highly integrated micro power supply approach is introduced, which is connected directly to the 120/230 Vrms mains, with an output power of 3mW, resulting in a power density >390μW/mm², which exceeds prior art by a factor of 11.
This publication gives a short introduction and overview of the European project SCOUT and introduces a methodology for a holistic approach to record the state of the art in technical (vehicle and connectivity, human factors regarding physiologic and ergonomic level) and non-technical enablers (societal, economic, legal, regulatory and policy level) of connected and automated driving in Europe. The paper addresses beside the technical topics of environmental perception, E/E architecture, actuators and security, the state of the art of the legal framework in the context of connected and automated driving.
In this work we investigate the behavior of MIS- and Schottky-gate AlGaN/GaN HEMTs under high-power pulsestress. A special setup capable of applying pulses of constant power is used to evaluate the electro-thermal response in different operating points. For both types of devices, the time to failure was found to decrease with increasing drain-source voltage. Overall, the Schottky-gate device displays a higher pulse robustness. The pulse withstand time of the MIS-gate device is limited by the occurrence of a thermal instability at approximately 240°C while the Schottky-gate device displays a rapid increase of the gate leakage current prior to failure. The mechanism responsible for this gate current is further investigated by static and transient temperature measurements and yielded activation energies of 0.6 eV and 0.84 eV.
In a digitally controlled slope shaping system, reliable detection of both voltage and current slope is required to enable a closed-loop control for various power switches independent of system parameters. In most state-of-the-art works, this is realized by monitoring the absolute voltage and current values. Better accuracy at lower DC power loss is achieved by sensing techniques for a reliable passive detection, which is achieved through avoiding DC paths from the high voltage network into the sensing network. Using a high-speed analog-to-digital converter, the whole waveform of the transient derivative can be stored digitally and prepared for a predictive cycle-by-cycle regulation, without requiring high-precision digital differentiation algorithms. To gain an accurate representation of the voltage and current derivative waveforms, system parasitics are investigated and classified in three sections: (1) component parasitics, which are identified by s-parameter measurements and extraction of equivalent circuit models, (2) PCB design issues related to the sensing circuit, and (3) interconnections between adjacent boards.
The contribution of this paper is an optimized sensing network on the basis of the experimental study supporting fast transition slopes up to 100 V/ns and 1 A/ns and beyond, making the sensing technique attractive for slope shaping of fast switching devices like modern generation IGBTs, CoolMOSTM and SiC mosfets. Measurements of the optimized dv/dt and di/dt setups are demonstrated for a hard switched IGBT power stage.
This paper presents a control strategy for optimal utilization of photovoltaic (PV) generated power in conjunction with an Energy Storage System (ESS). The ESS is specifically designed to be retrofitted into existing PV systems in an end-user application. It can be attached in parallel to the PV system and connects to existing DC/AC inverters. In particular, the study covers the impact such a modification has on the output power of existing PV panels. A distinct degradation of PV output power was found due to the different power characteristics of PV panel and ESS. To overcome such degradation a novel feedback system is proposed. The feedback system continuously modifies the power characteristic of the ESS to match the PV panel and thus achieves optimal power utilization. Impact on PV and power point tracking performance is analyzed. Simulation of the proposed system is performed in MATLAB/Simulink. The results are found to be satisfactory.
This paper presents a novel multi-modal CNN architecture that exploits complementary input cues in addition to sole color information. The joint model implements a mid-level fusion that allows the network to exploit cross modal interdependencies already on a medium feature-level. The benefit of the presented architecture is shown for the RGB-D image understanding task. So far, state-of-the-art RGB-D CNNs have used network weights trained on color data. In contrast, a superior initialization scheme is proposed to pre-train the depth branch of the multi-modal CNN independently. In an end-to-end training the network parameters are optimized jointly using the challenging Cityscapes dataset. In thorough experiments, the effectiveness of the proposed model is shown. Both, the RGB GoogLeNet and further RGB-D baselines are outperformed with a significant margin on two different tasks: semantic segmentation and object detection. For the latter, this paper shows how to extract object level groundtruth from the instance level annotations in Cityscapes in order to train a powerful object detector.
Understanding the factors that influence the accuracy of visual SLAM algorithms is very important for the future development of these algorithms. So far very few studies have done this. In this paper, a simulation model is presented and used to investigate the effect of the number of scene points tracked, the effect of the baseline length in triangulation and the influence of image point location uncertainty. It is shown that the latter is very critical, while the other all play important roles. Experiments with a well known semi-dense visual SLAM approach are also presented, when used in a monocular visual odometry mode. The experiments show that not including sensor bias and scale factor uncertainty is very detrimental to the accuracy of the simulation results.
Layout generators, commonly denoted as PCells (parameterized cells), play an important role in the layout design of analog ICs (integrated circuits). PCells can automatically create parts of a layout, whose properties are controlled by the PCell parameters. Any layout, whether hand-crafted or automatically generated, has to be verified against design rules using a DRC (design rule check) in order to assure proper functionality and producibility. Due to the growing complexity of today’s PCells it would be beneficial if a PCell itself could be ensured to produce DRC clean layouts for any allowed parameter values, i.e. a formal verification of the PCell’s code rather than checking all possible instances of the PCell. In this paper we demonstrate the feasibility of such a formal PCell verification for a simple NMOS transistor PCell. The set from which the parameter values can be chosen was found during the verification process.
A concept for a slope shaping gate driver IC is proposed, used to establish control over the slew rates of current and voltage during the turn-on and turn off switching transients.
It combines the high speed and linearity of a fully-integrated closed-loop analog gate driver, which is able to perform real-time regulation, with the advantages of digital control, like flexibility and parameter independency, operating in a predictive cycle-bycycle regulation. In this work, the analog gate drive integrated circuit is partitioned into functional blocks and modeled in the small-signal domain, which also includes the non-linearity of parameters. An analytical stability analysis has been performed in order to ensure full functionality of the system controlling a modern generation IGBT and a superjunction MOSFET. Major parameters of influence, such as gate resistor and summing node capacitance, are investigated to achieve stable control. The large-signal behavior, investigated by simulations of a transistor level design, verifies the correct operation of the circuit. Hence, the gate driver can be designed for robust operation.
In this paper we describe the design and development process of an electromagnetic picker for rivets. These rivets are used in a production process of leather or textile design objects like riveted waist belts or purses. The picker is designed such that it replaces conventional mechanical pickers thus avoiding mechanical wear problems and increasing the process quality. The paper illustrates the challenges in the design process of this mechatronic system. The design process was based on both simulation and experiments leading to a prototype that satisfies the requirements.
The diversity of energy prosumer types makes it difficult to create appropriate incentive mechanisms that satisfy both prosumers and energy system operators alike. Meanwhile, European energy suppliers buy guarantees of origin (GoO) which allow them to sell green energy at premium prices while in reality delivering grey energy to their customers. Blockchain technology has proven itself to be a robust paying system in which users transact money without the involvement of a third party. Blockchain tokens can be used to represent a unit of energy and, just as GoOs, be submitted to the market. This paper focuses on simulating marketplace using the ethereum blockchain and smart contracts, where prosumers can sell tokenized GoOs to consumers willing to subsidize renewable energy producers. Such markets bypass energy providers by allowing consumers to obtain tokenized GoOs directly from the producers, which in turn benefit directly from the earnings. Two market strategies where tokens are sold as GoOs have been simulated. In the Fix Price Strategy prosumers sell their tokens to the average GoO price of 2014. The Variable Price Strategy focuses on selling tokens at a price range defined by the difference between grey and green energy. The study finds that the ethereum blockchain is robust enough to functions as a platform for tokenized GoO trading. Simulation results have been compared and the results indicate that prosumers earn significantly more money by following the Variable Price
Strategy.
Condition Monitoring for mechanical systems like bearings or transmissions is often done by analysing frequency spectra obtained from accelerometers mounted to the components under observation. Although this approach gives a high amount on information about the system behaviour, the interpretation of the resulting spectra requires expert knowledge, that is, a deep understanding of the effect on condition deterioration on the measured spectra. However, an increasing number of condition monitoring applications demands other representations of the measured signals that can be easily interpreted even by non–experts. Therefore, the objective of this paper is to develop an approach for processing measured process data in order to obtain an easy to interpret measure for assessing the component condition. The main idea is to evaluate the deterioration of a component condition by computing the correlation function of current measurements with past measurements in order to detect a component condition deterioration from a change in these correlation functions. Besides the simplicity of the obtained measure, this approach opens the opportunity for integrating a model based approach as well. The developed method is tested based on a condition monitoring application in a roller chain.
This paper describes a new method for condition monitoring of a roller chain. In contrast to conventional methods, no additional accelerometers are used to measure and interpret frequency spectra but the chain condition is evaluated using an easy to interpret similarity measure based on correlation functions using the driving motor torque. An additional clustering of current data and reference measurements yields an easy to understand representation of the chain condition.
The main challenge when driving heat pumps by PV-electricity is balancing differing electrical and thermal demands. In this article, a heuristic method for optimal operation of a heat pump driven by a maximum share of PV-electricity is presented. For this purpose, the (DHW) are activated in order shift the operation of the heat pump to times of PV-generation. The system under consideration refers to thermal and electrical demands of a single family house. It consists of a heat pump, a thermal energy storage for DHW and of grid connected heating and generation of domestic hot water, the heat pump runs with two different supply temperatures and thereby achieving a maximum overall COP. Within the algorithm for optimization a set of heuristic rules is developed in a way that the operational characteristics of the heat pump in terms of minimum running and stopping times are met as well as the limiting constraints of upper and lower limits of room temperature and energy content of electricity generated, a varying number of heat pump schedules fulfilling the bundary conditions are created. Finally, the schedule offering the maximum on-site utilization of PV-electricity with a minimum number of starts of the heat pump, which serves as secondary condition, is selected. Yearly simulations of this combination have been carried out. Initial results of this method indicate a significant rise in on-site consumption of the PV-electricity and heating demand fulfilment by renewable electricity with no need for a massive TES for the heating system in terms of a big water tank.
This paper reports an analysis of application and impact of FMEA on susceptibility of generic IT-networks. It is not new that in communication system, the frequency and the data transmission rate play a very important role. The rapid increase in miniaturization of electronic devices leads to very sensitivity against electromagnetic interference. Since the IT network with the data transfer rate makes a huge contribution to this development it is very important to monitor their functionality. Therefore, tests are performed to observe and ensure the data transfer rate of IT networks against IEMI. A fault tree model is presented and observed effects during radiation of disturbance on complex system by a HPEM interference sources are described using a continuous and consistent model of the physical layer to the application layer.
Gallium nitride high electron mobility transistors (GaN-HEMTs) have low capacitances and can achieve low switching losses in applications where hard turn-on is required. Low switching losses imply a fast switching; consequently, fast voltage and current transients occur. However, these transients can be limited by package and layout parasitics even for highly optimized systems. Furthermore, a fast switching requires a fast charging of the input capacitance, hence a high gate current.
In this paper, the switching speed limitations of GaN-HEMTs due to the common source inductance and the gate driver supply voltage are discussed. The turn-on behavior of a GaN-HEMT is simulated and the impact of the parasitics and the gate driver supply voltage on the switching losses is described in detail. Furthermore, measurements are performed with an optimized layout for a drain-source voltage of 500 V and a drain-source current up to 60 A.
The demonstration project Virtual Power Plant Neckar-Alb is constructing a Virtual Power Plant (VPP) demonstration site at the Reutlingen University campus. The VPP demonstrator integrates a heterogeneous set of distributed energy resources (DERs) which are connected to control the infrastructure and an energy management system. This paper describes the components and the architecture of the demonstrator and presents strategies for demonstration of multiple optimization and control systems with different control paradigms.
Multilevel-cell (MLC) flash is commonly deployed in today’s high density NAND memories, but low latency and high reliability requirements make it barely used in automotive embedded flash applications. This paper presents a time domain voltage sensing scheme that applies a dynamic voltage ramp at the cells’ control gate (CG) in order to achieve fast and reliable sensing suitable for automotive applications.
This work presents a spiral antenna array, which can be used in the V- and W-Band. An array equipped with Dolph-Chebychev coefficients is investigated to address issues related to the low gain and side lobe level of the radiating structure. The challenges encountered in this achievement are to provide an antenna that is not only good matched but also presents an appreciable effective bandwidth at the frequency bands of interest. Its radiation properties including the effective bandwidth and the gain are analyzed for the W-Band.
Modern power semiconductor devices have low capacitances and can therefore achieve very fast switching transients under hard-switching conditions. However, these transients are often limited by parasitic elements, especially by the source inductance and the parasitic capacitances of the power semiconductor. These limitations cannot be compensated by conventional gate drivers. To overcome this, a novel gate driver approach for power semiconductors was developed. It uses a transformer which accelerates the switching by transferring energy from the source path to the gate path.
Experimental results of the novel gate driver approach show a turn-on energy reduction of 78% (from 80 μJ down to 17 μJ) with a drain-source voltage of 500V and a drain current of 60 A. Furthermore, the efficiency improvement is demonstrated for a hard-switching boost converter. For a switching frequency of 750 kHz with an input voltage of 230V and an output voltage of 400V, it was possible to extend the output power range by 35%(from 2.3kW to 3.1 kW), due to the reduction of the turn-on losses, therefore lowering the junction temperature of the GaN-HEMT.
A novel configuration of the dual active bridge (DAB) DC/DC converter is presented, enabling more efficient wide voltage range conversion at light loads. A third phase leg as well as a center tapped transformer are introduced to one side of the converter. This concept provides two different turn ratios, thus extending the zero voltage switching operation resulting in higher efficiency. A laboratory prototype was built converting an input voltage of 40V to an output voltage in the range of 350V to 650V. Measurements show a significant increase up to 20% in the efficiency for light-load operation.
This paper introduces a novel placement methodology for a common-centroid (CC) pattern generator. It can be applied to various integrated circuit (IC) elements, such as transistors, capacitors, diodes, and resistors. The proposed method consists of a constructive algorithm which generates an initial, close to the optimum, solution, and an iterative algorithm which is used subsequently, if the output of constructive algorithm does not satisfy the desired criteria. The outcome of this work is an automatic CC placement algorithm for IC element arrays. Additionally, the paper presents a method for the CC arrangement evaluation. It allows for evaluating the quality of an array, and a comparison of different placement methods.
A new method for the analysis of movement dependent parasitics in full custom designed MEMS sensors
(2017)
Due to the lack of sophisticated microelectromechanical systems (MEMS) component libraries, highly optimized MEMS sensors are currently designed using a polygon driven design flow. The strength of this design flow is the accurate mechanical simulation of the polygons by finite element (FE) modal analysis. The result of the FE-modal analysis is included in the system model together with the data of the (mechanical) static electrostatic analysis. However, the system model lacks the dynamic parasitic electrostatic effects, arising from the electric coupling between the wiring and the moving structures. In order to include these effects in the system model, we present a method which enables the quasi dynamic parasitic extraction with respect to in-plane movements of the sensor structures. The method is embedded in the polygon driven MEMS design flow using standard EDA tools. In order to take the influences of the fabrication process into account, such as etching process variations, the method combines the FE-modal analysis and the fabrication process simulation data. This enables the analysis of dynamic changing electrostatic parasitic effects with respect to movements of the mechanical structures. Additionally, the result can be included into the system model allowing the simulation of positive feedback of the electrostatic parasitic effects to the mechanical structures.
We present a new methodology for automatic selection and sizing of analog circuits demonstrated on the OTA circuit class. The methodology consists of two steps: a generic topology selection method supported by a “part-sizing” process and subsequent final sizing. The circuit topologies provided by a reuse library are classified in a topology tree. The appropriate topology is selected by traversing the topology tree starting at the root node. The decision at each node is gained from the result of the part-sizing, which is in fact a node-specific set of simulations. The final sizing is a simulation-based optimization. We significantly reduce the overall simulation effort compared to a classical simulation-based optimization by combining the topology selection with the part-sizing process in the selection loop. The result is an interactive user friendly system, which eases the analog designer’s work significantly when compared to typical industrial practice in analog circuit design. The topology selection method and sizing process are implemented as a tool into a typical analog design environment. The design productivity improvement achievable by our method is shown by a comparison to other design automation approaches.
This work presents a fully integrated GaN gate driver in a 180nm HV BCD technology that utilizes high-voltage energy storing (HVES) in an on-chip resonant LC tank, without the need of any external capacitor. It delivers up to 11nC gate charge at a 5V GaN gate, which exceeds prior art by a factor of 45-83, supporting a broad range of GaN transistor types. The stacked LC tank covers an area of only 1.44mm², which corresponds to a superior value of 7.6nC/mm².
A gate driver approach is presented for the reduction of turn-on losses in hard switching applications. A significant turn-on loss reduction of up to 55% has been observed for SiCMOSFETs. The gate driver approach uses a transformer which couples energy from the power path back into the gate path during switching events, providing increased gate driver current and thereby faster switching speed.
The gate driver approach was tested on a boost converter running at a switching frequency up to 300 kHz. With an input voltage of 300V and an output voltage of 600V, it was possible to reduce the converter losses by 8% at full load. Moreover, the output power range could be extended by 23% (from 2.75kW to 3.4 kW) due to the reduction of the turn-on losses.
A 3D face modelling approach for pose-invariant face recognition in a human-robot environment
(2017)
Face analysis techniques have become a crucial component of human-machine interaction in the fields of assistive and humanoid robotics. However, the variations in head-pose that arise naturally in these environments are still a great challenge. In this paper, we present a real-time capable 3D face modelling framework for 2D in-the-wild images that is applicable for robotics. The fitting of the 3D Morphable Model is based exclusively on automatically detected landmarks. After fitting, the face can be corrected in pose and transformed back to a frontal 2D representation that is more suitable for face recognition. We conduct face recognition experiments with non-frontal images from the MUCT database and uncontrolled, in the wild images from the PaSC database, the most challenging face recognition database to date, showing an improved performance. Finally, we present our SCITOS G5 robot system, which incorporates our framework as a means of image pre-processing for face analysis.
The presented wide-Vin step-down converter introduces a parallel-resonant converter (PRC), comprising an integrated 5-bit capacitor array and a 300 nH resonant coil, placed in parallel to a conventional buck converter. Unlike conventional resonant concepts, the implemented soft-switching control eliminates input voltage dependent losses over a wide operating range. This ensures high efficiency across a wide range of Vin= 12-48V, 100-500mA load and 5V output at up to 15MHz switching frequency. The peak efficiency of the converter is 76.3 %. Thanks to the low output current ripple, the output capacitor can be as small as 50 nF, while the inductor tolerates a larger ESR, resulting in small component size. The proposed PRC architecture is also suitable for future power electronics applications using fast-switching GaN devices.
More and more power electronics applications utilize GaN transistors as they enable higher switching frequencies in comparison to conventional Si devices. Faster switching shrinks down the size of passives and enables compact solutions in applications like renewable energy, electrical cars and home appliances. GaN transistors benefit from ~10× smaller gate charge QG and gate drive voltages in the range of typically 5V vs. ~15V for Si.
Modern power transistors are able to switch at very high transition speed, which can cause EMC violations and overshoot. This is addressed by a gate driver with variable gate current, which is able to control the transition speed. The key idea is that the gate driver can influence the di/dt and dv/dt transition separately and optimize whichever transition promises the highest improvement while keeping switching losses low. To account for changes in the load current, supply voltage, etc., a control loop is required in the driver to ensure optimized switching. In this paper, an efficient control scheme for an automotive gate driver with variable output current capability is presented. The effectiveness of the control loop is demonstrated for a MOSFET bridge consisting of OptiMOS-T2™devices with a total gate charge of 39nC. This bridge setup shows dv/dt transitions between 50 to 1000ns, depending on driving current. The driver is able to switch between gate current levels of 1 to 500mA in 10/15ns (rising/falling transition). With the implemented control loop the driver is measured to significantly reduce the ringing and thereby reduce device stress and electromagnetic emissions while keeping switching losses 52% lower than with a constant current driver.