Prodrive Technologies (Netherlands)

Nonisolated three-phase AC/DC converter concepts facilitate more compact and more efficient realizations of future electric vehicle (EV) chargers. However, without the galvanic isolation and/or high common-mode (CM) impedance provided by an isolation transformer, nonisolated chargers must employ other means to suppress CM leakage currents to ground sufficiently and to prevent nuisance tripping of mandatory residual current devices (RCDs). Typically, the required electromagnetic interference (EMI) filters reduce high-frequency (HF) CM leakage currents to uncritical values. However, low-frequency (LF) CM voltages, e.g., generated by third-harmonic injection, may drive significant LF CM currents through the parasitic capacitances of the DC output (including the battery pack) to protective earth (PE). Therefore, considering a nonisolated three-phase buck–boost (bB) current DC-link PFC rectifier system that consists of a buck-type current-source rectifier (CSR) stage and a three-level boost-type DC/DC-stage, this article first proposes a virtual grounding control (VGC) of the DC output voltage midpoint. VGC employs the DC/DC-stage to compensate the LF (third-harmonic) CM voltage inherently generated by the CSR-stage and thus controls the LF CM voltage between the DC output midpoint and PE to zero. This enables further a direct connection of the DC output midpoint to PE, where an additionally proposed ground current control (GCC) ensures near-zero LF CM leakage current. The proposed concepts are verified with a 10-kW hardware demonstrator (power density of 6.4 kW/dm 3 or 107.5 W/in 3 and full-load peak efficiency of 98.5%) considering terra–terra (TT) and terra–neutral (TN) grounding systems. With a direct connection of the DC output midpoint to PE, GCC limits the LF CM leakage current to < 6 mA RMS, i.e., significantly below typical RCD trip levels, and, using the human-body impedance model according to UL 2202, achieves a test voltage of 110 mV that is clearly below the most stringent limit (250 mV) of the standard.

Modelling persuasion strategies as predictors of task outcome has several real-world applications and has received considerable attention from the computational linguistics community. However, previous research has failed to account for the resisting strategies employed by an individual to foil such persuasion attempts. Grounded in prior literature in cognitive and social psychology, we propose a generalised framework for identifying resisting strategies in persuasive conversations. We instantiate our framework on two distinct datasets comprising persuasion and negotiation conversations. We also leverage a hierarchical sequence-labelling neural architecture to infer the aforementioned resisting strategies automatically. Our experiments reveal the asymmetry of power roles in non-collaborative goal-directed conversations and the benefits accrued from incorporating resisting strategies on the final conversation outcome. We also investigate the role of different resisting strategies on the conversation outcome and glean insights that corroborate with past findings. We also make the code and the dataset of this work publicly available at \url{https://github.com/americast/resper}.

The components and the solder joints that are made during assembly to hold components to their printed circuit board can suffer from defects and therefore need to be tested. Many research papers on board-Assembly testing focus on boundary scan test, processor-controlled test, or other powered digital testing techniques that mostly ignore the indispensable passive circuits and that can incur damage that could have been avoided by executing a non-powered test first. In-circuit testing is a non-powered test method that applies stimuli and measures responses using probe needles. However, often used self-learning solutions for designing these tests need a known-good-board, entailing significant disadvantages. In this paper, a software tool is described that automatically generates in-circuit tests based on the product design files, without requiring probe access on every net. Furthermore, the tool indicates where on the board fault coverage is not maximal, and hence where extra probe access will improve the test quality.

This paper introduces the quad-active-bridge (QAB) ac-dc converter, which provides isolation and bidirectional power flow in a single-stage topology. While matrix-based topologies commonly use bipolar voltage switches, the proposed solution allows the use of unipolar voltage switches. Compared to a six-switch inverter, the average voltage stress is reduced by a factor of 2. A modulation scheme is derived for this converter, which is analytically optimized toward minimum conduction losses to improve the conversion efficiency. The modulation scheme consists of closed-form algebraic solutions such that no lookup tables are required for implementation. Considerations for the converter design and the main component selection procedures are given. The proposed topology and modulation strategy is implemented in a 20-kW prototype. Measurements are conducted and show that the methods operate as expected. Experimental results show that the load step is stable, the power factor is close to unity, and the phase current total harmonic distortion is less than 5%. Finally, it is shown that the circulating current can be controlled independent of the output power. The methods and tools provided can be used for the design and analysis of ac-dc power converters based on the QAB topology.

The Internet routing system faces serious scalability challenges due to the growing number of IP prefixes that needs to be propagated throughout the network. Although IP prefixes are assigned hierarchically and roughly align with geographic regions, today’s Border Gateway Protocol (BGP) and operational practices do not exploit opportunities to aggregate routing information. We present DRAGON, a distributed route-aggregation technique whereby nodes analyze BGP routes across different prefixes to determine which of them can be filtered while respecting the routing policies for forwarding data-packets. DRAGON works with BGP, can be deployed incrementally, and offers incentives for Autonomous Systems (ASs) to upgrade their router software. We illustrate the design of DRAGON through a number of examples, prove its properties while developing a theoretical model of route aggregation, and evaluate its performance. Our experiments with realistic AS-level topologies, assignments of IP prefixes, and routing policies show that DRAGON reduces the number of prefixes in each AS by at least 70% with minimal stretch in the lengths of AS-paths traversed by data packets.

Nancy Herther: Thank you very much and I hope you will all find places to sit here. Hopefully this is going to be a wonderful session. We've designed this so that we have wonderful people up here with great experience, but at the same time we want to know your questions. First, a note on the title. We certainly are going to be looking at all of the major sorts of changes and issues that are coming up from all of the vendors. Obviously we couldn't fit all of the vendors up here, so in planning this program I tried to put together three people that I knew could do the job, and I'm hoping that those of you out in the audience who are working with other companies that are involved with this feel free to join the conversation and the discussion. As Charles was saying, we're planning on cutting this off so that we have a minimum of 10 minutes at the end because we really want this to be a conversation, a discussion with you.

Mechanical hybrid powertrains have the potential to improve the fuel economy of passenger vehicles at a relatively low cost, by adding a flywheel and only mechanical transmission components to a conventional powertrain. This paper presents a systematic approach to optimizing the topology and flywheel size, which are the key design parameters of a mechanical hybrid powertrain. The topology is optimized from a limited set of over 20 existing mechanical hybrid powertrains described in the literature. After a systematic classification of the topologies, a set of four competitive powertrains is selected for further investigation. The fuel-saving potential of each hybrid powertrain is computed using an optimal energy controller and modular component models, for various flywheel sizes and for three certified driving cycles. The hybridization cost is estimated based on the type and size of the components. Other criteria, such as control complexity, clutch wear, and driving comfort are qualitatively evaluated to put the fuel-saving potential and the hybridization cost into a wider perspective. Results show that, for each of the four investigated hybrid powertrains, the fuel-saving benefit returns the hybridization investment well within (about 50%) the service life of passenger vehicles. The optimal topology follows from a discussion that considers all the optimization criteria. The associated optimal flywheel size has an energy storage capacity that is approximately equivalent to the kinetic energy of the vehicle during urban driving (50 km/h).

Current software packages for Hybrid Electric Vehicle (HEV) modelling do not offer the comprehensive functionality to perform the wide variety of analyses required by both manufacturers and customers. The functionality is determined by the modelling structure, and often several structures must be employed to cater for all types of analysis. A new modelling structure for HEVs is proposed, employing an approach which overcomes the causes of limited functionality. It makes possible a wide range of investigations, the results of which offer quantification of the benefits that can be achieved in terms of, for example, tank-to-wheel analyses, emissions, and performance. The accuracy of calculations made with a software employing the new modelling structure is shown to be comparable to the accuracy of data supplied, satisfying the intended purpose.