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Wide bandgap semiconductors, SiC and GaN-based power devices represent key candidates in the development of more efficient devices due to their superior electrical and thermal properties compared to silicon. To achieve maximal performance from WBG semiconductors, new packaging technologies and thermo-electric designs must be developed to ensure efficient and fast switching of devices while minimizing losses. The paper aims to investigate the thermal and mechanical behavior of new prepackage embedding technologies by finite element simulation. The focus is on insulated substrates including direct bonded copper (DBC) with various dielectrics such as AlN, Al 2O 3, Si3N 4 and new insulated metal substrates (IMS) with emphasis on commercially available materials and thicknesses. This study proposes a thermo-mechanical pareto-optimization methodology able to identify the best substrate configuration. The sintered silver layer (in both sides of the chip), which is the most prone to failure due to delamination, has been modelled with a temperature-dependent bilinear hardening model to account for plasticity. Pareto-optimization accounts for the module thermal resistance and the plastic strain or Von Mises Stress in the sintered layer. Results demonstrate that the best candidate from the thermo-mechanical point of view is the DBC with AlN showing a thermal resistance of 0.34 K/W, accumulative plastic strain of 0.18 % and Von Mises stress of 274 MPa. Finally, the parasitic inductance of multiple pre-packages is evaluated to scale the power of the module. Proper design allows to achieve a stray inductance as small as 1.23 nH for two prepackages and 2.85 nH for four prepackages.
Horizontal chip cracks have been reported in various scientific publications on PCB embedded power semiconductor devices. This study investigates in detail the root cause of the cracks. Experimental evidence indicates that the chip fractures in the mechanical grinding process during preparation of the cross-sections. Here, two different factors are relevant: First, the mechanical fracture strength of the semiconductor die decreases when grinding its edge. The use of P320 sand paper reduces the characteristic fracture strength from 719 MPa to 211 MPa. Second, the tensile stresses in the chip edge increase considerably when, part of the die and package is removed by grinding. Both effects together result in a failure probability of 100%. The use of finer grain sandpaper for target preparation helps to reduce the probability of generating horizontal chip cracks during cross-sectioning.
In the early phase of new vehicle system developments, it is crucial to fully define and optimize working system and functional architectures. Architecture definition and validation in turn requires a quick and accurate evaluation of a system‟s overall performance. Modeling and simulating a complete vehicle system, however, is complex and in many cases was either technically not achievable or simply has been omitted within the development process. It is the utmost challenge in system modeling and simulation to realistically reflect interaction of various electrical, mechanical, thermal, and software elements as attributed to individual system modules and their relations. State-of-the-art tools meanwhile bear this capability. In this paper we present an approach how they may effectively and efficiently be incorporated into a car system development process. To accomplish this target, we „virtualize‟ all system entities while defining and reflecting all relevant system aspects. Our proposed development flow allows simulating, evaluating, and validating complete vehicle systems and their behavior. The proposed flow will sustainably change car system development processes.
The following paper points out the key role of IT in the future of car development. At the moment a fundamental change in the structure of automotive IT organizations can be observed. The fact that software update cycle in automotive, about 1 year, in comparison with Apple, Google or Tesla is too much. The entertainment industry is constantly proceeding ahead much faster than the automotive industry. On top of this, new emerging platforms like Apple CarPlay and Android Auto are providing the look and the feel of a mobile phone regarding the control of the car. The vehicle itself is getting more and more as an “ultimate mobile application or app”. This shows the need of speeding up the Time-to-Market of new innovations in automotive industry.
The structure of IT departments has to support these process. No wonder that CIOs of car manufacturers are looking for new structures in their IT departments that enable faster cycle update for automotive applications taking in consideration safety and security requirements.
This only represents a particular interest, as for Apple and Google, we can see that Google has already a fleet of 23 self-driving cars in place which has already autonomously driven more than one million miles with only 12 accidents on public roads and Apple is said to work under the project name "Titan" on its own electric car.
Another important aspect is the software running in the car itself, e.g. the software that “fuses” data from sensors into a comprehensible form: objects have to be accurately located in the environment model of the socalled ego vehicle as a basis for decisions making either by the driver himself or even by the software that can determine within a fraction of a second what the car is going to do. High definition maps also play a very important role in enabling autonomous driving, being developed and maintained by companies such as Nokia HERE, with accuracy of only a few centimeters are thought to be of strategic importance for Advanced Driver Assistance Systems and Self Driving Cars.
“We’re the engine room of the system,” says Mr. Ristevski, vice president of reality capture and processing for former Nokia’s mapping unit named HERE. To be independent from Apple and Google maps and with that from possible competitors, it is said to be the main reason why the German premium car manufacturer Audi, BMW and Daimler bought the online map service for about € 2.5 bn. This is only the first step in the restructuring of the automotive industry.
Trajectory Modelling for Autonomous Driving: Investigating the Artificial Potential Field Method
(2024)
Although the focus of autonomous driving is on maximizing safety and efficiency, comfort and familiarity will play a key role in the adoption of autonomous driving. Therefore, it is important to develop algorithms that can mimic human driving skills and adapt to individual driving styles. The potential field method (PFM) is an obstacle avoidance algorithm for autonomous driving that uses a repulsive potential field, as a environment model, to navigate the vehicle to the lowest risk potential. In this paper, the PFM is used in a overtake scenario at high speed, to test the impact of using prediction when calculating the ideal yaw rate. Analysis is done on how the potential field can be used for lane keeping while following a car and then for overtaking it. A driving simulator is used to record human driving data and compare it with automated driving using a PFM as is proposed by [3], with modifications to enable future prediction.
This paper reports the findings of an online between subject study that investigated the effectiveness of a non-humanoid socially assistive robot in providing positive reinforcement feedback to aid in improving performance on a cognitively demanding task. Four different feedback conditions were used, including verbal, expressive, neutral, and text-based feedback, to identify which type of feedback could positively influence behaviour. Results showed no significant differences in task performance, perceived workload or robot perception.
The main goals planned to achieve in fifth generation (5G) networks are to increase capacity, improve data rate, decrease latency, improve energy efficiency and provide a better quality of service. To achieve these goals, massive multiple input multiple output (MIMO) is considered as one of the competing technologies that provide high spectral efficiency (SE) and energy efficiency (EE). Hence, energy efficiency, spectral efficiency and transmission reliability are the main performance metrics for massive MIMO systems. Although these performance metrics are thoroughly studied independently, their joint effects are not considered and evaluated for massive MIMO systems. Hence, in this work, we investigate a mathematical model that jointly evaluates the spectral efficiency, energy efficiency and transmission reliability in downlink massive MIMO systems with linear precoding techniques. Closed-form analytical formulation is derived that jointly evaluates the impacts of spectral efficiency and transmission reliability on energy efficiency. Finally, numerical results are provided to validate the theoretical analysis.
A considerable amount of enabling technologies are being explored in the era of fifth generation (5G) mobile system. The dream is to build a wireless network that substantially improves the existing mobile networks in all performance metrics. To address this 5G design targets, massive MIMO (multiple input multiple output) and mmWave (millimeter wave) communication are also candidate technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form mmWave-massive MIMO which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid analog-digital beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.
This study investigated the thermal performance of a packaging solution designed to manage the electrical isolation and cooling of high voltage ( ) SiC power semiconductor > 3300 V devices. The proposed packaging merges the ceramic substrate and the heat exchanger into a single component, streamlining the overall design. Specifically, a novel heat exchanger is developed for a multi-chip module (20 kV), utilizing a combination of jet impingement and channel- flow cooling techniques. Computational fluid dynamics (CFD) simulations and experimental validation are conducted on a multi-chip module to assess the thermal resistance of this new cooling solution. The results demonstrate a
low thermal resistivity of 0.118 cm2K/W, indicating the potential for improved cooling performance in high voltage and power density semiconductor applications.
When we approach a group, there is an exchange of a multitude of verbal or non-verbal social signals to indicate that we are looking to interact. We continue to share these signals throughout the interaction to portray our thoughts and motivations. We define an interaction by the signals we send; sending different signals evokes a different response. Giving social robots the knowledge of group social interaction, they will have the ability to more effectively participate in these interactions in the real world. In this paper, we present the results from an online data collection study looking at social group dynamics. We collected a dataset of social behaviours in a group using a socially interactive game played online by 88 participants. We also introduce a novel visual social engagement metric, which is derived from two social signals: proxemics (distance between interaction participants) and mutual gaze. We propose a mathematical formula of both mutual gaze as the product of the mutual distances to the optical axis, and the visual social engagement as mutual gaze divided by distance between participants. Additionally, we investigate the influence of personality traits on the resulting interaction patterns. Using the metric, we create unique interaction profiles which suggest that participants have an interaction ‘style’. No clear correlation between personality and interaction patterns was found.