Detection Of Electric Vehicles And Photovoltaic Systems In Smart Meter Data

In the course of the switch to renewable energy sources, there is a shift from a few large energy sources (power plants) to a large number of small, distributed energy sources (e.g., photovoltaic systems) and energy storage devices (e.g., electric vehicles). This results in the need to know and identify these energy sources and sinks as soon as new devices are installed, in order to ensure grid... » read more

Machine Learning-Based Optimization Of Chiral Photonic Nanostructures: Evolution- And Neural Network-Based Design

Chiral photonics opens new pathways to manipulate light-matter interactions and tailor the optical response of metasurfaces and -materials by nanostructuring nontrivial patterns. Chirality of matter, such as that of molecules, and light, which in the simplest case is given by the handedness of circular polarization, have attracted much attention for applications in chemistry, nanophotonics and ... » read more

Virtual Testing Of Automotive Sensor Systems

The development of vehicles has always been a discipline of mechanical engineering. After all, cars were always about the engine, the power, the efficiency. Traditionally, the development of the complex overall automotive system has always been carried out in accordance with classical principles of mechanical engineering, for example by using development models like the V-model. Although the pr... » read more

Modeling Chips From Atoms To Systems

Complexity in hardware design is spilling over to other disciplines, including software, manufacturing, and new materials, creating issues for how to model more data at multiple abstraction levels. Challenges are growing around which abstraction level to use for a particular stage of the design, when to use it, and which data to include. Those decisions are becoming more difficult at each ne... » read more

Condition Monitoring Of Drive Trains By Data Fusion Of Acoustic Emission And Vibration Sensors

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. The data analysis can be improved by applying machine learning algorithms and fusion of data from heterogenous sensors. This paper presents an approach for a step-wise integration of classifications gained from vibration and ac... » read more

AnastASICA — Towards Structured and Automated Analog/Mixed-Signal IC Design For Automotive Electronics

In our world based on electronics, the design of analog/mixed-signal (AMS) ICs is still mainly done manually. While digital design benefits from complete synthesis flows, analog lags far behind in terms of development time, cost, and risk. Analog design flows are hardly standardized and necessitate the four eye principle as important quality tool. Thus, highly experienced designers who incorpor... » read more

Automated Traceability Of Requirements In The Design And Verification Process Of Safety-Critical Mixed-Signal Systems

System-level design and verification of safety-critical hardware requires a consistent methodology which complies with industrial safety-standards, for example ISO 26262 for automotive applications. For certification of safety-critical systems, the development process has to implement and enforce a strict traceability of requirements, linking the requirement specification, the design implementa... » read more

Week In Review: Auto, Security, Pervasive Computing

Security Infineon announced it has a Trusted Platform Module (TPM 2.0), called OPTIGA TPM 2.0, used to secure remote software updates, disc encryption, and user authentication on Linux-based systems. OPTIGA is an open software stack for securing comprehensive TSS* host software implementing the latest FAPI standard. Infineon developed the open-source software with Intel Corporation and Fraunho... » read more

Power Models For Machine Learning

AI and machine learning are being designed into just about everything, but the chip industry lacks sufficient tools to gauge how much power and energy an algorithm is using when it runs on a particular hardware platform. The missing information is a serious limiter for energy-sensitive devices. As the old maxim goes, you can't optimize what you can't measure. Today, the focus is on functiona... » read more

Brute-Force Analysis Not Keeping Up With IC Complexity

Much of the current design and verification flow was built on brute force analysis, a simple and direct approach. But that approach rarely scales, and as designs become larger and the number of interdependencies increases, ensuring the design always operates within spec is becoming a monumental task. Unless design teams want to keep adding increasing amounts of margin, they have to locate th... » read more

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