TY - JOUR A1 - Mohan, Nihesh A1 - Steinberger, Fabian A1 - Wächter, Sonja A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Additive Manufacturing for Automotive Radar Sensors Using Copper Inks and Pastes JF - Applied Sciences N2 - Radar sensors are critical for obstacle detection and navigation, especially for automated driving. Using the use-case “printing of heating coils on the inside of the front housing (primary radome)” needed for de-icing in winter, it is demonstrated that additive manufacturing (AM) can provide economic and functional benefits for manufacturing of the sensors. AM will allow significant cost reduction by eliminating parts and simplifying the manufacturing process. Different AM technologies for the coils were investigated, first, by applying the conductive traces by fused deposition modeling (FDM), and, second, by printing copper particle-free inks and pastes. The metal layers were electrically and mechanically characterized using a profilometer to measure the trace dimension and a four-point probe to measure the resistance. It was revealed that low-cost conductive filaments with low resistivity and current carrying capacity are commercially still not available. The best option sourced was a copper–polyester-based filament with 6000 µΩcm after printing. Therefore, low-cost particle-free copper inks and commercial copper flake paste were selected to print the heating coil. The Cu particle-free inks were amine-based Cu (II) formate complexes, where the Cu exists in an ionic form. Using contactless printing processes such as ink-jet printing or pneumatic dispensing, the traces could be deposited onto the low-melting temperature (225 °C) polymeric radome structure. After printing, the material needed to be sintered to form the conductive copper traces. To avoid damaging the polymer radome during sintering, two different processes were investigated: low-temperature (<150 °C) sintering in an oven for 30 min or fast laser sintering. The sintered Cu layers achieved the following specific electric resistivities when slowly sintered in the oven: paste 4 µΩcm and ink 8.8 µΩcm. Using laser sintering, the ink achieved 3.2 µΩcm because the locally high temperature provides better sintering. Also, the adhesion was significantly increased to (5 B). Therefore, laser sintering is the preferred technology. In addition, it allows fast processing directly after printing. Commercial equipment is available where printing and laser sintering is integrated. The potential of low-cost copper material and the integration in additive manufacturing of electronic systems using radar sensors as an example are demonstrated in this paper. UR - https://doi.org/10.3390/app15052676 Y1 - 2025 UR - https://doi.org/10.3390/app15052676 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58065 SN - 2076-3417 VL - 15 IS - 5 PB - MDPI CY - Basel ER - TY - CHAP A1 - Tavakolibasti, M. A1 - Meszmer, P. A1 - Böttger, Gunnar A1 - Kettelgerdes, Marcel A1 - Elger, Gordon A1 - Erdogan, Hüseyin A1 - Seshaditya, A. A1 - Wunderle, Bernhard T1 - Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR T2 - 2021 22nd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE52062.2021.9410831 KW - Couplings KW - Laser radar KW - Digital twin KW - Thermomechanical processes KW - Adaptive optics KW - Optical coupling KW - Real-time systems Y1 - 2021 UR - https://doi.org/10.1109/EuroSimE52062.2021.9410831 SN - 978-1-6654-1373-2 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Streck, Egor A1 - Schmok, Peter A1 - Schneider, Klaus A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Safeguarding future autonomous traffic by infrastructure based on multi radar sensor systems T2 - FISITA World Congress 2021 Y1 - 2021 UR - https://www.fisita.com/library/f2021-acm-121 N1 - Paper + Video PB - FISITA CY - Bishops Stortford ER - TY - CHAP A1 - Elger, Gordon A1 - Biberger, M. A1 - Meier, M. A1 - Schweigart, Helmut A1 - Schneider, Klaus A1 - Erdogan, Hüseyin T1 - Technische Sauberkeit von Radarbaugruppen T2 - Elektronische Baugruppen und Leiterplatten EBL 2018: Multifunktionale Aufbau- und Verbindungstechnik – Beherrschung der Vielfalt Y1 - 2018 UR - https://www.dvs-media.eu/de/buecher/dvs-berichte/3644/elektronische-baugruppen-und-leiterplatten-ebl-2018 SN - 978-3-96144-026-9 SP - 339 EP - 349 PB - DVS Media GmbH CY - Düsseldorf ER - TY - CHAP A1 - Tavakolibasti, M. A1 - Meszmer, P. A1 - Kettelgerdes, Marcel A1 - Böttger, Gunnar A1 - Elger, Gordon A1 - Erdogan, Hüseyin A1 - Seshaditya, A. A1 - Wunderle, Bernhard T1 - Structural-thermal-optical-performance (STOP) analysis of a lens stack for realization of a digital twin of an automotive LiDAR T2 - 2022 23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE54907.2022.9758897 KW - thermo-mechanical simulation KW - optical simulation KW - digital twin KW - structural thermal optical performance analysis Y1 - 2022 UR - https://doi.org/10.1109/EuroSimE54907.2022.9758897 SN - 978-1-6654-5836-8 PB - IEEE CY - Piscataway, NJ ER - TY - JOUR A1 - Kettelgerdes, Marcel A1 - Sarmiento, Nicolas A1 - Erdogan, Hüseyin A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors JF - Remote Sensing N2 - With current advances in automated driving, optical sensors like cameras and LiDARs are playing an increasingly important role in modern driver assistance systems. However, these sensors face challenges from adverse weather effects like fog and precipitation, which significantly degrade the sensor performance due to scattering effects in its optical path. Consequently, major efforts are being made to understand, model, and mitigate these effects. In this work, the reverse research question is investigated, demonstrating that these measurement effects can be exploited to predict occurring weather conditions by using state-of-the-art deep learning mechanisms. In order to do so, a variety of models have been developed and trained on a recorded multiseason dataset and benchmarked with respect to performance, model size, and required computational resources, showing that especially modern vision transformers achieve remarkable results in distinguishing up to 15 precipitation classes with an accuracy of 84.41% and predicting the corresponding precipitation rate with a mean absolute error of less than 0.47 mm/h, solely based on measurement noise. Therefore, this research may contribute to a cost-effective solution for characterizing precipitation with a commercial Flash LiDAR sensor, which can be implemented as a lightweight vehicle software feature to issue advanced driver warnings, adapt driving dynamics, or serve as a data quality measure for adaptive data preprocessing and fusion. UR - https://doi.org/10.3390/rs16132407 Y1 - 2024 UR - https://doi.org/10.3390/rs16132407 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-49599 SN - 2072-4292 VL - 16 IS - 13 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mohan, Nihesh A1 - Ahuir-Torres, Juan Ignacio A1 - Bhogaraju, Sri Krishna A1 - Webler, Ralf A1 - Kotadia, Hiren R. A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Decomposition mechanism and morphological evolution of in situ realized Cu nanoparticles in Cu complex inks JF - New Journal of Chemistry UR - https://doi.org/10.1039/D3NJ05185D Y1 - 2024 UR - https://doi.org/10.1039/D3NJ05185D SN - 1369-9261 VL - 48 IS - 15 SP - 6796 EP - 6808 PB - RSC CY - London ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Mohan, Nihesh A1 - Steinberger, Fabian A1 - Erdogan, Hüseyin A1 - Hadrava, Philipp A1 - Elger, Gordon T1 - Novel Low Temperature and Low Pressure Sintering of ADAS Radar Sensor Antenna Stack T2 - 2023 24th European Microelectronics and Packaging Conference & Exhibition (EMPC) UR - https://doi.org/10.23919/EMPC55870.2023.10418277 Y1 - 2024 UR - https://doi.org/10.23919/EMPC55870.2023.10418277 SN - 978-0-9568086-9-1 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Kettelgerdes, Marcel A1 - Hillmann, Tjorven A1 - Hirmer, Thomas A1 - Erdogan, Hüseyin A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Accelerated Real-Life (ARL) Testing and Characterization of Automotive LiDAR Sensors to facilitate the Development and Validation of Enhanced Sensor Models N2 - In the realm of automated driving simulation and sensor modeling, the need for highly accurate sensor models is paramount for ensuring the reliability and safety of advanced driving assistance systems (ADAS). Hence, numerous works focus on the development of high-fidelity models of ADAS sensors, such as camera, Radar as well as modern LiDAR systems to simulate the sensor behavior in different driving scenarios, even under varying environmental conditions, considering for example adverse weather effects. However, aging effects of sensors, leading to suboptimal system performance, are mostly overlooked by current simulation techniques. This paper introduces a cutting-edge Hardware-in-the-Loop (HiL) test bench designed for the automated, accelerated aging and characterization of Automotive LiDAR sensors. The primary objective of this research is to address the aging effects of LiDAR sensors over the product life cycle, specifically focusing on aspects such as laser beam profile deterioration, output power reduction and intrinsic parameter drift, which are mostly neglected in current sensor models. By that, this proceeding research is intended to path the way, not only towards identifying and modeling respective degradation effects, but also to suggest quantitative model validation metrics. UR - https://doi.org/10.48550/arXiv.2312.04229 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2312.04229 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59856 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Koval, Leonid A1 - Wächter, Sonja A1 - Erdogan, Hüseyin A1 - Großmann, Daniel T1 - Ontology-Driven Modeling and Integration of Production Processes in Advanced Driver-Assistance Systems within the Gaia-X Ecosystem T2 - 2025 11th International Conference on Computer Technology Applications (ICCTA 2025) UR - https://doi.org/10.1109/ICCTA65425.2025.11166225 Y1 - 2025 UR - https://doi.org/10.1109/ICCTA65425.2025.11166225 SN - 979-8-3315-1265-1 SP - 211 EP - 216 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kettelgerdes, Marcel A1 - Mezmer, Peter A1 - Haeussler, Michael J. A1 - Böttger, Gunnar A1 - Tavakolibasti, Majid A1 - Pandey, Amit A1 - Erdogan, Hüseyin A1 - Elger, Gordon A1 - Schacht, Ralph A1 - Wunderle, Bernhard T1 - Realization, multi-field coupled simulation and characterization of a thermo-mechanically robust LiDAR front end on a copper coated glass substrate T2 - Proceedings: IEEE 73rd Electronic Components and Technology Conference, ECTC 2023 UR - https://doi.org/10.1109/ECTC51909.2023.00131 KW - LiDAR KW - Reliability KW - Thermo-mechanical Simulation KW - Optical Simulation KW - VCSEL KW - Lifetime Testing KW - Glass Packaging Y1 - 2023 UR - https://doi.org/10.1109/ECTC51909.2023.00131 SN - 979-8-3503-3498-2 SN - 2377-5726 SP - 753 EP - 760 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kettelgerdes, Marcel A1 - Pandey, Amit A1 - Unruh, Denis A1 - Erdogan, Hüseyin A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Automotive LiDAR Based Precipitation State Estimation Using Physics Informed Spatio-Temporal 3D Convolutional Neural Networks (PIST-CNN) T2 - 2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) UR - https://doi.org/10.1109/M2VIP58386.2023.10413394 Y1 - 2024 UR - https://doi.org/10.1109/M2VIP58386.2023.10413394 SN - 979-8-3503-2562-1 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Pandey, Amit A1 - Kühn, Stephan A1 - Erdogan, Hüseyin A1 - Schneider, Klaus A1 - Elger, Gordon T1 - Finite Element Analysis: A Tool for Investigation of Sharpness Changes in Automotive Cameras T2 - 2020 21st International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE48426.2020.9152716 KW - Solid modeling KW - Creep KW - Load modeling KW - Lenses KW - Optical imaging KW - Optical sensors KW - Cameras Y1 - 2020 UR - https://doi.org/10.1109/EuroSimE48426.2020.9152716 SN - 978-1-7281-6049-8 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kühn, Stephan A1 - Pandey, Amit A1 - Zippelius, Andreas A1 - Schneider, Klaus A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Analysis of package design of optic modules for automotive cameras to realize reliable image sharpness T2 - 2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC48849.2020.9229786 KW - Condition Monitoring KW - Health Indicator KW - Change in Sharpness KW - Through Focus Y1 - 2020 UR - https://doi.org/10.1109/ESTC48849.2020.9229786 SN - 978-1-7281-6293-5 PB - IEEE CY - Piscataway ER -