TY - CHAP A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Liu, E A1 - Elger, Gordon T1 - Correlation of Scanning Acoustic Microscopy and Transient Thermal Analysis to Identify Crack Growth in Solder Joints T2 - Proceedings of the Twenty First InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2022 UR - https://doi.org/10.1109/iTherm54085.2022.9899664 KW - reliability KW - transient thermal analysis (TTA) KW - scanning acoustic microscopy (SAM) KW - finite element simulation KW - finite element optimization KW - LED KW - solder KW - crack Y1 - 2022 UR - https://doi.org/10.1109/iTherm54085.2022.9899664 SN - 978-1-6654-8503-6 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Zippelius, Andreas A1 - Strobl, Tobias A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Hoffmann, Alwin A1 - Elger, Gordon T1 - Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks T2 - 2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC55720.2022.9939465 KW - Solder Joints KW - LED KW - non-destructive testing KW - Machine Learning KW - Scanning Acoustic Microscopy (SAM) KW - Transient Thermal Analysis (TTA), Convolutional Neural Network (CNN) Y1 - 2022 UR - https://doi.org/10.1109/ESTC55720.2022.9939465 SN - 978-1-6654-8947-8 SP - 566 EP - 575 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Reliability of SAC Solders under Low and High Stress Conditions T2 - 2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC55720.2022.9939394 KW - reliability KW - solder joint cracking KW - SAC solder KW - transient thermal analysis KW - SAM Y1 - 2022 UR - https://doi.org/10.1109/ESTC55720.2022.9939394 SN - 978-1-6654-8947-8 SP - 553 EP - 559 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Liu, E A1 - Bhogaraju, Sri Krishna A1 - Lux, Kerstin A1 - Elger, Gordon A1 - Mou, Rokeya Mumtahana T1 - Investigation Of Stress Generated By Interconnection Processes With Micro-Raman Spectroscopy (μRS) T2 - Proceedings IEEE 72nd Electronic Components and Technology Conference: ECTC 2022 UR - https://doi.org/10.1109/ECTC51906.2022.00123 KW - component KW - μ-Raman Spectroscopy KW - Au80Sn20 KW - Cu sintering KW - finite element simultion Y1 - 2022 UR - https://doi.org/10.1109/ECTC51906.2022.00123 SN - 978-1-6654-7943-1 SP - 739 EP - 745 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Saccon, Rodolfo A1 - Benin, Alice A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Effect of binders on the performance of copper sintering pastes T2 - 2022 International Conference on Electronics Packaging (ICEP 2022) UR - https://doi.org/10.23919/ICEP55381.2022.9795555 KW - copper sintering KW - binders KW - nanoparticles KW - reduction KW - alcohols, polyols Y1 - 2022 UR - https://doi.org/10.23919/ICEP55381.2022.9795555 SN - 978-4-9911911-3-8 SP - 71 EP - 72 PB - IEEE CY - Piscataway (NJ) ER - TY - CHAP A1 - Kleiner, Jan A1 - Heider, Alexander A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Experimental Study on the Thermal Interactions in Novel Intelligent Lithium-Ion Modules for Electric Vehicles T2 - Proceedings of the Twentieth InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2021 UR - https://doi.org/10.1109/ITherm51669.2021.9503299 KW - Intelligent battery KW - Lithium-ion KW - Reconfiguration KW - Cooling KW - Thermal management KW - Parallel connection Y1 - 2021 UR - https://doi.org/10.1109/ITherm51669.2021.9503299 SN - 978-1-7281-8539-2 SN - 2694-2135 SP - 556 EP - 562 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Senel, Numan A1 - Elger, Gordon A1 - Festag, Andreas T1 - Sensor Time Synchronization in Smart Road Infrastructure T2 - FISITA Web Congress 2020 Y1 - 2020 UR - https://www.fisita.com/library/f2020-acm-083 PB - FISITA CY - Bishops Stortford ER - TY - JOUR A1 - Zippelius, Andreas A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Pérez-Velázquez, Judith A1 - Elger, Gordon T1 - Reliability analysis and condition monitoring of SAC+ solder joints under high thermomechanical stress conditions using neuronal networks JF - Microelectronics Reliability N2 - The thermo-mechanical fatigue of different SAC+ solders is investigated using transient thermal analysis (TTA) and predicted using artificial neural networks (ANN). TTA measures the thermal impedance and allows detection of solder cracks and delamination of material interfaces. LEDs soldered to printed circuit boards using seven different solders were aged within passive air-to-air temperature shock tests with TTA measurements every 50 cycles with the increase of the thermal resistance as failure criterium. A SnAgCuSb solder showed the best performance improvement over the SAC305 reference under the test conditions. In addition to standard evaluation by the cumulative failure-curve and Weibull plot, new approaches for reliability assessment are investigated to assess the reliability of the solder joint of the individual LEDs. A hybrid approach to predict failures in the solder joints of the individual LEDs during accelerated stress testing is set-up which processes the TTA data using artificial neural networks with memory, specifically LSTM, where the memory allows full use of the measurement history. Two ANN approaches, regression and classification, are used. Both approaches are shown to be quite accurate. The greater information gained from the regression approach requires more processing using external knowledge of the problem requirements, whereas the categorical approach can be more directly implemented. The results demonstrate the advantages of integrated approaches for assessment of the remaining useful life of solder joints. UR - https://doi.org/10.1016/j.microrel.2021.114461 KW - Artificial neural networks KW - LSTM KW - Prediction KW - Reliability KW - Solder joints KW - Transient thermal analysis Y1 - 2022 UR - https://doi.org/10.1016/j.microrel.2021.114461 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-19719 SN - 0026-2714 VL - 2022 IS - 129 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Conti, Fosca A1 - Elger, Gordon T1 - Reliability of sintered and soldered high power chip size packages and flip chip LEDs T2 - ECTC - The 2018 IEEE 68th Electronic Components and Technology Conference: Proceedings UR - https://doi.org/10.1109/ECTC.2018.00312 Y1 - 2018 UR - https://doi.org/10.1109/ECTC.2018.00312 SN - 978-1-5386-5000-4 SP - 2080 EP - 2088 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Mokhtari, Omid A1 - Pascucci, Jacopo A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Conti, Fosca A1 - Elger, Gordon T1 - Hybrid Cu particle paste with surface-modified particles for high temperature electronics packaging T2 - Proceedings 22nd European Microelectronics and Packaging Conference, EMPC UR - https://doi.org/10.23919/EMPC44848.2019.8951887 Y1 - 2020 UR - https://doi.org/10.23919/EMPC44848.2019.8951887 SN - 978-1-7281-6291-1 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Liu, E A1 - Elger, Gordon T1 - Transient thermal analysis as measurement method for IC package structural integrity JF - Chinese Physics B UR - https://doi.org/10.1088/1674-1056/24/6/068105 Y1 - 2015 UR - https://doi.org/10.1088/1674-1056/24/6/068105 SN - 2058-3834 SN - 1674-1056 VL - 24 IS - 6 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Hanss, Alexander A1 - Elger, Gordon T1 - Residual free solder process for fluxless solder pastes JF - Soldering & Surface Mount Technology UR - https://doi.org/10.1108/SSMT-10-2017-0030 KW - Reflow soldering KW - LED KW - Fluxless KW - Solder process Y1 - 2018 UR - https://doi.org/10.1108/SSMT-10-2017-0030 SN - 0954-0911 VL - 30 IS - 2 SP - 118 EP - 128 PB - Emerald CY - Bingley ER - TY - CHAP A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Conti, Fosca A1 - Elger, Gordon T1 - Process development and reliability of sintered high power chip size packages and flip chip LEDs T2 - 2018 International Conference on Electronics Packaging and iMAPS All Asia Conference (ICEP-IAAC) UR - https://doi.org/10.23919/ICEP.2018.8374351 KW - LED KW - Reliability KW - Sintering KW - Transient Thermal Testing Y1 - 2018 UR - https://doi.org/10.23919/ICEP.2018.8374351 SN - 978-4-9902-1885-0 SP - 479 EP - 484 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Elger, Gordon A1 - Conti, Fosca T1 - Evaluation of silver and copper sintering of first level interconnects for high power LEDs T2 - 2018 7th Electronic System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC.2018.8546499 KW - transient thermal analysis KW - pressureless silver sintering KW - pressureless copper sintering KW - bonding atmosphere KW - particle size KW - binder chemistry Y1 - 2018 UR - https://doi.org/10.1109/ESTC.2018.8546499 SN - 978-1-5386-6814-6 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Measurement of the transient thermal impedance of MOSFETs over the sensitivity of the threshold voltage T2 - EPE'18 ECCE Europe KW - Reliability KW - MOSFET KW - Thermal stress KW - Thermal design KW - Measurement Y1 - 2018 UR - https://ieeexplore.ieee.org/document/8515480 SN - 978-9-0758-1528-3 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Elger, Gordon A1 - Hanss, Alexander A1 - Schmid, Maximilian T1 - Transient Thermal Analysis as In-Situ Method in Accelerated Stress Tests to Access Package Integrity of LEDs T2 - 2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC.2018.8593278 KW - Temperature measurement KW - Conferences KW - Integrated circuits KW - Light emitting diodes KW - Transient analysis KW - Temperature dependence KW - Thermal analysis Y1 - 2018 UR - https://doi.org/10.1109/THERMINIC.2018.8593278 SN - 978-1-5386-6759-0 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Conti, Fosca A1 - Hanss, Alexander A1 - Mokhtari, Omid A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Formation of tin-based crystals from a SnAgCu alloy under formic acid vapor JF - New Journal of Chemistry UR - https://doi.org/10.1039/C8NJ04173C Y1 - 2018 UR - https://doi.org/10.1039/C8NJ04173C SN - 1369-9261 VL - 42 IS - 23 SP - 19232 EP - 19236 PB - RSC CY - London ER - TY - CHAP A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Combined Accelerated Stress Test with In-Situ Thermal Impedance Monitoring to Access LED Reliability T2 - Proceedings 2018 20th International Conference on Electronic Materials and Packaging (EMAP) UR - https://doi.org/10.1109/EMAP.2018.8660833 KW - Temperature measurement KW - Light emitting diodes KW - Temperature KW - Electronic packaging thermal management KW - Temperature sensors KW - Transient analysis KW - Sensitivity Y1 - 2019 UR - https://doi.org/10.1109/EMAP.2018.8660833 SN - 978-1-5386-5642-6 PB - IEEE CY - Piscataway 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 - Bhogaraju, Sri Krishna A1 - Schmid, Maximilian A1 - Liu, E A1 - Saccon, Rodolfo A1 - Elger, Gordon A1 - Klassen, Holger A1 - Müller, Klaus A1 - Pirzer, Georg T1 - Low cost copper based sintered interconnect material for optoelectronics packaging T2 - 2022 IEEE 72nd Electronic Components and Technology Conference (ECTC) UR - https://doi.org/10.1109/ECTC51906.2022.00270 KW - Cu sintering KW - flakes KW - PEG600 KW - reliability KW - encapsulation KW - oxidation KW - transient thermal analysis KW - Scanning acoustic microscopy KW - μ-Raman spectroscopy Y1 - 2022 UR - https://doi.org/10.1109/ECTC51906.2022.00270 SN - 978-1-6654-7943-1 SP - 1720 EP - 1725 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Signorini, Raffaella A1 - Pedron, Danilo A1 - Conti, Fosca A1 - Hanss, Alexander A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Thermomechanical Stress in GaN LED Soldered on Copper Substrate Evaluated by Raman Measurements and Computer Modelling T2 - 2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC.2018.8593304 KW - Stress KW - Light emitting diodes KW - Gallium nitride KW - Phonons KW - Substrates KW - Temperature measurement KW - Silicon Y1 - 2018 UR - https://doi.org/10.1109/THERMINIC.2018.8593304 SN - 978-1-5386-6759-0 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Liu, E A1 - Bhogaraju, Sri Krishna A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Investigation of stress relaxation in SAC305 with micro-Raman spectroscopy JF - Microelectronics Reliability UR - https://doi.org/10.1016/j.microrel.2022.114664 Y1 - 2022 UR - https://doi.org/10.1016/j.microrel.2022.114664 SN - 0026-2714 VL - 2022 IS - 138 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Mohan, Nihesh A1 - Bhogaraju, Sri Krishna A1 - Lysien, Mateusz A1 - Schneider, Ludovic A1 - Granek, Filip A1 - Lux, Kerstin A1 - Elger, Gordon T1 - Drop feature optimization for fine trace inkjet printing T2 - 2021 23rd European Microelectronics and Packaging Conference & Exhibition (EMPC): Technical Papers UR - https://doi.org/10.23919/EMPC53418.2021.9585004 KW - inkjet printing KW - Ag nanoparticles KW - fine trace KW - surface interactions KW - drop feature KW - ink properties KW - sintering Y1 - 2021 UR - https://doi.org/10.23919/EMPC53418.2021.9585004 SN - 978-0-9568086-7-7 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Kettelgerdes, Marcel A1 - Elger, Gordon T1 - In-Field Measurement and Methodology for Modeling and Validation of Precipitation Effects on Solid-State LiDAR Sensors JF - IEEE Journal of Radio Frequency Identification UR - https://doi.org/10.1109/JRFID.2023.3234999 KW - LiDAR KW - adverse weather KW - sensor model KW - automotive KW - simulation KW - virtual validation KW - ROS KW - ADAS Y1 - 2023 UR - https://doi.org/10.1109/JRFID.2023.3234999 SN - 2469-7281 VL - 7 SP - 192 EP - 202 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - New York ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Schmid, Maximilian A1 - Kotadia, Hiren R. A1 - Conti, Fosca A1 - Elger, Gordon T1 - Highly reliable die-attach bonding with etched brass flakes T2 - 2021 23rd European Microelectronics and Packaging Conference & Exhibition (EMPC): Technical Papers UR - https://doi.org/10.23919/EMPC53418.2021.9584967 KW - sintering KW - etched brass KW - flakes KW - reliability KW - LED KW - die-attach KW - in-situ copper oxide reduction KW - transient thermal analysis Y1 - 2021 UR - https://doi.org/10.23919/EMPC53418.2021.9584967 SN - 978-0-9568086-7-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Steinberger, Fabian A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Correlation between the characteristics of printed sinter paste and the quality of sintered interconnects through non-destructive analysis techniques T2 - NordPac 2023 Annual Microelectronics and Packaging Conference and Exhibition: Reviewed Papers UR - https://doi.org/10.23919/NordPac58023.2023.10186250 KW - profilometry KW - sinter paste KW - interconnect KW - SAM Y1 - 2023 UR - https://doi.org/10.23919/NordPac58023.2023.10186250 SN - 978-91-89821-06-4 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kettelgerdes, Marcel A1 - Elger, Gordon T1 - Modeling Methodology and In-field Measurement Setup to Develop Empiric Weather Models for Solid-State LiDAR Sensors T2 - 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) UR - https://doi.org/10.1109/DTPI55838.2022.9998918 KW - LiDAR KW - adverse weather KW - sensor model KW - auto-motive KW - simulation KW - virtual validation KW - ROS KW - ADAS Y1 - 2022 UR - https://doi.org/10.1109/DTPI55838.2022.9998918 SN - 978-1-6654-9227-0 PB - IEEE CY - Piscataway 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 - Senel, Numan A1 - Kefferpütz, Klaus A1 - Doycheva, Kristina A1 - Elger, Gordon T1 - Multi-Sensor Data Fusion for Real-Time Multi-Object Tracking JF - Processes N2 - Sensor data fusion is essential for environmental perception within smart traffic applications. By using multiple sensors cooperatively, the accuracy and probability of the perception are increased, which is crucial for critical traffic scenarios or under bad weather conditions. In this paper, a modular real-time capable multi-sensor fusion framework is presented and tested to fuse data on the object list level from distributed automotive sensors (cameras, radar, and LiDAR). The modular multi-sensor fusion architecture receives an object list (untracked objects) from each sensor. The fusion framework combines classical data fusion algorithms, as it contains a coordinate transformation module, an object association module (Hungarian algorithm), an object tracking module (unscented Kalman filter), and a movement compensation module. Due to the modular design, the fusion framework is adaptable and does not rely on the number of sensors or their types. Moreover, the method continues to operate because of this adaptable design in case of an individual sensor failure. This is an essential feature for safety-critical applications. The architecture targets environmental perception in challenging time-critical applications. The developed fusion framework is tested using simulation and public domain experimental data. Using the developed framework, sensor fusion is obtained well below 10 milliseconds of computing time using an AMD Ryzen 7 5800H mobile processor and the Python programming language. Furthermore, the object-level multi-sensor approach enables the detection of changes in the extrinsic calibration of the sensors and potential sensor failures. A concept was developed to use the multi-sensor framework to identify sensor malfunctions. This feature will become extremely important in ensuring the functional safety of the sensors for autonomous driving. UR - https://doi.org/10.3390/pr11020501 KW - environmental perception KW - sensor fusion KW - autonomous vehicle KW - unscented Kalman filter KW - object tracking KW - roadside units Y1 - 2023 UR - https://doi.org/10.3390/pr11020501 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-31989 SN - 2227-9717 VL - 11 IS - 2 PB - MDPI CY - Basel ER - TY - CHAP A1 - Hermann, Joseph A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Crack Growth Prediction in High-Power LEDs from TTA, SAM and Simulated Data T2 - THERMINIC 2022: Proceedings 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950673 KW - reliability KW - transient thermal analysis (TTA) KW - scanning acoustic microscopy (SAM) KW - finite element simulation KW - LED KW - solder KW - crack Y1 - 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950673 SN - 978-1-6654-9229-4 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Agrawal, Shiva A1 - Bhanderi, Savankumar A1 - Doycheva, Kristina A1 - Elger, Gordon T1 - Static multi-target-based auto-calibration of RGB cameras, 3D Radar, and 3D Lidar sensors JF - IEEE Sensors Journal UR - https://doi.org/10.1109/JSEN.2023.3300957 KW - Autonomous vehicles KW - camera KW - feature extraction KW - intelligent roadside infrastructure KW - lidar KW - radar KW - sensor calibration Y1 - 2023 UR - https://doi.org/10.1109/JSEN.2023.3300957 SN - 1530-437X VL - 23 IS - 18 SP - 21493 EP - 21505 PB - IEEE CY - Piscataway 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 - Mohan, Nihesh A1 - Ahuir-Torres, Juan Ignacio A1 - Bhogaraju, Sri Krishna A1 - Kotadia, Hiren R. A1 - Elger, Gordon T1 - Rapid Sintering of Inkjet Printed Cu Complex Inks Using Laser in Air T2 - 2023 24th European Microelectronics and Packaging Conference & Exhibition (EMPC) UR - https://doi.org/10.23919/EMPC55870.2023.10418323 Y1 - 2024 UR - https://doi.org/10.23919/EMPC55870.2023.10418323 SN - 978-0-9568086-9-1 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Ugolini, Francesco A1 - Belponer, Federico A1 - Greci, Alessio A1 - Elger, Gordon T1 - Reliability of Copper Sintered Interconnects Under Extreme Thermal Shock Conditions T2 - 2023 24th European Microelectronics and Packaging Conference & Exhibition (EMPC) UR - https://doi.org/10.23919/EMPC55870.2023.10418348 Y1 - 2024 UR - https://doi.org/10.23919/EMPC55870.2023.10418348 SN - 978-0-9568086-9-1 PB - IEEE CY - Piscataway 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 - CHAP A1 - Ahuir-Torres, Juan Ignacio A1 - Bhogaraju, Sri Krishna A1 - West, Geoff A1 - Elger, Gordon A1 - Kotadia, Hiren R. T1 - Understanding Cu Sintering and Its Role on Corrosion Behaviour for High-Temperature Microelectronic Application T2 - 2023 24th European Microelectronics and Packaging Conference & Exhibition (EMPC) UR - https://doi.org/10.23919/EMPC55870.2023.10418365 Y1 - 2024 UR - https://doi.org/10.23919/EMPC55870.2023.10418365 SN - 978-0-9568086-9-1 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Elger, Gordon A1 - Bhogaraju, Sri Krishna A1 - Schneider-Ramelow, Martin T1 - Hybrid Cu sinter paste for low temperature bonding of bare semiconductors JF - Materials Letters N2 - A novel hybrid copper paste was developed for low temperature sintering of bare semiconductors. Cu(II) formate (Cu(for)) is complexed in amino-2-propanol (A2P) and added to a paste of etched brass micro flakes. A two-step sintering process is applied: The paste is printed and dried at 120 °C under formic acid (FA) enriched N2 atmosphere (FAN2) for 5 min. Afterwards, bare semiconductors are placed and sintered at 250 °C for 5 min applying a bonding pressure of 20 MPa/10 MPa. By the thermal decomposition of the Cu(for) atomic Cu is released and forms in-situ Cu-nanoparticles. An interconnect is realized with shear strength >100 MPa. UR - https://doi.org/10.1016/j.matlet.2024.136973 Y1 - 2024 UR - https://doi.org/10.1016/j.matlet.2024.136973 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-49138 SN - 1873-4979 VL - 2024 IS - 372 PB - Elsevier CY - New York ER - TY - CHAP A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Elger, Gordon A1 - Beyerer, Jürgen T1 - FlexSense: Flexible Infrastructure Sensors for Traffic Perception T2 - 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC57777.2023.10422616 Y1 - 2024 UR - https://doi.org/10.1109/ITSC57777.2023.10422616 SN - 979-8-3503-9946-2 SP - 3810 EP - 3816 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Han, Longfei A1 - Xu, Qiuyu A1 - Kefferpütz, Klaus A1 - Lu, Ying A1 - Elger, Gordon A1 - Beyerer, Jürgen T1 - Scalable Radar-based Roadside Perception: Self-localization and Occupancy Heat Map for Traffic Analysis T2 - 2024 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/iv55156.2024.10588397 Y1 - 2024 UR - https://doi.org/10.1109/iv55156.2024.10588397 SN - 979-8-3503-4881-1 SP - 1651 EP - 1657 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Olcay, Ertug A1 - Meeß, Henri A1 - Elger, Gordon T1 - Dynamic Obstacle Avoidance for UAVs using MPC and GP-Based Motion Forecast T2 - 2024 European Control Conference (ECC) UR - https://doi.org/10.23919/ECC64448.2024.10591083 Y1 - 2024 UR - https://doi.org/10.23919/ECC64448.2024.10591083 SN - 978-3-9071-4410-7 SP - 1024 EP - 1031 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Paret, Paul A1 - Bhogaraju, Sri Krishna A1 - Busse, Dirk A1 - Dahlbüdding, Alexander A1 - Elger, Gordon A1 - Narumanchi, Sreekant T1 - Thermomechanical Degradation of Sintered Copper under High-Temperature Thermal Shock T2 - Proceedings: IEEE 74th Electronic Components and Technology Conference, ECTC 2024 UR - https://doi.org/10.1109/ECTC51529.2024.00196 Y1 - 2024 UR - https://doi.org/10.1109/ECTC51529.2024.00196 SN - 979-8-3503-7598-5 SP - 1219 EP - 1224 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Steinberger, Fabian A1 - Mohan, Nihesh A1 - Rämer, Olaf A1 - Elger, Gordon T1 - Low temperature die-attach bonding using copper particle free inks T2 - 2024 IEEE 10th Electronics System-Integration Technology Conference (ESTC), Proceedings UR - https://doi.org/10.1109/ESTC60143.2024.10712150 Y1 - 2024 UR - https://doi.org/10.1109/ESTC60143.2024.10712150 SN - 979-8-3503-9036-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Agrawal, Shiva A1 - Song, Rui A1 - Kohli, Akhil A1 - Korb, Andreas A1 - Andre, Maximilian A1 - Holzinger, Erik A1 - Elger, Gordon ED - Ploeg, Jeroen ED - Helfert, Markus ED - Berns, Karsten ED - Gusikhin, Oleg T1 - Concept of Smart Infrastructure for Connected Vehicle Assist and Traffic Flow Optimization T2 - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems N2 - The smart infrastructure units can play a vital role to develop smart cities of the future and in assisting automated vehicles on the road by providing extended perception and timely warnings to avoid accidents. This paper focuses on the development of such an infrastructure unit, that is specifically designed for a pedestrian crossing junction. It can control traffic lights at the junction by real-time environment perception through its sensors and can optimize the flow of vehicles and passing vulnerable road users (VRUs). Moreover, it can assist on-road vehicles by providing real-time information and critical warnings via a v2x module. This paper further describes different use-cases of the work, all major hardware components involved in the development of smart infrastructure unit, referred to as an edge, different sensor fusion approaches using the camera, radar, and lidar mounted on the edge for environment perception, various modes of communication including v2x, system design UR - https://doi.org/10.5220/0011068800003191 KW - Road Side Unit (RSU) KW - Smart Infrastructure KW - Radar KW - LiDAR KW - Camera KW - Perception KW - Sensor Data Fusion KW - Vehicle-to-everything (V2X) KW - Communication KW - Simulation KW - ITS Y1 - 2022 UR - https://doi.org/10.5220/0011068800003191 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-30926 SN - 978-989-758-573-9 SN - 2184-495X SP - 360 EP - 367 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Streck, Egor A1 - Herschel, Reinhold A1 - Wallrath, Patrick A1 - Sunderam, M. A1 - Elger, Gordon ED - Prasad, Venkatesha ED - Pesch, Dirk ED - Ansari, Nirwan ED - Benavente-Peces, César T1 - Comparison of Two Different Radar Concepts for Pedestrian Protection on Bus Stops T2 - Proceedings of the 11th International Conference on Sensor Networks N2 - This paper presents the joint work from the “HORIS” project, with a focus on pedestrian detection at bus-stops by radar sensors mounted in the infrastructure to support future autonomous driving and protecting pedestrians in critical situations. Two sensor systems are investigated and evaluated. The first based on single radar sensor phase-sensitive raw data analysis and the second based on sensor data fusion of cluster data with two radar sensors using neural networks to predict the position of pedestrians. UR - https://doi.org/10.5220/0010777100003118 KW - Sensor Data Fusion KW - Radar Sensor KW - Multiple-Sensor Systems KW - Machine Learning Y1 - 2022 UR - https://doi.org/10.5220/0010777100003118 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-30953 SN - 978-989-758-551-7 SN - 2184-4380 SP - 89 EP - 96 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Conti, Fosca A1 - Lux, Kerstin A1 - Bhogaraju, Sri Krishna A1 - Liu, E A1 - Lenz, Christoph A1 - Seitz, Roland A1 - Elger, Gordon ED - Baldini, Francesco ED - Homola, Jiri ED - Lieberman, Robert A. T1 - Raman spectroscopy to investigate gallium nitride light emitting diodes after assembling onto copper substrates T2 - Optical Sensors 2021 UR - https://doi.org/10.1117/12.2591947 Y1 - 2021 UR - https://doi.org/10.1117/12.2591947 SN - 978-1-5106-4379-6 N1 - Poster + Paper PB - SPIE CY - Bellingham ER - TY - JOUR A1 - Bhanderi, Savankumar A1 - Agrawal, Shiva A1 - Elger, Gordon T1 - Deep segmentation of 3+1D radar point cloud for real-time roadside traffic user detection JF - Scientific Reports N2 - Smart cities rely on intelligent infrastructure to enhance road safety, optimize traffic flow, and enable vehicle-to-infrastructure (V2I) communication. A key component of such infrastructure is an efficient and real-time perception system that accurately detects diverse traffic participants. Among various sensing modalities, automotive radar is one of the best choices due to its robust performance in adverse weather and low-light conditions. However, due to low spatial resolution, traditional clustering-based approaches for radar object detection often struggle with vulnerable road user detection and nearby object separation. Hence, this paper proposes a deep learning-based D radar point cloud clustering methodology tailored for smart infrastructure-based perception applications. This approach first performs semantic segmentation of the radar point cloud, followed by instance segmentation to generate well-formed clusters with class labels using a deep neural network. It also detects single-point objects that conventional methods often miss. The described approach is developed and experimented using a smart infrastructure-based sensor setup and it performs segmentation of the point cloud in real-time. Experimental results demonstrate 95.35% F1-macro score for semantic segmentation and 91.03% mean average precision (mAP) at an intersection over union (IoU) threshold of 0.5 for instance segmentation. Further, the complete pipeline operates at 43.61 frames per second with a memory requirement of less than 0.7 MB on the edge device (Nvidia Jetson AGX Orin). UR - https://doi.org/10.1038/s41598-025-23019-6 Y1 - 2025 UR - https://doi.org/10.1038/s41598-025-23019-6 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63458 SN - 2045-2322 VL - 15 PB - Springer Nature CY - London ER - TY - INPR A1 - Bhanderi, Savankumar A1 - Agrawal, Shiva A1 - Elger, Gordon T1 - Deep Segmentation of 3+1D Radar Point Cloud for Real-Time Roadside Traffic User Detection T2 - Research Square N2 - Smart cities rely on intelligent infrastructure to enhance road safety, optimize traffic flow, and enable vehicle-to-infrastructure (V2I) communication. A key component of such infrastructure is an efficient and real-time perception system that accurately detects diverse traffic participants. Among various sensing modalities, automotive radar is one of the best choices due to its robust performance in adverse weather and low-light conditions. However, due to low spatial resolution, traditional clustering-based approaches for radar object detection often struggle with vulnerable road user detection and nearby object separation. Hence, this paper proposes a deep learning-based 3+1D radar point cloud clustering methodology tailored for smart infrastructure-based perception applications. This approach first performs semantic segmentation of the radar point cloud, followed by instance segmentation to generate well-formed clusters with class labels using a deep neural network. It also detects single-point objects that conventional methods often miss. The described approach is developed and experimented using a smart infrastructure-based sensor setup and it performs segmentation of the point cloud in real-time. Experimental results demonstrate 95.35% F1-macro score for semantic segmentation and 91.03% mean average precision (mAP) at an intersection over union (IoU) threshold of 0.5 for instance segmentation. Further, the complete pipeline operates at 43.61 frames per second with a memory requirement of less than 0.7 MB on the edge device (Nvidia Jetson AGX Orin). UR - https://doi.org/10.21203/rs.3.rs-7222130/v1 Y1 - 2025 UR - https://doi.org/10.21203/rs.3.rs-7222130/v1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61996 SN - 2693-5015 PB - Research Square CY - Durham ER - TY - JOUR A1 - Kleiner, Jan A1 - Heider, Alexander A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal behavior of intelligent automotive lithium-ion batteries: Experimental study with switchable cells and reconfigurable modules JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2021.103274 KW - lithium-ion KW - intelligent battery KW - switchable cell KW - reconfiguration KW - smart cell KW - thermal management Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.103274 SN - 2352-1538 VL - 2021 IS - 44, Part A PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kleiner, Jan A1 - Lechermann, Lorenz A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal behavior of intelligent automotive lithium-ion batteries BT - operating strategies for adaptive thermal balancing by reconfiguration JF - Journal of energy storage UR - https://doi.org/10.1016/j.est.2021.102686 KW - intelligent battery KW - thermal management KW - balancing KW - cell-to-cell variations KW - inhomogeneities KW - thermal modeling Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.102686 SN - 2352-1538 VL - 2021 IS - 40 PB - Elsevier CY - Amsterdam ER -