@article{KleinerKomsiyskaElgeretal.2019, author = {Kleiner, Jan and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal modelling of a prismatic lithium-ion cell in a battery electric vehicle environment}, volume = {13}, pages = {62}, journal = {Energies}, subtitle = {influences of the experimental validation setup}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en13010062}, year = {2019}, abstract = {In electric vehicles with lithium-ion battery systems, the temperature of the battery cells has a great impact on performance, safety, and lifetime. Therefore, developing thermal models of lithium-ion batteries to predict and investigate the temperature development and its impact is crucial. Commonly, models are validated with experimental data to ensure correct model behaviour. However, influences of experimental setups or comprehensive validation concepts are often not considered, especially for the use case of prismatic cells in a battery electric vehicle. In this work, a 3D electro-thermal model is developed and experimentally validated to predict the cell's temperature behaviour for a single prismatic cell under battery electric vehicle (BEV) boundary conditions. One focus is on the development of a single cell's experimental setup and the investigation of the commonly neglected influences of an experimental setup on the cell's thermal behaviour. Furthermore, a detailed validation is performed for the laboratory BEV scenario for spatially resolved temperatures and heat generation. For validation, static and dynamic loads are considered as well as the detected experimental influences. The validated model is used to predict the temperature within the cell in the BEV application for constant current and Worldwide harmonized Light vehicles Test Procedure (WLTP) load profile.}, language = {en} } @article{LiuContiBhogarajuetal.2020, author = {Liu, E and Conti, Fosca and Bhogaraju, Sri Krishna and Signorini, Raffaella and Pedron, Danilo and Wunderle, Bernhard and Elger, Gordon}, title = {Thermomechanical stress in GaN-LEDs soldered onto Cu substrates studied using finite element method and Raman spectroscopy}, volume = {51}, journal = {Journal of Raman Spectroscopy}, number = {10}, publisher = {Wiley}, address = {Chichester}, issn = {1097-4555}, doi = {https://doi.org/10.1002/jrs.5947}, pages = {2083 -- 2094}, year = {2020}, abstract = {Local thermomechanical stress can cause failures in semiconductor packages during long-time operation under harsh environmental conditions. This study helps to explain the packaging-induced stress in blue GaN-LEDs soldered onto copper substrates using AuSn alloy as lead-free interconnect material. Based on the finite element method, a virtual prototype is developed to simulate the thermomechanical behavior and stress in the LED and in the complete LED/AuSn/Cu assembly considering plastic and viscoplastic strain. The investigations were performed by varying the temperature between -50°C and 180°C. To validate the model, the simulation results are compared to experimental data collected with Raman spectroscopy. Studies of the urn:x-wiley:03770486:media:jrs5947:jrs5947-math-0003 phonon mode of GaN semiconductor are elaborated to understand the induced thermomechanical stress. The model enables evaluation of the stress in the interfaces of the assembly, which otherwise cannot be accessed by measurements. It serves to predict how assemblies would perform, before committing resources to build a physical prototype.}, language = {en} } @inproceedings{AgrawalElger2021, author = {Agrawal, Shiva and Elger, Gordon}, title = {Concept of infrastructure based environment perception for IN2Lab test field for automated driving}, booktitle = {2021 IEEE International Smart Cities Conference (ISC2)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-4919-9}, issn = {2687-8860}, doi = {https://doi.org/10.1109/ISC253183.2021.9562894}, year = {2021}, language = {en} } @inproceedings{LiuContiBhogarajuetal.2021, author = {Liu, E and Conti, Fosca and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Simulations and experiments to analyze stress phenomena in soldered and sintered interconnections between silicon nitride chips and copper substrates}, booktitle = {2021 22nd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-1373-2}, doi = {https://doi.org/10.1109/EuroSimE52062.2021.9410869}, year = {2021}, language = {en} } @article{SchmidBhogarajuLiuetal.2020, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Liu, E and Elger, Gordon}, title = {Comparison of Nondestructive Testing Methods for Solder, Sinter, and Adhesive Interconnects in Power and Opto-Electronics}, volume = {10}, pages = {8516}, journal = {Applied Sciences}, number = {23}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {https://doi.org/10.3390/app10238516}, year = {2020}, abstract = {Reliability is one of the major requirements for power and opto-electronic devices across all segments. High operation temperature and/or high thermomechanical stress cause defects and degradation of materials and interconnects, which may lead to malfunctions with costly or even life-threatening consequences. To avoid or at least reduce failures, nondestructive testing (NDT) methods are common within development and production of power and opto-electronics. Currently, the dominating NDT methods are X-ray, scanning acoustic microscopy (SAM), and transient thermal analysis (TTA). However, they have different strengths and weaknesses with respect to materials and mechanical designs. This paper compares these NDT methods for different interconnect technologies, i.e., reflow soldering, adhesive, and sintered interconnection. While X-ray provided adequate results for soldered interfaces, inspection of adhesives and sintered interconnects was not possible. With SAM, evaluation of adhesives and sintered interconnects was also feasible, but quality depended strongly on the sample under test. TTA enabled sufficiently detailed results for all the interconnect applications. Automated TTA equipment, as the in-house developed tester used within this investigation, enabled measurement times compatible with SAM and X-ray. In the investigations, all methods revealed their pros and cons, and their selection has to depend on the sample under tests and the required analysis depth and data details. In the paper, guidelines are formulated for an appropriate decision on the NDT method depending on sample and requirements.}, language = {en} } @unpublished{HanXuKefferpuetzetal.2024, author = {Han, Longfei and Xu, Qiuyu and Kefferp{\"u}tz, Klaus and Elger, Gordon and Beyerer, J{\"u}rgen}, title = {Applying Extended Object Tracking for Self-Localization of Roadside Radar Sensors}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2407.03084}, year = {2024}, abstract = {Intelligent Transportation Systems (ITS) can benefit from roadside 4D mmWave radar sensors for large-scale traffic monitoring due to their weatherproof functionality, long sensing range and low manufacturing cost. However, the localization method using external measurement devices has limitations in urban environments. Furthermore, if the sensor mount exhibits changes due to environmental influences, they cannot be corrected when the measurement is performed only during the installation. In this paper, we propose self-localization of roadside radar data using Extended Object Tracking (EOT). The method analyses both the tracked trajectories of the vehicles observed by the sensor and the aerial laser scan of city streets, assigns labels of driving behaviors such as "straight ahead", "left turn", "right turn" to trajectory sections and road segments, and performs Semantic Iterative Closest Points (SICP) algorithm to register the point cloud. The method exploits the result from a down stream task -- object tracking -- for localization. We demonstrate high accuracy in the sub-meter range along with very low orientation error. The method also shows good data efficiency. The evaluation is done in both simulation and real-world tests.}, language = {en} } @inproceedings{MeessGernerHeinetal.2022, author = {Meess, Henri and Gerner, Jeremias and Hein, Daniel and Schmidtner, Stefanie and Elger, Gordon}, title = {Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation}, booktitle = {AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems}, publisher = {International Foundation for Autonomous Agents and Multiagent Systems}, address = {Richland}, isbn = {978-1-4503-9213-6}, doi = {https://dl.acm.org/doi/10.5555/3535850.3536081}, pages = {1699 -- 1701}, year = {2022}, language = {en} } @inproceedings{AgrawalSongDoychevaetal.2023, author = {Agrawal, Shiva and Song, Rui and Doycheva, Kristina and Knoll, Alois and Elger, Gordon}, title = {Intelligent Roadside Infrastructure for Connected Mobility}, booktitle = {Smart Cities, Green Technologies, and Intelligent Transport Systems: 11th International Conference, SMARTGREENS 2022 and 8th International Conference, VEHITS 2022: Revised Selected Papers}, editor = {Klein, Cornel and Jarke, Matthias and Ploeg, Jeroen and Helfert, Markus and Berns, Karsten and Gusikhin, Oleg}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-37470-8}, issn = {1865-0937}, doi = {https://doi.org/10.1007/978-3-031-37470-8_6}, pages = {134 -- 157}, year = {2023}, language = {en} } @inproceedings{AgrawalBhanderiAmanagietal.2023, author = {Agrawal, Shiva and Bhanderi, Savankumar and Amanagi, Sumit and Doycheva, Kristina and Elger, Gordon}, title = {Instance Segmentation and Detection of Children to Safeguard Vulnerable Traffic User by Infrastructure}, booktitle = {Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems}, editor = {Vinel, Alexey and Ploeg, Jeroen and Berns, Karsten and Gusikhin, Oleg}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-652-1}, issn = {2184-495X}, doi = {https://doi.org/10.5220/0011825400003479}, pages = {206 -- 214}, year = {2023}, abstract = {Cameras mounted on intelligent roadside infrastructure units and vehicles can detect humans on the road using state-of-the-art perception algorithms, but these algorithms are presently not trained to distinguish between human and adult. However, this is a crucial requirement from a safety perspective because a child may not follow all the traffic rules, particularly while crossing the road. Moreover, a child may stop or may start playing on the road. In such situations, the separation of a child from an adult is necessary. The work in this paper targets to solve this problem by applying a transfer-learning-based neural network approach to classify child and adult separately in camera images. The described work is comprised of image data collection, data annotation, transfer learning-based model development, and evaluation. For the work, Mask-RCNN (region-based convolutional neural network) with different backbone architectures and two different baselines are investigated and the perception precision of the architectures after transfer-learning is compared. The results reveal that the best performing trained model is able to detect and classify children and adults separately in different road scenarios with segmentation mask AP (average precision) of 85\% and bounding box AP of 92\%.}, language = {en} } @article{AgrawalBhanderiElger2025, author = {Agrawal, Shiva and Bhanderi, Savankumar and Elger, Gordon}, title = {Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection}, volume = {25}, pages = {3422}, journal = {Sensors}, number = {11}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {https://doi.org/10.3390/s25113422}, year = {2025}, abstract = {Mono RGB cameras and automotive radar sensors provide a complementary information set that makes them excellent candidates for sensor data fusion to obtain robust traffic user detection. This has been widely used in the vehicle domain and recently introduced in roadside-mounted smart infrastructure-based road user detection. However, the performance of the most commonly used late fusion methods often degrades when the camera fails to detect road users in adverse environmental conditions. The solution is to fuse the data using deep neural networks at the early stage of the fusion pipeline to use the complete data provided by both sensors. Research has been carried out in this area, but is limited to vehicle-based sensor setups. Hence, this work proposes a novel deep neural network to jointly fuse RGB mono-camera images and 3D automotive radar point cloud data to obtain enhanced traffic user detection for the roadside-mounted smart infrastructure setup. Projected radar points are first used to generate anchors in image regions with a high likelihood of road users, including areas not visible to the camera. These anchors guide the prediction of 2D bounding boxes, object categories, and confidence scores. Valid detections are then used to segment radar points by instance, and the results are post-processed to produce final road user detections in the ground plane. The trained model is evaluated for different light and weather conditions using ground truth data from a lidar sensor. It provides a precision of 92\%, recall of 78\%, and F1-score of 85\%. The proposed deep fusion methodology has 33\%, 6\%, and 21\% absolute improvement in precision, recall, and F1-score, respectively, compared to object-level spatial fusion output.}, language = {en} } @article{DaRosaZanattaCarvalhoLustosadaCostaAntreichetal.2020, author = {Da Rosa Zanatta, Mateus and Carvalho Lustosa da Costa, Joao Paulo and Antreich, Felix and Haardt, Martin and Elger, Gordon and Lopes de Mendon{\c{c}}a, F{\´a}bio L{\´u}cio and de Sousa Junior, Rafael Tim{\´o}teo}, title = {Tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios}, volume = {8}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2020.3024597}, pages = {174931 -- 174942}, year = {2020}, abstract = {Global Navigation Satellite Systems (GNSS) are crucial for applications that demand very accurate positioning. Tensor-based time-delay estimation methods, such as CPD-GEVD, DoA/KRF, and SECSI, combined with the GPS3 L1C signal, are capable of, significantly, mitigating the positioning degradation caused by multipath components. However, even though these schemes require an estimated model order, they assume that the number of multipath components is constant. In GNSS applications, the number of multipath components is time-varying in dynamic scenarios. Thus, in this paper, we propose a tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios. Our proposed approach exploits the estimates of the model order for each slice by grouping the data tensor slices into sub-tensors to provide high accuracy factor decomposition. We further enhance the proposed approach by incorporating the tensor-based Multiple Denoising (MuDe).}, language = {en} } @article{MohanAhuirTorresKotadiaetal.2025, author = {Mohan, Nihesh and Ahuir-Torres, Juan Ignacio and Kotadia, Hiren R. and Elger, Gordon}, title = {Laser sintering of Cu particle-free inks for high-performance printed electronics}, volume = {9}, pages = {18}, journal = {npj Flexible Electronics}, number = {1}, publisher = {Springer}, address = {London}, issn = {2397-4621}, doi = {https://doi.org/10.1038/s41528-025-00389-5}, year = {2025}, abstract = {This study investigates laser sintering of Cu particle-free ink (Cu formate tetrahydrate—amino-2-propanol complex) as an alternative to conventional sintering in an oven (under inert/reducing atmosphere). Utilizing benefits of high-speed localized heating using laser, substrate damage can be prevented for low-melting substrates such as Polyethylene Terephthalate (PET). Firstly, a suitable sintering process window is achieved based on energy density for two different flexible polymeric susbtrates: Polyimide and PET using different laser parameters (laser power, scan rate and spot diameter). Subsequently, characterization of laser sintered traces are also made using different laser optic profiles (Gaussian and top hat). Different methodologies for fabrication of metallized Cu layer were also demonstrated. A very low bulk resistivity of 3.24 µΩcm (1.87 times of bulk Cu) was achieved on trace thickness of 0.85 ± 0.15 µm exhibiting good adherence to polymeric substrates. A promising fabrication process of low-cost and reliable flexible printed electronic devices is demonstrated.}, language = {en} } @article{TheisslerPerezVelazquezKettelgerdesetal.2021, author = {Theissler, Andreas and P{\´e}rez-Vel{\´a}zquez, Judith and Kettelgerdes, Marcel and Elger, Gordon}, title = {Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry}, volume = {2021}, pages = {107864}, journal = {Reliability Engineering \& System Safety}, number = {215}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0951-8320}, doi = {https://doi.org/10.1016/j.ress.2021.107864}, year = {2021}, abstract = {Recent developments in maintenance modelling fuelled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive industry, ensuring the functional safety over the product life cycle while limiting maintenance costs has become a major challenge. One crucial approach to achieve this, is predictive maintenance (PdM). Since modern vehicles come with an enormous amount of operating data, ML is an ideal candidate for PdM. While PdM and ML for automotive systems have both been covered in numerous review papers, there is no current survey on ML-based PdM for automotive systems. The number of publications in this field is increasing — underlining the need for such a survey. Consequently, we survey and categorize papers and analyse them from an application and ML perspective. Following that, we identify open challenges and discuss possible research directions. We conclude that (a) publicly available data would lead to a boost in research activities, (b) the majority of papers rely on supervised methods requiring labelled data, (c) combining multiple data sources can improve accuracies, (d) the use of deep learning methods will further increase but requires efficient and interpretable methods and the availability of large amounts of (labelled) data.}, language = {en} } @article{AgrawalBhanderiElger2024, author = {Agrawal, Shiva and Bhanderi, Savankumar and Elger, Gordon}, title = {Semi-Automatic Annotation of 3D Radar and Camera for Smart Infrastructure-Based Perception}, volume = {12}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2024.3373310}, pages = {34325 -- 34341}, year = {2024}, abstract = {Environment perception using camera, radar, and/or lidar sensors has significantly improved in the last few years because of deep learning-based methods. However, a large group of these methods fall into the category of supervised learning, which requires a considerable amount of annotated data. Due to uncertainties in multi-sensor data, automating the data labeling process is extremely challenging; hence, it is performed manually to a large extent. Even though full automation of such a process is difficult, semiautomation can be a significant step to ease this process. However, the available work in this regard is still very limited; hence, in this paper, a novel semi-automatic annotation methodology is developed for labeling RGB camera images and 3D automotive radar point cloud data using a smart infrastructure-based sensor setup. This paper also describes a new method for 3D radar background subtraction to remove clutter and a new object category, GROUP, for radar-based object detection for closely located vulnerable road users. To validate the work, a dataset named INFRA-3DRC is created using this methodology, where 75\% of the labels are automatically generated. In addition, a radar cluster classifier and an image classifier are developed, trained, and tested on this dataset, achieving accuracy of 98.26\% and 94.86\%, respectively. The dataset and Python scripts are available at https://fraunhoferivi.github.io/INFRA-3DRC-Dataset/.}, language = {en} } @article{MohanSteinbergerWaechteretal.2025, author = {Mohan, Nihesh and Steinberger, Fabian and W{\"a}chter, Sonja and Erdogan, H{\"u}seyin and Elger, Gordon}, title = {Additive Manufacturing for Automotive Radar Sensors Using Copper Inks and Pastes}, volume = {15}, pages = {2676}, journal = {Applied Sciences}, number = {5}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {https://doi.org/10.3390/app15052676}, year = {2025}, abstract = {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.}, language = {en} } @inproceedings{KettelgerdesBoehmElger2021, author = {Kettelgerdes, Marcel and B{\"o}hm, Lena and Elger, Gordon}, title = {Correlating Intrinsic Parameters and Sharpness for Condition Monitoring of Automotive Imaging Sensors}, booktitle = {2021 5th International Conference on System Reliability and Safety (ICSRS)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-0049-7}, doi = {https://doi.org/10.1109/ICSRS53853.2021.9660665}, pages = {298 -- 306}, year = {2021}, language = {en} } @inproceedings{TavakolibastiMeszmerBoettgeretal.2021, author = {Tavakolibasti, M. and Meszmer, P. and B{\"o}ttger, Gunnar and Kettelgerdes, Marcel and Elger, Gordon and Erdogan, H{\"u}seyin and Seshaditya, A. and Wunderle, Bernhard}, title = {Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR}, booktitle = {2021 22nd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-1373-2}, doi = {https://doi.org/10.1109/EuroSimE52062.2021.9410831}, year = {2021}, language = {en} } @inproceedings{PascucciContiBhogarajuetal.2021, author = {Pascucci, Jacopo and Conti, Fosca and Bhogaraju, Sri Krishna and Signorini, Raffaella and Liu, E and Pedron, Danilo and Elger, Gordon}, title = {Micro-Raman to detect stress phenomena in Si-chips bonded onto Cu substrates}, booktitle = {Integrated Optics: Design, Devices, Systems and Applications VI}, editor = {Cheben, Pavel and Čtyrok{\´y}, Jiř{\´i} and Molina-Fern{\´a}ndez, I{\~n}igo}, publisher = {SPIE}, address = {Bellingham}, isbn = {978-1-5106-4385-7}, doi = {https://doi.org/10.1117/12.2576414}, year = {2021}, language = {en} } @inproceedings{BhogarajuSchmidHufnageletal.2021, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Hufnagel, Elias and Conti, Fosca and Kotadia, Hiren R. and Elger, Gordon}, title = {Low temperature and low pressure die-attach bonding of high power light emitting diodes with self reducing copper complex paste}, booktitle = {IEEE 71st Electronic Components and Technology Conference ECTC 2021, Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-4097-4}, doi = {https://doi.org/10.1109/ECTC32696.2021.00094}, pages = {526 -- 531}, year = {2021}, language = {en} } @inproceedings{SchmidBhogarajuElger2021, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Characterization of copper sintered interconnects by transient thermal analysis}, booktitle = {2021 International Conference on Electronics Packaging (ICEP 2021)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-4-9911-9111-4}, doi = {https://doi.org/10.23919/ICEP51988.2021.9451966}, pages = {71 -- 72}, year = {2021}, language = {en} } @inproceedings{KleinerHeiderHanzletal.2020, author = {Kleiner, Jan and Heider, Alexander and Hanzl, Christian and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of an intelligent li-ion cell under vehicle conditions}, booktitle = {Proceedings: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-5414-5}, issn = {2577-1647}, doi = {https://doi.org/10.1109/IECON43393.2020.9254336}, pages = {2081 -- 2086}, year = {2020}, language = {en} } @inproceedings{ContiLiuBhogarajuetal.2020, author = {Conti, Fosca and Liu, E and Bhogaraju, Sri Krishna and Wunderle, Bernhard and Elger, Gordon}, title = {Finite Element simulations and Raman measurements to investigate thermomechanical stress in GaN-LEDs}, booktitle = {2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6293-5}, doi = {https://doi.org/10.1109/ESTC48849.2020.9229843}, year = {2020}, language = {en} } @inproceedings{BhogarajuContiElger2020, author = {Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Copper die bonding using copper formate based pastes with α-terpineol, amino-2-propanol and hexylamine as binders}, booktitle = {2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6293-5}, doi = {https://doi.org/10.1109/ESTC48849.2020.9229801}, year = {2020}, language = {en} } @inproceedings{KeimTetzlaffElger2020, author = {Keim, Simon and Tetzlaff, Ulrich and Elger, Gordon}, title = {The influence of different-sized Ni micro- and nanopowders on the processing and microstructural properties of Sn-Ag-Cu-solder with low Ag content}, booktitle = {Proceedings: IEEE 70th Electronic Components and Technology Conference, ECTC 2020}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6180-8}, issn = {2377-5726}, doi = {https://doi.org/10.1109/ECTC32862.2020.00312}, pages = {2005 -- 2012}, year = {2020}, language = {en} } @inproceedings{ContiLiuBhogarajuetal.2021, author = {Conti, Fosca and Liu, E and Bhogaraju, Sri Krishna and Lenz, Christoph and Seitz, Roland and Elger, Gordon}, title = {Stress evaluations of silicon nitride chips bonded onto copper substrates via SAC soldering, AuSn soldering, and copper sintering}, booktitle = {2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-7643-7}, doi = {https://doi.org/10.1109/THERMINIC49743.2020.9420523}, pages = {204 -- 208}, year = {2021}, language = {en} } @inproceedings{SchmidBhogarajuRiedeletal.2021, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Riedel, Andreas and Elger, Gordon}, title = {Development of an in-line capable transient thermal analysis equipment for a power module with five half bridges}, booktitle = {2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-7643-7}, doi = {https://doi.org/10.1109/THERMINIC49743.2020.9420493}, pages = {268 -- 273}, year = {2021}, language = {en} } @inproceedings{LiuSchmidBhogarajuetal.2021, author = {Liu, E and Schmid, Maximilian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Advanced location resolved transient thermal analysis}, booktitle = {2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-7643-7}, doi = {https://doi.org/10.1109/THERMINIC49743.2020.9420538}, pages = {191 -- 196}, year = {2021}, language = {en} } @article{MokhtariContiSacconetal.2021, author = {Mokhtari, Omid and Conti, Fosca and Saccon, Rodolfo and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Formic acid and formate salts for chemical vapor deposition of copper on glass substrates at atmospheric pressure}, volume = {45}, journal = {New Journal of Chemistry}, number = {43}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/D1NJ02476K}, pages = {20133 -- 20139}, year = {2021}, language = {en} } @article{BhogarajuKotadiaContietal.2021, author = {Bhogaraju, Sri Krishna and Kotadia, Hiren R. and Conti, Fosca and Mauser, Armin and Rubenbauer, Thomas and Bruetting, Robert and Schneider-Ramelow, Martin and Elger, Gordon}, title = {Die-attach bonding with etched micro brass metal pigment flakes for high-power electronics packaging}, volume = {3}, journal = {ACS Applied Electronic Materials}, number = {10}, publisher = {ACS Publications}, address = {Washington}, issn = {2637-6113}, doi = {https://doi.org/10.1021/acsaelm.1c00721}, pages = {4587 -- 4603}, year = {2021}, language = {en} } @article{KleinerSinghSchmidetal.2020, author = {Kleiner, Jan and Singh, Randeep and Schmid, Michael and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Influence of heat pipe assisted terminal cooling on the thermal behavior of a large prismatic lithium-ion cell during fast charging in electric vehicles}, volume = {2021}, pages = {116328}, journal = {Applied Thermal Engineering}, number = {188}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1359-4311}, doi = {https://doi.org/10.1016/j.applthermaleng.2020.116328}, year = {2020}, language = {en} } @article{SchmidBhogarajuHanssetal.2021, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Hanss, Alexander and Elger, Gordon}, title = {A new noise-suppression algorithm for transient thermal analysis in semiconductors over pulse superposition}, volume = {70}, pages = {6500409}, journal = {IEEE Transactions on Instrumentation and Measurement}, publisher = {IEEE}, address = {New York}, issn = {0018-9456}, doi = {https://doi.org/10.1109/TIM.2020.3011818}, year = {2021}, language = {en} } @article{BhogarajuMokhtariContietal.2020, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Conti, Fosca and Elger, Gordon}, title = {Die-attach bonding for high temperature applications using thermal decomposition of copper(II) formate with polyethylene glycol}, volume = {2020}, journal = {Scripta Materialia}, number = {182}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1359-6462}, doi = {https://doi.org/10.1016/j.scriptamat.2020.02.045}, pages = {74 -- 80}, year = {2020}, language = {en} } @article{BhogarajuContiKotadiaetal.2020, author = {Bhogaraju, Sri Krishna and Conti, Fosca and Kotadia, Hiren R. and Keim, Simon and Tetzlaff, Ulrich and Elger, Gordon}, title = {Novel approach to copper sintering using surface enhanced brass micro flakes for microelectronics packaging}, volume = {2020}, pages = {156043}, journal = {Journal of Alloys and Compounds}, number = {844}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1873-4669}, doi = {https://doi.org/10.1016/j.jallcom.2020.156043}, year = {2020}, language = {en} } @article{MokhtariContiBhogarajuetal.2019, author = {Mokhtari, Omid and Conti, Fosca and Bhogaraju, Sri Krishna and Meier, Markus and Schweigart, Helmut and Tetzlaff, Ulrich and Elger, Gordon}, title = {Characterization of tin-oxides and tin-formate crystals obtained from SnAgCu solder alloy under formic acid vapor}, volume = {43}, journal = {New Journal of Chemistry}, number = {26}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/C9NJ02135C}, pages = {10227 -- 10231}, year = {2019}, language = {en} } @inproceedings{KleinerKomsiyskaElgeretal.2019, author = {Kleiner, Jan and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Modelling of 3D temperature behavior of prismatic lithium-ion cell with focus on experimental validation under battery electric vehicle conditions}, booktitle = {2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-2078-2}, doi = {https://doi.org/10.1109/THERMINIC.2019.8923604}, year = {2019}, language = {en} } @inproceedings{ZippeliusHanssLiuetal.2020, author = {Zippelius, Andreas and Hanss, Alexander and Liu, E and Schmid, Maximilian and P{\´e}rez-Vel{\´a}zquez, Judith and Elger, Gordon}, title = {Comparing prediction methods for LED failure measured with Transient Thermal Analysis}, booktitle = {2020 21st International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6049-8}, doi = {https://doi.org/10.1109/EuroSimE48426.2020.9152657}, year = {2020}, language = {en} } @inproceedings{BhogarajuContiSchmidetal.2020, author = {Bhogaraju, Sri Krishna and Conti, Fosca and Schmid, Maximilian and Meier, Markus and Schweigart, Helmut and Elger, Gordon}, title = {Development of sinter paste with surface modified copper alloy particles for die-attach bonding}, booktitle = {ETG-Fachbericht 161, CIPS 2020, 11th International Conference on Integrated Power Electronics Systems}, publisher = {VDE Verlag}, address = {Berlin}, isbn = {978-3-8007-5226-3}, url = {https://www.vde-verlag.de/proceedings-de/455225100.html}, pages = {582 -- 587}, year = {2020}, language = {en} } @inproceedings{HanssLiuAbdullahetal.2019, author = {Hanss, Alexander and Liu, E and Abdullah, Muhammad Rizwan and Elger, Gordon}, title = {Failure Identification in LED packages by Transient Thermal Analysis and Calibrated FE Models}, booktitle = {2019 20th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-8040-7}, doi = {https://doi.org/10.1109/EuroSimE.2019.8724558}, year = {2019}, language = {en} } @inproceedings{ElgerLiuContietal.2019, author = {Elger, Gordon and Liu, E and Conti, Fosca and Signorini, Raffaella and Brugnolotto, Enrico and Bhogaraju, Sri Krishna}, title = {Modelling Thermo-Mechanical Stress in GaN-LEDs Soldered on Copper Substrate with Simulations Validated by Raman Experiments}, booktitle = {2019 20th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-8040-7}, doi = {https://doi.org/10.1109/EuroSimE.2019.8724533}, year = {2019}, language = {en} } @inproceedings{ElgerMokhtariBhogarajuetal.2020, author = {Elger, Gordon and Mokhtari, Omid and Bhogaraju, Sri Krishna and Conti, Fosca and Meier, Markus and Schweigart, Helmut}, title = {Analyse der Reaktionsprodukte von Metall-Formiaten im r{\"u}ckstandfreien L{\"o}tprozess}, booktitle = {GMM-Fb. 94: EBL 2020 - Elektronische Baugruppen und Leiterplatten}, publisher = {VDE Verlag}, address = {Berlin}, isbn = {978-3-8007-5185-3}, doi = {https://www.vde-verlag.de/proceedings-de/455185053.html}, year = {2020}, language = {de} } @inproceedings{BhogarajuMokhtariPascuccietal.2019, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Pascucci, Jacopo and Conti, Fosca and Kotadia, Hiren R. and Elger, Gordon}, title = {A multi-pronged approach to low-pressure Cu sintering using surface-modified particles, substrate and chip metallization}, volume = {2019}, booktitle = {International Symposium on Microelectronics}, number = {1}, publisher = {IMAPS}, address = {Pittsburgh}, issn = {2380-4505}, doi = {https://doi.org/10.4071/2380-4505-2019.1.000387}, pages = {387 -- 392}, year = {2019}, language = {en} } @inproceedings{BhogarajuMokhtariPascuccietal.2019, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Pascucci, Jacopo and Conti, Fosca and Elger, Gordon}, title = {Improved sinterability of particles to substrates by surface modifications on substrate metallization}, volume = {2019}, booktitle = {Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT)}, number = {HiTen}, publisher = {IMAPS}, address = {Pittsburgh (PA)}, issn = {2380-4491}, doi = {https://doi.org/10.4071/2380-4491.2019.HiTen.000066}, pages = {66 -- 70}, year = {2019}, language = {en} } @inproceedings{SignoriniContiBrugnolottoetal.2019, author = {Signorini, Raffaella and Conti, Fosca and Brugnolotto, Enrico and Pedron, Danilo and Liu, E and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Thermomechanical local stress in assembled GaN LEDs investigated by Raman optical spectroscopy}, booktitle = {Integrated Optics: Design, Devices, Systems, and Applications V}, editor = {Cheben, Pavel and Čtyrok{\´y}, Jiř{\´i} and Molina-Fern{\´a}ndez, I{\~n}igo}, publisher = {SPIE}, address = {Bellingham}, isbn = {978-1-5106-2729-1}, doi = {https://doi.org/10.1117/12.2520992}, year = {2019}, language = {en} } @inproceedings{SchmidHanssBhogarajuetal.2019, author = {Schmid, Maximilian and Hanss, Alexander and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Time saving averaging algorithm for transient thermal analyses over deterministic pulse superposition}, booktitle = {2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-2078-2}, doi = {https://doi.org/10.1109/THERMINIC.2019.8923548}, year = {2019}, language = {en} } @inproceedings{BrugnolottoBhogarajuLiuetal.2019, author = {Brugnolotto, Enrico and Bhogaraju, Sri Krishna and Liu, E and Conti, Fosca and Pedron, Danilo and Signorini, Raffaella and Elger, Gordon}, title = {Investigation of thermomechanical local stress induced in assembled GaN LEDs}, booktitle = {2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-2078-2}, doi = {https://doi.org/10.1109/THERMINIC.2019.8923629}, year = {2019}, language = {en} } @inproceedings{SchmidBhogarajuElger2019, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Automatic transient thermal impedance tester for quality inspection of soldered and sintered power electronic devices on panel and tile level}, booktitle = {2019 IEEE 69th Electronic Components and Technology Conference (ECTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-1499-6}, doi = {https://doi.org/10.1109/ECTC.2019.00320}, pages = {2324 -- 2330}, year = {2019}, language = {en} } @inproceedings{SenelUdupaElger2021, author = {Senel, Numan and Udupa, Shrivatsa and Elger, Gordon}, title = {Sensor data preprocessing in road-side sensor units}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-acm-120}, year = {2021}, language = {en} } @inproceedings{StreckSchmokSchneideretal.2021, author = {Streck, Egor and Schmok, Peter and Schneider, Klaus and Erdogan, H{\"u}seyin and Elger, Gordon}, title = {Safeguarding future autonomous traffic by infrastructure based on multi radar sensor systems}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-acm-121}, year = {2021}, language = {en} } @inproceedings{MohanLangerElger2022, author = {Mohan, Nihesh and Langer, Stefan and Elger, Gordon}, title = {Fluxfree solder paste and process for standard SMD components}, booktitle = {2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8947-8}, doi = {https://doi.org/10.1109/ESTC55720.2022.9939528}, pages = {163 -- 168}, year = {2022}, language = {en} } @inproceedings{MeessGernerHeinetal.2022, author = {Meess, Henri and Gerner, Jeremias and Hein, Daniel and Schmidtner, Stefanie and Elger, Gordon}, title = {Real World Traffic Optimization by Reinforcement Learning: A Concept}, booktitle = {International Workshop on Agent-Based Modelling of Urban Systems (ABMUS) Proceedings: 2022}, editor = {Kieu, Minh Le and Dam, Koen H. van and Thompson, Jason and Malleson, Nick and Heppenstall, Alison and Ge, Jiaqi}, publisher = {figshare}, address = {[s. l.]}, doi = {https://doi.org/10.6084/m9.figshare.19733800.v1}, pages = {49 -- 54}, year = {2022}, language = {en} } @inproceedings{SchmidHermannLiuetal.2022, author = {Schmid, Maximilian and Hermann, Joseph and Liu, E and Elger, Gordon}, title = {Correlation of Scanning Acoustic Microscopy and Transient Thermal Analysis to Identify Crack Growth in Solder Joints}, booktitle = {Proceedings of the Twenty First InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8503-6}, doi = {https://doi.org/10.1109/iTherm54085.2022.9899664}, year = {2022}, language = {en} } @inproceedings{ZippeliusStroblSchmidetal.2022, author = {Zippelius, Andreas and Strobl, Tobias and Schmid, Maximilian and Hermann, Joseph and Hoffmann, Alwin and Elger, Gordon}, title = {Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks}, booktitle = {2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8947-8}, doi = {https://doi.org/10.1109/ESTC55720.2022.9939465}, pages = {566 -- 575}, year = {2022}, language = {en} } @inproceedings{SchmidHermannBhogarajuetal.2022, author = {Schmid, Maximilian and Hermann, Joseph and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Reliability of SAC Solders under Low and High Stress Conditions}, booktitle = {2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8947-8}, doi = {https://doi.org/10.1109/ESTC55720.2022.9939394}, pages = {553 -- 559}, year = {2022}, language = {en} } @inproceedings{LiuBhogarajuLuxetal.2022, author = {Liu, E and Bhogaraju, Sri Krishna and Lux, Kerstin and Elger, Gordon and Mou, Rokeya Mumtahana}, title = {Investigation Of Stress Generated By Interconnection Processes With Micro-Raman Spectroscopy (μRS)}, booktitle = {Proceedings IEEE 72nd Electronic Components and Technology Conference: ECTC 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7943-1}, doi = {https://doi.org/10.1109/ECTC51906.2022.00123}, pages = {739 -- 745}, year = {2022}, language = {en} } @inproceedings{SacconBeninBhogarajuetal.2022, author = {Saccon, Rodolfo and Benin, Alice and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Effect of binders on the performance of copper sintering pastes}, booktitle = {2022 International Conference on Electronics Packaging (ICEP 2022)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-4-9911911-3-8}, doi = {https://doi.org/10.23919/ICEP55381.2022.9795555}, pages = {71 -- 72}, year = {2022}, language = {en} } @inproceedings{KleinerHeiderKomsiyskaetal.2021, author = {Kleiner, Jan and Heider, Alexander and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Experimental Study on the Thermal Interactions in Novel Intelligent Lithium-Ion Modules for Electric Vehicles}, booktitle = {Proceedings of the Twentieth InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2021}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-8539-2}, issn = {2694-2135}, doi = {https://doi.org/10.1109/ITherm51669.2021.9503299}, pages = {556 -- 562}, year = {2021}, language = {en} } @inproceedings{SenelElgerFestag2020, author = {Senel, Numan and Elger, Gordon and Festag, Andreas}, title = {Sensor Time Synchronization in Smart Road Infrastructure}, booktitle = {FISITA Web Congress 2020}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-acm-083}, year = {2020}, language = {en} } @article{ZippeliusHanssSchmidetal.2022, author = {Zippelius, Andreas and Hanss, Alexander and Schmid, Maximilian and P{\´e}rez-Vel{\´a}zquez, Judith and Elger, Gordon}, title = {Reliability analysis and condition monitoring of SAC+ solder joints under high thermomechanical stress conditions using neuronal networks}, volume = {2022}, pages = {114461}, journal = {Microelectronics Reliability}, number = {129}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0026-2714}, doi = {https://doi.org/10.1016/j.microrel.2021.114461}, year = {2022}, abstract = {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.}, language = {en} } @inproceedings{HanssSchmidBhogarajuetal.2018, author = {Hanss, Alexander and Schmid, Maximilian and Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Reliability of sintered and soldered high power chip size packages and flip chip LEDs}, booktitle = {ECTC - The 2018 IEEE 68th Electronic Components and Technology Conference: Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-5000-4}, doi = {https://doi.org/10.1109/ECTC.2018.00312}, pages = {2080 -- 2088}, year = {2018}, language = {en} } @inproceedings{BhogarajuMokhtariPascuccietal.2020, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Pascucci, Jacopo and Hanss, Alexander and Schmid, Maximilian and Conti, Fosca and Elger, Gordon}, title = {Hybrid Cu particle paste with surface-modified particles for high temperature electronics packaging}, booktitle = {Proceedings 22nd European Microelectronics and Packaging Conference, EMPC}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6291-1}, doi = {https://doi.org/10.23919/EMPC44848.2019.8951887}, year = {2020}, language = {en} } @article{HanssSchmidLiuetal.2015, author = {Hanss, Alexander and Schmid, Maximilian and Liu, E and Elger, Gordon}, title = {Transient thermal analysis as measurement method for IC package structural integrity}, volume = {24}, pages = {068105}, journal = {Chinese Physics B}, number = {6}, publisher = {IOP Publishing}, address = {Bristol}, issn = {2058-3834}, doi = {https://doi.org/10.1088/1674-1056/24/6/068105}, year = {2015}, language = {en} } @article{HanssElger2018, author = {Hanss, Alexander and Elger, Gordon}, title = {Residual free solder process for fluxless solder pastes}, volume = {30}, journal = {Soldering \& Surface Mount Technology}, number = {2}, publisher = {Emerald}, address = {Bingley}, issn = {0954-0911}, doi = {https://doi.org/10.1108/SSMT-10-2017-0030}, pages = {118 -- 128}, year = {2018}, language = {en} } @inproceedings{HanssSchmidBhogarajuetal.2018, author = {Hanss, Alexander and Schmid, Maximilian and Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Process development and reliability of sintered high power chip size packages and flip chip LEDs}, booktitle = {2018 International Conference on Electronics Packaging and iMAPS All Asia Conference (ICEP-IAAC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-4-9902-1885-0}, doi = {https://doi.org/10.23919/ICEP.2018.8374351}, pages = {479 -- 484}, year = {2018}, language = {en} } @inproceedings{BhogarajuHanssSchmidetal.2018, author = {Bhogaraju, Sri Krishna and Hanss, Alexander and Schmid, Maximilian and Elger, Gordon and Conti, Fosca}, title = {Evaluation of silver and copper sintering of first level interconnects for high power LEDs}, booktitle = {2018 7th Electronic System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6814-6}, doi = {https://doi.org/10.1109/ESTC.2018.8546499}, year = {2018}, language = {en} } @inproceedings{SchmidElger2018, author = {Schmid, Maximilian and Elger, Gordon}, title = {Measurement of the transient thermal impedance of MOSFETs over the sensitivity of the threshold voltage}, booktitle = {EPE'18 ECCE Europe}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-9-0758-1528-3}, url = {https://ieeexplore.ieee.org/document/8515480}, year = {2018}, language = {en} } @inproceedings{ElgerHanssSchmid2018, author = {Elger, Gordon and Hanss, Alexander and Schmid, Maximilian}, title = {Transient Thermal Analysis as In-Situ Method in Accelerated Stress Tests to Access Package Integrity of LEDs}, booktitle = {2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6759-0}, doi = {https://doi.org/10.1109/THERMINIC.2018.8593278}, year = {2018}, language = {en} } @article{ContiHanssMokhtarietal.2018, author = {Conti, Fosca and Hanss, Alexander and Mokhtari, Omid and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Formation of tin-based crystals from a SnAgCu alloy under formic acid vapor}, volume = {42}, journal = {New Journal of Chemistry}, number = {23}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/C8NJ04173C}, pages = {19232 -- 19236}, year = {2018}, language = {en} } @inproceedings{HanssSchmidElger2019, author = {Hanss, Alexander and Schmid, Maximilian and Elger, Gordon}, title = {Combined Accelerated Stress Test with In-Situ Thermal Impedance Monitoring to Access LED Reliability}, booktitle = {Proceedings 2018 20th International Conference on Electronic Materials and Packaging (EMAP)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-5642-6}, doi = {https://doi.org/10.1109/EMAP.2018.8660833}, year = {2019}, language = {en} } @inproceedings{ElgerBibergerMeieretal.2018, author = {Elger, Gordon and Biberger, M. and Meier, M. and Schweigart, Helmut and Schneider, Klaus and Erdogan, H{\"u}seyin}, title = {Technische Sauberkeit von Radarbaugruppen}, booktitle = {Elektronische Baugruppen und Leiterplatten EBL 2018: Multifunktionale Aufbau- und Verbindungstechnik - Beherrschung der Vielfalt}, publisher = {DVS Media GmbH}, address = {D{\"u}sseldorf}, isbn = {978-3-96144-026-9}, url = {https://www.dvs-media.eu/de/buecher/dvs-berichte/3644/elektronische-baugruppen-und-leiterplatten-ebl-2018}, pages = {339 -- 349}, year = {2018}, language = {de} } @inproceedings{BhogarajuSchmidLiuetal.2022, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Liu, E and Saccon, Rodolfo and Elger, Gordon and Klassen, Holger and M{\"u}ller, Klaus and Pirzer, Georg}, title = {Low cost copper based sintered interconnect material for optoelectronics packaging}, booktitle = {2022 IEEE 72nd Electronic Components and Technology Conference (ECTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7943-1}, doi = {https://doi.org/10.1109/ECTC51906.2022.00270}, pages = {1720 -- 1725}, year = {2022}, language = {en} } @inproceedings{SignoriniPedronContietal.2018, author = {Signorini, Raffaella and Pedron, Danilo and Conti, Fosca and Hanss, Alexander and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Thermomechanical Stress in GaN LED Soldered on Copper Substrate Evaluated by Raman Measurements and Computer Modelling}, booktitle = {2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6759-0}, doi = {https://doi.org/10.1109/THERMINIC.2018.8593304}, year = {2018}, language = {en} } @article{LiuBhogarajuWunderleetal.2022, author = {Liu, E and Bhogaraju, Sri Krishna and Wunderle, Bernhard and Elger, Gordon}, title = {Investigation of stress relaxation in SAC305 with micro-Raman spectroscopy}, volume = {2022}, pages = {114664}, journal = {Microelectronics Reliability}, number = {138}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0026-2714}, doi = {https://doi.org/10.1016/j.microrel.2022.114664}, year = {2022}, language = {en} } @inproceedings{MohanBhogarajuLysienetal.2021, author = {Mohan, Nihesh and Bhogaraju, Sri Krishna and Lysien, Mateusz and Schneider, Ludovic and Granek, Filip and Lux, Kerstin and Elger, Gordon}, title = {Drop feature optimization for fine trace inkjet printing}, booktitle = {2021 23rd European Microelectronics and Packaging Conference \& Exhibition (EMPC): Technical Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-7-7}, doi = {https://doi.org/10.23919/EMPC53418.2021.9585004}, year = {2021}, language = {en} } @article{KettelgerdesElger2023, author = {Kettelgerdes, Marcel and Elger, Gordon}, title = {In-Field Measurement and Methodology for Modeling and Validation of Precipitation Effects on Solid-State LiDAR Sensors}, volume = {7}, journal = {IEEE Journal of Radio Frequency Identification}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {New York}, issn = {2469-7281}, doi = {https://doi.org/10.1109/JRFID.2023.3234999}, pages = {192 -- 202}, year = {2023}, language = {en} } @inproceedings{BhogarajuSchmidKotadiaetal.2021, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Kotadia, Hiren R. and Conti, Fosca and Elger, Gordon}, title = {Highly reliable die-attach bonding with etched brass flakes}, booktitle = {2021 23rd European Microelectronics and Packaging Conference \& Exhibition (EMPC): Technical Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-7-7}, doi = {https://doi.org/10.23919/EMPC53418.2021.9584967}, year = {2021}, language = {en} } @inproceedings{SteinbergerBhogarajuElger2023, author = {Steinberger, Fabian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Correlation between the characteristics of printed sinter paste and the quality of sintered interconnects through non-destructive analysis techniques}, booktitle = {NordPac 2023 Annual Microelectronics and Packaging Conference and Exhibition: Reviewed Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-91-89821-06-4}, doi = {https://doi.org/10.23919/NordPac58023.2023.10186250}, year = {2023}, language = {en} } @inproceedings{KettelgerdesElger2022, author = {Kettelgerdes, Marcel and Elger, Gordon}, title = {Modeling Methodology and In-field Measurement Setup to Develop Empiric Weather Models for Solid-State LiDAR Sensors}, booktitle = {2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-9227-0}, doi = {https://doi.org/10.1109/DTPI55838.2022.9998918}, year = {2022}, language = {en} } @inproceedings{TavakolibastiMeszmerKettelgerdesetal.2022, author = {Tavakolibasti, M. and Meszmer, P. and Kettelgerdes, Marcel and B{\"o}ttger, Gunnar and Elger, Gordon and Erdogan, H{\"u}seyin and Seshaditya, A. and Wunderle, Bernhard}, title = {Structural-thermal-optical-performance (STOP) analysis of a lens stack for realization of a digital twin of an automotive LiDAR}, booktitle = {2022 23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-5836-8}, doi = {https://doi.org/10.1109/EuroSimE54907.2022.9758897}, year = {2022}, language = {en} } @article{SenelKefferpuetzDoychevaetal.2023, author = {Senel, Numan and Kefferp{\"u}tz, Klaus and Doycheva, Kristina and Elger, Gordon}, title = {Multi-Sensor Data Fusion for Real-Time Multi-Object Tracking}, volume = {11}, pages = {501}, journal = {Processes}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2227-9717}, doi = {https://doi.org/10.3390/pr11020501}, year = {2023}, abstract = {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.}, language = {en} } @inproceedings{HermannSchmidElger2022, author = {Hermann, Joseph and Schmid, Maximilian and Elger, Gordon}, title = {Crack Growth Prediction in High-Power LEDs from TTA, SAM and Simulated Data}, booktitle = {THERMINIC 2022: Proceedings 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-9229-4}, doi = {https://doi.org/10.1109/THERMINIC57263.2022.9950673}, year = {2022}, language = {en} } @article{AgrawalBhanderiDoychevaetal.2023, author = {Agrawal, Shiva and Bhanderi, Savankumar and Doycheva, Kristina and Elger, Gordon}, title = {Static multi-target-based auto-calibration of RGB cameras, 3D Radar, and 3D Lidar sensors}, volume = {23}, journal = {IEEE Sensors Journal}, number = {18}, publisher = {IEEE}, address = {Piscataway}, issn = {1530-437X}, doi = {https://doi.org/10.1109/JSEN.2023.3300957}, pages = {21493 -- 21505}, year = {2023}, language = {en} } @article{KettelgerdesSarmientoErdoganetal.2024, author = {Kettelgerdes, Marcel and Sarmiento, Nicolas and Erdogan, H{\"u}seyin and Wunderle, Bernhard and Elger, Gordon}, title = {Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors}, volume = {16}, pages = {2407}, journal = {Remote Sensing}, number = {13}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {https://doi.org/10.3390/rs16132407}, year = {2024}, abstract = {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.}, language = {en} } @article{MohanAhuirTorresBhogarajuetal.2024, author = {Mohan, Nihesh and Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and Webler, Ralf and Kotadia, Hiren R. and Erdogan, H{\"u}seyin and Elger, Gordon}, title = {Decomposition mechanism and morphological evolution of in situ realized Cu nanoparticles in Cu complex inks}, volume = {48}, journal = {New Journal of Chemistry}, number = {15}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/D3NJ05185D}, pages = {6796 -- 6808}, year = {2024}, language = {en} } @inproceedings{MohanAhuirTorresBhogarajuetal.2024, author = {Mohan, Nihesh and Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and Kotadia, Hiren R. and Elger, Gordon}, title = {Rapid Sintering of Inkjet Printed Cu Complex Inks Using Laser in Air}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418323}, year = {2024}, language = {en} } @inproceedings{BhogarajuUgoliniBelponeretal.2024, author = {Bhogaraju, Sri Krishna and Ugolini, Francesco and Belponer, Federico and Greci, Alessio and Elger, Gordon}, title = {Reliability of Copper Sintered Interconnects Under Extreme Thermal Shock Conditions}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418348}, year = {2024}, language = {en} } @inproceedings{BhogarajuMohanSteinbergeretal.2024, author = {Bhogaraju, Sri Krishna and Mohan, Nihesh and Steinberger, Fabian and Erdogan, H{\"u}seyin and Hadrava, Philipp and Elger, Gordon}, title = {Novel Low Temperature and Low Pressure Sintering of ADAS Radar Sensor Antenna Stack}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418277}, year = {2024}, language = {en} } @inproceedings{AhuirTorresBhogarajuWestetal.2024, author = {Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and West, Geoff and Elger, Gordon and Kotadia, Hiren R.}, title = {Understanding Cu Sintering and Its Role on Corrosion Behaviour for High-Temperature Microelectronic Application}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418365}, year = {2024}, language = {en} } @article{ElgerBhogarajuSchneiderRamelow2024, author = {Elger, Gordon and Bhogaraju, Sri Krishna and Schneider-Ramelow, Martin}, title = {Hybrid Cu sinter paste for low temperature bonding of bare semiconductors}, volume = {2024}, pages = {136973}, journal = {Materials Letters}, number = {372}, publisher = {Elsevier}, address = {New York}, issn = {1873-4979}, doi = {https://doi.org/10.1016/j.matlet.2024.136973}, year = {2024}, abstract = {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.}, language = {en} } @inproceedings{HanKefferpuetzElgeretal.2024, author = {Han, Longfei and Kefferp{\"u}tz, Klaus and Elger, Gordon and Beyerer, J{\"u}rgen}, title = {FlexSense: Flexible Infrastructure Sensors for Traffic Perception}, booktitle = {2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9946-2}, doi = {https://doi.org/10.1109/ITSC57777.2023.10422616}, pages = {3810 -- 3816}, year = {2024}, language = {en} } @inproceedings{HanXuKefferpuetzetal.2024, author = {Han, Longfei and Xu, Qiuyu and Kefferp{\"u}tz, Klaus and Lu, Ying and Elger, Gordon and Beyerer, J{\"u}rgen}, title = {Scalable Radar-based Roadside Perception: Self-localization and Occupancy Heat Map for Traffic Analysis}, booktitle = {2024 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4881-1}, doi = {https://doi.org/10.1109/iv55156.2024.10588397}, pages = {1651 -- 1657}, year = {2024}, language = {en} } @inproceedings{OlcayMeessElger2024, author = {Olcay, Ertug and Meeß, Henri and Elger, Gordon}, title = {Dynamic Obstacle Avoidance for UAVs using MPC and GP-Based Motion Forecast}, booktitle = {2024 European Control Conference (ECC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-3-9071-4410-7}, doi = {https://doi.org/10.23919/ECC64448.2024.10591083}, pages = {1024 -- 1031}, year = {2024}, language = {en} } @inproceedings{ParetBhogarajuBusseetal.2024, author = {Paret, Paul and Bhogaraju, Sri Krishna and Busse, Dirk and Dahlb{\"u}dding, Alexander and Elger, Gordon and Narumanchi, Sreekant}, title = {Thermomechanical Degradation of Sintered Copper under High-Temperature Thermal Shock}, booktitle = {Proceedings: IEEE 74th Electronic Components and Technology Conference, ECTC 2024}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-7598-5}, doi = {https://doi.org/10.1109/ECTC51529.2024.00196}, pages = {1219 -- 1224}, year = {2024}, language = {en} } @inproceedings{SteinbergerMohanRaemeretal.2024, author = {Steinberger, Fabian and Mohan, Nihesh and R{\"a}mer, Olaf and Elger, Gordon}, title = {Low temperature die-attach bonding using copper particle free inks}, booktitle = {2024 IEEE 10th Electronics System-Integration Technology Conference (ESTC), Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9036-0}, doi = {https://doi.org/10.1109/ESTC60143.2024.10712150}, year = {2024}, language = {en} } @inproceedings{AgrawalSongKohlietal.2022, author = {Agrawal, Shiva and Song, Rui and Kohli, Akhil and Korb, Andreas and Andre, Maximilian and Holzinger, Erik and Elger, Gordon}, title = {Concept of Smart Infrastructure for Connected Vehicle Assist and Traffic Flow Optimization}, booktitle = {Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems}, editor = {Ploeg, Jeroen and Helfert, Markus and Berns, Karsten and Gusikhin, Oleg}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-573-9}, issn = {2184-495X}, doi = {https://doi.org/10.5220/0011068800003191}, pages = {360 -- 367}, year = {2022}, abstract = {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}, language = {en} } @inproceedings{StreckHerschelWallrathetal.2022, author = {Streck, Egor and Herschel, Reinhold and Wallrath, Patrick and Sunderam, M. and Elger, Gordon}, title = {Comparison of Two Different Radar Concepts for Pedestrian Protection on Bus Stops}, booktitle = {Proceedings of the 11th International Conference on Sensor Networks}, editor = {Prasad, Venkatesha and Pesch, Dirk and Ansari, Nirwan and Benavente-Peces, C{\´e}sar}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-551-7}, issn = {2184-4380}, doi = {https://doi.org/10.5220/0010777100003118}, pages = {89 -- 96}, year = {2022}, abstract = {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.}, language = {en} } @inproceedings{ContiLuxBhogarajuetal.2021, author = {Conti, Fosca and Lux, Kerstin and Bhogaraju, Sri Krishna and Liu, E and Lenz, Christoph and Seitz, Roland and Elger, Gordon}, title = {Raman spectroscopy to investigate gallium nitride light emitting diodes after assembling onto copper substrates}, booktitle = {Optical Sensors 2021}, editor = {Baldini, Francesco and Homola, Jiri and Lieberman, Robert A.}, publisher = {SPIE}, address = {Bellingham}, isbn = {978-1-5106-4379-6}, doi = {https://doi.org/10.1117/12.2591947}, year = {2021}, language = {en} } @article{BhanderiAgrawalElger2025, author = {Bhanderi, Savankumar and Agrawal, Shiva and Elger, Gordon}, title = {Deep segmentation of 3+1D radar point cloud for real-time roadside traffic user detection}, volume = {15}, pages = {38489}, journal = {Scientific Reports}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {https://doi.org/10.1038/s41598-025-23019-6}, year = {2025}, abstract = {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).}, language = {en} } @unpublished{BhanderiAgrawalElger2025, author = {Bhanderi, Savankumar and Agrawal, Shiva and Elger, Gordon}, title = {Deep Segmentation of 3+1D Radar Point Cloud for Real-Time Roadside Traffic User Detection}, titleParent = {Research Square}, publisher = {Research Square}, address = {Durham}, doi = {https://doi.org/10.21203/rs.3.rs-7222130/v1}, year = {2025}, abstract = {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).}, language = {en} } @article{KleinerHeiderKomsiyskaetal.2021, author = {Kleiner, Jan and Heider, Alexander and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of intelligent automotive lithium-ion batteries: Experimental study with switchable cells and reconfigurable modules}, volume = {2021}, pages = {103274}, journal = {Journal of Energy Storage}, number = {44, Part A}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2021.103274}, year = {2021}, language = {en} } @article{KleinerLechermannKomsiyskaetal.2021, author = {Kleiner, Jan and Lechermann, Lorenz and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of intelligent automotive lithium-ion batteries}, volume = {2021}, pages = {102686}, journal = {Journal of energy storage}, subtitle = {operating strategies for adaptive thermal balancing by reconfiguration}, number = {40}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2021.102686}, year = {2021}, language = {en} }