@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} } @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}, volume = {2021}, pages = {107864}, journal = {Reliability Engineering \& System Safety}, subtitle = {use cases and challenges in the automotive industry}, 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{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} } @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} } @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} } @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{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 (PA)}, issn = {2380-4505}, doi = {https://doi.org/10.4071/2380-4505-2019.1.000387}, pages = {387 -- 392}, year = {2019}, language = {en} } @article{SchmidZippeliusHanssetal.2023, author = {Schmid, Maximilian and Zippelius, Andreas and Hanß, Alexander and B{\"o}ckhorst, Stephan and Elger, Gordon}, title = {Investigations on High-Power LEDs and Solder Interconnects in Automotive Application: Part II - Reliability}, volume = {23}, journal = {IEEE Transactions on Device and Materials Reliability}, number = {3}, publisher = {IEEE}, address = {Piscataway}, issn = {1558-2574}, doi = {https://doi.org/10.1109/TDMR.2023.3300355}, pages = {419 -- 429}, year = {2023}, 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{SchmidZippeliusHanssetal.2022, author = {Schmid, Maximilian and Zippelius, Andreas and Hanss, Alexander and B{\"o}ckhorst, Stephan and Elger, Gordon}, title = {Investigations on High-Power LEDs and Solder Interconnects in Automotive Application: Part I - Initial Characterization}, volume = {22}, journal = {IEEE Transactions on Device and Materials Reliability}, number = {2}, publisher = {IEEE}, address = {Piscataway}, issn = {1530-4388}, doi = {https://doi.org/10.1109/TDMR.2022.3152590}, pages = {175 -- 186}, year = {2022}, abstract = {Thermo-mechanical reliability is one major issue in solid-state lighting. Mismatches in the coefficients of thermal expansion (CTE) between high-power LED packages and substrates paired with temperature changes induce mechanical stress. This leads to a thermal degradation of LED modules by crack formation in the solder interconnect and/or delamination in the substrate, which in turn increases junction temperature and thus decreases light output and reduces lifetime. To investigate degradation and understand influence of LED package design and solder material, a reliability study with a total of 1800 samples - segmented in nine LED types and five solder pastes - is performed. First of all, in this paper a state-of-the-art review of high-power LED packages is performed by analyzing and categorizing the packaging technologies. Second, the quality inspection after assembly is realized by transient thermal analysis (TTA), scanning acoustic microscopy (SAM) and X-ray. For TTA, a new method is introduced to separate the thermal resistance of the LED package from solder interconnect and substrate by applying the transient dual interface method (TDI) on samples with different solder interconnect void ratios. Further measurement effort is not required. The datasheet values for thermal resistance are verified and the different LED package types are benchmarked. The void ratio of the solder interconnects is determined by X-ray inspection combined with an algorithm to suppress disruptive internal LED package structures. TTA and TDI revealed that initial thermal performance is independent of solder paste type and that voiding is more critical to smaller LED packages. In addition, lower silver proportion in the paste is found to increase voiding. SAM is less sensitive for initial void detection than X-ray, but it's applied to monitor crack propagation while aging in combination with TTA. The results of the reliability study, i.e., the crack growth under temperature shock test for the different SAC solders, will be presented in a second independent paper.}, language = {en} }