07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access Design of zonal E/E architectures in vehicles using a coupled approach of k-means clustering and Dijkstra’s algorithm(2023) Maier, Jonas; Reuss, Hans-ChristianElectromobility and autonomous driving has started a transformation in the automotive industry, resulting in new requirements for vehicle systems. Due to its functions, the electrical/electronic (E/E) architecture is one of the essential systems. Zonal E/E architecture is a promising approach to tackle this issue. The research presented in this paper describes a methodology for determining the optimal number of zones, the position of the zone control units (ZCU), and the assignment of electric components to these zones and ZCUs. Therefore, the design of the power supply and the wiring harness is essential. This approach aims to identify the most suitable system architecture for a given vehicle geometry and a set of electric components. For this purpose, the assignment of electric components is accomplished by k-means clustering, and Dijkstra’s algorithm is used to optimize the cable routing. As ZCUs will be the hubs for the in-vehicle data and information transport in zonal architectures, their position and their number are crucial for the architecture and wiring harness development. Simulations show a suitable zonal architecture reduces wiring harness length as well as weight and brings functional benefits. However, the number of zones must be chosen with care, as there may also be functional limitations.Item Open Access Comparison of driver models for powertrain test benches using a digital twin(2023) Schilling, Jannes; Wilmsen, Jan-Michael; Nitschke, Paul; Reuss, Hans-ChristianItem Open Access Smart data preprocessing method for remote vehicle diagnostics to increase data compression efficiency(2022) Görne, Lorenz; Reuss, Hans-Christian; Krätschmer, Andreas; Sauerwald, RalfThe increasing number of functions in modern vehicle leads to an exponential increase in software complexity. The validity and reliability of all components must be ensured, making the use of appropriate vehicle diagnostics systems indispensable. The purpose of such systems is to collect and process data about the vehicle. To find issues during vehicle development, the OEMs will usually have a development fleet of thousands of vehicles. The challenge for diagnostic systems is to detect issues during these tests, as well as collecting as much data as possible about the circumstances that led to the fault. A single-vehicle produces hundreds of gigabytes of data per month. The required data bandwidth cannot be fulfilled by current mobile network subscriptions as well as WIFI or cable-based infrastructure. This limits the amount of data that can be collected during field tests and hinders big data analysis like AI training or validation. Hence a software solution for data reduction is necessary. The authors present a method for data handling that drastically reduces the amount of data consumption and optimizes the transfer delay between a remote-diagnostic systems and the cloud. Using a pipeline of data preprocessing as well as an established compression algorithm, the amount of transmitted data is reduced by a factor of nearly ten. This method will allow to collect more data in field testing and improve the understanding of issues during vehicle development.Item Open Access EVIAN - Electric Vehicle Intelligent Charging Technology R&D combined with Electricity Network Adaptation and Battery Lifetime Factors : technical report(Stuttgart : University of Stuttgart, Institute of Automotive Engineering, 2021) Auer, Chris; Brosi, Frank; Abu Mohareb, Omar; Reuss, Hans-ChristianThis technical report is an outcome of the EVIAN-Project funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung - BMBF). The aim of project EVIAN (Electric Vehicle Intelligent Charging Technology R&D Combined with Electricity Network Adaptation and Battery Lifetime Factors) is to intelligently integrate charging systems or electric vehicles with energy recovery into the power line. In order to be able to feed energy back into the grid, information must be exchanged and communicated between the vehicle, the charging station and the grid operator. This project identifies the parameters necessary to communicate such information between the participating systems. Therefore, a communication strategy is developed which takes into consideration the existing standards and protocols.Item Open Access Approach to design of piezoelectric energy harvester for sensors on electric machine rotors(2024) Brandl, Lukas; Reuss, Hans-Christian; Heidle, DanielThe reliability and efficiency of components are key aspects in the automotive industry. Electric machines become the focus of development. Thus, improvements in efficiency and reliability have gained significance. While it is established to attach sensors to the fixed parts of machines, such as stators, moving parts like rotors pose a major challenge due to the power supply. Piezoelectric generators can operate as energy harvesters on rotors and thus enable the rotor-based integration of sensors. The research in this article proposes the first approach to the design of a piezoelectric energy harvester (PEH) for an electric machine rotor dedicated to powering a wireless sensor system. After introducing the field of PEHs, the integration of the proposed device on a rotor shaft is presented. Further, a gap between the provided and needed data for the design of a PEH is identified. To overcome this gap, a method is presented, starting with the definition of the rotor shaft dimensions and the applied mechanical loads, including a method for the calculation of the imbalance of the rotor. With the first set of dimensions of the shaft and PEH, a co-simulation is performed to calculate the power output of this rotor and PEH set. The results of the simulation indicate the feasible implementation of the PEH on the rotor, providing enough energy to power a temperature sensor.Item Open Access Automated and virtual optimization of race-track simulation parameters on the power-train test bench(2023) Schilling, Jannes; Wilmsen, Jan-Michael; Reuss, Hans-Christian; Schmidt, Henrik; Prokop, GüntherThis paper focuses on powertrain test benches (PTB) in motorsports applications. In this case, a real powertrain is coupled with a virtual environment on the PTB to emulate mechanical loads experienced during racetrack driving. We utilize a Digital Twin of the PTB (a combination of the PTBs’ virtual environment, a powertrain model and a testbed model) to reduce setup time and allow offline virtual environment parameterization. The simulation models of the virtual environment may not always provide accurate representations due to unknown parameters or simplifications made to meet real-time requirements. Consequently, there are discrepancies between PTB and vehicle measurements. This paper aims to minimize such differences with a novel parame-ter optimization method.Item Open Access Development of a low-expansion and low-shrinkage thermoset injection moulding compound tailored to laminated electrical sheets(2024) Braunbeck, Florian; Schönl, Florian; Preußler, Timo; Reuss, Hans-Christian; Demleitner, Martin; Ruckdäschel, Holger; Berendes, PhilippThis study presents a thermoset moulding compound designed for electrical machines with high power densities. The compound reduces residual stresses induced by the difference in thermal expansion during use and by shrinkage in the compound during the manufacturing process. To reduce the internal stresses in the compound, in the electrical sheet lamination and at their interface, first the moulding’s coefficient of thermal expansion (CTE) must match that of the lamination because the CTE of the electrical sheets cannot be altered. Second, the shrinkage of the compound needs to be minimized because the moulding compound is injected around a prefabricated electrical sheet lamination. This provides greater freedom in the design of an electric motor or generator, especially if the thermoset needs to be directly bonded to the electrical sheet. The basic suitability of the material for the injection moulding process was iteratively optimised and confirmed by spiral flow tests. Due to the reduction of the residual stresses, the compound enables efficient cooling solutions for electrical machines with high power densities. This innovative compound can have a significant impact on electric propulsion systems across industries that use laminated electrical sheets.Item Open Access AI-based classification of CAN measurements for network and ECU identification(2022) Lutchen, Ralf; Krätschmer, Andreas; Reuss, Hans-ChristianDue to the constantly increasing number of functions offered by a modern vehicle, the complexity of vehicle development is also increasing as a result. A first indication of this connection is provided by the number of ECUs (electronic control units) used in current development vehicles. Furthermore, each ECU also performs more functions and is not only electrically networked with the other ECUs, but also logically and functionally. On this basis, new cooperative functions are being developed, which are used for example for autonomous driving. In vehicle development, more and more test sequences (diagnostic scripts) are established for function testing of individual components, systems and cross-functional methods. Due to decentralization and the modular approach, modern development vehicles consist of different numbers of ECUs. The high number of ECUs in purpose and number poses a challenge for test creation and updating. The ECU software is also developed in cycles within the vehicle cycle. This results in a very high software variance. This variance leads to the fact that in the vehicle development with global test conditions works. Global test conditions at this point mean that more ECUs are included in the measurement procedure than are installed in the vehicle. The vehicle structure (control unit and its software version) is not known to the person performing the measurement. He relies on the fact that his ECUs are inside in the global measurement task. This means that the vehicle network architecture is uncertain, which can lead to errors during test execution. Since the ECUs that are actually installed in the vehicle are first determined during test execution, this results in a longer script runtime than would be necessary. To support the development engineer and prevent avoidable errors, the diagnostic system should configure itself as far as possible. This means that individually customized measurements for each vehicle should be calculated in the cloud and not the global measurement tasks. For a diagnostic system to be able to configure itself independently, the vehicle network structure must be determined in a first step. This can be done by a simple CAN measurement (measurementXY.asc). An AI is able to analyze this measurement and classify the occurring ECUs as well as CAN networks. For larger measuring devices with more than one CAN interface, the user who analyzes the measurement is interested in which CAN was connected. Here, the AI is suitable to determine the name of the network and the communicating ECUs based on the communication that runs over the bus. For this purpose, the AI classifies the number of communicating ECUs based on the time intervals at which messages are sent. In addition, the AI can be supported by a special diagnostic script (global.pattern) to determine the vehicle structure at the OBD (on-board diagnostics) interface with maximum accuracy. Three AI approaches are presented, all connected in series and passing results to each other (pipeline mode). First comes the AI that separates vehicle communication from diagnostic communication. Based on the vehicle communication, the network name can be determined. Based on the diagnostic messages, the ECUs can be determined.Item Open Access Concept development for bearing fault detection on water-cooled electric machines using infrared(2025) Schamberger, Stephanie; Brandl, Lukas; Reuss, Hans-Christian; Wagner, AlfonsElectric machines (EMs) of electrified vehicle drivetrains can be tested on drivetrain test benches at an early stage of development. In order to protect the EMs from premature damage or failure during testing, monitoring their thermal condition is important. Due to the package requirements of compact and powerful EMs with high-speed requirements and high-power densities, the heat build-up inside the motor during operation is particularly high. For this reason, fluid cooling with heat exchangers is increasingly being used in EMs. The EMs analysed in this work are water-cooled by a cooling jacket. This influences the heat flow inside the machine through heat transfer mechanisms, making it difficult to detect damage to the EMs. This paper presents a novel method for non-destructive and non-contact thermal condition monitoring of water-cooled EMs on drivetrain test benches using thermography. In an experimental setup, infrared images of an intact water-cooled EM are taken. A bearing of the EM’s rotor is then damaged synthetically, and the experiment is repeated. The infrared images are then processed and analysed using appropriate software. The analysis of the infrared images shows that the heat propagation of the motor with bearing damage differs significantly from the heat propagation of the motor without bearing damage. This means that thermography opens up another method of condition monitoring for water-cooled EMs. The results of the investigation serve as a basis for future condition monitoring of water-cooled EMs on powertrain test benches using artificial intelligence (AI).