Browse Topic: Electrical, Electronics, and Avionics

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Exploring the Correlation Between Physiological States and Driving Behavior on Highways with Integrated ECG Measurements2025-01-0292To be published on 07/02/2025
Human driver errors, such as distracted driving, inattention, and aggressive driving, are the leading causes of road accidents. Understanding the underlying factors that contribute to these behaviors is critical for improving road safety. Previous studies have shown that physiological states, like raised heart rates due to stress and anxiety, can influence driving behavior, leading to erratic driving behaviors and an increased risk of accidents. In this study, we conducted on-road tests using a measurement system based on the Driver-Driven vehicle-Driving environment (3D) method. We collected physiological signals, specially electrocardiogram (ECG) data, from human drivers to examine the relationship between physiological states and driving behaviors. The aim was to determine whether ECG could serve as an indicator of potential risky driving behaviors, such as sudden acceleration and frequent steering adjustments. This information could enable automated driving systems (AD) to
Ji, Dejie, Flormann, Maximilian, Bollmann, Julian, Henze, Roman, Deserno, Thomas M.
Technical Paper
Improving Speed Trajectory Optimization for Electric Vehicles with Pre-Calculated Energy Maps and Dynamic Profile Discretization2025-01-0318To be published on 07/02/2025
Ongoing research and development in the field of electric vehicles (EVs) have resulted in a continuous expansion of their range. Additionally, advancements in vehicle connectivity have created new opportunities for intelligent driving assistance and energy optimization, particularly through the use of cloud data. However, the integration of eco-driving assistance with numerical optimization of speed trajectories remains challenging due to the high computational demands of these methods. To address this challenge and make such a system feasible for integration into vehicle systems, the computational effort required for an optimized driving trajectory must be minimized. This paper presents a method to accelerate speed trajectory optimization using pre-calculated energy and time consumption maps. For this purpose, a dynamic discretization of the anticipated driving profile is applied. Initial results show a substantial reduction in computation time, varying with different scenarios
Schilling Johnson, Rene, Henke, Markus
Technical Paper
Prediction of hazardous gaseous emissions from a gasoline engine during cold starts using machine learning methods2025-01-0321To be published on 07/02/2025
Internal combustion engines generate higher exhaust emissions of hazardous gases during the initial minutes after engine start. Experimental data from a state-of-the-art turbo-charged 3-cylinder, 999 cc gasoline engine are used to predict cold start emissions using two Machine Learning (ML) models: a Multilayer Perceptron (MLP) which is a fully connected neural network and an Encoder-Decoder Recurrent Neural Network (ED-RNN). Engine parameters and various temperatures are used as input for the models and NOx (Nitrogen Oxides), CO (Carbon monoxide) and unburned hydrocarbon (UHC) emissions are predicted. The dataset includes time series recordings from the Worldwide harmonized Light-duty vehicles Test Cycle (WLTC) and four Real Diving Emissions (RDE) cycles at ambient and initial engine temperatures ranging from -20 °C to +23 °C. In total, 21 cases are considered, consisting of eight different ambient temperatures and five distinct driving cycles. Each case consists of a sequence of 2500
Mangipudi, Manoj, Denev, Jordan A., Bockhorn, Henning, Trimis, Dimosthenis, Koch, Thomas, Debus, Charlotte, Götz, Markus, Zirwes, Thorsten, Hagen, Fabian P., Tofighian, Hesam, Wagner, Uwe, Braun, Samuel, Lanzer, Theodor, Knapp, Sebastian M.
Technical Paper
An LLM-Based Multi-Turn Task-Oriented Dialogue System for Machine Learning Algorithm Selection in Data Mining2025-01-0289To be published on 07/02/2025
For the systematic application of machine learning during data mining in product development processes, selecting a suitable algorithm is crucial for success. During an empirical study in the automotive industry, a team applying data mining to develop battery systems for battery electric vehicles was accompanied. Here, it could be observed that data mining tasks are often unique during product development processes and can differ in boundary conditions. Depending on these tasks, suitable machine learning algorithms must be selected. Because of the variety of machine learning paradigms, problems, and algorithms, it is often hard to select a suitable algorithm, especially for inexperienced data miners. This paper presents a large language model (LLM)-based, multi-turn, task-oriented dialogue system to support data miners in selecting machine learning algorithms that are suitable for their specific data mining tasks. This approach, called “Algorithm Selection Assistant” (ASA), enables
Hörtling, Stefan, Bause, Katharina, Albers, Albert
Technical Paper
The Automation Concept of the U-Shift II Vehicle2025-01-0281To be published on 07/02/2025
Autonomous driving technology enables new and innovative driverless vehicle concepts to emerge, like U-Shift. Designed from the ground up, the U-Shift II platform, called driveboard, exemplifies the advantages of separating a vehicle's driving capability from the intended transportation task. It allows different so-called capsules, such as public transport or cargo, to be transported using the same U-shaped driving platform. The driveboard can change the capsules autonomously, thus providing high flexibility for fleet operators. This novel approach introduces new challenges to the task of autonomous driving. On one hand, changing sensor and vehicle configurations, e.g., when transporting a capsule with its own sensors to compensate for occlusions of the driveboard sensors by the capsule itself, requires an adaptive approach to environmental perception. On the other hand, different environments and driving tasks, as well as the augmented motion capabilities of the driveboard, require
Buchholz, Michael, Wodtko, Thomas, Schumann, Oliver, Authaler, Dominik
Technical Paper
U-Shift IV: Innovations and challenges in autonomous urban mobility2025-01-0284To be published on 07/02/2025
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
Pohl, Eric, Scheibe, Sebastian, Münster, Marco, Osebek, Manuel, Kopp, Gerhard, Siefkes, Tjark
Technical Paper
Automated Test Process for Highly Configurable Software-Defined Mobility Systems in CI/CD2025-01-0297To be published on 07/02/2025
In the pursuit of customizability and evolvability of vehicle functions, manufacturers shift towards software-defined vehicles (SDV) to enable flexible customization and over-the-air updates. This results in multiple variants and versions of a vehicle model. While shifting to SDVs adds value and flexibility for customers, manufacturers struggle with homologating new and updated functionality because existing testing processes do not scale for high-frequency release cycles that limit available testing resources. Overcoming this challenge by using a coherent test process designed for testing variant-rich systems in continuous evolution will be one of the key enablers for the future development of SDVs. This paper presents an innovative end-to-end pipeline for efficient and comprehensive testing of variant-rich vehicle functionality tailored to an application in continuous development. Our transferable test pipeline employs sample-based variant selection, a software-in-the-loop
Hettich, Lennard, Pett, Tobias, Nägele, Ann-Therese, Schindewolf, Marc, Eriş, Halit, Wagner, Stefan, Sax, Eric, Schaefer, Ina, Weyrich, Michael
Technical Paper
Towards Change-Aware Testing of Multi-Domain Cyber-Physical Systems: Challenges and Future Directions2025-01-0296To be published on 07/02/2025
Vehicles are prime examples of cyber-physical systems that rely on multiple domains, including mechanics, electronics, and software. Due to high customizability and software changes introduced by bug fixes or functional upgrades, vehicle instances vary in space (variants) and time (versions). This results in a huge number of possible variants and versions; thus, testing all combinations to ensure functional safety is practically infeasible. Moreover, components of all domains interact with each other; thus, solely focusing on single domains while testing multi-domain cyber-physical systems is insufficient. In this paper, we propose a process for change-aware testing of cyber-physical systems, including test activities we identified during a literature analysis. The process consists of multiple structured steps, including the selection of affected variants, test case selection, and adaptive configuration of test environments. Based on the process and identified activities, we discuss
Beck, Maximilian, Birkemeyer, Lukas, Pett, Tobias, Urbano, Francesco, Bause, Katharina, Albers, Albert, Sax, Eric, Schaefer, Ina
Technical Paper
Optimized Cabin Heating Strategy for Battery Electric CEP Vehicles2025-01-0263To be published on 07/02/2025
Electromobility is gaining importance in the courier, express and parcel (CEP) sector, as parcel service providers increasingly rely on zero-emission vehicles to improve their CO₂ footprint. A common drawback of battery electric vehicles is their reduced range under cold operating conditions, due to the increased energy demand for cabin heating. Another CEP-specific factor influencing both energy consumption and cabin comfort is the frequent opening of doors during parcel delivery. Additionally, during delivery phases, the cabin cools down in the driver’s repeated absence from the cabin, as the heating is inactive. Nonetheless, a sufficient level of thermal comfort must be maintained during the driving phases between delivery stops. This paper presents an optimization-based strategy for the cabin heating of battery electric CEP vehicles. The objective is to maximize cabin comfort during driving phases while maintaining efficient energy consumption. For this purpose, a nonlinear model
Rehm, Dominik, Krost, Jonathan, Meywerk, Martin, Czarnetzki, Walter
Technical Paper
Enhancing Flexibility of Automotive Embedded Software: A Modular Reference Architecture2025-01-0282To be published on 07/02/2025
Vehicular software is a key driver of innovation and revenue in the automotive industry. However, the increasing complexity of vehicular software, driven by shorter development cycles, more frequent updates, and tight coupling of software with hardware, presents significant challenges. Microcontroller-based vehicular software is particularly affected due to resource constraints, which limit flexibility and complicate software updates. To address these challenges, we propose a modular reference architecture that enhances flexibility for microcontroller-based vehicular software, facilitating software modifications in the context of regular updates. The reference architecture is systematically derived from general requirements for microcontroller-based vehicular software and proposes a domain-based structure. It divides embedded vehicular software into five domains: the application domain, responsible for control, regulation, and monitoring functions; the base domain, managing hardware
Griebler, Dennis, Zhai, Yi, Caggiano, Mario, Fuchss, Thomas
Technical Paper
DISRUPT - Decentralized Intelligent System for Road User Prediction and Tracking2025-01-0294To be published on 07/02/2025
We present DISRUPT, a research project to develop a cooperative traffic perception and prediction system based on networked infrastructure and vehicle sensors. Decentralized tracking and prediction algorithms are used to estimate the dynamic state of road users and predict their state in the near future. Compared to centralized approaches, which currently dominate traffic perception, decentralized algorithms offer advantages such as greater flexibility, robustness and scalability. Mobile sensor boxes are used as infrastructure sensors and the locally calculated status estimates are communicated in such a way that they can augment local estimates from other sensor boxes or vehicles. In addition, the information is transferred to a cloud that collects the local estimates and provides traffic visualization functionalities. The prediction module then calculates the future dynamic state based on neurocognitive behavior and a measure of a road user's risk of being involved in dangerous
Beutenmüller, Frank, Brostek, Lukas, Doberstein, Christian, Han, Longfei, Kefferpütz, Klaus, Obstbaum, Martin, Pawlowski, Antonia, Rössert, Christian, Sas-Brunschier, Lucas, Schön, Thilo, Sichermann, Jörg
Technical Paper
Improving Gearbox Acoustics Through Elastomer-Based Bearing Damping2025-01-0323To be published on 07/02/2025
This study analyses the effect of external damping of roller bearings on the acoustic behaviour of gearboxes in electric powertrains. The increasing adoption of electric vehicles has increased the importance of mitigating gearbox noise, as the lack of masking noise from internal combustion engines and the higher operating speeds of electric motors exacerbate the acoustic challenges. Gearbox noise, which is primarily caused by tooth mesh excitation and its transmission through shafts and bearings, requires strategies to minimise its impact on vehicle comfort and performance. External damping is introduced via adapters integrated into the outer bearing ring, which are used to modify the vibrational behaviour of the bearing assembly and reduce both structure-borne and airborne noise emissions. A systematic approach using Design of Experiments (DoE) methodology is used to quantify the effects of this damping. This approach allows the analysis of critical parameters including material
von Schulz, Kai, Linde, Tilmann, Jäger, Steffen
Technical Paper
Wheel Hop Detection in High-Torque Vehicles: A Machine Learning Approach with Focus on Data Coverage and Model Generalization2025-01-0271To be published on 07/02/2025
Wheel hop is a vibration phenomenon that occurs in cars with a high torque during high accelerations from low speed. Drivers perceive wheel hop as vertical oscillations in the vehicle frame. In severe cases, it can lead to component damage or deformation. Therefore, the affected vehicles must be safeguarded against these vibrations through safe component design and additional software-based functions. Conventional software-based solutions such as the traction control system (TCS) are not explicitly designed to prevent wheel hop. These systems often intervene too late and apply abrupt torque adjustments that compromise driving comfort. Based on observations on real measurements the TCS intervention in some cases leads to an amplification of the wheel hop effect. To address these challenges, we propose a novel approach based on machine learning (ML) for the early detection of wheel hop by leveraging real-time measurements from a rear-wheel drive vehicle. Unlike conventional methods, our
Chehoudi, Moatez, Moisidis, Ioannis, Sailer, Marc, Peters, Steven
Technical Paper
Conception and Experience of Non-driving Related Activities in Semi-autonomous Vehicles2025-01-0260To be published on 07/02/2025
While semi-autonomous driving (SAE level 3 & 4) is already partially a reality, the driver still needs to take over driving upon notice. Hence, the cockpit cannot be designed freely to accommodate spaces for non-driving related activities. In the following use case, a mobile workplace is created by integrating a translucent acrylic glass pane into the cockpit and introducing joystick steering of the car. By using the technology Virtual Desktop 1, which is a software layer, any desktop application can be represented freely transformable on arbitrary physical and virtual surfaces. Thus, a complete Windows environment can be distributed across all curved and flat surfaces of an interior. The concept is further enhanced by a voice-driven generative AI which helps to summarize documents. A physical and a virtual demonstrator are created to experience and assess the mobile workspace, the well-being of the driver, external influences, and psychological aspects. The physical demonstrator is a
Beutenmüller, Frank, Reining, Nine, Rosenstiel, Reto, Schmidt, Maximilian, Layer, Selina, Bues, Matthias, Mendonca, Daisy
Technical Paper
Safe Obstacle Avoidance Maneuver for Autonomous Vehicles2025-01-0285To be published on 07/02/2025
This paper focuses on trajectory planning for autonomous vehicles, specifically addressing the challenge of obstacle avoidance during driving. The proposed approach generates a safe and efficient maneuver in real time when a static obstacle is detected in the vehicle's path. The method consists of a path generation algorithm that computes a collision-free trajectory to avoid the obstacle while guiding the vehicle back to its initial lane. Geometric and dynamic constraints are integrated to maintain vehicle stability and ensure the feasibility of the generated trajectories. The algorithm has been validated through an IPG CarMaker professional simulator and an experimental campaign using an instrumented vehicle. Trajectory generation and path tracking are embeded in the vehicle software platform tested on a track. The experimental results demonstrate the effectiveness of the proposed planning method in generating safe avoidance maneuvers, enhancing the reliability and safety of
Vigne, Benoit, Giuliani, Pio Michele, Orjuela, Rodolfo, Basset, Michel
Technical Paper
Upgradable Mechatronic Systems – Integration of Upgrade Planning and Design for Sustainable Vehicle Development2025-01-0290To be published on 07/02/2025
The automotive industry faces the challenge of developing vehicles that meet current customer requirements while being future-proof. Surveys show that customers fear financial risks associated with essential subsystems like batteries due to aging and performance degradation, which significantly affects the service life of vehicles. Therefore, the rapid technological progress in electrified powertrain systems requires innovative approaches for high adaptability to changing demands. This paper presents an approach combining foresight-based planning of system-level upgrades with product architecture design to create adaptable and sustainable vehicles through modularity. Potential battery and energy storage technologies are identified, their market introduction is forecasted, and they are analyzed technically-functional and geometrically to create flexible design spaces within the product architecture. This enables the future integration of new, more efficient, or higher-performance
Fehrenbacher, Rüdiger, Kuebler, Maximilian, Zeng, Yunying, Bause, Katharina, Albers, Albert, Nootny, Fabio, Kolbe, Lucia, Jung, Luca
Technical Paper
Reducing Traffic Congestion with Reinforcement Learning-Driven Signal Control Systems2025-01-0283To be published on 07/02/2025
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and duration at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL)-based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Kalra, Vikhyat, Tulpule, Punit, Giuliani, Pio
Technical Paper
Optimization of Metallic Substrate by 1D simulations to fulfill High Power Cold Start Conditions2025-01-0308To be published on 07/02/2025
The future of the internal combustion engine is strictly related to his capability to have Life Cycle Emission comparable to the pure Battery Electric Vehicles. To achieve this goal, it will be necessary not only to have carbon free fuels but also to increase the hybridization of the powertrain in order to have lower fuel consumption. On the other hand, it will be necessary to reduce to almost zero any further emissions of pollutants. For this reason, highly sophisticated exhaust aftertreatment must be developed. One particular use case is the so-called High-Power Cold Start. This can occur for the Plug-In Hybrid Electric Vehicles when the transition from pure electric drive to ICE assisted drive happens during high load request, for example an acceleration on the freeway ramp. This use case has been evaluated by CARB and in many other works. Nevertheless, in this particular paper, the Authors would like to investigate which Metallic Substrate Technology fits better during a HPCS. This
Montenegro, Gianluca, Onorati, Angelo, Marinoni, Andrea, Della Torre, Augusto, Pace, Lorenzo, Konieczny, Katrin, Laurell, Mats, Klövmark, Henrik
Technical Paper
Modular Thermal Management Framework for Electric Drive System Development2025-01-0262To be published on 07/02/2025
The automotive industry is undergoing a major shift from internal combustion engines (ICE) to hybrid (HEV) and battery-electric vehicles (BEV), which has led to significant advancements and increased complexity in drivetrain design and thermal management systems. This complexity reflects the growing need to optimize energy efficiency, extend vehicle range, and ensure system reliability in modern electric vehicles. At the Institute of Automotive Engineering, a specialized synthesis tool for drivetrain optimization is used to identify the best drivetrain configurations based on specific boundaries and requirements. Building up on this toolchain a modular and adaptable thermal management framework has been developed, addressing another critical aspect of vehicle and drive development: efficient thermal circuit layout and its impact on energy consumption and overall system reliability. The thermal framework emphasizes the dynamic interactions between key components, such as electric
Notz, Fabian, Sturm, Axel, Sander, Marcel, Kässens, Christoph, Henze, Roman
Technical Paper
Leveraging LLM-based AI Agents for Boosting the Vehicle Testing Process2025-01-0300To be published on 07/02/2025
The validation process in research and development involves several complex stages, including test requests, planning, execution, and the analysis and evaluation of results. In the automotive domain, compliance with regulatory standards, such as those required for Euro 7 homologation, adds an additional layer of complexity. Implementing these regulations into operational validation workflows and ensuring their seamless integration with supporting tools remains a significant challenge. Recent advancements in Large Language Models (LLMs) have introduced innovative use cases across various domains. In particular, AI agents powered by LLMs demonstrate immense potential by autonomously performing complex tasks while utilizing user-defined tools. This capability extends far beyond traditional applications like knowledge management or text generation typically associated with LLMs. In this paper, we explore how a modern AI agent can be developed and integrated into existing IT tools for test
Unterschütz, Stefan, Hansen, Björn
Technical Paper
Impact of the distribution of charging and hydrogen refueling stations on their reachability for craft vehicles with a defined usage profile2025-01-0310To be published on 07/02/2025
This paper examines the impact of the distribution of charging and hydrogen refueling stations on their reachability for craft vehicles with a defined usage profile. A simulation-based methodology is presented for this purpose. The simulation models daily trips for craft vehicles, considering amongst others the company location, the client stops, the operating radius and the mean daily driving distance. Based on these inputs, the number of charging or refueling opportunities for typical daily trips of the craft vehicle is calculated. To investigate the impact of locations on the frequency of encountering energy provisions, simulations are conducted in three regions: Ulm (urban), Stuttgart (metropolitan), and Munderkingen (rural). Furthermore, the impact of different locations within the same infrastructural area is examined by assessing multiple company locations in Ulm. The findings indicate that the urban zone of Ulm is characterized by a highly dense electric fast charging
Heilmann, Oliver, Müller, Julian, Heinrich, Marco, Cortès, Sven, Schlick, Michael, Kulzer, André Casal
Technical Paper
Methodology for Real-World Automated Function Development: From Virtual to On-Vehicle Implementation2025-01-0288To be published on 07/02/2025
The automotive industry is increasingly facing challenges stemming from growing system complexities, shortened development cycles, and the demand for rapid time-to-market transitions. Reinforcement learning (RL) has emerged as a promising approach to developing advanced control functions due to its adaptive and autonomous nature. The technique has already demonstrated its viability in virtualised X-in-the-Loop (XiL) environments. However, its application to real-world vehicle systems is inhibited by safety concerns, real-time constraints, and the integration into established software toolchains. This paper introduces a comprehensive methodology for developing practical control functions with RL: starting in a virtual environment, training then transitions to a Hardware-in-the-Loop (HiL) setup, and ultimately proceeds to a real vehicle. Utilising the open-source framework LExCI, the proposed approach facilitates seamless training across multiple development stages and showcases RL’s
Badalian, Kevin, Picerno, Mario, Lee, Sung-Yong, Schaub, Joschka, Andert, Jakob
Technical Paper
Thermal Simulation of CCS Charging Inlet at High Charging Currents with various Optimisation Approaches2025-01-0278To be published on 07/02/2025
Current status: In Europe, the CCS charging standard for electric vehicles is the most widely used charging system. In order to reduce the inconveniences caused by long charging times, the CCS charging standard has been gradually adapted to the need for higher charging capacities. Currently, charging currents of up to 500A are supported at a charging power of up to 500kW. In order to decarbonise road transport, commercial vehicles are also increasingly being electrified. Problem definition: Battery-electric commercial vehicles in particular have large battery capacities with several hundred kilowatt hours, some of which do not have enough energy for an entire working day, which is why they need to be recharged if necessary. High charging power with correspondingly high charging currents is required to recharge the electrical energy storage units of commercial vehicles in an acceptable time. Due to the electrical losses, waste heat is generated, which places a thermal load on the
Krings, Jochen, Reuss, Hans-Christian, Ziegler, Peter, Steinmetz, Paul
Technical Paper
Strategies for Improving Data Management in Automotive Testing and Commissioning Processes2025-01-0277To be published on 07/02/2025
The decoupling of software from hardware in automotive systems, driven by the rising share of software in modern vehicles, has introduced a paradigm shift, enabling various software configurations on identical hardware platforms. Consequently, ensuring the correct functionality and reliability of the electric and electronic hardware components, testing and commissioning processes in the vehicle production have grown in importance and complexity. However, the efficiency of these processes relies on diverse datasets, for example parameterization data that allows tailored testing based on the vehicle’s equipment configuration. Therefore, the availability and accuracy of these data need to be guaranteed. Data for testing and commissioning, influenced by the digitization of production processes and their planning, is not only facing the challenges of greater software volumes and faster update cycles, but also those arising from legacy processes or the integration of various IT systems into
El Asad, Aiman, Köhler, Katja, Hahn, Michael, Reuss, Hans-Christian
Technical Paper
Development and Evaluation of a Combined Driveline Oscillation and Traction Controller Using Model Predictive Control and Reinforcement Learning: A Comparative Case Study2025-01-0291To be published on 07/02/2025
In electric vehicles, the control of driveline oscillations and tire trac- tion is critical for guaranteeing driver comfort and safety. Yet, achiev- ing sufficient driveline control performance remains challenging in the presence of rapidly varying road conditions. Two promising avenues for further improving driveline control are adaptive model predictive control (MPC) and model-based reinforcement learning (RL). We de- rive such controllers from the same non-linear vehicle model and vali- date them through pre-defined test scenarios. The MPC approach em- ploys input and output trajectory tracking with soft constraints to en- sure feasible control actions even in the presence of constraint viola- tions and is further supported by a Kalman filter for robust state estima- tion and prediction. In contrast, the RL controller leverages the model- based DreamerV3 algorithm to learn control policies autonomously, adapting to different road conditions without relying on external infor- mation
Uhl, Ramón Tamino, Schüle, Isabel, Ludmann, Laurin, Geist, A. René
Technical Paper
Leveraging AI for Automated Code Generation from Systems Engineering Specifications2025-01-0295To be published on 07/02/2025
The increasing complexity of modern vehicles and the automotive industry's shift towards Software Defined Vehicles (SDVs) require innovative solutions to streamline development processes. Traditional methods of software development often struggle to meet the demands for agility, scalability, and precision in this context. In response, this paper presents a noval approach utilizing Artificial Intelligence (AI), specifically Large Language Models (LLMs), to automate the generation of executable code directly from Systems Engineering (SE) specifications. This novel approach aims to transform how SE requirements are converted into implementation-ready code, reducing the inefficiencies and potential errors associated with manual translation. LLMs trained on domain-specific data are capable of interpreting complex requirements, managing dependencies, and generating consistent and accurate code. By integrating LLMs into the automotive software pipeline, companies can improve productivity
Padubrin, Marcel, Reuss, Hans-Christian, Brosi, Frank, Menz, Leonhard, Guerocak, Erol
Technical Paper
Experimental Investigation of Factors Influencing Thermal Runaway in Lithium-Ion Battery Cells2025-01-0306To be published on 07/02/2025
In the fast-paced automotive development environment, experimental testing is often constrained by time and budget limitations. Consequently, tests are frequently conducted to meet regulatory requirements, industry standards, or internal guidelines. This leads to minimalistic testing approaches such as "One Factor at a Time" (OFAT) or "Trial and Error", which fail to capture parameter interactions and system complexities. This study investigates the critical factors influencing the thermal runaway behavior of lithium-ion battery cells under controlled experimental conditions. A statistical full-factorial experimental design was implemented to evaluate the impact of state of charge (SoC), heating trigger power, and cell capacity. The experiments, conducted using an autoclave setup, allowed for precise control of external conditions and detailed measurement of thermal and mechanical responses. The cells investigated are automotive-grade lithium-ion cells from development projects
Ceylan, Deniz, Kulzer, André Casal, Winterholler, Nina, Weinmann, Johannes, Schiek, Werner
Technical Paper
Design and Analysis of a Battery Thermal Management System for Fast Charging in Extreme Hot Condition2025-01-0322To be published on 07/02/2025
Fast charging of lithium-ion batteries presents significant thermal management challenges, due to the high demanding conditions of high C-rates, particularly at extreme ambient temperatures. This study explores the thermal behavior of a cylindrical lithium-ion cell during fast-charging scenarios designed to achieve a full charge in 15 minutes or less (SOC: 0%–100%), across a wide range of ambient temperatures. The analysis covers a broad spectrum of ambient temperatures, from 303 K to 333 K, addressing real-world operational challenges faced by electric vehicles and energy storage systems. A validated thermal model, calibrated with experimental data on the open circuit voltage (OCV) and internal resistance of the cell across varying conditions, is employed to accurately predict the temperature distribution of the cell at different states of charge (SOC). The model also includes scenarios involving high initial cell temperatures to assess their effect on thermal performance during fast
Jahanpanah, Jalal, Mahmoudzadeh Andwari, Amin, Babaie, Meisam, Konno, Juho, Akbarzadeh, Mohsen
Technical Paper
Applying Real World Traffic Data on Machine Learning Methods for Graph Based Cooperation Strategies of Automated Vehicles2025-01-0286To be published on 07/02/2025
With the increasing distribution of smart mobility systems, automated & connected vehicles are more and more interacting with each other and with smart infrastructure using V2X-communication. Hereby, the vehicles' position, driving dynamics data, or driving intention are exchanged. Previous research has explored graph-based cooperation strategies for automated vehicles in mixed traffic environments based on current V2X-communication standards. Thereby, the focus is set on cooperation optimization and maneuver negotiation. These strategies can be implemented through both centralized and decentralized computational approaches and are conflict-free by design. To enhance these previously established cooperation models, real-world traffic data is used to derive vehicle trajectories, providing a more accurate representation of actual traffic scenarios in order to enhance the practical application of the described methodology. Additionally, machine learning algorithms are employed to train
Flormann, Maximilian, Meyer, Felix, Henze, Roman
Technical Paper
Simulation-Based Investigation and its Experimental Validation of the Thermal Behaviour of a Battery Electric City Bus2025-01-0266To be published on 07/02/2025
Electrification of city busses is an important factor for decarbonisation of the public transport sector. Due to its strictly scheduled routes and regular idle times, the public transport sector is an ideal use case for battery electric vehicles (BEV). In this context, the thermal management has a high potential to decrease the energy demand or to increase the vehicles range. The thermal management of an electric city bus controls the thermal behaviour of the components of the powertrain, such as motor and inverters, as well as the conditioning of the battery system and the heating, ventilation, and air conditioning (HVAC) of the drivers’ front box and the passenger room. The focus of the research is the modelling of the thermal behaviour of the important components of an electric city bus in MATLAB/Simscape including real-world driving cycles and the thermal management. The heating of the components, geometry and behaviour of the cooling circuits as well as the different mechanisms of
Schäfer, Henrik, Meywerk, Martin, Hellberg, Tobias
Technical Paper
Inductance Estimation of an Electric Vehicle2025-01-0293To be published on 07/02/2025
Electric vehicles are no longer a rarity on Europe’s streets. But battery electric vehicles (BEVs) still have a long way to go to be the dominant vehicle type on the streets. In the last years, not only has the number of passenger cars risen, but also the number of electric trucks and heavy-duty vehicles. In 2023 electric trucks have share of 1.5% in the market. For the truck industry higher charging powers are even more important. Due to European regulations drivers of vehicles with more than 3.5t weight or buses with more than 10 passengers must rest for 45 minutes after 4.5hours of drive. Therefore, higher charging powers were needed, and the Megawatt Charging System (MCS) standard was developed. The voltage level goes up to 1250V and currents of 3000A are defined. This allows the battery of heavy-duty vehicles to be completely charged within the driving breaks. As with the upcoming MCS standard, the charging power increases, also the failure risk rises. Higher charging currents
Grund, Caroline, Reuss, Hans-Christian
Technical Paper
An Architecture for Vehicle Diagnostics in Software-Defined Vehicles2025-01-0280To be published on 07/02/2025
Vehicles are evolving into Software-Defined Vehicles. The increasing use of automotive High Performance Computers (HPCs) provides more computing power and storage resources in vehicles. This opens possibilities to use more in-vehicle software. However, it also leads to challenges for vehicle diagnostics. Today's diagnostic approaches, based on Diagnostic Trouble Codes (DTCs), are not suitable for software on HPCs. For example, this software is highly variable and updated over time, so predefined DTCs are not dynamic enough. This introduces a degree of ambiguity into the diagnostic processes. Additional diagnostic data are required. In the Cloud, observability approaches are becoming widely used for software. Observability involves examining the availability and performance of an entire software system. To detect failures early, observability data, such as logs, metrics, and traces, are used. This is of interest for vehicle diagnostics as new diagnostic approaches are needed to
Bickelhaupt, Sandra, Hahn, Michael, Weyrich, Michael, Morozov, Andrey
Technical Paper
In Situ Observation of Different Soot Layers in a Model Filter Channel During Its Regeneration2025-01-0312To be published on 07/02/2025
To keep the air clean, wall-flow particulate filters are predominantly used in the exhaust gas after-treatment systems of combustion engines to remove reactive soot and inert ash particles. These filters consist of parallel porous channels with alternately closed ends, effectively separating particles by forming a layer on the filter surface. However, the particulate layer increases the pressure drop, requiring periodic regeneration. During regeneration, soot oxidation breaks up the particulate layer, while resuspension and transport of individual agglomerates may occur. These phenomena are influenced by gas temperature and velocity, as well as dispersity and the reactivity of the soot particles. Sustainable fuels can produce different types of soot with different reactivities and dispersities, therefore this study focuses on the influences of soot dispersity and reactivity by varying the reactive particle system. A model wall-flow filter channel is used for the investigation, enabling
Desens, Ole, Hagen, Fabian P., Meyer, Jörg, Dittler, Achim
Technical Paper
3D-printed porous media combined with biomimetic distributor for small-scale polymer electrolyte membrane fuel cells2025-01-0196To be published on 06/16/2025
This study presents a novel biomimetic flow-field concept that integrates a triply periodic minimal surface (TPMS) porous architecture with a hierarchical leaf-vein-inspired distribution zone, fabricated through 3D printing. By mimicking natural transport systems, the proposed design enhances oxygen delivery and water removal in proton exchange membrane fuel cells (PEMFCs). The results showed that I-FF and G-FF significantly improved mass transport and water management compared to conventional CPFF. The integrated design I-FF-LDZ achieves up to 32% improvement in power density at 1.85 A/〖cm〗^2@0.4 V and delays the onset of mass transport losses. The study also reveals that optimizing the volume fraction V_f significantly affects gas penetration, with lower V_f (30%) improving performance in the mass-limited region. These findings underscore the promise of nature-inspired, 3D-printed flow-field architectures in overcoming key transport limitations and advancing the scalability of next
Ho-Van, Phuc, Lim, Ocktaeck
Technical Paper
Flame developments of pilot diesel ignited hydrogen jet in an optical dual direct injection engine2025-01-0237To be published on 06/16/2025
This study aims to characterise the flame development for hydrogen-diesel dual direct injection (H2DDI) in an optically accessible heavy-duty engine through high-speed imaging of the natural combustion luminosity. A single hole, side mounted injector was used to inject H2 at 350 bar in addition to a centrally mounted eight-hole diesel injector providing the ignition source for the H2. The diesel pilot flame was examined without H2 to establish the combustion characteristics of the pilot flame. The pilot fuel energy was reduced from 1200J to 120J while examining the distribution of the pilot flame as the H2 energy fraction was increased. The flame distribution transitioned from an initial quasi-steady diesel flame at peak load (1200 J), to a piston bowl wall-centric flame distribution (840 J) and then to an injector centric flame (120 J). The pilot fuel quantity of 120 J was selected to investigate the ignition process of hydrogen main fuel mixtures supplying 90% energy (only 10% energy
Heaton, Alastar, Chan, Qing Nian, Kook, Sanghoon
Technical Paper
Development of the Central Coordinated Motion Control System for Pure Electric Vehicles2025-01-0188To be published on 06/16/2025
The IM L6 is the fourth product under the IM brand, featuring both rear-motor two-wheel drive and dual-motor all-wheel drive configurations. This article introduces the Ling Xi Digital Intelligent Chassis system of the IM L6, which includes air springs, CDC (Continuous Damping Control), rear-wheel steering system, braking system, front-wheel steering system, and electric drive system. The study explores how adjusting the damping of the CDC achieves a more comfortable damping effect. Through precise control of the rear-wheel steering system, the vehicle achieves smaller turning radii, crab walk capability, optimized response in moose test conditions, and improved performance on split-friction surfaces. By coordinating the IBS (Intelligent Brake System) and VMC (Vehicle Motion Control), an exceptionally comfortable braking experience is achieved.
Zhou, Yuxing, Li, Wen
Technical Paper
Parametric Analysis of Injector Operational Parameters, Charge Dilution, and Intake Valve Opening on In-Cylinder Motion and Flame Development in an Automotive, Lean-Burn, Gasoline Engine with High-Tumble2025-01-0198To be published on 06/16/2025
The effect of injection pressure, start of injection (SOI) timing, charge dilution, and valve timing on charge motion and early flame development was investigated for a pre-production automotive gasoline engine. Experiments were performed in a single-cycle optical engine designed to represent the high-tumble (Tumble ratio = 1.8), lean-burn engine. Time-resolved particle image velocimetry (PIV) was used to characterize velocity flow fields throughout the swept volume during the intake and compression strokes. Diffuse back illuminated imaging allowed for visualization and quantification of the injected liquid fuel spray and its interactions with the tumble vortex. Hydroxyl (OH*) chemiluminescence imaging was performed to image spark channel elongation and early flame kernel development. It was observed that an optimal injection timing of 320° before top dead center (bTDC) resulted in attenuation of the tumble motion and an associated reduction in compression flows that shifted the tumble
MacDonald, James, Ekoto, Isaac, Han, Donghee, Lee, Jonghyeok
Technical Paper
Comparison of Methanol and Gasoline Fuel Spray Vaporization Using Direct-Injection Technology2025-01-0225To be published on 06/16/2025
Considering the large opportunity to reduce net lifecycle carbon emissions through the use of renewable methanol, we address spray technologies needed to overcome the challenge of wall wetting and poor vaporization for methanol and the need for improved computational modeling of these processes. High-speed extinction imaging followed by computed tomography reconstruction is utilized to provide three-dimensional liquid volume fraction for reference fuel injectors, to be used for model validation activities. The first injector is the symmetric 8-hole Spray M injector for the Engine Combustion Network, and the second injector is an asymmetric 6-hole injector designed for lateral-cylinder mounting. The degree of plume interaction and vaporization are characterized at representative injection conditions, showing substantially higher concentrations of liquid for methanol than gasoline even with preheated fuel temperatures (90 degrees C). In light of higher injected mass requirements for
Wan, Kevin, Clemente Mallada, Rafael, Buen, Zachary, White, Logan, Oh, Heechang, Dhanji, Meghnaa, Pickett, Lyle
Technical Paper
Effect of Ignition Condition and Fuel Octane Number on Knock Intensity in a Small 2-Stroke Engine2025-01-0211To be published on 06/16/2025
The internal combustion engines are widely used on automotive transportation for its high energy storage system efficiency and economic benefits. The 4-stroke engine has dominated all other forms to date, because the Otto cycle is simpler to comprehend. However, the significant benefits such as, less pumping work and friction, lighter construction of 2-stroke engine, helped with applications which appreciate the simplicity and power density as well as meet the emission regulations. The disadvantages of the 2-stroke engine mainly caused by the lack of sufficient scavenging process, which limited its trapping efficiency. Also, the overlap of the intake and exhaust phases results in charge short-circuiting, more fuel consumption and high unburned hydrocarbon emissions. For the reason above, it is difficult for 2-stroke engines to realize stoichiometric combustion and unable to use three-way catalyst to control emissions. The residual exhaust gas in the cylinder makes the spark ignition
Liu, Jinru, Yamazaki, Yoshiaki, Otaki, Yusuke, Kato, Hayato, Yokota, Takumi, Iijima, Akira
Technical Paper
Research on Combustion Characteristics of Flash-Boiling Spray in Cylinders Based on Machine Learning Methods2025-01-0205To be published on 06/16/2025
With the increasing number of vehicles in operation, exhaust emissions from engines have exerted negative impacts on ecological environments, prompting researchers to actively pursue cleaner and more efficient in-cylinder combustion strategies. Flash-boiling spray technology, capable of generating superior fuel atomization under relatively low injection pressures, has emerged as a promising approach for achieving performance breakthroughs in gasoline direct injection (GDI) engines. While current research primarily focuses on morphological characterization and mechanistic analysis of flashboiling spray, there remains insufficient understanding of flame development characteristics under flash boiling spray conditions within engine cylinders. This study systematically investigates the combustion characteristics of TPRF and PRF fuels under both subcooled and flash-boiling spray conditions through the integration of image processing and machine learning methodologies. Experimental
Zhang, Weixuan, Shahbaz, Muhammad, Cui, Mingli, Li, Xuesong, Xu, Min
Technical Paper
Applied Full-Bridge Micro Strain Gauge to High Pressure Sensor for Gasoline Direct Injection/Hybrid System2025-01-0220To be published on 06/16/2025
High Pressure Sensors (HPS) are essential for internal combustion engines and hybrid engine systems. High pressure sensor measures the pressure in the Delivery fuel rail Pipe Module (DPM) to allow the Engine Control Unit (ECU) to control the high pressure pump to generate the required fuel pressure. Most high pressure sensors measure the displacement of the metal-diaphragm according to pressure, and are mainly composed of Half-bridge type Micro Electro Mechanical System (MEMS) elements of the piezo-resistive method. This time, we would like to introduce a high pressure sensor that uses a Full-bridge type MEMS structure. This is cheaper than the existing one and can provide higher performance with reliability. However, there are disadvantages of the full-bridge type applied to high pressure sensors. Unlike the Half-bridge method that measures displacement over a wide area, it measures displacement over a narrow area, so it has the disadvantage of weak to external noise due to increased
Lim, SeungGu, Lee, DongYoung, Kim, JungTaek, Shin, MoonSung
Technical Paper
Effects of Injection and Intake Timing on Atomization and Combustion in a Hybrid Gasoline Direct Injection Optical Engine under the Low-Speed Low-Load Condition2025-01-0203To be published on 06/16/2025
With the growing trend of hybridization in modern engines, hybrid gasoline direct injection (GDI) engines are typically designed for high-load, mid-to-high-speed operation to achieve optimal fuel economy. However, these engines inevitably operate under low-speed, low-load conditions where insufficient intake air often leads to poor air-fuel mixing and weak turbulence, resulting in suboptimal combustion. Adjusting intake and injection timing presents a simple and effective approach to optimizing the combustion process in hybrid GDI engines. In this study, an optical engine with a combustion system geometry identical to that of an advanced hybrid GDI engine is used. The engine features a compression ratio of 15.0:1 and is equipped with a variable timing camshaft for intake timing control and an electronically controlled system for injection timing. High-speed color imaging, using transparent pistons and cylinder liners, captures the in-cylinder spray development and combustion processes
Cui, Mingli, Fu, Jinhong, Man, Xingjia, Nour, Mohamed, Zhang, Weixuan, Li, Xuesong, Xu, Min
Technical Paper
Hybrid Approaches to Software Reliability: Evaluating and Enhancing Prediction Models2025-01-502405/06/2025
Software reliability prediction involves predicting future failure rates or expected number of failures that can happen in the operational timeline of the software. The time-domain approach of software reliability modeling has received great emphasis and there exists numerous software reliability models that aim to capture the underlying failure process by using the relationship between time and software failures. These models work well for one-step prediction of time between failures or failure count per unit time. But for forecasting the expected number of failures, no single model will be able to perform the best on all datasets. For making accurate predictions, two hybrid approaches have been developed—minimization and neural network—to give importance to only those models that are able to model the failure process with good accuracy and then combine the predictions of them to get good results in forecasting failures across all datasets. These models once trained on the dataset are
Mahdev, Akash Ravishankar, Lal, Vinayak, Muralimohan, Pramod, Reddy, Hemanjaneya, Mathur, Rachit
Technical Paper
Model Based NVH Simulator for Virtual Development2025-01-005905/05/2025
For mature virtual development, enlarging coverage of performances and driving conditions comparable with physical prototype is important. The subjective evaluation on various driving conditions to find abnormal or nonlinear phenomena as well as objective evaluation becomes indispensable even in virtual development stage. From the previous research, the road noise had been successfully predicted and replayed from the synthesis of system models. In this study, model based NVH simulator dedicated to virtual development have been implemented. At first, in addition to road noise, motor noise was predicted from experimental models such as blocked force and transfer function of motor, mount and body according to various vehicle conditions such as speed and torque. Next, to convert driver’s inputs such as acceleration and brake pedal, mode selection button and steering wheel to vehicle’s driving conditions, 1-D performance model was generated and calibrated. Finally, the audio and visual
Park, Sangyoung, Dirickx, Tom, Kang, Yeon June, Nam, Jeong Min, Gonçalves, Vinícius Valencia
Technical Paper
Designing Rubber Flaps for Resonance Management: High-Frequency Tuning in Electric Vehicles Using AI/ML Approaches2025-01-012505/05/2025
High-frequency whine noise in electric vehicles (EVs) is a significant issue that impacts customer perception and alters their overall view of the vehicle. This undesirable acoustic environment arises from the interaction between motor polar resonance and the resonance of the engine mount rubber. To address this challenge, the proposal introduces an innovative approach to predicting and tuning the frequency response by precisely adjusting the shape of rubber flaps, specifically their length and width. The approach includes the cumulation of two solutions: a precise adjustment of rubber flap dimensions and the integration of ML. The ML model is trained on historical data, derived from a mixture of physical testing conducted over the years and CAE simulations, to predict the effects of different flap dimensions on frequency response, providing a data-driven basis for optimization. This predictive capability is further enhanced by a Python program that automates the optimization of flap
Hazra, Sandip, Khan, Arkadip
Technical Paper
Characterize the Sound Field Generated from a Vehicle Horn by Pellicular Analysis2025-01-005805/05/2025
To predict the sound field produced by a vehicle horn requires a good source representation of it in the full vehicle model. This paper investigates the characterization of a physical vehicle horn by an inverse method called pellicular analysis. To implement this method, firstly an acoustic testing is performed to measure the sound pressure radiated from the horn at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual horn, the locations of each microphone and measured sound pressure data, pellicular analysis is adopted to recover a set of vibration pattern of the virtual horn. The virtual horn and the recovered vibration information are then incorporated in a full vehicle numerical model to simulate its exterior sound field. The validity of this approach is confirmed by comparing the prediction for a horn in a production vehicle to the corresponding physical test which is required to meet the Brazilian regulation CONTRAN 764/2018.
Yang, Wenlong, Melo, Andre
Technical Paper
Leveraging User Feedback to Optimize the Tuning of EVSE Models2025-01-002005/05/2025
The implementation of active sound design models in vehicles requires precise tuning of synthetic sounds to harmonize with existing interior noise, driving conditions, and driver preferences. This tuning process is often time-consuming and intricate, especially facing various driving styles and preferences of target customers. Incorporating user feedback into the tuning process of Electric Vehicle Sound Enhancement (EVSE) offers a solution. A user-focused empirical test drive approach can be assessed, providing a comprehensive understanding of the EVSE characteristics and highlighting areas for improvement. Although effective, the process includes many manual tasks, such as transcribing driver comments, classifying feedback, and identifying clusters. By integrating driving simulator technology to the test drive assessment method and employing machine learning algorithms for evaluation, the EVSE workflow can be more seamlessly integrated. But do the simulated test drive results
Hank, Stefan, Kamp, Fabian, Gomes Lobato, Thiago Henrique
Technical Paper
A Review on Electric Vehicle NVH Challenges and Recent Trends2025-01-004205/05/2025
Electric vehicles (EVs) present a distinct set of challenges in noise, vibration, and harshness (NVH) compared to traditional internal combustion engine (ICE) vehicles. As EVs operate with significantly reduced engine noise, other sources of noise, such as motor whine, power electronics, and road and wind noise, become more noticeable. This review paper explores the key NVH issues faced by EVs, including high-frequency tonal noise from electric motors, gear meshing, and vibrations. Additionally, it examines recent advancements and trends in NVH mitigation techniques, such as active noise control, improved material insulation, and advanced vibration isolation systems. Furthermore, this paper discusses the role of computational tools, simulation technologies, and testing methodologies in predicting and addressing NVH concerns in EVs. By providing an in-depth analysis of the challenges and the latest innovations, this review aims to contribute to the ongoing development of quieter and
Hazra, Sandip, Khan, Arkadip Amitava
Technical Paper
Communication for Smart Charging of Plug-in Electric Vehicles Using Smart Energy Profile 2.0J2847/1_202505 (Current)05/05/2025
This document describes the details of the Smart Energy Profile 2.0 (SEP2.0) communication used to implement the functionality described in the SAE J2836-1 use cases. Each use case subsection includes a description of the function provided, client device requirements, and sequence diagrams with description of the steps. Implementers are encouraged to consult the SEP2.0 schema and application specification for further details. Where relevant, this document notes, but does formally specify, interactions between the vehicle and vehicle operator.
Hybrid - EV Committee
Recommended Practice
Evaluating Vibration Test Profiles for Battery Electric and Hybrid Vehicles2025-01-000905/05/2025
As the automotive industry transitions to electrification, understanding the differences in ambient operating vibration environments between conventional internal combustion engine (ICE) propulsion systems, battery electric vehicles (BEVs), and hybrid electric vehicles (HEVs) becomes increasingly important. Many automotive vibration testing standards provide frequency and amplitude test levels based on historical ICE vehicle data. Some standards note the potential inaccuracies of using this data source to test BEVs/HEVs and recommend using field-recorded data, if possible, while others make no note. Preliminary comparisons of BEV, HEV, and ICE vehicle ambient operating vibration environments show variations due to battery cell pack weight and engine vibration, among other factors. As accurate testing is tantamount to vehicle safety and longevity, the automotive testing industry must confirm the suitability of current test standards for BEVs and HEVs or create new ones. This paper
Achatz, Tom, Stoll, Cherie
Technical Paper
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