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Electronic Control Units for Enhanced Safety and Monitoring

2025-01-5040

07/03/2025

The rapid evolution of electric vehicles (EVs) necessitates advanced electronic control units (ECUs) for enhanced safety, monitoring, and performance. This study introduces an innovative ECU system designed with a modular architecture, incorporating real-time monitoring, cloud connectivity, and crash sensing. The methodology includes cost-effective design strategies, integrating STM32 controllers, CAN bus systems, and widely available sensors for motor RPM and temperature monitoring. Key findings demonstrate that the proposed ECU system improves data reliability, enhances vehicle safety through crash response systems, and enables predictive maintenance via cloud connectivity. This scalable and affordable ECU is adaptable to a broad range of EV models.

Padma Priya, S.R., Santhipkumar, S., Sasipriya, S., Srivisweswara, M.S.

SAE TOMORROW TODAY - Smarter Automotive Testing with AI and Simulation

1352207/03/2025

The new test track isn't asphalt--it's AI and simulation. From hardware-in-the-Loop (HIL) to real-time performance analytics, new innovations are reshaping how vehicles are designed, validated, and brought to market. At the forefront of this transformation is A&D Technology, a leader in integrated test automation and lab management solutions for the transportation and energy markets. By integrating AI-driven analytics with high-fidelity simulation environments, the company is empowering automotive engineers to streamline testing workflows, reduce physical prototypes, and accelerate innovation in everything from EV powertrains to autonomous systems. To learn more, we sat down with Mike Uhl, President & CEO, to discuss how A&D Technology's work in simulation and test automation is helping engineers bring the next generation of mobility technologies to life. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget

Hineman, Marcie

Variable Valve Actuation and Multiple Injections to Enhance the Gas Exchange of a Passive Pre-Chamber Igniter

2025-01-0315

07/02/2025

Pre-chambers, in general, represent an established technology for combustion acceleration by increasing the available ignition energy. Realizing rapid fuel conversion facilitates mixture dilution extension with satisfying combustion stability. More importantly, knock-induced spark retarding can be circumvented, thus reducing emissions and increasing efficiency at high engine loads. Adapted valve actuation and split injections were investigated for this study to enhance the gas exchange of a passive pre-chamber igniter in a single-cylinder engine. The findings support the development of passive pre-chamber ignition systems operable over the whole engine map for passenger vehicles. There are two configurations of pre-chamber igniters: passive pre-chambers and scavenged pre-chambers. This study focuses on the passive design, incorporating an additional small volume around the spark plug into the cylinder head. Hot jets exit this volume after the ignition onset through several orifices

Fellner, Felix, Härtl, Martin, Jaensch, Malte

U-Shift IV: Innovations and Challenges in Autonomous Urban Mobility

2025-01-0284

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

Design and Analysis of a Battery Thermal Management System for Fast Charging in Extreme Hot Condition

2025-01-0322

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

Applying Real World Traffic Data on Machine Learning Methods for Graph Based Cooperation Strategies of Automated Vehicles

2025-01-0286

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

Theory behind a Novel Method for the Quantification of Subjective Ride Comfort Phenomena

2025-01-0267

07/02/2025

In the automotive development process objective criteria are commonly used to evaluate the full vehicle ride comfort of vehicles. Based on these characteristics, vehicle concepts can be evaluated and compared at an early stage without using physical prototypes. Usually, these characteristics are determined in subjective studies using real vehicles. However, limitations in the implementation of vehicle variants, the controllability of external influences and longer intervals between the individual assessments have a negative impact on the quality of results using these approaches. Therefore, this paper presents an improved method to transfer the subjective perception and evaluation of ride comfort phenomena to objective characteristics. The corresponding procedure is shown on the basis of a one-dimensional, periodic phenomenon that is transferred to a frequency-dependent weighting function. In this process, a 6-degree of freedom driving simulator is used to overcome the limitations

Stroesser, Simon, Angrick, Christian, Zwosta, Tobias, Neubeck, Jens, Wagner, Andreas

Enhancing Flexibility of Automotive Embedded Software: A Modular Reference Architecture

2025-01-0282

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

Modular Thermal Management Framework for Electric Drive System Development

2025-01-0262

07/02/2025

The automotive industry is undergoing a major shift from internal combustion engines to hybrid and battery electric vehicles, 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 machines, power

Notz, Fabian, Sturm, Axel, Sander, Marcel, Kässens, Christoph, Henze, Roman

In Situ Observation of Different Soot Layers in a Model Filter Channel during Its Regeneration

2025-01-0312

07/02/2025

In order to comply with increasingly stringent emission regulations and ensure clean air, wall-flow particulate filters are predominantly used in exhaust gas aftertreatment systems of combustion engines to remove reactive soot and inert ash particles from exhaust gases. These filters consist of parallel porous channels with alternately closed ends, effectively separating particles by forming a layer on the filter surface. However, the accumulated particulate layer increases the pressure drop across the filter, requiring periodic filter regeneration. During regeneration, soot oxidation breaks up the particulate layer, while resuspension and transport of individual agglomerates can occur. These phenomena are influenced by gas temperature and velocity, as well as by the dispersity and reactivity of the soot particles. Renewable and biomass based fuels can produce different types of soot with different reactivities and dispersities. Therefore, this study focuses on the influences of soot

Desens, Ole, Hagen, Fabian P., Meyer, Jörg, Dittler, Achim

Experimental and Numerical Analysis of Direct Injection Process for Hydrogen-Fuelled Internal Combustion Engines

2025-01-0307

07/02/2025

In the context of the clean transport sector, there has been growing interest in the use of hydrogen in internal combustion engines due to its potential to nearly eliminate all engine-out criteria pollutants, while maintaining high thermal efficiency through the use of a lean combustion process. In direct injection configurations, mixing process is significantly influenced by hydrogen jet dynamics. First, a comprehensive experimental campaign was conducted in a constant volume vessel to assess the performance of a hydrogen injector using the Schlieren technique. The jet behavior was analyzed by varying injector recess, injection pressure, and back pressure. Subsequently, the case study was replicated in a 3D Computational Fluid Dynamics (CFD) environment, addressing the complexities associated with modeling under-expanded jets. The model was first validated against experimental data, both in terms of jet morphology and through three geometric indices. Then, a simplified simulation

Pucillo, Francesco, Piano, Andrea, Millo, Federico, Giordana, Sergio, Rapetto, Nicola, Vargiu, Luca

Experimental Investigation of Factors Influencing Thermal Runaway in Lithium-Ion Battery Cells

2025-01-0306

07/02/2025

Experimental testing in automotive development sometimes relies on ad hoc approaches like ‘One Factor at a Time’, particularly in time- and resource-limited situations. While widely used, these approaches are limited in their ability to systematically capture parameter interactions and system complexities, which poses significant challenges in safety-critical applications like high-voltage battery systems. This study systematically investigates the factors influencing thermal runaway in lithium-ion battery cells using a statistical full-factorial experimental design. Key parameters, including state of charge, cell capacity and heating trigger power, have been analyzed under controlled conditions with an autoclave setup, enabling precise measurement of thermal and mechanical responses. The use of automotive-grade lithium-ion cells ensures relevance for next-generation applications. By employing factorial regression and statistical analysis, the study identifies critical temperatures

Ceylan, Deniz, Kulzer, André Casal, Winterholler, Nina, Weinmann, Johannes, Schiek, Werner

Optimisation of Rotor Skewing of a Yokeless and Segmented Armature Axial Flux Machine

2025-01-0311

07/02/2025

This paper presents an optimisation approach for rotor skewing in a Yokeless and Segmented Armature (YASA) design Axial Flux Machine (AFM) for electric vehicle applications. Torque ripple amplitudes are a critical factor influencing the noise, vibration and harshness (NVH) behaviour of electric motors. The focus of this paper is to reduce the torque ripple amplitudes of the dominant harmonics over the entire torque-speed characteristic of the AFM. The principle of the proposed approach is a segmented permanent magnet configuration of the AFM, where individual magnet segments can be circumferentially shifted to achieve optimal skewing configurations. Initial optimisations are performed using 2D finite element (FE) simulations, modelled as linear motors with multiple slices and different numbers of magnet segmentation. However, the accuracy of the 2D FE results is limited due to the lack of interaction between the individual segments and the insufficient representation of three

Müller, Karsten, Maisch, Hannes, De Gersem, Herbert, Burkhardt, Yves

Towards Change-Aware Testing of Multi-Domain Cyber-Physical Systems: Challenges and Future Directions

2025-01-0296

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

Method for Externally Controlled Availability of Lubricating Oil in Internal Combustion Engines

2025-01-0302

07/02/2025

Reduced raw emissions from internal combustion engines (ICE) are a key requirement to reach future green-house-gas and pollutive emissions regulations. In parallel, to satisfy the need for increased engine efficiencies, the friction losses of ICEs gains attention. Measures to reduce parasitic drag inside the piston assembly such as reduced piston-ring pretension or thinner grade engine oils may increase oil ingress into the combustion chamber. The oil ingress is known to imply increased particle emissions directly counteracting the raw emission reduction target of engine development. To resolve this target conflict, the transport mechanisms of oil into the combustion chamber are the topic of current research. Specially developed research engines featuring a vertical optical window come with big potential to visualize the phenomena of the oil behavior inside the piston assembly group. Such ‘glass-liner’ engines play a pivotal role in identification and quantification of local and global

Stark, Michael, Fellner, Felix, Härtl, Martin, Jaensch, Malte

Numerical Analysis of Direct-Injection and Combustion Inside a H2 Engine

2025-01-0301

07/02/2025

The direct injection of hydrogen (H2) inside internal combustion engines (ICEs) is gaining large research interest over the port-fuel injection strategy, because of several advantages as higher volumetric efficiencies, increased power output and reduced risks of abnormal combustion. However, the required high pressure ratios across the injector nozzle produce moderate-to-high under-expanded jets, characterized by complex flow structures. This poses a challenge for the numerical modelling of the mixture preparation by means of 3D computational fluid dynamics (CFD) approaches. In this work, a validated 3D-CFD methodology has been employed to simulate the closed-valve cycle of a direct injection H2 engine equipped with a centrally mounted hollow-cone injector and a non-axisymmetric piston bowl. First, injection and mixture preparation have been studied considering an early injection at the beginning of the compression stroke, and a delayed injection in the second half of the compression

Capecci, Marcolucio, Sforza, Lorenzo, Lucchini, Tommaso, D'Errico, Gianluca, Pezza, Vincenzo, Tosi, Sergio

Requirements, Methods and Models for Early Electrified Drive Concept Development

2025-01-0304

07/02/2025

Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of drive system properties. Estimating these properties in the early stages of development is challenging due to the depth of modelling required. In addition, defined requirements play a critical role in drive system sizing. This paper presents a tool chain for the synthesis of new electrified drive concepts, with emphasis on requirements definition and modelling. The requirements definition method combines market analysis with a generalized calculation and estimation approach, providing a novel perspective. In addition, we introduce mass and cost modelling capabilities integrated into the tool chain. The mass model achieves high accuracy, with deviations of only 1.6 % at the vehicle level and 6.1 % at the component level. Finally, the paper examines the mass and cost

Sturm, Axel, Henze, Roman

Inductance Estimation of an Electric Vehicle

2025-01-0293

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. [1, 2] 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 4.5 hours of drive. [3] Therefore, higher charging powers were needed, and the Megawatt Charging System (MCS) standard was developed. The voltage level goes up to 1250 V and currents of 3000 A are defined. [4] 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

Grund, Caroline, Reuss, Hans-Christian

Impact of the Distribution of Charging and Hydrogen Refueling Stations on their Reachability for Craft Vehicles with a Defined Usage Profile

2025-01-0310

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

A Modular Framework for Lateral Movement Modeling

2025-01-0269

07/02/2025

The lateral movement of vehicles within their lane determines occurring occlusions, and thus decides on the range of vision of vehicle sensors used by automated driving functions, and the objects detected by down-stream algorithms. As simulations play an integral role in the validation of automated driving functions, their ability to realistically model the lateral movement is crucial. However, currently applied methods such as microscopic traffic simulations, and scenario-based testing making use of maneuver-based scenario descriptions simplify or neglect the lateral movement of vehicles. For that reason, a two-level stochastic model has been introduced in earlier work. It consists of a Markov model for the systematic coarse movement, and a noise model for the residual fine movement. In follow-up publications, several advancements for both model components have been presented. These follow a modular structure, thus, can be flexibly combined. This paper for the first time gives an

Neis, Nicole, Beyerer, Jürgen

Data-Driven Analysis of Vehicle Lateral Control in the Country Road Domain

2025-01-0268

07/02/2025

The optimization and further development of automated driving functions offer significant potential for reducing the driver's workload and increasing road safety. Among these functions, vehicle lateral control plays a critical role, especially with regard to its acceptance by end customers. Significant development efforts are required to ensure the effectiveness and reliability of this aspect in real-world conditions. This work focuses on analyzing lateral vehicle control using extensive measurement data collected from a dedicated vehicle fleet at the Institute of Automotive Engineering at the Technical University of Braunschweig. Equipped with state-of-the-art measurement technology, the fleet has driven several hundred thousand kilometers, allowing for the collection of detailed information on vehicle trajectories under various driving conditions. A total of 93 participants, aged between 20 and 43 years, contributed to the dataset. These measurements have been classified into

Iatropoulos, Jannes, Panzer, Anna, Arntz, Martin, Prueggler, Adrian, Henze, Roman

An LLM-Based Multi-Turn Task-Oriented Dialogue System for Machine Learning Algorithm Selection in Data Mining

2025-01-0289

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

DISRUPT - Decentralized Intelligent System for Road User Prediction and Tracking

2025-01-0294

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 state estimates are communicated in such a way that they can augment local estimates from other sensor boxes and/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 models and a measure of a road user's risk of being involved in

Beutenmüller, Frank, Brostek, Lukas, Doberstein, Christian, Han, Longfei, Kefferpütz, Klaus, Obstbaum, Martin, Pawlowski, Antonia, Rössert, Christian, Sas-Brunschier, Lucas, Schön, Thilo, Sichermann, Jörg

Leveraging AI for Automated Code Generation from Systems Engineering Specifications

2025-01-0295

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 novel 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

Exploring the Correlation between Physiological States and Driving Behavior on Highways with Integrated ECG Measurements

2025-01-0292

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 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 electrocardiography (ECG) data, from human drivers to examine the relationship between physiological states and driving behaviors. The aim was to determine whether ECG can serve as an indicator of potential risky driving behaviors, such as sudden acceleration and frequent steering adjustments. This information enables automated driving (AD) systems to intervene in dangerous

Ji, Dejie, Flormann, Maximilian, Bollmann, Julian, Henze, Roman, Deserno, Thomas M.

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