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The scope of this SAE performance standard is to provide a simple, practical, and broadly applicable test procedure for appraising luminous Illuminant A reflectance of reflecting safety glazing materials for road vehicles. This SAE performance standard, which provides a simple test procedure widely used in the optics field, may be used to measure the reflectivity which films applied to safety glazing materials for road vehicles may enhance. This test procedure applies to conditions where feasibility, rather than accuracy of measurement, is of prime importance. Measurements can be made outside laboratories in a quality control environment and in similar applications, when glazings, instead of small test specimens, have to be tested.
Glazing Materials Standards Committee
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.
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, SandraHahn, MichaelWeyrich, MichaelMorozov, Andrey
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, FabianSturm, AxelSander, MarcelKässens, ChristophHenze, Roman
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, DominikKrost, JonathanMeywerk, MartinCzarnetzki, Walter
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, HenrikMeywerk, MartinHellberg, Tobias
The design, development, and optimization of modern suspension systems is a complex process that encompasses several different engineering domains and disciplines such as vehicle dynamics simulation, tire data analysis, 1D lap-time simulation, 3D CAD design and structural analysis including full 3D collision detection. Typically, overall vehicle design and suspension development are carried out in multiple iterative design loops by several human specialists from diverse engineering departments. Fully automating this iterative design process can minimize manual effort, eliminate routine tasks and human errors, and significantly reduce design time. This desired level of automation can be achieved through digital modeling, automated model generation, and simulation using graph-based design languages and an associated language compiler for translation and execution. Graph-based design languages ensure the digital consistency of data, the digital continuity of processes, and the digital
Borowski, JulianRudolph, Stephan
The primary approach to meet the objectives of the EU Heavy Duty CO2 Regulation involves decarbonizing the road transport sector by battery electric vehicles (BEV) or hydrogen-fueled vehicles. Even though the well-to-wheel efficiency of hydrogen-fueled powertrains like fuel cell electric vehicles (FCEV) and H2-internal combustion engines (H2-ICE) is much lower in comparison to BEV, they are better suited for on-road heavy-duty trucks, long haul transport missions and regions with scarce charging infrastructure. Hence, this paper focuses on heavy-duty FCEVs and their overall energetic efficiency enhancement by intelligently managing energy transfer across coolant circuit boundaries through waste heat recovery, while ensuring that all relevant components remain within required temperature boundaries under both cold and hot ambient conditions. Results were obtained using a 1D-model that comprises all thermal fluid circuits (refrigerant, coolant, air) created through GT-Suite software
Uhde, SophiaLanghorst, ThorstenWuest, MarcelNaber, Dirk
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, SimonAngrick, ChristianZwosta, TobiasNeubeck, JensWagner, Andreas
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, DennisZhai, YiCaggiano, MarioFuchss, Thomas
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, FelixHärtl, MartinJaensch, Malte
In order to mitigate the effects of climate change, the global transport sector, one of the largest emitters of CO2, needs to drastically reduce its emissions. Although hybridization and electrification are becoming increasingly popular as a solution for a variety of applications, their use in two- and three-wheelers, as well as in recreational and powersports vehicles, remains limited due to their high costs and complexity compared to conventional drivetrains with continuously variable transmissions (CVTs). Despite their affordability and simplicity, CVTs suffer from low mechanical efficiency, with transmission losses ranging from 20–50 %, highlighting a significant opportunity for improvement. In response to these limitations, this study presents the development and experimental evaluation of an electrified planetary gear set (ePGS) in a lightweight off-road vehicle. It is designed to overcome the efficiency limitations of CVTs while maintaining high driving comfort and low system
Jakoby, MoritzEngels, MichaelFahrbach, TimmAndert, Jakob
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, MichaelWodtko, ThomasSchumann, OliverAuthaler, Dominik
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, ReneHenke, Markus
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, MarcolucioSforza, LorenzoLucchini, TommasoD'Errico, GianlucaPezza, VincenzoTosi, Sergio
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, AxelHenze, Roman
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, CarolineReuss, Hans-Christian
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, OliverMüller, JulianHeinrich, MarcoCortès, SvenSchlick, MichaelKulzer, André Casal
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, StefanBause, KatharinaAlbers, Albert
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, NicoleBeyerer, Jürgen
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, ManojDenev, Jordan A.Bockhorn, HenningTrimis, DimosthenisKoch, ThomasDebus, CharlotteGötz, MarkusZirwes, ThorstenHagen, Fabian P.Tofighian, HesamWagner, UweBraun, SamuelLanzer, TheodorKnapp, Sebastian M.
To achieve a significant reduction in net CO₂ emissions in the aviation sector, sustainable aviation fuels (SAFs) are considered a key factor. Current research efforts are therefore focused on SAFs, which exhibit properties that differ from conventional kerosene, particularly in aspects critical to compression-ignition (CI) engines, such as cetane number, evaporation behavior or lubricity. These differences necessitate dedicated investigations to assess their suitability and performance in such engines. However, real operating conditions — such as intake air- and exhaust- pressure levels during flight — cannot be fully replicated on standard engine test benches. For this reason, real flight experiments were conducted to address these limitations. Notably, this work marks the first instance of in-flight testing of SAFs in CI aviation engines, constituting a significant milestone in this research area. In the course of these investigations, ASTM D7566 Annex A2-compliant HEFA
Kleissner, FlorianReitmayr, ChristianHofmann, Peter