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The hydrogen engine is one of the promising technologies that enables carbon-neutral mobility, especially in heavy-duty on- or off-road applications. In this paper, a methodological procedure for the design of the combustion system of a hydrogen-fueled, direct injection spark ignited commercial vehicle engine is described. In a preliminary step, the ability of the commercial 3D computational fluid dynamics (CFD) code AVL FIRE classic to reproduce the characteristics of the gas jet, introduced into a quiescent environment by a dedicated H2 injector, is established. This is based on two parts: Temporal and numerical discretization sensitivity analyses ensure that the spatial and temporal resolution of the simulations is adequate, and comparisons to a comprehensive set of experiments demonstrate the accuracy of the simulations. The measurements used for this purpose rely on the well-known schlieren technique and use helium as a safe substitute for H2.

This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

Under the proposed Green Deal program, the European Union will aim to achieve zero net greenhouse gas (GHG) emissions by 2050. The interim target is to reduce GHG by 55% by 2030. In the current debate concerning CO2-neutral powertrains, bio-fuels and e-fuels could play an immediate and practical role in reducing lifecycle engine emissions. Hydrogen however, is one of the few practical fuels that can result in near zero CO2 emissions at the tailpipe, which is the main focus of current legislation. Compared to gasoline, hydrogen presents a higher laminar flame speed, a wider range of flammability and higher auto-ignition temperatures, making it among the most attractive of fuels for future engines. As a challenge, hydrogen requires a very low ignition energy. This may imply an increased susceptibility to Low Speed Pre-Ignition (LSPI), surface ignition and back-fire phenomena. In order to exploit hydrogen’s potential, the injection system plays an extremely important role.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

The accelerated processes in vehicle development require new technologies for function development and validation. With this motivation, Function-in-the-Loop (FiL) simulation was developed as a link between Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) simulation. The combination of real Electronic Control Unit (ECU) hardware and software in conjunction with virtual components is very well suited for function development and testing. This approach opens up new possibilities for mechatronic systems that would otherwise require special test benches. For this reason, an Electric Power Steering (EPS) was transferred to a virtual environment using FiL simulation. This enables a wide range of applications, from EPS testing to the development of connected driving functions on an integrated platform. Right from the early development phases, the technology can be used purposefully with short integration cycles.

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

The reduction of both harmful emissions (CO, HC, NOx, etc.) and gases responsible for greenhouse effects (especially CO2) are mandatory aspects to be considered in the development process of any kind of propulsion concept. Focusing on ICEs, the main development topics are today not only the reduction of harmful emissions, increase of thermodynamic efficiency, etc. but also the decarbonization of fuels which offers the highest potential for the reduction of CO2 emissions. Accordingly, the development of future ICEs will be closely linked to the development of CO2 neutral fuels (e.g. biofuels and e-fuels) as they will be part of a common development process. This implies an increase in development complexity, which needs the support of engine simulations. In this work, the virtual modeling of real fuel behavior is addressed to improve current simulation capabilities in studying how a specific composition can affect the engine performance.

Large Eddy Simulations (LES) and tracer-based Laser-Induced Fluorescence (LIF) measurements were performed to study the dynamics of fuel wall-films on the piston top of an optically accessible, four-valve pent-roof GDI research engine for a total of eight operating conditions. Starting from a reference point, the systematic variations include changes in engine speed (600; 1,200 and 2,000 RPM) and load (1000 and 500 mbar intake pressure); concerning the fuel path the Start Of Injection (SOI=360°, 390° and 420° CA after gas exchange TDC) as well as the injection pressure (10, 20 and 35 MPa) were varied. For each condition, 40 experimental images were acquired phase-locked at 10° CA intervals after SOI, showing the wall-film dynamics in terms of spatial extent, thickness and temperature.

The current trend in automobiles is towards electrical vehicles, but for the most part these vehicles still require an internal combustion engine to provide additional range and flexibility. These engines are under stringent emissions regulations, in particular, for the reduction of CO2. Gas engines which run lean burn combustion systems provide a viable route to these emission reductions, however designing these engines to provide sustainable and controlled combustion under lean conditions at λ=2.0 is challenging. To address this challenge, it is possible to use a scavenged Pre-Chamber Ignition (PCI) system which can deliver favorable conditions for ignition close to the spark plug. The lean charge in the main combustion chamber is then ignited by flame jets emanating from the pre-chamber nozzles. Accurate prediction of flame kernel development and propagation is essential for the analysis of PCI systems.

Over the past years, the question as to what may be the powertrain of the future has become ever more apparent. Aiming to improve upon a given technology, the internal combustion engine still offers a number of development paths in order to maintain its position in public and private mobility. In this study, an innovative combustion process is investigated with the goal to further approximate the ideal Otto cycle. Thus far, similar approaches such as Homogeneous Charge Compression Ignition (HCCI) shared the same objective yet were unable to be operated under high load conditions. Highly increased control efforts and excessive mechanical stress on the components are but a few examples of the drawbacks associated with HCCI. The approach employed in this work is the so-called Spark Assisted Compression Ignition (SACI) in combination with a pre-chamber spark plug, enabling short combustion durations even at high dilution levels.

Model guided application (MGA) combining physico-chemical internal combustion engine simulation with advanced analytics offers a robust framework to develop and test particle number (PN) emissions reduction strategies. The digital engineering workflow presented in this paper integrates the kinetics & SRM Engine Suite with parameter estimation techniques applicable to the simulation of particle formation and dynamics in gasoline direct injection (GDI) spark ignition (SI) engines. The evolution of the particle population characteristics at engine-out and through the sampling system is investigated. The particle population balance model is extended beyond soot to include sulphates and soluble organic fractions (SOF). This particle model is coupled with the gas phase chemistry precursors and is solved using a sectional method. The combustion chamber is divided into a wall zone and a bulk zone and the fuel impingement on the cylinder wall is simulated.

The introduction of new emission legislation and the demand of increased power for small two-wheelers lead to an increase of technical requirements. Especially for single cylinder engines with high compression ratio the transient behavior close to idling is challenging. The demand for two-wheeler specific responsiveness of the vehicle requires low overall rotational inertia as well as small intake manifold volumes. The combination with high compression ratio can lead to a stalling of the engine if the throttle opens and closes very quickly in idle operation. The fast opening and closing of the throttle is called a throttle blip. Fast, in this context, means that the blipping event can occur in one to two working cycles. Previous work was focused on the development of a procedure to apply reproducible blipping events to a vehicle in order to derive a deeper physical understanding of the stalling events.

The heat transfer process in a reciprocating engine is dominated by forced convection, which is drastically affected by mean flow, turbulence, flame propagation and its impingement on the combustion chamber walls. All these effects contribute to a transient heat flux, resulting in a fast-changing temporal and spatial temperature distribution at the surface of the combustion chamber walls. To quantify these changes in combustion chamber surface temperature, surface temperature measurements on the piston of a single cylinder diesel engine were taken. Therefore, thirteen fast-response thermocouples were installed in the piston surface. A wireless microwave telemetry system was used for data transmission out of the moving piston. A wide range of parameter studies were performed to determine the varying influences on the surface temperature of the piston.

Due to the new CO2 targets for vehicles, electrification of powertrains and operation strategies for electrified powertrains have drawn more attention. This article presents a predictive multi-objective operation strategy for hybrid electric vehicles (HEVs), which simultaneously minimizes the fuel consumption and the cycle aging of traction batteries. This proposed strategy shows better performance by using predictive information and high robustness to inaccuracy of predictive information. In this work, the benefits of the developed operation strategies are demonstrated in a strong hybrid electric vehicle (sHEV) with P2-configuration. For the cycle aging of a lithium-ion battery, an empirical model is built up with Gaussian processes based on experimental data.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

Battery electric vehicles (BEVs) are equipped with Mobile Air Conditioning systems (MACs) to ensure a comfortable cabin temperature in all climates and ambient conditions as well as the optional conditioning of the traction battery. An assessment of the global electrical energy consumption of various MACs has been derived, where the basis of the assessment procedure is the climate data GREEN-MAC-LCCP 2007 (Global Refrigerants Energy & Environmental - Mobile Air Condition - Life Cycle Climate Performance) and the improved LCCP2013 (Life Cycle Climate Performance. The percentage driving time during 6 AM and 24 PM is divided into six different temperature bins with the solar radiation and relative humidity for 211 cities distributed over Europe, North, Central, and South America, Asia, South West Pacific, and Africa. The energy consumption of the MACs is determined by a thermal vehicle simulation. In this work, four different MACs are simulated and compared.

The fuel spray behavior in the near nozzle region of a gasoline injector is challenging to predict due to existing pressure gradients and turbulences of the internal flow and in-nozzle cavitation. Therefore, statistical parameters for spray characterization through experiments must be considered. The characterization of spray velocity fields in the near-nozzle region is of particular importance as the velocity information is crucial in understanding the hydrodynamic processes which take place further downstream during fuel atomization and mixture formation. This knowledge is needed in order to optimize injector nozzles for future requirements. In this study, the results of three experimental approaches for determination of spray velocity in the near-nozzle region are presented. Two different injector nozzle types were measured through high-speed shadowgraph imaging, Laser Doppler Anemometry (LDA) and X-ray imaging.