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Synthetic fuels for internal combustion engines offer CO2-neutral mobility if produced in a closed carbon cycle using renewable energies. C1-based synthetic fuels can offer high knock resistance as well as soot free combustion due to their molecular structure containing oxygen and no direct C-C bonds. Such fuels as, for example, dimethyl carbonate (DMC) and methyl formate (MeFo) have great potential to replace gasoline in spark-ignition (SI) engines. In this study, a mixture of 65% DMC and 35% MeFo (C65F35) was used in a single-cylinder research engine to determine friction losses in the piston group using the floating-liner method. The results were benchmarked against gasoline (G100). Compared to gasoline, the density of C65F35 is almost 40% higher, but its mass-based lower heating value (LHV) is 2.8 times lower. Hence, more fuel must be injected to reach the same engine load as in a conventional gasoline engine, leading to an increased cooling effect.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

Pilot injection gas engines are commonly used as large stationary engines. Often, the combustion is implemented as a dual-fuel strategy, which allows both mixed and diesel-only operation, based on a diesel engine architecture. The current research project focuses on the application of pilot injection in an engine based on gasoline components of the passenger car segment, which are more cost-effective than diesel components. The investigated strategy does not aim for a diesel-only combustion, hence only small liquid quantities are used for the main purpose of providing a strong, reliable ignition source for the natural gas charge. This approach is mainly driven to provide a reliable alternative to the high spark ignition energies required for high cylinder charge densities. When using such small liquid quantities, a standard common-rail diesel nozzle will apparently not be ideal regarding some general specifications.

A new artificial intelligence (model order reduction) / finite element coupled approach will be presented for the risk assessment of battery fire during a car crash event. This approach combines standard crash finite element for the main car body with a reduced order model for the battery. Simulation is today used by automotive engineering teams to design lightweight vehicle bodies fulfilling vehicle safety regulations. Legislation is rapidly evolving to accommodate the growing electrical vehicle market share and is considering additional battery safety requirements. The focus is on avoiding internal short circuit due to internal damage within a cell which may result in a fire hazard. Assessing short circuit risk in CAE at the vehicle level is complex as there involves phenomena at different scales. The vehicle deforms on a macroscale level during the impact event.

Autonomous driving systems and connected mobility are the next big developments for the car manufacturers and their suppliers during the next decade. To achieve the high computing power needs and fulfill new upcoming requirements due to functional safety and security, heterogeneous processor architectures with a mixture of different core architectures and hardware accelerators are necessary. To tackle this new type of hardware complexity and nevertheless stay within monetary constraints, high performance computers, inspired by state of the art data center hardware, could be adapted in order to fulfill automotive quality requirements. The European Processor Initiative (EPI) research project tries to come along with that challenge for next generation semiconductors. To be as close as possible to series development needs for the next upcoming car generations, we present a hybrid semiconductor system-on-chip architecture for automotive.

External Exhaust Gas Recirculation (EGR) provides an opportunity to increase the efficiency of turbocharged spark-ignition engines. Of the competing technologies and configurations, Low-Pressure EGR (LP-EGR) is the most challenging in terms of its dynamic behavior. Only some of the stationary feasible potential can be used during dynamic engine operation. To guarantee fuel consumption-optimized engine operation with no instabilities, a load point-dependent limitation of the EGR rate or alternatively an adaptation of the operating point to the actual EGR rate is crucial. For this purpose, a precise knowledge of efficiency and combustion variance is necessary. Since the operating state includes the actual EGR rate, it has an additional dimension, which usually results in an immense measuring effort.

From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.

Current regulatory developments aim for stricter emission limits, increased environmental protection and purification of air on a local and global scale. In order to find solutions for a cleaner combustion process, it is necessary to identify the critical components and parameters responsible for the formation of emissions. This work provides an evaluation process for particle formation during combustion of a modern direct injection engine, which can help to create new aftertreatment techniques, such as a gasoline particle filter (GPF) system, that are fit for purpose. With the advent of “real driving emission” (RDE) regulations, which include market fuels for the particulate number testing procedure, the chemical composition and overall quality of the fuel cannot be neglected in order to yield a comparable emission test within the EU and worldwide.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Hybrid-electric vehicles provide additional functionality compared to conventional vehicles. So-called ‘hybrid’ software functions are required to coordinate the conventional powertrain control and these additional control functions. A key factor to reduce the fuel consumption lies in optimal control of the entire interconnected powertrain. This paper aims to provide a framework for efficient interface definition, connection and coordination of control units for hybrid electric vehicles. Such a framework supports an efficient development of control unit architectures and the distribution of software functions. The generic approach necessitates modular software functions. It defines the distribution of these functions in control units optimized with respect to reuse, interfaces and compatibility with different powertrain topologies and electrification variants, especially also considering compatibility with a conventional powertrain and its electric hybridization.

Although the ISO 26262 provides requirements and recommendations for an automotive functional safety lifecycle, practical guidance on how to handle these safety activities and safety artifacts is still lacking. This paper provides an overview of a semi-formal safety engineering approach based on SysML for specifying the relevant safety artifacts in the concept phase. Using specific diagram types, different views of the available data can be provided that reflects the specific needs of the stakeholders involved. One objective of this work is to improve the common understanding of the relevant safety aspects during the system design. The approach, which is demonstrated here from the perspective of a Tier1 supplier for an automotive battery system, covers different breakdown levels of a vehicle. The safety workflow presented here supports engineers' efforts to meet the safety standard ISO 26262 in a systematic way.

Optimization of engine warm-up behavior has traditionally made use of experimental investigations. However, thermal engine models are a more cost-effective alternative and allow evaluation of the fuel saving potential of thermal management measures in different driving cycles. To simulate the thermal behavior of engines in general and engine warm-up in particular, knowledge of heat distribution throughout all engine components is essential. To this end, gas-side heat transfer inside the combustion chamber and in the exhaust port must be modeled as accurately as possible. Up to now, map-based models have been used to simulate heat transfer and fuel consumption; these two values are calculated as a function of engine speed and load. To extend the scope of these models, it is increasingly desirable to calculate gas-side heat transfer and fuel consumption as a function of engine operating parameters in order to evaluate different ECU databases.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

Accurate simulation tools are needed for rapid and cost effective engine development in order to meet ever tighter pollutant regulations for future internal combustion engines. The formation of pollutants such as soot and NOx in Diesel engines is strongly influenced by local concentration of the reactants and local temperature in the combustion chamber. Therefore it is of great importance to model accurately the physics of the injection process, combustion and emission formation. It is common practice to approximate Diesel fuel as a single compound fuel for the simulation of the injection and combustion process. This is in many cases sufficient to predict the evolution of the in-cylinder pressure and heat release in the combustion chamber. The prediction of soot and NOx formation depends however on locally component resolved quantities related to the fuel liquid and gas phase as well as local temperature.

The potential to reduce the cost of embedded software by standardizing the application behavior for Automotive Body and Comfort domain functions is explored in this paper. AUTOSAR, with its layered architecture and a standard definition of the interfaces for Body and Comfort application functions, has simplified the exchangeability of software components. A further step is to standardize the application behavior, by developing standard specifications for common Body and Comfort functions. The corresponding software components can be freely exchanged between different OEM/Tier-1 users, even if developed independently by multiple suppliers. In practice, individual OEM users may need to maintain some distinction in the functionality. A method of categorizing the specifications as ‘common’ and ‘unique’, and to configure them for individual applications is proposed. This allows feature variability by means of relatively simple adapter functions.

Nowadays, a continually growing system complexity due to the development of an increasing number of vehicle concepts in a steadily decreasing development time forces the engineering departments in the automotive industry to a deepened system understanding. The virtual design and validation of individual components from subsystems up to full vehicles becomes an even more significant role. As an answer to the challenge of reducing complete hardware prototypes, the virtual competence in NVH, among other methods, has been improved significantly in the last years. At first, the virtual design and validation of objectified phenomena in analogy to hardware tests via standardized test rigs, e.g. four poster test rig, have been conceived and validated with the so called MBS (Multi Body Systems).

The development of hydrogen-fueled vehicles has created the need for established fuel consumption testing methods. Until now the EPA has only accepted three methods of hydrogen fuel consumption testing, gravimetric, PVT (stabilized pressure, volume and temperature), and Coriolis mass flow; all of which necessitate physical measurements of the fuel supply [1]. BMW has developed an equation and subsequent testing methods to accurately and effectively determine hydrogen fuel consumption in light-duty vehicles using only exhaust emissions. Known as “Hydrogen-Balance”, the new equation requires no changes to EPA procedures and only slight modifications to most existing chassis dynamometers and CVS (Constant Volume Sampling) systems. The SAE 2008-01-1036, also written by BMW, explains the background as well as required equipment and changes to the CVS testing system. This paper takes hydrogen balance further by testing it against the three EPA established forms of fuel consumption.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

There is a common understanding that hydrogen has a great potential to be the fuel of the future. In addition to the challenge of developing appropriate hydrogen propulsion systems the development of hydrogen storage systems is the second big issue. Due to its high potential in cost and weight and specific storage capacity, the BMW Group is focusing on the development of liquid hydrogen storage systems. In the next hydrogen 7-Series the BMW Group is about to make for the first time the step from demonstration fleets to cars used by external users with a liquid hydrogen storage system. To realize this significant goal, special focus has to be put on high safety standards so that hydrogen can be considered as safe as common types of fuel, and on the every day reliability of the storage system. Moreover, the development of strong partnerships with suppliers is a key factor to realize the design and identify appropriate manufacturing processes.