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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.

Increasingly stringent tailpipe emissions regulations have prompted renewed interest in catalyst heating technology – where an integrated device supplies supplemental heat to accelerate catalyst ‘light-off’. Bosch and Boysen, following a collaborative multi-year effort, have developed a Rapid Catalyst Heating System (RCH) for gasoline-fueled applications. The RCH system provides upwards of 25 kW of thermal power, greatly enhancing catalyst performance and robustness. Additional benefits include reduction of precious metal loading (versus a ‘PGM-only’ approach) and avoidance of near-engine catalyst placement (limiting the need for enrichment strategies). The following paper provides a technical overview of the Bosch/Boysen (BOB) Rapid Catalyst Heating system – including a detailed review of the system’s architecture, key performance characteristics, and the associated impact on vehicle-level emissions.

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).

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.

Software-in-the-Loop (SiL) test environments are the ideal virtual platforms for enabling continuous-development, -integration, -testing -delivery or -deployment commonly referred as Continuous-X (CX) of the complex functionalities in the current automotive industry. This trend especially is contributed by several factors such as the industry wide standardization of the model exchange formats, interfaces as well as architecture definitions. The approach of frontloading software testing with SiL test environments is predominantly advocated as well as already adopted by various Automotive OEMs, thereby the demand for innovating applicable methods is increasing. However, prominent usage of the existing monolithic architecture for interaction of various elements in the SiL environment, without regarding the separation between functional and non-functional test scope, is reducing the usability and thus limiting significantly the cost saving potential of CX with SiL.

High-pressure gasoline injection can improve combustion efficiency and lower engine-out emissions; however, the spray characteristics of high-pressure gasoline (>500 bar) are not well known. Effects of different injector nozzle geometry on high-pressure gasoline sprays were studied using a constant volume chamber. Five nozzles with controlled internal flow features including differences in nozzle inlet rounding, conicity, and outlet diameter were investigated. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar. The chamber pressure was varied using nitrogen at ambient temperature and pressures of 1, 5, 10, and 20 bar. Spray development was recorded using diffuse backlit shadowgraph imaging methods.

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control aimed at optimizing energy consumption with associated benefits. In this paper, we implement an optimal control framework, developed previously, in an Audi A3 etron plug-in hybrid electric vehicle, and demonstrate that we can improve the vehicle’s efficiency and travel time in a corridor including an on-ramp merging, a speed reduction zone, and a roundabout. Our exposition includes the development, integration, implementation and validation of the proposed framework in (1) simulation, (2) hardware-in-the-loop (HIL) testing, (3) connectivity enabled virtual reality based bench-test, and (4) field test in Mcity. We show that by adopting such inexpensive, yet effective process, we can efficiently integrate and test the control framework, establish proper connectivity and data transmission between different modules of the system, and reduce uncertainty.

This paper presents an experimental investigation of the impact of EGR dilution on the tradeoff between flame and end-gas autoignition heat release in a Spark-Assisted Compression Ignition (SACI) combustion engine. The mixture was maintained stoichiometric and fuel-to-charge equivalence ratio (ϕ′) was controlled by varying the EGR dilution level at constant engine speed. Under all conditions investigated, end-gas autoignition timing was maintained constant by modulating the mixture temperature and spark timing. Experiments at constant intake pressure and constant spark timing showed that as ϕ′ is increased, lower mixture temperatures are required to match end-gas autoignition timing. Higher ϕ′ mixtures exhibited faster initial flame burn rates, which were attributed to the higher laminar flame speeds immediately after spark timing and their effect on the overall turbulent burning velocity.

Safety-critical embedded software has to satisfy stringent quality requirements. One such requirement, imposed by all contemporary safety standards, is that no critical run-time errors must occur. Runtime errors can be caused by undefined or unspecified behavior of the programming language; examples are buffer overflows or data races. They may cause erroneous or erratic behavior, induce system failures, and constitute security vulnerabilities. A sound static analyzer reports all such defects in the code, or proves their absence. Sound static program analysis is a verification technique recommended by ISO/FDIS 26262 for software unit verification and for the verification of software integration. In this article we propose an analysis methodology that has been implemented with the static analyzer Astrée. It supports quick turn-around times and gives highly precise whole-program results.

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 success of model-based ECU-functions relies on precise and efficient modeling of the behavior of combustion engines. Due to the limited computing power, usually a combination of physical models and calibration parameters is preferred for engine modeling in ECU. The parameters can be scalars, 1 or 2-dimensional empirical models, such as look-up table for volumetric efficiency and effective area of the exhaust gas recirculation (EGR). A novel algorithm is proposed to automatically calibrate the look-up tables characterizing stationary functional relationships in ECU-function of the air system of a diesel engine with minimum calibration cost. The algorithm runs in the framework of online design of experiment (DoE), in which Gaussian process model (GPM) is adopted to approximate the relationships of interest.

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.

Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work.

High-pressure gasoline fuel injection is a means to improve combustion efficiency and lower engine-out emissions. The objective of this study was to quantify the effects of fuel injection pressure on transient gasoline fuel spray development for a wide range of injection pressures, including over 1000 bar, using a constant volume chamber and high-speed imaging. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar into the chamber, which was pressurized with nitrogen at 1, 5, 10, and 20 bar at room temperature (298 K). Bulk spray imaging data were used to quantify spray tip penetration distance, rate of spray tip penetration and spray cone angle. Near-nozzle data were used to evaluate the early spray development.

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.

The ongoing changes in the development of new power trains and the requirements due to driver assistance systems and autonomous driving could be the enabler for completely new brake system configurations. The shift in the brake load collective has to be included in the systems requirements for electric vehicles. Many alternative concepts for hydraulic brake systems, even for decentralized configurations, can be found in the literature. For a decentralized system with all state of the art safety functionalities included, four actuators are necessary. Therefore, the single brake module should be as cost-effective as possible. Previous papers introduced systems which are for example based on plunger-like concepts, which are very expensive and heavy due to the needed gearing and design. In this paper a comparison between a state of the art hydraulic brake system using an electromechanical brake booster, and a completely new decentralized hydraulic brake concept is presented.

Compressed Natural Gas (CNG) is a promising alternative fuel for internal combustion engines as its combustion is fuel-efficient and lean in carbon dioxide compared to gasoline. The high octane number of methane gives rise to significant increase of the thermodynamic efficiency due to higher possible compression ratios. In order to use this potential, new stratified mixture formation concepts for CNG are investigated by means of numerical fluid simulations. For decades RANS methods have been the industry standard to model three-dimensional flows. Indeed, there are well-known deficiencies of the widely used eddy viscosity turbulence models based on the applied Boussinesq hypothesis. Reynolds stress turbulence models as well as scale resolving simulation approaches can be appealing alternative choices since they offer higher accuracy. However, due to their large computing effort, they are still mostly impractical for the daily use in industrial product development processes.

A previous study by the authors has shown an efficiency benefit of up to Δηi = 10 % for stratified operation of a high pressure natural gas direct injection (DI) spark ignition (SI) engine compared to the homogeneous stoichiometric operation with port fuel injection (PFI). While best efficiencies appeared at extremely lean operation at λ = 3.2, minimum HC emissions were found at λ = 2. The increasing HC emissions and narrow ignition time frames in the extremely lean stratified operation have given the need for a detailed analysis. To further investigate the mixture formation and flame propagation und these conditions, an optically accessible single-cylinder engine was used. The mixture formation and the flame luminosity have been investigated in two perpendicular planes inside the combustion chamber.

As automobiles become increasingly smarter, the need to understand within the automotive software the physical behavior of its parts is growing as well. The laws of physics governing such behavior are mostly formulated as differential equations, which today are usually created or obtained from various modeling tools. For solving them, the tools offer several solvers to satisfy the requirements of different problems. E.g. simple and fast explicit low order solvers for non-stiff problems and more complex implicit solvers for stiff problems. Though the modeling and code generation features as available in such tools are desirable for embedded automotive software, they cannot be used directly due to special restrictions with respect to hard realtime constraints. One such restriction is the organization of automotive software in components complying with the AUTOSAR standard which is not widely supported by the modeling tools.