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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.

Currently, on-road transport contributes nearly 12% of India’s total energy related carbon dioxide (CO2) emissions that are expected to be doubled by 2040. Following the global trends of increasingly stringent greenhouse gas emissions (GHG) and criteria emissions, India will likely impose equivalent Bharat Stage (BS) regulations mandating simultaneous reduction in CO2 emissions and nearly 90% lower nitrogen oxides (NOx) from the current BS-VI levels. Consequently, Indian automakers would likely face tremendous challenges in meeting such emission reduction requirements while balancing performance and the total cost of ownership (TCO) trade-offs. Therefore, it is conceivable that cost-effective system improvements for the existing internal combustion engine (ICE) powertrains would be of high strategic importance for the automakers.

This study investigates the effect of exhaust rebreathe (RB) on the low-load regime of a Gasoline Compression Ignition (GCI) heavy-duty engine. For this engine, a custom-designed cam profile with a second exhaust event occurring during the intake stroke was tested under different experimental load and speed conditions. First, the study focuses on the of rebreathe on combustion and gas exchange processes in the low load range of 240-300 kPa BMEP at three key speeds: 820, 1200, and 1600 rpm. Then, a general analysis of the thermal management of this technology is assessed in the low-load map, evaluating the impact on turbine outlet temperature and after-treatment performance related to the conversion rates for NOx and total hydrocarbons (THC). The detailed analysis revealed an increase of around 9% in the trapped residuals for the RB operation, translating to an in-cylinder temperature increase and raising the exhaust temperature up to 50°C.

The global automotive industry is undergoing a significant transition as battery electric vehicles enter the market and diesel sales decline. It is widely recognized that internal combustion engines (ICE) are needed for transport for years to come, however, demands on fuel efficiency, emissions, cost, and performance are extremely challenging. Gasoline compression ignition (GCI) is one approach to achieving demanding future efficiency and emissions targets. A key technology enabler for GCI is partially premixed, compression ignition (PPCI) combustion, which involves two high-pressure, late, fuel injections during the compression stroke. Both NOx and smoke emissions are greatly reduced relative to diesel engines, and this reduces aftertreatment (AT) requirements significantly. Exhaust rebreathing (RB) is used for robust low-load and cold operation. This is enabled by use of 2-Step, mode switching rocker arms to allow switching between rebreathe and normal combustion modes.

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.

To achieve carbon neutrality by 2060, the Chinese government has put effort into decarbonizing the transportation sector. Consequently, China elaborated a new energy vehicle strategy promoting the production of electric vehicles and expanding into hydrogen (H2) vehicle technologies including fuel cell electric vehicles and H2 internal combustion engine vehicles. The Transportation Energy Analysis Model (TEAM) projects the market penetration as well as energy demand and greenhouse gas emissions in China up to 2050. By integrating the Monte Carlo simulation, this study tests the robustness of TEAM and investigates the key parameters that will shape passenger vehicle sales and emissions in the future. The results show that fuel cell cost, H2 price, and battery cost are the most sensitive parameters for H2 vehicle technologies.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

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.

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.

For electric vehicles the ability for regenerative braking reduces the use of friction brakes. Particularly on the rear axle of vehicles with reduced dynamic requirements such as urban vehicles, this can offer a potential for downsizing or, in extreme cases, even the elimination of the friction brakes on the rear axle. Due to the fact that the rear axle service brakes also represent the typical parking brake location in SoA (State-of-Art) vehicles, a rigorous rethinking of the parking brake concept is necessary to incorporate safe vehicle standstill management for such novel brake system topology. This research study introduces a novel parking brake design that covers SoA but also legal requirements while retaining potentials associated with the elimination of the rear service brakes such as cost and packaging.

India contributed to 11% of the global road accidents and was ranked 1st among road deaths according to the latest World Health Organization (WHO) report 2018. Indian National Highways (NH) is a meagre 5% of the country’s road network but accounts for 55% of the road accidents and 61% of the road deaths. Majority of the freight traffic is ferried by Commercial Vehicles (CV) or trucks along these highways and this in turn increases the probability of them being involved in a road accident. The country’s economy is forecasted to thrive in the coming years and hence the requirement of CVs is aligned to international categorisation in the supply chain and shall play a pivotal role. In the year 2019, 13,532 road deaths were associated with CV occupants. The trucking industry is an unorganized sector wherein the illegal overloading of vehicles and over-the-limit driving hours pose a serious threat to road users.

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.

Vibration testing is often carried out for automotive components to meet guidelines based on their operational environments. This is an iterative process wherein design changes may need to be made depending on an intermediate model’s dynamic behavior. Predicting the behavior based on modifications in boundary conditions of a well-defined numerical model imparts practical insights to the component’s responses. To this end, application of a general method using experimental free-free condition frequency response functions of a structure is discussed in the presented work. The procedure is shown to be useful for prediction of responses when kinematic boundary conditions are applied, without the need for an actual measurement. This approach is outlined in the paper and is applied to datasets where dynamic modifications are made at multiple boundary nodes.

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.

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.

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.

Particulate emissions from Gasoline Direct Injection (GDI) engines have been an important topic of recent research interest due to their known environmental effects. This review paper will characterise the influence of different gasoline direct injection fuel systems on particle number (PN) emissions. The findings will be reviewed for engine and vehicle measurements with appropriate driving cycles (especially real driving cycles) to evaluate effects of the fuel injection systems on PN emissions. Recent technological developments alongside the trends of the influence of system pressure and nozzle design on injector tip wetting and deposits will be considered. Besides the engine and fuel system it is known that fuel composition will have an important effect on GDI engine PN emissions. The evaporation qualities of fuels have a substantial influence on mixture preparation, as does the composition of the fuel itself.

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.

A major source for soot particle formation in Gasoline-Direct-Injection (GDI) engines are fuel-rich zones near walls as a result of wall wetting during injection. To address this problem, a thorough understanding of the wall film formation and evaporation processes is necessary. The wall temperature before, during and after fuel impingement is an important parameter in this respect, but is not easily measured using conventional methods. In this work, a recently developed laser-based phosphor thermography technique is implemented for investigations of spray-induced surface cooling. This spatially and temporally resolved method can provide surface temperature measurements on the wetted side of the surface without being affected by the fuel-film. Zinc oxide (ZnO) particles, dispersed in a chemical binder, were deposited onto a thin steel plate obtaining a coating thickness of 17 μm after annealing.