Search Results

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.

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.

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).

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.

A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

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 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.

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.

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.