Search Results

The enhancement of efficiency will play a more and more important role in the development of future (small) internal combustion engines. In recent years, the Atkinson (or Extended Expansion) cycle, realized over the crank drive, attracted increasing attention. Several OEMs have investigated this efficiency-increasing principle in the whole range from small engines up to automotive engines until now. In prior publications, the authors outlined the remarkable efficiency potentials of an Extended Expansion (EE) cycle. However, for an internal combustion engine, a smooth running performance as well as low vibrations and noise emissions are relevant aspects. This is especially true for an Extended Expansion engine realized over the crank drive. Therefore, design measures concerning friction and NVH need to be taken to enable possible series production status. Basically, these measures strongly depend on the reduction of the free mass forces and moments.

Usually the power output of 50 cm₃ two wheelers is higher than necessary to reach the maximum permitted vehicle speed, making engine power restriction necessary. This publication deals with different power restriction strategies for four-stroke engines and their effect on exhaust emissions. Alternative power limitation strategies like EGR and leaning were investigated and compared with the common method of spark advance reduction to show the optimization potential for this certain engine operation conditions. From these tests, a substantial set of data showing the pros and cons in terms of emissions, combustion stability and fuel economy could be derived for each speed limiting technique.

In the course of the last few years a continuous increase of the injection pressure level of gasoline direct injection systems appeared. Today's systems use an injection pressure up to 200bar and the trend shows a further increase for the future. Although several benefits go along with the increased injection pressure, the disadvantages such as higher system costs and higher energy demand lead to the question of the lowest acceptable injection pressure level for low cost GDI combustion systems. Lowering injection pressure and costs could enable the technological upgrading from MPFI to GDI in smaller engine segments, which would lead to a reduction of CO2 emission. This publication covers the investigation of a low pressure GDI system (LPDI) with focus on small and low cost GDI engines. The influence of the injection pressure on the fuel consumption and emission behavior was investigated using a 1.4l series production engine.

The advantages of 2-stroke engines, high power and low weight, are in conflict with their disadvantages, high emissions and bad fuel economy. As these disadvantages are caused by the scavenging process, a reason for the problem can be analyzed by using three dimensional computational fluid dynamics simulation (3D CFD simulation). The scavenging losses can be dramatically reduced with a high pressure fuel injection strategy. The purpose of this strategy is to prevent a fuel concentration in the incoming charge and to reduce the fuel concentration inside the exhaust system. These advantages can only be successfully exploited with the application of an optimal injection strategy. This paper covers a spray study for a gasoline direct injection (GDI) high performance 2-stroke engine using the commercial CFD Code Fluent.

The release of the “Regulation No. 168/2013” for the approval and market surveillance of two- or three-wheel motorcycles and quadricycles of the European Union started a new challenge for the motorcycle industry. One goal of the European Union is to achieve emission parity between passenger cars (EURO 6) and motorcycles (EURO 5) in 2020. The hybridization of motorcycle powertrains is one way to achieve these strict legislation limits. In the automotive sector, hybridization is well investigated and has already shown improvements of fuel consumption, efficiency and emission behavior. Equally, motorcycle applications have a high potential to improve efficiency and to meet customer needs as fun to drive as well. This paper describes a methodical approach to analyze conventional motorcycles regarding the energy and power demand for different driving cycles and driving conditions. Therefore, a dynamic or forward vehicle simulation within MATLAB Simulink is used.

A worldwide decrease of legal limits for CO2 emissions and fuel economy led to stronger efforts for achieving the required reductions. The task is to evaluate technologies for CO2 reduction and to define a combination of such measures to ensure the targets. The challenge therefor is to find the optimal combination with respect to minimal costs. Individual vehicles as well as the whole fleet have to be considered in the cost analysis - which raises the complexity. Hereby, the focus of this work is the consideration and improvement of a new model series against the background of a fleet and the selection of measures. The ratio between the costs and the effect of the measures can be different for the each vehicle configuration. Also, the determination of targets depends whether a fleet or an individual vehicle is selected and has impact on the selection and optimization process of those measures.

For a broad acceptance of electric vehicles, the trade-off between all electric range and battery cost respectively weight represents the most important challenge. The all electric range obtained under real world conditions most often deviates significantly from the nominal value which is measured under idealized conditions. Under extreme conditions - slow traffic and demanding requirements for cabin heating or cooling - the electrical range might become less a question of spatial distance but even more of total operation time. Whereas with conventional powertrain, high flexibility of the total driving range can be obtained without sacrificing cost, with a pure battery vehicle this results in extreme high cost and weight of the energy storage. Therefore the difference between the typical daily driving range (e.g. in Germany 80-90% is below 50 km) and the minimum total range requested by most customers for acceptance of battery vehicles (200- 250 km), becomes essential.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

A reduction in CO2 emissions and consequently fuel consumption is essential in the context of future greenhouse gas limits. With respect to the thermodynamic loss analysis of an internal combustion engine, a gap between the net indicated thermal efficiency and the brake thermal efficiency is recognizable. This share is caused by friction losses, which are the focus of this research project. The parasitic loss reduction potential by replacing the mechanical water pump with an electric coolant pump is discussed in the course of this work. This is not a novel approach in light duty vehicles, whereas in commercial vehicles a rigid drive of all auxiliaries is standard. Taking into account an implementation of a 48-V power system in the short or medium term, an electrification of auxiliary components becomes feasible. The application of electric coolant pumps on an Euro VI certified 6-cylinder in-line heavy-duty diesel engine regarding fuel economy was thus performed.

These days a new generation of hybrid electric vehicles (HEV) are penetrating the global vehicle market - the plug-in hybrid electric vehicles (PHEVs). Compared to conventional HEVs, PHEVs have additional significant potential. They are able to improve fuel efficiency and reduce local emissions due to higher battery capacities, and they can be recharged from external outlets. Energy management has a major impact on the PHEVs performance. In this publication, an innovative operation strategy for PHEVs is presented. This is due to the fact that both increasing fuel efficiency and enhancing the vehicle's longitudinal performance requires a fine balance between the consumption of fossil and electric energy. The new operation strategy combines advanced predictive and adaptive algorithms. In contrast to the charge-sustaining strategy of HEVs, the charge-depleting mode for PHEVs is more appropriate.

In the ongoing competition of powertrain concepts the Internal Combustion Engine (ICE) will also have to demonstrate its potential for increased efficiency [1]. Variable Compression Ratio (VCR) Systems for Internal Combustion Engines (ICE) can make an important contribution to meeting stringent global fuel economy and CO2 standards. Using such technology a CO2 reduction of between 5% and 9% in the World Harmonized Light-Duty Vehicle Test Cycle (WLTC) are achievable, depending on vehicle class, load profile and power rating [2]. This paper provides a detailed description of the measurement approaches that are used during development of the AVL Dual Mode VCSTM and other VCR systems in fired operation. Results obtained from these measurements are typically used to calibrate or verify simulation models, which themselves are an integral part of the development of these systems [3].

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).

In an era characterized by the rapid proliferation and advancement of AI-based technologies across various domains, the spotlight is placed on the integration of these technologies into trustworthy autonomous systems. The integration into embedded systems necessitates a heightened focus on dependability. This paper combines the findings from the TEACHING project, which delves into the foundations of humanistic AI concepts, with insights derived from an expert workshop in the field of dependability engineering. We establish the body of knowledge and key findings deliberated upon during an expert workshop held at an international conference focused on computer safety, reliability and security. The dialogue makes it evident that despite advancements, the assurance of dependability in AI-driven systems remains an unresolved challenge, lacking a one-size-fits-all solution.

Cybersecurity assumes a major role in the context of the automotive domain, where both existing and forthcoming regulations are heightening the need for robust security engineering. A significant milestone in advancing cybersecurity within the automotive industry is the release of the first international standard for automotive cybersecurity ISO/SAE 21434:2021 ‘Road Vehicles — Cybersecurity Engineering’. A recently published type approval regulation for automotive cybersecurity (UN R155) is also tailored for member countries of the UNECE WP.29 alliance. Thus, the challenges for embedded automotive systems engineers are increasing while frameworks, tools and shared concepts for cybersecurity engineering and training are scarce.

Due to the increasing number of minivans and sport utility vehicles, rollovers have become more significant. As a result, various accident reconstruction programs have been developed to address this issue. To reconstruct rollover crashes, various requirements have to be fulfilled. These consist of: providing a simple method that is able to model three dimensional environments that often play a major role in rollovers. including suspension, tire and collision models must be provided. This is particularily important in the rollover initiation phase. including proper vehicle geometry and contact stiffness must be available. These are important for simulation of body contacts that affect the vehicle motion. This study focuses on one program, PC-CRASH. This program was developed to allow simulations of vehicle 3-dimensional movements before, during and after the impact. The study also discusses the physical background of the models, their capabilities as well as their limitations.