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In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, also the battery and the electric motors have to be cooled. Currently, scroll compressors are widely used in the automotive industry, which generate one pressure pulse per revolution due to their discontinuous compression principle. This results in speed-dependent pressure fluctuations as well as higher-harmonic pulsations that arise from reflections. These fluctuations spread through the refrigeration cycle and cause the vibration excitation of refrigerant lines and heat exchangers. The sound transmission path in the air conditioning heat exchanger integrated in the dashboard is particularly critical. Various silencer configurations can be used to dampen these pulsations.

The production of electric vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. In comparison to conventional materials such as aluminum, ply wood structures exhibit beneficial damping properties. The loss factor of plywood structures with a thickness below 20 mm ranges from 0.013 to 0.032. Comparable aluminum structures however exhibit only a fraction of this loss factor with a range between 0.002 and 0.005.

In battery electric vehicles (BEV), thermal management is a key technique to improve efficiency and lifetime. Currently, manufacturers use different cooling concepts with numerous architectures. This work describes the development of a co-simulation framework to optimize BEV thermal management on system level, using advanced simulation methodologies also on component level, merging simulation and testing. Due to interactions between multiple conditioning circuits, thermal management optimization requires an overall vehicle approach. Thus, a full vehicle co-simulation of a BEV is developed, combining 1D thermal management software KULI and MATLAB/Simulink. Within co-simulation, the precise modeling of vehicle’s subsystems is important to predict thermal behavior and to calculate dynamic heating and cooling demands as well as exchanged energy flows with the thermal management system.

As alternative to electrification or carbon free fuels such as hydrogen, CO2-neutral fuels have been researched aiming to decrease the impact of fossil energy sources on the environment. Despite the potential benefit of capturing CO2 emission after combustion for own fuel production, the so-called eFuels also benefit by using a green source of energy during their fabrication. Among all the possibilities for eFuels, alcohols, ethers (such as MTBE and ETBE) and alternative hydrocarbons have shown positive impacts regarding emission reduction and performance when compared to standard gasoline. Previously in [1] and [2], synthetic fuels and methanol blends were tested at steady state conditions in order to verify advantages and drawbacks relative to gasoline, for power-sport motorcycles.

To achieve global climate goals, greenhouse gas emissions must be drastically reduced. The energy and transportation sectors are responsible for about one third of the greenhouse gases emitted worldwide, and they often use internal combustion engines (ICE). One effective way to decarbonize ICEs may be to replace carbon-containing fossil fuels such as natural gas entirely, or at least partially, with hydrogen. Cost-effective development of sustainable combustion concepts for hydrogen and natural gas/hydrogen mixtures in ICEs requires the intensive use of fast and robust simulation tools for prediction. The key challenge is appropriate modeling of flame front propagation. This paper evaluates and applies different approaches to modeling laminar flame speeds from the literature. Both appropriate models and reaction kinetic calculations are considered.

Aiming at the test safety problems in the early stage of self-driving cars development, firstly the virtual vehicle on-board CAN data acquisition module of the present project was designed based on virtual LabVIEW. Then a wireless remote control system for the self-driving car was constructed, which integrated the built virtual vehicle on-board CAN data acquisition system, the remote real-time image monitoring module and the remote upper computer control module based on ZigBee wireless transmission. It can execute the environmental awareness training and continuous and complex motion manipulation testing of the vehicle without relying on the driver, which can solve the safety problems in the tests of initial development of self-driving cars. Finally, the four-wheel independent steering electric vehicle was used as the self-driving test vehicle, and the wireless remote control system was tested on the double lane change type path and S-type path.

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].

The absence of combustion engine noise pushes increasingly attention to the sound generation from other, even much weaker, sources in the acoustic design of electric vehicles. The present work focusses on the numerical computation of flow induced noise, typically emerging in components of flow guiding devices in electro-mobile applications. The method of Large-Eddy Simulation (LES) represents a powerful technique for capturing most part of the turbulent fluctuating motion, which qualifies this approach as a highly reliable candidate for providing a sufficiently accurate level of description of the flow induced generation of sound. Considering the generic test configuration of turbulent pipe flow, the present study investigates in particular the scope and the limits of incompressible Large-Eddy Simulation in predicting the evolution of turbulent sound sources to be supplied as source terms into the acoustic analogy of Lighthill.

High-pressure direct injection (HPDI) of natural gas into the combustion chamber enables a non-premixed combustion regime known from diesel engines. Since knocking combustion cannot occur with this combustion process, an increase in the compression ratio and thus efficiency is possible. Due to the high injection pressures required, this concept is ideally suited to applications where liquefied natural gas (LNG) is available. In marine applications, the bunkering of and operation with LNG is state-of-the-art. Existing HPDI gas combustion concepts typically use a small amount of diesel fuel for ignition, which is injected late in the compression stroke. The diesel fuel ignites due to the high temperature of the cylinder charge. The subsequently injected gas ignites at the diesel flame. The HPDI gas combustion concept presented in this paper is of a monovalent type, meaning that no fuel other than natural gas is used.

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.

Small displacement two-stroke engines are cheap and low-maintenance propulsion systems and commonly used in scooters, recreation vehicles and handheld power-tools. The restriction by emission legislation and the increasing environmental awareness of end users as well as decreasing energy resources cause a rethinking in the development of propulsion systems and fuels in these fields. Despite recent improvements of electric powertrains, two stroke engines are the challenged propulsion system in high performance handheld power tools at the moment. The reasons are the extraordinary high power to weight ratio of two-stroke engines, the high energy density of liquid fuels and the reliability of the product with respect to extreme ambient conditions. Nevertheless, further improvements on emissions and fuel consumption of small displacement two-stroke engines can be realized.

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.

Car driver’s behavior and its influence on driving characteristics play an increasing role in the development of modern vehicles, e.g. in view of efficient powertrain control and implementation of driving assistance functions. In addition, knowledge about actual driving style can provide feedback to the driver and support efficient driving or even safety-related measures. Driving patterns are caused not only by the driver, but also influenced by road characteristics, environmental boundary conditions and other traffic participants. Thus, it is necessary to take the driving circumstances into account, when driving patterns are studied. This work proposes a methodology to cluster and evaluate driving patterns under consideration of vehicle-related parameters (e.g. acceleration and jerk) in combination with additional influencing factors, e.g. road style and inclination. Firstly, segmentation of the trip in distance series is performed to generate micro cycles.

The development of future internal combustion engines and fuels is influenced by decreasing energy resources, restriction of emission legislation and increasing environmental awareness of humanity itself. Alternative renewable fuels have, in dependency on their physical and chemical properties, on the production process and on the raw material, the potential to contribute a better well-to-wheel-CO2-emission-balance in automotive and nonautomotive applications. The focus of this research is the usage of alcohol fuels, like ethanol and 2-butanol, in motorcycle high power engines. The different propulsion systems and operation scenarios of motorcycle applications in comparison to automobile applications raise the need for specific research in this area.

Using natural gas as a fuel in internal combustion engines is a promising way to obtain efficient power generation with relatively low environmental impact. Dual fuel operation is especially interesting because it can combine the safety and reliability of the basic diesel concept with fuel flexibility. To deal with the greater number of degrees of freedom caused by the interaction of two fuels and combining different combustion regimes, it is imperative to use simulation methods in the development process to gain a better understanding of the combustion behavior. This paper presents current research into ignition and combustion of a premixed natural gas/air charge with a diesel pilot spray in a large bore diesel ignited gas engine with a focus on 3D-CFD simulation. Special attention was paid to injection and combustion. The highly transient behavior of the diesel injector especially at small injection quantities poses challenges to the numerical simulation of the spray.

Worldwide increasing energy consumption, decreasing energy resources and continuous restriction of emission legislation cause a rethinking in the development of internal combustion engines and fuels. Alternative renewable fuels, so called bio-fuels, have the potential to contribute to environmentally friendly propulsion systems. This study concentrates on the usage of alcohol fuels like ethanol, methanol and butanol in non-automotive high power engines, handheld power tools and garden equipment with the focus on mixture formation and cold start capability. Although bio-fuels have been investigated intensely for the use in automotive applications yet, the different propulsion systems and operation scenarios of nonautomotive applications raise the need for specific research. A zero dimensional vaporization model has been set up to calculate the connections between physical properties and mixture formation.

Dual fuel combustion processes, which burn varying ratios of natural gas and diesel, are an attempt to reach high efficiencies similar to diesel engines while exploiting the CO2 savings potential of natural gas. As shown in earlier studies, the main challenge of this combustion process is the high emission of unburned hydrocarbons during low load operation. Many publications have focused on a layout which utilizes port injection of natural gas and a direct injection of diesel to initiate combustion. However, previous studies indicated that a sequential direct injection of both fuels is more promising. It enables charge stratification of natural gas and air, whereby a remarkable reduction of the unburned hydrocarbon emissions was observed. This work develops this approach further, utilizing a low pressure direct injection of natural gas.

As emission limits become increasingly stringent and the price of gaseous fuels decreases, more emphasis is being placed on promoting gas engines. In the field of large engines for power generation, dual fuel combustion concepts that run on diesel/natural gas are particularly attractive. Knock in diesel/natural gas dual fuel engines is a well known yet not fully understood complex phenomenon that requires consideration in any attempt to increase load and efficiency. Thus combustion concept development requires a reliable yet robust methodology for detecting knock in order to ensure knock-free engine operation. Operating parameters such as rail pressure, start of injection and amount of diesel injected are the factors that influence oscillations in the in-cylinder pressure trace after the start of combustion. Oscillations in the pre-mixed combustion phase, or ringing, are caused by the rapid conversion of large parts of the injected diesel.

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.

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.