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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.

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.

The objective of this experimental investigation was to analyze the effect of various exhaust gas aftertreatment technologies on particulate number emissions (PN) of an MPFI EU5 motorcycle. Specifically, three different aftertreatment strategies were compared, including a three-way-catalyst (TWC) with LS structure as the baseline, a hybrid catalyst with a wire mesh filter, and an optimized gasoline particulate filter (GPF) with three-way catalytic coating. Experimental investigations using the standard test cycle WMTC performed on a two-wheeler chassis dynamometer, while the inhouse particulate sampling system was utilized to gather information about size-dependent filtering efficiency, storage, and combustion of nanoparticles. The particulate sampling and measuring system consist of three condensation particle counters (CPCs) calibrated to three different size classes (SPN4, SPN10, SPN23).

In this paper, we will show the potentials of reducing NOx emissions of an H2-ICE to an ultra-low level by hybridizing the H2-ICE in an NRMM powertrain. Real-world measurement data of NRMM together with a simulated hybrid powertrain and operating strategy form the input data for the H2-ICE on the test bench. We have modified a turbocharged four-cylinder in-line gasoline engine for use with directly injected hydrogen. Within several iteration loops, we obtained measurement data that shows that, depending on the operating strategy, ultra-low NOx emissions are reachable. The combination of hybridization, which implies the possibility of recuperation, and the CO2 emission-free H2-ICE leads to a highly efficient, robust, and economic drivetrain with the lowest emissions, perfectly suitable for Non-Road Machinery. Additionally, we will discuss the overall coupled measurement and simulation setup and the reachable NOx emission levels in our tested setup.

Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.

Brake wear particles are recognized as one of the dominant sources of road transport particulate matter emissions and are linked to adverse health effects and environmental impact. The UNECE mandated the Particle Measurement Program to address this issue, by developing a harmonized sampling and measurement methodology for the investigation of brake wear particles on a brake dynamometer (dyno). However, although the brake dyno approach with tightly controlled test conditions offers good reproducibility, a multitude of changing vehicle and surrounding conditions make real-driving emissions measurement a highly relevant task. Here we show two different prototypes for on-road particle measurement with minimal impact of the measurement setup on the emission behavior, tested on a brake dyno.

Drivetrain electrification is increasing in the kart racing sector since noise emissions are an important factor in urban areas. To improve range, it has become necessary to optimize the rolling resistance of kart racing tires. This paper introduces a parameter study for small bias-ply tires which are used in kart racing and investigates the effect of these parameters on rolling resistance. In recent literature, rolling resistance is mostly examined in radial passenger car tires. Most testing devices are limited to rim sizes from ten inches upwards. In this study, a test rig was developed with focus on low cost and small rim sizes. This self-developed test rig was validated through a comparison with an approved test rig according to ISO 18164 standard. A parameter study was conducted to investigate the effect of changes in the construction of the tire. These changes affect the warp count of the carcass fabric and the crown angle of the different plies.

In-cylinder flows in internal combustion engines are highly turbulent in nature. An important property of turbulence that plays a key role in mixture formation is anisotropy; it also influences ignition, combustion and emission formation. Thus, understanding the turbulence anisotropy of in-cylinder flows is critical. Since the most widely used two-equation Reynolds-averaged Navier-Stokes (RANS) turbulence models assume isotropic turbulence, they are not suitable for correctly capturing the anisotropic behavior of turbulence. However, large eddy simulation (LES) can account for the anisotropic behavior of turbulence. In this paper, the Reynolds stress tensor (RST) is analyzed to assess the predictive capability of RANS and LES with regard to turbulence anisotropy. The influence of mesh size on turbulence anisotropy is also looked into for multi-cycle LES.

World Championship races are the competition of the fastest motorcycle riders in the world. They are a rare selection of professionals which can ride race bikes on the absolute physical limits in the longitudinal and lateral direction. The exact understanding of race bike performance for race engineers, riders and race bike development companies is quite difficult as the movement of a race bike and a rider is a complex combination of various physical effects. The aim of the present work is to approach the understanding of race bike performance from a scientific point of view. The actual assessment of race bike performance is mainly data-driven and based on the comparison of racing lines and single measurement channels for different laps and race events. The new approach is to add physical multibody models to understand single segments from real-world racetrack measurements.

The upstream flow conditions and the use of tractive power to accelerate a vehicle are both sources of energy loss. The vehicle speed and the upstream flow conditions result in the oncoming wind vector experienced by the moving vehicle. The aim of the present work is to show a new approach to consider the chaotic and random behavior of surrounding flow conditions and their influence on driving performance. The approach is shown for the example of motorbike racing conditions. Special interest was put on a description of the flow conditions with respect to well know turbulent flow field parameters like the turbulent length scale or the turbulence intensity. Depending on where the flow conditions are measured, stationary in the earth reference frame, or on a moving vehicle, it is quite difficult to get a robust description of the flow field parameters. These parameters are used together with the Reynolds number to predict the aerodynamic behavior by correlation functions or maps.

This paper introduces a finite element (FE) approach to determine tire deformation and its effect on open-wheeled racecar aerodynamics. In recent literature tire deformation was measured optically. Combined loads like accelerating at corner exit are difficult to reproduce in wind tunnels and requires several optical devices to measure the tire deformation. In contrast, an FE approach is capable of determining the tire deformation in combined load states accurately. The FE tire model was validated using computer tomography images, 3D scan measurements, contact patch measurements and stiffness measurements. The deformed shape of the FE model was used in a computational fluid dynamics (CFD) simulation. A sensitivity study was created to determine the effect of the tire deformation on aerodynamics for unloaded and loaded tires. In addition, the influence of these tire deformations was investigated in a CFD study using a full vehicle model.

Given approximately one million small and light aircraft in operation worldwide, icing detection and icing quantification of in-flight icing are still an open research topic. Despite technical means are available to de-ice on ground, there is a lack of a suitable control system based on sensor data to de-ice while the aircraft is airborne. Most often, it is still task of the pilot to visually inspect the icing status of the airfoil and/or other critical parts of the aircraft such as engine air intakes, which distracts the flight crew from flying the aircraft especially in IMC conditions. Based on preliminary simulation and tests in 2014 in a collaborative research project lasting from 2015 until 2018, the technology of energy self-sustaining, wireless, self-adhesive smart sensors for industrial sensing in an aerodynamically critical environment (i.e. wind turbines) was further investigated to fulfil general aviation requirements.

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.

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.

Increasing demands on automotive comfort as well as diminishing vehicle noise levels draw new attention towards low-frequency vibration and noise issues of disk brake systems such as creep groan and moan. In view of this problem, the experimental investigation of relevant phenomena is within the scope of this article. The related experiments concerning two different setups have been performed at a drum driven suspension and brake test rig. Both assemblies consisted of a front axle corner including all parts of the integrated brake system. In order to gain understanding of characteristic triggering mechanisms and fundamental subsystem interactions, and moreover, to verify the suitability of modal methods for simulative evaluations of creep groan or moan, specifically elaborated Operating Deflection Shape (ODS) techniques have been applied. Via analyses of four different creep groan emergences, global stick-slip cycles between disk and pads are revealed.

A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure.

The reduction of environmentally harmful gases and the ambitions to reduce the exploitation of fossil resources lead to stricter legislation for all mobile sources. Legislative development significantly affected improvements in emissions and fuel consumptions over the last years, mainly measured under laboratory conditions. But real world operating scenarios have a major influence on emissions and it is already well known that these values considerably differ from officially published figures [1]. There are regulated emissions by the European Commission by means of real driving scenarios for passenger cars. A methodology to measure real drive emissions RDE is therefore well approved for automotive applications but was not adapted for two-wheeler-applications yet [2]. Hence measurements have been performed on-road and on chassis dynamometer for motorcycles with the state of the art RDE measurement equipment to be prepared for possible future legislation.

Real world operating scenarios have a major influence on emissions and fuel consumption. To reduce climate-relevant and environmentally harmful gaseous emissions and the exploitation of fossil resources, deep understanding concerning the real drive behavior of mobile sources is needed because emissions and fuel consumption of e.g. passenger cars, operated in real world conditions, considerably differ from the officially published values which are valid for specific test cycles only [1]. Due to legislative regulations by the European Commission a methodology to measure real drive emissions RDE is well approved for heavy duty vehicles and automotive applications but may not be adapted similar to two-wheeler-applications. This is due to several issues when using the state of the art portable emission measurement system PEMS that will be discussed.

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.

Vehicle road tests are meaningful for investigations of creep groan noise. However, problems in reproducing experiments and partly subjective evaluations may lead to imprecise conclusions. This work proposes an experimental test and evaluation procedure which provides a precise and objective assessment of creep groan. It is based on systematic corner test rig experiments and an innovative characterization method. The exemplary setup under investigation consisted of a complete front wheel suspension and brake system including all relevant components. The wheel has been driven by the test rig’s drum against a brake torque. The main parameters within a test matrix were brake pressure and drum velocity. Both have been varied stepwise to scan the relevant operating range of the automobile corner system for potential creep groan noise. Additionally, the experiments were extended to high brake pressures, where creep groan cannot be observed under road test conditions.