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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.

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 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.

Minimizing rattle noises is becoming increasingly important for hybrid and electrical vehicles as masking from the internal combustion engine is missing and in view of the functional requirements of the office-like interiors of next generation automated vehicles. Rattle shall therefore be considered in the design phase of component systems. One hurdle is the modelling of the excitation mechanisms and its experimental validation. In this work we focus on excitation by loose parts having functional clearances such as gear systems or ball sensors in safety belt retractors. These parts are excited by relatively large low frequency displacements such as road-induced movements of the car body or low order rigid body engine vibrations generating multiple impacts with broad band frequency content. Direct measurement of the impact forces is in many cases not possible.

Creep groan is an annoying brake noise at very low speeds of the vehicle. In general, stick-slip between brake disk and brake pads is believed to be the most dominating vibration mechanism of creep groan phenomena. This paper will show by sophisticated measurement techniques that stick-slip and speed-dependent friction is an important trigger. However, the overall vibration is much more complex than stick-slip reproduced by simple conveying belt minimal models. It turns out that in typical brake systems of passenger cars, creep groan appears from 15 to 25 Hz as well as 60 to 100 Hz. The mechanism from 15 to 25 Hz is highly impulsive and “hard”. Transitions between stick and slip phases trigger coupled nonlinear vibrations of the complete brake and suspension system. From 60 to 100 Hz, the vibrations show a more harmonic-like and “soft” signature, caused mainly by a speed-dependent friction behavior.

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.

From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.