Due to the increasing computational power, significant progress has been made over the past decades when it comes to CAD, multibody and simulation software. The application of this software allows to develop products from scratch, or to investigate the static and dynamic behavior of multibody models with remarkable precision. In order to keep the development costs low for highly sophisticated products, more precisely motorcycle rider assistance systems, it is necessary to focus extensively on the virtual prototyping using different software tools. In general, the interconnection of different tools is rather difficult, especially when considering the coupling of a detailed multibody model with a simulation software like MATLAB Simulink. The aim of this paper is to demonstrate the performance of a motorcycle rider assistance algorithm using a cosimulation approach between the free multibody software called FreeDyn and Simulink based on a sophisticated multibody motorcycle model.
The aim of the presented research is to propose and benchmark two brake models, namely the novel dynamic ILVO model and a neural network based regression. These can estimate the evolution of the brake friction between pad and disc under different load conditions, which are typically experienced in vehicle applications. The research also aims improving the knowledge of the underlying mechanism related to the evolution of the BLFC (boundary layer friction coefficient), the reliability of virtual environment simulations to speed up the product development time and reducing the amount of vehicle test in later phases and finally improving brake control functions. With the support of extensive brake dynamometer testing, the proposed models are benchmarked against State-of-the-Art. Both approaches are parametrised to render the friction coefficient dynamics with respect to the same input parameters.
Brakes are the most important safety device in a vehicle, however there are few barriers to manufacture, import, or sell friction materials in most of the countries, including USA. European countries, with the ECE R90 program, are a big exception. International Transport Forum published in 2016 the “Benchmarking of road safety in Latin America” report, it mentions that worldwide 17.5 people in every 100,000 die in road accidents, however Andean countries mortality rate is 23.4 and South American 21.0, considerably higher than the worldwide average.
The particulate emissions of two brake systems where characterized in a dilution tunnel optimized for PM10 measurements. The larger of them employed a fixed caliper (FXC) and the smaller one a floating caliper (FLC). Both used ECE brake pads of the same lining formulation. Measured properties included gravimetric PM2.5 and PM10, Particle Number (PN) concentrations of both untreated and thermally treated (according to exhaust number regulation) particles using Condensation Particle Counters (CPCs) having 23 and 10 nm cut-off sizes, and an Optical Particle Sizer (OPS). The brakes were tested over a novel test cycle developed from the database of the Worldwide harmonized Light-Duty vehicles Test Procedure (WLTP). A series of WLTP tests were performed starting from unconditioned pads, to characterize the evolution of emissions until their stabilization. Selected tests were also performed over a short version of the Los Angeles City Cycle.
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.
Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.
Axial cooling fans are commonly used in electric vehicles to cool batteries with high heating load. One drawback of the cooling fans is the high aeroacoustic noise level resulting from the fan blades and the obstacles facing the airflow. To create a comfortable cabin environment in the vehicle, and to reduce exterior noise emission, a low-noise installation design of the axial fan is required. The purpose of the project is to develop an efficient computational aeroacoustics (CAA) simulation process to assist the cooling-fan installation design. This paper reports the current progress of the development, where the narrow-band components of the fan noise is focused on. Two methods are used to compute the noise source. In the first method the source is computed from the flow field obtained using the unsteady Reynolds-averaged Navier-Stokes equations (unsteady RANS, or URANS) model.
Vehicle NVH (Noise, Vibration and Harshness) is one of the most critical customer touchpoints which may lead to buying decisions. The importance of Noise inside the cabin is increasing day by day because of the new era of E-mobility and autonomous driving. Noise source could be the engine, powertrain, tyre, suspension components, brake system, etc. depending on driving conditions. Among these, tire noise is being identified as biggest contributor at constant mid-speed driving where engine and powertrain operate at minimum noise and wind noise is also at a moderate level. This driving condition becomes very significant for electric vehicles where engine noise is replaced by motor noise which is a tonal noise at very high frequency. This makes the improvement of tire noise levels quintessential for good cabin acoustic feel. This demands a proactive approach to develop low noise tire platforms for future mobility by leveraging research tools and best practices in the industry.
The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.
Noise inside the passenger cabin is made up of multiple sources. A significant reduction of the major sound sources such as the engine, wind and tire noise helped to improve the comfort for passengers. As a consequence, the HVAC sound (heating, ventilation and air-conditioning) is unmasked as a primary noise source inside the passenger cabin and has to be taken into consideration when designing passenger cabin sound. While HVAC sound is often evaluated at stop, the most common situation of its use is while driving. In case of fresh air as mode of operation, the HVAC system is coupled to the environment through the air intake. Any change in the boundary conditions due to on-road driving events and gusts of wind affects the flow field in the HVAC system and in turn influences HVAC noise. This study investigates the effect of mass flow and pressure fluctuations on the HVAC noise. In a first step, major influences on the HVAC system are identified in an on-road test.
The development and production of resonators on the charged air side of combustion engines require profound base of knowledge in designing, simulating and the production of such parts in different materials (aluminum, copper, stainless steel and technical plastic). As combustion engines are under constant discussion, this existing knowledge base should be used for other applications within and outside the automotive industry. Very quickly it became apparent that new challenges often require completely new solutions, designs and materials to meet the requirements of flow noise reducing parts. For example, for clean air applications mufflers based on “special treated foams” and “meta-materials” can be introduced. These materials offer new potentials for tuning of the frequency range and allow improved broad banded flow noise attenuation. Such parts are named “Resabtors” in order to take respect of the different flow noise attenuation principles resonation and absorbing.
Electric vehicles (EV's) present new challenges to achieving the required noise, vibration & harshness performance (NVH) compared with conventional vehicles. Specifically, high-frequency noise and abnormal noise, previously masked by the internal combustion engine can also cause annoyance in an EV. Electric motor (E-motor) whine noise caused by electromagnetic excitation during E-motor operation is caused by torque ripple and stator local excitation. Under high speed and high load operating conditions, the sound level is low, however high frequency whine noise is a factor that can impair the vehicle level NVH performance. An example of a previously masked abnormal noise is a droning noise that can be caused by manufacturing quality variation of the spline coupling between the rotor shaft of the E-motor and the input shaft of the reducer, it is dominated by multiple higher orders of the E-motor rotation frequency.