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Intensive R&D is currently performed worldwide on hybrid and electric vehicles. For full electric vehicles the driving range is limited by the capacity of currently available batteries. If such a vehicle shall increase its driving range some range extending backup system should be available. Such a Range Extender is a small system of combustion engine and electric generator which produces the required electricity for charging the batteries in time. Since the acoustic response of an electric motor driving the vehicle and of a combustion engine as part of a Range Extender is very different by nature an extensive acoustic tuning of the Range Extender is necessary to meet the requirements of exterior vehicle noise and passenger comfort. This paper describes the NVH (noise, vibration & harshness) development work of a range extender within the AVL approach of an electrically driven passenger car with range extender.

When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.

Flow noise produced by the turbulent motion of the exhaust gases is one of the main contributions to the noise generation for a heavy-duty vehicle. The exhaust system has therefore to be optimized since the early stages of the design to improve the engine’s Noise Vibration Harshness (NVH) performance and to comply with legislation noise limits. In this context, the availability of reliable Computational Aero-Acoustics (CAA) methodologies is crucial to assess the noise mitigation potential of different exhaust system designs. In the present work, a characterization of the sound generation in a heavy-duty exhaust system was carried out evaluating the noise attenuation potential of a design modification, by means of a hybrid CAA methodology.

Worldwide regulations concerning noise emissions of road vehicles are constantly demanding further reductions of acoustic emissions, which are considered a major environmental health concern in several countries. Among the different sources contributing to noise generation in vehicles equipped with internal combustion engines, exhaust flow noise is one of the most significant, being generated by turbulence development in the exhaust gases, and robust and reliable numerical methodologies for its prediction in early design phases are currently still needed. To this extent, Computational Aero-Acoustics (CAA) can be considered a valuable approach to characterize the physical mechanisms leading to flow noise generation and its propagation, and it could therefore be used to support exhaust system development prior to the execution of experimental testing campaigns.

In the frame of automotive Noise Vibration and Harshness (NVH) evaluation, inner cabin noise is among the most important indicators. The main noise contributors can be identified in engine, suspensions, tires, powertrain, brake system, etc. With the advent of E-vehicles and the consequent absence of the Internal Combustion Engine (ICE), tire/road noise has gained more importance, particularly at mid-speed driving and in the spectrum up to 300 Hz. At the state of the art, the identification and characterization of Noise and Vibration sources rely on pointwise sensors (microphones, accelerometers, strain gauges). Optical methods such as Digital Image Correlation (DIC) and Laser Doppler Vibrometer (LDV) have recently received special attention in the NVH field because they can be used to obtain full-field measurements.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Grown interest in complex modern Hybrid Electric Vehicle (HEV) concepts has raised new challenges in the field of NVH. The switch between the Internal Combustion Engine (ICE) and the Electric Motor (EM) at low speeds produces undesirable vibrations and a sudden raise of noise levels that effects the sound quality and passenger comfort achieved by the close-to-silent electric powertrain operation. Starting the ICE in the most suitable driving situation to create a seamless transition between driving modes can be the key to minimize the NVH quality impact in driver and passenger’s perception in HEVs. To integrate this important aspect in the early stages of the development and design phase, simulation technologies can be used to address the customer acceptance. By analyzing NVH measurements, the different noise components of the vehicle operation can be separated into ICE-related noise, EM-related noise and driving noise.

This paper describes the simulation tool chain serving to design and optimize the transmission of an electric axle drive from concept to final design with respect to NVH. A two-stage transmission of an eAxle is designed from scratch by the initial layout of gears and shafts, including the optimization of gear micro geometry. After the shaft system and bearings are defined, the concept design of the transmission housing is evaluated with the help of a basic topology optimization regarding stiffness and certain eigenfrequencies. In the next step a fully flexible multi-body dynamic (MBD) and acoustic analysis of the transmission is performed using internally calculated excitations due to gear contact and bearing interaction with shaft and gear dynamics for the entire speed and load range. Critical operating conditions in terms of shaft dynamics, structure borne noise and noise radiation are evaluated and selected as target for optimization in the following steps.

Beside hard facts as performance, emissions and fuel consumption especially the brand specific attributes such as styling and sound are very emotional, unique selling prepositions. To develop these emotional characters, within the given boundary conditions of the future pass-by regulation, it is necessary to define them at the very beginning of the project and to follow a consequent development process. The following paper shows examples of motorcycle NVH development work on noise cleaning and sound engineering using a hybrid development process combining front loading, simulation and testing. One of the discussed solutions is the investigation of a piston pin offset in combination with a crankshaft offset for the reduction of friction. The optimization of piston slap noise as a result of the piston secondary motion was performed by simulation. As another example a simulation based development was performed for the exhaust system layout.

Due to more challenging future emission legislations and the trend towards downsizing, the number of turbocharged (TC) engines, especially petrol engines, is steadily increasing. The usage of TC has high risk to cause different noise phenomena apparent in the vehicle interior which are often perceived as annoying for the passengers. In order to further improve consideration of TC topics in the development, objective judgment and monitoring of TC noise issues is of high importance. Therefore, objective parameters and corresponding tools that are especially focusing on TC noise phenomena have to be developed. One main target of these tools is to deliver an objective TC assessment in an efficient way and with minimum additional effort. Application of the criteria presented in this publication therefore allows acoustic engineers to judge the NVH behavior and annoyance of the TC with respect to its vehicle interior noise contribution.

As an era of autonomous driving approaches, it is necessary to translate handling comfort - currently a responsibility of human drivers - to a vehicle imbedded algorithm. Therefore, it is imperative to understand the relationship between perceived driving comfort and human driving behaviour. This paper develops a methodology able to generate the information necessary to study how this relationship is expressed in highway overtakes. To achieve this goal, the approach revolved around the implementation of sensor Data Fusion, by processing data from CAN, camera and LIDAR from experimental tests. A myriad of variables was available, requiring individuating the key-information and parameters for recognition, classification and understanding of the manoeuvres. The paper presents the methodology and the role each sensor plays, by expanding on three main steps: Data segregation and parameter selection; Manoeuvre detection and processing; Manoeuvre classification and database generation.

Driven by worldwide climate change, governments are introducing more stringent emission regulations with particular focus on fuel saving for CO₂ emission reduction. Downsizing and weight reduction are two of the main drivers to achieve these demanding regulations. Both aspects however might have a strong negative effect on the overall vehicle NVH behavior. Weight reduction directly influences NVH due to reduction of absorption and damping material and due to light-weight design affecting the dynamic responses of powertrain and vehicle structures. Engine downsizing however has multiple negative effects on NVH. Beside higher vibrations and speed irregularities due to lower cylinder numbers and displacements also reduction of sound quality is a critical topic that will be handled within this publication.

In the past the exterior and interior noise level of vehicles has been largely reduced to follow stricter legislation and due to the demand of the customers. As a consequence, the noise quality and no longer the noise level inside the vehicle plays a crucial role. For an economic development of new powertrains it is important to assess noise quality already in early development stages by the use of simulation. Recent progress in NVH simulation methods of powertrain and vehicle in time and frequency domain provides the basis to pre-calculated sound pressure signals at arbitrary positions in the car interior. Advanced simulation tools for elastic multi-body simulation and novel strategies to measure acoustical transfer paths are combined to achieve this goal. In order to evaluate the obtained sound impression a roughness prediction model has been developed. The proposed roughness model is a continuation of the model published by Hoeldrich and Pflueger.

In mathematical and mechanical modeling terms, automotive seating is characterized by boundary conditions at the nonlinear contact interfaces. These contact interfaces are subjected to vibro-impacts (slaps) and frictional slips. The slaps occur in contact interfaces at high amplitude vibrations, being characterized by very short duration, rapid dissipation of energy and large accelerations and decelerations. By considering friction in contact interface modeling, the simulation of the interaction between the driver and the vehicle seat becomes more realistic. Vibro-impacts and frictional slips can be simultaneously developed in a contact surface. The boundary conditions identification for a seat and a wide range of drivers' body types is performed using the concept of interference distance or penetration. The interference distance is introduced as an optimization problem. It is shown that the optimization problem provides robust solutions to minimum distance and interference problems.

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.

In automotive market, today more than in the past, it is very important to reduce time to market and, mostly, developing costs before the final production start. Ideally, bench and on-road tests can be replaced by multi-body studies because virtual approach guarantees test conditions very close to reality and it is able to exactly replicate the standard procedures. Therefore, today, it is essential to create very reliable models, able to forecast the vehicle behavior on every road condition (including uneven surfaces). The aim of this study is to build an accurate multi-body model of a heavy-duty truck, check its handling performance, and correlate experimental and numerical data related to comfort tests for model tuning and validation purposes. Experimental results are recorded during tests carried out at different speeds and loading conditions on a Belgian blocks track. Simulation data are obtained reproducing the on-road test conditions in multi-body environment.

Urban mobility represents one of the most critical global challenges nowadays. Several options regarding design and power sources technologies were recently proposed; among which electric and hybrid vehicles are quite successful to meet the increasingly restrictive environmental targets. This significant goal may affect the perceived vehicle comfort and drivability, especially in everyday urban scenarios. The purpose of this paper is to carry out a comparison in terms of comfort between vehicles belonging to different categories, but all designed for urban mobility: an electric 2-passenger quadricycle used during the demonstration phase of the European project STEVE, an internal combustion engine 2-passenger car (Smart Fortwo), an electric 4-passenger car (Bolloré Bluecar) and an internal combustion engine 4-passenger car (Fiat 500). Leading European car-sharing services use the last three car models.

The new generation of automatic transmissions is characterized by a compact and highly efficient design. By the use of a higher overall gear ratio and lightweight components combined with optimal gear set concepts it is possible to improve significantly fuel consumption and driving dynamics. Precise and efficient real time models of the whole power train including models for complex subsystems like the automatic transmission are needed to combine real hardware with virtual models on XiL test rigs. Thereby it's possible to achieve a more efficient product development process optimized towards low development costs by less needed prototypes and shorter development times by pushing front loading in the process. In this paper a new real time model for automatic transmissions including approved models for the torque converter, the lock-up clutch and the torsional damper are introduced. At the current development stage the model can be used for comfort analysis and drivability assessment.

This paper presents the methodology adopted by Politecnico di Torino Vehicle Dynamics Research Team to obtain objective indices for the evaluation of the comfort during the gear change process. Some test drivers and different passengers traveled on a test vehicle and assigned marks on the basis of their subjective feeling of comfort during the gearshifts. The comparison between the most significant subjective evaluations and the experimental values obtained by the instruments located on the vehicle is presented. As a consequence, some indices (based on physical parameters) to evaluate the efficiency and the comfort of the gearshift process are obtained. They are in good agreement with the subjective evaluations of the drivers and the passengers. The second part of the paper presents a driveline and vehicle model which was conceived to reproduce the phenomena experimented on the vehicle. The experimental validation of the model is presented.

In the frame of the space food production research activities conducted in the Thales Alenia Space Italia (TAS-I) Advanced Life Support Research and Development laboratory (RecycLAB, [6]), and with the contribution of a degree thesis developed in collaboration with the Politecnico of Torino, a rack-like facility for ground research on Life Support Systems based on Plants has been designed, developed, integrated, verified and tested in TAS-I. The new facility, called EDEN EPISODE 2, is a significant evolution of a previous TAS-I project (EDEN EPISODE 1) and takes benefit from other lower size TAS-I demonstrators (CUBE). It aims at realizing a completely closed and controlled environment for crop production, while a mobile lighting panel allows to maximize the delivered light in each phase of the plant life cycle. Hydroponic and aeroponic techniques have been implemented in the project for nutrient delivery to the plant roots.