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.
Starting with a look at the transmission's primary function -- to couple the engine to the driveline and provide torque ratios between the two -- this updated and expanded seminar covers the latest transmission systems designed to achieve the most efficient engine operation. Current designs, the components and sub-systems used, their functional modes, how they operate, and the inter-relationships will be discussed. A manual transmission display will be used to explain ratios and how they function within the driveline.
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.
Integration of acoustic material concepts into vehicle design process is an important part of full vehicle design. The ability to assess the acoustic performance of a particular sound package component early in the design process allows designers to test various designs concepts before selecting a final products. This paper describes an innovative acoustic material concept which is easily integrated in a design process through the use of a database of Biot parameters. Biot parameters are widely used in the automotive industry to describe the physical interactions between the acoustics waves travelling through foams, fibers or metamaterials and the solid and fluid phase of these poro-elastic materials. This new acoustic material concept provides a combination of absorption, transmission loss and added damping on the panel it is attached to.
Automotive clutches are prone to rigid body torsional vibrations during engagement, a phenomenon referred to as take-up judder. This is also accompanied by fore and aft vehicle motions. Aside from driver behaviour in sudden release of clutch pedal (resulting in loss of clamp load), and type and state of friction lining material, the interfacial slip speed and contact temperature can significantly affect the propensity of clutch to judder. The ability to accurately predict the judder phenomenon relies significantly on the determination of operational frictional characteristics of the clutch lining material. This is dependent upon contact pressure, temperature and interfacial slip speed. The current study investigates the ability to predict clutch judder vibration with the degree of complexity of the torsional dynamics model. For this purpose, the results from a four and nine degrees of freedom dynamics models are compared and discussed.
In this paper,an amesim 1-d refined driveline model, including detailed engine, damper, dual clutch, transmission, differential, motor, halfshaft, wheel, body, suspension, powertrain mounting and powertrain rigid body, was built up, off a p2.5 topology phev,to predict torsional vibration induced vehicle NVH response addressing differing driving scenarios,like WOT rampup,parking engine start/stop,ev driving to tipnin(engine start) then to tipout(engine stop).firstly,the torsional vibration modes were predicted,addressing differing transmission gear steps of hev/ev driving mode,and the critical modes could be detected,as such, caveats/measures could be applied to setup the modal alignment chart/warn other engineering section from the very start of vehicle development; secondly,secondly,the holistic operational testing,which defined plenty measurement points including rpm fluctuation at differing location of engine/transmission,spark angle,crank position,injection angle,valve timing,MAP/MAF,etc, partly for later model calibration,partly for extract mandatory excitation input,like cylinder pressure trace/mount and suspension force,and partly for the reference of next optimization stage, was implemented on vehicle chassis dyno in a hemi-anechoic chamber.as it was merely centered on torsional vibration induced scenarios,the intake system/exhaust system /engine radiation noise contribution was excluded by specific measures,like BAM,etc, during the testing;thirdly,the NTF/VTF from the mount/suspension force exertion points to vehicle response points were measured off trimmed body impact testing, to create structural TPA model,that way,each transfer path contribution to the response point could be predicted and overall response can be synthesized from all paths;fourthly,the above-mentioned driveline model,combined the excitation on each cylinder considering the gas torque/inertia torque and motor average torque,was well calibrated to predict the mount/suspension force/critical rpm fluctuation/vibration;finally,it was validated that CAE results correlate very well to measurement outcome for defined loadcase, and that can be adopted to phev driveline/vehicle NVH development from the very start of vehicle development phase so as to expedite vehicle NVH developing process.
In motorsport power transmission systems, high-speed operation can be associated with significant rotordynamic effects. Changes in the natural frequencies of lateral (bending) vibrational modes as a function of spin speed are brought about by gyroscopic action linked to flexible shafts and mounted gear components. In the investigation of high-speed systems, it is important that these effects are included in the analysis in order to accurately predict the critical speeds encountered due to the action of the gear mesh and other sources of excitation. The rotordynamic behaviour of the system can interact with crucial physical parameters of the transmission, such as the stiffnesses of the gear mesh and rolling element-to-raceway contact in the bearings. In addition, the presence of the gear mesh acts to couple the lateral and torsional vibration modes of a dual-shaft transmission through which a torque flows.
Sales of SUV and luxury cars on the largest market of the world – China – are growing at a high rate. The highways in large cities like Beijing or Shanghai are increasingly populated with cars from all over the world like Japan, USA, Europe and Korea and even some refined domestic brands. More than 10 million rich people can afford those cars and are skilled drivers. This huge group of potential consumers is targeted by luxury brand OEMs and by startup companies. It has been understood, that these people have a strong attitude towards comfort. The twistbeam rear axle was replaced by multilink, double clutch transmissions were improved by comfort-mode drive programs, interior trims raised to Western standard performance levels, tyres specially developed for comfort in China, localized insulation materials and packages engineered to a one vehicle class higher level.
In general, when a problem occurs in a component, various phenomena appear, and abnormal noise is one of them. The service technicians diagnose the noise through the analysis using hearing and equipment. Depending on their experiences, the analysis time and diagnosis accuracy vary widely. The newly developed AI-based diagnostic technology diagnoses parts that cause abnormal noises within seconds when a noise is input to the equipment. To create a learning model for diagnosis, we collected as many abnormal noises as possible from various parts, and selected good and bad data. This process is very important in the development of diagnostic techniques. Artificial intelligence was learned by deep learning with selected good data. This paper is about the technology that can diagnose the abnormal noises generated from the engine, transmission, drivetrain and PE (Power Electric) parts of the eco-friendly vehicle through the diagnosis model composed of various methods of deep learning.
Over the past decade, there have been many efforts to generate engine sound inside the cabin either in reducing way or in enhancing way. To reduce the engine noise, the passive way, such as sound absorption or sound insulation, was widely used but it has a limitation on its reduction performance. In recent days, with the development of signal processing technology, ANC (Active Noise Control) is been used to reduce the engine noise inside the cabin. On the other hand, technologies such as ASD (Active Sound Design) and ESG (Engine Sound Generator) have been used to generate the engine sound inside the vehicle. In the last ISNVH, Hyundai Motor Company newly introduced ESEV (Engine Sound by Engine Vibration) technology. This paper describes the ESEV Plus Minus that uses engine vibration to not only enhance the certain engine order components but reduce the other components at the same time. Consequently, this technology would produce a much more diverse engine sound.