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One of the most important safety issues for automotive engineering is to avoid any fire due to the ignition of flammable liquids, which may result from leaks. Fire risk is a combination of hot temperature, fast vaporisation and accumulation of vapor in a cavity. In IC engines, potentially flammable liquids are fuel and oil. To guarantee safety, flammable liquids must not come into contact with hot parts of the engine. Consequently, shields are designed to guide the flow path of possible leakages and to take any flammable liquid out of the hot areas. Simulation is a great help to optimize the shape of the shield by investigating a large number of possible leakages rapidly. Recent breakthroughs in numerical methods make it possible to apply simulations to industrial design concepts. The employed approach is based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) method.

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.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

During the last ten years, there is a significant tendency in automotive design to use lower aspect ratio tires and meanwhile also more and more run-flat tires. In appropriate publications, the influences of these tire types on the dynamic loads - transferred from the road passing wheel center into the car - have been investigated pretty well, including comparative wheel force transducer measurements as well as simulation results. It could be shown that the fatigue input into the vehicle tends to increase when using low aspect ratio tires and particularly when using run-flat tires. But which influences do we get for the loading and fatigue behavior of the respective rims? While the influences on the vehicle are relatively easy to detect by using wheel force transducers, the local forces acting on the rim flange (when for example passing a high obstacle) are much more difficult to detect (in measurement as well as in simulation).

With the introduction of new regulations on emissions, fuel efficiency, driving cycles, etc. challenges for the powertrains are significantly increasing. In order to fulfil these regulations, hybrid-electric powertrains are an unquestioned option for short and long-term solutions. Hybridization however, is not only fulfilling these challenging efficiency or emission targets, but also allows numerous new possibilities on control strategies of different powertrain elements as well as new approaches of designing them. A good example is transmissions where, hybridization allows a new transmission type called Dedicated Hybrid Transmission (DHT), which enables to use novel control strategies bringing improved performance, driveability, durability and NVH behavior. This paper focuses on the novel shift strategy where friction clutches do not have to slip.

This paper describes a numerical study of the effect of hollow crankshafts on crankshaft local strength and durability as well as slider bearing contact behavior. Crankshaft dynamic simulation for durability is still a challenging task, although numerical methods are already worldwide established and integrated part of nearly every standard engine development process. Such standard methods are based on flexible multi-body dynamic simulation, combined with Finite Element analysis and multi-axial fatigue evaluation. They use different levels of simplification and consider the most influencing phenomena relevant for durability. Lightweight design and downsizing require more and more detailed methods due to higher deformation of the crankshaft. This is especially true for hollow shafts, as present in motorsport design or aerospace applications, but also for standard engine having high potential for significant weight savings.

The acoustics of automotive intake and exhaust systems is typically modeled using linear acoustics or gas-dynamics simulation. These approaches are preferred during basic sound design in the early development stages due to their computational efficiency compared to complex 3D CFD and FEM solutions. The linear acoustic method reduces the component being modelled to an equivalent acoustic two-port transfer matrix which describes the acoustic characteristic of the muffler. Recently this method was used to create more detailed and more accurate models based on a network of 3D cells. As the typical automotive muffler includes perforated elements and sound absorptive material, this paper demonstrates the extension of the 3D linear acoustic network description of a muffler to include the aforementioned elements. The proposed method was then validated against experimental results from muffler systems with perforated elements and sound absorptive material.

The paper focuses on an optimization methodology, which uses Design of Experiments (DoE) methods to define component parameters of parallel hybrid powertrains such as number of gears, transmission spread, gear ratios, progression factor, electric motor power, electric motor nominal speed, battery voltage and cell capacity. Target is to find the optimal configuration based on specific customer targets (e.g. fuel consumption, performance targets). In the method developed here, the hybrid drive train configuration and the combustion engine are considered as fixed components. The introduced methodology is able to reduce development time and to increase output quality of the early system definition phase. The output parameters are used as a first hint for subsequently performed detailed component development. The methodology integrates existing software tools like AVL CRUISE [5] and AVL CAMEO [1].

The present paper deals with the application of the LES approach to in-cylinder flow modeling. The main target is to study cycle-to-cycle variability (CCV) using 3D-CFD simulation. The engine model is based on a spark-ignited single-cylinder research engine. The results presented in this paper cover the motored regime aiming at analysis of the cycle-resolved local flow properties at the spark plug close to firing top dead center. The results presented in this paper suggest that the LES approach adopted in the present study is working well and that it predicts CCV and that the qualitative trends are in-line with established knowledge of internal combustion engine (ICE) in-cylinder flow. The results are evaluated from a statistical point of view based on calculations of many consecutive cycles (at least 10).

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

Rattle noise produced in the vehicle interior due to broadband excitation by road irregularities is a major concern with respect to driving comfort, and therefore has become one of the most important topics of acoustic development in recent years. A quantification i.e. measurement of this rattle noise is of fundamental importance for systematic development work and production control. Common noise level measurements (dB, dBA, etc. ) do not represent the rattle character in the vehicle interior as revealed during initial investigations. To overcome this problem and to substitute the subjective assessment with a combination of measurable parameters, the psychoacoustic software AVL-EAR was applied to create an Interior Rattle Quality Index. Based on more than 40 different vehicles that have been subjectively assessed by approximately 70 test persons, the index was generated by means of multiple pair comparisons and statistics on measurement data.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

Vibration testing is common in automotive industry validation and gains greater significance with increasing numbers of electrical components, which are particularly suspectable to vibration related failures. While the nature and intention of vibration testing is common, many contradicting testing standards claim to be a one-size-fits-all solution, leading to questions of which standard is correct for any specific application. This is compounded by the vast variation in vehicle types and applications (suspension systems, dampers, powertrain mass, tire radius, intended usage, etc.) This paper seeks to offer and demonstrate a method to determine characteristic vibration profiles, based on vehicle classes, and illuminate the process to accelerate these to an appropriate test profile. This can either be used to directly validate a system or to support the selection of the most appropriate vibration profile from options within standards.

With the increasing stringent emissions legislation on ICEs, alongside requirements for enhanced fuel efficiency as key driving factors for many OEMs, there are many research activities supported by the automotive industry that focus on the development of hybrid and pure EVs. This change in direction from engine downsizing to the use of electric motors presents many new challenges concerning NVH performance, durability and component life. This paper presents the development of experimental methodology into the measurement of NVH characteristics in these new powertrains, thus characterizing the structure borne noise transmissibility through the shaft and the bearing to the housing. A feasibility study and design of a new system level test rig have been conducted to allow for sinusoidal radial loading of the shaft, which is synchronized with the shaft’s rotary frequency under high-speed transient conditions in order to evaluate the phenomena in the system.

The noise vibration and harshness (NVH) simulation of electric machines becomes increasingly important due to the use of electric machines in vehicles. This paper describes a method to reduce the calculation time and required memory of the finite element NVH simulation of electrical machines. The stator of a synchronous electrical machine is modeled as a two-dimensional problem to reduce investigation effort. The electromagnetic forces acting on the stator are determined by FE-simulation in advance. Since these forces need to be transferred from the electromagnetic model to the structural model, a coupling algorithm is necessary. In order to reduce the number of nodes, which are involved in the coupling between the electromagnetic and structural model, multipoint constraints (MPC) are used to connect several coupling nodes to one new coupling node. For the definition of the new coupling nodes, the acting load is analyzed with a 2D-FFT.

This paper presents a system-level thermal model of a fluid-cooled Li-Ion battery module. The model is a reduced order model (ROM) identified by results from finite element analysis (FEA)/computational fluid dynamic (CFD) coupling simulation using the linear and time-invariant (LTI) method. The ROM consists of two LTI sub-systems: one of which describes the battery temperature response to a transient battery current, and the other of which takes into account of the battery temperature variation due to a heat flux induced by a varied inlet temperature of the battery cooling circuit. The thermal LTI model can be coupled to an electrical model to build a complete system-level battery ROM. Test examples show that the ROM is able to provide as accurate results as those from FEA/CFD coupling simulations.

A growing development of hybrid or fully electrical drives increases the demand for an accurate prediction of noise and vibration characteristics of electric and electronic components. This paper describes the numerical and experimental investigation of noise emissions from power electronics, as one of the new important noise sources in electric vehicles. The noise emitted from the printed circuit board (PCB) equipped with multi-layer ceramic capacitors (MLCC) is measured and used for the calibration and validation of numerical model. Material properties are tuned using results from experimental modal analysis, with special attention to the orthotropic characteristic of the PCB glass-reinforced epoxy laminate sheet (FR-4). Electroacoustic excitation is pre-calculated using an extension of schematic-based EMC simulation and applied to the structural model. Structural vibrations are calculated with a commercial FEM solver with the modal frequency response analysis.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.