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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.

In the virtual development process validated simulation models are requested to accurately predict power train vibration and comfort phenomena. Conclusions from refined parameter studies enable to avoid costly tests on rigs and on the road. Thereby, an appropriate modeling approach for specific phenomena has to be chosen to ensure high quality results. But then, parameters for characterizing the dynamic properties of components are often insufficient and have to be roughly estimated in this development stage. This results in a imprecise prediction of power train resonances and in a less conclusive understanding of the considered phenomena. Conclusions for improvements remain uncertain. This paper deals with the two different aspects of model refinement and parameter updating. First an existing power train model (predecessor power train) is analyzed whether the underlying modeling approach can reproduce the physical behavior of the power train dynamics adequately.

The need for significant reduction of fuel consumption and CO₂ emissions has become the major driver for development of new vehicle powertrains today. For the medium term, the majority of new vehicles will retain an internal combustion engine (ICE) in some form. The ICE may be the sole prime mover, part of a hybrid powertrain or even a range extender; in every case potential still exists for improvement in mechanical efficiency of the engine itself, through reduction of friction and of parasitic losses for auxiliary components. A comprehensive approach to mechanical efficiency starts with an analysis of the main contributions to engine friction, based on a measurement database of a wide range of production engines. Thus the areas with the highest potential for improvement are identified. For each area, different measures for friction reduction may be applicable with differing benefits.

This works presents a real-time capable simulation model for dual fuel operated engines. The computational performance is reached by an optimized filling and emptying modeling approach applying tailored models for in-cylinder combustion and species transport in the gas path. The highly complex phenomena taking place during Diesel and gasoline type combustion are covered by explicit approaches supported by testbed data. The impact of the thermodynamic characteristics induced by the different fuels is described by an appropriate set of transport equations in combination with specifically prepared property databases. A thermodynamic highly accurate 6-species approach is presented. Additionally, a 3-species and a 1-species transport approach relying on the assumption of a lumped fuel are investigated regarding accuracy and computational performance. The comparison of measured and simulated pressure and temperature traces shows very good agreement.

Global warming is the driver for introduction of CO2 and fuel consumption legislation worldwide. Indian truck manufacturers are facing the introduction of Indian fuel efficiency norms. In the European Union the CO2 emission monitoring phase of the most relevant truck classes was completed in June 2020 by usage of the Vehicle Energy Consumption Calculation TOol VECTO. Indian rule makers are currently considering an adaptation of VECTO for the usage in India, too. Indian truck market has always been very cost sensitive. Introduction of Bharat Stage VI Phase I has already led to a significant cost increase for emission compliance. Therefore, it will be of vital importance to keep the additional product costs for achievement of future fuel consumption legislation as low as possible as long as the real-world operation will not be promoted by the government.

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.

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.

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.

The present work describes an existing transient, non-isothermal 1D+1D particulate filter model to capture the impact of different types of particulate matter (PM) on filtration and regeneration. PM classes of arbitrary characteristics (size, composition etc.) are transported and filtered following standard mechanisms. PM deposit populations of arbitrary composition and contact states are used to describe regeneration on a micro-kinetical level. The transport class and deposit population are linked by introducing a splitting deposit matrix. Filtration and regeneration modes are compared to experimental data from literature and a brief numerical assessment on the filtration model is performed. The filter model as part of an exhaust line is used in a concept study on different coating variants. The same exhaust line model is connected to an engine thermodynamic and vehicle model. This system model is run through a random drive cycle in office simulation.

Today's powertrains are becoming more and more complex due to the increasing number of gear box types requiring gearshift patterns like conventional (equipped with GSI) and automatic-manual transmissions (AT, AMT), double clutch and continuous variable transmissions (DCT, CVT). This increasing variety of gear boxes requires a higher effort for the overall optimization of the powertrain. At the same time, it is necessary to assess the impact of different powertrains and control strategies on CO₂ emissions very early in the development process. The optimization of Gear Shift Patterns (G.S.P.) has to fulfill multiple constraints in terms of objective customers' requirements, like driveability, NVH, performance, emissions and fuel consumption. For these reasons, RENAULT and AVL entered an engineering collaboration in order to develop a dedicated simulation tool: CRUISE GSP.

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.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

The Particle Measurement Programme (PMP) developed an exhaust particle number measurement protocol that has been adopted by current light duty vehicle emission regulations in Europe. This includes thermal treatment of the exhaust aerosol to isolate solid particles only and a number counting device with a lower cutpoint of 23 nm to avoid measurement of smaller particles that may affect the repeatability of the measurement. In this paper, we examine a potential alternative to the PMP system, where the thermal treatment is replaced by a catalytic stripper (CS). This offers oxidation and not just evaporation of the volatile components. Alternative sampling systems, either fulfilling the PMP recommendations or utilizing a CS, have been explored in terms of their volatile particle removal efficiency. Tests have been conducted on diesel exhaust, diesel equipped with DPF and gasoline direct injection emissions.

Fuel cell electric vehicles are a promising technology to create CO2- neutral mobility. Model-based development approaches are key to reduce costs and to raise efficiencies. A model on vehicle system level is discussed that balances the need of physical depth and computational performance. The vehicle model comprises the domains of mechanics, electrics, thermodynamics, cooling and controls. Detailed models of the fuel cell and battery are presented as a part of the system model. The models apply electrochemical approaches and spatial resolutions up to 3D. The models of both components are validated via 3D reference simulations showing a seamless parameter transfer between system level and CFD-based simulations. The validity of the vehicle model, including the electrochemical components, is demonstrated by simulating the Toyota Mirai vehicle. Simulation results of an NEDC are compared to measurements.

This paper describes the findings of a design, simulation and test study into how to reduce particulate number (Pn) emissions in order to meet EU6c legislative limits. The objective of the study was to evaluate the Pn potential of a modern 6-cylinder engine with respect to hardware and calibration when fitted to a full size SUV. Having understood this capability, to redesign the combustion system and optimise the calibration in order to meet an engineering target value of 3×1011 Pn #/km using the NEDC drive cycle. The design and simulation tasks were conducted by JLR with support from AVL. The calibration and all of the vehicle testing was conducted by AVL, in Graz. Extensive design and CFD work was conducted to refine the inlet port, piston crown and injector spray pattern in order to reduce surface wetting and improve air to fuel mixing homogeneity. The design and CFD steps are detailed along with the results compared to target.

The European Emissions Stage 5b standard for diesel passenger cars regulates particulate matter to 0.0045 g/km and non-volatile part/km greater than 23 nm size to 6.0x10₁₁ as determined by the PMP procedure that uses a heated evaporation tube to remove semi-volatile material. Measurement artifacts associated with the evaporation tube technique prevents reliable extension of the method to a lower size range. Catalytic stripper (CS) technology removes possible sources of these artifacts by effectively removing all hydrocarbons and sulfuric acid in the gas phase in order to avoid any chemical reactions or re-nucleation that may cause measurement complications. The performance of a miniature CS was evaluated and experimental results showed solid particle penetration was 50% at 10.5 nm. The sulfate storage capacity integrated into the CS enabled it to chemically remove sulfuric acid vapor rather than rely on dilution to prevent nucleation.

Particulate emission reduction has long been a challenge for diesel engines as the diesel diffusion combustion process can generate high levels of soot which is one of the main constituents of particulate matter. Gasoline engines use a pre-mixed combustion process which produces negligible levels of soot, so particulate emissions have not been an issue for gasoline engines, particularly with modern port fuel injected (PFI) engines which provide excellent mixture quality. Future European and US emissions standards will include more stringent particulate limits for gasoline engines to protect against increases in airborne particulate levels due to the more widespread use of gasoline direct injection (GDI). While GDI engines are typically more efficient than PFI engines, they emit higher particulate levels, but still meet the current particulate standards.

Efficient integration of mechanics and microelectronics components is nowadays a must within the automotive industry in order to minimize integration risks and support optimization of the entire system. We propose in this work a cross domain co-simulation platform for the efficient analysis of mechatronic systems. The interfacing of two state-of-the-art simulation platforms provides a direct link between the two domains at an early development stage, thus enabling the validation and optimization of the system already during modeling phase. The proposed cross-domain co-simulation is used within our TEODACS project for the analysis of the FlexRay technology. We illustrate using a drive-by-wire use case how the different architecture choices may influence the system.