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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.

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.

To promote advanced combustion strategies complying with stringent emission regulations of CI engines, computational models have to accurately predict the injector inner flow and cavitation development in the nozzle. This paper describes a coupled 1D/2D/3D modeling technique for the simulation of fuel flow and nozzle cavitation in diesel injection systems. The new technique comprises 1D fuel flow, 2D multi-body dynamics and 3D modeling of nozzle inner flow using a multi-fluid method. The 1D/2D model of the common rail injector is created with AVL software Boost-Hydsim. The computational mesh including the nozzle sac with spray holes is generated with AVL meshing tool Fame. 3D multi-phase calculations are performed with AVL software FIRE. The co-simulation procedure is controlled by Boost-Hydsim. Initially Hydsim performs a standalone 1D simulation until the needle lift reaches a prescribed tolerance (typically 2 to 5 μm).

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.

This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

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.

Today’s automotive industry is changing rapidly towards environmentally friendly vehicle propulsion systems. All over the globe, legislative CO2 consumption targets are under discussion and partly already in force. Hybrid powertrain configurations are capable to lower fuel consumption and limit pollutant emissions compared to pure IC-Engine driven powertrains. Depending on boundary conditions a numerous of different hybrid topologies- and its control strategies are thinkable. Typical approach is to find the optimum hybrid layout and strategy, by performing certain technical design tasks in office simulation directly followed by vehicle prototype tests on the chassis dyno and road. This leads to a high number of prototype vehicles, overload on chassis dynos, time consuming road test and finally to tremendous costs. Our developed approach is using the engine testbed with simulation capabilities as bridging element between office and vehicle development environment.

Reynolds-averaged Navier-Stokes (RANS) computations of heat transfer involving wall bounded flows at elevated Prandtl numbers typically suffer from a lack of accuracy and/or increased mesh dependency. This can be often attributed to an improper near-wall turbulence modeling and the deficiency of the wall heat transfer models (based on the so called P-functions) that do not properly account for the variation of the turbulent Prandtl number in the wall proximity (y+< 5). As the conductive sub-layer gets significantly thinner than the viscous velocity sub-layer (for Pr >1), treatment of the thermal buffer layer gains importance as well. Various hybrid strategies utilize blending functions dependent on the molecular Prandtl number, which do not necessarily provide a smooth transition from the viscous/conductive sub-layer to the logarithmic region.

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 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.

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.

This study deals with the experimental investigation of the mechanical properties of a lithium-ion pouch cell and its modelling in an explicit finite element simulation code. One can distinguish between ‘macroscopic’ and ‘microscopic’ modelling approaches. In the ‘macroscopic’ approach, one material model approximates the behaviour of multiple inner cell layers. In the ‘microscopic’ approach, which is used in the present study, all layers and their interactions are modelled separately. The cell under study is a pouch-type lithium-ion cell with a liquid electrolyte. With its cell chemistry, design, size and capacity it is usable for automotive applications and can be assembled into traction batteries. One cell sample was fully discharged and disassembled, and its components (anode, cathode, separator and pouch) were examined and measured by electron microscopy. Components were also tensile tested.

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 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.

The modern power train calibration process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust aftertreatment and emission testing is becoming increasingly more sophisticated. The introduction of predictive simulation tools that represent the complete power train can likely contribute to improving the efficiency of the calibration process using an integral model based workflow. Engine models, which are purely based on complex physical principles, are usually not capable of real-time applications, especially if the simulation is focused on transient emission optimization. Methods, structures and the realization of a global dynamic real-time model are presented in this paper, combining physical knowledge and experimental models and also static and dynamic sub-structures. Such a model, with physical a priori information embedded in the model structure, provides excellent generalization capability.

Today's calibration process for ECU functions is often based on a wide variety of proprietary tools and individual expert knowledge of calibration engineers. Automatic calibration with an industrialized tool chain provides high potential to reduce testbed time, calibration time and project costs. Based on an efficient measurement procedure in combination with an offline calibration methodology the capability is validated, e.g. for calibrating the ECU function “Air Charge Determination” for SI engines. In this article the implementation, in a series production project of a major OEM, is shown. The whole workflow - which can also be applied to other calibration tasks - will be described in detail. Presented here will be how General Motors Corporation (GM) is able to speed up the calibration of the ECU functions, whilst maintaining at least the same quality of calibration as before, by the use of this tool chain.