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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.

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).

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.

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 present work introduces a fully integrated real-time (RT) capable engine and vehicle model. The gas path and drive line are described in the time domain of seconds whereas the reciprocating characteristics of an IC engine are reflected by a crank angle resolved cylinder model. The RT engine model is derived from a high fidelity 1D cycle simulation and gas exchange model to support an efficient and consistent transfer of model data like geometries, heat transfer or combustion. The workflow of model calibration and application is outlined and base ECU functionalities for boost pressure, EGR, smoke and idle speed control are applied for transient engine operation. Steady state results of the RT engine model are compared to experimental data and 1D high fidelity simulations for 19 different engine load points. In addition an NEDC (New European Drive Cycle) is simulated and results are evaluated with data from chassis dynamometer measurements.

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).

The present work introduces an innovative mechanistically based 0D spray model which is coupled to a combustion model on the basis of an advanced mixture controlled combustion approach. The model calculates the rate of heat release based on the injection rate profile and the in-cylinder state. The air/fuel distribution in the spray is predicted based on momentum conservation by applying first principles. On the basis of the 2-zone cylinder framework, NOx emissions are calculated by the Zeldovich mechanism. The combustion and emission models are calibrated and validated with a series of dedicated test bed data specifically revealing its capability of describing the impact of variations of EGR, injection timing, and injection pressure. A model based optimization is carried out, aiming at an optimum trade-off between fuel consumption and engine-out emissions. The findings serve to estimate an economic optimum point in the NOx/BSFC trade-off.

For a broad acceptance of electric vehicles, the trade-off between all electric range and battery cost respectively weight represents the most important challenge. The all electric range obtained under real world conditions most often deviates significantly from the nominal value which is measured under idealized conditions. Under extreme conditions - slow traffic and demanding requirements for cabin heating or cooling - the electrical range might become less a question of spatial distance but even more of total operation time. Whereas with conventional powertrain, high flexibility of the total driving range can be obtained without sacrificing cost, with a pure battery vehicle this results in extreme high cost and weight of the energy storage. Therefore the difference between the typical daily driving range (e.g. in Germany 80-90% is below 50 km) and the minimum total range requested by most customers for acceptance of battery vehicles (200- 250 km), becomes essential.

This paper presents the results of part of the research activity carried out by the Politecnico di Torino and AVL List GmbH as part of the European Community InGAS Collaborative Project. The work was aimed at developing a combustion system for a mono-fuel turbocharged CNG engine, with specific focus on performance, fuel economy and emissions. A numerical and experimental analysis of the jet development and mixture formation in an optically accessible, single cylinder engine is presented in the paper. The experimental investigations were performed at the AVL laboratories by means of the planar laser-induced fluorescence technique, and revealed a cycle-to-cycle jet shape variability that depended, amongst others, on the injector characteristics and in-cylinder backpressure. Moreover, the mixing mechanism had to be optimized over a wide range of operating conditions, under both stratified lean and homogeneous stoichiometric modes.

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining component technology with integration and industrialization requirements when heading for further significant efficiency optimization of the subsystem internal combustion engine. The requirements on the combustion engine in hybrid powertrains are quite different to those in a conventional powertrain solution. Next-generation hybrid engines, with brake thermal efficiency (BTE) targets starting from 42-43% and aiming for 45% and above within the product lifecycle, require a re-thinking of the base engine architecture of current modular engine platforms. At the same time focus on the product cost and minimized additional investment demand reuse of current production, machining and assembly facilities as far as possible.

The rate in the electrification of vehicles has risen in recent years and, despite that electric vehicles are quiet, NVH remains a major requirement of vehicle development. The typical NVH issues are gear whine from the gearbox, noise from the E-machine or electromagnetic whine, as well as the noise from the inverter, and noise from inverter harmonics effect on E-machine. Simulation methodologies and CAE workflows are being enhanced to contribute to electric drive systems development. Front loading in the concept and layout design phase are necessary to avoid significant NVH issues at the end of development. The authors previously presented a workflow for combining the electric and mechanical noise for electric drives for the concept and layout design phases. This paper shows an application of the formerly presented workflow for NVH simulation and validation of a system with an Interior Permanent Magnet (IPM) E-machine.

Growing development of hybrid and fully electrical drives increases demand for accurate prediction of noise and vibration characteristic of electric and electronic components. This paper describes the numerical and experimental investigation of noise emission from PMSM electric machine as a one of the most important noise sources in electric vehicles. Structural and air borne noise is measured on e-machine test rig and used for calibration and validation of the numerical model. The electro-magnetic field in PMSM is simulated using finite volume method. Electro-magnetic forces are applied as excitation to the 3D FE model of e-machine, mounded on test frame. Material properties are tuned using results from experimental modal analysis including identification of orthotropic characteristic of stator laminated core, assembled together with coil and end winding. Structural vibrations are calculated by modal frequency response analysis and applied as excitation in air borne noise simulation.

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.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.

The present works presents a real-time capable engine model with physical based description of the fuel injection and the combustion process. The model uses a crank-angle resolved cylinder model and a filling and emptying approach for cylinder and gas-path interaction. A common rail injection system model is developed and implemented into the real-time engine framework. The injection model calculates injection quantity and injection rate profile from the input of the ECU signals target injection pressure and injection timing. The model accounts for pressure oscillations in the injection system. A phenomenological combustion model for Diesel engines is implemented, which is based on the mixing controlled combustion modeling approach. The combustion model calculates the rate of heat release from the injection rate given by the injection model. The injection and combustion model are validated in detail against steady-state measurement data for two different passenger car sized engines.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Furthermore the increasing number of vehicle configurations leads to a high variability and degrees of freedom in possible system designs and the control thereof, which can only be handled by a comprehensive tool chain of vehicle system simulation and a generic control system architecture. The required model must comprise all relevant systems of the vehicle (control functionality, cooling system, lubrication system, engine, drive train, HV components etc.). For proper prediction with respect to energy consumption all interactions and interdependencies of those systems have to be taken into consideration, i.e. all energy fluxes (mechanical, hydraulically, electrical, thermal) have to be exchanged among the system boundaries accordingly.

The correct information about legal demands of the On-Board-Diagnostic (OBD) system in a vehicle project is required throughout the entire development process. Usually, the main obstacle in succeeding is to provide the company's expertise of some few experts for all employees who work in OBD related projects. The paper describes the AVL solution for knowledge management and tool supported control system design and calibration: OBD System Development Database. The software enables the user to access the regulatory requirements for a specific application and legislation from past, present and future (proposed rule-making) point of view. Information concerning already available and stored monitoring concepts is linked to the requirements in order to re-use potentially suitable concepts and to enable an efficient knowledge exchange within the company.