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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).

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.

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.

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.

Due to the continuous electrification of vehicles, the variety of different hybrid topologies is expected to increase in the future. As the calibration of real-time capable energy management systems (EMS) is still challenging, a development framework for the EMS that is independent of the hybrid topology would simplify the overall development process of hybrid vehicles. In this paper an analytical methodology, which is used to derive a fuel-optimal, rule-based EMS for parallel hybrids, is transferred to a series topology. It is shown that the fundamental correlations can be applied universally to both parallel and series configurations. This enables the possibility to develop a real-time capable, rule-based controller for a series HEV based on maps that ensures a fuel-optimal operation. These maps provide the optimal power threshold for the activation of the auxiliary power unit and the optimal power output dependent on the driver’s power request.

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.

The present work introduces an extended particulate filter model focusing on capabilities to cover catalytic and surface storage reactions and to serve as a virtual multi-functional reactor/separator. The model can be classified as a transient, non-isothermal 1D+1D two-channel model. The applied modeling framework offers the required modeling depth to investigate arbitrary catalytic reaction schemes and it follows the computational requirement of running in real-time. The trade-off between model complexity and computational speed is scalable. The model is validated with the help of an analytically solved reference and the model parametrization is demonstrated by simulating experimentally given temperatures of a heat-up measurement. The detailed 1D+1D model is demonstrated in a concept study comparing the impact of different spatial washcoat distributions.

This paper aims to contribute to the development of an electronic stability control for narrow, fully tiling vehicles with handling and stability characteristics similar to motorcycles, and to improve the understanding of the driver-vehicle interaction. To allow for high energy efficiency of the control system, mainly steering torque is applied to stabilize and tilt the vehicle. The dynamic properties of the specific investigated vehicle suggest high demands to a driver without an appropriate control system. To allow for automobile-like operation of the steering wheel, the motion of the steering wheel and the steering system of the front wheel has been decoupled, and a steer-by-wire system has been developed. Both simulations and field tests with a prototype proved proper performance of the electronic stability control, but also revealed the need of an automobile driver to adapt to this kind of vehicle when operating it even with the control system.

The Selective Catalytic Reduction (SCR) is a promising approach to meet future legislation regarding the nitric oxide emissions of diesel engines. In automotive applications a liquid urea-water solution (UWS) is injected into the hot exhaust gas. It evaporates and decomposes to ammonia vapor acting as the reducing agent. Significant criteria for an efficient SCR system are a fast mixture preparation of the UWS and a high ammonia uniformity at the SCR catalyst. Multiphase CFD simulation is capable to support the development of this process. However, major challenges are the correct description of the liquid phase behavior and the simulation of the ammonia vapor mixing in the turbulent exhaust gas upstream of the SCR catalyst. This paper presents a systematic study of the impact of the turbulence model and the numerical spatial discretization scheme on the prediction of the turbulent mixing process of the gaseous ammonia.

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.

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.

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.

For driver assistant systems and drive-by-wire architectures fault detection and diagnosis are essential parts. Fault detection using parity equations is a well known approach which can be implemented in a straightforward way. Especially for fault diagnosis of vehicle sensors good isolating patterns for the interpretation of the residuals are available. However, in critical driving situations false alarms can occur, which may compromise the efficiency of safety relevant stability systems. In this paper a method is presented which reliably detects critical driving situations utilizing the estimated nominal cornering stiffness. The instantaneous cornering stiffness is estimated using the sideslip angle obtained by an observer. Using this quantity the nominal cornering stiffness can be estimated in order to discern the linear and nonlinear region of the tire model. In the nonlinear region false alarms are likely to occur and simple fault detection using parity equations cannot be used.

Cost- and time-efficient vehicle development is increasingly depending on the usage of adequate software tools to enhance effectiveness. The aim is a continuous integration of simulation tools and test environments within the vehicle development process in order to save time and costs. This paper introduces a procedure to reveal the cause of low-frequency powertrain vibrations and the influences on the dynamic behavior of a vehicle on a roller test bench. The affected longitudinal acceleration signal is an arbitrative criterion for the driveability assessment with AVL-DRIVE™, a well-known driveability analysis and development tool for the objective assessment concerning NVH and driveability aspects of full vehicles. These experimental studies are embedded into an approach, which describes the functional assembly of three applied test environments "road," "roller test bench" and "simulation" with according tools in order to facilitate an integrated driveability development process.

This study presents a methodology to predict particle number (PN) generation on a naturally aspirated 4-cylinder gasoline engine with port fuel injection (PFI) from wall wetting, employing numerical CFD simulation and fuel film analysis. Various engine parameters concerning spray pattern, injection timing, intake valve timing, as well as engine load/speed were varied and their impact on wall film and PN was evaluated. The engine, which was driven at wide open throttle (WOT), was equipped with soot particle sampling technology and optical access to the combustion chamber of cylinder 1 in order to visualise non-premixed combustion. High-speed imaging revealed a notable presence of diffusion flames, which were typically initiated between the valve seats and cylinder head. Their size was found to match qualitatively with particulate number measurements. A validated CFD model was employed to simulate spray propagation, film transport and droplet impingement.