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A numerical investigation on a series of Diesel spray experiments in constant-volume vessels is proposed. Non reacting conditions were used to assess the spray models and to determine the grid size required to correctly predict the fuel-air mixture formation process. To this end, not only computed liquid and vapor penetrations were compared with experimental data, but also a detailed comparison between computed and experimental mixture fraction distributions was performed at different distances from the injector. Grid dependency was reduced by introducing an Adaptive Local Mesh Refinement technique (ALMR) with an arbitrary level of refinement. Once the capabilities of the current implemented spray models have been assessed, reacting conditions at different ambient densities and temperatures were considered. A Perfectly Stirred Reactor (PSR) combustion model, based on a direct integration of complex chemistry mechanisms over a homogenous cell, was adopted.

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 this work a multilevel CFD analysis have been applied for the design of an intake air-box with improved characteristics of noise reduction and fluid dynamic response. The approaches developed and applied for the optimization process range from the 1D to fully 3D CFD simulation, exploring hybrid approaches based on the integration of a 1D model with quasi-3D and 3D tools. In particular, the quasi-3D strategy is exploited to investigate several configurations, tailoring the best trade-off between noise abatement at frequencies below 1000 Hz and optimization of engine performances. Once the best configuration has been defined, the 1D-3D approach has been adopted to confirm the prediction carried out by means of the simplified approach, studying also the impact of the new configuration on the engine performances.

In the next years, the upcoming emission legislations are expected to introduce further restrictions on the admittable level of pollutants from vehicles measured on homologation cycles and real drive tests. In this context, the strict control of pollutant emissions at the cold start will become a crucial point to comply with the new regulation standards. This will necessarily require the implementation of novel strategies to speed-up the light-off of the reactions occurring in the after-treatment system, since the cold start conditions are the most critical one for cumulative emissions. Among the different possible technological solutions, this paper focuses on the evaluation of the potential of a burner system, which is activated before the engine start. The hypothetical burner exploits the lean combustion of an air-gasoline mixture to generate a high temperature gas stream which is directed to the catalyst section promoting a fast heating of the substrate.

The selective catalytic reduction has seen widespread adoption as the best technology to reduce the NOx emissions from internal combustion engines, particularly for Diesels. This technology uses ammonia as a reducing agent, which is obtained injecting an ammonia carrier into the exhaust gas stream. The dosing of the ammonia carrier, usually AdBlue, is the major concern during the design and engine calibration phases, since the interaction between the injected liquid and the components of the exhaust system can lead to the undesired formation of solid deposits. To avoid this, the thermal and kinematic interaction between the spray and the components of the after treatment system (ATS) must be modeled accurately. In this work, the authors developed a Conjugate Heat Transfer (CHT) framework to model the kinetic and thermal interaction among the spray, the eventual liquid layer and the pipe walls.

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.

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.

A wheel able to measure the generalized forces at the hub of a race motorcycle has been developed and used. The wheel has a very limited mass. It is made from magnesium with a special structure to sense the forces and provide the required level of stiffness. The wheel has been tested both indoor for preliminary approval and on the track. The three forces and the three moments acting at the hub can be measured with a resolution of 1N and 0.3Nm respectively. A specifically programmed DSP (Digital Signal Processor) embedded in the sensor allows real-time acquisition and processing of the six signals of forces/torques components. The signals are sent via Bluetooth to an onboard receiver connected to the vehicle CAN (Controller Area Network) bus. Each signal is sampled at 200Hz. The wheel can be used to derive the actual tyre characteristics or to record the loads acting at the hub.

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.

In the last few years, the effect of diabatic test conditions on compressor performance maps has been widely investigated, leading some Authors to propose different correction models. The accuracy of turbocharger performance map constitute the basis for the tuning and validation of a numerical method, usually adopted for the prediction of engine-turbocharger matching. Actually, it is common practice in automotive applications to use simulation codes, which can either require measured compression ratio and efficiency maps as input values or calculate them “on the fly” throughout specific sub-models integrated in the numerical procedures. Therefore, the ability to correct the measured performance maps taking into account internal heat transfer would allow the implementation of commercial simulation codes used for engine-turbocharger matching calculations.

Nowadays a great attention is paid to the level and quality of noise radiated from the tailpipe end of intake and exhaust systems, to control the gas dynamic noise emitted by the engine as well as the characteristics of the cabin interior sound. The muffler geometry can be optimized consequently, to attenuate or remark certain spectral components of the engine noise, according to the result expected. Evidently the design of complex silencing systems is a time-consuming operation, which must be carried out by means of concurrent experimental measurements and numerical simulations. In particular, 1D and multiD linear/non-linear simulation codes can be applied to predict the silencer behavior in the time and frequency domain. This paper describes the development of a 1D-multiD integrated approach for the simulation of complex muffler configurations such as reverse chambers with inlet and outlet pipe extensions and perforated silencers with the addition of sound absorbing material.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

Many studies have been carried out to optimize the aerodynamic performances of a single car or a single vehicle. In present days the traffic increases and sophisticated technologies are developing to guarantee the drivers safety, to minimize the fuel consumption and be more environmentally friendly. Within this research area a new technique that is being studied is Platooning: this means that different vehicles travel in a configuration that minimizes the aerodynamic drag and therefore the fuel consumption and the longitudinal space. In the present study platoons with different vehicles and configurations are taken into account, to analyze the influence of car shape and relative distance between the vehicles. The research has been carried out using CFD techniques to investigate the different flow fields around different platoons, while wind tunnel tests have been used to validate the results of the CFD simulations.

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.

In this paper, a recently improved Computational Fluid Dynamics (CFD) methodology for virtual prototyping of the heat treatment of cast aluminum parts, above most of cylinder heads of internal combustion engines (ICE), is presented. The comparison between measurement data and numerical results has been carried out to simulate the real time immersion quenching cooling process of realistic cylinder head structure using the commercial CFD code AVL FIRE®. The Eulerian multi-fluid modeling approach is used to handle the boiling flow and the heat transfer between the heated structure and the sub-cooled liquid. While for the fluid region governing equations are solved for each phase separately, only the energy equation is solved in the solid region. Heat transfer coefficients depend on the boiling regimes which are separated by the Leidenfrost temperature.

In recent years, concerns for environmental pollution and oil price stimulated the demand for vehicles based on technologies alternative to traditional IC engines. Nowadays several carmakers include hybrid vehicles among their offer and first full electric vehicles appear on the market. Among the different layout of the electric power-train, four in-wheel motors appear to be one of the most attractive. Besides increasing the inner room, this architecture offers the interesting opportunity of easily and efficiently distribute the driving/braking torque on the four wheels. This characteristic can be exploited to generate a yaw moment (torque vectoring) able to increase lateral stability and to improve the handling of a vehicle. The present paper presents and compares two different torque vectoring control strategies for an electric vehicle with four in-wheel motors. Performances of the control strategies are evaluated by means of numerical simulations of open and closed loop maneuvers.

In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.