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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).

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.

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.

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.

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).

This paper presents a simulation environment and methodology for noise and vibration analyses of a driven rear axle in a bus application, with particular focus on medium to high frequency range (400 Hz to 3 kHz). The workflow demonstrates structure borne noise and sound radiation analyses. The fully flexible Multi-Body Dynamics (MBD) model - serving to cover the actual mechanical excitation mechanisms and the structural domain - includes geometrical contacts of hypoid gear in the central gear and planetary gear integrated at hubs, considering non-linear meshing stiffness. Contribution of aforementioned gear stages, as well as the propeller shaft universal joint at the pinion axle, on overall axle noise levels is investigated by means of sensitivity analysis. Based on the surface velocities computed at the vibrating axle-housing structure the Wave Based Technique (WBT) is employed to solve the airborne noise problem and predict the radiated sound.

Combustion of premixed stoichiometric charge is free of soot particle formation. Consequently, the development of direct injection (DI) spark ignition (SI) engines aims at providing premixed charge to avoid or minimize soot formation in order to meet particle emissions targets. Engine development methods not only need precise engine-out particle measurement instrumentation but also sensors and measurement techniques which enable identification of in-cylinder soot formation sources under all relevant engine test conditions. Such identification is made possible by recording flame radiation signals and with analysis of such signals for premixed and diffusion flame signatures. This paper presents measurement techniques and analysis methods under normal engine and vehicle test procedures to minimize sooting combustion modes in transient engine operation.

The paper is devoted to the coupled 1D-3D modeling technology of injector flow and cavitation in diesel injections systems. The technology is based on the 1D simulation of the injector with the AVL software BOOST-HYDSIM and 3D modeling of the nozzle flow with AVL FIRE. The nozzle mesh with spray holes and certain part of the nozzle chamber is created with the FIRE preprocessor. The border between the 1D and 3D simulation regions can be chosen inside the nozzle chamber at any position along the needle shaft. Actual coupling version of both software tools considers only one-dimensional (longitudinal) needle motion. Forthcoming version already includes the two-dimensional motion of the needle. Furthermore, special models for the needle tip contact with the nozzle seat and needle guide contact with the nozzle wall are developed in HYDSIM. The co-simulation technology is applied for different common rail injectors in several projects.

Currently lithium-batteries are the most promising electrical-energy storage technology in fully-electric and hybrid vehicles. A crashworthy battery-design is among the numerous challenges development of electric-vehicles has to face. Besides of safe normal operation, the battery-design shall provide marginal threat to human health and environment in case of mechanical damage. Numerous mechanical abuse-tests were performed to identify load limits and the battery's response to damage. Cost-efficient testing is provided by taking into account that the battery-system's response to abuse might already be observed at a lower integration-level, not requiring testing of the entire pack. The most feasible tests and configurations were compiled and discussed. Adaptions of and additions to existing requirements and test-procedures as defined in standards are pointed out. Critical conditions that can occur during and after testing set new requirements to labs and test-rigs.

The present paper deals with the application of the LES approach to in-cylinder flow modeling. The main target is to study cycle-to-cycle variability (CCV) using 3D-CFD simulation. The engine model is based on a spark-ignited single-cylinder research engine. The results presented in this paper cover the motored regime aiming at analysis of the cycle-resolved local flow properties at the spark plug close to firing top dead center. The results presented in this paper suggest that the LES approach adopted in the present study is working well and that it predicts CCV and that the qualitative trends are in-line with established knowledge of internal combustion engine (ICE) in-cylinder flow. The results are evaluated from a statistical point of view based on calculations of many consecutive cycles (at least 10).

Fast charging of batteries at cold conditions faces the challenge of promoting undesired cell degradation phenomena such as lithium plating. The occurrence of lithium plating is strongly related to local surface potentials and temperatures involving the scales of the electrode surface, the unit cell and the entire module or pack. A multi-scale, multi-domain model is presented, enhancing a Newman based unit cell model with consistent models for heat generation and lithium plating and integrating this 1D+1D approach into a thermal 3D model on module level. The basic equations are presented and three different plating models from literature are discussed. The thermal model is assessed in open-loop simulations and the different plating approaches are compared in charge/discharge simulations at different operating conditions. The full multi-scale, multi-domain model is applied as a virtual sensor for model-based control of fast charging at cold conditions.

This work elaborates the transferability of electrode diffusion coefficients gained from fitting procedures in frequency domain to an electrochemical battery model run in time domain. An electrochemical battery model of an NMC622 half-cell electrode is simulated with sinusoidal current excitations at different frequencies. The current and voltage signals are analyzed in frequency domain via Nyquist and Bode plots. The frequency domain analysis of time domain simulations is applied to assess the numerical convergence of the simulation and the sensitivity on particle diameter, electrode and electrolyte diffusion coefficients. The simulated frequency spectra are used to fit the electrode diffusion coefficient by means of different electrical equivalent circuit models and the electrochemical battery model itself. The fitted diffusion coefficients from the different electrical equivalent circuit models deviate by one order of magnitude from the a priori known reference data.

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.

A growing development of hybrid or fully electrical drives increases the demand for an accurate prediction of noise and vibration characteristics of electric and electronic components. This paper describes the numerical and experimental investigation of noise emissions from power electronics, as one of the new important noise sources in electric vehicles. The noise emitted from the printed circuit board (PCB) equipped with multi-layer ceramic capacitors (MLCC) is measured and used for the calibration and validation of numerical model. Material properties are tuned using results from experimental modal analysis, with special attention to the orthotropic characteristic of the PCB glass-reinforced epoxy laminate sheet (FR-4). Electroacoustic excitation is pre-calculated using an extension of schematic-based EMC simulation and applied to the structural model. Structural vibrations are calculated with a commercial FEM solver with the modal frequency response analysis.

Modern safety and comfort features must behave country specific to the local environment and traffic conditions in order to gain end consumers’ trust and strengthening OEMs market success respectively. In order to achieve this, a new methodology was developed. In this paper, the approach for designing advanced driving assistance systems (ADAS) with a tailored controller behavior optimized for country specific market expectations like in India is described. Furthermore, the definition of objective performance and calibration targets with automated evaluation of target fulfillment will be deeply discussed. The method is focused on saving time at calibration and validation without compromising the quality of ADAS features. Local market specific driving behavior is investigated and measurement data from real-world driving collected. Data clustering via maneuver detection is performed automatically, which is saving time and effort.

The internal combustion engine contains several actuators to control engine performance and emissions. These are controlled within the engine ECU and follow a specific operating strategy to achieve objectives such as NOx reduction and fuel economy. However, these two goals are conflicting and a compromise is required. The operating state depends on system constraints such as engine speed, load, temperature levels, and aftertreatment system efficiency. This results in constantly changing target values to stay within the defined limits, especially the legal emission limits. The conventional approach is to use multiple operating modes. Each mode represents a specific compromise and is activated accordingly. Multiple modes are required to meet emissions regulations under all required conditions, which increases the calibration effort. This new control approach uses an artificial neural network to replace the conventional multiple mode approach.

Calibrating a vehicle’s powertrain for dynamic operation needs to focus on efforts to mitigate the risks of thermal overload which may arise in the stator or rotor components of an e-motor. Risks also may arise for expected NVH or durability targets, with torque and torque “oscillations” acting as primary sources for the vehicles’ NVH behavior. Both topics, temperature measurement of stator and rotor as well as dynamic torque measurements of the powertrain’s drive shaft are addressed with examples demonstrating the sensors applications in normal test bed and vehicle configurations.

As electrified powertrains trends towards the new norm in development, the need to consider modular development approaches becomes more prevalent. Modular system developments seek to offer an adaptable product range by considering each system component (transmission, e-motor, inverter, battery, etc.) and system element (park-lock, disconnect, differential, etc.) as interchangeable. This can result in a lower cost development process overall to increase the returns for tier1 suppliers by expanding the marketability of the platform. Such an approach has hitherto held relatively low commercial interest as the rate of technological advancement negated the benefits of a modular development due to the lack of long-term competitivity. Previously large technological advances between successive productions and the relatively limited EV market, centred around SUV and small car applications, reduced the value in committing to a platform development.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.