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Cybersecurity assumes a major role in the context of the automotive domain, where both existing and forthcoming regulations are heightening the need for robust security engineering. A significant milestone in advancing cybersecurity within the automotive industry is the release of the first international standard for automotive cybersecurity ISO/SAE 21434:2021 ‘Road Vehicles — Cybersecurity Engineering’. A recently published type approval regulation for automotive cybersecurity (UN R155) is also tailored for member countries of the UNECE WP.29 alliance. Thus, the challenges for embedded automotive systems engineers are increasing while frameworks, tools and shared concepts for cybersecurity engineering and training are scarce.

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.

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.

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.

Hybrid powertrains utilize an engine to benefit from the power density of the liquid fuel to extend the range of the vehicle. On the other hand, the electric machine is used for; transient operation, for very low loads and where legislation prohibits any gaseous and particulate emissions. Consequently, the operating points of an engine nowadays shifted from its conventional, broad range of speed and load to a narrower operating range of high thermal efficiency. This requires a departure from conventional engine architecture, meaning that analytical models used to predict the behavior of the engines early in the design cycle are no longer always applicable. Friction models are an example of sub-models which struggle with previously unexplored engine architectures. The “pressurized motored” method has proven to be a simple experimental setup which allows a robust FMEP determination against which engine friction simulation can be fine-tuned.

The presented paper focuses on the computation of heat transfer related to continuously variable transmissions (CVTs). High temperatures are critical for the highly loaded rubber belts and reduce their lifetime significantly. Hence, a sufficient cooling system is inevitable. A numerical tool which is capable of predicting surface heat transfer and maximum temperatures is of high importance for concept design studies. Computational Fluid Dynamics (CFD) is a suitable method to carry out this task. In this work, a time efficient and accurate simulation strategy is developed to model the complexity of a CVT. The validity of the technique used is underlined by field measurements. Tests have been carried out on a snowmobile CVT, where component temperatures, air temperatures in the CVT vicinity and engine data have been monitored. A corresponding CAD model has been created and the boundary conditions were set according to the testing conditions.

The release of the “Regulation No. 168/2013” for the approval and market surveillance of two- or three-wheel motorcycles and quadricycles of the European Union started a new challenge for the motorcycle industry. One goal of the European Union is to achieve emission parity between passenger cars (EURO 6) and motorcycles (EURO 5) in 2020. The hybridization of motorcycle powertrains is one way to achieve these strict legislation limits. In the automotive sector, hybridization is well investigated and has already shown improvements of fuel consumption, efficiency and emission behavior. Equally, motorcycle applications have a high potential to improve efficiency and to meet customer needs as fun to drive as well. This paper describes a methodical approach to analyze conventional motorcycles regarding the energy and power demand for different driving cycles and driving conditions. Therefore, a dynamic or forward vehicle simulation within MATLAB Simulink is used.

A reduction in CO2 emissions and consequently fuel consumption is essential in the context of future greenhouse gas limits. With respect to the thermodynamic loss analysis of an internal combustion engine, a gap between the net indicated thermal efficiency and the brake thermal efficiency is recognizable. This share is caused by friction losses, which are the focus of this research project. The parasitic loss reduction potential by replacing the mechanical water pump with an electric coolant pump is discussed in the course of this work. This is not a novel approach in light duty vehicles, whereas in commercial vehicles a rigid drive of all auxiliaries is standard. Taking into account an implementation of a 48-V power system in the short or medium term, an electrification of auxiliary components becomes feasible. The application of electric coolant pumps on an Euro VI certified 6-cylinder in-line heavy-duty diesel engine regarding fuel economy was thus performed.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

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 level of infotainment in today's vehicles and the customer expectation of the functionality imply a significant effort is required on thermal management of the systems, to guarantee their full operation under all operating conditions. The worst case thermal conditions the system will get exposed to are caused by solar loading on the cabin or heat up as a result of cabin heating. Simulation of a solar load driven case will be discussed in this paper. The long soak conditions during these tests result in the modelling requirement for long natural convection periods. This is creating a challenge for the conventional CFD simulations in turnaround time. New simulation methodology has resulted in significant speed up enabling these fully transient simulations in a reasonable turnaround time to enable programme support. A two phase approach to simulating this problem is proposed in this paper.

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

In battery electric vehicles (BEV), thermal management is a key technique to improve efficiency and lifetime. Currently, manufacturers use different cooling concepts with numerous architectures. This work describes the development of a co-simulation framework to optimize BEV thermal management on system level, using advanced simulation methodologies also on component level, merging simulation and testing. Due to interactions between multiple conditioning circuits, thermal management optimization requires an overall vehicle approach. Thus, a full vehicle co-simulation of a BEV is developed, combining 1D thermal management software KULI and MATLAB/Simulink. Within co-simulation, the precise modeling of vehicle’s subsystems is important to predict thermal behavior and to calculate dynamic heating and cooling demands as well as exchanged energy flows with the thermal management system.

When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.

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.

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.

An efficient and economic method to increase the performance of four stroke engines can be accomplished by utilizing the crankcase supercharging method. The lubrication of the movable parts in the crankcase by mixing the intake air with lubricant leads to a high oil consumption and disadvantages in the emission characteristics. This paper describes parts of a research project with the goal to develop a supercharged four–stroke engine with a closed loop lubrication system for the crank train and the cylinder head. The thermodynamic layout and the development of an oil separating system have been carried out with the help of simulation tools and development work on a flow test bench.

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.

In recent years, more attentions have been paid to stringent legislations on fuel consumption and emissions. Turbocharged downsized gasoline direct injection (DI) engines are playing an increasing important role in OEM’s powertrain strategies and engine product portfolio. Dongfeng Motor (DFM) has developed a new 1.0 liter 3-cylinder Turbocharged gasoline DI (TGDI) engine (hereinafter referred to as C10TD) to meet the requirements of China 4th stage fuel consumption regulations and the China 6 emission standards. In this paper, the concept of the C10TD engine is explained to meet the powerful performance (torque 190Nm/1500-4500rpm and power 95kW/5500rpm), excellent part-load BSFC and NVH targets to ensure the drivers could enjoy the powerful output in quiet and comfortable environment without concerns about the fuel cost and pollution.

In a tiered cooling pack, the airflow through the individual heat exchangers is determined by the package and aperture lay out. Each heat exchanger rejects heat as a function of the internal coolant flows, the cooling airflow and the air temperature. In a typical automotive cooling pack, the cooling airflow will be non-uniform in velocity and temperature due to fans, aperture geometry, exterior flows, heat exchangers and recirculation. In a drive cycle, these boundary conditions will change with vehicle operating conditions like vehicle speed, engine speed, ambient temperature, and altitude. These non-uniform conditions on the cooling pack can lead to significant errors when uniform boundary conditions are assumed in a transient simulation. This error is commonly corrected using vehicle test data. A predictive approach, which eliminates the need for correlation vehicle testing, is presented.