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Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Current e-vehicle platforms still present architectural similarities with respect to combustion engine vehicle (e.g., centralized motor). Target of the European project EVC1000 is to introduce corner solutions with in-wheel motors supported by electrified chassis components (brake-by-wire, active suspension) and advanced control strategies for full potential exploitation. Especially, it is expected that this solution will provide more architectural freedom toward “design-for-purpose” vehicles built for dedicated usage models, further providing higher performances.

Increasing requirements for the result quality of exhaust emission analyzers and state of the art analyzer technology require a new point of view regarding measuring range definitions and linearization procedures. To make best use of the power of this analyzer technology, linearization procedures need reconsideration. In certification laboratories, legislation defines the procedures to linearize an exhaust emission analyzer more or less stringently. On the other hand, on testbeds for development purposes there are many possibilities for making use of today's improved analyzers. However, procedures are often used in development labs that are very similar to those mentioned in the legislation. For some measurement purposes it is necessary to leave these procedures regarding measuring ranges and their specifications behind. The exhaust gas analyzing system has to provide consistent result quality during the whole test procedure.

Today’s automotive industry is changing rapidly towards environmentally friendly vehicle propulsion systems. All over the globe, legislative CO2 consumption targets are under discussion and partly already in force. Hybrid powertrain configurations are capable to lower fuel consumption and limit pollutant emissions compared to pure IC-Engine driven powertrains. Depending on boundary conditions a numerous of different hybrid topologies- and its control strategies are thinkable. Typical approach is to find the optimum hybrid layout and strategy, by performing certain technical design tasks in office simulation directly followed by vehicle prototype tests on the chassis dyno and road. This leads to a high number of prototype vehicles, overload on chassis dynos, time consuming road test and finally to tremendous costs. Our developed approach is using the engine testbed with simulation capabilities as bridging element between office and vehicle development environment.

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.

Fuel consumption is the most important contributor to the total cost of ownership for mass produced motorcycles. Therefore, best fuel economy is one main influencing criteria for a decision to purchase motorcycles. Furthermore, increasingly stringent emission legislations limit and additional OBD requirements must be fulfilled. A new combined test approach has been developed that minimizes accuracy losses in the development process which compensates for the variability of driving behavior in the chassis dyno environment. An engine testbed combined with a belt drive transmission enables operation in single engine or in Powerpack (i.e. internal combustion engine including transmission) configuration as well as under steady state or dynamic operating mode. Since the belt drive transmission is integrated in the test rig, realistic inertia situation for the single engine operating test configuration is ensured.

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).

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.

System lubrication in automotive powertrains is a growing topic for development engineers. Hybrid and pure combustion system complexity increases in search of improved efficiency and better control strategy, increasing the number of components with lubrication demand and the interplay between them, while fully electric systems drive for higher input speeds to increase e-motor efficiency, increasing bearing and gear feed rate demands. Added to this, many e-axle and hybrid systems are in development with a shared medium and circuit for e-motor cooling and transmission lubrication. Through all this, the lubricant forms a common thread and is a fundamental component in the system, but no standardized tests can provide a suitable methodology to investigate the adequate lubrication of components at powertrain level, to support the final planned vehicle usage.

In 2017 the European authorities put into effect the first part of a new certification test procedure for Real Driving Emissions (RDE). Similar tests are planned in other regions of the world, such as the upcoming China 6a/6b standards, further tightening emission limits, and also the introduction of RDE tests. Both restrictions pose challenging engineering tasks for upcoming vehicles. RDE certification tests feature significantly more demanding engine operating conditions and thus, emit more pollutants by orders of magnitude compared to known cycles like NEDC. Here, especially the reduction of NOx is a specific technical challenge, as it needs to compromise also with reduction targets on carbon dioxide. The fulfilment of both emission limits requires a widening of the focus from an isolated engine or exhaust aftertreatment view to a system engineering view involving all hardware and software domains of the vehicle.

State-of-the-art motorcycle engines consist of numerous variable components and require a powerful motor management to meet the growing customer expectations and the legislative requirements (e.g. exhaust and noise emissions, fuel consumption) at the same time. These demands are often competing and raise the level of complexity in calibration. In the racing domain, the optimization requirements are usually higher and test efficiency is crucial. Whilst the number of variables to control is growing, the time to perform an engine optimization remains the same or is even shortened. Therefore, simulation is becoming an essential part of the engine calibration optimization. Considering the special circumstances in racing, involving valuable hardware, as well as extremely short development and calibration iteration loops, only transient testing is possible.

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.

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).

Over the past 30 years, simulation of the N&V (Noise and Vibration) behaviour of automotive drivelines became an integral part of the powertrain development process. With current and future HEVs (Hybrid-Electrical Vehicles), additional phenomena and effects have entered the scene and need to be taken into account during layout/design as well as optimization phase. Beside effects directly associated with the e-components (namely electric whistle and whine), torque changes caused by activation/deactivation of the e-machine give rise to vibration issues (e.g. driveline shuffle or clonk) as well. This is in particular true for transient operation conditions like boosting and recuperation. Moreover, aspects of starting the Internal Combustion Engine (ICE) using the built-in e-machine in conjunction with the dynamic behaviour of torsional decoupling devices become increasingly important. In order to cope with above-mentioned effects a multi-physics simulation approach is required.

Gear trains applied to automotive transmissions and combustion engines are potential excitation sources of undesired whine noise. Consequently, the prediction of gear whine issues in an early stage of the product development process is strongly requested. Beside the actual excitation mechanism which is closely related to the gear's transmission error, the vibratory behavior (e.g. resonances) of other affected components like shafts, bearings and housing plays an important role in terms of structure borne noise transfer. The paper deals with gear contact models of different degree of detail, which are embedded in a multi-body dynamics (MBD) environment. Since gear meshing frequency and their harmonics may easily reach up to 5 kHz or even 10 kHz, applied gear contact models must be highly efficient with respect to calculation performance. Otherwise, major requirements of the development process in terms of process time can not be satisfied as is the case with FEA-based contact models.

Over the past few years, the fuel mass measurement gained in importance to record the consumed fuel mass and the specific fuel consumption [g/kWh] with high accuracy. Measuring instruments, such as positive displacement meters, methods based on the burette or the Wheatstone bridge mass flow meter measure either the volumetric flow and a temperature-dependant fuel density correction is necessary or they have old technology and therefore poor accuracy and repeatability. A new-generation Coriolis sensor featuring an ideal measurement range for engine test beds but still with flow depending pressure drop has been integrated in a fuel meter to ensure that no influence is given to the engine behaviour for example after engine load change. The new Coriolis meter offers better accuracy and repeatability, gas bubble venting and easy test bed integration. For returnless fuel injection systems the fuel system supplies the fuel pressure.

This paper presents a comparison of a hybrid and a conventional powertrain using physical based simulation models on the system engineering level. The system engineering model comprises mechanistic sub-models of the internal combustion engine including exhaust aftertreatment devices, electric components, mechanical drivetrain, thermoregulation system and the corresponding controllers. Essential sub-models are discussed in detail and their interaction on the system level is pointed out. Special attention is paid to compile a real-time capable model by combining mean value air path and drivetrain models with a crank-angle resolved cylinder description and quasi-steady state considerations applied in electrical and cooling networks. A turbocharged gasoline direct injection engine is modeled and calibrated based on steady-state measurements. The conversion performance of a three way catalyst is compared to light-off measurements.

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.

Fused filament fabrication (FFF) 3D printing technology, one of the most accessible additive manufacturing technologies, can be used to create sensors based on different sensing principles, e.g.: capacitance, inductance, piezoelectricity, piezoresistivity. Piezoresistivity (strain-dependent electrical resistivity) has been predominantly used for the creation of static/quasistatic 3d printed sensors with relatively low sensitivity. This study researches the possibilities of a single-process 3d printing of a piezoresistive accelerometer. Initially, the methods for the axial and cross-axial identification of the piezoresistive properties are discussed. It is shown that the sensitivity is highly dependent on the printing parameters, especially the printing track orientation vs the mechanical load orientation. The research on the sensitivity of a 3D printed piezoresistive structure is extended with an inertial mass-based accelerometer design.

In the virtual development process validated simulation models are requested to accurately predict power train vibration and comfort phenomena. Conclusions from refined parameter studies enable to avoid costly tests on rigs and on the road. Thereby, an appropriate modeling approach for specific phenomena has to be chosen to ensure high quality results. But then, parameters for characterizing the dynamic properties of components are often insufficient and have to be roughly estimated in this development stage. This results in a imprecise prediction of power train resonances and in a less conclusive understanding of the considered phenomena. Conclusions for improvements remain uncertain. This paper deals with the two different aspects of model refinement and parameter updating. First an existing power train model (predecessor power train) is analyzed whether the underlying modeling approach can reproduce the physical behavior of the power train dynamics adequately.