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India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.

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.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

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.

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.

Meeting the particle number (PN) emissions limits in vehicle test sequences needs specific attention on each power variation event occurring in the internal combustion engine (ICE). ICE power variations arise from engine start onwards along the entire test drive. In hybrid systems, there is one further source for transient ICE response: each power shift between E-motor and ICE introduces gas flow variations with subsequent temperature response in the ICE and in the engine aftertreatment system (EAS). This bears consequences for engine out emissions as well as for the EAS efficiency and even for the durability of a catalytic converter. As system calibration engineers must decide on numerous actuator parameters, their decisions, finally, are crucial for meeting legislative limits under the boundary conditions given by the hybrid vehicle’s drive environment.

Most stringent emission legislations have been implemented in all major markets to improve air quality across the past years. This effects the product cost of the vehicles which is considered being critical and needs to be minimized. India suffers from bad air quality and countermeasures have been defined. One being the implementation of similar emission standards than EU VI. By doing so, India takes a large step going from the currently effective BS IV directly to BS VI. Emission reduction is currently mainly handled by the usage of EGR, thus no engine aftertreatment system has been applied. BS VI will require an aftertreatment (EAS) concept with several catalysts and corresponding control system. India is a very cost sensitive market and a carry over of solutions from the EU needs to be evaluated carefully and new approaches need to be found.

The use of state of the art simulation tools for effective front-loading of the calibration process is essential to support the additional efforts required by the new Real Driving Emission (RDE) legislation. The process needs a critical model validation where the correlation in dynamic conditions is used as a preliminary insight into the bounds of the representation domain of engine mean values. This paper focuses on the methodologies for correlating dynamic simulations with emissions data measured during dynamic vehicle operation (fundamental engine parameters and gaseous emissions) obtained using dedicated instrumentation on a diesel vehicle, with a particular attention for oxides of nitrogen NOx specie. This correlation is performed using simulated tests run within AVL’s mean value engine and engine aftertreatment (EAS) model MoBEO (Model Based Engine Optimization).

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.

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 continuously decreasing emission limits lead to a growing importance of exhaust aftertreatment in Diesel engines. Hence, methods for achieving a rapid catalyst light-off after engine cold start and for maintaining the catalyst temperature during low load operation will become more and more necessary. The present work evaluates several valve timing strategies concerning their ability for doing so. For this purpose, simulations as well as experimental investigations were conducted. A special focus of simulation was on pointing out the relevance of exhaust temperature, mass flow and enthalpy for these thermomanagement tasks. An increase of exhaust temperature is beneficial for both catalyst heat-up and maintaining catalyst temperature. In case of the exhaust mass flow, high values are advantageous only in case of a catalyst heat-up process, while maintaining catalyst temperature is supported by a low mass flow.

For nearly twenty years, DiMethyl Ether has been known to be an outstanding fuel for combustion in diesel cycle engines. Not only does it have a high Cetane number, it burns absolutely soot free and produces lower NOx exhaust emissions than the equivalent diesel. However, the physical properties of DME such as its low viscosity, lubricity and bulk modulus have negative effects for the fuel injection system, which have both limited the achievable injection pressures to about 500 bar and DME's introduction into the market. To overcome some of these effects, a common rail fuel injection system was adapted to operate with DME and produce injection pressures of up to 1000 bar. To understand the effect of the high injection pressure, tests were carried out using 2D optically accessed nozzles. This allowed the impact of the high vapour pressure of DME on the onset of cavitation in the nozzle hole to be assessed and improve the flow characteristics.

A key element to achieving vehicle emission certification for most light-duty vehicles using spark-ignition engine technology is prompt catalyst warming. Emission mitigation largely does not occur while the catalyst is below its “light-off temperature”, which takes a certain time to achieve when the engine starts from a cold condition. If the catalyst takes too long to light-off, the vehicle could fail its emission certification; it is necessary to minimize the catalyst warm up period to mitigate emissions as quickly as possible. One technique used to minimize catalyst warm up is to calibrate the engine in such a way that it delivers high temperature exhaust. At idle or low speed/low-load conditions, this can be done by retarding spark timing with a corresponding increase in fuel flow rate and / or leaning the mixture. Both approaches, however, encounter limits as combustion stability degrades and / or nitrogen oxide emissions rise excessively.

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 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.

This paper presents a numerical study on the impact of washcoat diffusion on the overall conversion performance of catalytic converters. A comprehensive transient 1D pore diffusion reaction model is embedded in state-of-the-art 1D and 3D catalytic converter models. The pore diffusion model is discussed with its model equations and the applied diffusive transport approaches are summarized. The diffusion reaction model is validated with the help of two available analytical solutions. The impact of basic washcoat characteristics such as pore diameters or thickness on overall conversion performance is investigated by selected 1D+1D calculations. This model is also used to highlight the impact of boundary layer transfer, pore diffusion and reaction on the overall converter conversion performance. The interaction of pore diffusion and flow non-uniformities is demonstrated by 3D+1D CFD simulations.

The paper describes a zero-dimensional crank angle resolved combustion model which was developed for the analysis and prediction of combustion in compression ignition (CI) engines. The model relies on the multi zone combustion model (MZCM) approach of Hiroyasu. The main sub-models were taken from literature and extended with additional features described in this paper. A special procedure described in a previous paper is used to identify the mechanisms of the combustion process on the basis of the measured cylinder pressure trace. Based on the identified mechanisms the present work concentrates on the analysis of the causal effects that predominantly control the combustion process and the formation of NOx and Soot. The focus lies on the changes of the thermodynamic states and the composition of the reaction zones caused by different emission control strategies.

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.

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e. g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure - consisting of a number of global data-based sub-models - is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

The subjectively perceived playback quality of conventional artificial head recordings does not fully comply with the original perception of engine and vehicle interior sound. There exist differences in subjective perception between different artificial heads and even between models of one supplier. Additionally, the listening situations are often judged unnatural. One important reason for these problems is the fact that the transfer function of an artificial head system is always different from the torso and the outer ear transfer function of a specific person. The neurological processing of a specific test person is not trained to the significantly different head related transfer functions of the conventional artificial heads. Especially the significant differences of the outer ear transfer functions between an artificial head and a specific test person are considered as a main reason for an unnatural playback quality.