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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.

Fully flexible dual fuel (DF) internal combustion (IC) engines, that can burn diesel and gas simultaneously, have become established among heavy-duty engines as they contribute significantly to lower the environmental impact of the transport sector. In order to gain better understanding of the DF combustion process and establish an effective design methodology for DFIC engines, high fidelity computational fluid dynamics (CFD) simulation tools are needed. The DF strategy poses new challenges for numerical modelling of the combustion process since all combustion regimes have to be modelled simultaneously. Furthermore, DF engines exhibit higher cycle-to-cycle variations (CCV) compared to the pure diesel engines. This issue can be addressed by employing large eddy simulation coupled with appropriate DF detailed chemistry mechanism. However, such an approach is computationally too expensive for today’s industry-related engine calculations.

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.

Considering worldwide future emission and CO2-legislation for the Light Commercial Vehicle segment, a wide range of powertrain variants is expected. Dependent on the application use cases all powertrain combinations, from pure Diesel engine propulsion via various levels of hybridization, to pure battery electric vehicles will be in the market. Under this aspect as well as facing differing legal and market requirements, a modular approach is presented for the LCV and SUV Segment, which can be adapted flexibly to meet the different requirements. A displacement range of 2.0L to 2.3L, representing the current baseline in Europe is taken as basis. To best fulfill the commercial boundaries, tailored technology packages, based on a common global engine platform are defined and compared. These packages include engine related technical features for emission- and fuel consumption improvement, as well as electrification measures, in particular 48V-MHEV variants.

Faced with the need to reduce development time and cost in view of additional system complexity driven by ever more stringent emission regulations, the Hardware-in-the-Loop (HiL) simulation increasingly proves itself to be an advantageous tool not only in automotive companies but also in the off-road engine industry. The approach offers the possibility to analyze new engine control systems with fewer expensive engine dynamometer experiments and test drives. Thus, development cycles can be shortened and development costs reduced. This paper presents the development of an Internal Combustion Engine (ICE) and the correspondent Exhaust Aftertreatment System (EAS) model, its deployment on a HiL system and its application to pre-calibrate the engine for different vehicle cycles. A zero-dimensional mean value approach was chosen to guarantee adequate real-time factors for the coupling between the models and the Engine Control Unit (ECU).

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.

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.

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.

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.

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).

In the automotive industry, various simulation-based analysis methods have been suggested and applied to reduce the time and cost required to develop the engine structure to improve the NVH performance of powertrain. This simulation is helpful to set the engine design concept in the initial phase of the powertrain development schedules. However, when using the conventional simulation method with a uniformed force, the simulation results sometimes show different results than the test results. Therefore, in this paper, we propose a method for predicting the radiated noise level of a diesel engine using actual combustion excitation force. Based on the analytical radiated noise development target, we identify the major components of the engine that are beyond this development target by in the frequency range. The components of the problem found in this way are reflected in the engine design of the early development stage to shorten the development time.

This paper presents a newly developed quasi-dimensional multi-zone dual fuel combustion model, which has been integrated within the commercial engine system simulation framework. Model is based on the modified Multi-Zone Combustion Model and Fractal Combustion Model. Modified Multi-Zone Combustion Model handles the part of the combustion process that is governed by the mixing-controlled combustion, while the modified Fractal Combustion Model handles the part that is governed by the flame propagation through the combustion chamber. The developed quasi-dimensional dual fuel combustion model features phenomenological description of spray processes, i.e. liquid spray break-up, fresh charge entrainment, droplet heat-up and evaporation process. In order to capture the chemical effects on the ignition delay, special ignition delay table has been made.

Commonly, the spray process in Direct Injection (DI) diesel engines is modeled with the Euler Lagrangian discrete droplet approach which has limited validity in the dense spray region, close to the injector nozzle hole exit. In the presented research, a new reactive spray modelling method has been developed and used within the 3D RANS CFD framework. The spray process was modelled with the Euler Eulerian multiphase approach, extended to the size-of-classes approach which ensures reliable interphase momentum transfer description. In this approach, both the gas and the discrete phase are considered as continuum, and divided into classes according to the ascending droplet diameter. The combustion process was modelled by taking into account chemical kinetics and by solving general gas phase reaction equations.

This paper describes a numerical study of the effect of hollow crankshafts on crankshaft local strength and durability as well as slider bearing contact behavior. Crankshaft dynamic simulation for durability is still a challenging task, although numerical methods are already worldwide established and integrated part of nearly every standard engine development process. Such standard methods are based on flexible multi-body dynamic simulation, combined with Finite Element analysis and multi-axial fatigue evaluation. They use different levels of simplification and consider the most influencing phenomena relevant for durability. Lightweight design and downsizing require more and more detailed methods due to higher deformation of the crankshaft. This is especially true for hollow shafts, as present in motorsport design or aerospace applications, but also for standard engine having high potential for significant weight savings.

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.

This paper presents a methodology for numerical investigation of a full flexible balancer drive together with engine and crank train under realistic operating conditions where shaft dynamics, gear contact and rattle impacts, gear root stresses and friction losses in bearings and gear interaction are taken into account and can be balanced against each other to achieve the design criteria. Gear rattle is driven by the speed fluctuation of the crank train, the resistance torque (mainly friction), shaft inertia and the backlash in the gears. The actual trend to engine downsizing and up-torqueing increases the severity to rattle as engines are running on higher combustion pressures. This increases torque and speed fluctuation, which makes the detailed investigation in this torque transfer even more demanding. A common method to reduce gear rattle is the usage of so-called scissors gears.