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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.

In recent years, the use of high-power inverters has become increasingly prevalent in vehicles applications. With the increasing number of electric vehicle models comes the need for efficient and reliable testing methods to ensure the proper functioning of these inverters. One such method is the use of Hardware-in-the-Loop (HiL) environments, where the inverter is connected to a simulated environment to test its performance under various operating conditions. HiL testing allows for faster and more cost-effective testing than traditional methods and provides a safe environment to evaluate the inverter's response to different scenarios. Further, in such an environment, it is possible to specifically stimulate those system states in which conflicts between the lines arise regarding the ideal system parametrization. By combining HiL testing with design-of-experiments and modelling methods, the propulsion system can hence be optimized in a holistic manner.

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the finite volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1]. In that work, it was shown that the same accuracy of predicted aerodynamic forces can be achieved by using Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model on both types of meshes, the standard body-fitted (BF), and on the immersed boundary (IB) mesh. Due to all well-known shortcomings of the steady state approach, in this work we deal with the Partially Averaged Navier-Stokes (PANS), which belongs to the hybrid RANS-LES (scale resolving / high fidelity) methods. This approach was developed to resolve a part of the turbulence spectrum adjusting seamlessly from RANS to DNS (Direct Numerical Simulation).

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 demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

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.

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).

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.

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.

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.

Direct injection Diesel engines are a propulsion technology that is continuously developed to meet emission standards. Great optimization potential lies in the combustion process itself. The application of closed loop combustion control allows reacting online to environmental conditions and stabilizing the combustion regarding performance and emissions. Dedicated real-time plant models help to develop and calibrate control algorithms in office and hardware in the loop environments. The present work describes a real-time capable, crank-angle resolved engine, cylinder and combustion model. The cylinder applies an 0D, two-zone approach and a phenomenological combustion model describes ignition delay, premixed and diffusive combustion. The latter is enhanced by a quasi-dimensional description of the injection spray. The model is validated with dedicated measurements. The plant model is applied in two use-cases for closed loop combustion control.

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.

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).

The Particle Measurement Programme (PMP) developed an exhaust particle number measurement protocol that has been adopted by current light duty vehicle emission regulations in Europe. This includes thermal treatment of the exhaust aerosol to isolate solid particles only and a number counting device with a lower cutpoint of 23 nm to avoid measurement of smaller particles that may affect the repeatability of the measurement. In this paper, we examine a potential alternative to the PMP system, where the thermal treatment is replaced by a catalytic stripper (CS). This offers oxidation and not just evaporation of the volatile components. Alternative sampling systems, either fulfilling the PMP recommendations or utilizing a CS, have been explored in terms of their volatile particle removal efficiency. Tests have been conducted on diesel exhaust, diesel equipped with DPF and gasoline direct injection emissions.

Engine simulation can be performed using model approaches of different depths in capturing physical effects. The present paper presents a comprehensive comparison study on seven different engine models. The models range from transient 1D cycle resolved approaches to steady-state non-dimensional maps. The models are discussed in the light of key features, amount and kind of required input data, model calibration effort and predictability and application areas. The computational performance of the different models and their capabilities to capture different transient effects is investigated together with a vehicle model under real-life driving conditions. In the trade-off field of model predictability and computational performance an innovative approach on crank-angle resolved cylinder modeling turned out to be most beneficial.

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).