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In view of BS-VI emission norms implementation in Commercial Vehicle (CV) application, the emissions are not only confirmed in standard condition but also in non-standard condition including different combinations of ambient temperature and pressure especially for checking the emission in WNTE cycle. However, achieving the emissions in different environmental conditions require physical emission calibration to be performed in those conditions. Hence, engine must be calibrated in climatic test chambers to ensure emission in different climatic conditions leading to multifold increase in the calibration effort. With addition of BS-VI emission regulation, After Treatment System (ATS) is a mandatory requirement to reduce the tail pipe emissions. Efficient functioning of ATS requires enough heating to convert the engine out emissions. Vehicle level Real Drive Emission (RDE) measurement without Conformity Factor (CF) limitation are added as an important legislative requirement.

The major objective of this paper is to develop thermal management strategy targeting optimum performance of Selective Catalytic Reduction (SCR) catalyst in a Medium Duty Diesel Engine performing in BS6 emission cycles. In the current scenario, the Emissions Norms are becoming more stringent and with the introduction of Real Drive Emission Test (RDE) and WHTC test comprising of both cold and hot phase, there is a need to develop techniques and strategies which are quick to respond in real time to cope with emission limit especially NOx. SCR seems to be suitable solution in reducing NOx in real time. However, there are limitations to SCR operating conditions, the major being the dosing release conditions which defines the gas temperature at which DEF (Diesel Exhaust Fluid) can be injected as DEF injection at lower gas temperatures than dosing release will lead to Urea deposit formation and will significantly hamper the SCR performance.

The safety of BEVs in driving, charging and parking condition is essential for the success of electrification in automotive industry as well as key driver of any future development of Li-Ion HV battery. AVL has developed a unique simulation approach in which the multi-physical behavior of the single cell in thermal runaway is modelled and applied to module, pack or vehicle level. In addition and beside this cell behavior, various more physical phenomena during thermal propagation on pack level are considered and predicted by the simulation method: component melting, ignition and flammibilty of venting gas and HV failures.

In this paper, the multi-physical simulation workflow from electromagnetics to structural dynamics for a squirrel-cage induction machine is explored. In electromagnetic simulations, local forces and rotor torque are calculated for specific speed-torque operation points. In order to consider non-linearities and interaction with control system as well as transmission, time-domain simulations are carried out. For induction machines, the computational effort with full transient numerical methods like finite element analysis (FEA) is very high. A novel reduced order electro-mechanical model is presented. It still accounts for vibro-acoustically relevant harmonics due to pulse-width modulation (PWM), slotting, distributed winding and saturation effects, but is substantially faster (minutes to hours instead of days to weeks per operation point).

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.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

The latest generation of internal combustion engines may emit significant levels of sub-23 nm particles. The main objective of the Horizon 2020 “DownToTen” project was to develop a robust methodology and provide policy recommendations towards the particle number (PN) emissions measurements in the sub-23 nm region. In order to achieve this target, a new portable exhaust particle sampling system (PEPS) was developed, being capable of measuring exhaust particles down to at least 10 nm under real-world conditions. The main design target was to build a system that is compatible with current PMP requirements and is characterized by minimized losses in the sub-23 nm region, high robustness against artefacts and high flexibility in terms of different PN modes investigation, i.e. non-volatile, volatile and secondary particles.

Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling processes occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved.

The development of modern combustion engines (spark ignition as well as compression ignition) for vehicles compliant with future oriented emission legislation (BS6, Euro VI, China 6) has introduced several technologies for improvement of both fuel efficiency as well as low emissions combustion strategies. Some of these technologies as there are high pressure multiple injection systems or sophisticated exhaust gas after treatment system imply substantial increase in test and calibration time as well as equipment cost. With the introduction of 48V systems for hybridization a cost- efficient enhancement and, partially, an even attractive alternative is now available. An overview will be given on current technologies as well as on implemented test procedures. The focus will be on solutions which have potential for the Indian market, i.e. solutions which can be implemented with moderate application effort for currently available compact and medium size cars.

In the context of today’s and future legislative requirements for NOx and soot particle emissions as well as today’s market trends for further efficiency gains in gasoline engines, computational fluid dynamics (CFD) models need to further improve their intrinsic predictive capability to fulfill OEM needs towards the future. Improving fuel chemistry modelling, knock predictions and the modelling of the interaction between the chemistry and turbulent flow are three key challenges to improve the predictivity of CFD simulations of Spark-Ignited (SI) engines. The Flamelet Generated Manifold (FGM) combustion modelling approach addresses these challenges. By using chemistry pre-tabulation technologies, today’s most detailed fuel chemistry models can be included in the CFD simulation. This allows a much more refined description of auto-ignition delays for knock as well as radical concentrations which feed into emission models, at comparable or even reduced overall CFD run-time.

This report describes the implementation of the spark channel short circuit and blow-out submodels, which were described in the previous report, into a spark ignition model. The spark channel which is modeled by a particle series is elongated by moving individual spark particles along local gas flows. The equation of the spark channel resistance developed by Kim et al. is modified in order to describe the behavior of the current and the voltage in high flow velocity conditions and implemented into the electrical circuit model of the electrical inductive system of the spark plug. Input parameters of the circuit model are the following: initial discharge energy, inductance, internal resistance and capacitance of the spark plug, and the spark channel length obtained by the spark channel model. The instantaneous discharge current and the voltage are obtained as outputs of the circuit model.

This study models short circuits and blow-outs of spark channels. The short circuit model assumes that a spark channel is short-circuited between two arbitrary locations when the electric potential difference between the two locations exceeds the voltage which enables electrical insulation breakage in-between. The threshold voltage can be raised by increasing the distance between the two locations and decreasing the discharge current. Discharge current, in this model, represents the influence of both the spread and the number of electrically charged particles, i.e., electrons and positive ions, distributed near the two locations. Meanwhile, the blow-out model assumes that a strong flow diffuses electrons and positive ions in the spark channel, and consequently the discharge blows out.

Turbulent combustion modeling in a RANS or LES context imposes the challenge of closing the chemical reaction rate on the sub-grid level. Such turbulent models have as their two main ingredients sources from chemical reactions and turbulence-chemistry interaction. The various combustion models then differ mainly by how the chemistry is calculated (level of detail, canonical flame model) and on the other hand how turbulence is assumed to affect the reaction rate on the sub-grid level (TCI - turbulence-chemistry interaction). In this work, an advanced combustion model based on tabulated chemistry is applied for 3D CFD (computational fluid dynamics) modeling of Diesel engine cases. The combustion model is based on the FGM (Flamelet Generated Manifold) chemistry reduction technique. The underlying chemistry tabulation process uses auto-ignition trajectories of homogeneous fuel/air mixtures, which are computed with detailed chemical reaction mechanisms.

A TGDI (turbocharged gasoline direct injection) engine is developed to realize both excellent fuel economy and high dynamic performance to guarantee fun-to-drive. In order to achieve this target, it is of great importance to develop a superior combustion system for the target engine. In this study, CFD simulation analysis, steady flow test and transparent engine test investigation are extensively conducted to ensure efficient and effective design. One dimensional thermodynamic simulation is firstly conducted to optimize controlling parameters for each representative engine operating condition, and the results serve as the input and boundary condition for the subsequent Three-dimensional CFD simulation. 3D CFD simulation is carried out to guide intake port design, which is then measured and verified on steady flow test bench.

Local air pollution, noise emissions as well as global CO2 reduction and public pressure drive the need for zero emission transport solutions in urban areas. OEMs are currently developing battery electric vehicles with the focus to provide emission free urban transportation combined with lowest total cost of ownership and consequently a positive business case for the end customers. Thereby the main challenges are electric range, product cost, system weight, vehicle packaging and durability. Hence they are the main drivers in current developments. In this paper AVL describes two of its truck and bus solutions - a modular battery concept as well as a concept for an integrated electric axle. Based on the vehicle requirements concept designs for both systems are presented.

This paper describes the development of a 0-D-sulfur poisoning model for a NOx storage catalyst (NSC). The model was developed and calibrated using findings and data obtained from a passenger car diesel engine used on testbed. Based on an empirical approach, the developed model is able to predict not only the lower sulfur adsorption with increasing temperature and therefore the higher SOx (SO2 and SO3) slip after NSC, but also the sulfur saturation with increasing sulfur loading, resulting in a decrease of the sulfur adsorption rate with ongoing sulfation. Furthermore, the 0-D sulfur poisoning model was integrated into an existing 1-D NOx storage catalyst kinetic model. The combination of the two models results in an “EAS Model” (exhaust aftertreatment system) able to predict the deterioration of NOx-storage in a NSC with increasing sulfation level, exhibiting higher NOx-emissions after the NSC once it is poisoned.

This study aims at the development of a projection pattern that is capable of shortening the time required by a driver to perceive a pedestrian at night when a vehicle’s high beams are utilized. Our approach is based on the spatio-temporal frequency characteristics of human vision. Visual contrast sensitivity is dependent on spatiotemporal frequency, and maximum contrast sensitivity frequency varies depending on environmental luminance. Conventionally, there are several applications that utilize the spatio-temporal frequency characteristics of human vision. For example, the National Television System Committee (NTSC) television format takes into consideration low-sensitivity visual characteristics. In contrast, our approach utilizes high-sensitivity visual characteristics based on the assumption that the higher contrast sensitivity of spatio-temporal frequencies will correlate more effectively with shorter perception times.

A reduction in brain disorders owing to traumatic brain injury (TBI) caused by head impacts in traffic accidents is needed. However, the details of the injury mechanism still remain unclear. In past analyses, brain parenchyma of a head finite element (FE) model has generally been modeled using simple isotropic viscoelastic materials. For further understanding of TBI mechanism, in this study we developed a new constitutive model that describes most of the mechanical properties in brain parenchyma such as anisotropy, strain rate dependency, and the characteristic features of the unloading process. Validation of the model was performed against several material test data from the literature with a simple one-element model. The model was also introduced into the human head FE model of THUMS v4.02 and validated against post-mortem human subject (PMHS) test data about brain displacements and intracranial pressures during head impacts.

In order to reduce the energy consumption of the automotive air conditioning system, adsorption heat pump (AHP) system is one of the key technologies. We have been developing compact AHP system utilizing the exhaust heat from the engine coolant system (80-100 °C), which can meet the requirements in the automotive application. However, AHP systems have not been practically used in automotive applications because of its low volumetric power density of the adsorber. The volumetric power density of the adsorber is proportional to sorption rate, packing density and latent heat. In general, the sorption rate is determined by mass transfer resistance in primary particle of an adsorbent and heat and mass transfer resistance in packed bed. In order to improve the volumetric power density of the adsorber, it is necessary to increase the production of the sorption rate and the packing density.

We investigated a lighting method that supports pedestrian perception by vehicle drivers. This lighting method makes active use of visual characteristics such as the spatio-temporal frequency of contrast sensitivity. Using reasonable parameter values derived from preliminary experiments using a Campbell-Robson chart, we determined a suitable lighting pattern that improves the driver's pedestrian perception. In order to assess the influence of visual characteristics on a reaction-time-dependent task, such as pedestrian perception in nighttime, tests were performed in the target environment, the results of which validated the proposed method.