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A numerical modeling technique is proposed for computer simulations of high speed valve train dynamics. The dynamic terms in the valve spring reaction forces are calculated using linear vibration theory for given kinematic valve motions. Because the spring dynamics are analyzed before the time stepping integration, spring surge phenomena can be included without using additional computer time. Consequently, valve train dynamics can be simulated very quickly without noticeable errors in accuracy. The experimental results prove the computer model developed here is accurate and also computationally efficient.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

Most of the phenomena that occur during the high pressure cycle of a spark ignition engine are highly influenced by the gas temperature, turbulence intensity and turbulence length scale inside the cylinder. For a pre chamber gas engine, the small volume and the high surface-to-volume ratio of the pre chamber increases the relative significance of the gas-to-wall heat losses, the early flame kernel development and the wall induced quenching; all of these phenomena are associated up to a certain extent with the turbulence and temperature field inside the pre chamber. While three-dimensional (3D) computational fluid dynamics (CFD) simulations can capture complex phenomena inside the pre chamber with high accuracy, they have high computational cost. Quasi dimensional models, on the contrary, provide a computationally inexpensive alternative for simulating multiple operating conditions as well as different geometries.

Motorcycle usage continues to expand globally. Motorcycles use various fuels in different countries and regions, and it is required that they comply with emissions and fuel consumption regulations as specified in UN-GTR No.2 (WMTC). In general, a motorcycle engine has a large bore diameter and a high compression ratio due to demands of high performance. Poor fuel quality may cause damage to the engine, mainly by knocking. Knock control systems utilizing high-frequency vibration detection strategies like knock sensors, which are equipped on several sport-touring motorcycles, are not used widely for reasons of complex construction and high cost. This research aims to develop a new concept of combustion control for common motorcycle as an alternative.

Large Eddy Simulation (LES) of premixed turbulent combustion in a confined cylinder setup at engine relevant conditions has been carried out for three different initial turbulence intensities, mimicking different flame propagation regimes. Direct Numerical Simulation (DNS) of the setup under investigation provides the reference data to be compared against. The DNS fields have been filtered on the LES grid and are used as initial conditions for the LES at onset of combustion, guaranteeing a direct comparability of the single realizations between the modeled and reference data. Two different combustion models, the G-Equation and CMC-premixed (Conditional Moment Closure) are compared with respect to their predictive capabilities as well as their usability and computational cost. While the G-Equation is a widely adopted approach for industrial applications and usually relies on a tunable turbulent flame speed closure, the novel LES-CMC comes as a tuning parameter free model.

Three-dimensional reactive computational fluid dynamics (CFD) plays a crucial role in IC engine development tasks complementing experimental efforts by providing improved understanding of the combustion process. A widely adopted combustion model in the engine community for (partially) premixed combustion is the G-Equation where the flame front is represented by an iso-level of an arbitrary scalar G. A convective-reactive equation for this iso-surface is solved, for which the turbulent flame speed ST must be provided. In this study, the commonly used and well-established Damköhler approach is compared to a novel correlation, derived from an algebraic closure for the scalar dissipation of reaction progress as proposed by Kolla et al. [1].

Dual-fuel combustion is an attractive approach for utilizing alternative fuels such as natural gas in compression-ignition internal combustion engines. In this approach, pilot injection of a more reactive fuel provides a source of ignition for the premixed natural gas/air. The overall performance combines the high efficiency of a compression-ignition engine with the relatively low emissions associated with natural gas. However the combustion phenomena occurring in dual-fuel engines present a challenge for existing turbulent combustion models because, following ignition, flame propagates through a partially-reacted and inhomogeneous mixture of the two fuels. The objective of this study is to test a new modelling formulation that combines the ability of the Conditional Moment Closure (CMC) approach to describe autoignition of fuel sprays with the ability of the G-equation approach to describe the subsequent flame propagation.

Modern Diesel engines have become ever more complex systems with many degrees of freedom. Simultaneously, with increasing computational power, simulations of engines have become more popular, and can be used to find the optimum set up of engine operation parameters which result in the desired point in the emission-efficiency trade off. With increasing number of engine operation parameter combinations, the number of calculations increase exponentially. Therefore, adequate models for combustion and emissions with limited calculation costs are required. For obvious reasons, the accuracy of the ignition timing is a key point for the following combustion and emission model quality. Furthermore, the combination of mixing and chemical processes during the ignition delay is very challenging to model in a fast way for a wide range of operation conditions.

A mean value soot model (MVSM) was developed and validated for the realtime prediction of the raw, engine-out soot emissions from common rail diesel engines. Through the consideration of five representative states during the combustion cycle, the developed MVSM determines the engine out soot emissions based on the soot formation and oxidation processes, using only parameters available from a standard engine control unit. 16 model parameters are used to describe the engine, fuel, and combustion characteristics, and must be determined for each engine and fuel combination. The MVSM was parameterized and validated using the measured soot emissions from two different engines operating with a total of three different fuels. After parameterization, the MVSM was capable of qualitatively and quantitatively reproducing the soot emissions for operating points throughout the entire operating map, including for operating regimes not considered during the parameterization.

The Drive By Wire (hereafter referred to as DBW) system is the electronically throttle control system. It controls a throttle valve in order to aim at a suitable throttle position according to an engine operating condition and a demand of driver or rider. This system is basically composed of a throttle body with driving motor, an Accelerator Position Sensor (hereafter referred to as APS), and an Electronic Control Unit (hereafter referred to as ECU). The DBW system is spreading to motorcycle field as replacement of existing mechanical intake control system. This is because there are some advantages as the following especially in the large displacement model: capability for installation of several functions, flexibility in adaptation to recent environmental regulations, and effect on reduction of system cost, etc. In general, the motorcycle has some unique features compared with the automobile. Among them, important features for the DBW system are following three points.

The performance of Gasoline Direct Injection (GDI) engines is governed by multiple physical processes such as the internal nozzle flow and the mixing of the liquid stream with the gaseous ambient environment. A detailed knowledge of these processes even for complex injectors is very important for improving the design and performance of combustion engines all the way to pollutant formation and emissions. However, many processes are still not completely understood, which is partly caused by their restricted experimental accessibility. Thus, high-fidelity simulations can be helpful to obtain further understanding of GDI injectors. In this work, advanced simulation and experimental methods are combined in order to study the spray characteristics of two different 3-hole GDI injectors.

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing.

Fuel spray propagation and its morphology are important aspects for the in-cylinder mixture preparation in Diesel engines. Since there is still a lack of suitable measurements with regard to large 2-stroke marine Diesel engines combustion systems, a comprehensive data set of spray characteristics has been investigated using a test facility reflecting the specific features of such combustion systems. The spray penetration, area and cone angle were analysed for a variation of gas density (including the behaviour at evaporation and non-evaporating conditions), injection pressure and nozzle diameter. Moreover, spray and swirl flow interaction as well as fuel quality influences have been studied. To analyse the impacts and effects of each measured parameter, an empirical correlation for the spray penetration has been derived and discussed for all measurements presented.

An existing three-stage ignition delay model which has seen successful application to Primary Reference Fuels (PRFs) has been extended to six surrogate fuels which constitute potential candidates for future Homogeneous Charge Compression Ignition (HCCI) engines. The fuels include petroleum-derived and oxygenated components and can be divided into low, intermediate and high cetane number groups. A new methodology to obtain the model parameters is presented which relies jointly on simulation and experimental data: in a first step, constant volume adiabatic reactor simulations using chemical kinetic mechanisms are performed to generate ignition delays for a very wide range of conditions, namely variations in equivalence ratio, Exhaust Gas Recirculation (EGR), pressure and temperature.

In this study, a novel 3D-CFD combustion model employing Flamelet Generated Manifolds (FGM) for dual fuel combustion was developed. Validation of the platform was carried out using recent experimental results from an optically accessible Rapid Compression Expansion Machine (RCEM). Methane and n-dodecane were used as model fuels to remove any uncertainties in terms of fuel composition. The model used a tabulated chemistry approach employing a reaction mechanism of 130 species and 2399 reactions and was able to capture non-premixed auto ignition of the pilot fuel as well as premixed flame propagation of the background mixture. The CFD model was found to predict well all phases of the dual fuel combustion process: I) the pilot fuel ignition delay, II) the Heat Release Rate of the partially premixed conversion of the micro pilot spray with entrained methane/air and III) the sustained background mixture combustion following the consumption of the spray plume.

Large-bore natural gas engines may use pre-chamber ignition. Despite extensive research in engine environments, the exact nature of the jet, as it exits the pre-chamber orifice, is not thoroughly understood and this leads to uncertainty in the design of such systems. In this work, a specially-designed rig comprising a quartz pre-chamber fit with an orifice and a turbulent flowing mixture outside the pre-chamber was used to study the pre-chamber flame, the jet, and the subsequent premixed flame initiation mechanism by OH* and CH* chemiluminescence. Ethylene and methane were used. The experimental results are supplemented by LES and 0D modelling, providing insights into the mass flow rate evolution at the orifice and into the nature of the fluid there. Both LES and experiment suggest that for large orifice diameters, the flow that exits the orifice is composed of a column of hot products surrounded by an annulus of unburnt pre-chamber fluid.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Fuel spray injected by a port injector has significant effects on engine power output and combustion efficiency. For this reason, it is necessary to atomize fuel into fine droplets and accurately supply it without being susceptible to any changes in temperature or negative pressure affected by engine. This document introduces an atomization technique with optimized layout of nozzle holes and drastically reduced pressure loss (energy loss) in the flow under a needle valve seat. It also describes an injector having a short fuel flow path and a small dead volume under the valve seat, which can have good resistance against any changes in temperature and negative pressure.

This paper presents the evolution of a series of connected, automated vehicle technologies from simulation to in-vehicle validation for the purposes of minimizing the fuel usage of a class-8 heavy duty truck. The results reveal that an online, hierarchical model-predictive control scheme, implemented via the use of extended horizon driver advisories for velocity and gear, achieves fuel savings comparable to predictions from software-in-the-loop (SiL) simulations and engine-in-the-loop (EiL) studies that operated with a greater degree of powertrain and chassis automation. The work of this paper builds on prior work that presented in detail this predictive control scheme that successively optimizes vehicle routing, arrival and departure at signalized intersections, speed trajectory planning, platooning, predictive gear shifting, and engine demand torque shaping.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.