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The first objective of this work is to develop a numerical simulation model of the spark ignited (SI) engine combustion, taking into account knock avoidance and heat transfer between in-cylinder gas and combustion chamber wall. Secondly, the model was utilized to investigate the potential of reducing heat losses by applying a heat insulation coating to the combustion chamber wall, thereby improving engine thermal efficiency. A reduction in heat losses is related to important operating factors of improving SI engine thermal efficiency. However, reducing heat losses tends to accompany increased combustion chamber wall temperatures, resulting in the onset of knock in SI engines. Thus, the numerical model was intended to make it possible to investigate the interaction of the heat losses and knock occurrence. The present paper consists of Part 1 and 2.

Heavy soot deposition in wall-flow type diesel particulate filters reduces engine output and fuel efficiency. This necessitates forced regeneration to oxidize soot via exothermic reactions in a diesel oxidation catalyst upstream of the Diesel Particulate Filter (DPF). Soot loading in the wall of the DPF during forced regeneration causes much greater pressure drops than cake deposition, which is undesirable because high pressure drops reduce engine performance. We show that the description of soot deposition using a DPF model is improved by using a shrinking sphere soot oxidation sub-model. We then use this revised model to analyze cake deposition during forced regeneration, and to study the effects of varying the forced regeneration temperature and duration on the local soot reaction rate and soot mass distribution in the radial and longitudinal directions of the DPF channels during forced regeneration.

A mixed time-scale subgrid large eddy simulation was used to simulate mixture formation, combustion and soot formation under the influence of turbulence during diesel engine combustion. To account for the effects of engine wall heat transfer on combustion, the KIVA code's standard wall model was replaced to accommodate more realistic boundary conditions. This were carried out by implementing the non-isothermal wall model of Angelberger et al. with modifications and incorporating the log law from Pope's method to account for the wall surface roughness. Soot and NOx emissions predicted with the new model are compared to experimental data acquired under various EGR conditions.

Difference of engine combustion characteristics, species and amount of exhaust gas and PM (particulate matter consisted of SOF and Soot and Ash), and especially PM oxidation characteristics were studied when diesel fuel or bio-fuel, here PME (palm oil methyl ester) as an example, was used as a fuel. The fueling rate was adjusted to obtain the same torque for both fuels and engine was operated under several range of EGR (Exhaust Gas Recirculation) ratio. Under such conditions, PME showed shorter ignition delay time and lower R.H.R (rate of heat release) under 0-40% EGR ratio. With respect to engine exhaust gas species, CO, NO, THC and HCHO, CH3CHO concentration was almost the same when the EGR ratio is higher than 35% (Intake-Air/Fuel: A/F=20). However, PME also showed lower exhaust gas emission when the EGR ratio is higher than 30%.

Experimental and numerical studies on PAHs (Polycyclic Aromatic Hydrocarbons) and PM (Particulate Matters) formed in the fuel rich mixture have been conducted. In the experiment, neat n-heptane and n-heptane with benzene 25 % by weight were chosen as test fuels. In-cylinder gases produced by the fuel-rich HCCI (Homogeneous Charge Compression Ignition) combustion were directly sampled and analyzed by the use of GC/MS (Gas Chromatograph/Mass Spectro- metry), and PM emission was also measured by PM sampling system to reveal characteristics of PM formation. Numerical study has been also carried out using a zero dimensional combustion model combined with detailed chemistry. Furthermore, simple surface growth of soot particles was integrated into a detailed chemical kinetic model, and validated with the experimental data.

A CFD code combined with detailed chemical kinetics has been developed, linking with KIVA-3 and subroutines in CHEMKIN-II directly with some modifications. By using this CFD code, formation processes of combustion and exhaust gas emission for a turbo-charged DI diesel engine with common rail fuel injection system were simulated. As a result, formation processes of pollutant including NOx and soot were also considered according to the calculation results. The results show that NO caused by the extended Zeldvich mechanism accounted for about 88% of all NO, and it was found that there is a possibility to predict where and when soot will be formed by considering a simplified soot formation model.

Experimental and numerical studies are conducted on the formation of soot and Polycyclic Aromatic Hydrocarbons (PAHs), regarded as precursors of soot, during the combustion of fuel-rich homogeneous n-heptane mixtures. In-cylinder gases are sampled directly through a high-speed solenoid valve in engine tests, to be analyzed by GC/MS for qualifying PAHs. Smoke concentration is also measured. A numerical study is carried out by using a zero-dimensional model combined with detailed chemical kinetics. The experiments and computations show that PAHs can be predicted qualitatively by means of the present kinetic model.

Experimental and numerical studies on the combustion of the particulate matter in the diesel particulate filter with the particulate matter loaded under different particulate matter loading condition were carried out. It was observed that the pressure losses through diesel particulate filter loaded with particulate matter having different mean aggregate particle diameters during both particulate matter loading and combustion periods. Diesel particulate filter regeneration mode was controlled with introducing a hot gas created in Diesel Oxidation Catalyst that oxidized hydrocarbon injected by a fuel injector placed on an exhaust gas pipe. The combustion amount was calculated with using a total diesel particulate filter weight measured by the weight meter both before and after the particulate matter regeneration event.

A mixed timescale subgrid model of a large eddy simulation was used to simulate the turbulence regime in diesel engine combustion. The combustion model used the direct integration approach with a diesel oil surrogate mechanism (developed at Chalmers University of Technology and consisting of 70 species and 309 reactions). Additional reactions for the generation and consumption of OH*, CO2*, and CH* species were added from recent kinetic studies. Collisional quenching and spontaneous emission resulted in de-excitation of the excited state radical. A phenomenological soot formation model (developed at Waseda University) was combined with the LES code. The following important steps were considered in the soot model: particle inception where naphthalene grows irreversibly to form soot, surface growth with the addition of C2H2, surface oxidation (induced by OH radicals and O2 attack), and particle coagulation.

Experimental studies were carried out to investigate the effect of soot deposition on NOx purification phenomena in an ammonia selective catalytic reduction coated diesel particulate filter (SCR/DPF) catalyst. To study soot deposition effects on the chemical reactions and mass transfer, two types of testing device were used. A synthetic gas bench enabling tests to be conducted with temperature and flow rate ranges relevant to real driving conditions was used to investigate the soot influence on reduction of NOx to N2 (DeNOx). A micro-reactor that removed the effect of soot deposition on mass transfer in the catalyst layer was used to analyze chemical reactions on a soot surface and their interaction with the SCR catalyst. A filter test brick of a Cu-zeolite SCR/DPF catalyst and a powder catalyst were used for the synthetic gas bench and micro-reactor tests, respectively. Engine soot was sampled in all the tests.

Cars with diesel engines are commonly equipped with a Diesel Particulate Filter (DPF) to reduce their emissions of particulate matter (PM). Because the pressure drop within the DPF reduces engine performance, it must be predicted with accuracy. The purpose of this study was to improve the accuracy of a DPF simulation model under transient conditions by parameter optimization. The DPF model under consideration consists of an inlet channel, a cake layer, wall layer, and an outlet channel. The pressure drop is influenced by the location, mass, and density of the deposited soot. Therefore, the model includes the following sub-models: Sub-model 1: Calculates the soot density deposited in the wall layer Sub-model 2: Computes the filtration efficiency and mass of the wall and cake layer Sub-model 3: Calculates the soot density deposited in the cake layer Because the sub-models include some empirical formulae, the first step in refining the model was to optimize their fitting parameters.

Experimental and numerical studies were conducted on diesel particulate filters (DPFs) under different soot loading conditions and DPF configurations. Pressure drops across DPFs with various mean pore diameters loaded with soots having different mean particle diameters were measured by introducing exhaust gases from a 2.2 liter inline four-cylinder, TCI diesel engine designed for use in passenger cars. A mechanistic hypothesis was then proposed to explain the observed trends, accounting for the effects of the soot loading regime in the wall and the soot cake layer on the pressure drop. This hypothesis was used to guide the development and validation of a numerical model for predicting the pressure drop in the DPF. The relationship between the permeability and the porosity of the wall and soot cake layer was modeled under various soot loading conditions.

The reduced chemical reaction scheme which can take the effect of major fuel components on auto ignition timing into account has been developed. This reaction scheme was based on the reduced reaction mechanism for the primary reference fuels (PRF) proposed by Tsurushima [1] with 33 species and 38 reactions. Some pre-exponential factors were modified by using Particle Swarm Optimization to match the ignition delay time versus reciprocal temperature which was calculated by the detailed scheme with 2,301 species and 11,116 elementary chemical reactions. The result using the present reaction scheme shows good agreements with that using the detailed scheme for the effects of EGR, fuel components, and radical species on the ignition timing under homogeneous charge compression ignition combustion (HCCI) conditions.

A three-dimensional computational fluid dynamics (3D-CFD) code was combined with a detailed combustion chamber heat transfer model. The established model allowed not only prediction of instantaneous combustion chamber wall surface temperature distributions in practical calculation time but also investigation of the characteristics of combustion, emissions and heat losses affected by the wall temperature distributions. Although zero-dimensional combustion analysis can consider temporal changes in the heat transfer coefficient and in-cylinder gas temperature, it cannot take into account the effect of interactions between spatially distributed charge and wall temperatures. In contrast, 3D-CFD analysis can consider temporal and spatial changes in both parameters. However, in most zero-/multi- dimensional combustion analyses, wall temperatures are assumed to be temporally constant and spatially homogeneous.

Synthetic fuels can significantly improve the combustion and emission characteristics of heavy-duty diesel engines toward decarbonizing heavy-duty propulsion systems. This work analyzes the effects of engine operating conditions and synthetic fuel properties on spray, combustion, and emissions (soot, NOx) using a supercharging single-cylinder engine experiment and KIVA-4 code combined with CHEMKIN-II and in-house phenomenological soot model. The blended fuel ratio is fixed at 80% diesel and 20% n-paraffin by volume (hereafter DP). Diesel, DP1 (diesel with n-pentane C5H12), DP2 (diesel with n-hexane C6H14), and DP3 (diesel with n-heptane C7H16) are used in engine-like-condition constant volume chamber (CVC) and engine experiments. Boosted engine experiments (1080 rpm, common-rail injection pressure 160 MPa, multi-pulse injection) are performed using the same DP fuel groups under various main injection timings, pulse-injection intervals, and EGR = 0-40%.

Performances of battery electric vehicles (BEV) are affected by the thermal imbalance in the battery packs under driving cycles. BEV thermal management system (VTMS) should be managed efficiently for optimal energy consumption and cabin comfort. Temperature changes in the brick, module, and pack under the repeated transient cycles must be understood for model-based development. The authors conducted chassis dynamometer experiments on a fully electric small crossover sports utility vehicle (SUV) to address this challenge. A BEV is tested using a hub-type, 4-wheel motor chassis dynamometer with an air blower under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and Federal Test Procedures (FTP) with various ambient temperatures. The mid-size BEV with dual-motor featured 80 thermocouples mounted on the 74-kWh battery pack, including the cells, upper tray, side cover, and pack cover.

A major issue of battery electric vehicles (BEV) is optimizing driving range and energy consumption. Under actual driving, transient thermal and electrical performance changes could deteriorate the battery cells and pack. These performances can be investigated and controlled efficiently with a thermal management system (TMS) via model-based development. A complete battery pack contains multiple cells, bricks, and modules with numerous coolant pipes and flow channels. However, such an early modeling stage requires detailed cell geometry and specifications to estimate the thermal and electrochemical energies of the cell, module, and pack. To capture the dynamic performance changes of the LIB pack under real driving cycles, the thermal energy flow between the pack and its TMS must be well predicted. This study presents a BTMS model development and validation method for a 75-kWh battery pack used in mass-production, mid-size battery SUV under WLTC.