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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.

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.

Synthetic fuels (e-fuels) synthesized from H2 and CO by renewable electricity are expected as the next- generation diesel fuels and two types of e-fuels have received extensive attention: Fischer-Tropsch (FT) fuel and Oxymethylene dimethyl ether (OME). In this study the effects of OME blending ratios with 0 to 50 vol.% in FT fuels on combustion, emissions and spray characteristics in diesel engines are investigated. The results suggest that the OME blends to FT fuels suppressed the deterioration in combustion efficiency under low intake oxygen concentration conditions. The smoke emissions of FT fuels and OME blended fuels were both lower than those of diesel fuel and decreased with the increase in the OME blend ratio, and the soot-NOx trade-off relation in diesel engines can be improved.

The authors have reported significant smoke reduction in twin shaped semi-premixed diesel combustion with a newly designed combustion chamber to distribute the first and the second sprays into upper and lower layers. However, the first stage premixed combustion tends to advance far from the TDC, resulting in lowering of thermal efficiencies. In this report, improvement of thermal efficiency by optimizing the combustion phase with lower ignitability fuels was identified with the divided combustion chamber. The experiment was conducted with four fuels with different cetane numbers. The first stage premixed combustion can be retarded to the optimum phase with the fuel with cetane number 38, establishing high efficiencies.

Pre-chamber (PC) natural gas and hydrogen (CH4-H2) combustion can improve thermal efficiency and greenhouse gas emissions from decarbonized stationary engines. However, the engine efficiency is worsened by prolonged combustion duration due to PC jet velocity extinction. This work investigates the impact of cylindrical PC internal shapes to increase its jet velocity and shorten combustion duration. A rapid compression and expansion machine (RCEM) is used to investigate the combustion characteristics of premixed CH4 gas. The combustion images are recorded using a high-speed camera of 10,000 fps. The experiments are conducted using two types of long PC shapes with diameters φ=4 mm (hereafter, longφ4) and 5 mm (hereafter, long φ5), and their combustions are compared against a short PC shape (φ=12 mm). For all designs of the PC shapes, the PC holes are 6 with 2 mm in diameter.

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%.

For a series hybrid electric vehicle (SHEV), the electric motor is responsible for driving the wheels, while the engine drives the only generator to provide electricity. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of a conventional drive system using only an internal combustion engine, and it is time-consuming to obtain the optimal components specification values and control parameters. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method.

Spark knock suppression with hydrogen addition was investigated at two engine speeds (2000 rpm and 4800 rpm). The experimental results showed that the spark knock is strongly suppressed with increasing hydrogen fraction at 2000 rpm while the effect is much smaller at 4800 rpm. To explain these results, chemical kinetic analyses with a two-zone combustion model were performed. The calculated results showed that the heat release in the end gas zone rises in two stages with a remarkable appearance of low temperature oxidation (LTO) at 2000 rpm, while a single stage heat release without apparent LTO process is presented at 4800 rpm due to the shorter residence time in the low temperature region.

In a natural gas fueled engine ignited by diesel fuel, the addition of hydrogen to the engine could be a possible way to improve thermal efficiency and reduce unburned methane which has a warming potential many times that of carbon dioxide as it promotes a more rapid and complete combustion. This study carried out engine experiments using a single cylinder engine with natural gas and hydrogen delivered separately into the intake pipe, and with pilot-injection of diesel fuel. The percentages of hydrogen in the natural gas-hydrogen mixtures were varied from 0% to 50% of the heat value. The results showed that the hydrogen addition has an insignificant effect on the ignition delay of the diesel fuel and that it shortens the combustion duration. The increase in the hydrogen ratio decreased the unburned hydrocarbon emissions more than the reduction of the amount of natural gas that was replaced by the hydrogen.

The purpose of this paper is to build up a model for predicting turbulent burning velocity which can be used for One-Dimensional (1D) engine simulation. This paper presents the relationship between turbulent burning velocity, the Karlovitz number, and the Markstein number for building up the prediction model. The turbulent burning velocity was measured using a single-cylinder gasoline engine, which has an external Exhaust Gas Recirculation (EGR) system. In the experiment, various engine operating parameters, e.g. engine loads and EGR rates, and various engine specifications, i.e. different types of intake ports were tested. The Karlovitz number was calculated using Three-Dimensional Computational Fluid Dynamics (3D-CFD) and detailed chemical kinetics simulation with a premixed laminar flame model. The Markstein number was also calculated using detailed chemical kinetics simulation with the Extinction of Opposed-flow Flame model.

The purpose of the present study is to find a way to extend a combustion stability limit for diluted combustion in a spark-ignition (SI) gasoline engine which has a high compression ratio. This paper focuses on partial oxidation in an unburned mixture which is observed in the high compression engine and clarifies the effect of partial oxidation in an unburned mixture on the behavior of a flame stretch and the extinction limit. The behavior of the flame stretch was simulated using the detailed chemical kinetics simulation with the opposed-flow flame reactor model. In the simulation, the reactants which have various reaction progress variables were examined to simulate the flame stretch and extinction under the partial oxidation conditions. The mixtures were also diluted by complete combustion products which represent exhaust gas recirculation (EGR).

Soot mass production was investigated in high-boosted diesel engine tests by changing various operating parameters. A mixed timescale subgrid model of large eddy simulation (LES) was applied to simulate the detailed mixture formation, combustion and soot formation influenced by turbulence in diesel engine combustion. The combustion model used a direct integration approach with an explicit ordinary differential equation (ODE) solver and additional parallelization by OpenMP. Soot mass production within a computation cell was determined from a phenomenological soot formation model developed by WASEDA University. The model was combined with the LES code and included the following important steps: particle inception, in which naphthalene was assumed to grow irreversibly to form soot; surface growth with the addition of C2H2; surface oxidation due to OH radicals and O2 attack; particle coagulation; and particle agglomeration.

This paper describes the development of an integrated simulation model for evaluating the effects of electrically heating the three-way catalyst (TWC) in a series hybrid electric vehicle (s-HEV) on fuel economy and exhaust gas purification performance. Engine and TWC models were developed in GT-Power to predict exhaust emissions during transient operation. These models were validated against data from vehicle tests using a chassis dynamometer and integrated into an s-HEV model built in MATLAB/Simulink. The s-HEV model accurately reproduced the performance characteristics of the vehicle’s engine, motor, generator, and battery during WLTC mode operation. It can thus be used to predict the fuel consumption, emissions, and performance of individual powertrain components. The engine combustion characteristics were reproduced with reasonable accuracy for the first 50 combustion cycles, representing the cold-start condition of the driving mode.

To reproduce wall quenching phenomena using 3D-CFD, a wall quenching model was constructed based on the Peclet number. The model was further integrated with the flame propagation model. Combustion analysis showed that that a large amount of unburned hydrocarbons (UHCs) remained in the piston clevis and small gaps. Furthermore, the model was capable of predicting the increase in UHC emissions when there was a delay in the ignition time. The flame front cells were plotted on Peters' premixed turbulent combustion diagram to identify transitions in the combustion states. It was found that the flame surface transitioned from corrugated flamelets through thin reaction zones to wrinkled flamelets and further to laminar flamelets, which led to wall quenching. The turbulent Reynolds number (Re) decreased rapidly due to the increase in laminar flame speed and flame thickness and the decrease in turbulent intensity and turbulent scale.

In this study, reaction path analysis and modeling of NOx reduction phenomena by fast SCR reaction on a Cu-chabazite catalyst were conducted, considering the formation and decomposition of ammonium nitrate (NH4NO3). White crystals of NH4NO3 decompose at temperatures < 200 °C. Thus, the reaction behavior changes at 200 °C under fast SCR reaction conditions. NH4NO3 formation can occur on both Cu sites and Brønsted acid sites, which are active sites for NOx reduction in the Cu-chabazite catalyst, but it is unclear where NH4NO3 accumulates on the catalyst. Analyses using catalyst test pieces with different active sites were performed to estimate this accumulation. The results suggested that NH4NO3 accumulation does not depend on the presence of either Cu sites or Brønsted acid sites. Therefore, it is assumed that NH4NO3 can be accumulated everywhere on the catalyst, including on the zeolite framework. This phenomenon was included in the model as formation/accumulation sites S'.

Performance predictions of advanced turbocharged engines are becoming difficult because conventional engine models are built using performance map data of turbochargers with a proportional integral derivative (PID) controller. Improving prediction capabilities under transient test cycles or real driving conditions is a challenging task. This study applies a machine learning technique to predict turbocharger performances with high accuracy under steady-state and transient conditions. The manipulated signals of engine speed and torque created based on Compressed High-Intensity Radiated Pulse (Chirp signal) and Amplitude-modulated Pseudo-Random Binary Signal (APRBS) are used as inputs to the engine testbed. Data from the engine experiments are used as training data for the AI-based turbocharger model. High prediction accuracy of the AI turbocharger model is achieved with the co-efficient of determination in the model, and cross-validation results are higher than 0.8.

Emission regulations are becoming tighter, and Real Driving Emissions (RDE) is proposed as a testing cycle for evaluating modern engine emissions under a wide operation range. For this reason, engine manufacturers have been developing a method to effectively assess engine performances and emissions under a wide range of transient conditions. Transient engine performances can be evaluated efficiently by applying time-series data created by chirp signals. However, when the time-series data produced by the chirp signal are used directly, the engine hardware may damage, and emission performances deteriorate drastically. It is therefore essential to develop a method to avoid these undesirable operating conditions. This work aims to develop an algorithm to avoid such unrealistic operation conditions for engine performance evaluation. A virtual diesel engine (VDE) model is developed based on a four-cylinder engine using GT-POWER software.

Three-way catalyst (TWC) converters can purify harmful substances, such as carbon monoxide, nitrogen oxides, and hydrocarbons, from the exhaust gases of gasoline engines. However, large amounts of these substances may be emitted before the TWC reaches its light-off temperature during cold starts, and its performance may be impaired by thermal deterioration during high-load driving. In this work, a simulation model was developed using axisuite commercial software by Exothermia S.A to predict the light-off conversion performance of Pd/CeO2-ZrO2-Al2O3 catalysts with different degrees of thermal deterioration. The model considered detailed surface reactions and the main factor of the deterioration mechanism. In the detailed reaction mechanism, adsorption, desorption, and surface reactions of each gas species at active sites of the platinum group metal (PGM) particles were considered based on the Langmuir-Hinshelwood mechanism.

The purpose of this paper is to find a universal law to predict a turbulent burning velocity under various operating conditions and engine specifications. This paper presents the relationship between turbulent burning velocity and Karlovitz number. The turbulent burning velocity was measured using a single-cylinder gasoline engine, which has an external Exhaust Gas Recirculation (EGR) system. In the experiment, various engine operating parameters, e.g. engine speed and EGR rates, and various engine specifications, i.e. different types of intake ports were tested. Karlovitz number was calculated with Three Dimensional Computational Fluid Dynamics (3D-CFD) and detailed chemical reaction calculation, which condition was based on the experiment. The experimental and calculation results show that turbulent burning velocity is predicted by using Karlovitz number in the engine conditions, which varies depending on engine speed, EGR rates and the designs of intake ports.

Natural gas has been used in spark-ignition (SI) engines of natural gas vehicles (NGVs) due to its resource availability and stable price compared to gasoline. It has the potential to reduce carbon monoxide emissions from the SI engines due to its high hydrogen-to-carbon ratio. However, short running distance is an issue of the NGVs. In this work, methodologies to improve the fuel economy of a heavy-duty commercial truck under the Japanese Heavy-Duty Driving Cycle (JE05) is proposed by numerical 1D-CFD modeling. The main objective is a comparative analysis to find an optimal fuel economy under three variable mechanisms, variable valve timing (VVT), variable valve actuation (VVA), and variable compression ratio (VCR). Experimental data are taken from a six-cylinder turbocharged SI engine fueled by city gas 13A. The 9.83 L production engine is a CR11 type with a multi-point injection system operated under a stoichiometric mixture.