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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.

Battery thermal management system (BTMS) significantly improves battery electric vehicle (BEV) performance, especially under cold weather. A tradeoff between battery power consumption and cabin heating performance must be considered in cold driving conditions. This preliminary study aims to develop an integrated battery pack and coolant channel model to predict the thermal behavior of a BEV thermal management system. In this study, we develop and calibrate the physical baseline model with testbench data using finite element and CFD software. First, an electrochemical battery cell 1D model (Pseudo-2D or P2D) is built and calibrated against the cell reference data. An integrated pack model consisting of four modules (each has 23 and 25 bricks and a total of 4416 cells) with coolant flow channels is developed using reference and benchmarked data.

HEV and PHEV require an improved aftertreatment system to clean the exhaust gas in various driving situations. The efficiency of aftertreatment system is significantly influenced by the residence time of the gas in a catalyst which gas flow has generally strong pulsation. Simulation showed up to 70% reduction of exhaust gas emission if the pulsation could be completely attenuated. A new concept exhaust manifold was designed to minimize pulsation flow by wall impingement, with slight increase of pressure loss. Experimental results with new concept exhaust manifold showed exhaust gas emission were reduced 16% at cold condition and 40% at high-load condition.

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.

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'.

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.

In this study, reaction path analysis and modeling of NOx reduction phenomena by selective catalytic reduction (SCR) with NH3 over a Cu-chabazite catalyst were conducted considering changes in the valence state of Cu sites and local structure due to differences in ligands to the Cu sites. The analysis showed that in the Cu-chabazite catalyst, NOx was mainly reduced by adsorbed NH3 on divalent Cu sites accompanied by a change in valence state of Cu from divalent to monovalent. It is known that the activation energy of NOx reduction on a Cu-chabazite catalyst changes between low temperatures ≤ 200 °C and mid to high temperatures ≥ 300 °C. To express this phenomenon, a reversible hydrolysis reaction based on the difference in coordination state of hydroxyl groups (OH−) to Cu sites at low and high temperatures was introduced into the model.

Battery models are being developed as a component of the powertrain systems of hybrid electric vehicles (HEVs) to predict the state of charge (SOC) accurately. Electrically heated catalysts (EHCs) can be employed in the powertrains of HEVs to reach the catalyst light off temperature in advance. However, EHCs draw power from the battery pack and hence sufficient energy needs to be stored to power auxiliary components. In series HEVs, the engine is primarily used to charge the battery pack. Therefore, it is important to develop a control strategy that triggers engine start/stop conditions and reduces the frequency of engine operation to minimize the equivalent fuel consumption. In this study, a battery pack model was constructed in MATLAB-Simulink to investigate the SOC variation of a high-power lithium ion battery during extreme engine cold start conditions (-7°C) with/without application of an EHC.

This paper describes a method for estimating constants related to NH3 gas diffusion phenomena to the active sites in a selective catalytic reduction diesel particulate filter (SCR/DPF) catalyst. A simple one-dimensional NH3 gas diffusion model based on the pore structure inside the catalyst was developed and used to estimate the intracrystalline diffusion coefficient. It was shown that the estimated value agreed well with experimental data.

Three-way catalyst (TWC) converters are often used to purify toxic substances contained in exhaust emissions from gasoline engines. However, a large amount of CO, NOx and THC may be emitted before the TWC reaches its light-off temperature during a cold start. In this work, a numerical model was developed for studying the purification performance of a close-coupled TWC converter during the cold start period. The TWC model was built using axisuite, commercial software by Exothermia S.A. Model gas experiments were designed for calibrating the chemical reaction scheme and corresponding reaction rate parameters in the TWC model. The TWC model was able to simulate the purification performance of CO, NOx and THC under both lean and rich air-fuel equivalence ratios (λ) for different conditions. The light-off temperature and oxygen storage capacity (OSC) behavior were also successfully validated in the model. Vehicle tests were conducted on a chassis dynamometer to verify the TWC model.

The NOx-reducing activity of a Cu-chabazite selective catalytic reduction (SCR) catalyst was analyzed over a wide temperature range. The analysis was based on the ammonia SCR (NH3-SCR) mechanism and accounted for Cu redox chemistry and reactions at Brønsted acid sites. The reduction of NOx to N2 (De-NOx) at Cu sites was found to proceed via different paths at low and high temperatures. Consequently, the rate-limiting step of the SCR reaction at Cu sites varied with the temperature. The rate of NOx reduction at Cu sites below 200°C was determined by the rate of Cu oxidation. Conversely, the rate of NOx reduction above 300°C was determined by the rate of NH3 adsorption on Cu sites. Moreover, the redox state of the active Cu sites differed at low and high temperatures. To clarify the role of the chabazite Brønsted acid sites, experiments were also performed using a H-chabazite catalyst that lacks Cu sites.

Three-way catalyst (TWC) converters are used to remove harmful substances (e.g., carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HC)) emitted from gasoline engines. However, a large amount of emissions could be emitted before the TWC reaches its light-off temperature during a cold start. For hybrid electric vehicles (HEVs) powered by gasoline engines, the emission purification performance by TWC converters unfortunately deteriorates because of mode switching from engine to battery and vice versa, which can repeatedly generate cold start conditions for the TWCs. In this study, aiming to reduce emissions from series HEVs by early activation of TWCs, numerical simulations and experiments are carried out. An HEV is tested on a chassis dynamometer in the Worldwide Light-duty Test Cycle (WLTC) mode. The upstream and downstream gas conditions of the close-coupled catalyst converter are measured.

Pre-chamber spark ignition technology can stabilize combustion and improve thermal efficiency of lean burn natural gas engines. During compression stroke, a homogeneous lean mixture is introduced into pre-chamber, which separates spark plug electrodes from turbulent flow field. After the pre-chamber mixture is ignited, the burnt jet gas is discharged through multi-hole nozzles which promotes combustion of the lean mixture in the main chamber due to turbulence caused by high speed jet and multi-points ignition. However, details mechanism in the process has not been elucidated. To design the pre-chamber geometry and to achieve stable combustion under the lean condition for such engines, it is important to understand the fundamental aspects of the combustion process. In this study, a high-speed video camera with a 306 nm band-pass filer and an image intensifier is used to visualize OH* self-luminosity in rapid compression-expansion machine experiment.

Ammonia-selective catalytic reduction (SCR) systems have been introduced commercially in diesel vehicles, however catalyst systems with higher conversion efficiency and better control characteristics are required to know the actual emissions during operation and the emissions in random test cycles. Computational fluid dynamics (CFD) is an effective approach when applied to SCR catalyst development, and many models have been proposed, but these models need experimental verification and are limited in the situations they apply to. Further, taking account of redox cycle is important to have better accuracy in transient operation, however there are few models considering the cycle. Model development considering the redox reactions in a zeolite catalyst, Cu-ZSM-5, is the object of the research here, and the effects of exhaust gas composition on the SCR reaction and NH3 oxidation at high temperatures are investigated.