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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.

The recent and future trends of energy for heavy-duty vehicles are considered e-fuel, H2, and electricity, and the Selective Catalytic Reduction (SCR) system is necessary for achieving the goals of zero-emission internal combustion engines that use e-fuel and H2 as a fuel. The Japanese automotive industry uses a Cu-zeolite based SCR catalyst since Vanadium is designated as a specific chemical substance, which the Ministry of Environment prohibits its release into the atmosphere. This study attempted purification rate improvement by controlling the NH3 supply with a mini-reactor and by simulated exhaust gas. Specifically, the experiment was done by examining the effect of the pulse amplitude, frequency, and duty ratio on the purification rate by supplying the NH3 pulse injection to the test piece Cu-chabazite catalyst. Additionally, the results of the reactor experiment were validated by numerical simulation considering the detailed surface reaction processes on the catalyst.

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.

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%.

Alternative propulsion systems such as renewable fuels and electric powertrains are expensive; thus, efficient internal combustion engines (ICE) with hybrid powertrains still play significant roles in the transportation fleet in the coming decades. Modern engine technologies have been adopted to meet stringent emissions and fuel economy standards. As a result, engine control systems are becoming more complex. Furthermore, as ICE control parameters increase exponentially, engine calibration and design become bottlenecks in the development process. While a map-based feed-forward control method is a current de facto standard in combustion control, online closed-loop feedback control can improve engine performance and robustness. However, adding physical sensors to measure the various data for the online feedback control and calibration increase the vehicle cost.

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).

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.

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.

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.

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.

This paper focuses on an assessment of predictive combustion model using a 0D/1D simulation tool under high load, different excess air ratio λ , and different combustion stabilities (based on coefficient of variation of indicated mean effective pressure COVimep). To consider that, crank angle resolved data of experimental pressure of 500 cycles are recorded under engine speed 1000 RPM and 2000 RPM, wide-open throttle, and λ=1.0, 1.42, 1.7, and 2.0. Firstly, model calibration is conducted using 18 cases at 2000 RPM using 500 cycle-averaged in-cylinder pressure to find optimized model constants. Then, the model constants are unchanged for other cases. Next, different cycle-averaged pressure data are used as inputs in the simulation based on the COVimep for studying sensitivity of the turbulent model constants. The simulation is conducted using 1D simulation software GT-Power.

With the development of downsized spark ignition (SI) engines, low-speed pre-ignition (LSPI) has been observed more frequently as an abnormal combustion phenomenon, and there is a critical need to solve this issue. It has been acknowledged that LSPI is not directly triggered by autoignition of the fuel, but by some other material with a short ignition delay time. It was previously reported that LSPI can be caused by droplets of lubricant oil intermixed with the fuel. In this work, the ignition behavior of lubricant component containing fuel droplets was experimentally investigated by using a constant volume chamber (CVC) and a rapid compression and expansion machine (RCEM), which enable visualization of the combustion process in the cylinder. Various combinations of fuel compositions for the ambient fuel-air mixture and fractions of base oil/metallic additives/fuel for droplets were tested.

Primary work is to investigate premixed laminar flame propagation in a constant volume chamber of iso-octane/air combustion. Experimental and numerical results are investigated by comparing flame front displacements under lean to rich conditions. As the laminar flame depends on equivalence ratio, temperature, and pressure conditions, it is a main property for chemical reaction mechanism validation. Firstly, one-dimensional laminar flame burning velocities are predicted in order to validate a reduced chemical reaction mechanism. A set of laminar burning velocities with pressure, temperature, and mixture equivalence ratio dependences are combined into a 3D-CFD calculation to compare the predicted flame front displacements with that of experiments. It is found that the reaction mechanism is well validated under the coupled 1D-3D combustion calculations. Next, lean experiments are operated in a SI engine by boosting intake pressure to maintain high efficiency without output power penalty.

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.

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.

Natural gas is a promising alternative fuel for internal combustion engines because of its clean combustion characteristics and abundant reserves. However, it has several disadvantages due to its low energy density and low thermal efficiency at low loads. Thus, to assist efforts to improve the thermal efficiency of spark-ignited (SI) engines operating on natural gas and to minimize test procedures, a numerical simulation model was developed to predict and optimize the performance of a turbocharged test engine, considering flame propagation, occurrence of knock and ignition timing. The numerical results correlate well with empirical data, and show that increasing compression ratios and retarding the intake valve closing (IVC) timing relative to selected baseline conditions could effectively improve thermal efficiency. In addition, employing moderate EGR ratios is also effective for avoiding knock.

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.