Search Results

Abstract The water droplet erosion (WDE) on high-speed rotating wheels appears in several engineering fields such as wind turbines, stationary steam turbines, fuel cell turbines, and turbochargers. The main reasons for this phenomenon are the high relative velocity difference between the colliding particles and the rotor, as well as the presence of inadequate material structure and surface parameters. One of the latest challenges in this area is the compressor wheels used in turbochargers, which has a speed up to 300,000 rpm and have typically been made of aluminum alloy for decades, to achieve the lowest possible rotor inertia. However, while in the past this component was only encountered with filtered air, nowadays, due to developments in compliance with tightening emission standards, various fluids also collide with the spinning blades, which can cause mechanical damage.

Abstract This article presents surrogate mixtures that simulate the physical and chemical properties in the auto-ignition of hydrotreated vegetable oil (HVO). Experimental investigation was conducted in the Ignition Quality Tester (IQT) to validate the auto-ignition properties with respect to those of the target fuel. The surrogate development approach is assisted by artificial neural network (ANN) embedded in MATLAB optimization function. Aspen HYSYS is used to calculate the key physical and chemical properties of hundreds of mixtures of representative components, mainly alkanes—the dominant components of HVO, to train the learning algorithm. Binary and ternary mixtures are developed and validated in the IQT. The target properties include the derived cetane number (DCN), density, viscosity, surface tension, molecular weight, and volatility represented by the distillation curve. The developed surrogates match the target fuel in terms of ignition delay and DCN within 6% error range.

Abstract A numerical study using large-eddy simulations (LES) to reproduce and understand sources of cycle-to-cycle variation (CCV) in spark-initiated internal combustion engines (ICEs) is presented. Two relevantly different spark-ignition (SI) units, that is, a homogeneous-charge slow-speed single-cylinder research unit (the transparent combustion chamber (TCC)-III, Engine 1) and a stratified-charge high-revving speed gasoline direct injection (GDI) (Engine 2) one, are analyzed in fired operations. Multiple-cycle simulations are carried out for both engines and LES results well reproduce the experimentally measured combustion CCV. A correlation study is carried out, emphasizing the decisive influence of the early flame period variability (1% of mass fraction burnt (MFB1)) on the entire combustion event in both ICEs. The focus is moved onto the early flame characteristics, and the crucial task to determine the dominant causes of its variability (if any) is undertaken.

Abstract The variability of fuel economy (FE) is of significant importance as that of average FE to realize FE benefits of hybrid electric vehicles (HEVs) consistently by all users in the real world. Over the years, majority of the research has been focused on improving average FE overlooking the variability. Although in recent years few studies have been focused on the reduction of FE variability, no study has been concentrated to understand why certain design has lower FE variability as that of others. This article provides a detailed analysis to decipher the reasons for the FE variability in the real world. This study considered the optimum designs based on two established design optimization methodologies considering Toyota Prius non-plug-in hybrid as a base vehicle. This study analyses the impacts of the parameters of driving patterns and the operation of powertrains on FE variability.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract This article focuses on the development of a two-way coupled methodology to predict gear temperature of oil jet lubricated transmissions using commercial software for computational fluid dynamics simulation. The proposed methodology applies an overset mesh technique to model the gear interlocking motion, multiphase of air-oil mixture, and heat transfer. Two gear pairs were used to develop and validate the methodology, an overdrive helical gear pair of a commercial vehicle transmission and a standard spur gear pair. Different oil jet lubrication methods were investigated using the proposed methodology, such as oil jet directed at the into-mesh position and at the out-of-mesh position. This investigation showed that out of mesh lubrication direction shows better cooling performance which is in well agreement with previous studies of literature.

Abstract In urban roads the engine speed and the load vary suddenly and frequently, resulting in increased exhaust emissions. In such operations, the effect of air injection technique to access the transient response of the engine is of great interest. The effectiveness of air injection technique in improving the transient response under speed transient is investigated in detail [1]; however, it is not evaluated for the load transients. Load step demand of the engine is another important event that limits the transient response of the turbocharger. In the present study, response of a heavy-duty turbocharged diesel engine is investigated for different load conditions. Three cases of load transients are considered: constant load, load magnitude variation, and load scheduling. Air injection technique is simulated and after optimization of injection pressure based on orifice diameter, its effect on the transient response is presented.

Abstract Low-Pressure cooled Exhaust Gas Recirculation (LP-cEGR) is proven to be an effective technology for fuel efficiency improvement in turbocharged spark-ignition (SI) engines. Aiming to fully exploit the EGR benefits, new challenges are introduced that require more complex and robust control systems and strategies. One of the most important restrictions of LP-cEGR is the transient response, since long air-EGR flow paths introduce significant transport delays between the EGR valve and the cylinders. High dilution generally increases efficiency, but can lead to cycle-by-cycle combustion variation. Especially in SI engines, higher-than-requested EGR dilution may lead to combustion instabilities and misfires. Considering the long EGR evacuation period, one of the most challenging transient events is throttle tip-out, where the engine operation shifts from a high-load point with high dilution tolerance to a low-load point where EGR tolerance is significantly reduced.

Abstract Autonomy and connectivity are considered among the most promising technologies to improve safety and mobility and reduce fuel consumption and travel delay in transportation systems. In this paper, we devise an optimal control-based trajectory planning model that can provide safe and efficient trajectories for the subject vehicle while incorporating platoon formation and lane-changing decisions. We embed this trajectory planning model in a simulation framework to quantify its fuel efficiency and travel time reduction benefits for the subject vehicle in a dynamic traffic environment. Specifically, we compare and analyze the statistical performance of different controller designs in which lane changing or platooning may be enabled, under different values of time (VoTs) for travelers.

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Abstract A torque converter was instrumented with 29 pressure transducers inside five cavities under study (impeller, turbine, stator, clutch cavity between the pressure plate and the turbine shell). A computer model was created to establish correlation with measured torque and pressure. Torque errors between test and simulation were within 5% and K-Factor and torque ratio errors within 2%. Turbulence intensity on the computer model was used to simulate test conditions representing transmission low and high line pressure settings. When turbulence intensity was set to 5%, pressure simulation root mean square errors were within 11%-15% for the high line pressure setting and up to 34% for low line pressure setting. When turbulence intensity was increased to 50% for the low line pressure settings, a 6% reduced root mean square error in the pressure simulations was seen.

Abstract This article introduces a finite element (FE) approach to determine tire deformation and its effect on open-wheel race car aerodynamics at high vehicle velocities. In recent literature tire deformation was measured optically. Combined loads like accelerating at a corner exit are difficult to reproduce in wind tunnels and require several optical devices to measure the tire deformation. In contrast, an FE approach is capable of determining the tire deformation in combined load states accurately. Additionally, the temperature influence on tire deformation is investigated. The FE tire model was validated using three-dimensional (3D) scan measurements; stiffness measurements in the vertical, lateral, and longitudinal direction; and the change of loaded radius with speed at different loads, respectively. The deformed shape of the tire of the FE model was used in a computational fluid dynamics (CFD) simulation.

Abstract The wide application of Gasoline Direct Injection (GDI) engines and the increasingly stringent Particulate Matter (PM) and Particulate Number (PN) regulations make Gasoline Particulate Filters (GPFs) with high filtration efficiency and low pressure drop highly desirable. However, due to the specifics of GDI operation and GDI PM, the design of these filters is even more challenging as compared to their diesel counterparts. Computational Fluid Dynamics (CFD) studies have been shown to be an effective way to investigate filter performance. In particular, our previous two-dimensional (2D) CFD study explicated the pore size and pore-size distribution effects on GPF filtration efficiency and pressure drop. The “throat unit collector” model developed in this study furthers this work in order to characterize the GPF wall microstructure more precisely.

Abstract The range of an aircraft is determined by the amount of energy that its batteries can store. Today, larger batteries are used to increase the range of electric vehicles, although energy efficiency decreases as the weight of the vehicles increases. Among the elements, lithium (Li) is the lightest and has the highest electrochemical potential. Therefore, the use of Li-ion batteries is recommended for hybrid aircraft. In addition, Li-ion batteries are the most common type of battery that is used in portable electronic devices such as smartphones, tablets, and laptops. However, Li-ion batteries may explode due to temperature. Therefore, the thermal analysis of Li-ion batteries was investigated both experimentally and numerically. Li-ion batteries were connected in series (the number is 9). Noboru’s theory of heat generation was discussed in the estimation of energy data.

Abstract Accurate exhaust gas temperature (EGT) measurements are vital in the design and development process of internal combustion engines (ICEs). The unsteady ICE exhaust flow and thermal inertia of commonly used sheathed thermocouples and resistance thermometers require high bandwidth EGT pulse measurements for accurate cycle-resolved and mean EGTs. The EGT pulse measurement challenge is typically addressed using exposed thin-wire resistance thermometers or thermocouples. The sensor robustness to response tradeoff limits ICE tests to short durations over a few exhaust conditions. Larger diameter multiwire thermocouples using response compensation potentially overcomes the tradeoff. However, the literature commonly adopts weaker slack wire designs despite indications of coated weld taut wires being robust.

Abstract Diesel engines include systems for cooling, lubrication, and fuel injection and contain a variety of components. A malfunction in any of the engine systems or the presence of any faulty element influences engine performance and deteriorates its components. This research is concerned with the untimely appearance of vital cracks in the liners of a turbocharged heavy-duty Diesel engine. To find the root causes for premature failure, rigorous examinations through visual observations, material characterization, and metallographic investigations are performed. These include Scanning Electron Microscope (SEM) and Energy-Dispersive Spectroscopy (EDS), fracture mechanics analysis, and performance examination, which are also followed by Finite Element Moldings. To find the proper remedy to resolve the problem, drawing a precise and reliable picture of the engine’s operating conditions is required.

Abstract Increasing thermal and fuel efficiency in Internal Combustion Engines (ICEs) requires thorough investigations on the combustion process and its thermodynamics. The first law of thermodynamics expresses the balance of the energy, while the second law specifies the maximum achievable work. In this article, Low-Temperature Combustion (LTC) strategies, including Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), Partially Premixed Combustion (PPC), and Direct Dual-Fuel Stratification (DDFS) were analyzed by the first and second law approaches, and they were compared with ideal-diesel cycle and Conventional Diesel Combustion (CDC). HCCI and RCCI had the highest exergy efficiency of 50.8% and 49.2%, respectively, compared to other cases, and exergy destruction in these cases was the lowest (25.3% and 27.5%, respectively).

Abstract The brake discs are subjected to thermal load due to sliding by the brake pad and fluctuating loads because of the braking load. This combined loading problem requires simulation using coupled thermo-mechanical analysis for design evaluation. This work presents a combined thermal and mechanical finite element analysis (FEA) and evolutionary optimization-based novel approach for estimating the optimal design parameters of the ventilated brake disc. Five parameters controlling the design: inboard plate thickness, outboard plate thickness, vane height, effective offset, and center hole radius were considered, and simulation runs were planned. A total of 27 brake disc designs with design parameters as recommended by the Taguchi method (L27) were modeled using SolidWorks, and the FEA simulation runs were carried out using the ANSYS thermal and structural analysis tool.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract Off-highway equipment are subjected to diverse environmental conditions, severe duty cycles, and multiple simultaneous operations. Due to its continuous, high-power adverse operating conditions, equipment are exposed to high thermal loads, which result in the deterioration of its performance and efficiency. This article describes a model-based system simulation approach for thermal performance evaluation of a self-propelled off-highway vehicle. The objective of developing the simulation model including thermal fidelity is to quantify the impact of thermal loads on vehicular system/subsystems performance. This article also describes the use of simulation models for driving architectural design decisions and virtual test replication in all stages of product development.