Search Results

To improve the maneuverability and energy consumption of an electrical vehicle, a two-level speed control method based on model predictive control (MPC) is proposed for accurate control of the vehicle during downhill coasting. The targeted acceleration is planned using the anti-interference speed filter and MPC algorithm in the upper-level controller and executed using the integrated algorithm with the inverse vehicle dynamics and proportional-integral-derivative control model (PID) in the lower-level controller, improving the algorithm’s anti-interference performance and road adaptability. Simulations and vehicle road tests showed that the proposed method could realize accurate real-time speed control of the vehicle during downhill coasting. It can also achieve a smaller derivation between the actual and targeted speeds, as well as more stable speeds when the road resistance changes abruptly, compared with the conventional PID method.

The fuel-saving potential of a series hybrid electric vehicle (SHEV) was investigated in this work based on the future goals and technical roadmaps proposed by China's automobile and internal combustion engine (ICE) industry. The genetic algorithm optimization method and dynamic programming energy management strategy are used to optimize the key component parameters of a typical SHEV SUV to improve the fuel economy of the vehicle. Results showed that the fuel consumption of the vehicle would be 3.24 L / 100km in 2035, which is 37.21% less than 5.16 L / 100km in 2020, following the industries’ roadmaps. The results also indicated that the improvement of the ICE’s thermal efficiency is the main reason for the decrease of the vehicle’s fuel consumption. In addition, the improvement of working points and the reduction of energy losses of the key components also contribute to the improvement of the fuel economy.

The driving conditions of commercial logistics vehicles have the characteristics of combined urban and suburban roads with relatively fixed mileage and cargo load alteration, which affect the vehicular fuel economy. To this end, an adaptive equivalent consumption minimization strategy (A-ECMS) with vehicle speed and weight recognition is proposed to improve the fuel economy for a range-extender electric van for logistics in this work. The driving conditions are divided into nine representative groups with different vehicle speed and weight statuses, and the driving patterns are recognized with the use of the bagged trees algorithm through vehicle simulations. In order to generate the reference SOC near the optimal values, the optimal SOC trajectories under the typical driving cycles with different loads are solved by the shooting method and the optimal slopes for these nine patterns are obtained.

Numerical analysis of thermal efficiency improvement up to 45% of an 1.8-liter turbocharged direct-injection (DI) gasoline engine was conducted in this study in response to the need of improving vehicle fuel economy. 1D thermodynamics simulations and 3D computational fluid dynamics (CFD) modeling were carried out to investigate the technical approaches for improving engine thermal efficiency. Effects of various technologies on the improvement in the engine performance were evaluated, and then the technical routes to achieve 41% and 45% brake thermal efficiency were summarized, respectively. It is concluded that 41% thermal efficiency can be reached under stoichiometric combustion conditions, while it is expected lean burn technology is needed for the target of 45% thermal efficiency. The effects of high tumble intake flow on accelerating burning speed and of high compression ratio on intensifying knocking were analyzed.

Knocking combustion limits the application of high compression ratios in gasoline engines and therefore obstructs the improvement of thermal efficiency. Predicting knock and knock limited spark advance (KLSA) can guide engine upfront design and optimization before the prototype is built. This study employed three-dimensional computational fluid dynamics (CFD) simulations coupled with an accurate and computation-efficient knock model to predict the KLSA of a turbocharged direct-injection spark-ignition engine. The knock model predicted the end-gas auto-ignition based on a Livengood-Wu (L-W) integral transport equation instead of directly using detailed chemical mechanisms, which was able to achieve a fast computation time. To keep the predictability, ignition delay data was calculated using zero-dimensional chemistry simulation and tabulated a priori, which was then used for CFD simulation on the fly.

In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.

Studies were carried out for improvement of combustion performance of an 1.2 L dedicated range-extender gasoline engine which uses a high compression ratio, cooled exhaust-gas-recirculation (EGR) and Atkinson cycle. The intake-charging characteristics were investigated both computationally and experimentally in order to compensate the torque reduction mainly due to the charge pushback in the Atkinson cycle. The design parameters of the intake manifold were refined to increase the intake air charges. 1D simulations were carried out to investigate the effect of the runner lengths and diameters. The results indicated that the increased length and reduced diameter could improve the volumetric efficiency in the most used engine speed range. Furthermore, computational fluid dynamics (CFD) simulations were employed to evaluate the cylinder-to-cylinder charging variations of the proposed manifold and reduced variations were obtained.

Surface film formation is an important phenomenon during spray impingement in a combustion chamber. The film that forms on the chamber walls and piston bowl produces soot post-combustion. While some droplets stick to the wall surface, others splash and interact with the gas present inside the combustion chamber. Accurate prediction of both the film thickness and splashed mass is crucial for surface film model development since it leads to a precise estimation of the amount of soot and other exhaust gases formed. This information could guide future studies aimed at a comprehensive understanding of the combustion process and might enable development of engines with reduced emissions. Dynamic structure Large Eddy Simulation (LES) turbulence model implemented for in-cylinder sprays [1] has shown to predict the flow structure of a spray more accurately than the Reynolds-averaged Navier-Stokes turbulence model.

In most large-eddy simulation (LES) applications to two-phase engine flows, the liquid-air interactions need to be accounted for as source terms in the respective governing equations. Accurate calculation of these source terms requires the relative velocity “seen” by liquid droplets as they move across the flow, which generally needs to be estimated using a turbulent dispersion model. Turbulent dispersion modeling in LES is very scarce in the literature. In most studies on engine spray flows, sub-grid scale (SGS) models for the turbulent dispersion still follow the same stochastic approach originally proposed for Reynolds-averaged Navier-Stokes (RANS). In this study, an SGS dispersion model is formulated in which the instantaneous gas velocity is decomposed into a deterministic part and a stochastic part. The deterministic part is reconstructed using the approximate deconvolution method (ADM), in which the large-scale flow can be readily calculated.

Although turbocharging can extend the high load limit of low temperature combustion (LTC) strategies such as reactivity controlled compression ignition (RCCI), the low exhaust enthalpy prevalent in these strategies necessitates the use of high exhaust pressures for improving turbocharger efficiency, causing high pumping losses and poor fuel economy. To mitigate these pumping losses, the divided exhaust period (DEP) concept is proposed. In this concept, the exhaust gas is directed to two separate manifolds: the blowdown manifold which is connected to the turbocharger and the scavenging manifold that bypasses the turbocharger. By separately actuating the exhaust valves using variable valve actuation, the exhaust flow is split between two manifolds, thereby reducing the overall engine backpressure and lowering pumping losses. In this paper, results from zero-dimensional and one-dimensional simulations of a multicylinder RCCI light-duty engine equipped with DEP are presented.

A swept-volume method of calculating the volume swept by the flame during each time step is developed and used to improve the calculation of fuel reaction rates. The improved reaction rates have been applied to the ignition model and coupled with the level set G-equation combustion model. In the ignition model, a single initial kernel is formed after which the kernel is convected by the gas flow and its growth rate is determined by the flame speed and thermal expansion due to the energy transfer from the electrical circuit. The predicted ignition kernel size was compared with the available experimental data and good agreements were achieved. Once the ignition kernel reaches a size when the fully turbulent flame is developed, the G-equation model is switched on to track the mean turbulent flame front propagation.

Natural gas is a promising alternative fuel for internal combustion engines due to its rich reserves and low price, as well as good physical and chemical properties. Its low carbon structure and high octane number are beneficial for CO2 reduction and knock mitigation, respectively. Diesel and natural gas dual fuel combustion is a viable pathway to utilize natural gas in diesel engines. To achieve high efficiency and low emission combustion in a practical diesel engine over a wide range of operating conditions, understanding the performance responses to engine system parameter variations is needed. The controllability of two combustion strategies, diesel pilot ignition (DPI) and single injection reactivity controlled compression ignition (RCCI), were evaluated using the multi-dimension CFD simulation in this paper.

In this paper, large eddy simulation (LES) coupled with two uncertainty quantification (UQ) methods, namely latin-hypercube sampling (LHS) and polynomial chaos expansion (PCE), have been used to quantify the effects of model parameters and spray boundary conditions on diesel and gasoline spray simulations. Evaporating, non-reacting spray data was used to compare penetration, mixture fraction and spray probability contour. Two different sets of four uncertain variables were used for diesel and gasoline sprays, respectively. UQ results showed good agreement between experiments and predictions. UQ statistics indicated that discharge coefficient has stronger impact on gasoline than diesel sprays, and spray cone angle is important for vapor penetration of both types of sprays. Additionally, examination of the gasoline spray characteristics showed that plume-to-plume interaction and nozzle dribble are important phenomena that need to be considered in high-fidelity gasoline spray simulations.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

Three time integration schemes and four finite volume interpolation schemes for the convection term in momentum equation were tested under turbulent planar gas jet and Sandia non-reacting vaporizing Spray-H cases. The three time integration schemes are the first-order Euler implicit scheme, the second-order backward scheme, and the second-order Crank-Nicolson scheme. The four spatial interpolation schemes are cubic central, linear central, upwind, and vanLeer schemes. Velocity magnitude contour, centerline and radial mean velocity and Reynolds stress profiles for the planar turbulent gas jet case, and fuel vapor contour and liquid and vapor penetrations for the Diesel spray case predicted by the different numerical schemes were compared. The sensitivity of the numerical schemes to mesh resolution was also investigated. The non-viscosity based dynamic structure subgrid model was used. The numerical tool used in this study was OpenFOAM.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

Knock in a Rotax-914 engine was modeled and investigated using an improved version of the KIVA-3V code with a G-equation combustion model, together with a reduced chemical kinetics model. The ERC-PRF mechanism with 47 species and 132 reactions [1] was adopted to model the end gas auto-ignition in front of the flame front. The model was validated by a Caterpillar SI engine and a Rotax-914 engine in different operating conditions. The simulation results agree well with available experimental results. A new engineering quantified knock criterion based on chemical mechanism was then proposed. Hydroperoxyl radical (HO2) shows obvious accumulation before auto-ignition and a sudden decrease after auto-ignition. These properties are considered to be a good capability for HO2 to investigate engine knock problems.

The paper reports the application of Proper Orthogonal Decomposition (POD) to LES calculations for the analysis of combustion and knock tendency in a highly downsized turbocharged GDI engine that is currently under production. In order to qualitatively match the cyclic variability of the combustion process, Large-Eddy Simulation (LES) of the closed-valve portion of the cycle is used with cycle-dependent initial conditions from a previous multi-cycle analysis [1, 2, 3]. Detailed chemical modelling of fuel's auto-ignition quality is considered through an ad-hoc implemented look-up table approach, as a trade-off between the need for a reasonable representation of the chemistry and that of limiting the computational cost of the LES simulations. Experimental tests were conducted operating the engine at knock-limited spark advance (KLSA) and the proposed knock model was previously validated for such engine setup [3].

The paper reports the application of a look-up table approach within a LES combustion modelling framework for the prediction of knock limit in a highly downsized turbocharged DISI engine. During experimental investigations at the engine test bed, high cycle-to-cycle variability was detected even for relatively stable peak power / full load operations of the engine, where knock onset severely limited the overall engine performance. In order to overcome the excessive computational cost of a direct chemical solution within a LES framework, the use of look-up tables for auto-ignition modelling perfectly fits with the strict mesh requirements of a LES simulation, with an acceptable approximation of the actual chemical kinetics. The model here presented is a totally stand-alone tool for autoignition analysis integrated with look-up table reading from detailed chemical kinetic schemes for gasoline.

In this work non-reacting spray simulations are performed using two Computational Fluid Dynamic (CFD) codes, KIVA and OpenFoam. The metric used is the liquid tip penetration which is compared with experimental data from the Engine Combustion Network at Sandia National Laboratories. Some important spray sub-models, available in KIVA, are implemented in OpenFOAM so that the two codes have more common models. In addition, model coefficients and computations cells used in the simulations are the same in both codes. The differences in spray source terms formulations and other spray sub models between the codes and their effect on liquid penetration are discussed.