Search Results

With the increasing number of hybrid vehicles in the Chinese market, research on aftertreatment systems for hybrid vehicles has become very popular. China has currently implemented national on-road China 6 regulations for emission control of all gasoline and diesel vehicles, including hybrid ones. So far, there are few papers on the optimization of aftertreatment for hybrid gasoline vehicles. Due to the introduction of electric motors in hybrid vehicles, the engine starts frequently and leads to inconsistent stability of engine operating conditions and brings the challenge to emission control of engine exhaust. This article selects a highly popular hybrid gasoline vehicle in China for research, which is a dual-mode hybrid (DM hybrid) passenger car. There is an obvious correlation between the emissions between the driving pattern and the hybrid strategy.

The possibility to operate current diesel engines in dual-fuel mode with the addition of an alternative fuel is fundamental to accelerate the energy transition to achieve carbon neutrality. The simulation of the dual- fuel combustion process with 0D/1D combustion models is fundamental for the performance prediction, but still particularly challenging, due to chemical interactions of the mixture. The authors defined a novel data-driven workflow for the development of combustion reaction mechanisms and used it to generate a dual-fuel mechanism for Ammonia and Diesel Primary Reference Fuels (DPRF) suitable for efficient combustion simulations in heavy duty engines, with variable cetane number Diesel fuels. A baseline reaction mechanism was created by merging the detailed ammonia mechanism by Glarborg et al. with reaction pathways for n- hexadecane and 2,2,4,4,6,8,8-heptamethylnonane from a well-established multi-component fuel mechanism.

We propose a novel dual-fuel combustion model for simulating heavy-duty engines with the G-Equation. Dual-Fuel combustion strategies in such engines features direct injection of a high-reactivity fuel into a lean, premixed chamber which has a high resistance to autoignition. Distinct combustion modes are present: the DI fuel auto-ignites following chemical ignition delay after spray vaporization and mixing; a reactive front is formed on its surroundings; it develops into a well-structured turbulent flame, which propagates within the premixed charge. Either direct chemistry or the flame-propagation approach (G- Equation), taken alone, do not produce accurate results. The proposed Dual-Fuel model decides what regions of the combustion chamber should be simulated with either approach, according to the local flame state; and acts as a “kernel” model for the G- Equation model. Direct chemistry is run in the regions where a premixed front is not present.

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 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.

Aiming at the fault that the speed signal of the automatic transmission output shaft Hall-type speed sensor fluctuates abnormally due to the change of the air gap, the method of fault detection and diagnosis is proposed. Firstly, a limited low-pass filter module was designed according to the characteristics of the fault, and a good filter effect is achieved. Secondly, by comparing the signals before and after filtering, a residual generator is designed, and an adaptive dynamic threshold is designed by analyzing the causes and influencing factors of the residual, which can configure a reliable and effective threshold for the generated residual in real time, which improves the fault identification robustness and effectiveness. Then, a fault debounce method is designed to avoid frequent false alarms of occasional faults. Finally, simulation verification proves the effectiveness of the method.

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.

Simulation and Optimization of Internal Combustion Engines provides the fundamentals and up-to-date progress in multidimensional simulation and optimization of internal combustion engines. While it is impossible to include all the models in a single book, this book intends to introduce the pioneer and/or the often-used models and the physics behind them providing readers with ready-to-use knowledge. Key issues, useful modeling methodology and techniques, as well as instructive results, are discussed through examples. Readers will understand the fundamentals of these examples and be inspired to explore new ideas and means for better solutions in their studies and work. Topics include combustion basis of IC engines, mathematical descriptions of reactive flow with sprays, engine in-cylinder turbulence, fuel sprays, combustions and pollutant emissions, optimization of direct-injection gasoline engines, and optimization of diesel and alternative fuel engines.

Cast aluminum alloys are used for cylinder heads in internal combustion engines to meet low weight and high strength (lightweight) design requirements. In the combustion chamber, the alloy experiences harsh operating conditions; i.e., temperature variation, constrained thermal expansion, chemical reaction, corrosion, oxidation, and chemical deposition. Under these conditions, thermomechanical fatigue (TMF) damage arises in the form of mechanical damage, environmental (oxidation) damage, and creep damage. In the present work, several important properties that influence the TMF life of the cylinder head have been identified through TMF and finite element analysis (FEA). The results show that improving the strength at high temperatures helps improve TMF life on the exhaust side of the head. On the other hand, improving strength and ductility extend TMF life at low temperature on the intake side.

An engine exhaust manifold undergoes repeated thermal expansion and contraction due to temperature variation. Thermomechanical fatigue (TMF) arises due to the boundary constraints on thermal expansion so that mechanical strain is introduced. Therefore, TMF evaluation is very important in engine design. In this work, the mechanical properties important for TMF assessment and modeling of a silicon (Si)- and molybdenum (Mo)-containing ductile cast iron used for exhaust manifold have been evaluated. Tensile, creep, isothermal low cycle fatigue (LCF), and TMF tests have been conducted. Parameters for material modeling, such as the viscoplastic constitutive model and the Neu-Sehitoglu TMF damage model, have been calibrated, validated, and used to evaluate the TMF life of the exhaust manifold.

Heavy-duty vehicles, currently the second largest source of fuel consumption and carbon emissions are projected to be fastest growing mode in transportation sector in future. There is a clear need to increase fuel efficiency and lower emissions for these engines. The Opposed-Piston Engine (OP Engine) has the potential to address this growing need. In this paper, results are presented for a 9.8L three-cylinder two-stroke OP Engine that shows the potential of achieving 55% brake thermal efficiency (BTE), while simultaneously satisfying emission targets for tail pipe emissions. The two-stroke OP Engines are inherently more cost effective due to less engine parts. The OP Engine architecture presented in this paper can meet this performance without the use of waste heat recovery systems or turbo-compounding and hence is the most cost effective technology to deliver this level of fuel efficiency.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Due to the new challenge of meeting number-based regulations for particulate matter (PM), a numerical and experimental study has been conducted to better understand particulate formation in engines fuelled with compressed natural gas. The study has been conducted on a Heavy-Duty, Euro VI, 4-cylinder, spark ignited engine, with multipoint sequential phased injection and stoichiometric combustion. For the experimental measurements two different instruments were used: a condensation particle counter (CPC) and a fast-response particle size spectrometer (DMS) the latter able also to provide a particle size distribution of the measured particles in the range from 5 to 1000 nm. Experimental measurements in both stationary and transient conditions were carried out. The data using the World Harmonized Transient Cycle (WHTC) were useful to detect which operating conditions lead to high numbers of particles. Then a further transient test was used for a more detailed and deeper analysis.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.

A novel 2-zone combustion chamber concept (patent pending) was developed using multi-dimensional modeling. At minimum volume, an axial projection in the piston divides the volume into distinct zones joined by a communication channel. The projection provides a means to control the mixture formation and combustion phasing within each zone. The novel combustion system was applied to reactivity controlled compression ignition (RCCI) combustion in both light-duty and heavy-duty diesel engines. Results from the study of an 8.8 bar BMEP, 2600 RPM operating condition are presented for the light-duty engine. The results from the heavy-duty engine are at an 18.1 bar BMEP, 1200 RPM operating condition. The effect of several major design features were investigated including the volume split between the inner and outer combustion chamber volumes, the clearance (squish) height, and the top ring land (crevice) volume.

Control of the timing and magnitude of heat release is one of the biggest challenges for premixed compression ignition, especially when attempting to operate at high load. Single-fuel strategies such as partially premixed combustion (PPC) use direct injection of gasoline to stratify equivalence ratio and retard heat release, thereby reducing pressure rise rate and enabling high load operation. However, retarding the heat release also reduces the maximum work extraction, effectively creating a tradeoff between efficiency and noise. Dual-fuel strategies such as reactivity controlled compression ignition (RCCI) use premixed gasoline and direct injection of diesel to stratify both equivalence ratio and fuel reactivity, which allows for greater control over the timing and duration of heat release. This enables combustion phasing closer to top dead center (TDC), which is thermodynamically favorable.