Search Results

Ultra-lean combustion of GDI engine could achieve higher thermal efficiency and lower NOx emissions, but it also faces challenges such as ignition difficulties and low-speed flame propagation. In this paper, the sparked-spray is proposed as a novel ignition method, which employs the spark to ignite the fuel spray by the cooperative timing control of in-cylinder fuel injection and spark ignition and form a jet flame. Then the jet flame fronts propagate in the ultra-lean premixed mixture in the cylinder. This combustion mode is named Sparked-Spray Induced Combustion (SSIC) in this paper. Based on a 3-cylinder 1.0L GDI engine, a 3D simulation model is established in the CONVERGE to study the effects of ignition strategy, compression ratio, and injection timing on SSIC with a global equivalence ratio of 0.50. The results show it is easier to form the jet flame when sparking at the spray front because the fuel has better atomization and lower turbulent kinetic energy at the spray front.

As one of the pollutants that cannot be ignored, soot has a great impact on human health, environment, and energy conversion. In this investigation, the effect of residence time (25ms, 35ms, and 45ms) and ammonia on morphology and nanostructure of soot in laminar ethylene flames has been studied under atmospheric conditions and different flame heights (15 mm and 30 mm). The transmission electron microscopy (TEM) and high-resolution transmission electron microscope (HRTEM) are used to obtain morphology of aggregates and nanostructure of primary particles, respectively. In addition, to analyze the nanostructure of the particles, an analysis program is built based on MATLAB software, which is able to obtain the fringe separation distance, fringe length, and fringe tortuosity parameters of primary particles, and has been verified by the multilayer graphene interlayer distance.

In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement. The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution.

The passive pre-chamber (PC) is valued for its jet ignition (JI) and is suitable for wide use in the field of gasoline direct injection (GDI) for small passenger cars, which can improve the performance of lean combustion. However, the intake, exhaust, and ignition combustion stability of the engine at low speed is a shortcoming that has not been overcome. Changing the structural design to increase the fluidity of the main chamber (MC) and pre-chamber (PC) may reduce jet ignition performance, affecting engine dynamics. This investigation is based on non-uniformly nozzles distributed passive pre-chamber, which is adjusted according to the working medium exchange between PC and MC. The advantages and disadvantages of the ignition mode of PC and SI in the target engine speed range are compared through optical experiments on a small single-cylinder GDI engine.

As a novel ignition technology, pre-chamber ignition can enhance ignition energy, promote flame propagation, and augment turbulence. However, this technology undoubtedly faces challenges, particularly in the context of emission regulations. Of this study, the transient characteristics of combustion and emissions in a hybrid electric vehicle (HEV) gasoline engine with active pre-chamber ignition (PCI) under the first combustion cycle of quick start are focused. The results demonstrate that the PCI engine is available on the first cycle for lean combustion, such as lambda 1.6 to 2.0, and exhibit particle number (PN) below 7×107 N/mL at the first cycle. These particles are predominantly composed of nucleation mode (NM, <50 nm) particles, with minimal accumulation mode (AM, >50 nm) particles.

Argon Power Cycle (APC) is an innovative future potential power system for high efficiency and zero emissions, which employs an Ar-O2 mixture rather than air as the working substance. However, APC hydrogen engines face the challenge of knock suppression. Compared to hydrogen, methane has a better anti-knock capacity and thus is an excellent potential fuel for APC engines. In previous studies, the methane is injected into the intake port. Nevertheless, for lean combustion, the stratified in-cylinder mixture formed by methane direct injection has superior combustion performances. Therefore, based on a methane direct injection engine at compression ratio = 9.6 and 1000 r/min, this study experimentally investigates the effects of replacing air by an Ar-O2 mixture (79%Ar+21%O2) on thermal efficiencies, loads, and other combustion characteristics under different excess oxygen ratios. Meanwhile, the influences of varying the methane injection timing are studied.

Hydrogen energy is a kind of secondary energy with an abundant source, wide application, green, and is low-carbon, which is important for building a clean, low-carbon, safe, and efficient energy system and achieving the goal of carbon peaking and being carbon neutral. In this paper, the effect of nozzle position, hydrogen injection timing, and ignition timing on the in-cylinder combustion characteristics is investigated separately with the 13E hydrogen engine as the simulation object. The test results show that when the nozzle position is set in the middle of the intake and exhaust tracts (L2 and L3), the peak in-cylinder pressure is slightly higher than that of L1, but when the nozzle position is L2, the cylinder pressure curve is the smoothest, the peak exothermic rate is the lowest, and the peak cylinder temperature is the lowest.

The Chinese government and industries have proposed strategic plans and policies for automotive renewable-energy transformation in response to China’s commitments to peak the national carbon emissions before 2030 and to achieve carbon neutrality by 2060. We thus analyze the evolution of carbon emissions from the vehicle fleet in China with our data-driven models based on these plans. Our results indicate that the vehicle life-cycle carbon emissions are appreciable, accounting for 8.9% of the national total and 11.3% of energy combustion in 2020. Commercial vehicles are the primary source of automotive carbon emissions, accounting for about 60% of the vehicle energy cycle. Among these, heavy-duty trucks are the most important, producing 38.99% of the total carbon emissions in the vehicle operation stage in 2020 and 52.18% in 2035.

Reinforcement learning is a promising approach to solve the energy management for hybrid electric vehicles. In this paper, based on the DQN (Deep Q-Network) reinforcement learning algorithm which is widely used at present, double DQN, dueling DQN and learning from demonstration are integrated; states, actions, rewards and the experience pool based on the characteristics of series-parallel multi-speed hybrid powertrain are designed; the hybrid energy management strategy based on D4QN (Double Dueling Deep Q-Network with Demonstrations) algorithm is established. Based on the training results of D4QN algorithm, multi-parameter analysis under state and action space, HCU (Hybrid control unit) application and MIL (Model in-loop) test research are conducted.

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.

SEAT Department of SAIC Motor Vehicle Company starts innovatively applying the single motor and P2.5 configuration scheme from EDU G2(Electric Drive Unit Generation 2), which consists of six engine gears and four motor gears. EDU G2 is very compact and adaptable through the coupling design. Gear coupling make the engine and motor coordination limited, so as to the high efficiency zone of the engine and the high efficiency zone of the motor cannot match in some working conditions, which affect the performance of the vehicle. Therefore, SEAT developed the second generation of single-motor plug-in hybrid system EDU G2 Plus EDU G2(Electric Drive Unit Generation 2 Plus), which realized the decoupling design of 5 engine gears and 2 motor gears, so that the power output of engine and motor is freely. With excellent power and economic performance, the vehicle has been well received by customers.

Combustion diagnostics of highly diluted mixtures are essential for the estimation of the combustion quality, and control of combustion timing in advanced combustion systems. In this paper, a novel fast response flame detection technique based on active plasma is introduced and investigated. Different from the conventional ion current sensing used in internal combustion engines, a separate electrode gap is used in the detecting probing. Further, the detecting voltage across the electrode gap is modulated actively using a multi-coil system to be slightly below the breakdown threshold before flame arrival. Once the flame front arrives at the probe, the ions on the flame front tend to decrease the breakdown voltage threshold and trigger a breakdown event. Simultaneous electrical and optical measurements are employed to investigate the flame detecting efficacy via active plasma probing under both quiescent and flow conditions.

As a prerequisite for energy management of hybrid vehicles, the results of speed prediction can optimize the performance of vehicles and improve fuel efficiency. Energy management strategies are usually developed based on standard driving cycles, which are too generalized to show the variability of driving conditions in different time and locations. Therefore, this paper constructs a representative driving cycle based on driving data of the corresponding time and location, used as historical information for prediction. We propose a method to construct the driving cycle based on Markov chain theory before constructing the prediction model. In this paper, multiple prediction methods are compared with traditional parametric methods. The difference in prediction accuracy between multiple prediction methods under the single time scale and multiple time scale were compared, which further verified the advantages of the speed prediction method based on Markov chain theory.

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.

As the international community strengthens the control of carbon dioxide emissions, electric vehicles have gradually become a substitute for internal combustion engine vehicles. The battery pack is one of the most important components of electric vehicles. The strength and fatigue performance of the battery support plate not only affect the performance of the vehicle but also concern the safety of the driver. In the present study, the finite element model of a battery pack for fatigue analysis is completely established. The random vibration stress response analysis and acceleration power spectral density response analysis of the support plate for the battery pack are carried out, and the accuracy of the finite element model is verified by a random vibration test.

Ethanol reforming gas combined with EGR technology can not only improve thermal efficiency, but also reduce pollutant emission under lean combustion condition. In this investigation, GT-Power is used to carry out one-dimensional simulation model calculation and analysis to explore the combustion characteristics, economy performance of a direct injection gasoline engine when the excess air coefficient (λ) increases from 1 to 1.3 and the ethanol reforming gas mixing ratio increases from 0% to 30% at the working condition of 2000 r/min and 10 bar. Then the EGR system is introduced to deeply discuss the working characteristics of the direct injection gasoline engine when the EGR rate increases from 0% to 20%. The results show that the increase of λ leads to the decrease of in-cylinder pressure and the delay of the peak of cylinder pressure.

In the ultra-lean combustion mode, the combustion temperature is relatively low, which is expected to avoid the high-temperature NOx generation. And it also can use excess air to fully oxidize CO, HC and Soot, to achieve cleaner combustion. But at the same time, ultra-lean combustion has difficulties in ignition and flame propagation. This paper used CONVERGE to simulate the combustion process and products of a new ultra-lean combustion mode, which ignited the ultra-lean premixed fuel/air mixture with the spark-ignited micro-fuel-jet, in a constant-volume vessel with a 6-hole GDI injector. The differences of combustion processes and products were simulated for two spark-ignition positions, including ‘on’ the micro-jet spray and ‘between’ two micro-jet sprays. It was found that the combustion duration (the time for burned-fuel-ratio from 10% to 90%) could be shortened by about 14.3% if igniting ‘on’ the micro-jet spray, but the amount of NOx generated would increase about 21.0%.

Hydrous ethanol not only has the advantages of high-octane number and valuable oxygen content, but also reduce the energy consumption in the production process. However, little literature investigated the internal flow and cavitation of hydrous ethanol-gasoline fuels in the multi-hole direct injector. In this simulation, a two-phase fuel flow model in injector is established based on the multi-fluid model of Euler-Euler method, and the accuracy of model is verified. On the basis of this model, the flow of different hydrous ethanol-gasoline blends is calculated under different injection conditions, and the cavitation, flow rate, and velocity at the outlet of the nozzle are predicted. Meanwhile, the influence of temperature and back pressure on the flow is also analyzed. The results show that the use of hydrous ethanol reduces the flow rate, compared with the velocity of E0, that of E10w, E20w, E50w, E85w, and E100w decreases by 10%, 12.9%, 17.6%, 20%, and 23.5%, respectively.

As an excellent nanoscale material, carbon nanotubes (CNTs) play a very important role in improving the batteries of new energy vehicles. The micro-scale combustion flame synthesis method is a promising method for preparing carbon nanotubes. To explore the optimal growth condition of carbon nanotubes under micro-scale combustion, the detailed mechanism of methanol C3 (114 species, 1999 reactions) was reduced based on whole-species sensitivity analysis, then a suitable model of methanol combustion was established by using Fluent software coupling with simplified mechanism (16 species, 65 reactions) of methanol. The model was used for the numerical simulation of micro-scale coaxial diffusion combustion of methanol, and then it was verified by the experimental results of micro-scale combustion of methanol.

The Argon Power Cycle engine is a novel concept for high efficiency and zero emission through the replacement of N2 by Ar. However, the higher in-cylinder temperature and pressure as by-products cause heavier knock. The anti-knock strategies, such as reducing compression ratio and retarding ignition time, offset the efficiency increased by the Argon Power Cycle. Therefore, knock control becomes the most urgent task for the Argon Power Cycle engine development. The anti-knock methods, including fuel replacement, ultra-lean combustion, high dilution combustion, and water injection, were considered. The simulated ignition delay times were used to evaluate the probability of knock. The Otto cycle, combined with chemical equilibrium, was utilized to confirm the effect on the thermal conversion efficiency and each in-cylinder thermodynamic state parameter. The results show that the ignition delay times increase by a factor of two when the Ar dilution ratio increases from 79% to 95%.