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Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

It’s well known that startup process of proton exchange membrane fuel cells (PEMFCs) under subzero temperature is extremely significant because of its influence on fuel cell performance and durability. In the study, a quasi-2D numerical model is developed and dynamic equations of mass conservation, energy conservation, membrane water conservation, ice conservation, species conservation are all considered. Three different hydrogen supply modes are studied in detail: flow-through anode (FTA) mode, dead-ended anode (DEA) mode and off-gas recirculation (OR) mode. It is found that the local current density (LCD) and temperature distribution vary remarkably along flow channel in OR mode as t > 500s due to nitrogen crossover and accumulation. During the cold start operation, the DEA mode and OR mode hold more water in anode catalyst layer (ACL) which reduces the effects of hydraulic permeation, resulting in more ice formation in cathode catalyst layer (CCL) and slower temperature rising.

A new two-dimensional wall-flow DPF microstructure model has been developed in this paper to investigate the particle deposition distribution in DPF channels and the deep-bed filtration process of DPF. The substrate wall of the DPF having a thickness of L is divided into several layers with a uniform thickness of Δy along the cross-wall direction, and each layer has specific porosity and pore size. The pressure drop, particle deposition distribution and the dynamic deep-bed filtration process of the DPF with inhomogeneous wall structure are studied under various space velocities. Besides, the differences on DPF’s performance brought by the inhomogeneous wall structure are discussed by comparing with a homogeneous wall structure.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.

P2 hybrid electric vehicle is the single-motor parallel configuration integrating with an engine disconnect clutch (EDC) between the engine and the motor. The key point with P2 hybrid electric vehicle is to start the engine utilizing the single driving motor while still propelling the vehicle, which requires an appropriate engine-start control strategy and a high mechanical performance of EDC. Since the space for EDC is limited, EDC torque response is difficult to follow the torque command, which complicates the issue of precisely controlling the clutch. Consequently, methods proposed in massive papers are inappropriate for current EDC of target vehicle. Considering that slip control of shifting clutch also contributes to reducing impact of engine start assisted by EDC, a detailed engine-start control strategy was proposed to simplify the control of EDC for being applied to actual target vehicle.

In decade years, Spark Ignition-Controlled Auto Ignition (SI-CAI) hybrid combustion, also called Spark Assisted Compression Ignition (SACI) has shown its high-efficiency and low emissions advantages. However, high dilution causes the problem of unstable initial ignition and flame propagation, which leads to high cyclic variation of heat release and IMEP. The instability of SI-CAI hybrid combustion limits its dilution degree and its ability to improve the thermal efficiency. In order to solve instability problems and expand the dilution boundary of hybrid combustion, micro flame ignition (MFI) strategy is applied in gasoline hybrid combustion engines. Small amount of Dimethyl Ether (DME) chosen as the ignition fuel is injected into cylinder to form micro flame kernel, which can stabilize the ignition combustion process.

Modeling techniques matter a lot in many fields of engine engineering. Models are requested not only for control design but also for dynamic prediction. However, problems might be encountered during modeling process either because of the system complexity or the unaffordable modeling cost. As a result, a new modeling technique based on disturbance estimation is proposed in this paper. By employing the proposed modeling technique, models are set up in real time with the online information from input and output. The uncertainties of system dynamics are handled as internal disturbance of the system, while the perturbation from outside are taken as the external disturbance, and the combination of the two can be estimated online by a kind of active observer called extended state observer (ESO).

During the aero-engine operation, the compressor blades are subjected to periodic inertial force and aerodynamic excitation caused by blade rotation and airflow disturbance, respectively. Under the coupling alternating loads, the blade is prone to high cycle fatigue failure. In this paper, a time domain calculation model of fluid-structure interaction (FSI) is established to study the vibration characteristics of the blade and its failure modes are analyzed. Then, the fatigue damage of the blade under multi-level loading is evaluated by the nonlinear damage accumulation model. Considering the coupling effect of the airflow and the blade, computational fluid dynamics (CFD) is applied to calculate the aerodynamic parameters on the blade surface under different working conditions, which is imported to the finite element (FE) model to analyze the dynamic characteristics.

Strategies to suppress knock have been extensively investigated to pursue thermal efficiency limits in downsized engines with a direct-injection spark ignition. Comprehensive considerations were given in this work, including the effects of second injection timing and injector location on knock combustion in a downsized gasoline engine by large eddy simulation. The turbulent flame propagation is determined by an improved G-equation turbulent combustion model, and the detailed chemistry mechanism of a primary reference fuel is employed to observe the detailed reaction process in the end-gas auto-ignition process. The conclusions were obtained by comparing the data to the baseline single-injection case with moderate knock intensity. Results reveal that for both arrangements of injectors, turbulence intensity is improved as the injecting timing is retarded, increasing the flame propagation speed.

The purpose of this study is to investigate the effect of intake air hydrogenation coupled with intake air humidification (IAH) on the combustion and emission of marine diesel engines. A 3D numerical model of four-stroke turbocharged intercooled marine diesel engine was established by using commercial software AVL-Fire. The effects of hydrogen and water injected into the intake port on engine in-cylinder combustion and emission characteristics at 1350 r/min and partial load were studied. The novelty of this study is to combine different hydrogen-fuel ratios and water-fuel ratios, so as to find the optimization method that can reduce NOx and soot emissions and ensure the thermal efficiency of the engine doesn’t decrease.

Although turbulence plays a critical role in engines operated within low temperature combustion (LTC) regime, its interaction with chemistry on auto-ignition at low-ambient-temperature and lean-oxygen conditions remains inadequately understood. Therefore, it is worthwhile taking turbulence-chemistry interaction (TCI) into consideration in LTC engine simulation by employing advanced combustion models. In the present study, large eddy simulation (LES) coupled with linear eddy model (LEM) is performed to simulate the ignition process in n-heptane spray under engine-relevant conditions, known as Spray H. With LES, more details about unsteady spray flame could be captured compared to Reynolds-averaged Navier-Stokes equations (RANS). With LEM approach, both scalar fluctuation and turbulent mixing on sub-grid level are captured, accounting for the TCI. A skeletal mechanism is adopted in this numerical simulation, including 41 species and 124 reactions.

Clean combustion is critical for marine engines to meet the Tier III emission regulation. In this paper, the effects of EGR and injection strategies (including injection pressure, injection timing as well as multiple injection technology) on the performance and emissions of a 2-stroke, low speed marine diesel engine were investigated by using computational fluid dynamics (CFD) simulations to reach the IMO Tier III NOx emissions target and reduce the fuel consumption rate. Due to the large length scale of the marine engine, RANS simulation was performed in combination with the CTC-SHELL combustion model. Based on the simulation model, the variation of the cylinder pressure curve, the average temperature in the cylinder, the combustion heat release rate and the emission characteristics were studied.

Turbulent jet ignition (TJI) has the advantages of improving burning rates and expanding lean burn limitations of gasoline engines. Based on a single cylinder engine, combustion process with different ignition methods, including single spark ignition, twin spark ignition, one-hole TJI and seven-hole TJI, are studied in this work. Experiments are carried out under conditions with different air/fuel equivalence ratios and different engine loads. Results show that the cycle-to-cycle variations of TJI combustion, which is evaluated by coefficient of variations (CoV) of IMEP and CoV of peak pressure, are obviously reduced due to the fast burning rate induced by the jet flame, and one-hole TJI combustion has the best combustion stability, especially for reducing the CoV of peak pressure.

Chinese new legislations on two wheels and mopeds have been published recently. Depending on the latest exhaust statistic analyses, with the resulting of tighter limits, the application of catalytic converters is becoming a prevalent and a cost-efficient solution for Chinese motorcycle manufacturers. The phenomenon of exhaust temperature changes rapidly during real driving process is well known as one of major destructive factors which have effects upon converter's durability. One 125 cm3 motorcycle is selected as a typical model in this research project. Exhaust temperature of the 125 cm3 motorcycle is measured and recorded during the process of ECE 40 driving cycle. A simulation test system has been set up successfully depending on those temperature data. Conversion ratio of converter sample lost distinctly after 18 hours' thermal impact tests. After further analyses, there were not evident changes in microstructure and substance on the surface of converter.

Combustion cycle-to-cycle variation (CCV) of Spark-Ignition (SI) engines can be influenced by the cyclic variations in charge motion, trapped mass and mixture composition inside the cylinder. A high CCV leads to misfire or knock, limiting the engine’s operating regime. To understand the mechanism of the effect of flow field and mixture compositions on CCV, the present numerical work was performed in a single cylinder Direct Injection Spark-Ignition (DISI) engine. A large eddy simulation (LES) approach coupled with the G-equation combustion model was developed to capture the CCV by accurately resolving the turbulent flow field spatially and temporally. Further, the ignition process was modeled by sourcing energy during the breakdown and arc phases with a line-shape ignition model which could move with the local flow. Detailed chemistry was solved both inside and outside the flame front. A compact 48-species 152-reactions primary reference fuel (PRF) reduced mechanism was used.

Most of algorithms of lane detection mainly aim at the scenes of daytime. However, those algorithms are unstable for the lane detection at night because the camera is very sensitive to the light change. This paper proposed a lane detection algorithm that largely improves the detection system’s performance when it is used at night. The algorithm has two main stage: Image processing and Kalman filter (KF). The key process steps of Stage 1 are: extracting the Region of Interesting (ROI)→Edge Detection →Binarization→Hough→ Lane Selection→Lane fitting. First step, a ROI could be extracted according to the relatively fixed location of lanes. In step of edge detection, we use a creative filter named Correlation filter to remove image noise and remain the feature of lane. The filter matrix looks like “[0 1 1, −1 0 1; −1 −1 0]”. Next, the candidate lines are detected by the Hough transform, then, the equations of lane are acquired by fitting spots obtained from Hough.

Nowadays, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA).

As a critical power source, the diesel engine is widely used in various situations. Diesel engine failure may lead to serious property losses and even accidents. Fault detection can improve the safety of diesel engines and reduce economic loss. Surface vibration signal is often used in non-disassembly fault diagnosis because of its convenient measurement and stability. This paper proposed a novel method for engine fault detection based on vibration signals using variational mode decomposition (VMD), K-means, and genetic algorithm. The mode number of VMD dramatically affects the accuracy of extracting signal components. Therefore, a method based on spectral energy distribution is proposed to determine the parameter, and the quadratic penalty term is optimized according to SNR. The results show that the optimized VMD can adaptively extract the vibration signal components of the diesel engine. In the actual fault diagnosis case, it is difficult to obtain the data with labels.

The scavenging process in two-stroke marine engines not only transports burnt gas out of the cylinder but also provides fresh air for the next cycle, thereby significantly affecting the engine performance. In order to enhance fuel-air mixing, the scavenging process usually generates swirling flow in uniflow-type scavenging engines. The scavenging stability directly determines the scavenging efficiency and even influences fuel-air mixing, combustion, and emission of the engine. In the present study, a computational fluid dynamics (CFD) analysis of the scavenging process in a steady-state scavenging flow test is conducted. A precession phenomenon is found in the high swirl model, and Proper Orthogonal Decomposition (POD) method is used to analyze the reason and the multi-scale characteristics of the precession phenomenon.