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The absence of combustion information continues to be one of the key obstacles to the intelligent development of engines. Currently, the cost of integrating cylinder pressure sensors remains too high, prompting attention to methods for extracting combustion information from existing sensing data. Mean-value combustion models for engines are unable to capture changes of combustion parameters. Furthermore, the methods of reconstructing combustion information using sensor signals mainly depend on the working state of the sensors, and the reliability of reconstructed values is directly influenced by sensor malfunctions. Due to the concentration of operating conditions of hybrid vehicles, the reliability of priori calibration map has increased. Therefore, a combustion information reconstruction method based on priori calibration information and the fused feature deviations of existing sensing signals is proposed and named the "Deviation-based Centroid Displacement Method" (DCDM).

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.

Hybrid powertrain has been proven to be an effective fuel-saving technology in commercial vehicles, but many hybrid commercial vehicles still use conventional diesel engines, resulting in limited fuel savings. The main purpose of this study is to enhance the thermal efficiency of a dedicated hybrid diesel engine focusing on the characteristic operating conditions. Via fundamental thermodynamics process analysis of internal combustion engine, steel piston with high compression ratio, air system involving two-stage turbocharger(2TC) with an intercooler, and late intake valve closing(IVC) timing are proposed to improve the thermal efficiency of the engine. Experimental results show that high compression ratio and lower thermal conductivity of the combustion chamber surface lead to lower heat release rates, requiring optimization of piston profile to accelerate the mixing rate. Besides, high compression ratio also leads to higher mechanical losses.

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.

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.

Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.

In this study, a new system of assessment method was developed to evaluate the characteristics of urban buses based on remote online monitoring. Four types of buses, including China V emission standards diesel bus, lean-burn CNG bus, air-fuel equivalence ratio combustion CNG bus and gas-electric hybrid bus, were chosen as samples to analyze the emission characteristics of urban buses with different engine types in urban scenario. Based on the traffic conditions in Beijing, the actual emission characteristics of buses under newly-built driving conditions were analyzed. Moreover, the emission factor database of urban buses in Beijing was established to analyze the characteristics of excess emission. The research results are shown as follows. 1) Compared with other types of buses, NOX emission factor and emission rate of lean-burn CNG bus are much higher.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

As a major power source, diesel engines are being widely used in a variety of fields. However, because of complex structure, some faults which cannot be detected by direct signals would occur on engines and even lead to accidents. Among all kinds of indirect signals, vibration signal is the most common choice for faults detection without disassemble because of its convenience and stability. This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN). Since the quadratic penalty has a great influence on adaptable VMD that may make expected component signals cannot be extracted exactly, this paper proposed a dynamic quadratic penalty value, which will change with decomposing level. This paper selected a best dynamic quadratic penalty value by analyzing a large amount of data and results showed that this approach can decompose signals more exactly.

Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.

OH, soot and temperature distributions of wall-impinging diesel fuel spray were investigated in a high-temperature high-pressure constant volume combustion vessel. The ambient temperature (Ta) was set as 773 K, and the wall temperature (Tw) was set as 523 K, 673 K, 773 K, respectively. Three different injection pressures (Pi) of 60 MPa, 100 MPa, 160 MPa, and the ambient pressures (Pa) of 4 MPa were applied. The OH spatial distributions of wall-impinging spray were measured by the method of OH chemiluminescence imaging. Two-color pyrometry was applied to evaluate the spatial distributions of KL factor and flame temperature of wall-impinging spray. The results reveal that, OH chemiluminescence is observed in the region near the impingement point firstly. The regions of high OH chemiluminescence intensity and high KL factor appear in the location near the wall surface along the whole combustion process.

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.

Nowadays the strong knocking combustion involving destructive pressure wave or shock wave has become the main bottleneck for highly boosted engines when pursuing high thermal efficiency. However, its fundamental mechanism is still not fully understood. In this study, synchronization measurements through simultaneous pressure acquisition and high-speed direct photography were performed to comparatively investigate the strong knocking combustion of iso-octane and propane in a rapid compression machine with flat piston design. The pressure characteristics and visualized images of autoignition and reaction wave propagation were compared, and the correlations between thermodynamic trajectories and mixture reactivity progress were analyzed. The results show that iso-octane behaves a greater propensity to strong knocking combustion than propane at similar target pressures.

Liquefied natural gas (LNG) engine could provide both reduced operating cost and reduction of greenhouse gas (GHG) emissions. Stoichiometric operation with EGR and the three-way catalyst has become a potential approach for commercial LNG engines to meet the Euro VI emissions legislation. In the current study, numerical investigations on the knocking tendency of several combustion chambers with different geometries and corresponding performances were conducted using CONVERGE CFD code with G-equation flame propagation model coupled with a reduced natural gas chemical kinetic mechanism. The results showed that the CFD modeling approach could predict the knock phenomenon in LNG engines reasonably well under different thermodynamic and flow field conditions.

Proton exchange membrane (PEM) fuel cell is widely recognized as an outstanding portable power plant and expected to be possibly commercialization in the near future. As is well known, mechanical stresses implemented on the bipolar plates during the assembly procedure should have prominent influences on mass and heat transfer behavior inside the cell, as well as the resultant performance. In this study, an analytical model is proposed to comprehensively investigate the influence of clamping force on the mass transport, electrochemical properties and overall cell output capability of a PEM fuel cell. The results indicate that proper clamping force not only benefits the gas leakage prevention but also increases the contact area between the neighboring components to decrease the contact ohmic resistance.

In order to achieve high-efficiency and clean combustion in HCCI engines, combustion must be controlled reasonably. A great variety of species with various reactivities can be produced through low temperature oxidation of fuels, which offers possible solutions to the problem of controlling in-cylinder mixture reactivity to accommodate changes in the operating conditions. In this work, in-cylinder combustion characteristics with low temperature reforming (LTR) were investigated in an optical engine fueled with low octane number fuel. LTR was achieved through low temperature oxidation of fuels in a reformer (flow reactor), and then LTR products (oxidation products) were fed into the engine to alter the charge reactivity. Primary Reference Fuels (blended fuel of n-heptane and iso-octane, PRFs) are often used to investigate the effects of octane number on combustion characteristics in engines.

Methane as an attractive alternative fuel offers the most potential in clean combustion and low CO2 emissions. In this work, combustion characteristics of methane/gasoline dual-fuel were investigated in a spark-ignited engine with port-injection of methane and direct-injection of gasoline, allowing for variations in methane addition and excess air coefficient. Engine experimental results showed that under low load conditions, as methane mass rate was raised, there was a promotion in methane/gasoline dual-fuel combustion, and this became more obvious at lean conditions. Similar observations were also obtained when the engine was operated at intermediate load conditions, but a prolonged combustion duration was found with the methane addition. Further analysis showed that the promotion of methane/gasoline dual-fuel combustion with methane addition mainly occurred in the early stage of combustion, especially for lean conditions.

High-pressure common rail (HPCR) fuel injection system is the most widely used fuel system in diesel engines. However, when multiple injection strategy is used, the pressure wave fluctuation is un-avoided due to the opening and closing of the needle valve which will affect the subsequent fuel injection and combustion characteristics. In this paper, several parameters: injection pressure, injection intervals, the main injection pulse widths are investigated on a common rail fuel injection test rig with two injection pulses to explore their effect on the fuel injection rate and fuel quantity. The result showed that the longer injection interval between the pilot and main injections will lead to a rail pressure drop at the beginning of the main injection so that a smaller fuel quantity will be delivered. The main injection pulse width also influences fuel injection rate and the main fuel quantity.

Wall temperature in GDI engine is influenced by both water jacket and gas heat source. In turn, wall temperature affects evaporation and mixing characteristics of impingement spray as well as combustion process and emissions. Therefore, in order to accurately simulate combustion process, accurate wall temperature is essential, which can be obtained by conjugate heat transfer (CHT) and piston heat transfer (PHT) models based on mapping combustion results. This CHT model considers temporal interaction between solid parts and cooling water. This paper presents an integrated methodology to reliably predict in-cylinder combustion process and temperature field of a 2.0L GDI engine which includes engine head/block/gasket and water jacket components. A two-way coupling numerical procedure on the basis of this integrated methodology is as follows.

The evolution of surface functional groups (SFGs) and the graphitization degree of soot generated in premixed methane flames are studied and the correlation between them is discussed. Test soot samples were obtained from an optimized thermophoretic sampling system and probe sampling system. The SFGs of soot were determined by Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) after removing the soluble impurities from the soot samples, while the graphitization degree of soot was characterized by Raman spectrum and electron energy loss spectroscopy (EELS). The results reveal that the number of aliphatic C-H groups and C=O groups shows an initial increase and then decrease in the sooting history. The large amount of aliphatic C-H groups and small amount of aromatic C-H groups in the early stage of the soot mass growth process indicate that aliphatic C-H groups make a major contribution to the early stage of soot mass growth.