Intelligent perception and control of fuel injection characteristics is a key frontier technology for achieving engine controllable and efficient combustion. To accurately obtain reliable real-time information on fuel injection characteristics, a fuel injection characteristic perception method that integrated variational Bayesian and bidirectional long short-term memory networks (VB-BiLSTM) was proposed. By the collaborative optimization of variational inference and adaptive moment estimation algorithm, the optimal variational approximation of hyperparameter probability density distribution was determined, and the determination of credible interval for fuel injection rate and the precise perception was achieved. The perception performance was evaluated under different levels of noise interference using different typical deep learning models as controls, and online perception verification of fuel injection characteristics was conducted on a test bench. The research results show that the VB-BiLSTM model has significantly better noise resistance performance compared to other models. The experimental data of fuel injection rate are within the 95% credible interval of perceived injection rate, and the maximum error between the perceived and actual value is less than 6%. The end-to-end perception time is on the order of milliseconds.

To address issues such as high soot emissions and short regeneration intervals in crane-specific engines operating at low speed, experiment was combined with chemical kinetics to investigate the effects of different-flow-rate injectors on engine performance and soot emissions, and the formation pathways of PAHs were identified. The results show that the low-flow injectors reduce peak cylinder pressure and peak instantaneous heat release rate and prolong the combustion duration compared to the large-flow fuel injectors. The release of a large amount of heat reduces key PAHs intermediates such as A₂，A₂—，A₃，A₃—and A₂R₅, thereby lowering soot emissions. Additionally, the adoption of low-flow injector not only has a minimal impact on engine performance but also significantly reduces the emissions of soot. Within the operating conditions of cranes, when a low-flow injector is used, as the operating torque increases, the combination of delayed injection timing and lower injection pressure enables the engine to achieve high thermal efficiency and low soot emissions. This is beneficial for enhancing engine fuel economy and reducing costs associated with excessive carbon deposition.

The effects of petrochemical diesel fuels with different physicochemical properties on engine particle emissions were investigated under steady state and transient loading conditions. Regarding ignition performance, as the cetane number increased under low load conditions, the total particle number concentration and accumulation mode particle number concentration initially decreased and then increased slightly, while the nucleation mode particle number concentration continued to rise. Under medium and high load conditions, the number concentrations of both nucleationmode and accumulation mode particles increased gradually. During transient loading processes, the number concentration of total particles first decreased and then stabilized. In terms of evaporation performance, as the aromatic content increased under low load conditions, the number concentrations of nucleation mode and accumulation mode particles first decreased and then remained largely unchanged. Under medium and high load conditions and transient operating conditions, no significant changes were observed in the number concentrations of both types of particles.

In a heavy-duty methanol engine developed to meet China-Ⅵ emission standards, stoichiometric-combustion and lean-combustion strategies were respectively applied to conduct cold-start and hot-start WHTC cycles. The raw exhaust emissions of regulated gaseous pollutants and particulate matter were measured. Results showed that, compared with stoichiometric-combustion, the lean-combustion strategy reduced methanol consumption by approximately 7%. Under both cold-start and hot-start conditions, lean-combustion operation benefits decreasing CO，CH₄，NO_x，NH₃, PM, and PN emissions from the heavy-duty methanol engine. However, lean-combustion operation led to higher unburned methanol and formaldehyde emissions during cold starts, and increased NMHC emissions during hot starts. With the lean-burn strategy, the raw PM and PN emissions of the heavy-duty methanol engine already met the China-Ⅵ limits, whereas NMHC and NO_x remained the primary compliance challenges. These issues can be addressed using an oxidation catalyst (OC) and a selective catalytic reduction (SCR) aftertreatment system, but particular attention should be paid to optimizing the control of unburned methanol and formaldehyde emissions at low exhaust temperatures.

To address the issue of fatigue cracking in engine exhaust manifolds under high and low-temperature loads and to bridge the gap between traditional bench tests and actual user operation, an accelerated test and reliability assessment method were proposed based on a combined analysis of damage modeling and big data. A temperature-driven quantitative damage model for the exhaust manifold was established based on the Coffin-Manson fatigue theory and Miners linear cumulative damage rule. Then a virtual sensor model for estimating the manifold surface temperature was developed. The operational data from vehicle users were collected and extrapolated to determine a target pseudo-damage value covering 95% of user damage levels. And the accelerated thermal shock tests were subsequently conducted on the engine test bench for comparative validation. The results demonstrate that the virtual sensor model achieves a calculation error of less than 5%, meeting engineering application requirements. The accuracy of damage model was verified through both bench tests and vehicle usage data, with predictions indicating that the optimized exhaust manifold could withstand over 600 000 kilometers of service under general user conditions. The proposed damage calculation model provides a reliable basis for the durability assessment and life prediction of engine exhaust manifolds.

In order to establish the correlation between engine lubricating oil and electro-chemical impedance spectroscopy (EIS) and to achieve oil degradation pattern recognition based on electro-chemical response, Mobil 1 FS 0W-30 engine oil was taken as the object. Based on the analysis of the mechanism of lubricating oil degradation, the experimental research was carried out on the electro-chemical response characteristics of typical degradation modes such as oxidation aging, moisture pollution, metal debris pollution, coal activated carbon pollution, fuel pollution and quartz powder pollution. Oil samples with different degradation modes were prepared, and the impedance mode values and phase differences of each degraded oil sample were analyzed through impedance spectrum frequency scanning test. An improved Randles model was used to analyze the impedance spectrum data, and electro-chemical parameters were extracted to characterize the performance state of oil. The research results indicate that the improved Randles model can be used to construct the electro-chemical fingerprints that describe the degradation state of lubricating oil performance. By monitoring the electro-chemical response characteristics, effective identification and differentiation of oil degradation patterns can be achieved, providing a powerful technical means for state based predictive maintenance.

The heat release performance of liquid cooling plate for motor controller was experimentally investigated using subnanometer silver fluid and 50% ethylene glycol-water solution as the coolant. At an inlet temperature of 70 ℃, the temperature difference between the inlet and outlet of liquid cooling plate and the heat source temperature were measured under varying flow rates and heating loads of 2.5 kW, 3.5 kW, 4.5 kW, and 5.5 kW. The heat release efficiency was subsequently analyzed. The results indicated that, at a heating load of 5.5 kW and a mass flow rate of 0.22 kg/s, the liquid cooling plate using subnanometer silver fluid with a mass concentration of 700×10^-6 exhibited 6.28% increase in the inlet-outlet temperature difference, and a 6.8% improvement in heat release efficiency compared to the 50% ethylene glycol-water solution.

For a methanol/diesel dual-fuel engine incorporating a waste heat recovery-coupled methanol gas-assisted injection system, waste heat recovery evaluation metrics were established according to energy flow analysis. These metrics assessed the impacts of gas-assisted pressure and methanol substitution ratio on methanol fuel utilization efficiency. The results indicate that methanol utilization efficiency increases with the rise of gas-assisted pressure at a constant gas-assisted temperature of 80 ℃ and methanol substitution ratio of 40%. Within the 0.1-0.2 MPa gas-assisted pressure range, the exhaust energy increase accompanied by the gas-assisted pressure increase leads to higher heat absorption efficiency of mixture and greater energy absorbed by methanol from the mixture. Consequently, the methanol fuel utilization rate rises from 50.19% to 95.26%. Under test conditions with a gas-assisted temperature of 80 ℃ and a gas-assisted pressure of 0.15 MPa, the methanol fuel utilization rate gradually decreases as the methanol substitution rate increases. The methanol fuel utilization rate is 97.23% when the methanol substitution rate is 10% and decreases to 62.95% when the methanol substitution rate is 50%.

The installing and driving environment model of diesel power unit was built by using vehicle dynamics software, and four road models including paved road, wave-typed road, D-staged road and slope road were established according to application scenes. Based on the established vehicle and road models, the vibration characteristics for diesel power unit under different road conditions were studied. The results show that the vibration peak and frequency band distribution of diesel power unit are influenced at different degrees by different surface characteristic roads. The order of maximum peak for diesel power unit is D-staged road, wave-typed road, slope road and paved road during the velocity-increasing process of starting on four kinds of roads. According to the peak-peak value, the vibration of wave-typed road, D-staged road and slope road are equivalent and the vibration of paved road is the smallest. According to the frequency spectrum, the frequency bands of wave-typed road, D-staged road and slope road are relatively concentrated and that of paved road is approximately even. During the normal driving of vehicle, the vibration of slope road is larger than that of the other three roads.

Based on a 1.5T gasoline direct injection（GDI） hybrid engine with high compression ratio, the effects of engine cooling system design on knock and performance were studied by establishing a computational fluid dynamics（CFD）model and bench test analysis. The system adopted a series cooling mode of cylinder head first and then cylinder block. By optimized design of the cylinder block and cylinder head water jacket, efficient heat exchange was achieved in the exhaust nose bridge area, which could effectively suppress knock. By optimized design of electronic water pumps, EGR coolers and watercooled intercoolers, the system met the cooling requirements under high EGR rates while featuring a compact size and low pressure drop. This resulted in a 0.6% increase in the engine maximum effective thermal efficiency and a 11% increase in maximum net power without enrichment. Furthermore, introducing an additional 5% of EGR gas could boost maximum power by another 8%.

In order to improve the performance of a new designed diesel engine, a simulation model of in-cylinder combustion was set up to study the effects of combustion chamber and injector nozzle parameters on combustion performance. Then a prototype of engine was built and tested according to the simulation results. The simulation results show that nozzle protrusion and spray include angle have a significantly greater impact on fuel consumption and soot emissions under the rated operating conditions than under the maximum thermal efficiency conditions. A 9.09% change in injector flow rate has a negligible effect on fuel consumption and soot emissions under the maximum thermal efficiency operating conditions, but increasing the flow rate is more effective in controlling the high-temperature thermal load on the cylinder block under the rated operating conditions. Among the three schemes of V01-V03, V01 scheme achieves the greatest reduction in high-pressure cycle indicated specific fuel consumption (HPISFC) with reaching 4.70% and soot emissions by 29.72% under the maximum thermal efficiency operating conditions, while the reductions in HPISFC and soot emissions under the rated operating conditions were the smallest. V02 scheme shows the smallest reduction by 4.23% in HPISFC under the maximum thermal efficiency operating conditions, but the largest reductions in HPISFC and soot emissions under the rated operating conditions. The test results of V01 scheme indicate that the effective specific fuel consumption reduces by 4.10% and the soot emissions reduce by 30.23% under the maximum thermal efficiency operating conditions, which is consistent with the simulation results regarding the expected reductions in HPISFC and soot emissions.

In order to realize the collaborative optimization of braking energy recovery efficiency and driving stability of distributed drive electric vehicles, a composite braking hierarchical control strategy integrating an anti-lock braking system (ABS) coordination mechanism was proposed. The strategy adopted the upper and lower double-layer optimization architecture. The upper layer utilized a variable-ratio braking force distribution strategy to make the actual distribution curve approximate the ideal braking force distribution curve, thereby maximizing tire-road adhesion utilization. The lower layer consisted of a dynamic coordination control mechanism for electric and hydraulic braking based on slip rate, achieving precise coordination between ABS system and regenerative braking while ensuring braking stability. Then the particle swarm optimization algorithm was introduced to optimize the membership function of fuzzy controller offline, and the regenerative braking force distribution coefficient was dynamically optimized with battery state of charge (SOC), braking strength and vehicle speed as input variables, so as to further improve the energy recovery efficiency under complex working conditions. Based on Matlab/Simulink simulation verification, the optimized SOC contribution rates under NEDC and FTP75 conditions were 17.81% and 18.53% respectively. The energy recovery rate of low adhesion road surface was 52%, and that of μ-split surface was 23.9%. The analysis results show that the strategy can effectively improve the braking stability and energy recovery rate.

For the problem of braking energy recovery control in pure electric vehicles, a motor drive force control strategy was proposed. This strategy reasonably distributed the mechanical braking force of front axle and the electric braking force, which realized the dynamic optimization for the proportion of electric braking force on the front axle through the ANFIS controller and balanced the braking stability and energy recovery efficiency by introducing the pruning algorithm to reduce the computational complexity. The control algorithm was verified through joint simulation. The results show that the strategy maintains good stability under different braking intensities. Under the NEDC driving condition, the strategy achieves a SOC increase by 0.46% compared with the ANFIS control strategy and 1.81% compared with the AVL Cruise control. Meanwhile, the motor torque fluctuation is effectively suppressed. Hardware-in-the-loop (HIL) testing results demonstrate that the improved ANFIS control strategy performs excellently in terms of effectiveness and real-time performance.