For the digitization of turbocharger, the prediction of compressor working state is essential. How to build a model with accurate prediction and less time-consuming is the premise of studying the digitization of turbochargers. As the relationship between compressor parameters is obtained through experiments, it cannot be expressed by simple functional equations, so the surrogate model is often used for fitting the curve. Five surrogate models, the Kriging model, Response Surface Methodology, Artificial Neural Networks, Radial Basis Function, and Support vector machines, were used to fit and regression compressor characteristic curves. And four optimization algorithms, Particle Swarm Optimization, Genetic Algorithm, Gray Wolf algorithm, and Firefly Algorithm, were used to optimize the model. A method to construct a hybrid surrogate model is proposed. The results show that the influencing factors of the modeling pressure ratio and efficiency at all speed groups were confirmed; Different optimization algorithms have different optimization degrees for the five surrogate models; The prediction accuracy of the hybrid surrogate model is better than the optimized model and the single model. The constructed model can be applied in the digital twins system to predict the working state of the compressor in time to achieve the purpose of rapid response.

To improve the problem of high NOx emissions in ammonia/methanol engines, this article explores the impact of different EGR rates on engine performance under three different ammonia/methanol mixing ratios through simulation research. The research results indicate that when the proportion of methanol in ammonia fuel is small, the power and economy of the engine significantly decrease after increasing the EGR rate, and the density of unburned ammonia and N2O in the waste gas grows markedly. When the proportion of methanol in ammonia fuel is high, the decrease in engine power is relatively small after growing the EGR rate, and the density of unburned ammonia and N2O in the waste gas modestly grows. The introduction of EGR rate will reduce the overall performance of the engine, but the effect of reducing NOx emissions is very significant. By increasing the proportion of methanol in ammonia fuel, the adverse effects of EGR technology can be reduced. A60/M40/EGR12 % is the optimal combination of ammonia/methanol mixture ratio and EGR rate in this study. In previous studies, the combustion modes of ammonia/hydrogen fuel, ammonia/natural gas fuel and ammonia/methanol fuel all have the problem of high NOx emission. The research results of this paper can provide solutions and data support for such research.

To improve the low accuracy of the zero-dimensional combustion model established by BP-NN, a particle swarm-neural network (PSO-NN) algorithm was proposed. The PSO optimize weights and thresholds of NN, and the operating and combustion parameters are constructed, and then compared with NN algorithm. The results show that comparing with NN algorithm, the zero-dimensional combustion model constructed by PSO-NN algorithm has higher prediction accuracy, and the mean square error of the main combustion period m is 0.0034, which is 78.21% lower than that before optimization. The particle swarm algorithm has quicker convergence and stronger versatility, which is suitable for the study of diesel engine 0-D model.

In order to achieve real-time mapping and online optimization of the combustion process of a dual-fuel engine that is in prolonged operation, this paper is the first to combine the Wiebe function with a deep learning neural network to propose a zero-dimensional (0-D) combustion prediction model for a biodiesel-diesel dual-fuel engine. First, the parameters of the double Wiebe functions are calculated by the Pelican Optimization Algorithm (POA), and the operating parameters and Wiebe parameters are used as input and output parameters of neural networks, respectively, to construct parameter identification models. Then, the combustion process is simplified and reconstructed by combining the Wiebe function with the deep learning neural network, and a 0-D prediction model based on the hybrid model-driven and data-driven method is established, which can further obtain combustion results such as cylinder pressure curve and indicated mean effective pressure (IMEP). The results show that the coefficient of determination (R2) value of the dual-fuel engine 0-D prediction model based on the double Wiebe function combined with POA–CNN–Bi-LSTM is 0.9827, and the model has good prediction accuracy and generalization. The development of the combustion model provides reliable numerical model support for the online evaluation and optimization of dual-fuel engine performance.

The combustion efficiency of ammonia fuel engines is low, and the concentration of unburned ammonia and N2O emissions in the exhaust gas is high. This article aims to study the impact of diesel-ignited ammonia/methanol engines on combustion and emission performance, explore the improvement of methanol on ammonia fuel combustion, and find the optimal ammonia/methanol mixture ratio. The research indicates that as the methanol mixing ratio increases, the concentration of unburned ammonia in the exhaust gas gradually decreases, and the power performance is greatly improved. The concentration of CO, soot, CO2, and NOx in the exhaust gas has increased, but due to the combustion support of methanol, the engine N2O emissions have significantly decreased. Mixing methanol improves combustion efficiency and solves the problems of ammonia escape and high N2O emissions. In this paper, the optimal mixing ratio of ammonia/methanol is 8:2. The combustion mode of the diesel ignition ammonia/methanol engine studied effectively solves the problems of ammonia escape and high N2O emissions during ammonia combustion, promotes the development of ammonia in the field of compression ignition engines, and promotes the realization of the purpose of carbon reduction.

Ammonia fuel engines face problems such as low combustion efficiency, ammonia escape, and high N2O emissions. However, natural gas reserves are abundant, and the combustion speed is fast. In order to explore whether the mixing of natural gas can promote the combustion of ammonia fuel, this article discusses the combustion and emission performance of ammonia/natural gas hybrid fuel engines through simulation research. The results indicate that mixing ammonia fuel with natural gas can greatly improve the combustion efficiency of ammonia in the cylinder. Appropriate natural gas can greatly improve the power and economic efficiency of engines. Although the N2O emissions of the engine have significantly decreased, the CO2 and NOx emissions of the engine have significantly increased, and the engine's overall emission performance has become worse. Considering the engine's overall performance, this article selects A50/N50 as the optimal mixture ratio for ammonia/natural gas. The article's research results have effectively improved the problems existing in ammonia engines, providing research direction and data support for the development of ammonia fuels.

Optimizing the combustion process by predicting combustion parameters during prolonged engine operation is crucial for engine maintenance. This study presents a zero-dimensional (0-D) prediction model that integrates the advantages of model-driven and data-driven approaches. Initially, the snake optimization algorithm (SO) is employed to address the challenges related to low parameter fitting accuracy and multiple solutions in calculating Wiebe parameters. Subsequently, a convolutional neural network-bidirectional long short-term memory neural network (CNN–Bi-LSTM) is devised to establish a nonlinear correlation between operating parameters and Wiebe parameters. The structural parameters of CNN–Bi-LSTM are then optimized using the SO algorithm (SO–CNN–Bi-LSTM). Ultimately, a 0-D prediction combustion model is formulated by amalgamating the Wiebe function with the neural network, enabling real-time prediction of combustion results and generalization analysis of prediction performance under non-calibrated conditions. The findings demonstrate that the combustion model exhibits heightened accuracy, thereby establishing a robust technical foundation for the development of a digital twin in the engine combustion process.

To tackle the challenges of low efficiency and excessive NOx emissions in biodiesel-diesel dual-fuel engines, this paper presents an optimization method using the Pareto-multiple objective snake optimizer (Pareto-MOSO) to drive a convolutional neural network-gated recurrent unit (CNN-GRU). In the Pareto-MOSO, brake specific fuel consumption (BSFC), NOx, Soot, and CO are optimized by changing the engine control parameters, including injection timing (Tinject), engine speed (n), biodiesel blending ratio, torque (Ttorque), exhaust gas recirculation (EGR rate), intake pressure (Pin), and rail pressure (Prail). The experiment generates training data for CNN-GRU and verifies the accuracy of the Pareto-MOSO optimization results. The findings suggest that the optimized engine exhibits a balanced correlation between economy and emissions under propulsion characteristics. Furthermore, the NOx emissions are all in accordance with the IMO Tier III emission regulations. Under the rated condition, scheme 2 demonstrates a significant reduction of 76.57% in NOx emissions. However, this optimization has resulted in a 1.63% increase in BSFC compared to its pre-optimized state. Therefore, the adoption of suitable control strategies proves advantageous in addressing the trade-off between economy and emissions of engines.

Ammonia is a zero-carbon fuel. Diesel/ammonia dual-fuel combustion mode can solve the problem of difficult compression ignition of pure ammonia. This article aims to explore the best mixing method and mixing ratio of ammonia fuel. The research results show that with the increase of the ammonia mixing ratio in the intake duct, the fuel consumption rate decreases by 7.71%. However, the serious ammonia escape phenomenon reaches a maximum of 37.35%, resulting in a serious decrease in power output. The cylinder temperature dropped by 197.12K, CO2 emissions decreased by 49.34%, NOx emissions decreased by 16.84%, and emissions significantly improved. When using direct injection ammonia mixing in the cylinder, as the ammonia mixing ratio increases, the explosion pressure in the cylinder decreases by 8.32%, the temperature in the cylinder decreases by 127.37K, the maximum ammonia escape is only 6.89%, CO2 emissions decreased by 88.10%, NOx emissions decrease by 75.90%, and CO2 and NOx emissions significantly decrease. Compared with the two ammonia blending methods, the direct injection ammonia blending method in the cylinder is obviously better. When the direct injection ammonia blending ratio in the cylinder is 70%, compared to the original engine, the diesel engine has the best working performance, increased power, and improved economy by 7.52%, and the proportion of ammonia escape is small. CO2 emissions are reduced by 69.05%, and NOx emissions are reduced by 29.22%. The research results of this article provide data support for achieving energy-saving, emission reduction, and low-carbon environmental protection of diesel engines.

To improve the deterioration of combustion in the cylinder of diesel engines due to insufficient supercharging pressure under low operating conditions, two-stage turbocharging is combined with sequential turbocharging technology. First, the matching calculation of two-stage sequential turbocharging and diesel engine is carried out through propulsion characteristic tests, and the turbocharger model is determined. Secondly, the combined operation curve of the supercharger and diesel engine is obtained by using GT-power software to verify the feasibility of the scheme. Finally, the bench test is carried out to analyze the influence of two-stage sequential turbocharging on diesel engine performance under propulsion and load characteristics. The test results show that with propulsion characteristics, single turbocharging（1TC mode） can effectively improve the combustion deterioration under the engine load of 0–50%. Under the engine load of 50%–100%, the twin turbocharging（2TC mode） can further increase the air-fuel ratio and improve the in-cylinder combustion; especially at 60% engine load, the fuel consumption rate is 8.08% lower than that of the original engine. The two-stage sequential turbocharging mode can achieve good matching of turbochargers at low speed and full torque as well as mediumhigh speed and high torque.

Under the low load conditions, the motor drives the compressor to increase the intake of the engine, and under the high load conditions, the motor recovers the excess exhaust energy, which greatly improves the performance of the diesel engine in all aspects. In this paper, the one-dimensional simulation prediction model of TBD620V16 diesel engine is established and checked. On this basis, the external electric auxiliary turbocharging system of motor is established. The influence of motor power on the performance of diesel engine under different working conditions is studied by simulation, and the control strategy is put forward according to the influence of power and economy of diesel engine under low load. Based on this control strategy, the improvement effect of power performance and economy under low load conditions is studied. The results show that there is an optimal motor power in each load condition to make the comprehensive thermal efficiency of diesel engine reach the maximum value. Under low load condition, with the increase of diesel engine speed, the pressure ratio of electrically assisted turbocharged diesel engine is higher and the fuel consumption is lower. When the diesel engine is accelerated from 25% to 30% load condition, the supercharged pressure of electrically assisted turbocharged diesel engine is stabilized for about 3s, and the supercharged pressure is higher when it is stable, and BSFC is significantly lower than that of traditional turbocharged diesel engine.

The structure of diffuser vanes has a significant influence on the performance of centrifugal compressors. To research the influence of diffuser vane thickness on the overall performance and internal flow condition of the centrifugal compressor. This paper takes a centrifugal compressor as the research object. By changing the diffuser vane thickness, and using three-dimensional fluid simulation technology to carry out simulation research. The results show that the thinner diffuser vanes can greatly improve the efficiency, flow rate and outlet temperature of the centrifugal compressor. For internal local fluid characteristics, thin diffuser blades have lower internal heat load. However, the local flow of fluid is not consistent with the change of vane thickness.

为实现柴油机节能减排,提高燃烧效率,满足Tier Ⅲ NOx排放法规和碳中和目标,建立TBD620柴油机三维仿真模型.通过甲醇进气道喷射法和缸内直喷掺水乳化油技术相结合,研究燃用低活性燃料对柴油机RCCI燃烧模式的工作性能影响.在额定工况下,柴油机转速为1 800r/min,设置10％～50％共5组甲醇掺混比,每组甲醇掺混比都对应0～20％的6组掺水率,共30组模拟组合进行研究.研究结果表明:随着进气道甲醇量增加,柴油机燃烧始点滞后1～2℃A、燃烧初期放热率峰值升高,燃烧效率下降40.0％,缸内爆压升高5.1％,CO2和NOx排放分别下降41.8％和7.7％;随着掺水率增加,柴油机燃烧始点滞后1～2.5℃A,燃烧初期放热率峰值升高,燃烧效率提高8.1％,NOx排放最大下降13.3％,2种技术不同组合下柴油机CO2和NOx排放显著改善、燃烧效率升高,甲醇进气道喷射法和缸内直喷掺水乳化油技术组合的RCCI燃烧模式,对于实现Tier ⅢNOx排放法规和碳中和目标提供一种有效方法.

In order to study the sequential turbocharging switching process of low-speed diesel engine, this paper uses GT-power software to establish a simulation model of sequential turbocharging low-speed diesel engine. It is enhanced and improved into a model of a sequential supercharged diesel engine. Modules such as load, governor, valve control, and surge margin are set up in the simulation model. Then parameters such as switching speed, valve opening time and response time are set in the model. Through the above preparations, the thesis has carried out the simulation calculation of the sequential supercharging transient switching process and verified the rationality of the setting parameters and the accuracy of the module setting. This provides a certain reference for the valve control strategy of the sequential supercharging switching system of low-speed diesel engines.

To realize zero carbon emission in internal combustion engines and boost the growth of ammonia fuel, we mixed a few hydrogens into ammonia fuel to boost the atomization and combustion performance in the combustion chamber. We study hydrogen and ammonia mixed and injected directly through two injectors, the intake temperature is 551k, to find the best injection advance angle combination to ensure the overall working performance of the ammonia Dual fuel engine. The investigation shows that when the main/auxiliary fuel injection timing is 704°CA, the knock value is less than 2, the combustion in the cylinder is gentle, and the negative work phenomenon of knock combustion is avoided. The engine power is the highest and the best economy. The emissions of soot, CO, HC, and CH 2 O are at a very low level, the CO 2 content before and after combustion increases to zero, and the NO x emission is slightly higher than the original engine. We will improve engine NOx emission through SCR Technology in the future. The investigation results will boost the development of an ammonia and hydrogen compression ignition engine and boost the internal combustion engine to zero carbon combustion mode.

Accurate and comprehensive reconstruction of in-cylinder combustion process is essential for timely monitoring of engine combustion state. This article developed a method based on the zero-dimensional (0-D) physical model integrated with big data. The traditional 0-D prediction model based on cumulative fuel mass is improved, the factor of in-cylinder temperature is introduced to adjust the heat release rate, which solves the problem of difficulty in calibrating the heat release rate. Then, convolutional neural network-gated recurrent unit (CNN-GRU), as a deep neural network, including a special convolutional layer and a gated recurrent unit (GRU) neural network is designed for the parameters to be calibrated in the model. The 0-D predictive combustion model is constructed by combining the physical model with CNN-GRU, the combustion process is simplified and reconstructed. The fitting results show that the 0-D physical model based on improved cumulative fuel mass approach is an effective method to reflect the heat release law. Under non-calibration conditions, the root mean square error (RMSE) value of peak firing pressure (PFP) based on CNN-GRU prediction model is 0.5862. The prediction model is a promising method to realize online fitting and optimization of combustion process.

Ammonia fuel is considered one of the most promising zero-carbon fuels. However, ammonia fuel's ignition and combustion performance are poor, and the autoignition temperature is high. Mixing hydrogen fuel and increasing the inlet air temperature is one of the effective methods to realize the ammonia engine. The purpose of this paper is to research the effect of ammonia/hydrogen mixture ratio with engine combustion and emission performance at different inlet temperatures. At the four intake temperatures of 476K–551K, we set the ammonia-hydrogen fuel mixture ratio of 0–90% to study the changes in engine combustion and emission performance. The research shows that in the hydrogen ignition mode when the intake air temperature is 476K, and the hydrogen mixing ratio is 30%, the engine power is the highest, and the KI value is slightly greater than 2MPa/°CA. Fewer parts do negative work, the overall engine performance is the best, the ammonia escape phenomenon is eliminated, and the emission performance is better. A hydrogen/ammonia blended fuel is the best solution to achieve zero-carbon combustion. The research results can promote the development of ammonia/hydrogen engines and promote the internal combustion engine towards zero-carbon combustion mode.

Ammonia fuel is considered to be one of the most promising zero carbon fuels. Mixing a certain amount of hydrogen fuel with ammonia fuel can effectively improve the ignition and combustion performance of ammonia fuel. After burning ammonia/hydrogen mixed fuel, the target of zero carbon emission of an internal combustion engine has been achieved. But the NO x emission in the exhaust gas is still high and the ignition delay period is long, and the dynamic performance is poor. We will study the injection strategy of ammonia/hydrogen dual fuel engines under different compression ratios, and find out the best combination of compression ratio and injection timing of ammonia/hydrogen mixed fuel. We set four compression ratios from 13.5 to 16.5, and each corresponds to eight injection timings from 696°CA to 708°CA. The results show that after delaying the injection timing, the power and economy of the engine become worse, but the NO x emission is greatly improved; After increasing the compression ratio, the power and economy of the engine are greatly improved, and the increase of NO x emission is small. Under any combination of compression ratio and injection timing, the NO x emission of the engine can meet the Tier II emission standard. When the injection timing of ammonia hydrogen / mixed fuel is A/H696 and the compression ratio is 13.5 and 14.5, the NO x emission of this operation combination of ammonia /hydrogen dual fuel engine can meet the Tier III emission standard.

To reach zero carbon emissions and meet carbon neutrality targets, ammonia is one of the most promising zero-carbon fuels. However, ammonia escapes significantly when too much ammonia is blended. Therefore, a certain percentage of hydrogen is blended with the ammonia, which can promote in-cylinder combustion reactions. This paper aims to study the effect of varying ammonia blending hydrogen ratio on in-cylinder explosion pressure, temperature, power, fuel consumption rate, CA50, ammonia escape ratio, hydrogen escape ratio, NOx, CO2 and soot emissions under two ignition modes when the diesel engine speed of 1800 r/min at rated operating conditions in a high-pressure common rail diesel engine, and set nine groups of hydrogen blending ratios from 10% to 90% for diesel ignition. The results show that: when the hydrogen blending ratio is 30% compared to 0, the in -cylinder explosion pressure increases by 10.7%, the power increases by 1.8%, the fuel consumption rate de-creases by 0.3%, the ammonia escape ratio decreases by 99.1%, the NO(x )emissions increase by 58.8%, the CO2 increases by zero, the soot and HC emissions improvements, and the overall performance of the diesel engine is improved after hydrogen blending combustion. To achieve the net-zero carbon emission goal of carbon neutralization, a small amount of diesel ignition direct injection ammonia blended with 30% hydrogen is the better solution.

The diesel ignition ammonia/hydrogen mixed fuel engine adopts the dual injector mode. This paper studies the dual injection strategy of the engine through simulation and selects the best combination of dual injection timing to optimize the combustion and emission performance of the diesel ignition ammonia/hydrogen mixed fuel engine. The results show that under the dual fuel injection strategy, with the delay of fuel injection timing, the power and economy of the engine gradually decline, HC, soot, CO, and N2O emissions in the exhaust gas increase progressively, while NOx emission concentration significantly decreases. However, after using ammonia/ hydrogen mixed fuel, the engine's ammonia escape and hydrogen escape are very low. The emission of HC, soot, and CO in the exhaust gas is also low. At the same time, the engine's NOx emission can meet the emission standards of Tier II when any fuel injection combination is used. At D708/A/H712, the NOx emission of the engine can meet the emission standard of Tier III. One of the purposes of using ammonia as an alternative fuel for diesel is to reduce CO2 emissions in the exhaust gas and prevent further global warming. But the impact of N2O on global warming is nearly 298 times that of CO2. At D698/A/H698, the engine has the best power performance and economic performance. At the same time, N2O emissions are low, but NOx emissions are relatively high. Considering that N2O emissions cause significant harm to the greenhouse effect, D698/A/H698 is selected as the best fuel injection timing combination in this paper. The research results in this paper can promote the devel-opment of ammonia fuel in the field of the internal combustion engine and provide theoretical guidance for the practical application of ammonia.