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Abnormal combustion is an important factor in the development process of hydrogen engine and it mainly includes pre-ignition, backfire and knocking, among which pre-ignition has the most serious impact on hydrogen engine. In this paper, it is divided into four types: normal combustion, slight pre-ignition, moderate pre-ignition and severe pre-ignition according to different crankshaft rotation angles. In order to identify different combustion types, this paper proposes a fault diagnosis model based on the fusion of SOM neural network and Multi-Agent System (SOM-MAS). Firstly, different combustion types are identified by SOM. Secondly, the abnormal combustion is tracked and located mainly through the Multi-Agent System, and the location of the abnormality is identified. Finally, based on 44 sets of pressure data samples collected from the in-cylinder combustion of a hydrogen engine on the experimental bench, different combustion types were diagnosed and identified, and the location of abnormal combustion faults was tracked, which verifies the effectiveness of the proposed method shows that the method has certain feasibility and superiority for the diagnosis of hydrogen engine pre-ignition. • Research carried out by the 492Q hydrogen engine, close to actual conditions. • The dataset is original and contains data for normal and abnormal combustion. • SOM-MAS can be applied in abnormal combustion of hydrogen fuel engines. • Less relevant dataset, we will publish the dataset for future research. [ABSTRACT FROM AUTHOR]

With the development of new energy, hydrogen fuel engines have become a research boom in the automotive field. But there are abnormal problems such as backfire and pre-ignition during the combustion of hydrogen engines. This paper is based on the Ant Colony Optimization-Back Propagation (ACO-BP) algorithm to study the influence of different speed and load conditions on the ignition advance angle, so as to optimize the control of the hydrogen engine. The experimental system is established on a hydrogen engine converted from a 492Q gasoline engine. The prediction of the optimal ignition advance angle was obtained through experiments, and the optimal ignition MAP diagram of the hydrogen engine is constructed. The optimal ignition advance angle under different working conditions can effectively avoid the occurrence of hydrogen engine pre-ignition. The accuracy reaches 0.0018209 when the training reaches 14 times, the fitness between the actual value and the predicted value of ACO-BP training is 0.99921, the verification accuracy reaches 0.99913, and the test accuracy reaches 0.99932. Compared with the three optimization methods, the convergence speed and error accuracy of ACO-BP are significantly better than the BP neural networks and Genetic Algorithm-Back Propagation (GA-BP). This method realized the model of the nonlinear mapping model from hydrogen engine speed and load to optimal ignition advance angle, which is of great significance for solving the problem of abnormal combustion in hydrogen engine. • Research carried out by the 492Q hydrogen engine, close to actual conditions. • The dataset is original, collected under different speed and load conditions. • ACO-BP can be applied in abnormal combustion of hydrogen fuel engines. • Less relevant dataset, we will publish the dataset for future research. [ABSTRACT FROM AUTHOR]

When hydrogen internal combustion engine works using the intake manifold injection mode to provide the hydrogen, it has to face a contradiction between the abnormal combustion (preignition, backfire, etc.). Currently, most researches on abnormal combustion in hydrogen internal combustion engines have focused primarily on backfire and detonation, with limited investigation of pre-ignition, particularly when initiated by in-cylinder hot spots. In order to explore the relationship between the hot spot and the pre-ignition of hydrogen internal combustion engine, the influence of characteristic parameters of hot spot, such as hot spot area, initial temperature, duration of hot spot and temperature change rate, on pre-ignition of hydrogen internal combustion engines were analyzed. On the basis of using the isolated factor method to research the influence of each characteristic parameter on the occurrence time of pre-ignition of hydrogen internal combustion engines, the comprehensive effect of these characteristic parameters on the occurrence moment of pre-ignition in hydrogen internal combustion engines was also investigated with the orthogonal test method. It is found that the occurrence of pre-ignition of hydrogen internal combustion engines is the result of multi-factor interaction. Pre-ignition is most affected by hot spot area, and when the hot spot area is the same, the order of influence of pre-ignition timing is initial temperature > temperature change rate > duration of hot spot. The research results can promote the practical application of hydrogen fuel in internal combustion engines and provide guidance for the structural design of hydrogen internal combustion engines. • Hydrogen engine pre-ignition results from combined effects of several parameters such as the area, initial temp. • Strategies to control temp change rates could mitigate pre-ignition risks and optimize combustion performance. • Compared to initial temp, the moment of pre-ignition is more sensitive to changes in the area of the hot spot. • With equal hot spot area: initial temp > temp change rate > duration influence hydrogen engine pre-ignition. [ABSTRACT FROM AUTHOR]

For the port injection hydrogen-fueled spark ignition (SI) engine modified from the Jialing JH600 gasoline engine, the hydrogen injection timing and ignition timing of the hydrogen SI engine are comprehensively optimized on the AVL-FIRE software based on the combination of design of experiment (DOE) and multiple population genetic algorithm (MPGA). Firstly, the effects of hydrogen injection timing and ignition timing on the performance of the hydrogen engine are investigated through the full factors design of experiment scheme, and then the optimum intervals of them are determined respectively. Secondly, the uniform design of experiments scheme is arranged, and the regression functions of indicated power, indicated thermal efficiency and emissions of the hydrogen engine under different working conditions are fitted. Then, the comprehensive optimization model is constructed. Finally, the optimum hydrogen injection timing and ignition timing of the hydrogen engine under different working conditions are solved based on MPGA. The results show that, compared with the standard genetic algorithm (SGA), the MPGA has faster convergence speed and higher convergence accuracy. In addition, as the load increases from low to high, the optimum hydrogen injection timing is advanced and the rate of variation increases from 0.6% to 1.1%, the optimum ignition timing is delayed and the rate of variation decreases from 29.1% to 17.8%. • The uniform design can substantially reduce experimental study effort and cost. • Optimization models obtained by regression analysis based on the uniform design. • Solving optimization models with MPGA instead of SGA. • Providing a new idea for optimizing hydrogen SI engine. [ABSTRACT FROM AUTHOR]