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An opposed piston two-stroke engine is more suitable for use in an unmanned aerial vehicle because of its small size, excellent self-balancing, stable operation, and low noise. Consequently, in this study, based on experimental data for a prototype opposed piston two-stroke engine, numerical simulation models were established using GT-POWER for 1D simulation and AVL-FIRE for 3D CFD simulation. The mesh grid and solver parameters for the numerical model of the CFD simulation were determined to guarantee the accuracy of the numerical simulation, before studying and optimizing the ventilation efficiency of the engine with different dip angles. Furthermore, the fuel spray and combustion were analyzed and optimized in details.

The Structure and principle of the hydraulic free piston engine (HFPE) is analyzed, and the mathematical model is established according to the feature of the working principle. The transient processes are analyzed through simulation. The result shows that: 1) the working cycle of the HFPE is unsymmetrical, the compression stroke time is 16ms and the expansion stroke time is 10ms. 2) The speed of the power piston is faster than the conventional diesel engine, the maximum speed in the compression stroke is 12m/s and the maximum speed in the expansion stroke is 17m/s. 3) The acceleration is bigger than the conventional engine, the maximum value is 16500m/s2, at the top dead centre and the smallest value is 3500m/s2 at the bottom dead centre.

A new method for driving the hydraulic free piston engine is proposed. This method achieves the compression stroke automatically rather than special recovery system. Principle of hydraulic differential drive free-piston engine is analyzed and the control strategy of this novel hydraulic driving engine is also introduced. Then energy balance method is used to design the main parameters of the novel engine. High pressure and secondary high pressure of the hydraulic system are constrained by the combustion parameters and therefore parameters are analyzed. In order to verify the effectiveness of energy balance method, the mathematical model is established based on the piston force analysis and engine working principle. The transient results of dynamics are obtained through simulation. In addition, the effectiveness of the simulation is proofed by dimensionless analysis. It indicates that energy balance method realizes the basic performance of hydraulic free piston engine.

The electronic control of direct injection fuel system, which could improve engine fuel efficiency, dynamics and engine emission performance through good atomization, precise control of fuel injection time and improvement of fuel-gas mixture, is the key technology to achieve the stratified combustion and lean combustion. In this paper, a direct injection injector that based on voice coil motor was designed aiming at the technical characteristics of one 800cc two-stroke cam-less engine. Prior to a one - dimensional simulation model of injector was established by AMEsim and the maximal fuel injection demand was met via the optimization of the main parameters of the injector, the structure of the voice coil motor was optimized by magnetic equivalent circuit method. After that, the maximal flow rate of the injector was verified by the injector bench test while the atomization characteristic of the injector was verified by using a high-speed camera.

Considering the randomness and instability of the oil pressure in the lubrication system, a new approach for fault detection and diagnosis of diesel engine lubrication system based on support vector machine optimized by particle swarm optimization (PSO-SVM) model and centroid location algorithm has been proposed. Firstly, PSO algorithm is chosen to determine the optimum parameters of SVM, to avoid the blindness of choosing parameters. It can improve the prediction accuracy of the model. The results show that the classify accuracy of PSO-SVM is improved compared with SVM in which parameters are set according to experience. Then, the support vector machine classification interface is fitted to a curve, and the boundary conditions of fault diagnosis are obtained. Finally, diagnose algorithm is achieved through analyzing the centroid movement of features. According to Performance degradation data, degenerate trajectory model is established based on centroid location.