Zhewu Cheng

The prominent problem of articulated steering structure of engineering vehicle is that there is pressure oscillation in the hydraulic system during steering, which seriously affects the performance of steering system. To solve this problem, the maximum stroke difference of left and right cylinders and the minimum maximum cylinder pressure are the optimization objectives, and the position of cylinder hinge point is the design variable. The multi-objective optimization design of articulated steering system is carried out by using the particle swarm optimization algorithm. After optimization, the maximum pressure of the steering system is reduced by 13.5%, and the oscillation amplitude is reduced by 16%, so the optimization effect is obvious. The dynamic characteristics of the hydraulic steering system under different loads, such as pressure and flow rate, are obtained through field steering tests of wheel loaders. The results show that the load has an important effect on the pressure response of the system, and the causes and influencing factors of pressure and flow fluctuation are determined. The relationship between mileage and hydrogen consumption is obtained, which provides data support for vehicle control strategy. The high-pressure overflow power consumption accounts for 60% of the total work, and the work lost on the steering gear reaches 36 kJ. The test results verify the rationality and correctness of the optimization method of steering mechanism and provide data support for the improvement in steering hydraulic system.

Real-time estimation of three-dimensional field data for enclosed spaces is critical to HVAC control. This task is challenging, especially for large enclosed spaces with complex geometry, due to the nonuniform distribution and nonlinear variations of many environmental variables. Moreover, constructing and maintaining a network of sensors to fully cover the entire space is very costly, and insufficient sensor data might deteriorate system performance. Facing such a dilemma, gappy proper orthogonal decomposition (POD) offers a solution to provide three-dimensional field data with a limited number of sensor measurements. In this study, a gappy POD method for real-time reconstruction of contaminant distribution in an enclosed space is proposed by combining the POD method with a limited number of sensor measurements. To evaluate the gappy POD method, a computational fluid dynamics (CFD) model is utilized to perform a numerical simulation to validate the effectiveness of the gappy POD method in reconstructing contaminant distributions. In addition, the optimal sensor placement is given based on a quantitative metric to maximize the reconstruction accuracy, and the sensor placement constraints are also considered during the sensor design process. The gappy POD method is found to yield accurate reconstruction results. Further works will include the implementation of real-time control based on the POD method.

The loading-to-flow diagram is a widely used classical method for the preliminary design of radial turbines. This study improves this method to optimize the design of radial turbines in the early design phase under variable operating conditions. The guide vane outlet flow angle is a key factor affecting the off-design performance of the radial turbine. To optimize the off-design performance of radial turbines in the early design phase, we propose a hypothesis that uses the ratio of the mean velocity of the fluid relative to the rotor passage with respect to the circumferential velocity of the rotor as an indicator to indirectly and qualitatively estimate the rotor loss, as it plays a key role in the off-design efficiency. Theoretical analysis of rotor loss characteristics under different types of variable operating conditions shows that a smaller design value of guide vane outlet flow angle results in a better off-design performance in the case of a reduced mass flow. In contrast, radial turbines with a larger design value of guide vane outlet flow angle can obtain a better off-design performance with increased mass flow. The above findings were validated with a mean-line model method. Furthermore, this study discusses the optimization of the design value of guide vane outlet flow angle based on the matching of rotor loss characteristics with specified variable operating conditions. It provides important guidance for the design optimization of multistage radial turbines with variable operating conditions in compressed air energy storage (CAES) systems.