Asymmetric vibration characteristics of two-cylinder four-stroke single-piston hydraulic free piston engine

The structure and working principle of a two-cylinder four-stroke single-piston hydraulic free piston engine(HFPE) were introduced. The basic vibration equation of free piston assembly(FPA) was established based upon the energy conversion between the injected fuel and the friction together with the load. Both the theoretical and numerical results show that the vibration system of FPA is a nonlinear conservative autonomous system in one cycle. The FPA vibration is symmetric with constant amplitude when FPA is only driven by the compression pressure in the compression accumulator and that in the combustion chamber. When considering the friction and load, FPA could still achieve a stable vibration after a few cycles' adjustment whether the input energy is equal to the consumed energy or not. The vibration characteristics are different when FPA vibrates in the compression stroke and the expansion stroke, which is the unique feature of the single-piston HFPE.

NOISE IDENTIFICATION FOR HYDRAULIC AXIAL PISTON PUMP BASED ON ARTIFICIAL NEURAL NETWORKS

The noise identification model of the neural networks is established for the 63SCY14 IB hydraulic axial piston pump. Taking four kinds of different port plates as instances, the noise identification is successfully carried out for hydraulic axial piston pump based on experiments with the MATLAB and the toolbox of neural networks, The operating pressure, the flow rate of hydraulic axial piston pump, the temperature of hydraulic oil, and bulk modulus of hydraulic oil are the main parameters having influences on the noise of hydraulic axial piston pump. These four parameters are used as inputs of neural networks, and experimental data of the noise are used as outputs of neural networks, Error of noise identification is less than 1% after the neural networks have been trained. The results show that the noise identification of hydraulic axial piston pump is feasible and reliable by using artificial neural networks. The method of noise identification with neural networks is also creative one of noise theoretical research for hydraulic axial piston pump.

Thermal-hydraulic modeling and analysis of hydraulic system by pseudo-bond graph

To increase the efficiency and reliability of the thermodynamics analysis of the hydraulic system, the method based on pseudo-bond graph is introduced. According to the working mechanism of hydraulic components, they can be separated into two categories: capacitive components and resistive components. Then, the thermal-hydraulic pseudo-bond graphs of capacitive C element and resistance R element were developed, based on the conservation of mass and energy. Subsequently, the connection rule for the pseudo-bond graph elements and the method to construct the complete thermal-hydraulic system model were proposed. On the basis of heat transfer analysis of a typical hydraulic circuit containing a piston pump, the lumped parameter mathematical model of the system was given. The good agreement between the simulation results and experimental data demonstrates the validity of the modeling method.

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system（IHPS） based on a nonlinear unknown input observer（NUIO） is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.

Massive energy storage systems enable secure electricity supply from renewables

Climate change is mainly attributed to the burning of fossil fuels.To solve the problem,current inhabitants have to dispense with fossil fuels as a source of power.It has been demonstrated that this can be secured before 2050 by transitioning to renewable sources of energy.Massive energy storage(MES)incorporated into long distance high voltage direct current(HVDC)transmission systems is the key technology for the transition.This paper describes the current state-of-the-art in electricity grid configurations.It demonstrates how MES,and other back-up local electricity storage schemes represent a natural way of buffering electricity consumers from the intermittency of inherent in the primary renewable systems.Consequently,it can solve the base-load issues and facilitate a global transition to 100%renewable energy sources over the next fifteen to twenty years.