A Simulation-Based Multi-Objective Optimization Design Method for Pump-Driven Electro-Hydrostatic Actuators

Abstract

A pump-driven actuator, which usually called an electro-hydrostatic actuator (EHA), is widely used in aerospace and industrial applications. It is interesting to optimize both its static and dynamic performances, such as weight, energy consumption, rise time, and dynamic stiffness, in the design phase. It is difficult to decide the parameters, due to the high number of objectives to be taken into consideration simultaneously. This paper proposes a simulation-based multi-objective optimization (MOO) design method for EHA with AMESim and a python script The model of an EHA driving a flight control surface is carried out by AMESim. The python script generates design parameters by using an intelligent search method and transfers them to the AMESim model. Then, the script can run a simulation of the AMESim model with a pre-set motion and load scenario of the control surface. The python script can also obtain the results when the simulation is finished, which can then be used to evaluate performance as the objective of optimization. There are four objectives considered in the present study, which are weight, energy consumption, rise time, and dynamic stiffness. The weight is predicted by the scaling law, based on the design parameters. The performances of dynamic response energy efficiency and dynamic stiffness are obtained by the simulation model. A multi-objective particle swarm optimization (MOPSO) algorithm is applied to search for the parameter solutions at the Pareto-front of the desired objectives. The optimization results of an EHA, based on the proposed methodology, are demonstrated. The results are very useful for engineers, to help determine the design parameters of the actuator in the design phase. The proposed method and platform are valuable in system design and optimization.

Special Issue: Smart Flow Control in Micro Scale

“…Xue et al [10] proposed a design method based on Amesim and a Python script for the purpose of multi-objective optimization in static and dynamic performances of a pump-driven actuator. The mapping between the design parameters and the relations between the objectives are plotted.…”

Multi-Level Modeling Methodology for Optimal Design of Electric Machines Based on Multi-Disciplinary Design Optimization

“…The magnetic potential of pole F p can be calculated by the corresponding magnetic intensity H p and pole height h p . Therein, B p has the same meaning as the afore-mentioned B y ; see Equation (19):…”

“…In addition, with the development of artificial intelligence and information technologies, model-based system engineering (MBSE) [8][9][10] and optimization-assisted design [11] have become the focus of researchers, becoming increasingly mature, and will be particularly powerful for the design of aircraft power systems. In this context, models of the electrical environment control system (ECS) [12,13], electromagnetic actuators (EMAs) [14][15][16][17], and electro-hydraulic actuators (EHAs) [16,18,19] were established to support the trade-offs between the weight and power loss of More-electric systems. To implement these analyses, machine models for optimal designs have been widely investigated.…”

Position Control Study on Pump-Controlled Servomotor for Steam Control Valve

“…The drive and control part of the SM usually adopts electrohydraulic servo-valve-controlled technology; that is, the hydraulic station provides system oil supply pressure, and the hydraulic cylinder is controlled by the throttle characteristic of the servo valve to adjust the opening of the steam control valve. Although this technology has good control performance, it has technical defects such as poor antipollution ability, low energy efficiency, large volume size, and limited installation space [7]. The application of electrohydraulic servo pump control technology in the field of SM has mostly focused on the analysis of structural principles, and there is a lack of in-depth research on its specific control strategies.…”