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Multi-Objective Optimization Design of an Electrohydrostatic Actuator Based on a Particle Swarm Optimization Algorithm and an Analytic Hierarchy Process

Author

Listed:
  • Bo Yu

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

  • Shuai Wu

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

  • Zongxia Jiao

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

  • Yaoxing Shang

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

Abstract

During the last few years, the concept of more-electric aircraft has been pushed ahead by industry and academics. For a more-electric actuation system, the electrohydrostatic actuator (EHA) has shown its potential for better reliability, low maintenance cost and reducing aircraft weight. Designing an EHA for aviation applications is a hard task, which should balance several inconsistent objectives simultaneously, such as weight, stiffness and power consumption. This work presents a method to obtain the optimal EHA, which combines multi-objective optimization with a synthetic decision method, that is, a multi-objective optimization design method, that can combine designers’ preferences and experiences. The evaluation model of an EHA in terms of weight, stiffness and power consumption is studied in the first section. Then, a multi-objective particle swarm optimization (MOPSO) algorithm is introduced to obtain the Pareto front, and an analytic hierarchy process (AHP) is applied to help find the optimal design in the Pareto front. A demo of an EHA design illustrates the feasibility of the proposed method.

Suggested Citation

  • Bo Yu & Shuai Wu & Zongxia Jiao & Yaoxing Shang, 2018. "Multi-Objective Optimization Design of an Electrohydrostatic Actuator Based on a Particle Swarm Optimization Algorithm and an Analytic Hierarchy Process," Energies, MDPI, vol. 11(9), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2426-:d:169581
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    References listed on IDEAS

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    1. Sayyaadi, Hoseyn & Babaie, Meisam & Farmani, Mohammad Reza, 2011. "Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system," Energy, Elsevier, vol. 36(8), pages 4777-4789.
    2. Perera, A.T.D. & Attalage, R.A. & Perera, K.K.C.K. & Dassanayake, V.P.C., 2013. "A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems," Applied Energy, Elsevier, vol. 107(C), pages 412-425.
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    Cited by:

    1. Mingkun Yang & Gexin Chen & Jianxin Lu & Cong Yu & Guishan Yan & Chao Ai & Yanwen Li, 2021. "Research on Energy Transmission Mechanism of the Electro-Hydraulic Servo Pump Control System," Energies, MDPI, vol. 14(16), pages 1-17, August.
    2. Guishan Yan & Zhenlin Jin & Mingkun Yang & Bing Yao, 2021. "The Thermal Balance Temperature Field of the Electro-Hydraulic Servo Pump Control System," Energies, MDPI, vol. 14(5), pages 1-24, March.

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