应用科学学报 ›› 2011, Vol. 29 ›› Issue (3): 325-330.doi: 10.3969/j.issn.0255-8297.2011.03.017

• 控制与系统 • 上一篇    

飞机环控系统最小熵产分析

李洪波1, 董新民1, 李婷婷2, 郭军1   

  1. 1. 空军工程大学工程学院,西安710038
    2.飞行自动控制研究所,西安710065
  • 收稿日期:2010-11-12 修回日期:2011-01-04 出版日期:2011-05-26 发布日期:2011-05-26
  • 通信作者: 李洪波,博士生,研究方向:机载公共设备综合优化、飞行控制,E-mail: lhbfirst-81@163.com;董新民,教授,博导,研究方向:飞行器控制理论与应用、智能控制等,E-mail: dongxinmin@163.com
  • 作者简介:李洪波,博士生,研究方向:机载公共设备综合优化、飞行控制,E-mail: lhbfirst-81@163.com;董新民,教授,博导,研究方向:飞行器控制理论与应用、智能控制等,E-mail: dongxinmin@163.com
  • 基金资助:

    航空科学基金(No.2008ZC01006)资助

Minimum Entropy Generation Analysis of Aircraft Environmental Control System

LI Hong-bo1, DONG Xin-min1, LI Ting-ting2, GUO Jun1   

  1. 1. Engineering College, Air Force Engineering University, Xi’an 710038, China
    2. Flight Automatic Control Research Institute, Xi’an 710065, China
  • Received:2010-11-12 Revised:2011-01-04 Online:2011-05-26 Published:2011-05-26
  • About author:李洪波,博士生,研究方向:机载公共设备综合优化、飞行控制,E-mail: lhbfirst-81@163.com;董新民,教授,博导,研究方向:飞行器控制理论与应用、智能控制等,E-mail: dongxinmin@163.com

摘要:

根据热力学第二定律,提出采用多目标优化方法对飞机环境控制系统进行最小熵产分析. 选取起飞、加速爬升和高空超音速巡航为设计点,以系统熵产最小为目标函数建立优化模型,并进行了优化计算,分析了热交换器流比、引气流量、涡轮和压气机压力比在不同飞行阶段对系统熵产的影响. 为克服在不同飞行阶段使系统熵产减小对设计变量的要求不一致的问题,将各设计点系统熵产最小作为不同目标函数建立多目标优化模型,并应用NSGA-Ⅱ算法进行优化计算得到了非劣最优解集,在此基础上进行方案决策. 仿真结果验证了方法的有效性.

关键词: 环境控制系统, 熵产, 多目标优化, 非劣最优解集, 多目标决策

Abstract:

 Based on the second law of thermodynamics, minimum entropy generation analysis of aircraft environmental control is conducted using the multi-objective optimization method. To design takeoff, climb and supersonic cruise, and take entropy generation minimum as the objective function, an optimization model is established. In the optimization computation, influences of flow ratio of heat exchanger, mass flow of bleed air, pressure ratio of compressor and turbine on system entropy generation during different flight phases are analyzed. To overcome the conflict between design variables during different phases, a multi-objective optimization model is established with minimum entropy generations as different objective functions at the
design points. The Pareto optimal set is obtained using the NSGA-II algorithm, leading to an optimal scheme. Simulation shows validity of the proposed method.

Key words: environmental control system (ECS), entropy generation, multi-objective optimization, Pareto optimal set, multi-objective decision-making

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