基于遗传算法的半履带气垫车多参数优化  

Multi-parameter Optimization for a Semi-Track Air-Cushion Vehicle Based on Genetic Algorithms

作　　者：周科[1] 罗哲[1] 喻凡[1] 

机构地区：[1]上海交通大学机械系统与振动国家重点实验室汽车工程研究院,上海200240

出　　处：《传动技术》2008年第2期15-18,48,共5页Drive System Technique

基　　金：国家自然科学基金资助项目(50675135)

摘　　要：在分析半履带气垫车行驶阻力的基础上,建立了百公里油耗的理论模型,讨论了砂壤土条件下风机转速和车辆前进速度对百公里油耗的影响。在MATLAB环境下设计了基本遗传算法模型以优化百公里油耗及相应的参数,得到了较理想的优化结果,但优化过程存在着一定的问题。通过分析基本遗传算法的缺陷性,明确了优化过程中问题的主要来源,并有针对性地改进了算法。此改进遗传算法优化过程和结果表现出寻优的有效性和稳定性。Based on the analyses of the resistances for a semi-track air-cushion vehicle （STACV）, a theoretical model for fuel consumption of 100 km is established, and the effects of fan rotational speed and vehicle forward speed on fuel consumption of 100 km are examined in sandy loam working condition. In a MATLAB software environment, a basic genetic algorithms model is designed to optimize the fuel consumption and relevant parameters. The optimization result of the basic model is comparatively ideal; however, there exists some problems in its optimization process. By analyzing dejects of the basic genetic algorithms, the main sources of the problems in optimization process are figured out, and the pertinent improvements of algorithms model are proposed. The optimization process and result of the improved genetic algorithms indicate its effectiveness and stability.

关 键 词：半履带气垫车 风机转速 车速 百公里油耗 基本遗传算法 改进遗传算法 优化 

分 类 号：U489[交通运输工程—载运工具运用工程]