Optimal Design of a High-power Friction Brake Based on Improved Genetic Algorithm

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• 英文论文题名：Optimal Design of a High-power Friction Brake Based on Improved Genetic Algorithm
• 论文作者：LI Pengfei ; WANG Guangsen ; ZHANG Xiangming ; MA Mingzhong
• 英文论文作者：LI Pengfei ; WANG Guangsen ; ZHANG Xiangming ; MA Mingzhong ; National Key Laboratory of Science and Technology on Vessel Integrated Power System ; Naval Univ. of Engineering
• 年：2017
• 作者机构：National Key Laboratory of Science and Technology on Vessel Integrated Power System,Naval Univ. of Engineering;
• 英文论文关键词：friction brake ; genetic algorithm ; multi-objective optimization ; penalty function
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：O313.5;TP18
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：381k
• 原文格式：D
• 会议级别：全国

摘要

For the emergency braking of a large-capacity inertia flywheel energy storage system, this paper refers to a rapid braking scheme based on the friction brake. However, its difficulty lies in the design of a high power brake, which includes temperature, volume, power and so on. The present multi-objective optimization algorithm is not available for engineers due to its complicated design, much difficulty in implementation, and time-consuming calculation. Therefore, this paper has proposed an improved genetic algorithm to solve multiple constraints, which can be changed into a problem of common constraint. Moreover the algorithm is convenient for designers because of its ideal convergence, universality and flexibility. The prototype testing proves the braking scheme of the large-capacity flywheel energy storage system to be feasible and the optimized algorithm for the friction brake to be effective, which can play a certain guiding role in engineering practice.
For the emergency braking of a large-capacity inertia flywheel energy storage system, this paper refers to a rapid braking scheme based on the friction brake. However, its difficulty lies in the design of a high power brake, which includes temperature, volume, power and so on. The present multi-objective optimization algorithm is not available for engineers due to its complicated design, much difficulty in implementation, and time-consuming calculation. Therefore, this paper has proposed an improved genetic algorithm to solve multiple constraints, which can be changed into a problem of common constraint. Moreover the algorithm is convenient for designers because of its ideal convergence, universality and flexibility. The prototype testing proves the braking scheme of the large-capacity flywheel energy storage system to be feasible and the optimized algorithm for the friction brake to be effective, which can play a certain guiding role in engineering practice.

引文

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