贺玉海，蒋乾.船用低速柴油机电控喷油器多参数优化匹配[J].内燃机工程,2020,41(6):78-85.
船用低速柴油机电控喷油器多参数优化匹配
Multi-Parameter Optimal Matching of Electronically Controlled Injector for Marine Low-Speed Diesel Engines
DOI：10.13949/j.cnki.nrjgc.2020.06.010
关键词:低速柴油机  电控喷油器  参数优化  数值模拟
Key Words:low-speed diesel engine  electronically controlled injector  parameter optimization  numerical simulation
基金项目:船用低速机工程（一期）研制（工信部联装函[2017]21号）
作者单位
贺玉海，蒋乾 1.武汉理工大学 能源与动力工程学院，武汉 430063； 2.武汉理工大学 船舶动力工程技术交通行业重点实验室，武汉 430063 
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摘要:为了更好地优化电控喷油器性能，基于一种自主设计的船用低速机电控喷油器结构，借助AMESim 软件搭建了电控喷油器的仿真模型，利用专用试验平台验证了模型的准确性。随后通过开展各结构参数对电控喷油器性能影响灵敏度量化分析，筛选出对电控喷油器性能影响较大的结构参数，并采用正交试验和遗传算法两种优化法相结合的数值模拟方法，以提高电控喷油器针阀响应速率为目标，对电控喷油器开展了参数优化匹配，得到了关键结构参数对电控喷油器针阀动态响应特性的影响权重和最佳参数组合。结果表明：出油口直径是对针阀响应特性影响权重最大的结构参数，控制活塞直径和进油口直径次之，而控制腔容积和针阀弹簧预紧力影响相对较小；应用正交试验法优化后，与原参数方案相比，参数优化后针阀上升时间缩短了1.00ms，针阀下降时间缩短了140ms；相比于原参数方案，通过应用遗传算法优化，后电控喷油器针阀响应特性明显改善，针阀上升时间缩短了40.90%，针阀下降时间缩短了29.10%。
Abstract:In order to better optimize the performance of electronically controlled injector, a simulation model of electronically controlled injector was established for a self-designed marine low-speed diesel engine by using AMESim software, and the accuracy of the model was verified by a dedicated test platform. Firstly, a quantitative analysis of the influence of various structural parameters on injector performance was carried out to screen out the structural parameters with greater influence. Then, with the purpose of improving the response rate of injectors needle valve, a numerical simulation method combining the orthogonal experiment and genetic algorithm was used to optimally match the structural parameters in order to obtain the weighting factor and the optimal combination of multi-target parameters for the different effects of key structural parameters on dynamic response characteristics of the needle valve. Results show that the diameter of fuel metering outlet is the structural parameter that has the greatest influence on response characteristics of a needle valve, followed by the diameter of the control piston and fuel metering inlet, while the volume of control chamber and the preload of needle valve spring have less influence. Compared with the original structural parameter scheme, after optimization by the orthogonal experiment, the needle rise time is shortened by 1.00ms coupled with the reduction of needle fall time by 1.40ms, and after optimization by the genetic algorithm, the needle response time is significantly improved, resulting in the reduction of needle rise time by 40.9%, and hence needle fall time by 29.1%.
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