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Multi-objective optimization of the volumetric and thermal efficiencies applied to a multi-cylinder internal combustion engine

机译：体积和热效的多目标优化应用于多缸内燃机的多气体效率

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摘要

The engines produced with valve timing systems have been growing in recent years, given the growing demand to improve their operation and efficiency. Certain operating conditions of valve timing engine increasing volumetric efficiency have a reduction in thermal efficiency. This study aims to apply multi-objective optimization to find conditions for opening and closing valves of maximum volumetric and thermal efficiency, evaluating through performance metrics two optimization methods. The inlet and exhaust valves timing were chosen as design variables. The multi-objective optimization methods used are Non-dominated Sorting Genetic Algorithm - II and Multi-Objective Differential Evolution. Simulations are performed for four different engine speeds. The compressible duct flow is numerically solved by the two step Lax-Wendroff method with Total Variation Diminishing flow control. The performance metrics used in this study are maximum values, number of non-dominated solutions, spacing, hyper-volume and time simulation. The results showed a Pareto front maximizing the volumetric efficiency and decreasing thermal efficiency, and vice versa. The Multi-Objective Differential Evolution presented greater values than Non-dominated Sorting Genetic Algorithm - II, more non-dominated solutions, higher hyper-volume values, with the advantage of spent less computational time. Both approaches were able to optimize internal combustion engine efficiencies finding the optimal valve timing sets. Moreover, allows finding conditions for opening and closing valves that favor both efficiencies.
机译：鉴于提高其运营和效率的需求不断增长，近年来，随着气门正时系统生产的发动机越来越大。阀门正时发动机的某些操作条件增加了体积效率的热效率降低。本研究旨在应用多目标优化，以找到最大体积和热效率的打开和关闭阀的条件，通过性能指标评估两种优化方法。选择入口和排气阀时序作为设计变量。使用的多目标优化方法是非主导的分类遗传算法 - II和多目标差分演进。为四种不同的发动机速度执行模拟。通过具有总变化的流量控制的两个步骤LAX-WendRoff方法在数值求解的可压缩管道流。本研究中使用的性能指标是最大值，非主导解决方案数，间距，超容量和时间仿真。结果显示了帕累托前线，最大化体积效率和降低热效率，反之亦然。多目标差分进化呈现出比非主导分类遗传算法 - II，更非主导的解决方案，更高的超容量值更高的值，其中具有较少的计算时间。两种方法都能够优化内燃机效率，找到最佳气门正时组。此外，允许寻找有利效的打开和关闭阀的条件。

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