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Definition of a Methodology Promoting the Use of 1D Thermo-Fluid Dynamic Analysis for the Reduction of the Experimental Effort in Engine Base Calibration

机译:方法的定义促进使用1D热流体动力学分析,以减少发动机基础校准中的实验努力

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Over the last decades, internal combustion engines have undergone a continuous evolution to achieve better performance, lower pollutant emissions and reduced fuel consumption. The pursuit of these often-conflicting goals involved changes in engine architecture in order to carry out advanced management strategies. Therefore, Variable Valve Actuation, Exhaust Gas Recirculation, Gasoline Direct Injection, turbocharging and powertrain hybridization have found wide application in the automotive field. However, the effective management of a such complex system is due to the contemporaneous development of the on-board Engine electronic Control Unit. In fact, the additional degrees of freedom available for the engine regulation highly increased the complexity of engine control and management, resulting in a very expensive and long calibration process. To overcome these drawbacks, an effective methodology based on the adoption of 1D thermo-fluid dynamic analysis is proposed in this study. In particular, starting from a complete experimental set of data actually used for the base calibration of a reference spark ignition engine, a novel procedure based on vector optimization approach is used to reliably calibrate a 1D engine model starting from a reduced experimental dataset. Once validated, the engine model is then used as a virtual test bench to reproduce the experimental campaign numerically, thus obtaining a detailed and complete dataset exploitable for calibration purposes, here called numerical or virtual dataset. To verify the potential of the proposed methodology, experimental and virtual dataset have been finally compared. The research clearly demonstrates the effectiveness of the proposed approach since the average errors are comparable with the measurement errors. Therefore, the methodology shows promising results concerning the use of numerical dataset obtained from reliable 1D CFD engine models as input to computer aided calibration software. This way, a significant cut to the experimental campaign required for calibration purposes is achieved, with their related times and costs.
机译:在过去十年中,内燃机经历了连续的演化,以实现更好的性能,降低污染物排放和降低的燃料消耗。追求这些经常冲突的目标涉及发动机架构的变化,以便进行先进的管理策略。因此,可变阀致动,废气再循环,汽油直接注射,涡轮增压和动力总成杂交在汽车领域中发现了广泛的应用。然而,这种复杂系统的有效管理是由于车载发动机电子控制单元的同时发展。实际上,发动机调节的额外自由度高度增加了发动机控制和管理的复杂性,导致了非常昂贵和长的校准过程。为了克服这些缺点,本研究提出了一种基于通过1D热流体动态分析的有效方法。特别地,从实际用于参考火花点火发动机的基本校准的完整实验数据开始,基于矢量优化方法的新方法用于可靠地校准从减少的实验数据集开始校准1D发动机模型。经过验证,然后将发动机模型用作虚拟测试台以数字上重现实验活动,从而获得用于校准目的的详细和完整的数据集,这里称为数字或虚拟数据集。为了验证所提出的方法的潜力,最终终于比较了实验和虚拟数据集。该研究清楚地证明了所提出的方法的有效性,因为平均误差与测量误差相当。因此,该方法显示了关于使用从可靠的1D CFD发动机模型获得的数值数据集作为计算机辅助校准软件的输入。这样,实现了校准目的所需的实验活动的显着切割,其相关的时间和成本。

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