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Development and validation of a marine sequential turbocharging diesel engine combustion model based on double Wiebe function and partial least squares method

机译:基于双韦伯函数和偏最小二乘方法的船用顺序增压柴油机燃烧模型的开发与验证

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摘要

Developing an accurate combustion model for a Sequential Turbocharging diesel engine is an efficient way to reduce the time consumption and the expensive experiment costs in the process of determining the control strategy of a Sequential Turbocharging system. In this paper, 142 operations of a marine diesel engine with two Sequential Turbocharging systems are used for this research. A novel method is proposed to calculate the initial values and limit bounds of the Wiebe parameters, and the use of this method could effectively avoid the occurrence of impossible solutions or multiple solutions caused by only using nonlinear least square fitting. The calculated Wiebe parameters could achieve a high level of accuracy that the mean value of the determination coefficient between the simulated and experimental heat release rate profiles is 0.98 for all the operations, and they are accurate enough for developing the combustion model. The partial least square regression is first imposed to relate the Wiebe parameters to the operating conditions. For the ability to solve the multiple correlations among the operating conditions, the prediction performance of the combustion model developed by partial least square regression is much higher than that by least square regression. The mean absolute percentage errors of the brake specific fuel consumption and maximum in-cylinder pressure simulated by the model are 0.284% and 1.39%, respectively. The model could accurately predict the engine performance and is sufficient to make the reasonable control strategies for the different Sequential Turbocharging systems.
机译:为顺序涡轮增压柴油发动机开发准确的燃烧模型是减少确定顺序涡轮增压系统控制策略过程中的时间消耗和昂贵的实验成本的有效方法。在本文中,具有两个顺序涡轮增压系统的船用柴油机的142个操作用于此研究。提出了一种新的方法来计算Wiebe参数的初始值和极限范围,并且该方法的使用可以有效地避免仅通过使用非线性最小二乘拟合就可以避免出现不可能的解或多重解。计算出的Wiebe参数可以达到很高的精度,在所有操作中,模拟和实验放热速率曲线之间的确定系数平均值为0.98,并且对于开发燃烧模型来说足够准确。首先施加偏最小二乘回归,以将Wiebe参数与操作条件相关联。为了能够解决运行条件之间的多重相关性,通过偏最小二乘回归开发的燃烧模型的预测性能要比最小二乘回归高得多。该模型模拟的制动器比油耗和最大缸内压力的平均绝对百分比误差分别为0.284%和1.39%。该模型可以准确地预测发动机性能,并且足以为不同的顺序涡轮增压系统制定合理的控制策略。

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