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Parameter estimation in non-linear models of pressure dynamics in CNG injection systems

机译:CNG注射系统压力动力学非线性模型中的参数估计

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Common rail injection systems in innovative gas engines require an accurate control of the rail pressure dynamics. This task is, in fact, combined with a precise setting of the opening/closing time intervals of electro-injectors to achieve a satisfactory metering of the ratio between gas and air, then a good performance that reduces pollution and consumption. To achieve a trade-off between model accuracy and control simplicity, an important issue is to optimize the model of the pressure dynamics in the main accumulation volumes. This paper reports preliminary results in estimating the optimal parameters of a non-linear model by two different techniques. First delays in the main variables are estimated by a particle swarm optimization. Then, time-variability of model parameters is investigated.
机译:创新燃气发动机中的共轨注射系统需要准确控制轨道压力动力学。事实上,该任务结合了电气喷射器的开口/关闭时间间隔的精确设置,以实现气体和空气之间的比率的令人满意的计量,然后是降低污染和消费的良好性能。为了在模型准确性和控制简单之间实现权衡,重要的问题是优化主要累积体积中的压力动力学模型。本文报告了通过两种不同技术估计非线性模型的最佳参数的初步结果。主要变量中的第一延迟由粒子群优化估算。然后,研究了模型参数的时间可变性。

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