Ion-Current Sensor based Closed-Loop Control of Lean Gasoline Combustion with High Compression Ratio

稀薄燃烧为提高汽油发动机的能源效率提供了巨大的潜力，特别是在进一步减少油门损失和提高压缩比的情况下。与传统的火花点火（SI）稀薄燃烧相比，均质装药压缩点火（HCCI）燃烧可以减少高达99%的NOx原始排放。一般来说，稀薄燃烧对燃烧室内无法直接测量的全局和局部参数的变化非常敏感。因此，稀薄燃烧在可控性方面有很大的缺点，特别是如果使用HCCI燃烧方式。气缸充能状态的波动导致燃烧的循环偏差，对效率和排放产生强烈影响，并对过程产生干扰，直至失火。这强调了快速周期内闭环控制算法的必要性，以主动稳定过程。申请人的研究假设是，来自离子电流传感器的信号可以提供有关气缸电荷状态的额外信息，从而提高稀薄燃烧的可控性。中间物质的形成对离子电流的影响需要在硬件和软件方面采用新的方法，目前还没有详细的分析。此外，用于解释离子电流传感器信号的硬件分析电路必须得到显著改进。需要一个系统的方法来确定最佳的电传感器布局和软件信号处理算法。对于以高压缩比为主的SI燃烧，气缸装药的预点火是一个具有挑战性的问题。为了积极预防这种现象，需要快速可靠地识别即将到来的预点火。对弱离子电流信号的高级分析可以提供有关气缸电荷的额外信息，并允许建立新的基于fpga的周期控制干预措施。利用数字信号处理器进行频域分析是一种很有前途的方法，可用于稳定稀薄燃烧的快速循环控制算法。在这个项目中，申请者的目标是更深入地了解离子电流传感器信号的相关性，以及在圆柱体电荷和由此产生的电导率中潜在的化学和物理效应。为了改进测量和信号预处理方法，结合上海和亚琛的试验发动机进行了详细的仿真。采用了离子电流分析硬件设置，提高了信噪比。离子电流与气缸电荷状态之间确定的相关性将用于在试验台对新的基于fpga的循环控制算法进行可行性研究。

Lean combustion offers a high potential for improvement of the energy efficiency of gasoline engines, particularly in combination with a further reduction of throttle losses and higher compression ratios. Homogenous Charge Compression Ignition (HCCI) combustion can reduce NOx raw emission by up to 99 %, when compared to conventional spark-ignition (SI) lean combustion.Generally speaking, lean combustion is very sensitive to changing global and local parameters in the combustion chamber that cannot be measured directly. Accordingly, lean combustion has major drawbacks in controllability, especially if the HCCI combustion mode is used. Fluctuations of the cylinders charge state cause cyclic deviations of the combustion with strong effects on efficiency and emissions and process disturbances up to misfiring. This underlines the necessity of fast in-cycle closed-loop control algorithms to actively stabilize the process. Research hypothesis of the applicants is, that signals from an ion current sensor can deliver additional information about the state of the cylinder charge that can improve the controllability of lean combustion. The effects of formation of intermediate species on the ion current require new approaches on the hard-and software side and have not yet been analyzed in detail. Additionally, the hardware analysis circuits that are used for interpretation of the ion current sensor signal have to be improved significantly. A systematic methodology is required to identify the optimum electrical sensor layout and the software signal processing algorithm.For SI combustion, predominantly with high compression ratios, pre-ignition of the cylinder charge is a challenging problem. For active prevention of this phenomena, a fast and reliable identification of an approaching pre-ignition is required. Advanced analysis of weak ion current signals is assumed to deliver additional information about the cylinder charge and allows to establish new FPGA-based in-cycle control interventions.Analysis in the frequency domain with digital signal processors is a promising approach for utilization in fast in-cycle control algorithms to stabilize lean combustion. In this project, the applicants target a deeper understanding about the correlations of the ion current sensors signal and the underlying chemical and physical effects in the cylinder charge and the resulting conductivity. To improve the measurement and signal preprocessing methodology, a detailed simulation is combined with investigations on test engines in Shanghai and Aachen. The ion current analysis hardware setup is adapted to improve the signal to noise ratio. The identified correlation between the ion current and cylinder charge state will be used to perform a feasibility study for new FPGA-based in-cycle control algorithms at the test bench.