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

基于离子电流传感器的高压缩比稀薄汽油燃烧闭环控制

• 批准号: 392430670
• 负责人: Professor Dr.-Ing. Jakob Andert
• 金额: --
• 依托单位: School of Automotive Studies
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/392430670?language=en
• 关键词: Ion; Current; Sensor; based; Closed

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.

稀薄燃烧为提高汽油发动机的能源效率提供了很大的潜力，特别是与进一步减少油门损失和更高的压缩比相结合。与火花点火稀燃相比，均质充量压缩点火（HCCI）燃烧可降低NOx原始排放高达99%，但稀燃对燃烧室内局部和全局参数的变化非常敏感，无法直接测量。因此，稀薄燃烧在可控性方面具有主要缺点，特别是如果使用HCCI燃烧模式。气缸充气状态的波动引起燃烧的周期性偏差，对效率和排放以及过程扰动产生强烈影响，直至失火。这强调了快速循环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传递关于气缸充气状态的附加信息，这可以改善稀薄燃烧的可控性。中间物种的形成对离子电流的影响需要在硬件和软件方面的新方法，尚未进行详细分析。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。对于高压缩比的火花点火燃烧，提前点火是一个具有挑战性的问题，需要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。为了积极预防这种现象，需要快速可靠地识别即将到来的提前点火。先进的分析弱离子电流信号被假定为提供额外的信息，气缸充电，并允许建立新的基于FPGA的在循环控制interventions.Analysis在频域与数字信号处理器是一个有前途的方法，利用在快速在循环控制算法，以稳定稀薄燃烧。在该项目中，申请人的目标是更深入地了解离子电流传感器信号与气缸充气中的潜在化学和物理效应以及由此产生的电导率之间的相关性。为了改进测量和信号预处理方法，结合在上海和亚琛的试验发动机上的调查，进行了详细的仿真。离子电流分析硬件设置适于提高信噪比。离子电流和气缸充气状态之间的识别相关性将用于在试验台上对基于FPGA的新循环控制算法进行可行性研究。

项目成果

Dynamic measurement with in-cycle process excitation of HCCI combustion: The key to handle complexity of data-driven control?

HCCI 燃烧循环过程激励的动态测量：处理数据驱动控制复杂性的关键？

• DOI: 10.1177/14680874221078264
• 发表时间: 2022
• 期刊: International Journal of Engine Research
• 影响因子: 2.5
• 作者: J. Bedei;M. Oberlies;. P. Schaber;D. Gordon;E. Nuss;L. Liguang;J. Andert
• 通讯作者: J. Andert

Cycle resolved control for HCCI engine load range expansion by combining ion current and pressure sensor

• DOI: 10.1016/j.proci.2020.09.003
• 发表时间: 2021-04-13
• 期刊: PROCEEDINGS OF THE COMBUSTION INSTITUTE
• 影响因子: 3.4
• 作者: Zhu, Denghao;Deng, Jun;Li, Liguang
• 通讯作者: Li, Liguang

Detection of transient low-temperature combustion characteristics by ion current – The missing link for homogeneous charge compression ignition control?

• DOI: 10.1016/j.apenergy.2020.116299
• 发表时间: 2020-12
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: Jinqiu Wang;Julian Bedei;J. Deng;J. Andert;Denghao Zhu;Liguang Li

Analysis of ion current signal during negative valve overlap of HCCI combustion with high compression ratio

• DOI: 10.1177/1468087420972899
• 发表时间: 2020-11
• 期刊: International Journal of Engine Research
• 影响因子: 2.5
• 作者: Maximilian Wick;Denghao Zhu;J. Deng;Liguang Li;J. Andert

Development and Application of Ion Current/Cylinder Pressure Cooperative Combustion Diagnosis and Control System

• DOI: 10.3390/en13215656
• 发表时间: 2020-10
• 期刊: Energies
• 影响因子: 3.2
• 作者: Denghao Zhu;J. Deng;Jinqiu Wang;Shuo Wang;Hongyu Zhang;J. Andert;Liguang Li