Investigation of Ignition Specification for Lean Limit Expansion of
                    Pre-chamber Combustion

Yoneya, Naoki; Mitsufuji, Kenta; Kumano, Kengo; Sukegawa, Yoshihiro; Uchise, Yoshifumi; Jitsu, Hideo

doi:10.4271/03-16-04-0028

Misfire Detection Technology with Deep Neural Network Based on Ignition Coil Signals

Yoneya

¹

,

Amaya

²

,

Kumano

³

et al. 2023

SAE Int. J. Engines

0

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<div>For achieving high efficiency and low exhaust emissions, engines need to be operated near the limits of stable combustion, such as lean or exhaust gas recirculation (EGR) conditions. Sensing technologies of the combustion state by existing engine components are of high interest. And the utilization of voltage and current signals from ignition coils is discussed in this article. The discharge channel of an ignition spark is strongly affected by flow variation and spark plug surface conditions, and the behavior of discharge channel stretching and restrike event can vary greatly from cycle to cycle. As a result, the effects of flow velocity, temperature, pressure, and electrode surface resistance are compounded in the voltage-current response, making it difficult to accurately detect the combustion state for each cycle by a threshold judgment process using a single feature value.</div> <div>In this article, a method for inductively detecting misfires from voltage and current signals of ignition coils by applying deep learning image recognition is introduced. First, post-ignition for misfire detection is performed on the engine bench during the expansion stroke in an engine cycle, when the cylinder pressure is expected to differ between the combustion cycle and the ignition cycle, and the ignition coil voltage and current are measured. Next, a two-dimensional frequency distribution of voltage and current (discharge histogram) is created as an input image for deep learning, and the AlexNet model, which has been trained with more than one million images, is trained with images of the ignition and combustion cycles as a supervised learning. The accuracy of classification is then verified using a validation dataset. In addition, to making the deep learning model more explainable, the activation score distribution on the discharge histogram was visualized when the trained model judges the images, and the discharge characteristics that provided the basis for deep learning classifications were analyzed.</div>

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Impact of Passive Pre-Chamber Nozzle Diameter on Jet Formation Patterns and Dilution Tolerance in a Constant-Volume Optical Engine

Lee,

Iyer,

Wooldridge

et al. 2023

SAE Int. J. Engines

2

0

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<div>Pre-chamber jet ignition technologies have been garnering significant interest in the internal combustion engine field, given their potential to deliver shorter burn durations, increased combustion stability, and improved dilution tolerance. However, a clear understanding of the relationship between pre-chamber geometry, operating condition, jet formation, and engine performance in light-duty gasoline injection engines remains under-explored. Moreover, research specifically focusing on high dilution levels and passive pre-chambers with optical accessibility is notably scarce. This study serves to bridge these knowledge gaps by examining the influence of passive pre-chamber nozzle diameter and dilution level on jet formation and engine performance. Utilizing a modified constant-volume gasoline direct injection engine with an optically accessible piston, we tested three passive pre-chambers with nozzle diameters of 1.2, 1.4, and 1.6 mm, while nitrogen dilution varied from 0 to 20%. With the help of high-speed imaging, we captured pre-chamber jet formations and subsequent flame propagation within the main chamber. Our novel findings reveal that asymmetric temporal and spatial jet formation patterns arising from pre-chambers significantly impact engine performance. The larger-nozzle-diameter pre-chambers exhibited the least variation in jet formation due to their improved scavenging and main mixture filling processes, but had the slowest jet velocity and lowest jet penetration depth. At no dilution condition, the 1.2 mm-PC demonstrated superior performance attributed to higher pressure build-up in the pre-chamber, resulting in accelerated jet velocity and increased jet penetration depth. However, at high dilution condition, the 1.6 mm-PC performed better, highlighting the importance of scavenging and symmetry jet formation. This study emphasizes the importance of carefully selecting the pre-chamber nozzle diameter, based on the engine’s operating conditions, to achieve an optimal and balanced configuration that can improve both jet formation and jet characteristics, as well as scavenging.</div>

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Advanced Rapid Combustion Concept Using Autoignition Assisted Flame for High Compression Ratio SI Engines

Sasaki,

Hori,

Seto

et al. 2023

SAE Technical Paper Series

2

0

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<div class="section abstract"><div class="htmlview paragraph">To achieve higher thermal efficiency for spark- ignition (SI) engines, advanced rapid combustion technology under high compression ratio is needed. The results of single-cylinder preliminary engine tests using E.U. commercial fuel at 96 RON show that the higher the compression ratio, the faster the combustion speed. Additional engine test and computations using S5R five-component surrogate gasoline with reliable chemistry under various temperature and pressure conditions implied that the autoignition assisted flame played significant role under higher compression ratio conditions, i.e., high temperature and pressure conditions, where apparent increases in laminar flame speeds compared to conventional combustion.</div></div>

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Investigation of Ignition Specification for Lean Limit Expansion of Pre-chamber Combustion

Cited by 3 publications

References 0 publications

Misfire Detection Technology with Deep Neural Network Based on Ignition Coil Signals

Misfire Detection Technology with Deep Neural Network Based on Ignition Coil Signals

Impact of Passive Pre-Chamber Nozzle Diameter on Jet Formation Patterns and Dilution Tolerance in a Constant-Volume Optical Engine

Advanced Rapid Combustion Concept Using Autoignition Assisted Flame for High Compression Ratio SI Engines

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