Transient combustion timing management in controlled auto-ignition engine based on ion current signal

Hunicz, Jacek; Filipek, P.; Kordos, P.; Gęca, Michał; Rybak, Arkadiusz

doi:10.1109/ccsse.2017.8087955

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Among the research on fuels, the large share of gaseous fuels, such as LPG [19,20], natural gas [21], CNG [22], LNG [23,24] hydrogen feed systems [25], PEM fuel cells [26], and others [27][28][29], should be emphasized. In recent years, there has been a huge development in the field of internal combustion engines [30][31][32][33][34][35][36], the existing power supply systems for spark ignition engines [37][38][39][40], diesel engines [30,31,[41][42][43], battery electric vehicles [9,[44][45][46][47], and hybrid systems [48][49][50][51]. A completely different issue is autonomous vehicles (AV), which constitute a separate, quite extensive part of the transport sector and hence the great interest and multifaceted research in this field [52][53][54][55][56][57][58][59].…”

Section: Introductionmentioning

confidence: 99%

The Planning Process of Transport Tasks for Autonomous Vans—Case Study

et al. 2022

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Transport is an area that is developing at a tremendous pace. This development applies not only to electric and hybrid cars appearing more and more often on the road but also to those of an autonomous or semi-autonomous nature. This applies to both passenger cars and vans. In many different publications, you can find a description of a number of benefits of using automated guided vehicles (AGV) for logistics and technical tasks, e.g., in the workplace. An important aspect is the use of knowledge management and machine learning, i.e., artificial intelligence (AI), to design these types of processes. An important issue in the construction of autonomous vehicles is the IT connection of sensors receiving signals from the environment. These signals are data for deep learning algorithms. The data after IT processing enable the decision-making by AI systems, while the used machine learning algorithms and neural networks are also needed for video image analysis in order to identify and classify registered objects. The purpose of this article is to present and verify a mathematical model used to respond to vehicles’ demand for a transport service under set conditions. The optimal conditions of the system to perform the transport task were simulated, and the efficiency of this system and benefits of this choice were determined.

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Section: Introductionmentioning

confidence: 99%

The Planning Process of Transport Tasks for Autonomous Vans—Case Study

et al. 2022

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“…24–26 There have also been many studies on use of the IC signal for monitoring and closed-loop control of the combustion process in homogeneous charge compression ignition (HCCI) engines 27–36 and controlled auto-ignition (CAI) engines. 37,38 A recent proposed application regards the possibility of detecting precursor phenomena of pre-ignition. 39…”

Section: Introductionmentioning

confidence: 99%

“…[24][25][26] There have also been many studies on use of the IC signal for monitoring and closed-loop control of the combustion process in homogeneous charge compression ignition (HCCI) engines [27][28][29][30][31][32][33][34][35][36] and controlled auto-ignition (CAI) engines. 37,38 A recent proposed application regards the possibility of detecting precursor phenomena of pre-ignition. 39 The observation of Arrigoni et al 9 that the second IC peak occurs in proximity of the pressure peak suggested the possibility of closed-loop control of spark timing.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the reliability of ionization current measurement in estimating peak pressure angle in a spark ignition engine

Giglio¹,

Ragione²,

Gaeta³

et al. 2021

International Journal of Engine Research

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Ionization current measured at the spark plug during combustion in spark ignition engines has often been proposed to determine the crank-angle at combustion pressure peak, namely the peak pressure angle, for the purpose of regulating spark timing to attain maximum brake torque (MBT). The proposal is based on the assumption that agreement exists between peak pressure angle and the angular position of the ionization current second peak, although no one has ever proved it by an appropriate statistical analysis. The aim of this work, for the first time and by rigorous statistical methods, is to prove the agreement between Peak Pressure Angle and Ionization Current Second Peak Angle (ICSPA), without which a MBT control via ICSPA would be ineffective. Our experimental database consisted of about 9000 pairs of Peak Pressure Angle and Ionization Current Second Peak Angle values corresponding to 90 different operating conditions of a spark ignition engine. A two-sample comparison was first carried out between mean values of Peak Pressure Angle and Ionization Current Second Peak Angle, which showed a statistically significant difference between them. Then Bland-Altman analysis (Lancet, 1986), widely known and used for checking agreement between two different measurement methods, was conducted. It demonstrated that under almost all the experimental operating conditions, there was no agreement between the Ionization Current Second Peak Angle and the Peak Pressure Angle.

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“…These problems can be overcome by the application of ion sensing at individual cylinders [ 8 ]. This real-time λ determination method ensures sufficient accuracy (errors typically do not exceed 3%) [ 9 ], while the use of the same hardware offers the additional advantage of combustion timing determination [ 10 ]. For UEGO sensors, the relatively long feedback delay problem is usually solved by various adaptive compensation algorithms incorporating Smith predictors [ 11 , 12 ] or other feed-forward/feed-back systems [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Excess Air Ratio Management in a Diesel Engine with Exhaust Backpressure Compensation

Kasprzyk

Hunicz

Rybak

et al. 2020

Sensors

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The paper investigates the operation of a wideband universal exhaust gas oxygen (UEGO) sensor in a diesel engine under elevated exhaust backpressure. Although UEGO sensors provide the excess air ratio feedback signal primarily in spark ignition engines, they are also used in diesel engines to facilitate low-emission combustion. The excess air signal is used as an input for the fuel mass observer, as well as to run the engine in the low-emission regime and enable smokeless acceleration. To ensure a short response time and individual cylinder control, the UEGO sensor can be installed upstream of a turbocharger; however, this means that the exhaust gas pressure affects the measured oxygen concentration. Therefore, this study determines the sensor’s sensitivity to the exhaust pressure under typical conditions for lean burn low-emission diesel engines. Identification experiments are carried out on a supercharged single-cylinder diesel engine with an exhaust system mimicking the operation of the turbocharger. The apparent excess air measured with the UEGO sensor is compared to that obtained in a detailed exhaust gas analysis. The comparison of reference and apparent signals shows that the pressure compensation correlations used in gasoline engines do not provide the correct values for diesel engine conditions. Therefore, based on the data analysis, a new empirical formula is proposed, for which the suitability for lean burn diesel engines is verified.

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Transient combustion timing management in controlled auto-ignition engine based on ion current signal

Cited by 5 publications

References 10 publications

The Planning Process of Transport Tasks for Autonomous Vans—Case Study

The Planning Process of Transport Tasks for Autonomous Vans—Case Study

Assessment of the reliability of ionization current measurement in estimating peak pressure angle in a spark ignition engine

Excess Air Ratio Management in a Diesel Engine with Exhaust Backpressure Compensation

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