Closed-Loop Control of Spark Advance and Air-Fuel Ratio in SI Engines Using Cylinder Pressure

Yoon, Paljoo; Park, Seungbum; Sunwoo, Myoungho; Ohm, In-Yong; Yoon, Kum-Jung

doi:10.4271/2000-01-0933

Cited by 39 publications

(15 citation statements)

References 2 publications

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“…In their study, the maximum pressure and its location were estimated by using a multi-layer feedforward neural network. Their experimental results revealed a favorable agreement between the real MBT and the target air-fuel ratio [9]. Saravasti et al, and Park et al designed a neural network and a fuzzy logic-based controller to fix the location of maximum pressure at a desired value of the crank angle [10].…”

Section: Introductionmentioning

confidence: 86%

Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines

Kaleli

Ceviz

ERENTÜRK>

2015

Applied Thermal Engineering

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Section: Introductionmentioning

confidence: 86%

Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines

Kaleli

Ceviz

ERENTÜRK>

2015

Applied Thermal Engineering

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“…In an alternative approach, directly using a more expensive pressure sensor scheme rather than a lower cost spark-ionization system, Yoon et al [19] used NNs and the in-cylinder pressure to control SA and AFR. Using the pressure sensors to take pressure samples at 5 crank angles, the location of peak pressure and magnitude were estimated using the trained NN.…”

Section: Article In Pressmentioning

confidence: 99%

A transient virtual-AFR sensor using the in-cylinder ion current signal

Rivara¹,

Dickinson²,

Shenton³

2009

Mechanical Systems and Signal Processing

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“…Closed-loop combustion control on multi-cylinder IC engines offers an important way to improve fuel economy, and thereby reduce CO2 emissions [1][2] [3]. Combustion control also offers a potentially inexpensive route to reduce harmful tailpipe emissions, particularly for HD diesel [4].…”

Section: Introductionmentioning

confidence: 99%

A crank-kinematics-based engine cylinder pressure reconstruction model

Dunne

Bennett

2019

International Journal of Engine Research

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A new inverse model is proposed for reconstructing steady-state and transient engine cylinder pressure using measured crank kinematics. An adaptive nonlinear timedependent relationship is assumed between windowed-subsections of cylinder pressure and measured crank kinematics in a time-domain format (rather than in crank-angledomain). This relationship comprises a linear sum of four separate nonlinear functions of crank jerk, acceleration, velocity, and crank angle. Each of these four nonlinear functions is obtained at each time instant by fitting separate m-term Chebychev polynomial expansions, where the total 4m instantaneous expansion coefficients are found using a standard (over-determined) linear least-square solution method. A convergence check on the calibration accuracy shows this initially improves as more Chebychev polynomial terms are used, but with further increase, the over-determined system becomes singular. Optimal accuracy Chebychev expansions are found to be of degree m=4, using 90 or more cycles of engine data to fit the model. To confirm the model accuracy in predictive mode, a defined measure is used, namely the 'calibration peak pressure error'. This measure allows effective a priori exclusion of occasionally unacceptable predictions. The method is tested using varying speed data taken from a 3-cylinder DISI engine fitted with cylinder pressure sensors, and a high resolution shaft encoder. Using appropriately-filtered crank kinematics (plus the 'calibration peak pressure error'), the model produces fast and accurate predictions for previously unseen data. Peak pressure predictions are consistently within 6.5% of target, whereas locations of peak pressure are consistently within ± 2.7˚ CA. The computational efficiency makes it very suitable for real-time implementation. main-section pages (double-spaced) 33 references 15 FiguresNo Appendices

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Closed-Loop Control of Spark Advance and Air-Fuel Ratio in SI Engines Using Cylinder Pressure

Cited by 39 publications

References 2 publications

Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines

Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines

A transient virtual-AFR sensor using the in-cylinder ion current signal

A crank-kinematics-based engine cylinder pressure reconstruction model

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