Analysis and Detection Methodology of Knock Phenomenon in Gasoline Engines Based on Cylinder Pressure Sensors

Author(s):  
Wentao Zhang ◽  
Tong Wu ◽  
Lidong Dong ◽  
Wei Hao
2017 ◽  
pp. 279-296 ◽  
Author(s):  
Benedikt van Booven ◽  
Harry Schüle ◽  
Thorben Walder ◽  
Hermann Rottengruber

2019 ◽  
Vol 8 (1) ◽  
pp. 75-85 ◽  
Author(s):  
Dennis Vollberg ◽  
Dennis Wachter ◽  
Thomas Kuberczyk ◽  
Günter Schultes

Abstract. Different sensor concepts for time-resolved cylinder pressure monitoring of combustion engines are realized and evaluated in this paper. We distinguish a non-intrusive form of measurement outside the cylinder, performed by means of a force compression rod from intrusive, real in-cylinder measurement by means of pressure membrane sensors being exposed to the hot combustion process. The force compression rod has the shape of a sine wave with thinner zones equipped with highly sensitive foil strain gauges that experience a relatively moderate temperature level of 120 ∘C. The sensor rod delivers a relative pressure value that may be influenced by neighbour cylinders due to mechanical coupling. For the intrusive sensor type, two different materials for the membrane-type sensor element were simulated and tested, one based on the ceramic zirconia and the other based on stainless steel. Due to the higher thermal conductivity of steel, the element experiences only 200 ∘C while the zirconia element reaches 300 ∘C. Metallic chromium thin films with high strain sensitivity (gauge factor of 15) and high-temperature capability were deposited on the membranes and subsequently structured to a Wheatstone bridge. The pressure evolution can be measured with both types in full detail, comparable to the signals of test bench cylinder pressure sensors. For the preferential steel-based sensor type, a reliable laser-welded electrical connection between the thin films on the membrane and a copper wire was developed. The in-cylinder pressure sensors were tested both on a diesel test bench and on a gas-fired engine. On the latter, an endurance test with 20 million cycles was passed. Reliable cylinder pressure sensors with a minimum of internal components are thus provided. The signals will be processed inside the sensor housing to provide analysis and aggregated data, i.e. mass fraction burned (MFB50) and other parameters as an output to allow for smart combustion control.


2000 ◽  
Author(s):  
Mark C. Sellnau ◽  
Frederic A. Matekunas ◽  
Paul A. Battiston ◽  
Chen-Fang Chang ◽  
David R. Lancaster

Author(s):  
Jinli Wang ◽  
Fuyuan Yang ◽  
Minggao Ouyang ◽  
Ying Huang

Cylinder pressure based combustion state control is a direction that has drawn much attention in the field of internal combustion engine control, especially in the field of diesel HCCI (Homogeneous Charge Compression Ignition) research. In-cylinder pressure sensors have the potential to diagnose or even replace many traditional sensors, including camshaft and crankshaft sensors. This paper did research on engine synchronization method based on in-cylinder pressure signal. The research was based on a 4-cylinder high pressure common rail diesel engine equipped with 4 PSG (Pressure Sensor Glow Plug) type piezo-resistance cylinder pressure sensors, intended for HCCI research. Through theoretical analysis and experimental proof, methods and models for cylinder identification, engine phase estimation and engine speed estimation are given and further verified by experiments. Results show that cylinder pressure sensor could be used to identify cylinder instead of cam shaft sensor. The models for engine phase and speed estimation have been proved to have precision of 3° crank angle and 4.6rpm, respectively. The precision of engine phase and speed estimation provides a possibility for the engine to run if the crankshaft sensor fails, but more researches have to be carried out with respect to crankshaft sensor replacement.


Author(s):  
Ponti Fabrizio ◽  
Ravaglioli Vittorio ◽  
Cavina Nicolò ◽  
De Cesare Matteo

The increasing request for pollutant emissions reduction spawned a great deal of research in the field of combustion control and monitoring. As a matter of fact, newly developed low temperature combustion strategies for diesel engines allow obtaining a significant reduction both in particulate matter and NOx emissions, combining the use of high EGR rates with a proper injection strategy. Unfortunately, due to their nature, these innovative combustion strategies are very sensitive to in-cylinder thermal conditions. Therefore, in order to obtain a stable combustion, a closed-loop combustion control methodology is needed. Many works demonstrate that a closed-loop combustion control strategy can be based on real-time analysis of in-cylinder pressure trace that provides important information about the combustion process, such as start of combustion, center of combustion and torque delivered by each cylinder. Nevertheless, cylinder pressure sensors on-board installation is still uncommon, due to problems related to unsatisfactory measurement long term reliability and cost. This paper presents a newly developed approach that allows extracting information about combustion effectiveness through the analysis of engine vibrations. In particular, the developed methodology can be used to obtain an accurate estimation of the indicated quantities of interest combining the information provided by engine speed fluctuations measurement and by the signals coming from acceleration transducers mounted on the engine. This paper also reports the results obtained applying the whole methodology to a light-duty turbocharged common rail diesel engine.


2018 ◽  
Vol 204 ◽  
pp. 04001
Author(s):  
Nike Septivani ◽  
Byan Wahyu Riyandwita

Mathematical model for four-stroke gasoline engines based on a cylinder-by-cylinder engine modeling method that incorporates physical formulas such as engine geometry and empirical formulas such as combustion duration are applied in this study. In-cylinder pressure and temperature can be calculated for gasoline four-cycle engine. Modeling is done by treating each step in the cylinder as a volume control, solving the conservation equations of energy with submodules for combustion, heat transfer and dynamic analysis. Calculations in cycles are performed at each crank angle, so that the correct angle of ignition, variations in velocity, amount of intake mass and fuel burning speed can be predicted. Adjustment for the combustion parameter such as burn duration and form factor of the Wiebe function to increase the model accuracy was performed. It is shown that the optimization of the Wiebe function parameters able to improve the sum squared error of the engine pressure estimation by 58.17% compared to the result from generalized parameter functions, and the parameter of form factor and burn duration are influential by around twice of (1.86 and 2.55 times, respectively) the efficiency factor.


2020 ◽  
Author(s):  
Simon Haertl ◽  
Josef Kainz ◽  
Harry Schuele ◽  
Johannes Beer ◽  
Matthias Gaderer

2000 ◽  
Author(s):  
L. Peron ◽  
A. Charlet ◽  
P. Higelin ◽  
B. Moreau ◽  
J. F. Burq

2016 ◽  
Vol 18 (3) ◽  
pp. 256-272 ◽  
Author(s):  
Stuart Trimby ◽  
Julian F Dunne ◽  
Colin Bennett ◽  
Dave Richardson

Closed-loop combustion control in gasoline engines can improve efficiency, calibration effort, and performance using different fuels. Knowledge of in-cylinder pressures is a key requirement for closed-loop combustion control. Adaptive cylinder pressure reconstruction offers a realistic alternative to direct sensing, which is otherwise necessary as legislation requires continued reductions in CO2 and exhaust emissions. Direct sensing, however, is expensive and may not prove adequately robust. A new approach is developed for in-cylinder pressure reconstruction on gasoline engines. The approach uses time-delay feedforward artificial neural networks trained with the standard Levenberg–Marquardt algorithm. The same approach can be applied to reconstruction via measured crank kinematics obtained from a shaft encoder or measured engine cylinder block vibrations obtained from a production knock sensor. The basis of the procedure is initially justified by examination of the information content within measured data, which is considered to be equally important as the network architecture and training methodology. Key hypotheses are constructed and tested using data taken from a three-cylinder (direct injected spark ignition) engine to reveal the influence of the data information content on reconstruction potential. The findings of these hypotheses tests are then used to develop the methodology. The approach is tested by reconstructing cylinder pressure across a wide range of steady-state engine operation using both measured crank kinematics and block accelerations. The results obtained show a very marked improvement over previously published reconstruction accuracy for both crank kinematics and cylinder block vibration–based reconstruction using measurements obtained from a multi-cylinder engine. This article shows that by careful processing of measured engine data, a standard neural network architecture and a standard training algorithm can be used to very accurately reconstruct engine cylinder pressure with high levels of robustness and efficiency.


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