Fuzzy Logic Control of Diesel Combustion Phasing Using Ion Current Signal

2012 ◽  
Author(s):  
Tamer Badawy ◽  
Nassim Khaled ◽  
Naeim Henein
Keyword(s):  
Fuzzy Logic ◽  
Diesel Engines ◽  
Fuzzy Logic Controller ◽  
Combustion Process ◽  
Open Loop ◽  
Operating Conditions ◽  
Ion Current ◽  
Injection System ◽  
Loop Control ◽  
Engine Life

Diesel engines have to meet stringent emissions standards without penalties in performance and fuel economy. This necessitated the use of elaborate after treatment devices to reduce the tail pipe emissions. In order to decrease the demand on the after treatment devices, there is a need to reduce the emissions in the formation stage during combustion. This requires a precise control of the phasing of the combustion process. Currently, diesel engines are controlled by pre-set open loop schedules that require extensive, time consuming and costly laboratory tests and calibration tasks to meet the production target goals which are stricter than the emission standards. Such goals are set as a safe guard against the deterioration during engine life cycle. This paper presents an incremental fuzzy logic controller that adjusts the combustion phasing as per desired targets to meet production goals over the engine life period. An ion current/ glow plug sensor and its circuit are used to produce a signal indicative of different combustion parameters. Signal conditioning and filtering are applied to improve the quality of ion current. The algorithm developed in this paper optimizes the ion current feed back to increase its reliability for stable engine control while maintaining fast controller response, and high accuracy. Experiments are carried out on a four cylinder, turbo-charged, 4.5L heavy duty diesel engine equipped with a common rail injection system and an open ECU. The response of the controller is evaluated from experimental data obtained by running the engine under different steady, and transient operating conditions. The results demonstrate the ability of the closed-loop control system in achieving the desired combustion phasing.

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2001 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines

Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.

Enhanced Splash Models for High Pressure Diesel Sprays

2006 ◽  
Author(s):  
L. Allocca ◽  
L. Andreassi ◽  
S. Ubertini
Keyword(s):  
Diesel Engines ◽  
Second Harmonic ◽  
Laser Sheet ◽  
Combustion Process ◽  
Numerical Data ◽  
Ccd Camera ◽  
Operating Conditions ◽  
Injection System ◽  
Correct Operation ◽  
Common Rail Injection System

Mixture preparation is a crucial aspect for the correct operation of modern DI Diesel engines as it greatly influences and alters the combustion process and therefore, the exhaust emissions. The complete comprehension of the spray impingement phenomenon is a quite complete task and to completely exploit the phenomenon a mixed numerical-experimental approach has to be considered. On the modeling side, several studies can be found in the scientific literature but only in the last years complete multidimensional modeling has been developed and applied to engine simulations. Among the models available in literature, in this paper, the models by Bai and Gosman [1] and by Lee et al. [2, 3] have been selected and implemented in the KIVA-3V code. On the experimental side, the behavior of a Diesel impinging spray emerging from a common rail injection system (injection pressures of 80 MPa and 120 MPa) has been analysed. The impinging spray has been lightened by a pulsed laser sheet generated from the second harmonic of a Nd-YAG laser. The images have been acquired by a CCD camera at different times from the start of injection (SOI). Digital image processing software has enabled to extract the characteristic parameters of the impinging spray with respect to different operating conditions. The comparison of numerical and experimental data shows that both models should be modified in order to allow a proper simulation of the splash phenomena in modern Diesel engines. Then the numerical data in terms of radial growth, height and shape of the splash cloud, as predicted by modified versions of the models are compared to the experimental ones. Differences among the models are highlighted and discussed.

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2003 ◽  
Vol 10 (2) ◽  
pp. 81-95 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines ◽  
First Case

Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them has become difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control attractive.In this work a fuzzy logic controller is introduced with the idea of “split-horizon”; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent sub-controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FIE). Computer simulations are used to verify the performance of the controller. Three simulation cases are presented. In the first case, the crane is operated in the gantry (radial) mode in which the trolley moves along the jib while the jib is fixed. In the second case (rotary mode), the trolley moves along the jib and the jib rotates. In the third case, the trolley and jib are fixed while the load is given an initial disturbance. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing the maneuvers in relatively reasonable times.

A New Predictive ID Model for Advanced High Speed Direct Injection Diesel Engines

2004 ◽  
Author(s):  
Lurun Zhong ◽  
Naeim A. Henein ◽  
Walter Bryzik
Keyword(s):  
Diesel Engines ◽  
High Speed ◽  
Direct Injection ◽  
Combustion Process ◽  
Operating Conditions ◽  
Injection System ◽  
Injection Timing ◽  
Common Rail Injection System ◽  
Common Rail Injection ◽  
Starting Conditions

Advance high speed direct injection diesel engines apply high injection pressures, exhaust gas recirculation (EGR), injection timing and swirl ratios to control the combustion process in order to meet the strict emission standards. All these parameters affect, in different ways, the ignition delay (ID) which has an impact on premixed, mixing controlled and diffusion controlled combustion fractions and the resulting engine-out emissions. In this study, the authors derive a new correlation to predict the ID under the different operating conditions in advanced diesel engines. The model results are validated by experimental data in a single-cylinder, direct injection diesel engine equipped with a common rail injection system at different speeds, loads, EGR ratios and swirl ratios. Also, the model is used to predict the performance of two other diesel engines under cold starting conditions.

Enhanced Splash Models for High Pressure Diesel Spray

2006 ◽  
Vol 129 (2) ◽  
pp. 609-621 ◽  
Author(s):  
L. Allocca ◽  
L. Andreassi ◽  
S. Ubertini
Keyword(s):  
Diesel Engines ◽  
Yttrium Aluminum Garnet ◽  
Second Harmonic ◽  
Laser Sheet ◽  
Direct Injection ◽  
Combustion Process ◽  
Numerical Data ◽  
Operating Conditions ◽  
Injection System ◽  
Correct Operation

Mixture preparation is a crucial aspect for the correct operation of modern direct injection (DI) Diesel engines as it greatly influences and alters the combustion process and, therefore, the exhaust emissions. The complete comprehension of the spray impingement phenomenon is a quite complete task and a mixed numerical-experimental approach has to be considered. On the modeling side, several studies can be found in the scientific literature but only in the last years complete multidimensional modeling has been developed and applied to engine simulations. Among the models available in literature, in this paper, the models by Bai and Gosman (Bai, C., and Gosman, A. D., 1995, SAE Technical Paper No. 950283) and by Lee et al. (Lee, S., and Ryou, H., 2000, Proceedings of the Eighth International Conference on Liquid Atomization and Spray Systems, Pasadena, CA, pp. 586–593; Lee, S., Ko, G. H., Ryas, H., and Hong, K. B., 2001, KSME Int. J., 15(7), pp. 951–961) have been selected and implemented in the KIVA-3V code. On the experimental side, the behavior of a Diesel impinging spray emerging from a common rail injection system (injection pressures of 80 and 120MPa) has been analyzed. The impinging spray has been lightened by a pulsed laser sheet generated from the second harmonic of a Nd-yttrium-aluminum-garnet laser. The images have been acquired by a charge coupled device camera at different times from the start of injection. Digital image processing software has enabled to extract the characteristic parameters of the impinging spray with respect to different operating conditions. The comparison of numerical and experimental data shows that both models should be modified in order to allow a proper simulation of the splash phenomena in modern Diesel engines. Then the numerical data in terms of radial growth, height and shape of the splash cloud, as predicted by modified versions of the models are compared to the experimental ones. Differences among the models are highlighted and discussed.

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

scholarly journals Mat lab/simulink based fault analysis of pv grid with intelligent fuzzy logic control mppt

2018 ◽  
Vol 7 (2.12) ◽  
pp. 198
Author(s):  
Neeraj Priyadarshi ◽  
Amarjeet Kr. Sharma ◽  
Akash Kr. Bhoi ◽  
S N. Ahmad ◽  
Farooque Azam ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Fault Analysis ◽  
Operating Conditions ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Hysteresis Controller ◽  
Power Point ◽  
Pv Grid

This paper mainly presents the fault analysis of Photovoltaic (PV) grid power system. The fuzzy logic controller (FLC) based intelligent maximum power point tracking (MPPT) algorithm has been employed in this work. Moreover, the hysteresis controller has been implemented for inverter control. Simulation results based on MATLAB/SIMULINK justify the effectiveness of the proposed PV power system under different fault operating conditions. 

scholarly journals Feedback Loop Control Strategies of the Multi Dc Bus Link Voltages Using Adaptive Fuzzy Logic Control

2013 ◽  
Vol 64 (3) ◽  
pp. 143-151
Author(s):  
Farid Bouchafaa ◽  
Mohamed Seghir Boucherit ◽  
El Madjid Berkouk
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Harmonic Distortion ◽  
Power Converter ◽  
Voltage Source ◽  
Switching Frequency ◽  
Pwm Rectifier ◽  
Loop Control ◽  
Multilevel Inverters

Voltage source multilevel inverters have become very attractive for power industries in power electronics applications during last years. The main purposes that have led to the development of the studies about multilevel inverters are the generation of output voltage signals with low harmonic distortion; the reduction of switching frequency. A serious constraint in a multilevel inverter is the capacitor voltage-balancing problem. The unbalance of different DC voltage sources of five-level neutral point clamping (NPC) voltage source inverter (VSI) constitutes the major limitation for the use of this new power converter. In order to stabilize these DC voltages, we propose in this paper to study the cascade constituted by three phases five-level PWM rectifier, a clamping bridge and five-level NPC (VSI). In the first part, we present a topology of five-level NPC VSI, and then they propose a model of this converter and an optimal PWM strategy to control it using four bipolar carriers. Then in the second part, we study a five-level PWM rectifier, which is controlled by a multiband hysteresis strategy. In the last part of this paper, the authors study shows particularly the problem of the stability of the multi DC voltages of the inverter and its consequence on the performances of the induction motors (IM). Then, we propose a solution to the problem by employed closed loop regulation using PI regulator type fuzzy logic controller (FLC). The results obtained with this solution confirm the good performances of the proposed solution, and promise to use the inverter in high voltage and great power applications as electrical traction.

Fuzzy ignition timing control for a spark ignition engine

2000 ◽  
Vol 214 (3) ◽  
pp. 297-306 ◽  
Author(s):  
W Wang ◽  
E. C. Chirwa ◽  
E Zhou ◽  
K Holmes ◽  
C Nwagboso
Keyword(s):  
Fuzzy Logic ◽  
Detection System ◽  
Open Loop ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Coolant Temperature ◽  
Optimum Level ◽  
Ignition Timing ◽  
Timing Control ◽  
Engine Design

It is well known that the optimum ignition timing, which gives the maximum brake torque (MBT) for a given engine design, varies with the rate of flame development and propagation in the cylinder. This depends, among other factors, on engine design and operating conditions, and on the properties of the air-fuel mixture. In modern engines the ignition timing is generally controlled by fixed open-loop schedules as functions of engine speed, load and coolant temperature. It is desairable that this ignition timing can be adjusted to the optimum level producing the best torque to obtain minimum fuel consumption and maximum available power. This paper presents an ignition timing control system based on fuzzy logic theory. A pressure sensor system ws developed for the determination of combustion parameters and ignition control on a Ford 1600cm3 four-cylinder engine fuelled with natural gas. Several tests were carried out in optimizing the pressure detection system. The results obtained provide important information compatible with intelligent control of the engine using fuzzy logic technology. Moreover, tests carried out to date using this technology show good results that fit quite well with the original engine output torque characteristics.

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