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Research Papers: Fuel Combustion

Auto-Ignition Control in Spark-Ignition Engines Using Internal Model Control Structure

[+] Author and Article Information
Jorge Duarte

Department of Mechanical Engineering,
Universidad del Norte,
Barranquilla 080007, Colombia;
Department of Mechanical Engineering,
Universidad Antonio Nariño,
Barranquilla 080008, Colombia
e-mail: jduartee@uninorte.edu.co

Jesús Garcia

Department of Mechanical Engineering,
Universidad del Norte,
Barranquilla 080007, Colombia
e-mail: jesusmg@uninorte.edu.co

Javier Jiménez

Department of Mechanical Engineering,
Universidad del Norte,
Barranquilla 080007, Colombia
e-mail: cabasa@uninorte.edu.co

Marco E. Sanjuan

Department of Mechanical Engineering,
Universidad del Norte,
Barranquilla 080007, Colombia
e-mail: msanjuan@uninorte.edu.co

Antonio Bula

Department of Mechanical Engineering,
Universidad del Norte,
Barranquilla 080007, Colombia
e-mail: abula@uninorte.edu.co

Jorge González

Department of Mechanical Engineering,
Universidad Antonio Nariño,
Barranquilla 080008, Colombia
e-mail: jorgegonzalez30@uan.edu.co

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received February 13, 2016; final manuscript received June 21, 2016; published online July 12, 2016. Assoc. Editor: Dr. Avinash Kumar Agarwal.

J. Energy Resour. Technol 139(2), 022201 (Jul 12, 2016) (11 pages) Paper No: JERT-16-1089; doi: 10.1115/1.4034026 History: Received February 13, 2016; Revised June 21, 2016

This paper analyzes the feasibility of applying model predictive control strategies for mitigation of the auto-ignition phenomenon, which affects the performance of spark-ignition internal combustion engines. The first part of this paper shows the implementation and experimental validation of a two-dimensional model, based on thermodynamic equations, to simulate operating conditions in engines fueled with natural gas. Over this validated model, several control strategies are studied in order to evaluate, through simulation analysis, which of these offer the best handling capacity of the auto-ignition phenomenon. In order to achieve this goal, multivariate control strategies are implemented for a simultaneous manipulation of the fuel/air ratio, the crank angle at ignition, and the inlet pressure. The controlled variable in this research is the temperature at the ignition point. This temperature is obtained through an estimation based on pressure in the combustion chamber at that point, which is located toward the end zone of the compression stroke. If the ignition temperature of the fuel–air mixture is reached during the compression process, then auto-ignition takes place. Proposed control strategies consist of maintaining the temperature in the ignition point below the fuel–air mixture auto-ignition temperature. The results show that auto-ignition is difficult to avoid using a single input–single output (SISO) strategy. However, a multiple input–single output (MISO) approach avoids the influence of the phenomenon without a significant impact over the engine's performance. Among the developed strategies, an approach based on model predictive control and feedforward control strategy shows the best performance, measured through the integral absolute error (IAE) index. These results open the possibility of new ways for improving the control capacity of auto-ignition phenomenon in engines compared to currently available feedback control systems.

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Figures

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Fig. 1

General scheme of the process

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Fig. 2

Two-zone model general scheme

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Fig. 3

Validation of the proposed model. λ = 1.45, pinlet = 1.01 bar, and SA = 23 deg before TDC (5.88 rad).

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Fig. 4

Internal model control scheme: (a) general scheme for an IMC strategy and (b) IMC strategy applied over the internal combustion engine

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Fig. 5

Step responses for FIT 3 identification method

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Fig. 6

Strategy I structure

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Fig. 7

Strategy II structure

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Fig. 8

Strategy III structure

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Fig. 9

Steady-state response of the internal combustion engine

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Fig. 10

Temperature profile for simulation

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Fig. 11

Process response to a change in the temperature intake

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Fig. 12

Responses obtained using a factorial experiment versus the levels used for the fuel–air ratio input variable

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Fig. 13

Responses obtained using a factorial experiment versus the levels used for the starting-angle input variable

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Fig. 14

Responses obtained using a factorial experiment versus the levels used for the inlet-pressure input variable

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Fig. 15

Ambient temperature profile used as disturbance for testing the control strategies

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Fig. 16

Performance given by all the control strategies implemented

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Fig. 17

Behavior of the manipulated variable N1 (fuel/air ratio) for each control strategy

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Fig. 18

Behavior of the manipulated variable N2 (spark angle) for each control strategy

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Fig. 19

Behavior of the manipulated variable N3 (intake pressure) for each control strategy

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Fig. 20

Pressure comparison between the most dissimilar performances in the proposed control strategies: (a) pressure difference between strategies I and III and (b) pressure variation for strategies I and III

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Fig. 21

Behavior of the strategy proposal versus typical PID loop

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