Nonlinear modeling and identification of a spark ignition engine torque

Toğun, Necla; Bayseç, Sedat; Kara, Tolgay

doi:10.1016/j.ymssp.2011.06.010

Cited by 50 publications

(20 citation statements)

References 41 publications

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“…The performance of accuracies of the proposed Hammerstein model is also quite satisfactory with ( R = 0.8343 and RMSE = 2.8864 for SI engine torque). The results of the proposed ANFIS‐NARX model are compared with the Hammerstein model developed by Togun et al (Togun et al, ) with which the results are found to be in excellent agreement.…”

Section: Identification Resultsmentioning

confidence: 84%

“…The input–output data obtained from Togun et al (Figure ) include 2000 data for input and output (Togun et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…where u α is the throttle valve angle (rad. ),

{\overset{falseitaliċ}{m}}_{α}

is the air mass flow rate through the intake manifold (kg/s),

\overset{m}{true}

is the total mixture flow rate into the cylinders (kg/s), and K α is the valve constant (Togun et al, ).…”

Section: Simplified Mean Value Model For An Si Enginementioning

confidence: 99%

“…Several studies were conducted for the identification of automotive engines. The Hammerstein nonlinear system approach was used to identify the nonlinear system model of an SI engine torque (Togun, Bayseç, & Kara, 2012). Recurrent neural network was used to simulate the air-fuel ratio (AFR) dynamics in the intake manifold of an SI engine (Arsie, Pianese, & Sorrentino, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear identification of a spark ignition engine torque based on ANFIS with NARX method

Toğun

Bayseç

2016

Expert Systems

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Spark ignition (SI) engines have a nonlinear dynamic system with inherent uncertainties and unpredictable disturbances. The identification of a nonlinear system is vital in many fields of engineering. In this study, SI engine torque is identified from an input–output measurement. This study aims to propose a dynamic nonlinear model that uses an adaptive neuro‐fuzzy inference system and a nonlinear auto‐regressive with exogenous input structure to identify the dynamic nonlinear behavior of an SI engine. Considerable good performance is achieved using the adaptive neuro‐fuzzy inference system nonlinear auto‐regressive with exogenous input method. For model validation, the proposed method is compared with the more conventional identification approach called the Hammerstein method. The results show that the two methods are in excellent agreement. The Hammerstein model was chosen because its identification result of the SI system was studied previously by the author. Validation results prove that the ability of the proposed model can capture the highly nonlinear behavior of the SI system.

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Section: Identification Resultsmentioning

confidence: 84%

“…The input–output data obtained from Togun et al (Figure ) include 2000 data for input and output (Togun et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…where u α is the throttle valve angle (rad. ),

{\overset{falseitaliċ}{m}}_{α}

is the air mass flow rate through the intake manifold (kg/s),

\overset{m}{true}

is the total mixture flow rate into the cylinders (kg/s), and K α is the valve constant (Togun et al, ).…”

Section: Simplified Mean Value Model For An Si Enginementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear identification of a spark ignition engine torque based on ANFIS with NARX method

Toğun

Bayseç

2016

Expert Systems

Self Cite

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“…Moreover only a static behavior is taken into account with those maps. To overcome this drawback, some methods deal with a dynamic model of the engine to estimate the torque [12] [13]. Nevertheless problems appear due to the parameter identification techniques of nonlinear systems and requirements of important sets of data.…”

Section: Introductionmentioning

confidence: 99%

Discrete angular torque observer applicated to the engine torque and clutch torque estimation via a dual-mass flywheel

Losero¹,

Lauber²,

Guerra³

2015

2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)

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The interest in engine torque and clutch torque estimation is important in the automotive industry. They are determinant variables in engine and powertrain management like hybrid engine vehicle, automated transmission and energy saving strategies. An instantaneous brake engine torque and transmitted clutch torque estimation method based on discrete angular domain fuzzy observer using a torsion angle calculation is proposed in this paper. It is applied on a filtration device; the dual mass flywheel. The observer permits to obtain good experimental results of the engine torque and clutch torque estimation.

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Double closed‐loop control with adaptive strategy for automotive engine speed tracking system

Feng

Jiao

2017

Adaptive Control & Signal

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In order to improve the transient and static performances of an engine speed control system in a wide speed range, this paper presents an adaptive double closed-loop control strategy. The control scheme possesses intake manifold pressure inner closed-loop adaptive proportional-integral control and engine speed outer closed-loop adaptive proportional-integral control for achieving the tracking precision in a wide range of speed, as well as adaptive nonlinearity and feedforward compensators for overcoming parameter uncertainty and nonlinearity. The whole closed-loop system's stability and the speed tracking convergence are ensured theoretically by the Lyapunov stability theory and the LaSalle invariant principle. The effectiveness of the proposed control strategy is validated through the operation results on the simulator of a V6 engine exploited by the Research Committee of the Society of Instrument and Control Engineers of Japan. KEYWORDS adaptive update, double closed loop, engine speed control system, nonlinearity compensation, parameter uncertainty INTRODUCTIONWith increasing concern for cleaner environment and fuel conservation, the requirements for vehicle performance, such as drivability, fuel economy, and emissions, have become increasingly higher. For both conventional vehicles and developing hybrid electric vehicles (HEVs), the internal combustion engine (ICE) is indispensable and ubiquitous in nature; hence, control for engine operating performance has been a fundamental issue in the automotive control research field. 1,2 From the view of their essential roles, the engine control inputs contain the fuel injection regulating the stoichiometric air-to-fuel ratio accurately, the throttle angle managing the engine speed in the wide range, and the spark advance generating the engine torque. The speed control problem of the ICE through the angular position of the throttle valve has been one of the key concerns for idle speed, 3-6 cold start, 7 stop-go cruise, 8 and speed regulation 9-16 of the ICE in conventional vehicles and for wide-range speed tracking [17][18][19][20] of ICEs operating at higher speeds in HEVs.The core of engine speed control is to improve the performance of speed responses in any operating condition, thereby, to achieve the drivability and fuel consumption performances. Although many control approaches have been provided for engine speed systems, precise speed control for ICEs during transient operation modes is still a challenging issue. The challenge mainly stems from the uncertainties of the system behavior. While the engine is operating at a wide range of speed variation, the system's physical parameters are uncertain with the impacts of the air path, fuel efficiency, air-to-fuel ratio, spark timing, and so on. To solve the parameter uncertainty problem in the model-based control design of the engine speed system, a lot of efforts have been made from two aspects. On the one hand, the identification/calibration technique is adopted to obtain the physical parameters Int J Adapt Control...

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Nonlinear modeling and identification of a spark ignition engine torque

Cited by 50 publications

References 41 publications

Nonlinear identification of a spark ignition engine torque based on ANFIS with NARX method

Nonlinear identification of a spark ignition engine torque based on ANFIS with NARX method

Discrete angular torque observer applicated to the engine torque and clutch torque estimation via a dual-mass flywheel

Double closed‐loop control with adaptive strategy for automotive engine speed tracking system

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