Control Oriented Model and Dynamometer Testing for a Single-Cylinder, Heated-Air HCCI Engine

Wang, Yanying; Makkapati, Satheesh; Janković, Mrdjan; Zubeck, Michael; Lee, Dong‐Hoon

doi:10.4271/2009-01-1129

Cited by 6 publications

(7 citation statements)

References 11 publications

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“…All the parameters in (1) and (2) were determined based on averaging the simulated flows over the intake stroke using the crank angle based HCCI engine model in [1]. The comparisons of W ivc and r ivc between the crank angle based HCCI engine model simulation data and the pumping flow maps from (1) and (2) for various loads, engine speeds, and throttles are shown in Fig.…”

Section: B Cycle Averaged Pumping Flowsmentioning

confidence: 99%

“…The crank angle of 50% fuel burned, θ CA50 can be approximated using a linear equation based on θ CA02 as suggested in [1] and shown in Fig. 5 θ…”

Section: Combustion Timing and Durationmentioning

confidence: 99%

“…This MVM is based on the crank-angle resolved HCCI model presented in [1]. In section 3, we show that the combustion duration, ∆θ comb , defined as the duration between the crank angle of 10 and 90% fuel burned, can be a good proxy for both combustion stability and fuel efficiency with respect to the covariance of indicated mean effective pressure (IMEP) and indicated specific fuel consumption (ISFC), respectively.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling and control of a heated air intake homogeneous charge compression ignition (HCCI) engine

Lee

Stefanopoulou

Makkapati

et al. 2010

Proceedings of the 2010 American Control Conference

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In this paper a statistical physics based mean value model (MVM) is introduced for a heated intake homogeneous charge compression ignition (HCCI) engine based on a previously developed crank angle resolved model [1] and validated. In this HCCI engine, regulation of combustion timing is based on manipulating the cylinder charge temperature through the cold and hot throttle actuators. This two-input and single-output (TISO) system offers an input redundancy which is utilized to separately account for the fast fuel loading changes and the slower variations in the hot inlet (heated air) temperatures via appropriate actuator authority allocation. All the available experimental data sets suggest that the combustion duration ∆θ comb between the crank angle of 10% and 90% fuel burned (θ CA10 and θ CA90 ) can be used as the combustion timing regulation variable. This choice is shown to guarantee both combustion stability and fuel efficiency in terms of covariance of indicated mean effective pressure (IMEP) and indicated specific fuel consumption (ISFC) respectively. Simulations of the linear controller with the nonlinear plant demonstrate the closed loop performance.

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Section: B Cycle Averaged Pumping Flowsmentioning

confidence: 99%

“…The crank angle of 50% fuel burned, θ CA50 can be approximated using a linear equation based on θ CA02 as suggested in [1] and shown in Fig. 5 θ…”

Section: Combustion Timing and Durationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling and control of a heated air intake homogeneous charge compression ignition (HCCI) engine

Lee

Stefanopoulou

Makkapati

et al. 2010

Proceedings of the 2010 American Control Conference

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show abstract

“…Homogeneous Charge Compression Ignition (HCCI) Engines are of significant interest to the automotive industry owing to their ability to reduce emissions and fuel consumption significantly compared to traditional spark ignition and compression ignition engines [2], [3], [4]. The highly efficient operation of HCCI is achieved using advanced control strategies such as exhaust gas recirculation (EGR) [5], variable valve timings (VVT) [6], intake charge heating [7] among others. Such complex manipulations of the system results in a highly nonlinear behavior [8] with a narrow region of stable operation [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines

2016

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In this article, a stochastic gradient based online learning algorithm for Extreme Learning Machines (ELM) is developed (SG-ELM). A stability criterion based on Lyapunov approach is used to prove both asymptotic stability of estimation error and stability in the estimated parameters suitable for identification of nonlinear dynamic systems. The developed algorithm not only guarantees stability, but also reduces the computational demand compared to the OS-ELM approach [1] based on recursive least squares. In order to demonstrate the effectiveness of the algorithm on a real-world scenario, an advanced combustion engine identification problem is considered. The algorithm is applied to two case studies: An online regression learning for system identification of a Homogeneous Charge Compression Ignition (HCCI) Engine and an online classification learning (with class imbalance) for identifying the dynamic operating envelope of the HCCI Engine. The results indicate that the accuracy of the proposed SG-ELM is comparable to that of the state-of-the-art but adds stability and a reduction in computational effort.

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“…Operation in HCCI offers substantial improvements in fuel economy over traditional spark ignition (SI) combustion, as well as the potential for ultra-low NOx emissions [1]. Several methods exist for enabling HCCI operation, such as intake air heating [2,3], exhaust gas recirculation (EGR) [4,5], or variable compression ratio [6]. This paper focuses on the EGR method, in which hot exhaust gases are mixed with the fresh charge to manipulate the charge's thermodynamic state, so that when compressed, the mixture auto-ignites with desirable combustion phasing.…”

Section: Introductionmentioning

confidence: 99%

Model-Based Feedback Control for an Automated Transfer Out of SI Operation During SI to HCCI Transitions in Gasoline Engines

Gorzelic¹,

Hellström²,

Stefanopoulou³

et al. 2012

Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Pred

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This paper takes a first step towards model-based feedback control for the transition between spark ignition (SI) and homogeneous charge compression ignition (HCCI) combustion modes by approaching the transfer out of SI operation during the SI into HCCI transition in a closed-loop control framework. The combustion mode switch is taken to be directly from SI to HCCI without an intermediate combustion mode between the two, and the HCCI phase of the transition is not addressed. The transfer out of SI operation is formulated as a multi-input, multi-output control problem with input and output constraints. A baseline feedback controller for the transfer is designed using linear quadratic regulator methods, and is tested in simulation on a nonlinear mean value engine model. A simple open-loop transition based on look-up table set points is included as well for comparison. The feedback controller shows the ability to complete the SI phase of the transition in a short number of cycles, while maintaining a minimal disturbance to the engine torque in comparison to the open-loop controller.

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Control Oriented Model and Dynamometer Testing for a Single-Cylinder, Heated-Air HCCI Engine

Cited by 6 publications

References 11 publications

Modeling and control of a heated air intake homogeneous charge compression ignition (HCCI) engine

Modeling and control of a heated air intake homogeneous charge compression ignition (HCCI) engine

Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines

Model-Based Feedback Control for an Automated Transfer Out of SI Operation During SI to HCCI Transitions in Gasoline Engines

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