Research Papers

Nonlinear Estimation of Variables for Heat Release Calculation Using a Gradient Method

[+] Author and Article Information
Lianhao Yin

Department of Energy Sciences,
Lund University,
Lund 223 63, Sweden
e-mail: Lianhao.Yin@energy.lth.se

Gabriel Turesson

Department of Automatic Control,
Lund University,
Lund 223 63, Sweden
e-mail: Gabriel@control.lth.se

Rolf Johansson

Department of Automatic Control,
Lund University,
Lund 223 63, Sweden
e-mail: Rolf.Johansson@control.lth.se

Per Tunestål

Department of Energy Sciences,
Lund University,
Lund 223 63, Sweden
e-mail: Per.Tunestal@energy.lth.se

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received September 18, 2017; final manuscript received February 6, 2019; published online March 8, 2019. Assoc. Editor: Junmin Wang.

J. Dyn. Sys., Meas., Control 141(6), 061011 (Mar 08, 2019) (9 pages) Paper No: DS-17-1473; doi: 10.1115/1.4042877 History: Received September 18, 2017; Revised February 06, 2019

Advanced combustion such as the partially premixed combustion (PPC) is characterized by high energy efficiency. However, they are sensitive to the inlet condition and injection of a combustion engine. Therefore, it is essential to use combustion feedback. The accuracy of the feedback variables, derived from the cylinder pressure signal, is crucial for effective combustion feedback control. This paper proposes a nonlinear least-squares regression method to estimate the pressure offsets and variable polytropic exponent in heat release calculation automatically. The combustion feedback variables derived from the auto-tuned heat-release rate were applied to a heavy-duty compression ignition (CI) engine burning with gasoline fuel.

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Fig. 1

Heat-release rate with heat transfer loss of a typical PPC point [16]

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Fig. 2

Engine configuration

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Fig. 3

Illustration of the pressure signal from one cycle

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Fig. 4

Illustration of heat-release rate and cumulative heat-release rate as an average of 100 cycles

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Fig. 5

Estimate κ̂ in 100 cycles

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Fig. 7

Estimate κ̂ and in-cylinder temperature trace through the whole combustion period

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Fig. 8

Heat-release rate using three different methods

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Fig. 9

Cumulative heat-release rate. The dashed line is the total energy of the burned fuel. The three methods have the accuracy of 84%, 76%, and 98% in terms of the total energy of the burned fuel, respectively.

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Fig. 10

Combustion phasing

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Fig. 11

The end of the combustion timing and the combustion duration

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Fig. 12

Comparison between the linear regression and the proposed nonlinear regression method

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Fig. 13

Autocovariance of the estimation results



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