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Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

A New Method for Online Estimation of the Piston Maximum Temperature in Diesel-Natural Gas Dual Fuel Engine

[+] Author and Article Information
Youyao Fu

School of Geophysics and
Measurement-Control Technology,
East China University of Technology,
Nanchang 330013, China
e-mail: fuyouyao828@126.com

Bing Xiao

College of Automation Science and Engineering,
South China University of Technology,
Guangzhou 510640, China
e-mail: aubxiao@scut.edu.cn

Chengwei Zhang

Electrical Engineering College,
Guizhou Institute of Technology,
Guiyang 550003, China
e-mail: weiwei433410@sina.com

Jun Liu

School of Geophysics and
Measurement-Control Technology,
East China University of Technology,
Nanchang 330013, China
e-mail: liujun@ecit.cn

Jiangxiong Fang

School of Geophysics and
Measurement-Control Technology,
East China University of Technology,
Nanchang 330013, China
e-mail: fangchj2002@163.com

1Corresponding author.

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received November 5, 2015; final manuscript received November 17, 2017; published online February 27, 2018. Assoc. Editor: Jeffrey Naber.

J. Eng. Gas Turbines Power 140(6), 061507 (Feb 27, 2018) (8 pages) Paper No: GTP-15-1516; doi: 10.1115/1.4038836 History: Received November 05, 2015; Revised November 17, 2017

Diesel-natural gas dual fuel engine has gained increasing interesting in recent years because of its excellent power and economy. However, the reliability of the dual fuel engine does not meet the requirements of practical application. The piston maximun temperature (PMT) of the dual fuel engine easily exceeds the security border. In view of this, this paper proposes a method based on the lasso regression to estimate the PMT of the dual fuel engine, so as to real-timely monitor the health state of the dual fuel engine. Specifically, PMTs under some working conditions were offline acquired by the finite element analysis with ANSYS. A model is presented to describe the relationship between the PMT and some indirect engine variables, including NOx emission, excess air coefficient, engine speed, and inlet pressure, and the model parameters are optimized using the lasso regression algorithm, which can be easily implemented by the electronic control unit (ECU). Finally, the model is employed to real-timely estimate the PMT of the dual fuel engine. Experiments reveal that the proposed model produces satisfying predictions with deviations less than 10 °C.

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References

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Figures

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Fig. 1

Diesel-natural gas dual fuel engine control system

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Fig. 2

Simulations and measurements: (a) cylinder pressure and (b) heat release rate

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Fig. 3

3D solid model of piston

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Fig. 4

Finite element model of piston

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Fig. 5

Measured points distribution

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Fig. 6

Cylinder temperatures and heat transfer coefficients: (a) 1000 rpm, 106 kW, 11 deg BTDC, 70% DRR and (b) 1000 rpm, 106 kW, 14 deg BTDC, 80% DRR

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Fig. 7

Piston temperature fields: (a) 1000 rpm, 106 kW, 11 deg BTDC, 70% DRR and (b) 1000 rpm, 106 kW, 14 deg BTDC, 80% DRR

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Fig. 8

Cross validation flow chart

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Fig. 9

Cross validation error distributions: (a) ridge regression and (b) lasso regression

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Fig. 10

Element distributions of weight vector w: (a) least-squares model, (b) ridge model, and (c) lasso model

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