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Performance optimization through response surface methodology of an integrated coal gasification and CI engine fuelled with diesel and low-grade coal-based producer gas

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  • Singh, Deepak Kumar
  • Tirkey, Jeewan Vachan

Abstract

The efficient and optimum utilization of energy resources could bring an encouraging effect on our well-being, atmosphere, and economy. The purpose of the present study is to determine the optimum engine operating condition of dual fuelled engines using low grade coal-based producer gas (PG) and diesel. To do this, variation of gasifier equivalence ratio, engine compression ratio, and engine load has been considered as Gasifier-IC engine input variables to optimize the response of engine performance and emissions using response surface methodology (RSM). The optimization of input variables is mainly attributed to maximize brake power (BP), brake thermal efficiency (BTE), and minimize the brake specific fuel consumption (BSFC) and exhaust emission (CO, UHC, CO2, and NOx). In the experiment, a total of 48 number of the experimental matrix were executed to perform RSM optimization and ANOVA sensitivity test. RSM result reveals that the optimal values of independent parameters of equivalence ratio, compression ratio, and engine load are 0.12, 17.01, and 12 kg respectively. The corresponding optimal repose values of BP, BTE, BSFC, CO, UHC, CO2, and NO were observed to the value of 3.54 kW, 28.23%, 0.38 kg/kWh, 0.0231 (% vol), 4.2539 (ppm), 0.9569 (vol %), and 9.6958 ppm respectively. Maximum diesel saving at compression ratio (CR) 16, 17, and 18 observed was 14.38%, 22.48%, and 49.05% respectively using Dual fuel mode.

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  • Singh, Deepak Kumar & Tirkey, Jeewan Vachan, 2022. "Performance optimization through response surface methodology of an integrated coal gasification and CI engine fuelled with diesel and low-grade coal-based producer gas," Energy, Elsevier, vol. 238(PC).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pc:s0360544221022301
    DOI: 10.1016/j.energy.2021.121982
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    6. Tirkey, Jeewan Vachan & Kumar, Ajeet & Singh, Deepak Kumar, 2022. "Energy consumption, greenhouse gas emissions and economic feasibility studies of biodiesel production from Mahua (Madhuca longifolia) in India," Energy, Elsevier, vol. 249(C).
    7. Alruqi, Mansoor & Sharma, Prabhakar & Ağbulut, Ümit, 2023. "Investigations on biomass gasification derived producer gas and algal biodiesel to power a dual-fuel engines: Application of neural networks optimized with Bayesian approach and K-cross fold," Energy, Elsevier, vol. 282(C).
    8. Wang, Huaiyu & Ji, Changwei & Yang, Jinxin & Wang, Shuofeng & Ge, Yunshan, 2022. "Towards a comprehensive optimization of the intake characteristics for side ported Wankel rotary engines by coupling machine learning with genetic algorithm," Energy, Elsevier, vol. 261(PB).
    9. Zardoya, Ander Ruiz & Lucena, Iñaki Loroño & Bengoetxea, Iñigo Oregui & Orosa, José A., 2022. "Research on an internal combustion engine with an injected pre-chamber to operate with low methane number fuels for future gas flaring reduction," Energy, Elsevier, vol. 253(C).
    10. Sharma, Prabhakar & Bora, Bhaskor J., 2023. "Modeling and optimization of a CI engine running on producer gas fortified with oxyhydrogen," Energy, Elsevier, vol. 270(C).

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