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Study on high-altitude ceiling strategy of compression ignition aviation piston engines based on BP-NSGA II algorithm optimization

Author

Listed:
  • Chen, Guisheng
  • Sun, Min
  • Li, Junda
  • Wang, Jiguang
  • Shen, Yinggang
  • Liang, Daping
  • Xiao, Renxin

Abstract

This paper explores the influence of different turbocharging modes and multi-parameter coordinated control on the performance of compression-ignition (CI) aviation piston engine (APE). Firstly, based on a constructed one-dimensional thermodynamic model of a CI APE, the study investigates the effects of different turbocharging modes and combinations of high and low-pressure stage variable geometry turbines (VGT) on the operational performance of the engine. Subsequently, a novel stepwise approximate multi-objective optimization algorithm is proposed, combining backpropagation neural networks and the non-dominated sorting genetic algorithm II. This algorithm evaluates the influence of multiple control parameters on a two-stage turbocharged engine's performance, achieving a balance between fuel economy and reliability. The research shows that equipping CI APEs with twin VGT for supercharging can notably enhance engine performance, enabling the achievement of favorable power recovery objectives at an altitude of 8000 m. The proposed optimization algorithm exhibits strong predictability and reliability, substantially accelerating the computation speed and reducing the data volume by approximately 95%. At an engine speed of 3887 rpm, compared to the unoptimized conditions, the brake specific fuel consumption of the best scenario at altitudes of 2000 m, 4000 m, 6000 m, and 8000 m is reduced by 7.1%, 7.2%, 8.6%, and 6.9%, respectively.

Suggested Citation

  • Chen, Guisheng & Sun, Min & Li, Junda & Wang, Jiguang & Shen, Yinggang & Liang, Daping & Xiao, Renxin, 2024. "Study on high-altitude ceiling strategy of compression ignition aviation piston engines based on BP-NSGA II algorithm optimization," Energy, Elsevier, vol. 294(C).
    • Handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224007382
    DOI: 10.1016/j.energy.2024.130966
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    References listed on IDEAS

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    1. Li, Yaopeng & Jia, Ming & Han, Xu & Bai, Xue-Song, 2021. "Towards a comprehensive optimization of engine efficiency and emissions by coupling artificial neural network (ANN) with genetic algorithm (GA)," Energy, Elsevier, vol. 225(C).
    2. Wang, Huaiyu & Ji, Changwei & Shi, Cheng & Yang, Jinxin & Wang, Shuofeng & Ge, Yunshan & Chang, Ke & Meng, Hao & Wang, Xin, 2023. "Multi-objective optimization of a hydrogen-fueled Wankel rotary engine based on machine learning and genetic algorithm," Energy, Elsevier, vol. 263(PD).
    3. Serrano, José Ramón & Piqueras, Pedro & De la Morena, Joaquín & Gómez-Vilanova, Alejandro & Guilain, Stéphane, 2021. "Methodological analysis of variable geometry turbine technology impact on the performance of highly downsized spark-ignition engines," Energy, Elsevier, vol. 215(PB).
    4. Zhang, Huiyan & Shi, Lei & Deng, Kangyao & Liu, Sheng & Yang, Zhenhuan, 2020. "Experiment investigation on the performance and regulation rule of two-stage turbocharged diesel engine for various altitudes operation," Energy, Elsevier, vol. 192(C).
    5. Chen, Longfei & Ding, Shirun & Liu, Haoye & Lu, Yiji & Li, Yanfei & Roskilly, Anthony Paul, 2017. "Comparative study of combustion and emissions of kerosene (RP-3), kerosene-pentanol blends and diesel in a compression ignition engine," Applied Energy, Elsevier, vol. 203(C), pages 91-100.
    6. Zhou, Lei & Song, Yuntong & Hua, Jianxiong & Liu, Fengnian & Wei, Haiqiao, 2020. "Effects of miller cycle strategies on combustion characteristics and knock resistance in a spark assisted compression ignition (SACI) engine," Energy, Elsevier, vol. 206(C).
    7. Zhao, Jinxing, 2017. "Research and application of over-expansion cycle (Atkinson and Miller) engines – A review," Applied Energy, Elsevier, vol. 185(P1), pages 300-319.
    8. Wang, Xin & Ge, Yunshan & Yu, Linxiao & Feng, Xiangyu, 2013. "Effects of altitude on the thermal efficiency of a heavy-duty diesel engine," Energy, Elsevier, vol. 59(C), pages 543-548.
    9. Aygun, Hakan & Dursun, Omer Osman & Toraman, Suat, 2023. "Machine learning based approach for forecasting emission parameters of mixed flow turbofan engine at high power modes," Energy, Elsevier, vol. 271(C).
    10. Park, Sangjun & Cho, Jungkeun & Park, Jungsoo & Song, Soonho, 2017. "Numerical study of the performance and NOx emission of a diesel-methanol dual-fuel engine using multi-objective Pareto optimization," Energy, Elsevier, vol. 124(C), pages 272-283.
    11. Zhao, Zhenfeng & Cui, Huasheng, 2022. "Numerical investigation on combustion processes of an aircraft piston engine fueled with aviation kerosene and gasoline," Energy, Elsevier, vol. 239(PD).
    Full references (including those not matched with items on IDEAS)

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