IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v320y2025ics036054422500948x.html

Multi-objective optimization of variable altitude high-dimensional compression-ignition aviation piston engine based on Kriging model and NSGA-III

Author

Listed:
  • Xu, Yuchen
  • Sun, Min
  • Chen, Guisheng
  • Xiao, Renxin
  • Gong, Hang
  • Yang, Jie
  • Yang, Sen

Abstract

The operation of compression-ignition aviation piston engines in high-altitude environments is prone to critical issues such as power degradation and insufficient thrust. The research and optimization of the rapid coordination mechanism between fuel and air are crucial for preventing power loss during high-altitude operation and improving the service ceiling of the engine. Based on the constructed one-dimensional thermodynamic model of a compression-ignition aviation piston engine (CI APE), the Kriging surrogate model and non-dominated sorting genetic algorithm (NSGA) are utilized to optimize the brake specific fuel consumption (BSFC), maximum pressure rise rate (MPRR), and the maximum cylinder pressure (Pmax), exploring the optimal fuel-air combination at different altitudes. Firstly, the Pearson correlation coefficient analysis method is employed to confirm variables, and Latin hypercube sampling is used to generate training model samples. Secondly, a Kriging surrogate model of the engine with BSFC, MPRR, and Pmax as objective functions is constructed, and its accuracy is validated. Finally, the NSGA-III is employed for multi-objective optimization. The results indicate that injection timing, compression ratio, high-pressure stage blade opening, and low-pressure stage blade opening have the most significant impact on engine performance. The constructed surrogate models exhibit good predictive accuracy, with coefficient of determination (R2) values all greater than 0.9. At altitudes of 2000 m, 4000 m, 6000 m, and 8000 m, compared to before optimization, the BSFC decreased by 10.1 %, 11.5 %, 12.7 %, and 12 %, respectively. Compared to the power at 2000 m altitude before optimization, the optimized engine can achieve approximately 85 % of the power recovery target at 8000 m altitude.

Suggested Citation

  • Xu, Yuchen & Sun, Min & Chen, Guisheng & Xiao, Renxin & Gong, Hang & Yang, Jie & Yang, Sen, 2025. "Multi-objective optimization of variable altitude high-dimensional compression-ignition aviation piston engine based on Kriging model and NSGA-III," Energy, Elsevier, vol. 320(C).
  • Handle: RePEc:eee:energy:v:320:y:2025:i:c:s036054422500948x
    DOI: 10.1016/j.energy.2025.135306
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422500948X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.135306?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Lu, Kangbo & Shi, Lei & Zhang, Huiyan & Chen, Ziqiang & Deng, Kangyao, 2023. "Theoretical and experimental study on performance improvement of diesel engines at different altitudes by adaptive regulation method of the two-stage turbocharging system," Energy, Elsevier, vol. 281(C).
    2. Xu, Zheng & Ji, Fenzhu & Ding, Shuiting & Zhao, Yunhai & Zhang, Xiangbo & Zhou, Yu & Zhang, Qi & Du, Farong, 2020. "High-altitude performance and improvement methods of poppet valves 2-stroke aircraft diesel engine," Applied Energy, Elsevier, vol. 276(C).
    3. Ma, Zetai & Xie, Wenping & Xiang, Hanchun & Zhang, Kun & Yang, Mingyang & Deng, Kangyao, 2023. "Thermodynamic analysis of power recovery of marine diesel engine under high exhaust backpressure by additional electrically driven compressor," Energy, Elsevier, vol. 266(C).
    4. Ramos, Ángel & García-Contreras, Reyes & Armas, Octavio, 2016. "Performance, combustion timing and emissions from a light duty vehicle at different altitudes fueled with animal fat biodiesel, GTL and diesel fuels," Applied Energy, Elsevier, vol. 182(C), pages 507-517.
    5. Zhang, Zhongjie & Peng, Qikai & Liu, Riulin & Dong, Surong & Zhou, Guangmeng & Liu, Zengyong & Zhao, Xumin & Yang, Chunhao & Wang, Zengquan & Xia, Xu, 2024. "A matching method for Twin-VGT systems under varying expansion ratios at high altitudes," Energy, Elsevier, vol. 289(C).
    6. 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).
    7. 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).
    8. 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).
    9. Xiao, Renxin & Liang, Daping & Ba, Tingjie & Sun, Min & Chen, Guisheng & Yao, Guozhong & Zheng, Yongming, 2024. "Integrated optimization of dedicated engine and energy management strategy for the plug-in hybrid commercial vehicle at high altitude," Energy, Elsevier, vol. 290(C).
    10. Jaliliantabar, Farzad & Ghobadian, Barat & Najafi, Gholamhassan & Mamat, Rizalman & Carlucci, Antonio Paolo, 2019. "Multi-objective NSGA-II optimization of a compression ignition engine parameters using biodiesel fuel and exhaust gas recirculation," Energy, Elsevier, vol. 187(C).
    11. Açıkel, Halil Hakan & Serdar Genç, Mustafa, 2018. "Control of laminar separation bubble over wind turbine airfoil using partial flexibility on suction surface," Energy, Elsevier, vol. 165(PA), pages 176-190.
    12. Motlagh, Tara Yazdani & Azadani, Leila N. & Yazdani, Kaveh, 2020. "Multi-objective optimization of diesel injection parameters in a natural gas/diesel reactivity controlled compression ignition engine," Applied Energy, Elsevier, vol. 279(C).
    13. Xiao, Dasheng & Lin, Zhifu & Yu, Aiyang & Tang, Ke & Xiao, Hong, 2024. "Data-driven method embedded physical knowledge for entire lifecycle degradation monitoring in aircraft engines," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    14. Arias Chao, Manuel & Kulkarni, Chetan & Goebel, Kai & Fink, Olga, 2022. "Fusing physics-based and deep learning models for prognostics," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    15. 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).
    16. 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).
    17. 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.
    18. Jia, Guohai & Gao, Sheng & Shu, Xiong & Ren, Bing & Zhang, Bin & Ma, Guangyu & Zhang, Jian & Liu, Hui & Li, Dongmei, 2024. "Multi-objective optimization of emission parameters of a diesel engine using oxygenated fuel and pilot injection strategy based on RSM-NSGA III," Energy, Elsevier, vol. 293(C).
    19. Ekici, Selcuk & Ayar, Murat & Orhan, Ilkay & Karakoc, Tahir Hikmet, 2024. "Cruise altitude patterns for minimizing fuel consumption and emission: A detailed analysis of five prominent aircraft," Energy, Elsevier, vol. 295(C).
    20. Zhang, Jiankun & Liu, Haihu, 2023. "Multi-objective optimization of aerodynamic and erosion resistance performances of a high-pressure turbine," Energy, Elsevier, vol. 277(C).
    21. Haifeng Liu & Junsheng Ma & Laihui Tong & Guixiang Ma & Zunqing Zheng & Mingfa Yao, 2018. "Investigation on the Potential of High Efficiency for Internal Combustion Engines," Energies, MDPI, vol. 11(3), pages 1-20, February.
    22. Zhang, Chunhua & Li, Yangyang & Liu, Zhentao & Liu, Jinlong, 2022. "An investigation of the effect of plateau environment on the soot generation and oxidation in diesel engines," Energy, Elsevier, vol. 253(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Jianli & Ren, Jiayi & Yang, Cheng & Xu, Zihan & Wang, Yaqi & Sun, Jiawen & Wu, Yunna, 2025. "A three-stage optimization planning model for the integrated energy service station from the sustainable perspective of energy-transportation-information-humanities," Energy, Elsevier, vol. 332(C).
    2. Zuo, Qingsong & Yang, Daliao & Shen, Zhuang & Kou, Chuanfu & Qin, Yufeng & Chen, Wei & Wang, Yong & Wang, Zhiqi & Guan, Qingwu, 2026. "Optimization of direct injection parameters for lean-burn hydrogen-ammonia engines using Kriging surrogate model coupled NSGA-II," Renewable Energy, Elsevier, vol. 256(PI).
    3. Yang, Langjian & Lei, Jilin & Wang, Dongfang & Deng, Xiwen & Wang, Baojian & Sun, Liang, 2025. "Experimental and numerical investigation on mixture formation, ignition, combustion and emission characteristics of aviation piston engines during cold-start under variable altitudes," Energy, Elsevier, vol. 341(C).
    4. Chen, Longfei & Zafar, Aaqib & Zhong, Shenghui & Pan, Kang & Wang, Minghua & Fan, Yukun & Zhang, Yang & Shi, Wentao & Xu, Zheng, 2025. "Sustainable aviation fuel blends in aircraft piston engine: Comparative analysis of 30 % vs. 50 % SAF on combustion performance and emission reduction," Energy, Elsevier, vol. 335(C).
    5. Yang, Qinghan & Wei, Mingliang & Su, Jie & Duan, Yu & Zhu, Jingyu, 2025. "Multi-objective optimization of hybrid agricultural powertrain via crowding-adaptive NSGA-II with dynamic population control," Energy, Elsevier, vol. 335(C).
    6. Chen, Guisheng & Dai, Ru & Kong, Weilong & Bi, Yuhua & Xiao, Renxin & Yang, Jie, 2025. "Influence of injection timing and water-to-fuel ratio coupling on combustion characteristics and piston thermal load of jet fuel engines at variable altitudes," Energy, Elsevier, vol. 335(C).
    7. Zhou, Yu & Li, Xueyu & Geng, Tai & Shao, Longtao & Xu, Zheng & Zhong, Zhiming & Zhu, Kun & Song, Yue & Ding, Shuiting, 2025. "Piston engine energy utilization for variable-altitude applications: A review of two-stage turbocharging technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Yang, Qinghan & Wei, Mingliang & Su, Jie & Duan, Yu & Zhu, Jingyu, 2025. "Multi-objective optimization of hybrid agricultural powertrain via crowding-adaptive NSGA-II with dynamic population control," Energy, Elsevier, vol. 335(C).
    3. Zhou, Yu & Li, Xueyu & Geng, Tai & Shao, Longtao & Xu, Zheng & Zhong, Zhiming & Zhu, Kun & Song, Yue & Ding, Shuiting, 2025. "Piston engine energy utilization for variable-altitude applications: A review of two-stage turbocharging technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).
    4. Yang, Langjian & Lei, Jilin & Wang, Dongfang & Deng, Xiwen & Wang, Baojian & Sun, Liang, 2025. "Experimental and numerical investigation on mixture formation, ignition, combustion and emission characteristics of aviation piston engines during cold-start under variable altitudes," Energy, Elsevier, vol. 341(C).
    5. Zhong, Lingfeng & Xin, Qianfan & Liu, Rui & Raihanul, Islam & Saiful, Islam MD. & Chen, Yufeng, 2025. "Visual multi-objective optimization of the performance of a two-stroke aviation piston engine with the predictive combustion model at different altitude based on 3D scavenging computation," Energy, Elsevier, vol. 335(C).
    6. Liu, Jinlong & Wang, Bosen & Meng, Zhongwei & Liu, Zhentao, 2023. "An examination of performance deterioration indicators of diesel engines on the plateau," Energy, Elsevier, vol. 262(PB).
    7. Chen, Longfei & Zafar, Aaqib & Zhong, Shenghui & Pan, Kang & Wang, Minghua & Fan, Yukun & Zhang, Yang & Shi, Wentao & Xu, Zheng, 2025. "Sustainable aviation fuel blends in aircraft piston engine: Comparative analysis of 30 % vs. 50 % SAF on combustion performance and emission reduction," Energy, Elsevier, vol. 335(C).
    8. Zhipeng Li & Qiang Zhang & Fujun Zhang & Hongbo Liang & Yu Zhang, 2023. "Investigation of Effect of Nozzle Numbers on Diesel Engine Performance Operated at Plateau Environment," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    9. Song, Yue & Zhou, Yu & Li, Xueyu & Zhong, Zhiming & Yan, Huansong & Xu, Zheng & Ding, Shuiting, 2025. "Investigation on cycle modes and energy distribution strategies of a novel combined cycle aviation engine," Energy, Elsevier, vol. 319(C).
    10. Song, Yue & Zhou, Yu & Zhao, Shuai & Du, Fa-rong & Li, Xue-yu & Zhu, Kun & Yan, Huan-song & Xu, Zheng & Ding, Shui-ting, 2024. "Cyclic coupling and working characteristics analysis of a novel combined cycle engine concept for aviation applications," Energy, Elsevier, vol. 301(C).
    11. Rajkumar, Sundararajan & Das, Arnab & Thangaraja, Jeyaseelan, 2022. "Integration of artificial neural network, multi-objective genetic algorithm and phenomenological combustion modelling for effective operation of biodiesel blends in an automotive engine," Energy, Elsevier, vol. 239(PA).
    12. Lu, Kangbo & Qiu, Hongjian & Chen, Ziqiang & Shi, Lei & Deng, Kangyao, 2023. "Environmental adaptability method for improving the cold start performance of the diesel engine based on pilot injection strategy," Energy, Elsevier, vol. 281(C).
    13. Serrano, José Ramón & Martín, Jaime & Piqueras, Pedro & Tabet, Roberto & Gómez, Javier, 2023. "Effect of natural and forced charge air humidity on the performance and emissions of a compression-ignition engine operating at high warm altitude," Energy, Elsevier, vol. 266(C).
    14. Wang, Bin & Xie, Fangxi & Li, Xiaoping & Jiang, Beiping & Su, Yan & Wang, Zhongshu & Liu, Yuhao & Liang, Zhendong, 2025. "Optical and simulation investigation of effect of jet-wall interaction on combustion performance of methanol pre-chamber turbulent jet ignition system," Applied Energy, Elsevier, vol. 385(C).
    15. Xu, Zheng & Ji, Fenzhu & Ding, Shuiting & Zhao, Yunhai & Zhang, Xiangbo & Zhou, Yu & Zhang, Qi & Du, Farong, 2020. "High-altitude performance and improvement methods of poppet valves 2-stroke aircraft diesel engine," Applied Energy, Elsevier, vol. 276(C).
    16. Basora, Luis & Viens, Arthur & Chao, Manuel Arias & Olive, Xavier, 2025. "A benchmark on uncertainty quantification for deep learning prognostics," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    17. Hai, Tao & Hussein Kadir, Dler & Ghanbari, Afshin, 2023. "Modeling the emission characteristics of the hydrogen-enriched natural gas engines by multi-output least-squares support vector regression: Comprehensive statistical and operating analyses," Energy, Elsevier, vol. 276(C).
    18. Reyes García-Contreras & Andrés Agudelo & Arántzazu Gómez & Pablo Fernández-Yáñez & Octavio Armas & Ángel Ramos, 2019. "Thermoelectric Energy Recovery in a Light-Duty Diesel Vehicle under Real-World Driving Conditions at Different Altitudes with Diesel, Biodiesel and GTL Fuels," Energies, MDPI, vol. 12(6), pages 1-18, March.
    19. Zhang, Huixian & Wei, Xiukun & Liu, Zhiqiang & Ding, Yaning & Guan, Qingluan, 2025. "Condition-based maintenance for multi-state systems with prognostic and deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    20. Li, Yuanfu & Chen, Yao & Hu, Zhenchao & Zhang, Huisheng, 2023. "Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:320:y:2025:i:c:s036054422500948x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.