IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i21p5656-d436673.html
   My bibliography  Save this article

Development and Application of Ion Current/Cylinder Pressure Cooperative Combustion Diagnosis and Control System

Author

Listed:
  • Denghao Zhu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Jun Deng

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Jinqiu Wang

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Shuo Wang

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Hongyu Zhang

    (Chinesisch-Deutsches Hochschulkolleg, Tongji University, Shanghai 201804, China)

  • Jakob Andert

    (Mechatronic Systems for Combustion Engines, RWTH Aachen University, 52074 Aachen, Germany)

  • Liguang Li

    (School of Automotive Studies, Tongji University, Shanghai 201804, China
    Chinesisch-Deutsches Hochschulkolleg, Tongji University, Shanghai 201804, China)

Abstract

The application of advanced technologies for engine efficiency improvement and emissions reduction also increase the occurrence possibility of abnormal combustions such as incomplete combustion, misfire, knock or pre-ignition. Novel promising combustion modes, which are basically dominated by chemical reaction kinetics show a major difficulty in combustion control. The challenge in precise combustion control is hard to overcome by the traditional engine map-based control method because it cannot monitor the combustion state of each cycle, hence, real-time cycle-resolved in-cylinder combustion diagnosis and control are required. In the past, cylinder pressure and ion current sensors, as the two most commonly used sensors for in-cylinder combustion diagnosis and control, have enjoyed a seemingly competitive relationship, so all related researches only use one of the sensors. However, these two sensors have their own unique features. In this study, the idea is to combine the information obtained from both sensors. At first, two kinds of ion current detection system are comprehensively introduced and compared at the hardware level and signal level. The most promising variant (the DC-Power ion current detection system) is selected for the subsequent experiments. Then, the concept of ion current/cylinder pressure cooperative combustion diagnosis and control system is illustrated and implemented on the engine prototyping control unit. One application case of employing this system for homogenous charge compression ignition abnormal combustion control and its stability improvement is introduced. The results show that a combination of ion current and cylinder pressure signals can provide richer and also necessary information for combustion control. Finally, ion current and cylinder pressure signals are employed as inputs of artificial neural network (ANN) models for combustion prediction. The results show that the combustion prediction performance is better when the inputs are a combination of both signals, instead of using only one of them. This offline analysis proves the feasibility of using an ANN-based model whose inputs are a combination of ion current and pressure signals for better prediction accuracy.

Suggested Citation

  • Denghao Zhu & Jun Deng & Jinqiu Wang & Shuo Wang & Hongyu Zhang & Jakob Andert & Liguang Li, 2020. "Development and Application of Ion Current/Cylinder Pressure Cooperative Combustion Diagnosis and Control System," Energies, MDPI, vol. 13(21), pages 1-21, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:21:p:5656-:d:436673
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/21/5656/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/21/5656/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seokwon Cho & Jihwan Park & Chiheon Song & Sechul Oh & Sangyul Lee & Minjae Kim & Kyoungdoug Min, 2019. "Prediction Modeling and Analysis of Knocking Combustion using an Improved 0D RGF Model and Supervised Deep Learning," Energies, MDPI, vol. 12(5), pages 1-25, March.
    2. Yang, Zhuyong & Miganakallu, Niranjan & Miller, Tyler & Worm, Jeremy & Naber, Jeffrey & Roth, David, 2020. "Comparing methods for improving spark-ignited engine efficiency: Over-expansion with multi-link cranktrain and high compression ratio with late intake valve closing," Applied Energy, Elsevier, vol. 262(C).
    3. Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.
    4. Steven Chu & Arun Majumdar, 2012. "Opportunities and challenges for a sustainable energy future," Nature, Nature, vol. 488(7411), pages 294-303, August.
    5. Zhu, Sipeng & Zhang, Kun & Deng, Kangyao, 2020. "A review of waste heat recovery from the marine engine with highly efficient bottoming power cycles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    6. Hüseyin Emre Doğan & Osman Akın Kutlar & Majid Javadzadehkalkhoran & Abdurrahman Demirci, 2019. "Investigation of Burn Duration and NO Emission in Lean Mixture with CNG and Gasoline," Energies, MDPI, vol. 12(23), pages 1-18, November.
    7. Wick, Maximilian & Bedei, Julian & Andert, Jakob & Lehrheuer, Bastian & Pischinger, Stefan & Nuss, Eugen, 2020. "Dynamic measurement of HCCI combustion with self-learning of experimental space limitations," Applied Energy, Elsevier, vol. 262(C).
    8. Wick, Maximilian & Bedei, Julian & Gordon, David & Wouters, Christian & Lehrheuer, Bastian & Nuss, Eugen & Andert, Jakob & Koch, Charles Robert, 2019. "In-cycle control for stabilization of homogeneous charge compression ignition combustion using direct water injection," Applied Energy, Elsevier, vol. 240(C), pages 1061-1074.
    9. Chao, Yuedong & Chen, Xinye & Deng, Jun & Hu, Zongjie & Wu, Zhijun & Li, Liguang, 2018. "Additional injection timing effects on first cycle during gasoline engine cold start based on ion current detection system," Applied Energy, Elsevier, vol. 221(C), pages 55-66.
    10. Gong, Changming & Yi, Lin & Zhang, Zilei & Sun, Jingzhen & Liu, Fenghua, 2020. "Assessment of ultra-lean burn characteristics for a stratified-charge direct-injection spark-ignition methanol engine under different high compression ratios," Applied Energy, Elsevier, vol. 261(C).
    11. Kumar, Madan & Shen, Tielong, 2017. "In-cylinder pressure-based air-fuel ratio control for lean burn operation mode of SI engines," Energy, Elsevier, vol. 120(C), pages 106-116.
    12. Vittorio Ravaglioli & Carlo Bussi, 2019. "Model-Based Pre-Ignition Diagnostics in a Race Car Application," Energies, MDPI, vol. 12(12), pages 1-12, June.
    13. Tsuboi, Seima & Miyokawa, Shinji & Matsuda, Masayoshi & Yokomori, Takeshi & Iida, Norimasa, 2019. "Influence of spark discharge characteristics on ignition and combustion process and the lean operation limit in a spark ignition engine," Applied Energy, Elsevier, vol. 250(C), pages 617-632.
    14. Ansari, Ehsan & Shahbakhti, Mahdi & Naber, Jeffrey, 2018. "Optimization of performance and operational cost for a dual mode diesel-natural gas RCCI and diesel combustion engine," Applied Energy, Elsevier, vol. 231(C), pages 549-561.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Jinqiu & Bedei, Julian & Deng, Jun & Andert, Jakob & Zhu, Denghao & Li, Liguang, 2021. "Detection of transient low-temperature combustion characteristics by ion current – The missing link for homogeneous charge compression ignition control?," Applied Energy, Elsevier, vol. 283(C).
    2. Ahmad, Zeeshan & Kaario, Ossi & Qiang, Cheng & Vuorinen, Ville & Larmi, Martti, 2019. "A parametric investigation of diesel/methane dual-fuel combustion progression/stages in a heavy-duty optical engine," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Al-Harbi, Ahmed A. & Alabduly, Abdullah J. & Alkhedhair, Abdullah M. & Alqahtani, Naif B. & Albishi, Miqad S., 2022. "Effect of operation under lean conditions on NOx emissions and fuel consumption fueling an SI engine with hydrous ethanol–gasoline blends enhanced with synthesis gas," Energy, Elsevier, vol. 238(PA).
    4. Schröder, Lukas & Hillenbrand, Thomas & Brüggemann, Dieter, 2024. "Evaluation of the combustion process of directly injected methane in a rapid compression machine with a laser-based ignition system and an electrical ignition system," Energy, Elsevier, vol. 289(C).
    5. Haruki Tajima & Takuya Tomidokoro & Takeshi Yokomori, 2022. "Deep Learning for Knock Occurrence Prediction in SI Engines," Energies, MDPI, vol. 15(24), pages 1-14, December.
    6. Kumano, Kengo & Akagi, Yoshihiko & Matohara, Shinya & Uchise, Yoshifumi & Yamasaki, Yudai, 2020. "Using an ion-current sensor integrated in the ignition system to detect precursory phenomenon of pre-ignition in gasoline engines," Applied Energy, Elsevier, vol. 275(C).
    7. Chen, Long Xiang & Xie, Mei Na & Zhao, Pan Pan & Wang, Feng Xiang & Hu, Peng & Wang, Dong Xiang, 2018. "A novel isobaric adiabatic compressed air energy storage (IA-CAES) system on the base of volatile fluid," Applied Energy, Elsevier, vol. 210(C), pages 198-210.
    8. Kale, Aneesh Vijay & Krishnasamy, Anand, 2023. "Experimental study of homogeneous charge compression ignition combustion in a light-duty diesel engine fueled with isopropanol–gasoline blends," Energy, Elsevier, vol. 264(C).
    9. Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
    10. Chen, Xuejun & Yang, Yongming & Cui, Zhixin & Shen, Jun, 2019. "Vibration fault diagnosis of wind turbines based on variational mode decomposition and energy entropy," Energy, Elsevier, vol. 174(C), pages 1100-1109.
    11. Muhammad Habib Ur Rehman & Luigi Coppola & Ernestino Lufrano & Isabella Nicotera & Cataldo Simari, 2023. "Enhancing Water Retention, Transport, and Conductivity Performance in Fuel Cell Applications: Nafion-Based Nanocomposite Membranes with Organomodified Graphene Oxide Nanoplatelets," Energies, MDPI, vol. 16(23), pages 1-11, November.
    12. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
    13. Sung-Fu Hung & Aoni Xu & Xue Wang & Fengwang Li & Shao-Hui Hsu & Yuhang Li & Joshua Wicks & Eduardo González Cervantes & Armin Sedighian Rasouli & Yuguang C. Li & Mingchuan Luo & Dae-Hyun Nam & Ning W, 2022. "A metal-supported single-atom catalytic site enables carbon dioxide hydrogenation," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    14. Zheng, Bobo & Xu, Jiuping & Ni, Ting & Li, Meihui, 2015. "Geothermal energy utilization trends from a technological paradigm perspective," Renewable Energy, Elsevier, vol. 77(C), pages 430-441.
    15. Mao, Guozhu & Zou, Hongyang & Chen, Guanyi & Du, Huibin & Zuo, Jian, 2015. "Past, current and future of biomass energy research: A bibliometric analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1823-1833.
    16. Luo, Rongrong & Wang, Liuwei & Yu, Wei & Shao, Feilong & Shen, Haikuo & Xie, Huaqing, 2023. "High energy storage density titanium nitride-pentaerythritol solid–solid composite phase change materials for light-thermal-electric conversion," Applied Energy, Elsevier, vol. 331(C).
    17. Ewa C. E. Rönnebro & Greg Whyatt & Michael Powell & Matthew Westman & Feng (Richard) Zheng & Zhigang Zak Fang, 2015. "Metal Hydrides for High-Temperature Power Generation," Energies, MDPI, vol. 8(8), pages 1-25, August.
    18. Chen, Dongfang & Pan, Lyuming & Pei, Pucheng & Huang, Shangwei & Ren, Peng & Song, Xin, 2021. "Carbon-coated oxygen vacancies-rich Co3O4 nanoarrays grow on nickel foam as efficient bifunctional electrocatalysts for rechargeable zinc-air batteries," Energy, Elsevier, vol. 224(C).
    19. Chang, Chih-Chang & Huang, Wei-Hao & Mai, Van-Phung & Tsai, Jia-Shiuan & Yang, Ruey-Jen, 2021. "Experimental investigation into energy harvesting of NaCl droplet flow over graphene supported by silicon dioxide," Energy, Elsevier, vol. 229(C).
    20. Luiz Almeida & Ana Soares & Pedro Moura, 2023. "A Systematic Review of Optimization Approaches for the Integration of Electric Vehicles in Public Buildings," Energies, MDPI, vol. 16(13), pages 1-26, June.

    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:gam:jeners:v:13:y:2020:i:21:p:5656-:d:436673. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.