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Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

Author

Listed:
  • Yanting Du

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Guangdi Hu

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Shun Xiang

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Ke Zhang

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Hongxing Liu

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Feng Guo

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

Abstract

In order to estimate the diesel particulate filter (DPF) soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC) test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF). The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

Suggested Citation

  • Yanting Du & Guangdi Hu & Shun Xiang & Ke Zhang & Hongxing Liu & Feng Guo, 2018. "Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model," Energies, MDPI, vol. 11(2), pages 1-13, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:472-:d:132961
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    References listed on IDEAS

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    1. Kuwahara, T. & Nishii, S. & Kuroki, T. & Okubo, M., 2013. "Complete regeneration characteristics of diesel particulate filter using ozone injection," Applied Energy, Elsevier, vol. 111(C), pages 652-656.
    2. Anna, Petrenko, 2016. "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(1), March.
    3. Xiong, Rui & Sun, Fengchun & Chen, Zheng & He, Hongwen, 2014. "A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles," Applied Energy, Elsevier, vol. 113(C), pages 463-476.
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    Cited by:

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    2. Jaehwan Jang & Byungchae Min & Seongyool Ahn & Hyunjun Kim & Sangkyung Na & Jeongho Kang & Heehwan Roh & Gyungmin Choi, 2022. "Modeling Differential Pressure of Diesel Particulate Filters in Marine Engines," Energies, MDPI, vol. 15(10), pages 1-12, May.
    3. Priyanka & Sarla Pareek, 2023. "A sustainable inventory model for stochastic demand using innovative multi-item production system with reduced failure rate," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(3), pages 844-864, June.
    4. Mitali Sarkar & Biswajit Sarkar & Muhammad Waqas Iqbal, 2018. "Effect of Energy and Failure Rate in a Multi-Item Smart Production System," Energies, MDPI, vol. 11(11), pages 1-21, October.
    5. Irfanullah Khan & Jihed Jemai & Han Lim & Biswajit Sarkar, 2019. "Effect of Electrical Energy on the Manufacturing Setup Cost Reduction, Transportation Discounts, and Process Quality Improvement in a Two-Echelon Supply Chain Management under a Service-Level Constrai," Energies, MDPI, vol. 12(19), pages 1-32, September.
    6. Raj Kumar Bachar & Shaktipada Bhuniya & Santanu Kumar Ghosh & Biswajit Sarkar, 2022. "Controllable Energy Consumption in a Sustainable Smart Manufacturing Model Considering Superior Service, Flexible Demand, and Partial Outsourcing," Mathematics, MDPI, vol. 10(23), pages 1-29, November.

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