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Fuel consumption and emission characteristics in asymmetric twin-scroll turbocharged diesel engine with two exhaust gas recirculation circuits

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  • Zhu, Dengting
  • Zheng, Xinqian

Abstract

This paper is the first known presentation of an asymmetric twin-scroll turbocharged engine with two exhaust gas recirculation circuits for emission and energy improvements. The traditional asymmetric twin-scroll turbocharged engine has one exhaust gas recirculation circuit, which is simple in structure and can improve the trade-off between low fuel consumption and nitrogen oxide emissions. However, at the high-speed range, the turbine’s larger scroll has an exhaust pressure that is higher than the intake pressure, leading to poor fuel economy. A test bench experiment was performed to validate numerical models of the asymmetric twin-scroll turbocharged engine with one and two exhaust gas recirculation circuits. Based on the models, both the influences of critical turbine parameters (turbine asymmetry, efficiency and throat area) on engine emission and fuel consumption characteristics, and the EGR valves and the wastegate control strategy were studied, and they were different from the asymmetric twin-scroll turbocharged engine with one exhaust gas recirculation circuit. The maximum exhaust gas recirculation rate and fuel economy improvements were approximately 8.59% and 1.98%. The new technology of the asymmetric twin-scroll turbocharged engine with two exhaust gas recirculation circuits described in this report has the potential to provide substantial gains in engine emission and energy.

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  • Zhu, Dengting & Zheng, Xinqian, 2019. "Fuel consumption and emission characteristics in asymmetric twin-scroll turbocharged diesel engine with two exhaust gas recirculation circuits," Applied Energy, Elsevier, vol. 238(C), pages 985-995.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:985-995
    DOI: 10.1016/j.apenergy.2019.01.188
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    References listed on IDEAS

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    Cited by:

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    3. Jarosław Ziółkowski & Mateusz Oszczypała & Jerzy Małachowski & Joanna Szkutnik-Rogoż, 2021. "Use of Artificial Neural Networks to Predict Fuel Consumption on the Basis of Technical Parameters of Vehicles," Energies, MDPI, vol. 14(9), pages 1-23, May.
    4. Sasanka Katreddi & Arvind Thiruvengadam, 2021. "Trip Based Modeling of Fuel Consumption in Modern Heavy-Duty Vehicles Using Artificial Intelligence," Energies, MDPI, vol. 14(24), pages 1-12, December.

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