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A model based system approach to innovative smart intake products: CO2 savings and specific performance

  • Jérôme Migaud
  • H. Bühl
  • Vincent Raimbault
  • A. Korn
  • D. Chalet
  • H. Mezher
  • Q. Montaigne
  • Pierre Emmanuel Prétot
Conference paper
Part of the Proceedings book series (PROCEE)

Abstract

On modern combustion engines, air induction systems are evermore evolving into more complicated elements with an objective to find the best trade-off between fuel consumption, pollutant emissions and engine performance. This pursuit has led to the emergence of the downsized turbocharged engine. For such an engine, it’s necessary to reinforce the low end torque. This is because, at low operating speeds and loads, the lack of enthalpy at the exhaust side causes a poor behavior of the turbocharger which leads to a poor boost pressure and consequently a deficit of engine performance. The proposed idea in this case would be to benefit from an optimized ‘smart’ air intake system to solve this issue while assuring other interesting functions as well. First, cylinder filling can be enhanced by assuring acoustic resonance conditions at the intake. The result is an increase of air flow leading to a better torque response and vehicle responsiveness. Pressure waves induced boosting can also help to reduce the thermal stress on the turbocharger as well as the size of the charge air cooler. Secondly, pressure waves can help to save energy by ‘de-throttling’ at part load operation on an SI engine. This has the effect of reducing the pumping loop and thus enhancing specific fuel consumption. Mechatronic integration into smart systems at the intake is necessary to achieve such goals. The Active Charge Air Duct (ACAD) and the active air intake manifold presented in this paper are innovative plastic products that aim to reduce fuel consumption. This is achieved through geometries with a high flexibility of thermoplastic processes.

Keywords

Pressure Wave Engine Speed Intake Valve Volumetric Efficiency Engine Test Bench 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Fachmedien Wiesbaden 2015

Authors and Affiliations

  • Jérôme Migaud
    • 1
  • H. Bühl
    • 3
  • Vincent Raimbault
    • 1
  • A. Korn
    • 3
  • D. Chalet
    • 2
  • H. Mezher
    • 2
  • Q. Montaigne
    • 2
  • Pierre Emmanuel Prétot
    • 2
  1. 1.MANN+HUMMEL France S.A.S.LavalFrance
  2. 2.École Centrale de NantesNantesFrance
  3. 3.MANN+HUMMEL GMBHLudwigsburgGermany

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