Design improvements of an automotive air intake system

2020 ◽  
Author(s):  
Han-Bo Ronald Gan ◽  
Noor Zafirah Abu Bakar ◽  
Nur Fadzilah Shaikh Dawood ◽  
Muhammad Adam Rosli
Keyword(s):  
Intake System ◽  
Air Intake

Application of Box-Behnken Analysis on the Optimisation of Air Intake System for a Naturally Aspirated Engine

2020 ◽  
Vol 17 (2) ◽  
pp. 8029-8042
Author(s):  
N.S. Mustafa ◽  
N.H.A. Ngadiman ◽  
M.A. Abas ◽  
M.Y. Noordin
Keyword(s):  
Fuel Consumption ◽  
Fuel Efficiency ◽  
Engine Performance ◽  
Fuel Price ◽  
Design Expert ◽  
Intake System ◽  
Analysis Technique ◽  
System Components ◽  
Air Intake ◽  
High Influence

Fuel price crisis has caused people to demand a car that is having a low fuel consumption without compromising the engine performance. Designing a naturally aspirated engine which can enhance engine performance and fuel efficiency requires optimisation processes on air intake system components. Hence, this study intends to carry out the optimisation process on the air intake system and airbox geometry. The parameters that have high influence on the design of an airbox geometry was determined by using AVL Boost software which simulated the automobile engine. The optimisation of the parameters was done by using Design Expert which adopted the Box-Behnken analysis technique. The result that was obtained from the study are optimised diameter of inlet/snorkel, volume of airbox, diameter of throttle body and length of intake runner are 81.07 mm, 1.04 L, 44.63 mm and 425 mm, respectively. By using these parameters values, the maximum engine performance and minimum fuel consumption are 93.3732 Nm and 21.3695×10-4 kg/s, respectively. This study has fully accomplished its aim to determine the significant parameters that influenced the performance of airbox and optimised the parameters so that a high engine performance and fuel efficiency can be produced. The success of this study can contribute to a better design of an airbox.

A Novel Virtual Approach of Air Intake System Acoustic Sensitivity Study for Passenger Vehicle

2017 ◽  
Author(s):  
Muthukumar Arunachalam ◽  
Sankarasubramanian Thirukkotti ◽  
S Arunkumar ◽  
Abdul Haiyum
Keyword(s):  
Sensitivity Study ◽  
Passenger Vehicle ◽  
Intake System ◽  
Air Intake ◽  
Acoustic Sensitivity

AIR INTAKE SYSTEM FOR V6 ENGINES

2010 ◽  
Vol 15 (11) ◽  
pp. 56-61
Author(s):  
Thomas Karle ◽  
Steffen Muth ◽  
Klaus Hartmann ◽  
Wolfgang Pantle
Keyword(s):  
Intake System ◽  
Air Intake

Adaptation for Air-Intake System Throttle Control in a Gasoline Engine With Low-Pressure Exhaust-Gas Recirculation

2015 ◽  
Author(s):  
Mario Santillo ◽  
Suzanne Wait ◽  
Julia Buckland
Keyword(s):  
Feedback Control ◽  
Control Strategy ◽  
Gasoline Engine ◽  
Exhaust Gas Recirculation ◽  
Lookup Table ◽  
Exhaust Gas ◽  
Feed Forward ◽  
Intake System ◽  
Air Intake ◽  
Gas Recirculation

We investigate control strategies for traditional throttle-in-bore as well as low-cost cartridge-style throttle bodies for the air-intake system (AIS) throttle used in low-pressure exhaust-gas recirculation (LPEGR) on a turbocharged gasoline engine. Pressure sensors placed upstream and downstream of the AIS throttle are available as signals from the vehicle’s engine control unit, however, we do not use high-bandwidth feedback control of the AIS throttle in order to maintain frequency separation from the higher-rate EGR loop, which uses the downstream pressure sensor for feedback control. A design-of-experiments conducted using a feed-forward lookup table-based AIS throttle control strategy exposes controller sensitivity to part-to-part variations. For accurate tracking in the presence of these variations, we explore the use of adaptive feedback control. In particular, we use an algebraic model representing the throttle plate effective opening area to develop a recursive least-squares (RLS)-based estimation routine. A low-pass filtered version of the estimated model parameters is subsequently used in the forward-path AIS throttle controller. Results are presented comparing the RLS-based feedback algorithm with the feed-forward lookup table-based control strategy. RLS is able to adapt for part-to-part and change-over-time variabilities and exhibits an improved steady-state tracking response compared to the feed-forward control strategy.

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