Noise Control for Internal Combustion Engine Exhaust Design Review – Week 5 Greg Wodzicki Kyle...
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Transcript of Noise Control for Internal Combustion Engine Exhaust Design Review – Week 5 Greg Wodzicki Kyle...
Noise Control for Internal Combustion Engine Exhaust
Design Review – Week 5
Greg Wodzicki
Kyle Desrosiers
Brad Fiedler
Chris VanWagenen
Agenda Introduction / Background Understanding the Problem and Current
Technology Courses of Action Course of Action Comparison Best Courses of Action Closing Questions
Introduction/Background
Background
Customer Needs
Design Objectives
Risk Assessment
Gantt Chart
FSAE Formula One Vehicle
Click icon to add picture
What year Vehicle is this?
Problem Background
FSAE rules dictate engine noise under 110dB. Current Passive Noise Control device (Glass
pack) holds engine sound from wide range above and below 110dB
Current technology is not tuned for optimal noise reduction or engine performance
Engine Exhaust
Noise
>110dB
Glass pack
Introduction / Background
Design Objectives
Utilize Active / Passive Noise Cancellation Technology to: Maintain engine output under FSAE limit of 110dB. Adhere to all FSAE Rules To not add significant weight to vehicle Maintain/Improve engine performance Lower Vehicle Center of Gravity
Engine Exhaust
Noise
<110dB
Active / Passive Noise
Cancellation
Introduction / Background
Performance Objective
Possible Performance Effects of Different Exhaust Technology: A – No Exhaust Tuning B – Traditional Exhaust Length Tuning C – Possible Active Noise Cancellation Improvement*
* Dependent on cancellation method
Introduction / Background
Risk Assesment
xxxxxxxxxx: xxxxxx
Introduction / Background
Project Plan
xxxxxxxxxx: xxxxxx
Introduction / Background
Understanding the Problem and Current Technology
Internal Combustion Engine
ICE Exhaust Acoustics
Tuning a Exhaust
Understanding ANC
Lawnmower Engine
Glass Pack Muffler
Turbo Muffler
Baffle Muffler
Understanding the 4 Stroke ICE
Engine
Exhaust
Noise
Understanding the Problem and Current Technology
Understanding Optimal Acoustics
Exhaust
Noise
NoiseTop Dead Center
Exhaust Stage
Pressure From Combustion
Pressure From Vacuum
Vacuum
Understanding the Problem and Current Technology
Calculating Tuned Exhaust Length
Exhaust
Noise
Engine
𝐿=𝑘∗ (𝐸𝑜∗𝑉 𝑠 )
𝑁
= Crankshaft Speed in RPM = Constant
Understanding the Problem and Current Technology
Understanding Active Noise Cancellation - 1 Superposition Harmonics
Understanding the Problem and Current Technology
Understanding Active Noise Cancellation - 2
Understanding the Problem and Current Technology
𝐴𝑒𝑖𝑤𝑡−𝑖𝑘𝑥
𝐵𝑒𝑖𝑤𝑡−𝑖 𝑘(𝐿¿ ¿𝑡−𝐿1)¿
+
Noise
Engine
ExhaustSpeakers
𝐿𝑡 𝐿1
+
+
Signal Equations:
Noise Reduction:
Glass Pack
Exhaust Travels through Pipe with Perforated Holes Sound Insulation Absorbs Sound Minimal Back Pressure Least Effective in Reducing Sound
NoiseEngin
eExhaust Glass
pack
Inner Pipe
Sound Insulation
Housing
Understanding the Problem and Current Technology
Turbo Muffler
NoiseEngin
eExhaust
Turbo Muffler
No Baffles Exhaust Forced to turn
back and forth Increases Exhaust
Length Increased Back
Pressure with each turn
Sound Insulation Absorbs Sound
Moderately Effective in Reducing Sound
Understanding the Problem and Current Technology
Baffle Muffler
NoiseEngin
eExhaust
Baffle Muffler
Reflects Exhaust Throughout Chamber
Reflections Cancel each other
Most Back Pressure created
Greatest Sound Reduction
Understanding the Problem and Current Technology
Lawnmower Engine
xxxxxxxxxx: xxxxxx
Introduction / Background
Courses of Action
Noise Reduction Techniques Explored
Signal Processing for ANC
Internal ANC with Microphone and Feedback
Noise
Courses of Action
Engine
Exhaust
<110dB
Speaker
Primary Microphone
Feedback Microphon
e
Speaker Signal
Controller
Exhaust in Speaker Chamber
NoiseEngin
eExhaust <110dB
Speaker
Primary Microphone
Feedback Microphon
e
Speaker Signal
Controller
Multiple Speaker with Error Microphone
Noise
Courses of Action
Engine
Exhaust
<110dB
Speakers
Primary Microphone
Feedback Microphon
e
Speaker Signal
Controller
Signal Generation:Digital Signal Processing
Courses of Action
Filtering Technique 1:Filtered-X Least Mean Squared Filter
Courses of Action