AI Engine Sound Color Control via Dynamic RPM and Vibration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing engine sound color control systems for vehicles do not effectively combine auditory and visual effects to enhance the driving experience, as they rely on recorded virtual sound sources and virtual RPM controls that lack dynamic engine characteristics, limiting the audio-visual synergy and driver engagement.
Innovation Solution
An engine sound color control method using artificial intelligence that learns driving patterns to control virtual engine RPM and adjust sound volume in real-time based on engine vibration signals, integrating visual and auditory controls to create a harmonized audio-visual experience, including dynamic sound color changes and low-frequency noise reflection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If virtual sound source generation type is used to provide interior sound from recorded virtual sound source, then auditory effect is improved, but it becomes independent of dynamic characteristic of engine corresponding to actual driving of vehicle
Solution Approach 1:
The system dynamically adjusts the virtual sound source parameters based on real-time engine operating conditions including RPM, load, and acceleration rates. The auditory output transitions from static recorded sounds to dynamically generated sounds that adapt to changing engine characteristics, resolving the contradiction between providing reliable auditory feedback and adapting to dynamic engine behavior.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor engine dynamic characteristics and adjust the virtual sound source generation accordingly. Sensors detect actual engine parameters and feed this information back to the sound generation system, enabling the auditory output to reflect real-time engine behavior rather than relying on pre-recorded static sounds.
2Ease of operation
If virtual engine RPM type is used to create virtual effect of quick response misunderstanding effect, then fun-to-drive is improved, but it requires control of cluster that virtually rapidly progress engine RPM
Solution Approach 1:
The system merges the visual RPM display control with the auditory sound generation control into a unified system. Both the cluster display and sound output are driven by the same engine parameter inputs and control logic, eliminating the need for separate virtual RPM progression control systems while achieving coordinated audio-visual feedback that enhances driver engagement.
Solution Approach 2:
The control system is designed to serve multiple functions simultaneously: it generates visual RPM displays, produces auditory sound effects, and provides driver information all through a single integrated processing unit that receives engine parameters and distributes processed information to multiple output devices, reducing overall system complexity.
3Reliability
If artificial intelligence learns driving pattern and performs change speed visualization control using optimal visual extraction virtual RPM together with real-time sound control, then audio-visual synergy effect is maximized, but device complexity increases
Solution Approach 1:
The artificial intelligence system acts as an intermediary layer between raw engine sensor data and the audio-visual output devices. It processes engine parameters, learns driving patterns, and generates optimized control signals for both visual and auditory systems, coordinating their operation to achieve synergistic effects while keeping the individual output devices relatively simple.
Solution Approach 2:
The AI system continuously learns from driving patterns and automatically optimizes the audio-visual coordination without requiring manual intervention or complex external control systems. It self-adjusts parameters based on accumulated data, providing adaptive audio-visual synergy that improves over time while maintaining system simplicity through autonomous operation.
Data Source
AI summary
An engine sound color control method based on an engine dynamic characteristic with artificial intelligence is provided. The method maximizes audio-visual control through the audio-visual synergy effect by performing both of the visual control of the dash board by the artificial intelligence using the virtual engine revolution per minute based on the shifting event and driving pattern of a vehicle. In particular, the auditory control of the speaker is operated by the signal processing controller based on the virtual engine RPM in response to an engine vibration signal of the engine. Further, a driver is provided with rapid response with vehicle power performance control through a real-time audio-visual change regulated by the artificial intelligence.