System and method for controlling engine tone by artificial intelligence based on sound index of vehicle

US11049489B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11049489-B2
Application numberUS-201916692271-A
CountryUS
Kind codeB2
Filing dateNov 22, 2019
Priority dateDec 13, 2018
Publication dateJun 29, 2021
Grant dateJun 29, 2021

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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A system for controlling an engine tone by an artificial intelligence based on a sound quality index of a vehicle may include a sound output device for generating a reinforcing sound to reinforce an engine sound of the vehicle; an engine characteristic measurement sensor for measuring sound source characteristics of the engine sound; an interior noise measurement sensor for detecting interior noise of the vehicle; a signal processing controller that receives signals from the engine characteristic measurement sensor in real time and controls the sound output device such that the engine sound reaches a target tone; and a tone control operation unit connected to the signal processing controller to optimize the sound quality index such that the engine sound reaches the target tone through the artificial intelligence.

First claim

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What is claimed is: 1. A system for controlling an engine tone by an artificial intelligence based on a sound quality index of a vehicle, comprising: a sound output device for generating a reinforcing sound to reinforce an engine sound of the vehicle; an engine characteristic measurement sensor for measuring sound source characteristics of the engine sound; an interior noise measurement sensor for detecting interior noise of the vehicle; a signal processing controller that receives signals from the engine characteristic measurement sensor in real time and controls the sound output device such that the engine sound reaches a target tone; and a processor connected to the signal processing controller to optimize the sound quality index such that the engine sound reaches the target tone through the artificial intelligence wherein the sound quality index is the target tone corresponding to a driving performance sound, wherein the processor performs real-time active control of the engine tone based on deep learning, wherein the active control based on the deep learning determines and outputs an order array and an order level as factors for controlling the target tone based on a target tone requested by a driver and the measured interior noise, wherein the order array is an array of frequencies and the order level is magnitudes of the frequencies of the order array, and wherein the order array and the order level are determined as necessary components of an order, and the necessary components of the order are extracted based on a fast Fourier transform (FFT) analysis. 2. The system according to claim 1 , wherein the signal processing controller further receives at least one of vehicle driving information emerged through controller area network (CAN) communication or information of the interior noise measured by a microphone. 3. The system according to claim 1 , wherein the signal processing controller outputs an engine tone calculated by the processor through an interior audio. 4. The system according to claim 1 , wherein the active control based on the deep learning determines the order array and the order level as the factors for controlling the target tone based on the target tone requested by the driver and the measured interior noise with respect to a noise source required to be reduced, and controls an unnecessary frequency band to be reduced. 5. The system according to claim 1 , wherein the sound quality index is any one of a powerful index, a pleasant index, a dynamic index, or a sporty index and represents a desired driving mode to be selected by the driver. 6. The system according to claim 1 , wherein the sound output device is at least one of a speaker in an engine room, a speaker in the vehicle interior, or a speaker outside the vehicle. 7. The system according to claim 1 , further comprising a proportional-integral-differential (PID) controller for controlling the sound output device such that the engine sound is reinforced by the reinforcing sound due to output of the engine tone. 8. The system according to claim 1 , wherein the reinforcing sound and the target tone are stored as data and reinforcing the engine sound is implemented based on the stored data. 9. The system according to claim 8 , wherein the stored data is active sound design (ASD). 10. The system according to claim 1 , wherein information of the sound source characteristics of the engine sound is an engine noise characteristic of at least one of engine vibration, combustion pressure, boost pressure, or exhaust pressure. 11. The system according to claim 2 , wherein the vehicle driving information is an engine noise characteristic of at least one of vehicle speed, pedaling, engine speed, or a driving mode. 12. The system according to claim 1 , wherein input variables of the artificial intelligence comprise at least one of plural vehicle sound characteristics, a target tone requested by the driver, and a driving pattern of the driver. 13. A method for controlling an engine tone by an artificial intelligence based on a sound quality index of a vehicle using the system of claim 1 , comprising: outputting a sound having an engine tone calculated by a signal processing controller based on at least one of vehicle driving information, engine noise characteristic information, or interior noise information, wherein the signal processing controller performs optimizing an index of the sound based on the artificial intelligence. 14. The method according to claim 13 , wherein the sound quality index is output as output variables of the artificial intelligence when an order array of engine speed and an order level of engine speed are changed. 15. The method according to claim 13 , wherein a control value satisfying the sound quality index is output in the vehicle interior through a speaker. 16. The method according to claim 13 , wherein the output engine sound of the vehicle interior is monitored to calculate a changed sound quality index, and feedback control is performed again. 17. The method according to claim 13 , wherein the engine noise characteristic information is an engine noise characteristic of at least one of engine vibration, combustion pressure, boost pressure, or exhaust pressure. 18. The method according to claim 13 , wherein the vehicle driving information is an engine noise characteristic of at least one of vehicle speed, pedaling, engine speed, or a driving mode. 19. The method according to claim 13 , input variables of the artificial intelligence comprise at least one of plural vehicle sound characteristics, a target tone requested by the driver, and a driving pattern of the driver.

Assignees

Inventors

Classifications

  • Neural networks · CPC title

  • by using a self-diagnostic function or a malfunction prevention function, e.g. detecting abnormal output levels · CPC title

  • Arrangements for fixing loudspeaker transducers, e.g. in a box, furniture · CPC title

  • for comparison or discrimination · CPC title

  • F02D29/02Primary

    peculiar to engines driving vehicles; peculiar to engines driving variable pitch propellers · CPC title

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What does patent US11049489B2 cover?
A system for controlling an engine tone by an artificial intelligence based on a sound quality index of a vehicle may include a sound output device for generating a reinforcing sound to reinforce an engine sound of the vehicle; an engine characteristic measurement sensor for measuring sound source characteristics of the engine sound; an interior noise measurement sensor for detecting interior n…
Who is the assignee on this patent?
Hyundai Motor Co Ltd, Kia Motors Corp
What technology area does this patent fall under?
Primary CPC classification G10K11/17833. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jun 29 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).