阅读说明：本技术 基于电动机振动控制电动车辆的音调的方法 (Method for controlling tone of electric vehicle based on motor vibration ) 是由 李东喆 郑仁秀 于 2020-09-29 设计创作，主要内容包括：一种基于电动机振动来控制电动车辆的音调的方法,可以包括：根据电动车辆的电动车辆电动机的振动信号计算阶次分量；提取所计算的阶次分量中的对于电动机输出转矩具有最大线性度的一阶分量；然后通过将电动车辆电动机的每分钟转数RPM变换为频率,来计算阶次频率；通过将一阶分量的振动水平应用至要输出的阶次频率的水平并且对阶次分量进行重新排列,来设置电动车辆模式音调；以及输出设置的电动车辆模式音调,并且可以在提取一阶分量时,应用LMS滤波算法、FFT/IFFT变换和阶次跟踪算法。(A method of controlling a tone of an electric vehicle based on motor vibration may include: calculating an order component from a vibration signal of an electric vehicle motor of the electric vehicle; extracting a first-order component having a maximum linearity for the motor output torque among the calculated order components; then calculating an order frequency by converting RPM of the electric vehicle motor into a frequency; setting an electric vehicle mode tone by applying a vibration level of the first order component to a level of an order frequency to be output and rearranging the order component; and outputting the set electric vehicle mode tone, and may apply an LMS filtering algorithm, an FFT/IFFT transformation, and an order tracking algorithm when extracting the first order component.)

1. A method of controlling a tone of an electric vehicle based on motor vibration, the method comprising:

calculating, by a signal processing controller, an order component from a vibration signal of an electric vehicle motor;

extracting, by the signal processing controller, an nth order component having a maximum linearity for a motor output torque among the calculated order components;

calculating, by the signal processing controller, an order frequency by converting RPM of the electric vehicle motor into a frequency; and

setting, by the signal processing controller, an electric vehicle mode tone by applying a vibration level of the nth order component to a level of the order frequency to be output and rearranging the order component.

2. The method of claim 1, wherein extracting the nth order component comprises:

extracting has a coefficient of determination greater than or equal to 90%R²The first order component of (a).

3. The method of claim 1, wherein calculating the order component comprises:

the order component is calculated from a vibration sensor configured to sense a vibration signal of the electric vehicle motor.

4. The method of claim 3, wherein the method further comprises:

when the highest amplitude is detected, the frequency is scanned by the vibration sensor to find the appropriate location of the vibration sensor.

5. The method of claim 3, wherein the vibration sensor is a knock sensor.

6. The method of claim 1, wherein the method further comprises:

outputting the set electric vehicle mode tone; and

adjusting, by the signal processing controller, an output volume based on the RPM of the electric vehicle motor by applying a band pass filter prior to output.

7. The method of claim 1, wherein the method further comprises:

outputting the set electric vehicle mode tone; and

adjusting an output volume by assigning a weight value to an RPM of the electric vehicle motor prior to output.

8. The method of claim 1, wherein the method further comprises:

outputting the set electric vehicle mode tone; and

before output, the output volume is adjusted by assigning a weight value to the pedal position.

9. The method of claim 1, wherein the method further comprises:

outputting the set electric vehicle mode tone; and

the output volume is adjusted by calculating a differential change value of the vehicle speed before output.

10. The method of claim 1, wherein the method further comprises:

selecting an order component according to a change of a driving mode, wherein the driving mode includes an energy saving mode, a normal mode and a sport mode; and

when the electric vehicle mode tone is set, the selected order component is used.

11. A method of controlling a tone of an electric vehicle based on motor vibration, the method comprising:

calculating, by a vibration sensor signal processing controller, an order component based on a vibration signal of an electric vehicle motor;

extracting, by the vibration sensor signal processing controller, an nth order component having a maximum linearity for a motor output torque among the calculated order components;

calculating, by the vibration sensor signal processing controller, an order frequency by converting RPM of the electric vehicle motor into a frequency;

setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying a vibration level of the nth order component to a level of the order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the nth order component comprises:

extracting the nth order component by updating a weight value to converge a level of the nth order component to 0 when the vibration signal is recycled using a least mean square LMS filtering algorithm for the vibration signal.

12. A method of controlling a tone of an electric vehicle based on motor vibration, the method comprising:

calculating, by a vibration sensor signal processing controller, an order component based on a vibration signal of an electric vehicle motor;

extracting, by the vibration sensor signal processing controller, an nth order component having a maximum linearity for a motor output torque among the calculated order components;

calculating, by the vibration sensor signal processing controller, an order frequency by converting RPM of the electric vehicle motor into a frequency;

setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying a vibration level of the nth order component to a level of the order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the nth order component comprises:

extracting the Nth order component by:

performing Fast Fourier Transform (FFT) on the vibration signal;

resampling by non-equidistant fast fourier transform, NFFT; and

an inverse fast fourier transform IFFT is performed.

13. A method of controlling a tone of an electric vehicle based on motor vibration, the method comprising:

calculating, by a vibration sensor signal processing controller, an order component based on a vibration signal of an electric vehicle motor;

extracting, by the vibration sensor signal processing controller, an nth order component having a maximum linearity for a motor output torque among the calculated order components;

calculating, by the vibration sensor signal processing controller, an order frequency by converting RPM of the electric vehicle motor into a frequency;

setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying a vibration level of the nth order component to a level of the order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the nth order component comprises:

the Nth order component is extracted using an order tracking analysis for an electric vehicle motor and an RPM-based band pass filter.

14. The method of any of claims 11 to 13, wherein the method further comprises:

when the highest amplitude is detected, the frequency is scanned by the vibration sensor.

15. The method of claim 14, wherein the vibration sensor is a knock sensor.

16. The method of any of claims 11 to 13, wherein the method further comprises:

prior to output, the output volume is adjusted by an external amplifier signal processing controller by applying a band pass filter based on the RPM of the electric vehicle motor.

17. The method of any of claims 11 to 13, wherein the method further comprises:

prior to output, the output volume is adjusted by an external amplifier signal processing controller by assigning a weight value to the RPM of the electric vehicle motor.

18. The method of any of claims 11 to 13, wherein the method further comprises:

the output volume is adjusted by the external amplifier signal processing controller by assigning a weight value to the pedal position prior to output.

19. The method of any of claims 11 to 13, wherein the method further comprises:

before output, the output volume is adjusted by the external amplifier signal processing controller by calculating a differential change value of the vehicle speed.

20. The method of any of claims 11 to 13, wherein the method further comprises:

selecting an order component according to a change of a driving mode, wherein the driving mode includes an energy saving mode, a normal mode and a sport mode; and

when the electric vehicle mode tone is set, the selected order component is used.

Technical Field

The present invention relates to a method of controlling a tone (tone) of an Electric Vehicle (EV) based on motor vibration, which controls a tone of the electric vehicle based on motor vibration of the electric vehicle using a motor as a power source.

Background

In recent years, due to the advent of vehicles that do not emit engine sound (e.g., electric vehicles that can run using all electric motors), there is a tendency for the noise generation device to be forcibly mounted to an environmentally-friendly vehicle. Generally, noise generated by a vehicle is uncomfortable to a driver and pedestrians around the vehicle to some extent, and such noise is used to increase the vehicle recognition ability of the pedestrians to recognize the vehicles around the pedestrians by the visual sense and the auditory sense, thereby preventing a traffic accident in advance.

Therefore, since an electric vehicle is very quiet during acceleration/deceleration and generates only high-frequency electromagnetic noise unlike a vehicle of an internal combustion engine, tone control for an electric vehicle has been mainly developed to store and reproduce virtual sounds.

In recent years, since the driving pleasure of the driver is enhanced by hearing and vision, the pitch control technique is considered as a marketable dimension of the vehicle. Therefore, it is required to store and generate music or sound suitable for electric vehicles.

The matter described herein is background to aid in understanding the present invention and may include matter not previously known to those of skill in the art to which the invention pertains.

Disclosure of Invention

Accordingly, the present invention proposes a technique of matching the performance of a vehicle and controlling a tone desired by a customer based on the motor characteristics of an electric vehicle that replaces the power of a general internal combustion engine.

The present invention provides a technique of controlling a tone of an electric vehicle, which can extract an order component (order component) of motor vibration having a high correlation with a motor output characteristic of the electric vehicle (corresponding to a power performance of an internal combustion engine) in real time, then realize a sound required for the internal combustion engine matching the power performance characteristic of the vehicle, and perform ultra-modern sound control using a high frequency characteristic.

A method of controlling a tone of an electric vehicle based on a vibration of a motor according to the present invention includes:

calculating an order component from a vibration signal of a rotating electric vehicle motor;

extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components;

calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency;

setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone.

In addition, the extraction has a determination coefficient (R) of 90% or more²) As an nth order component having the greatest linearity, and positions the position of the vibration sensor sensing the vibration signal of the electric vehicle motor at which the highest amplitude is detected while sweeping the frequency.

In addition, it is necessary to perform, before outputting the set electric vehicle mode tone: the output volume is adjusted by assigning a weight value to the RPM of the electric vehicle motor or the pedal position based on the RPM of the electric vehicle motor by applying a band pass filter, or by calculating a vehicle speed differential change value according to the vehicle speed.

In addition, the order component is selected according to a change (power saving/normal/sport) of the running mode to be arranged when the electric vehicle mode tone is set.

A method of controlling a tone of an electric vehicle based on a vibration of a motor, as a preferred exemplary embodiment, includes:

calculating an order component from a vibration signal of a rotating electric vehicle motor;

extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components;

calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency;

setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the nth order component comprises: the nth order component is extracted by updating the weight value to converge the level of the nth order component to 0 when the vibration signal is recycled using the LMS filtering algorithm for the vibration signal.

A method of controlling a tone of an electric vehicle based on a vibration of a motor, as a preferred exemplary embodiment, includes:

calculating an order component from a vibration signal of a rotating electric vehicle motor;

extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components;

calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency;

setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the order-N component comprises extracting the order-N component by:

performing a Fast Fourier Transform (FFT) on the vibration signal;

resampling by non-equidistant fast fourier transform (NFFT); and

an Inverse Fast Fourier Transform (IFFT) is performed.

Preferred exemplary embodiments include:

calculating an order component from a vibration signal of a rotating electric vehicle motor;

extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components;

calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency;

setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and

outputting the set electric vehicle mode tone,

wherein extracting the nth order component comprises: the nth order component is extracted using a band pass filter for electric vehicle motor order tracking analysis and RPM based.

The present invention is a technology of matching the performance of a vehicle and controlling a customer-desired tone based on the motor characteristics of an electric vehicle, which can extract order components of motor vibration having a high correlation with the motor output characteristics of the electric vehicle in real time, then realize a sound required by an internal combustion engine matching the power performance characteristics of the vehicle, and perform ultra-modern sound control using high frequency characteristics.

In addition, the change of the power performance can be reflected, and the sound matched with the acceleration intention of the driver is realized.

In particular, in extracting the nth order component, an algorithm for extracting the nth order component may be selected in terms of speed and accuracy. Specifically, the LMS filtering algorithm may be used to increase the calculation speed, and the FFT/IFFT transformation algorithm may be used to increase the amount of calculation and improve the accuracy. On the other hand, the order tracking algorithm can reduce the amount of calculation. The present invention selectively adopts the above-described algorithms in consideration of speed, accuracy, and calculation amount, rather than presenting only any one of them.

In addition, at the time of acceleration, a speaker having a control setting value (using an nth order component) may be used to enhance the tone, and at the time of deceleration, a natural deceleration tone may be provided by applying a fade-out considering the characteristics (quietness) of the electric vehicle.

Drawings

Fig. 1 is a diagram showing an electric vehicle to which the present invention is applied.

Fig. 2 is a diagram showing an example of input value flow and output value flow in the present invention.

Fig. 3A, 3B, and 3C are graphs showing changes in the order level (order degree) and the order level (order level) according to changes in the output torque of each load.

Fig. 4 is a diagram illustrating an algorithm from various signal inputs to an output from the sound output device.

Fig. 5A and 5B are diagrams showing a case where a Least Mean Square (LMS) filter algorithm advantageous to computation speed is applied.

Fig. 6 is a diagram showing a case where a Fast Fourier Transform (FFT)/Inverse Fast Fourier Transform (IFFT) algorithm advantageous to accuracy is applied.

Fig. 7 is a diagram showing a case where an order tracking algorithm with a small calculation amount, which extracts an nth order component based on RPM information, is applied.

Fig. 8A and 8B are diagrams showing a case where the vibration sensor signal processing controller and the external amplifier signal processing controller are separated.

Detailed Description

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying exemplary drawings, and these exemplary embodiments are examples and may be implemented in various forms by those skilled in the art to which the present invention pertains, and thus are not limited to the exemplary embodiments described herein.

Fig. 1 is a diagram showing an electric vehicle to which the present invention is applied, and fig. 2 is a diagram showing an example of an input value flow and an output value flow in the present invention.

Referring to fig. 1, the present invention mounted to an electric vehicle includes: a vibration sensor 10 measuring a vibration signal generated when the motor rotates; a CAN signal 20 connected by CAN communication in the vehicle; a signal processing controller 30 for processing the vibration signal and the CAN signal; and a sound output device 40 to implement the present invention.

The vibration signal of the motor measured by the vibration sensor 10 is input to the signal processing controller 30, and the vibration characteristics can be measured according to the real-time motor rotation. The vibration sensor 10 may also use a MEMS sensor through which digital signals are self-processed, including a knock sensor approach that is capable of converting analog signals to digital signals through a digital signal conversion module.

The motor RPM, the position of the accelerator pedal, and the vehicle speed CAN be obtained in real time from the CAN signal 20, and information on the variation of the driving mode, the motor power, and the vehicle running characteristic CAN also be obtained.

The signal processing controller may determine a driving condition or a driver's intention to accelerate/decelerate/uniform-speed driving from the vibration signal and the CAN signal as input signals, and generate a target tone signal using the motor RPM and the vibration signal to transmit the target tone signal as output data to the sound output device 40. The signal processing controller may be applied to a car audio Digital Signal Processor (DSP). DSPs are also used for speech coding that digitize sounds as analog signals, and DSPs are integrated circuits that allow machine devices to process digital signals quickly.

The sound output device 40 outputs the output data received from the signal processing controller through a speaker installed for outputting a specific frequency band in the motor-embedded engine room. In order to protect pedestrians, the sound output device may be installed outside the engine room instead of inside the engine room, or may output data to the driver or the passenger through an audio speaker installed inside the vehicle.

Fig. 2 is a diagram showing that real-time information on motor RPM and motor vibration and vehicle CAN information are obtained from a vibration sensor to perform calculation in a signal processing controller and then an acceleration sensing sound in a vehicle is output through an audio external amplifier, and a sound output device may be located outside the vehicle, inside an engine room, or the like as described above.

The vibration level due to the rotation of the electric vehicle motor represents a very low value compared to the vibration level due to the combustion of the internal combustion engine. Therefore, it is important to select the position of the sensor that can accurately extract small variations in the vibration level. One method of selecting the sensor location is as follows:

(1) first, by analyzing a structural analysis model of an electric vehicle motor, a position having a high amplitude should be selected when scanning frequencies, and the position should be a flat surface for mounting a vibration sensor, so that a position having a high amplitude sensitivity should be selected based on the flat surface. In addition, the vibration measurement direction of the vibration sensor is measured in a direction perpendicular to the seat surface. That is, the vertical variation of the amplitude with respect to the seat surface can be predicted by analysis.

(2) After the structural analysis, by actually measuring the change in the output torque of each motor load and the level of each motor vibration order at the same time to perform regression analysis on the change in the motor output torque according to the change in the motor load and the level of the order of the motor, it is possible to extract the output characteristic of the motor and have a determination coefficient (R) of 0.9 or more²) To select the location with high sensitivity that results in the maximum amplitude. That is, a position most indicative of the characteristic of the amplitude of the vibration of the motor may be selected as the final position.

In an electric vehicle, the power performance of the motor is expressed as motor output torque. In the present invention, in order to control the motor vibration-based pitch, a component having a high correlation with the tendency of the motor output torque is extracted from the order level and order level characteristics of the motor based on the motor RPM among a large amount of information on the vibration signal of the motor, and thus should be selected as the nth order component. The order component is changed differently according to the internal structure of the motor including the number of cores and the like.

Fig. 3A, 3B, and 3C are graphs showing examples of the order levels and the changes of the order levels according to the changes of the output torque for each load. In particular, the variation of the order level is an example of 24 orders. Accordingly, a graph of motor RPM-order level (nth order) -order level (dB) is completed, and thus, the order component having a high correlation with the motor output torque has a determination coefficient (R) of 0.9 or more²) And therefore 24 th order can be determined as a reference (Ref) order component.

Fig. 4 is a diagram illustrating an algorithm showing a calculation process from various signal inputs (S10) to an output (S40) from a sound output device.

The input signal is a vibration signal of the electric vehicle motor and measured using the vibration sensor 10, RPM, pedal position, vehicle speed data, driving mode, and gear of the electric vehicle motor may be input from the CAN signal 20. The following algorithm is calculated by the signal processing controller 30, and final output is performed by the sound output device 40 including an internal audio speaker.

An nth order component is extracted from an input vibration signal of the motor and set as a reference (Ref) order component, and a level of the nth order component, i.e., the reference (Ref) order component, is determined (S30).

This can always be used as a reference (Ref) order component by first calculating the reference (Ref) order component once from the nth order component for subsequent input to the signal processing controller. Meanwhile, the nth order component may also be set to be automatically determined by the signal processing controller by extracting the nth order component from the vibration signal of the motor every certain time.

Meanwhile, an order component (e.g., 2 th order/4 th order) generated for the motor RPM obtained in real time may be generated (S31).

When the nth order component, which is a reference of the input order level, is determined in S30, the order is rearranged by matching the order components generated in S31 (S36). At this time, the amplification level of the levels of the arranged order components may be determined, and the amplification is controlled in real time (S36).

In S36, rearrangement of the order components of the engine may be additionally considered according to which one of the energy saving/normal/sporty modes the driving mode is from the input of the driving mode and the gear (S35).

Meanwhile, the calculated value of the electric vehicle mode tone set in S36 may be selectively changed in conjunction with the input signal or the external signal (S38, S39, S40).

First, there is a case where a variable band filter based on the motor RPM is applied (S37). The band filter refers to a band pass filter, and is a filter that removes a component having a specific frequency or less and a component having a specific frequency or more from an input signal and outputs only frequencies within a specific frequency band. The band filter may be formed by a combination of a low-pass filter and a high-pass filter. Therefore, in S38, the electric vehicle mode tone may be implemented only for a specific frequency band region.

In order to reflect the change in the vehicle dynamics in the electric vehicle tone control and realize a sound matching the driver' S intention to accelerate, a weight value may be given to the motor RPM itself (S32) or to the position of the accelerator pedal (S33).

Alternatively, both may be applied or selection may be performed (S39). Further, the vehicle speed difference variation value may be applied to the vehicle speed data (S34).

Meanwhile, an algorithm for extracting the N-order component may be selectively determined according to a calculation speed, accuracy, a calculation amount, and the like.

Fig. 5A and 5B are diagrams showing a case where a Least Mean Square (LMS) filter algorithm advantageous to computation speed is applied. The LMS filtering algorithm is a filtering technique for active noise reduction (ANC), and extracts a target N-order component in a numerical calculation process. The calculation process is shown in fig. 5A, which is ultimately an algorithm for separating the N-th order y (N) extracted from the vibration signal d (N) measured in real time, and for this, the filter weight value w (z) is applied. In addition, the N-order level information extraction value x (N) is applied to both the filter weight value and the LMS algorithm, and the filter weight value w (z) is repeatedly updated until the level of the set N-order component converges to 0. Finally, the filter weight values w (z) and updates are done, and then the LMS filter is applied to the real-time vibration signal.

Fig. 5B is a graph showing changes in the vibration signal before and after the LMS filter is applied.

When an Nth order component extracted from real-time vibration signal information including all order levels is set, the Nth order component having a high correlation with the motor output torque or having a high linearity is determined. As a result of comparing the N-th order extracted by the FFT analysis with the N-th order extracted by applying the LMS filter, it can be seen that the case of applying the N-th order of the LMS filter is slightly smaller in level and also smaller in data amount than the N-th order by the FFT. That is, when the LMS filter is used, since the number of sample data is small compared to the FFT, data loss due to the resolution occurs, and since the FFT has a higher resolution, the level (level) is also higher.

Applying the above-described overall algorithm can control the electric vehicle motor tone of an electric vehicle by: calculating an order component from a vibration signal of the rotating electric vehicle motor; extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components by updating a weight value to converge a level of the nth order component to 0 when recycling the vibration signal using an LMS filtering algorithm for the vibration signal; calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of the order frequency to output a rearranged order component; and outputting the set electric vehicle mode tone.

Fig. 6 is a diagram showing a case where a Fast Fourier Transform (FFT)/Inverse Fast Fourier Transform (IFFT) algorithm advantageous to accuracy is applied.

Fig. 6 is a diagram showing conversion of time data into frequency data. The FFT can be performed on the measurement region in a short time and the frequency resolution is low. Frequency resolution means that when the desired signal is observed in the frequency domain, a dense spacing of the values of the respective frequency bands can be observed. Therefore, a non-equally spaced fast fourier transform (NFFT) technique is additionally applied. By forcing the addition of M additional zero padding data to increase the resolution, the raw data information measured by the vibration sensor can be preserved. Finally, by obtaining FFT data re-sampled to a level of 2Hz, the exact value of the nth order component can be extracted using the motor RPM. When the target sound is controlled, only when the time difference between the input data and the output data satisfies the condition within 30 msec, a natural sound that the human ear does not feel a delay can be realized. When the vibration signal is transformed by the FFT, i.e., transformed to the frequency domain based on 20 msec data at the time of measurement, the frequency interval is very wide, so that desired dense frequency characteristics cannot be found. For this reason, when the amount of data is insufficient, the NFFT technique may be applied by performing zero padding processing to resample the resolution to 2 Hz.

Applying the above-described overall algorithm includes: calculating an order component from a vibration signal of a rotating electric vehicle motor; extracting an nth order component having the greatest linearity for the motor output torque among the calculated order components; calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and outputting the set electric vehicle mode tone, and extracting the N-order component may control an electric vehicle motor tone of the electric vehicle based on the motor vibration of the extracted N-order component by performing a Fast Fourier Transform (FFT), performing resampling by a non-equidistant fast fourier transform (NFFT), and performing an Inverse Fast Fourier Transform (IFFT) on the vibration signal.

Fig. 7 is a diagram showing a case where an order tracking algorithm with a small calculation amount is applied and an nth order component is extracted based on RPM information. First, the order component of the vibration signal is extracted through the order tracking calculation, and the nth order is calculated according to the variation of the motor RPM and the band pass filter is applied.

Applying the above-described overall algorithm can control the electric vehicle motor tone of an electric vehicle by: calculating an order component from a vibration signal of the rotating electric vehicle motor; extracting an nth order component using an order tracking analysis for the electric vehicle motor and an RPM-based band pass filter among the calculated order components; calculating an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting an electric vehicle mode tone by applying a vibration level of the nth order component to a level of an order frequency to be output and rearranging the order component; and outputting the set electric vehicle mode tone.

Meanwhile, referring to fig. 8A and 8B, the vibration sensor signal processing controller may be separated from the external amplifier signal processing controller. That is, in fig. 8, the vibration sensor signal processing controller may extract an nth order component (S30), generate an order according to RPM information (S31), and set an electric vehicle mode tone (S36). The external amplifier signal processing controller may control the rest except for S30, S31, and S36.

That is, the Micro Control Unit (MCU) in the external amplifier signal processing controller may perform integrated electric vehicle tone control by receiving the output signals controlled in S30, S31, S36 from the vibration sensor signal processing controller and the CAN information from the vehicle, and output the electric vehicle tone through various speakers. The function of providing the target tone output signal of the vibration sensor signal processing controller performs the calculation processing in fig. 4 as it is (S30, S31, S36). Other functions than the function of providing the target tone output signal may also be handled by the external amplifier signal processing controller as shown in fig. 8A and 8B.