Method for controlling the tone of electric vehicles based on motor vibration

Abstract

A method for controlling the tone of an electric vehicle based on motor vibration may include: calculating order components based on a vibration signal of an electric vehicle motor of the electric vehicle; extracting a first-order component having maximum linearity with respect to the motor output torque from the calculated order components; then 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 first-order component to a level of an order frequency to be output and rearranging the order components; and outputting the set electric vehicle mode tone, and an LMS filtering algorithm, an FFT / IFFT transform, and an order tracking algorithm may be applied when extracting the first-order component.

Description

Technical Field

[0001] The present invention relates to a method of controlling the tone of an electric vehicle (EV) based on motor vibration, which controls the tone of an EV based on motor vibration of the EV using the motor as a power source. Background Art

[0002] In recent years, with the emergence of vehicles that do not emit engine noise (for example, electric vehicles that can run entirely on electric motors), there has been a trend to compulsorily install noise-generating devices on environmentally friendly vehicles. Generally, the noise generated by a vehicle causes discomfort to the driver and pedestrians around the vehicle to a certain extent, and this noise is used to enhance pedestrians' ability to recognize vehicles around them through vision and hearing, thereby preventing traffic accidents in advance.

[0003] Therefore, because electric vehicles are very quiet during acceleration / deceleration and generate only high-frequency electromagnetic noise, unlike vehicles with internal combustion engines, tone control for electric vehicles has been mainly developed to store and reproduce virtual sounds.

[0004] In recent years, the tone control technology has been considered as a dimension of vehicle marketability because it improves the driver's driving pleasure through hearing and vision. Therefore, it is necessary to store and generate music or sounds suitable for electric vehicles.

[0005] The contents described herein are intended to aid understanding of the background of the invention and may include contents not previously known to those skilled in the art to which the invention pertains. Summary of the Invention

[0006] Therefore, the present invention proposes a technology for matching the performance of a vehicle based on the characteristics of a motor of an electric vehicle that replaces the power of a general internal combustion engine and controlling a tone desired by a customer.

[0007] The present invention provides a technology for controlling the tone of an electric vehicle, which can extract in real time the order components of the motor vibration that have a high correlation with the output characteristics of the electric motor of the electric vehicle (corresponding to the power performance of the internal combustion engine), and then realize the sound required by the internal combustion engine that matches the power performance characteristics of the vehicle, and perform ultra-modern sound control using high-frequency characteristics.

[0008] A method for controlling the tone of an electric vehicle based on motor vibration according to the present invention comprises:

[0009] calculating order components based on a vibration signal of a rotating electric vehicle motor;

[0010] extracting an N-th order component having the greatest linearity with respect to the motor output torque from among the calculated order components;

[0011] The order frequency is calculated by converting the RPM of the electric vehicle motor into frequency;

[0012] setting an electric vehicle mode tone by applying a vibration level of an N-order component to a level of an order frequency to be output and rearranging the order component; and

[0013] Outputs the set electric vehicle mode tone.

[0014] In addition, the extraction had a coefficient of determination (R 2 ) as the Nth-order component with the greatest linearity, and when scanning the frequency, the position of the vibration sensor for sensing the vibration signal of the electric vehicle motor is positioned to where the highest amplitude is detected.

[0015] In addition, before outputting the set electric vehicle mode tone, it is necessary to perform the following: adjusting the output volume by assigning a weight value to the RPM of the electric vehicle motor or the pedal position by applying a bandpass filter based on the RPM of the electric vehicle motor, or calculating the vehicle speed differential change value according to the vehicle speed to adjust the output volume.

[0016] In addition, the order components are selected according to the change of the driving mode (eco / normal / sport) to arrange the order components when setting the electric vehicle mode tone.

[0017] A method for controlling the tone of an electric vehicle based on motor vibration, as a preferred exemplary embodiment, includes:

[0018] calculating order components based on a vibration signal of a rotating electric vehicle motor;

[0019] extracting an N-th order component having the greatest linearity with respect to the motor output torque from among the calculated order components;

[0020] The order frequency is calculated by converting the RPM of the electric vehicle motor into frequency;

[0021] setting an electric vehicle mode tone by applying a vibration level of an N-order component to a level of an order frequency to be output and rearranging the order component; and

[0022] Outputs the set electric vehicle mode tone,

[0023] The extracting of the Nth order component includes extracting the Nth order component by updating a weight value so that a level of the Nth order component converges to 0 when recirculating the vibration signal using an LMS filter algorithm for the vibration signal.

[0024] A method for controlling the tone of an electric vehicle based on motor vibration, as a preferred exemplary embodiment, includes:

[0025] calculating order components based on a vibration signal of a rotating electric vehicle motor;

[0026] extracting an N-th order component having the greatest linearity with respect to the motor output torque from among the calculated order components;

[0027] The order frequency is calculated by converting the RPM of the electric vehicle motor into frequency;

[0028] setting an electric vehicle mode tone by applying a vibration level of an N-order component to a level of an order frequency to be output and rearranging the order component; and

[0029] Outputs the set electric vehicle mode tone,

[0030] Extracting the N-order component includes extracting the N-order component by the following method:

[0031] Perform fast Fourier transform (FFT) on the vibration signal;

[0032] Resampling via non-uniformly spaced fast Fourier transform (NFFT); and

[0033] Perform an inverse fast Fourier transform (IFFT).

[0034] Preferred exemplary embodiments include:

[0035] calculating order components based on a vibration signal of a rotating electric vehicle motor;

[0036] extracting an N-th order component having the greatest linearity with respect to the motor output torque from among the calculated order components;

[0037] The order frequency is calculated by converting the RPM of the electric vehicle motor into frequency;

[0038] setting an electric vehicle mode tone by applying a vibration level of an N-order component to a level of an order frequency to be output and rearranging the order component; and

[0039] Outputs the set electric vehicle mode tone,

[0040] The extracting of the N-order component includes extracting the N-order component by using a bandpass filter based on RPM and an order tracking analysis of an electric vehicle motor.

[0041] The present invention is a technology that matches the performance of an electric vehicle and controls the tone desired by customers based on the motor characteristics of the electric vehicle. The technology can extract the order components of the motor vibration that have a high correlation with the output characteristics of the electric vehicle motor in real time, and then realize the sound required by the internal combustion engine that matches the dynamic performance characteristics of the vehicle, and perform ultra-modern sound control using high-frequency characteristics.

[0042] In addition, it can also reflect changes in power performance and achieve a sound that matches the driver's acceleration intention.

[0043] In particular, when extracting N-order components, an algorithm for extracting N-order components can be selected in terms of speed and accuracy. Specifically, an LMS filter algorithm can be used to increase computational speed, while an FFT / IFFT transform algorithm can increase computational complexity and improve accuracy. On the other hand, an order tracking algorithm can reduce computational complexity. The present invention selectively employs the aforementioned algorithms in consideration of speed, accuracy, and computational complexity, rather than presenting only one of them.

[0044] In addition, during acceleration, the tone can be enhanced using a speaker with a control setting value (using Nth-order components), and during deceleration, a natural deceleration tone can be provided by applying a fade-out that takes into account the characteristics of the electric vehicle (quietness). BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 FIG. 1 is a diagram showing an electric vehicle to which the present invention is applied.

[0046] Figure 2 is a diagram showing an example of an input value flow and an output value flow in the present invention.

[0047] Figure 3A 、 Figure 3B 、 Figure 3C Graphs showing changes in order degree and order level according to changes in output torque for each load.

[0048] Figure 4 This is a diagram explaining an algorithm from various signal inputs to outputs from a sound output device.

[0049] Figure 5A 、 Figure 5B 1 is a diagram showing a case where a least mean square (LMS) filter algorithm advantageous in calculation speed is applied.

[0050] Figure 6This is a diagram showing a case where a fast Fourier transform (FFT) / inverse fast Fourier transform (IFFT) algorithm advantageous in accuracy is applied.

[0051] Figure 7 : is a diagram showing a case where an order tracking algorithm having a small calculation amount and extracting an N-order component based on RPM information is applied.

[0052] Figure 8A 、 Figure 8B This is a diagram showing a case where the vibration sensor signal processing controller and the external amplifier signal processing controller are separated. DETAILED DESCRIPTION

[0053] 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 can be implemented in various forms by those skilled in the art to which the present invention pertains, and are therefore not limited to the exemplary embodiments described herein.

[0054] Figure 1 is a diagram showing an electric vehicle to which the present invention is applied, and Figure 2 is a diagram showing an example of an input value flow and an output value flow in the present invention.

[0055] Reference Figure 1 The present invention installed in an electric vehicle includes: a vibration sensor 10, which measures a vibration signal generated when the motor rotates; a CAN signal 20, which is connected through a CAN communication in the vehicle; a signal processing controller 30, which processes the vibration signal and the CAN signal; and a sound output device 40, to implement the present invention.

[0056] 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 can also use a MEMS sensor, and the digital signal is processed by the MEMS sensor itself, including a knock sensor method that can convert the analog signal into a digital signal through a digital signal conversion module.

[0057] 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 changes in the driving mode, motor power, and vehicle running characteristics can also be obtained.

[0058] The signal processing controller can determine driving conditions or the driver's intention to accelerate, decelerate, or maintain a constant speed 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, and transmit the target tone signal as output data to the sound output device 40. The signal processing controller can be applied to an in-vehicle audio digital signal processor (DSP). DSPs can also be used for voice encoding, which digitizes analog sound signals, and are integrated circuits that enable equipment to quickly process digital signals.

[0059] The sound output device 40 outputs the output data received from the signal processing controller via a speaker installed within the engine compartment, where the electric motor is embedded, to output a specific frequency band. To protect pedestrians, the sound output device may be installed outside the engine compartment rather than inside. Alternatively, the output data may be output to the driver or passengers via an audio speaker installed within the vehicle.

[0060] Figure 2 is a diagram showing that real-time information about motor RPM and motor vibration and vehicle CAN information are obtained from a vibration sensor to perform calculations in a signal processing controller, and then the acceleration sensing sound in the vehicle is output through an audio external amplifier, and the sound output device can be located outside the vehicle, inside the engine room, etc. as described above.

[0061] Compared to the vibration level caused by combustion in an internal combustion engine, the vibration level caused by the rotation of the electric vehicle motor is very low. Therefore, it is important to select a sensor location that can accurately detect small changes in the vibration level. One method for selecting the sensor location is as follows:

[0062] (1) First, by analyzing the structural analysis model of the electric vehicle motor, it was determined that when sweeping the frequency, a location with high amplitude should be selected. This location should also be a flat surface for mounting the vibration sensor, so that a location with high amplitude sensitivity should be selected based on this flat surface. Furthermore, the vibration sensor's vibration measurement direction was measured perpendicular to the seat surface. In other words, the vertical change in amplitude relative to the seat surface could be predicted through analysis.

[0063] (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, the change in the motor output torque is regressed according to the change in the motor load and the motor order level. The output characteristics of the motor can be extracted and the motor order level can be obtained with a coefficient of determination (R) of 0.9 or higher. 2) to select a position with high sensitivity that forms the maximum amplitude. That is, the position that best represents the characteristics of the amplitude caused by motor vibration can be selected as the final position.

[0064] In electric vehicles, the power performance of the motor is expressed as motor output torque. In the present invention, to control the tone of the motor's vibration, a component highly correlated with the trend of the motor's output torque is extracted from the motor's order grade and order level characteristics based on the motor's RPM, among a large amount of information about the motor's vibration signal. This component is therefore selected as the Nth-order component. The order component is varied depending on the motor's internal structure, including the number of magnetic cores, etc.

[0065] Figure 3A 、 Figure 3B 、 Figure 3C Graph showing an example of changes in order level and order grade according to changes in output torque for each load. In particular, the change in order level is an example of 24 orders. Thus, a graph of motor RPM-order level (N order)-order level (dB) is completed, and therefore, the order component having a high correlation with the motor output torque has a determination coefficient (R) of 0.9 or higher. 2 ), so the 24th order can be determined as the reference (Ref) order component.

[0066] Figure 4 It is a diagram for explaining an algorithm showing a calculation process from various signal inputs ( S10 ) to outputs from a sound output device ( S40 ).

[0067] The input signal is a vibration signal of the electric vehicle motor and is measured using a vibration sensor 10, and RPM, pedal position, vehicle speed data, driving mode, and gear position of the electric vehicle motor may be input from a CAN signal 20. The following algorithm is calculated by a signal processing controller 30, and the final output is performed through a sound output device 40 including an internal audio speaker.

[0068] An N-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 N-order component (ie, the reference (Ref)-order component) is determined ( S30 ).

[0069] By first calculating a reference (Ref) order component from the Nth order component and then inputting it to the signal processing controller, this can always be used as the reference (Ref) order component. At the same time, the Nth order component can 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 at each specific time.

[0070] At the same time, an order component (eg, 2nd order / 4th order) generated with respect to the motor RPM obtained in real time may be generated ( S31 ).

[0071] When the N-order component as a reference for the input order level is determined in S30, the order is rearranged by matching the order component generated in S31 (S36). At this time, the amplification level of the level of the arranged order component can be determined and the amplification is controlled in real time (S36).

[0072] In S36 , the rearrangement of the order components of the engine ( S35 ) may be additionally considered based on the input of the driving mode and the gear position, depending on whether the driving mode is the eco / normal / sport mode.

[0073] Meanwhile, the calculated value of the electric vehicle mode tone set in S36 may be selectively changed in conjunction with an input signal or an external signal ( S38 , S39 , S40 ).

[0074] First, there is a case where a variable frequency band filter based on the motor RPM is applied (S37). A frequency band filter is a bandpass filter that removes components with a specific frequency or lower and components with a specific frequency or higher from the input signal and outputs only frequencies within a specific frequency band. The frequency band filter can also be composed of a combination of a low-pass filter and a high-pass filter. Therefore, in S38, the electric vehicle mode tone can be implemented only for a specific frequency band area.

[0075] To reflect changes in vehicle dynamics in electric vehicle tone control and achieve a sound that matches the driver's acceleration intention, a weight value may be assigned to the motor RPM itself ( S32 ) or to the position of the accelerator pedal ( S33 ).

[0076] Alternatively, both of them may be applied or selected (S39). Alternatively, the vehicle speed differential change value may be applied to the vehicle speed data (S34).

[0077] At the same time, the algorithm for extracting the N-order component can be selectively determined based on calculation speed, accuracy, calculation amount, etc.

[0078] Figure 5A 、 Figure 5B : is a diagram showing a case where a least mean square (LMS) filtering algorithm is applied that is advantageous for calculation speed. The LMS filtering algorithm is a filtering technique used for active noise reduction (ANC) and extracts a target N-order component during numerical calculation. Figure 5AThe calculation process is shown in Figure 1, which ultimately results in an algorithm for separating the Nth-order y(n) extracted from the vibration signal from the real-time measured vibration signal d(n). To this end, a filter weight value W(z) is applied. Furthermore, the Nth-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 set level of the Nth-order component converges to 0. Finally, the filter weight value W(z) is updated and then the LMS filter is applied to the real-time vibration signal.

[0079] Figure 5B Graphs showing changes in vibration signals before and after application of the LMS filter.

[0080] When extracting Nth-order components from real-time vibration signal information encompassing all order levels, an Nth-order component with a high correlation or high linearity with the motor output torque is determined. Comparing the Nth-order components extracted using FFT analysis with those extracted using an LMS filter, it can be seen that the Nth-order components extracted using the LMS filter are slightly smaller in level and smaller in data volume than those obtained using the FFT. Specifically, when using an LMS filter, data loss due to resolution occurs because the amount of sampled data is smaller than with an FFT, and the level is also higher due to the higher resolution of the FFT.

[0081] Applying the above-mentioned overall algorithm can control the electric vehicle motor tone of an electric vehicle through the following steps: calculating order components based on the vibration signal of the rotating electric vehicle motor; as a step of extracting the Nth order component with the maximum linearity for the motor output torque from the calculated order components, extracting the Nth order component by updating the weight value when the vibration signal is recycled using an LMS filtering algorithm on the vibration signal so that the level of the Nth order component converges to 0; calculating the order frequency by converting the RPM of the electric vehicle motor into a frequency; setting the electric vehicle mode tone by applying the vibration level of the Nth order component to the level of the order frequency to output a rearranged order component; and outputting the set electric vehicle mode tone.

[0082] Figure 6 This is a diagram showing a case where a fast Fourier transform (FFT) / inverse fast Fourier transform (IFFT) algorithm advantageous in accuracy is applied.

[0083] Figure 6This figure illustrates the transformation of time data into frequency data. FFTs can be performed on the measurement area in a very short time, and the frequency resolution is low. Frequency resolution means that when observing the desired signal in the frequency domain, the values ​​of the corresponding frequency band are closely spaced. Therefore, a non-uniformly spaced fast Fourier transform (NFFT) technique is additionally applied. By forcibly adding M additional zero-padding data to increase resolution, the original data information measured by the vibration sensor can be preserved. Finally, by obtaining FFT data resampled to a level of 2Hz, the precise value of the Nth-order component can be extracted using the motor RPM. When controlling the target sound, a natural sound with no perceptible delay to the human ear can only be achieved if the time difference between the input and output data is within 30 milliseconds. When transforming the vibration signal using FFT—that is, converting it to the frequency domain based on 20 milliseconds of data during measurement—the frequency spacing is very wide, making it impossible to find the desired dense frequency characteristics. To this end, when the amount of data is insufficient, the NFFT technique can be applied to resample the resolution to 2Hz by performing zero-padding.

[0084] Applying the above-mentioned overall algorithm includes: calculating order components based on the vibration signal of the rotating electric vehicle motor; extracting the Nth order component with the maximum linearity for the motor output torque among the calculated order components; calculating the order frequency by converting the RPM of the electric vehicle motor into a frequency; setting the electric vehicle mode tone by applying the vibration level of the Nth order component to the level of the order frequency to be output and rearranging the order components; and outputting the set electric vehicle mode tone, and the extracted Nth order component can be controlled based on the motor vibration of the extracted Nth order component by performing a fast Fourier transform (FFT) on the vibration signal, performing resampling by a non-uniformly spaced fast Fourier transform (NFFT), and performing an inverse fast Fourier transform (IFFT).

[0085] Figure 7 This figure shows the case of applying an order tracking algorithm with a small amount of calculation and extracting the N-order component based on RPM information. First, the order component of the vibration signal is extracted by order tracking calculation, and the N-order is calculated according to the change in the motor RPM, and a bandpass filter is applied.

[0086] Applying the above-mentioned overall algorithm can control the electric vehicle motor tone of an electric vehicle through the following steps: calculating order components based on the vibration signal of the rotating electric vehicle motor; extracting N-order components from the calculated order components using order tracking analysis for the electric vehicle motor and an RPM-based bandpass filter; calculating order frequencies by converting the RPM of the electric vehicle motor into frequencies; setting the electric vehicle mode tone by applying the vibration level of the N-order component to the level of the order frequency to be output and rearranging the order components; and outputting the set electric vehicle mode tone.

[0087] At the same time, refer to Figure 8A and Figure 8B , the vibration sensor signal processing controller can be separated from the external amplifier signal processing controller. That is, in Figure 8, the vibration sensor signal processing controller can extract the Nth order component (S30), generate the order according to the RPM information (S31), and set the electric vehicle mode tone (S36). The external amplifier signal processing controller can control the remaining parts except S30, S31, and S36.

[0088] That is, the microcontroller unit (MCU) in the external amplifier signal processing controller can perform integrated electric vehicle tone control by receiving the output signal electric vehicle tone controlled in S30, S31, and S36 from the vibration sensor signal processing controller and receiving 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 is performed as it is Figure 4 The calculation process (S30, S31, S36) in the above example can also be performed as follows. Figure 8A and Figure 8B The external amplifier signal processing controller shown handles other functions in addition to the function of providing the target tone output signal.

Claims

1. A method for controlling the pitch of an electric vehicle based on motor vibration, the method comprising: The signal processing controller calculates the order component based on the vibration signal of the electric vehicle motor; The signal processing controller extracts, from among the calculated order components, an Nth-order component having the greatest linearity with respect to the motor output torque; calculating, by the signal processing controller, an order frequency by converting RPM of the electric vehicle motor into a frequency; as well as setting, by the signal processing controller, an electric vehicle mode tone by applying the vibration level of the N-order component to the level of the order frequency to be output and rearranging the order component, The extracting of the N-th order component includes: Extract the samples with a coefficient of determination R greater than or equal to 90% 2 The first-order component of .

2. The method according to claim 1, wherein Calculating the order components includes: The order components are calculated based on a vibration sensor configured to sense a vibration signal of the electric vehicle motor.

3. The method according to claim 2, wherein: The method further comprises: When the highest amplitude is detected, the frequency is swept by the vibration sensor to find the appropriate position of the vibration sensor.

4. The method according to claim 2, wherein: The vibration sensor is a knock sensor.

5. The method according to claim 1, wherein The method further comprises: outputting the set electric vehicle mode tone; and Before output, the output volume is adjusted by the signal processing controller based on the RPM of the electric vehicle motor by applying a bandpass filter.

6. The method according to 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 RPM of the electric vehicle motor.

7. The method according to claim 1, wherein The method further comprises: outputting the set electric vehicle mode tone; and Adjust the output volume by assigning a weight value to the pedal position before output.

8. The method according to claim 1, wherein The method further comprises: outputting the set electric vehicle mode tone; and Before output, the output volume is adjusted by calculating the differential change value of the vehicle speed.

9. The method according to claim 1, wherein The method further comprises: selecting an order component according to a change in a driving mode, wherein the driving mode includes an energy-saving mode, a normal mode, and a sport mode; and The selected order components are used when setting the electric vehicle mode tone.

10. A method for controlling the pitch of an electric vehicle based on motor vibration, the method comprising: The vibration sensor signal processing controller calculates the order component based on the vibration signal of the electric vehicle motor; The vibration sensor signal processing controller extracts, from the calculated order components, an Nth-order component having the greatest linearity with respect to the motor output torque; calculating, by the vibration sensor signal processing controller, an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying the vibration level of the N-order component to the level of the order frequency to be output and rearranging the order component; as well as Outputs the set electric vehicle mode tone, The extracting of the N-th order component includes: extracting the Nth-order component by updating a weight value so that the level of the Nth-order component converges to 0 while recirculating the vibration signal using a least mean square (LMS) filtering algorithm for the vibration signal, The extracting of the N-th order component includes: Extract the samples with a coefficient of determination R greater than or equal to 90% 2 The first-order component of .

11. A method for controlling the pitch of an electric vehicle based on motor vibration, the method comprising: The vibration sensor signal processing controller calculates the order component based on the vibration signal of the electric vehicle motor; The vibration sensor signal processing controller extracts, from the calculated order components, an Nth-order component having the greatest linearity with respect to the motor output torque; calculating, by the vibration sensor signal processing controller, an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying the vibration level of the N-order component to the level of the order frequency to be output and rearranging the order component; as well as Outputs the set electric vehicle mode tone, The extracting of the N-th order component includes: The Nth-order component is extracted in the following way: Performing a fast Fourier transform (FFT) on the vibration signal; Resampling by non-uniformly spaced Fast Fourier Transform (NFFT); and Perform inverse fast Fourier transform IFFT, The extracting of the N-th order component includes: Extract the samples with a coefficient of determination R greater than or equal to 90% 2 The first-order component of .

12. A method for controlling the pitch of an electric vehicle based on motor vibration, the method comprising: The vibration sensor signal processing controller calculates the order component based on the vibration signal of the electric vehicle motor; The vibration sensor signal processing controller extracts, from the calculated order components, an Nth-order component having the greatest linearity with respect to the motor output torque; calculating, by the vibration sensor signal processing controller, an order frequency by converting the RPM of the electric vehicle motor into a frequency; setting, by the vibration sensor signal processing controller, an electric vehicle mode tone by applying the vibration level of the N-order component to the level of the order frequency to be output and rearranging the order component; as well as Outputs the set electric vehicle mode tone, The extracting of the N-th order component includes: Extracting the Nth-order component using order tracking analysis for electric vehicle motors and an RPM-based bandpass filter, The extracting of the N-th order component includes: Extract the samples with a coefficient of determination R greater than or equal to 90% 2 The first-order component of .

13. The method according to any one of claims 10 to 12, wherein The method further comprises: When the highest amplitude is detected, the frequency is swept by the vibration sensor.

14. The method according to claim 13, wherein: The vibration sensor is a knock sensor.

15. The method according to any one of claims 10 to 12, wherein The method further comprises: Before output, the output volume is adjusted by an external amplifier signal processing controller based on the RPM of the electric vehicle motor by applying a bandpass filter.

16. The method according to any one of claims 10 to 12, wherein The method further comprises: Before 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.

17. The method according to any one of claims 10 to 12, wherein The method further comprises: Before output, the external amplifier signal processing controller adjusts the output volume by assigning a weight value to the pedal position.

18. The method according to any one of claims 10 to 12, wherein The method further comprises: Before output, the external amplifier signal processing controller adjusts the output volume by calculating the differential change value of the vehicle speed.

19. The method according to any one of claims 10 to 12, wherein The method further comprises: selecting an order component according to a change in a driving mode, wherein the driving mode includes an energy-saving mode, a normal mode, and a sport mode; and The selected order components are used when setting the electric vehicle mode tone.

Images