A semi-active suspension damping adjustment method based on Teager energy operator impact identification

Abstract

The application relates to the technical field of vehicle engineering, in particular to a semi-active suspension damping adjustment method based on impact identification of a Teager energy operator, acceleration sensors are arranged at the lower end of the semi-active suspension to collect acceleration signals, the acceleration signals are subjected to low-pass filtering processing, impact features are extracted based on the Teager energy operator, the mean value and the standard deviation of a Teager energy sequence are dynamically updated by adopting an exponential weighted moving average method, and an adaptive discrimination threshold is constructed in combination with a fixed bias; whether impact is generated is judged through the threshold, the corresponding side threshold is updated when the impact is detected, and threshold drift caused by impact energy is prevented; single impact and continuous bumping road surfaces are distinguished through impact frame intervals and trigger times, the suspension damping is adjusted to be small under the impact working condition to buffer vibration, and the damping is adjusted to be large on ordinary grade road surfaces to maintain the stable attitude of a cab. The application considers the real-time performance and the accuracy of impact identification, can effectively reduce the transient vibration of the cab, and improves the riding comfort of the vehicle.

Description

Technical Field

[0001] This invention relates to the field of vehicle engineering technology, specifically to a semi-active suspension damping adjustment method based on Teager energy operator impact identification. Background Technology

[0002] Semi-active suspension systems in automobiles can adjust damping in real time according to road conditions, reducing the transmission of vibrations to the vehicle body and improving ride comfort. The prerequisite for precise damping adjustment in a semi-active suspension system is the ability to quickly and accurately identify road conditions, especially impact excitations such as speed bumps, manhole covers, and road joints. These impact excitations are characterized by high frequency, large amplitude, and short duration, requiring a high degree of real-time performance from the identification method. If the identification time is too long, it will lead to a lag in damping parameter adjustment, failing to effectively suppress vibration transmission. If the identification accuracy is insufficient, normal road vibrations may be misjudged as impact excitations, or real impacts may be missed, resulting in a deterioration in the control strategy and reduced ride comfort.

[0003] Existing methods for identifying impact excitation typically use a preset acceleration threshold. When the vibration acceleration collected by the sensor exceeds the threshold, it is determined to be an impact excitation. This method is simple to calculate and has strong real-time performance, but it is greatly affected by road noise and is prone to misjudgment. Some literature uses Hilbert transform to solve for instantaneous frequency to identify impact earlier, but it requires complex frequency domain conversion calculations, which is not real-time enough for vehicle-mounted embedded devices. Summary of the Invention

[0004] The purpose of this invention is to provide a semi-active suspension damping adjustment method based on Teager energy operator impact identification, which aims to solve the technical problem that the existing impact identification schemes used in semi-active suspension systems cannot simultaneously achieve both identification accuracy and real-time response speed. This method can quickly identify impact excitation with low computational load and is adaptable to the judgment of impact under various complex road conditions.

[0005] To achieve the above objectives, this invention provides a semi-active suspension damping adjustment method based on Teager energy operator impact identification, comprising the following steps:

[0006] Step 1: Install an acceleration sensor at the lower end of the semi-active suspension and acquire acceleration signals in real time;

[0007] Step 2: Perform low-pass filtering on the acquired acceleration signal;

[0008] Step 3: Calculate the Teager energy operator for the filtered acceleration signal using a sliding window with a length of 3 and a step size of 1, and take the absolute value;

[0009] Step 4: Calculate the mean and variance of the cumulative Teager energy operator output sequence, update the mean and variance using the exponentially weighted moving average method, and calculate the adaptive threshold;

[0010] Step 5: Set control decisions that include impact trigger judgment, working condition classification, and threshold freezing mechanism;

[0011] Step 6: Adjust the semi-active suspension damping according to the detection results.

[0012] Optionally, the formula for calculating the absolute value in step 3 is as follows:

[0013]

[0014] Where a(n) is the result of acceleration filtering at the nth sampling time.

[0015] Optionally, the formula for calculating the mean of the teo(n) sequence in step 4 is as follows:

[0016]

[0017] Where N is the preset window length;

[0018] The process of updating the mean using the exponentially weighted moving average method is performed according to the following formula:

[0019]

[0020] α is the update weight for the current Teager energy value, and its value ranges from (0,1).

[0021] Optionally, the calculation and updating of the standard deviation follows the formula:

[0022]

[0023]

[0024] in, This represents the initial standard deviation.

[0025] Optionally, in step 4, the threshold calculation is performed by adding the mean of the Teager energy operator values ​​plus k times the standard deviation, and then adding a constant offset.

[0026] Optionally, in the control decision of step 5, if the real-time Teager energy operator teo(n) is greater than the adaptive threshold th(n), it is determined that an impact has occurred on that side.

[0027] If the interval between two impact frames is less than N1 and the cumulative number of impacts reaches N2, it is determined to be a normal road surface; otherwise, it is a single impact.

[0028] Optionally, after an impact event is detected, the threshold update corresponding to the sensor on the impacted side is frozen; if the threshold is below the threshold or the threshold is frozen for more than N3 frames, it is determined that the impact has ended, and the threshold update is resumed.

[0029] Optionally, after an impact is detected in step 6, the suspension damping is reduced; after the impact ends and the road surface is normal, the suspension damping is increased again.

[0030] Optionally, the semi-active suspension damping adjustment method based on Teager energy operator impact identification continuously collects acceleration signals and repeats steps 2 to 6 to achieve closed-loop damping adjustment through iterative cyclic execution.

[0031] This invention provides a semi-active suspension damping adjustment method based on Teager energy operator impact recognition. An accelerometer is placed at the lower end of the semi-active suspension to collect acceleration signals, which are then low-pass filtered. Impact features are extracted based on the Teager energy operator, and the mean and standard deviation of the Teager energy sequence are dynamically updated using an exponentially weighted moving average method. An adaptive discrimination threshold is constructed using a fixed bias. The threshold is used to determine whether an impact has occurred. When an impact is detected, the corresponding side threshold update is frozen to prevent threshold drift caused by impact energy. The impact frame interval and trigger count distinguish between single impacts and continuous bumpy road conditions. Under impact conditions, the suspension damping is adjusted downwards to buffer vibration, while under continuous bumpy conditions, the damping is adjusted upwards to suppress continuous vibration. This invention balances real-time performance and accuracy in impact recognition, effectively reducing transient vibrations in the cab and improving vehicle ride comfort. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a schematic diagram of the specific control flow of a semi-active suspension damping adjustment method based on Teager energy operator impact identification according to the present invention.

[0034] Figure 2 This is a schematic diagram of the installation position of the acceleration sensor in a specific embodiment of the present invention.

[0035] Figure 3 This is a diagram showing the detection effect of the Teager operator impact recognition algorithm in a specific embodiment of the present invention.

[0036] Figure 4 This is a schematic diagram of the impact recognition results in a specific embodiment of the present invention.

[0037] Figure 5 This is a partially enlarged schematic diagram of a vehicle driving over the first speed bump in a specific embodiment of the present invention. Detailed Implementation

[0038] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0039] This invention provides a semi-active suspension damping adjustment method based on Teager energy operator impact identification, comprising the following steps:

[0040] Step 1: Install an acceleration sensor at the lower end of the semi-active suspension and acquire acceleration signals in real time;

[0041] Step 2: Perform low-pass filtering on the acquired acceleration signal;

[0042] Step 3: Calculate the Teager energy operator for the filtered acceleration signal using a sliding window with a length of 3 and a step size of 1, and take the absolute value;

[0043] Step 4: Calculate the mean and variance of the cumulative Teager energy operator output sequence, update the mean and variance using the exponentially weighted moving average method, and calculate the adaptive threshold;

[0044] Step 5: Set control decisions that include impact trigger judgment, working condition classification, and threshold freezing mechanism;

[0045] Step 6: Adjust the semi-active suspension damping according to the detection results.

[0046] The following provides further explanation in conjunction with the specific implementation process:

[0047] In step 1, the acceleration signal of the lower end of the suspension is collected in real time, and the acceleration at the nth sampling time is a′(n);

[0048] Step 2 involves performing a low-pass filter on the acquired acceleration signal a′(n) to remove high-frequency interference components, resulting in the filtered vibration signal a(n), thus avoiding interference signals from affecting the feature extraction accuracy.

[0049] Step 3: After the system samples three acceleration data points, the Teager energy operator is used to calculate the filtered acceleration signal a(n). To facilitate adaptive threshold determination, the absolute value of the calculated result is taken, as shown in the following formula:

[0050]

[0051] Step 4 is the adaptive threshold calculation process, during which:

[0052] (1) When the length of the collected Teager energy operator output sequence reaches the preset window length N, calculate the mean of the teo(n) sequence within the window:

[0053]

[0054] The calculation is performed only once after the system initially collects N data points. To reduce computational load and track changes in the current Teager operator value, the mean is subsequently updated using the Exponentially Weighted Moving Average (EWMA) method.

[0055]

[0056] Where α is the update weight of the current Teager energy value, and its value ranges from (0,1).

[0057] (2) Initial standard deviation Compared with the initial mean Similarly, the calculation is performed only once after the initial collection of N data points:

[0058]

[0059] Subsequent updates will also utilize the exponentially weighted moving average method:

[0060]

[0061] (3) The threshold is calculated using the mean plus k times the standard deviation. To avoid misjudging the impact in the initial state and to reduce the probability of triggering the impact judgment due to occasional disturbances, a constant bias term β is introduced:

[0062]

[0063] The control decisions set in step 5 are as follows:

[0064] (1) Trigger judgment: If the real-time Teager energy operator teo(n) is greater than the adaptive threshold th(n), it is determined that an impact has occurred on that side;

[0065] (2) Type differentiation: If the interval between two impact frames is less than N1 and the cumulative number of impacts reaches N2, it is determined to be a normal road surface; otherwise, it is a single impact.

[0066] (3) After an impact is detected, in order to avoid the high Teager energy operator value of the impact signal interfering with the threshold calculation, the threshold update corresponding to the sensor on the impacted side is frozen after the impact event is detected; if the threshold is lower than the threshold or the threshold is frozen for more than N3 frames, it is determined that the impact has ended and the threshold update is restored.

[0067] Step 6: After an impact is detected, the suspension damping is reduced. After the impact ends and the road surface is normal, the suspension damping is increased again.

[0068] The semi-active suspension damping adjustment method based on Teager energy operator impact identification acquires signals from two acceleration sensors in real time, repeats the above steps, and improves accuracy through repeated iterations.

[0069] The specific control process is as follows: Figure 1 As shown.

[0070] Furthermore, this invention introduces a semi-active suspension system for commercial vehicle cabs through specific embodiments for further explanation:

[0071] like Figure 2 As shown, four adjustable-damping semi-active suspension mounts are respectively installed on the front left, front right, rear left, and rear right sides of the cab bottom, connecting the cab to the frame; the greater the current of the semi-active suspension, the greater the damping of the shock absorber; the hardware system includes two acceleration sensors, a suspension controller, and a signal acquisition module; the two acceleration sensors are respectively installed on the left front and right front positions of the frame (lower end of the semi-active suspension) to collect acceleration signals from the lower end of the suspension:

[0072] In this example, the vehicle travels at a speed of 40 km / h over three speed bumps, each 100 meters apart. The specific steps are as follows:

[0073] 1. An accelerometer is used to collect the vibration acceleration signal a′(n) of the lower end of the left front and right front suspension of the frame in real time at a sampling frequency of 100Hz, where n is the sampling time index, and the signal is transmitted to the suspension controller in real time.

[0074] 2. The original vibration signal a′(n) is low-pass filtered by the suspension controller with a cutoff frequency of 20Hz to obtain the noise-reduced vibration signal a(n);

[0075] 3. After the system samples three acceleration data points, the Teager energy operator is used to calculate the filtered acceleration signal a(n). To facilitate adaptive threshold determination, the absolute value of the calculated result is taken, as shown in the following formula:

[0076]

[0077] 4. Adaptive threshold calculation:

[0078] (1) When the length of the output sequence of the Teager energy operator reaches the preset initial statistical window length N=60, calculate the mean of the teo(n) sequence within the window:

[0079]

[0080] The mean is calculated only once after the system initially collects 60 data points. Subsequent calculations use an exponentially weighted moving average to update the mean. The current weight value α is set to 0.01.

[0081]

[0082] (2) Initial standard deviation Compared with the initial mean Each calculation is performed once after the initial collection of 60 data points:

[0083]

[0084] Subsequent updates will also utilize an exponentially weighted moving average, with the current weight value α set to 0.01.

[0085]

[0086] (3) Update threshold:

[0087]

[0088] The coefficient k is set to 3, which is designed based on the "3σ statistical criterion" and can cover the signal fluctuation range under most normal operating conditions; the fixed compensation offset β is a preset compensation value for the basic noise level, which can be set according to the actual acceleration noise level, and is set to 30 here.

[0089] 5. Control Decisions:

[0090] (1) Trigger judgment: When the real-time Teager energy teo(n) is greater than the adaptive threshold th(n), the impact is judged to have occurred;

[0091] (2) Type differentiation: If the interval between two impacts is less than N1=40 frames and the cumulative number of impacts is greater than N2=3, it is determined to be a normal road surface; otherwise, it is a single impact.

[0092] (3) After an impact is detected, the impact state is maintained for the next N3=30 frames, and the adaptive threshold update corresponding to the sensor on the impacted side is frozen. When the Teager energy operator value is lower than the threshold after the impact ends, the normal update of the threshold is restored.

[0093] 6. After an impact is detected, adjust the damping current of the four suspension mounts in the cab to 0.8A, that is, reduce the damping to reduce the transmission of the impact to the cab. If the road surface is determined to be of normal grade after the impact, adjust the current to 1.4A, that is, increase the damping to reduce the self-vibration of the suspension mounts.

[0094] 7. Acquire acceleration signals in real time and repeat the above steps.

[0095] 8. For example Figure 3 The Teager energy operator value is calculated as a function of the sampling points. The Teager value changes significantly when subjected to impact.

[0096] like Figure 4 The initial point of the impact detected by the Teager operator impact recognition algorithm is marked on the acceleration signal collected by the frame acceleration sensor. At the same time, a constant acceleration threshold is set based on the recognition speed and accuracy. If the acceleration exceeds the threshold, it is marked as an impact. It can be seen that the Teager energy operator impact recognition algorithm detected all three speed bump impacts normally, while the constant acceleration threshold impact detection algorithm had two false detections.

[0097] The acceleration waveform of the vehicle as it passes over the first speed bump is magnified locally, such as... Figure 5 The Teager operator algorithm identifies high-frequency transient impacts ahead of the traditional constant acceleration threshold method, while the fixed acceleration threshold method has a significant lag.

[0098] Compared to the constant acceleration threshold algorithm, which detects the impact of the first and second speed bumps one data frame earlier and the third speed bump five data frames earlier, the constant acceleration threshold algorithm can detect the impact 10ms to 50ms earlier.

[0099] 9. Using a passive suspension with non-adjustable damping, drive over a speed bump under the same conditions, collect the vertical acceleration under the driver's seat, and calculate the maximum transient vibration value (MTVV) to evaluate the vibration reduction effect. The results are shown in Table 1:

[0100] Table 1 Vertical MTVV at the Lower End of Driver's Seat

[0101]

[0102] This damping control method improves the MTVV value by about 10% compared to passive suspension.

[0103] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0104] 1. The three-point sliding window Teager energy operator calculation algorithm is adopted, which has low algorithm complexity. Compared with the traditional constant acceleration threshold impact identification method, this method can advance the impact detection time by 1 to 5 data frames.

[0105] 2. The Teager energy operator can simultaneously reflect the amplitude and instantaneous frequency changes of a signal, and can identify the characteristics of the impact excitation of an acceleration signal from noise. Compared with the constant acceleration threshold impact identification method, it improves the identification accuracy of impact excitation.

[0106] 3. The adaptive threshold is updated using the exponentially weighted moving average (EWMA) method, combined with the threshold freezing mechanism, which can adaptively adapt to different road surfaces and solve the problem that traditional fixed thresholds need to be calibrated separately for different road surfaces when encountering impact excitation or different sensor positions.

[0107] 4. Using this damping control method, the maximum transient vibration value (MTVV) of vertical acceleration under the driver's seat is improved by about 10% compared to passive suspension with non-adjustable damping.

[0108] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A semi-active suspension damping adjustment method based on Teager energy operator impact identification, characterized in that, Includes the following steps: Step 1: Install an acceleration sensor at the lower end of the semi-active suspension and acquire acceleration signals in real time; Step 2: Perform low-pass filtering on the acquired acceleration signal; Step 3: Calculate the Teager energy operator for the filtered acceleration signal using a sliding window with a length of 3 and a step size of 1, and take the absolute value; Step 4: Calculate the mean and standard deviation of the cumulative Teager energy operator output sequence, update the mean and standard deviation using the exponential weighted moving average method, and calculate the adaptive threshold; Step 5: Set control decisions that include impact trigger judgment, working condition classification, and threshold freezing mechanism; Step 6: Adjust the semi-active suspension damping according to the detection results.

2. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 1, characterized in that, The formula for calculating the absolute value in step 3 is as follows: Where a(n) is the result of acceleration filtering at the nth sampling time.

3. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 2, characterized in that, The formula for calculating the mean of the teo(n) sequence in step 4 is as follows: Where N is the preset window length; The process of updating the mean using the exponentially weighted moving average method is performed according to the following formula: α is the update weight for the current Teager energy value, and its value ranges from (0,1).

4. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 3, characterized in that, The calculation and updating of standard deviation follows the formula below: in, This represents the initial standard deviation.

5. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 4, characterized in that, In step 4, the threshold calculation process uses the mean of the Teager energy operator value plus k times the standard deviation, and then adds a constant offset to this.

6. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 5, characterized in that, In step 5, the control decision is made when the real-time Teager energy operator teo(n) is greater than the adaptive threshold th(n), indicating that an impact has occurred on that side. If the interval between two impact frames is less than N1 and the cumulative number of impacts reaches N2, it is determined to be a normal road surface; otherwise, it is a single impact.

7. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 6, characterized in that, After an impact event is detected, the threshold update corresponding to the sensor on the impacted side is frozen; if the threshold is below the threshold or the threshold is frozen for more than N3 frames, it is determined that the impact has ended, and the threshold update is resumed.

8. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 7, characterized in that, After an impact is detected in step 6, the suspension damping is reduced. After the impact ends and the road surface is normal, the suspension damping is increased again.

9. The semi-active suspension damping adjustment method based on Teager energy operator impact identification as described in claim 8, characterized in that, The semi-active suspension damping adjustment method based on Teager energy operator impact identification continuously collects acceleration signals and repeats steps 2 to 6 to achieve closed-loop damping adjustment through iterative cyclic execution.

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