Commercial vehicle speed signal processing method and system based on TCU multi-source signals

Abstract

The invention belongs to the technical field of vehicle signal processing, and particularly relates to a commercial vehicle speed signal processing method and system based on TCU multi-source signals, and the method comprises the steps: collecting an ABS speed signal, an instrument speed signal and a gearbox output shaft rotating speed signal; carrying out Kalman filtering processing on the acquired ABS vehicle speed signal; carrying out redundancy check and credibility evaluation on the instrument vehicle speed signal, the optimized ABS vehicle speed signal and the vehicle speed signal obtained by converting the rotating speed of the output shaft; dynamically selecting an optimal vehicle speed signal according to a verification result, and performing smooth switching when a signal source is abnormal; and outputting a final vehicle speed signal to a vehicle control system. According to the method, the instrument speed signal and the gearbox output shaft rotating speed signal are introduced as redundant signal sources, the reliability of the redundant signal sources is evaluated by calculating the absolute deviation between the signals, other reliable signal sources can be automatically selected when a single signal fails or is abnormal, and the limitation of a traditional single routing signal scheme under complex working conditions is avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of vehicle signal processing, and particularly relates to a commercial vehicle speed signal processing method, system, terminal and storage medium based on a TCU multi-source signal. BACKGROUND

[0002] With the increasing degree of electrification and intelligentization of commercial vehicles, the vehicle control system has increasingly strict requirements for the accuracy and reliability of the vehicle speed signal. As a core parameter of vehicle control, the quality of the vehicle speed directly affects the execution effect of the automatic transmission gear shifting strategy, cruise control, load calculation and advanced driving assistance system (ADAS) functions. The traditional AMT vehicle generally adopts a vehicle speed processing scheme based on an ABS system, and the wheel speed information is collected by the anti-lock braking device, and the average value of the front two wheel speeds is taken as the reference vehicle speed signal.

[0003] However, under actual operating conditions, this scheme has obvious limitations. First, factors such as electromagnetic interference of the electrical system, sensor aging and poor contact of the wire harness connector easily lead to the original ABS vehicle speed signal jumping, oscillating or frame breaking. Second, in the steering condition, due to the speed difference between the left and right wheels, the calculation method based on the average wheel speed will produce inherent deviation. In addition, in special conditions such as low-speed crawling and tunnel crossing, a single signal source is easily affected by the environment and may have signal delay or failure problems.

[0004] These signal abnormalities will trigger a series of chain reactions, including unexpected exit of the cruise control system, false judgment of the transmission system to cause no upshift, automatic throttle during turning and other fault phenomena, which not only affects the driving comfort, but also may endanger the driving safety. The existing solutions mostly use simple threshold filtering or single path redundancy backup, but lack dynamic noise suppression and multi-source signal collaborative verification mechanism, and it is difficult to fundamentally improve the anti-interference ability and continuity of the signal. SUMMARY

[0005] In view of the above deficiencies of the prior art, the application provides a commercial vehicle speed signal processing method, system, terminal and storage medium based on a TCU multi-source signal.

[0006] In a first aspect, the application provides a commercial vehicle speed signal processing method based on a TCU multi-source signal, comprising: S1, collecting an ABS vehicle speed signal, an instrument vehicle speed signal and a transmission output shaft speed signal; S2, performing Kalman filtering processing on the collected ABS vehicle speed signal to suppress noise and output an optimized vehicle speed signal; S3, performing redundancy verification and credibility evaluation on the instrument vehicle speed signal, the optimized ABS vehicle speed signal and the vehicle speed signal converted from the output shaft speed; S4, dynamically selecting the optimal vehicle speed signal according to the check result, and performing smooth switching when the signal source is abnormal; S5, outputting the final vehicle speed signal to the vehicle control system.

[0007] Further improvement of the technical solution is that step S1 comprises: S11, collecting the ABS vehicle speed signal from the ABS control system in real time through the TCU connected vehicle CAN bus, which is calculated by the ABS system based on the front wheel speed sensor data, specifically, taking the average of the left front wheel and right front wheel speed; S12, synchronously collecting the instrument vehicle speed signal from the instrument panel control system through the TCU connected vehicle CAN bus, which is derived from the GPS module; S13, collecting the transmission output shaft speed signal in real time through the TCU connected transmission sensor, and converting the output shaft speed signal into corresponding vehicle speed value by using the conversion formula, the conversion formula is: ; Among them, represents the vehicle speed information corresponding to the transmission output shaft speed after conversion, the unit is kilometer / hour; represents the transmission output shaft speed, the unit is revolutions / minute, which is derived from the direct measurement value of the transmission sensor; represents the vehicle tire radius, the unit is meter, which is a pre-calibrated vehicle fixed parameter; represents the vehicle rear axle speed ratio.

[0008] Further improvement of the technical solution is that step S2 comprises: S21, establishing the system state equation and the observation equation of Kalman filter, wherein the system state equation is set as , and the observation equation is set as ; in the formula, is the prior state estimation value of ABS speed at the current time k, the unit is km / h; A is the state transition matrix, which is 1, representing that the speed signal has no sudden change transmission relationship between adjacent time points; is the posterior state estimation value of ABS speed at the previous time k-1, the unit is km / h; B is the control input matrix, which is 0, because the speed signal filtering process does not need additional external control input; is the control input vector at the previous time k-1; is the original ABS speed signal collected at the current time k, the unit is km / h; is the observation matrix, which is 1, representing that the observation value directly corresponds to the state value; is the observation noise at the current time k, which is subject to normal distribution with mean value of 0, reflecting the random disturbance of the original ABS speed signal; S22, calculate the prior covariance matrix of the Kalman filter prediction stage: ; Wherein, is the prior covariance matrix of the current time k, unit: , reflecting the uncertainty of the prior state estimate; is the posterior covariance matrix of the previous time k-1, unit: ; is the transpose matrix of the state transition matrix A; is the process noise covariance matrix; S23, calculate the Kalman gain and complete the state correction and covariance update of the update stage, the calculation formula of the Kalman gain is: ; Wherein, is the Kalman gain of the current time k; is the transpose matrix of the observation matrix H; R is the observation noise covariance matrix; is the inverse matrix of the matrix ; According to the formula , the ABS speed posterior state estimate value of the current time k is obtained, and according to the formula , the posterior covariance matrix is updated; wherein, is the optimized ABS speed signal of the current time k; is the unit matrix, taking the value of 1; is the posterior covariance matrix of the current time k, used for the prior covariance calculation of the next filtering period; S24, judge whether the optimized ABS speed signal output by filtering meets the preset speed range, if is in the actual driving speed interval of commercial vehicle, that is, 0~120km / h; Then is taken as the optimized ABS speed signal finally output by step S2; If it is out of the interval, the posterior state estimate value of the previous time k-1 is used as the output.

[0009] Further improvement of the technical scheme is that step S3 includes: S31, calculate the first absolute deviation between the optimized ABS speed signal and the instrument speed signal, and calculate the second absolute deviation between the optimized ABS speed signal and the output shaft speed conversion speed signal, the calculation formulas of the first absolute deviation and the second absolute deviation are respectively: ; ; Wherein, is the first absolute deviation; is the ABS speed signal after optimization at the current time k; is the instrument speed signal; represents the speed information corresponding to the converted speed of the transmission output shaft; is the second absolute deviation; S32, according to the preset first deviation threshold to the first absolute deviation , it is judged that the first absolute deviation is less than or equal to the first deviation threshold , the trusted flag of the instrument is configured , otherwise 0; according to the preset second deviation threshold to the second absolute deviation , it is judged that the second absolute deviation is less than or equal to the second deviation threshold , the trusted flag of the instrument is configured to 1, otherwise 0; S33, if or at least one of them is true, it is determined that the ABS speed is trusted and the is the candidate optimal signal; if both are not true, the third absolute deviation between the converted speed signal of the output shaft speed and the instrument speed signal is calculated, and the calculation formula is: ; if the third absolute deviation is less than or equal to the third deviation threshold , it is determined that the converted speed signal of the output shaft speed is trusted, and the output shaft speed trusted flag is set to an effective state, and is set as the lowest priority trusted candidate; otherwise, it is determined that the converted speed signal of the output shaft speed is not trusted, and the output shaft speed trusted flag is set to an invalid state.

[0010] Further improvement of the technical solution is that step S4 includes: S41, according to the trusted flag , output by step S3 and the ABS optimized speed , the candidate speed is determined according to the priority order: ; Wherein, is the selected speed; S42, in the selection process of step S41, introduce a time delay judgment mechanism, when the signal is not trusted state continues to exceed the preset time threshold , trigger signal switching.

[0011] Further improvement of the technical solution is that step S4 further comprises: When the signal is switched, the selected vehicle speed signal Apply a first-order low-pass smoothing filter algorithm to output the final vehicle speed signal, and the smoothing filter formula is: ; Where, is the final vehicle speed output signal at time k, with units of km / h; is the weight coefficient; is the final vehicle speed output signal at time k-1, with units of km / h; is the vehicle speed signal selected based on step S41 at time k, with units of km / h.

[0012] Further improvement of the technical solution is that step S5 comprises: S51, the final vehicle speed signal determined in step S4 Data format standardization processing is performed to convert the vehicle speed value to a numerical coding format that conforms to the vehicle-mounted CAN bus communication protocol, and the calculation formula is ; is the CAN bus coding value of the vehicle speed signal, which is a 16-bit integer; is a scaling coefficient, which is 2, used to map the vehicle speed value to the coding range; is an offset, which is 0, to ensure that 0 km / h corresponds to the coding value 0; is a rounding function, which maps the vehicle speed range of 0~120 km / h to the coding range of 0~240; S52, construct a CAN bus data frame containing the vehicle speed signal, define the data frame structure according to the SAE J1939 protocol, including frame start, arbitration field, control field, data field, CRC field, ACK field and frame end, the arbitration field contains priority, data page and PDU format, wherein the data field length is 2 bytes, used to store the calculated in step S51, and the data frame identifier is determined by the formula , where is the 11-bit identifier of the CAN bus data frame; is the priority, which is 6 to ensure the transmission priority of the vehicle speed signal; is the data page, which is 0, representing the basic data page; The PDU format is 236, corresponding to the PGN of the vehicle speed signal; the identifier ensures that the whole vehicle control system can accurately identify the vehicle speed signal frame; S53, transmitting the CAN bus data frame to the whole vehicle control system and verifying the transmission validity, setting a transmission period The CAN controller of the TCU transmits the data frame periodically.

[0013] In a second aspect, the application provides a commercial vehicle speed signal processing system based on a TCU multi-source signal, comprising: A multi-source speed acquisition module is configured to acquire ABS vehicle speed signals, instrument vehicle speed signals, and gearbox output shaft speed signals. A filtering processing module is configured to perform Kalman filtering processing on the acquired ABS vehicle speed signals to suppress noise and output optimized vehicle speed signals. A speed credibility evaluation module is configured to perform redundancy verification and credibility evaluation on the instrument vehicle speed signals, the optimized ABS vehicle speed signals, and the vehicle speed signals converted from the output shaft speed. An optimal vehicle speed selection module is configured to dynamically select the optimal vehicle speed signal according to the verification result and perform smooth switching when the signal source is abnormal. A vehicle speed output module is configured to output the final vehicle speed signal to the whole vehicle control system.

[0014] In a third aspect, the application provides a terminal, comprising: A processor and a memory, wherein The memory is configured to store a computer program, The processor is configured to call and run the computer program from the memory, so that the terminal executes the method of the terminal described above.

[0015] In a fourth aspect, the application provides a computer storage medium, wherein the computer readable storage medium stores instructions, when the instructions are run on a computer, the computer executes the method described in the above aspects.

[0016] The application has the following advantages: The application performs Kalman filtering processing on the ABS vehicle speed signal (step S2), effectively suppresses high-frequency interference and random noise, and outputs a more smooth and stable vehicle speed signal. This not only improves the accuracy of the vehicle speed signal, but also reduces the signal jump phenomenon caused by sensor aging or electromagnetic interference, ensuring that the whole vehicle control system can make accurate decisions based on high-precision vehicle speed information.

[0017] ​The present application introduces the instrument vehicle speed signal and the gearbox output shaft speed signal as redundant signal sources (step S3), and evaluates their reliability by calculating the absolute deviation between the signals. This multi-source signal fusion mechanism can automatically select other reliable signal sources when a single signal fails or is abnormal, avoiding the limitations of traditional single-route signal schemes in complex working conditions.

[0018] When the signal source is abnormal, the present application uses a delay judgment mechanism and a first-order low-pass filtering algorithm (step S4) to realize smooth switching of the signal. The delay judgment mechanism can avoid false switching caused by transient interference, and the smooth filtering ensures the continuous transition between the new and old signals, preventing sudden changes in vehicle speed from affecting the transmission system and driving experience. This not only improves the robustness of the system, but also enhances driving comfort and safety.

[0019] The present application describes in detail how to encapsulate the final vehicle speed signal as a standard data frame that meets the CAN bus communication protocol in step S5, and indicates the health status of the current signal source through the status byte. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, for those of ordinary skill in the art, other drawings can also be obtained without creative labor based on these drawings.

[0021] Figure 1 A schematic flowchart of the method of an embodiment of the present application.

[0022] Figure 2 A schematic block diagram of the system of an embodiment of the present application.

[0023] Figure 3 A structural schematic diagram of a terminal provided by an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to make the purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the specific embodiments. Obviously, the following described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for describing particular embodiments only and is not intended to be limiting of the application.

[0026] Figure 1 is a schematic flow chart of a commercial vehicle speed signal processing method based on TCU multi-source signals provided by the present application. Among them, Figure 1 The execution subject can be a commercial vehicle speed signal processing system based on TCU multi-source signals. According to different needs, the order of steps in the flow chart can be changed, and some can be omitted.

[0027] As Figure 1 shown, the method comprises: S1, collecting ABS speed signal, instrument speed signal and gearbox output shaft speed signal; S2, performing Kalman filtering processing on the collected ABS speed signal to suppress noise and output the optimized speed signal; S3, performing redundancy check and credibility evaluation on the instrument speed signal, the optimized ABS speed signal and the speed signal converted from the output shaft speed; S4, dynamically selecting the optimal speed signal according to the check result, and performing smooth switching when the signal source is abnormal; S5, outputting the final speed signal to the vehicle control system.

[0028] In order to facilitate the understanding of the present application, the principle of the commercial vehicle speed signal processing method based on TCU multi-source signals provided by the present application is described further based on the process of processing the speed signal of the commercial vehicle based on TCU multi-source signals in the embodiment.

[0029] Firstly, step S1 comprises: S11, connecting the vehicle CAN bus through the TCU, and collecting the ABS speed signal from the ABS (Anti-lock Braking System, Anti-lock Braking System) control system in real time, which is calculated by the ABS system based on the front wheel speed sensor data, specifically taking the average value of the left front wheel and right front wheel speed; S12, connecting the vehicle CAN bus through the TCU, and synchronously collecting the instrument speed signal from the instrument panel control system, which is derived from the GPS module; S13, connecting the gearbox sensor through the TCU, collecting the gearbox output shaft speed signal in real time, and converting the output shaft speed signal into the corresponding speed value by using the conversion formula, the conversion formula is: ; wherein, represents the converted vehicle speed information corresponding to the gearbox output shaft speed, in km / h; represents the gearbox output shaft speed, in rpm, from direct measurement of the gearbox sensor; represents the vehicle tire radius, in meters, which is a pre-calibrated fixed parameter of the vehicle; represents the vehicle rear axle speed ratio.

[0030] Through the CAN communication interface of the commercial vehicle transmission control unit (TCU), a twisted pair is connected to the vehicle CAN bus (compliant with ISO 11898-2 standard), and the CAN controller parameters of the TCU are configured: the baud rate is set to 250 kbps (commonly used rate for commercial vehicle chassis CAN bus), the message receiving mode is set to "filtered reception", and only wheel speed related messages (PGN (Parameter Group Number) code is pre-set to 65256, corresponding to the "wheel speed information" parameter group in SAE J1939 protocol) sent by the ABS control system are received.

[0031] The ABS control system collects wheel speed signals through Hall type wheel speed sensors installed on the left front wheel (inside the left front wheel hub) and the right front wheel (inside the right front wheel hub), and the sensor outputs a square wave signal proportional to the wheel speed (resolution is 1 pulse / revolution). After shaping and debouncing processing of the two square wave signals, the ABS ECU converts the frequency signal to wheel speed.

[0032] The commercial vehicle combination instrument has a built-in GPS module (supports Beidou / GPS dual-mode positioning, positioning accuracy ≤10m), and the GPS module receives satellite positioning data at a frequency of 1Hz and outputs GGA statements (including latitude, longitude, and positioning time) and RMC statements (including ground speed) through NMEA-0183 protocol. The instrument ECU converts the ground speed data in the RMC statement (unit: knots, 1 knot = 1.852 km / h) to obtain the original instrument speed signal , and removes GPS signal jump interference through low-pass filtering (cutoff frequency 1Hz) to obtain a stable instrument speed signal .

[0033] The TCU receives the speed message sent by the instrument ECU through the vehicle CAN bus (the same bus as ABS signal acquisition), the message PGN code is pre-set to 65264 (corresponding to the "instrument speed" parameter group in SAE J1939 protocol), and the data length is 2 bytes. The TCU configures a CAN message receiving filter to only filter messages with this PGN code, and collects Data, and record the acquisition time stamp. If no instrument vehicle speed message is received for 5 consecutive periods, or If the deviation from the value of the previous period exceeds 20 km / h (judged as loss or abnormality of GPS signal), the instrument signal acquisition abnormal flag is triggered.

[0034] A magneto-rotational speed sensor (detection gap 0.5-1.5 mm) is installed on the end cover of the gearbox output shaft (close to the rear axle input end), the sensor senses the alternating voltage signal generated by the rotation of the signal tooth (30 teeth) on the output shaft, and the voltage amplitude changes with the speed (amplitude ≥0.5V at 500r / min, amplitude ≥2V at 2000r / min). The TCU receives the voltage signal through an analog signal acquisition interface (sampling rate 1kHz), converts it into a square wave signal through a shaping circuit (Schmitt trigger), and then calculates the square wave frequency through a counter module.

[0035] The application collects ABS, instrument and gearbox output shaft three types of vehicle speed related signals through TCU, covers three vehicle speed acquisition paths of "wheel speed-positioning-mechanical transmission", avoids the failure problem of traditional single ABS signal in electromagnetic interference, steering, tunnel and other scenes. At the same time, the abnormal flag is set to monitor the signal acquisition state in real time, and the "signal health degree" basis is provided for subsequent redundancy check, and the signal abnormality sensing ability of the system is improved.

[0036] Secondly, step S2 comprises: S21, establishing the system state equation and the observation equation of Kalman filtering, wherein the system state equation is set as , and the observation equation is set as ; in the formula , the ABS speed prior state estimation value of the current time k is unit: km / h; A is the state transition matrix, and the value is 1, representing that the vehicle speed signal has no sudden change transmission relationship at adjacent time; , the ABS speed posterior state estimation value of the previous time k-1 is unit: km / h; B is the control input matrix, and the value is 0, because the vehicle speed signal filtering process does not need additional external control input; , the control input vector of the previous time k-1 is unit: km / h; , the original ABS speed signal collected at the current time k is unit: km / h; , the observation matrix is 1, representing that the observation value corresponds to the state value directly; , the observation noise of the current time k is subject to normal distribution with mean value 0, reflecting the random interference of the original ABS speed signal; S22, calculating the prior covariance matrix of the prediction stage of Kalman filtering: ; , wherein is the prior covariance matrix at the current time k, unit: , reflecting the uncertainty of the prior state estimate; is the posterior covariance matrix at the previous time k-1, unit: ; is the transpose matrix of the state transition matrix A; is the process noise covariance matrix; S23, calculate the Kalman gain and complete the state correction and covariance update in the update stage, the formula for calculating the Kalman gain is: ; wherein, is the Kalman gain at the current time k; is the transpose matrix of the observation matrix H; R is the observation noise covariance matrix; is the inverse matrix of the matrix ; According to the formula , the ABS speed posterior state estimate value at the current time k is obtained, and the posterior covariance matrix is updated according to the formula ; wherein, is the optimized ABS speed signal at the current time k; is the unit matrix, taking the value of 1; is the posterior covariance matrix at the current time k, used for the prior covariance calculation of the next filtering period; S24, judge whether the optimized ABS speed signal output by the filter is in the preset speed range, if is in the actual driving speed interval of commercial vehicles, i.e. 0~120km / h; then is taken as the optimized ABS speed signal finally output by step S2; if it is out of the interval, the posterior state estimate value at the previous time k-1 is used as the output.

[0037] The process noise is mainly caused by the mechanical gap of the ABS system (such as the gap change between the wheel speed sensor and the gear ring), electromagnetic interference (such as the interference of high-voltage wire harness on the sensor signal), and the value of Q is calibrated through real vehicle test: Select 10 commercial vehicles of the same type, drive on flat road at three typical speeds of 30km / h, 60km / h and 90km / h, collect the ABS original signal and high-precision reference speed (obtained by differential GPS, error≤0.1km / h) at each speed; Calculate the process noise variance at different speeds, and take the average value as (unitless, because the unit of covariance matrix is , to ensure that the process noise intensity covers more than 95% of the working conditions.

[0038] The actual driving speed of the commercial vehicle is limited by the power system, the braking system and the road conditions, and a reasonable speed judgment range is set: Lower limit: 0 km / h (vehicle static state, ABS signal static fluctuation ≤0.5 km / h, so the lower limit is set to 0 km / h); Upper limit: 120 km / h (the legal maximum speed of the commercial vehicle is ≤100 km / h, considering signal fluctuation and special working conditions, 20 km / h redundancy is reserved to avoid misjudgment in normal driving).

[0039] The setting of state transition matrix A=1 conforms to the physical characteristics of the speed change of the commercial vehicle, ensures smooth transition of the speed signal at adjacent time, avoids "sudden change" (speed change ≤0.5 km / h within 0.1 s) of the filtered signal, and improves driving comfort (for example, the gear shifting strategy is based on stable speed adjustment, without jerk).

[0040] Next, step S3 includes: S31, calculate the first absolute deviation between the optimized ABS speed signal and the instrument speed signal, and calculate the second absolute deviation between the optimized ABS speed signal and the output shaft speed converted speed signal, and the calculation formulas of the first absolute deviation and the second absolute deviation are respectively: ; ; Wherein, is the first absolute deviation; is the optimized ABS speed signal at the current time k; is the instrument speed signal; indicates the speed information corresponding to the gearbox output shaft speed after conversion; is the second absolute deviation; S32, according to the preset first deviation threshold , the first absolute deviation is judged, when the first absolute deviation is less than or equal to the first deviation threshold within a continuous preset time, the trusted flag bit of the instrument is configured , otherwise it is 0; according to the preset second deviation threshold , the second absolute deviation is judged, when the second absolute deviation is less than or equal to the second deviation threshold within a continuous preset time, the trusted flag bit of the instrument is configured 1, otherwise it is 0; S33, if or If at least one of the conditions is true, it is determined that the ABS vehicle speed is reliable and maintained If both conditions are not true, a third absolute deviation between the output shaft speed converted vehicle speed signal and the instrument vehicle speed signal is calculated, and the formula is: ; If the third absolute deviation is less than or equal to a third deviation threshold , it is determined that the output shaft speed converted vehicle speed signal is reliable, and the output shaft speed reliable flag is set to an active state, and is set as the lowest priority reliable candidate; otherwise, it is determined that the output shaft speed converted vehicle speed signal is not reliable, and the output shaft speed reliable flag is set to an inactive state.

[0041] Through the calculation of the absolute deviation between the multiple source signals in the S31 step, the system can quantitatively evaluate the consistency of each signal source. This deviation calculation mechanism can effectively identify signal abnormalities caused by sensor failure, electromagnetic interference or environmental factors. For example, when the ABS vehicle speed signal jumps due to temporary failure of the wheel speed sensor, the deviation between it and the instrument vehicle speed or the output shaft vehicle speed will exceed the threshold, triggering the unreliable flag, and avoiding the propagation of false signals to the vehicle control system.

[0042] The threshold judgment and delay verification mechanism introduced in the S32 and S33 steps ensures the dynamic adaptability of signal evaluation. The threshold can be dynamically adjusted according to the vehicle speed range (such as 3 km / h at low speed and expanded to 8 km / h at high speed), avoiding false judgments of fixed thresholds in extreme working conditions. For example, when the vehicle is turning, the left and right wheel speed difference will cause inherent deviation of the ABS vehicle speed, but through the third deviation check, the system can preferentially select the output shaft or instrument vehicle speed, reducing the vehicle speed calculation error in the turning condition to within 2%. At the same time, the delay mechanism (such as triggering the flag change only when the threshold is exceeded for 3 consecutive sampling periods) filters transient disturbances (such as wheel speed fluctuations caused by road bumps), preventing signal oscillation caused by frequent switching.

[0043] The priority logic in the S33 step builds a hierarchical redundancy architecture. When a single signal source fails (such as ABS due to loose wiring), the system can automatically switch to the backup signal source (output shaft or instrument vehicle speed), and through the lowest priority design (output shaft vehicle speed as the final backup), it ensures signal continuity.

[0044] Through real-time evaluation of the reliable flag, the system can actively identify potential risks (such as long-term failure of the instrument GPS module), and provide maintenance prompts for the driver. In addition, the redundancy verification mechanism reduces the vehicle movement or shift impact caused by signal jumps, especially in low-speed crawling and tunnel crossing scenarios, smooth signal transition improves driving comfort.

[0045] Additionally, step S4 comprises: S41, determining candidate vehicle speed according to the trusted flag outputted in step S3 , and the ABS optimized vehicle speed in priority order: ; wherein, is the selected vehicle speed; S42, introducing a time delay judgment mechanism in the selection process of step S41, triggering signal switching when the untrusted state of the signal lasts more than a preset time threshold .

[0046] Further, step S4 further comprises: applying a first-order low-pass smoothing filter algorithm to the selected vehicle speed signal at signal switching, outputting the final vehicle speed signal, and the smoothing filter formula is: ; wherein, is the final vehicle speed output signal at time k, with the unit of km / h; is the weight coefficient; is the final vehicle speed output signal at time k-1, with the unit of km / h; is the selected vehicle speed signal at time k based on step S41, with the unit of km / h.

[0047] Through the priority logic of step S41 , the optimal signal source can be dynamically selected according to the trusted flag bit of step S3 and . This mechanism ensures that the ABS optimized vehicle speed is the first choice, and the instrument vehicle speed is the final backup, forming a hierarchical redundant structure. For example, when the ABS is temporarily disabled due to electromagnetic interference , the system automatically switches to the output shaft speed converted vehicle speed , avoiding signal interruption.

[0048] The time delay judgment mechanism introduced in step S42 (preset time threshold ) requires that the untrusted state of the signal lasts more than a set time (for example, 3 sampling periods, about 300 milliseconds) to trigger switching. This design effectively filters short-term interference (such as wheel speed jump caused by road bumps), preventing false actions. For example, when the vehicle passes through a speed bump, the ABS speed may be temporarily above the threshold, but because the duration is less than , the system maintains the original signal, avoiding unnecessary switching.

[0049] The system realizes gradual transition at signal switching by a first-order low-pass smoothing filter formula. The smoothing coefficient (usually 0.6-0.8) controls the filtering strength, balancing the response speed and stability. For example, when switching from ABS vehicle speed to output shaft vehicle speed, the filtering algorithm limits the signal change rate within 2 km / h per sample, avoiding the transmission system impact (such as gear shifting jerk) or cruise control oscillation caused by sudden vehicle speed change.

[0050] The output of step S4 is the core input of the vehicle control system, and its smoothness and continuity directly affect the performance of ADAS (Advanced Driver Assistance Systems). Smooth filtering ensures that the vehicle speed signal has no step change when switching, providing a stable reference for adaptive cruise control (ACC) and automatic transmission control. For example, when the GPS signal is lost in a tunnel scenario, the system switches to the output shaft vehicle speed and smoothly transitions through filtering, avoiding unexpected exit of the ACC function and ensuring driving safety. At the same time, the combination of the delay mechanism and the filtering algorithm meets the ISO 26262 standard requirements for signal integrity ASIL B level.

[0051] Finally, step S5 includes: S51, determining the final vehicle speed signal of step S4 performing data format standardization processing to convert the vehicle speed value into a numerical coding format conforming to the vehicle CAN bus communication protocol, the calculation formula is ; is the CAN bus coding value of the vehicle speed signal, which is a 16-bit integer; is the scaling coefficient, taking the value of 2, used to map the vehicle speed value to the coding range; is the offset, taking the value of 0, ensuring that 0 km / h corresponds to the coding value 0; is the rounding function, which maps the vehicle speed range of 0-120 km / h to the coding range of 0-240 through the formula; S52, constructing a CAN bus data frame containing the vehicle speed signal, defining the data frame structure according to the SAE J1939 protocol, including frame start, arbitration field, control field, data field, CRC field, ACK field and frame end, the arbitration field contains priority, data page and PDU format, wherein the data field length is 2 bytes, used to store the calculated in step S51, and the data frame identifier is determined by the formula , wherein is the 11-bit identifier of the CAN bus data frame; is the priority, taking the value of 6 to ensure the transmission priority of the vehicle speed signal; This is a data page, with a value of 0 representing a basic data page; It is in PDU format, with a value of 236, corresponding to the PGN of the vehicle speed signal; this identifier ensures that the vehicle control system can accurately identify the vehicle speed signal frame. S53. Send the CAN bus data frame to the vehicle control system and verify the transmission validity, then set the sending period. Press via the TCU's CAN controller Data frames are sent periodically.

[0052] Step S5 also includes: S54. After sending, monitor the ACK response signal at the receiving end. If no response is received after three consecutive transmissions, proceed according to the formula. Set the highest bit of the encoded value to 1 (in the formula) This is an encoded value with error marking (0x8000 is the error marking mask), and triggers a retry mechanism with a retry interval of [number missing]. Increasing (in the formula) The retry interval is in milliseconds; n is the number of retries (initial value is 1, maximum value is 3). If the retries fail after 3 attempts, a fault code is recorded and the vehicle speed signal transmission is indicated on the instrument panel. S55. The vehicle control system receives and analyzes the vehicle speed signal according to the formula. Restore the actual vehicle speed value (in the formula) The vehicle speed value obtained by the receiving end (unit: km / h) is compared with the preset reasonable range (0~120km / h). If it is within the range, it is used for functions such as vehicle power control and braking adjustment; if it is outside the range, it is determined to be an invalid signal, and the most recent valid vehicle speed value is used to ensure the stable operation of the vehicle control system.

[0053] The vehicle speed signal is converted into a 16-bit integer code (range 0-240) conforming to the CAN bus protocol using the standardized formula in step S51. The scaling factor ensures a linear mapping across the vehicle speed range of 0 km / h to 120 km / h, achieving a coding resolution of 0.5 km / h / LSB (least significant bit), significantly better than the 1.5 km / h / LSB resolution of traditional 8-bit coding. This design allows different controllers (such as ECU and ABS modules) to losslessly resolve vehicle speed values, avoiding parsing errors caused by data format differences.

[0054] The S52 step strictly follows the SAE J1939 protocol to construct data frames. The identifier calculation formula uses a priority P=6, data page DP=0, and PDU format PF=236 configuration to ensure that vehicle speed signals are transmitted with high priority (second only to braking / steering control signals), and that the PGN (parameter group number) is uniquely identified by the entire vehicle system. The data field has a fixed length of 2 bytes (for storage). ) and CRC check field, the bus transmission error rate is reduced to In the following, the integrity requirements of the safety-critical signals according to the ISO 14229 standard are met.

[0055] S53 step sets the sending period (typical value 100 ms) and is scheduled by the CAN controller hardware of the TCU, ensuring that the vehicle speed signal is updated at a fixed frequency, meeting the real-time requirements (delay < 150 ms) of functions such as adaptive cruise control. The ACK monitoring and retry mechanism of S54 step effectively deals with bus transient congestion.

[0056] S55 step restores the vehicle speed value at the receiving end through a formula and combines with a reasonableness range check (0-120 km / h), effectively filtering out jump values (e.g. suddenly changing to 250 km / h) caused by electromagnetic interference. If the signal is out of limits, the system automatically uses the most recent valid value (maintaining time up to 500 ms) to prevent transmission system misoperation (e.g. sudden acceleration / braking) caused by abnormal signals.

[0057] The fault code recording function (e.g. vehicle speed signal transmission timeout code U0101) of S54 step is linked with the instrument prompt, enabling the driver to promptly know the system status. The retry count limit (maximum 3 times) and the incremental interval design avoid excessive occupation of bus resources, while providing a clear troubleshooting path for maintenance personnel.

[0058] In some embodiments, the commercial vehicle vehicle speed signal processing system based on TCU multi-source signals 200 can include a plurality of functional modules composed of computer program segments. The computer programs of each program segment in the commercial vehicle vehicle speed signal processing system based on TCU multi-source signals 200 can be stored in the memory of the computer device and executed by at least one processor to perform (see Figure 1 Description) the functions of the commercial vehicle vehicle speed signal processing based on TCU multi-source signals.

[0059] In this embodiment, the commercial vehicle vehicle speed signal processing system based on TCU multi-source signals 200 can be divided into a plurality of functional modules according to the functions it performs, as shown in Figure 2 The functional modules can include a multi-source speed acquisition module 210, a filtering processing module 220, a speed credibility evaluation module 230, an optimal vehicle speed selection module 240, and a vehicle speed output module 250. The module referred to by the present application refers to a series of computer program segments that can be executed by at least one processor and can complete a fixed function, which are stored in the memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0060] Specifically, the multi-source speed acquisition module 210 is configured to acquire ABS vehicle speed signals, instrument vehicle speed signals and gearbox output shaft speed signals; the filtering processing module 220 is configured to perform Kalman filtering processing on the acquired ABS vehicle speed signals to suppress noise and output optimized vehicle speed signals; the speed credibility evaluation module 230 is configured to perform redundancy checking and credibility evaluation on the instrument vehicle speed signals, the optimized ABS vehicle speed signals and the vehicle speed signals converted from the output shaft speed; the optimal vehicle speed selection module 240 is configured to dynamically select optimal vehicle speed signals according to the checking results and perform smooth switching when the signal source is abnormal; and the vehicle speed output module 250 is configured to output the final vehicle speed signals to the vehicle control system.

[0061] Figure 3 A structure schematic diagram of a terminal 300 is provided for the embodiment of the present application, and the terminal 300 can be used to execute the commercial vehicle speed signal processing method based on TCU multi-source signals provided by the embodiment of the present application.

[0062] The terminal 300 can include a processor 310, a memory 320 and a communication module 330. These components communicate through one or more buses, and those skilled in the art can understand that the structure of the server shown in the figure does not constitute a limitation on the present application, which can be a bus structure or a star structure, and can include more or fewer components than shown in the figure, or combine some components or different component arrangements.

[0063] The memory 320 can be used to store the execution instructions of the processor 310, and the memory 320 can be realized by any type of volatile or non-volatile storage terminal or their combination, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 can execute part or all of the steps in the following method embodiments.

[0064] The processor 310 is a control center of the storage terminal, connects various parts of the entire electronic terminal by using various interfaces and lines, and executes various functions of the electronic terminal and / or processes data by running or executing software programs and / or modules stored in the memory 320 and calling data stored in the memory. The processor can be composed of an integrated circuit (IC), for example, can be composed of a single packaged IC, or can be composed of a plurality of packaged ICs connected together. For example, the processor 310 can only include a central processing unit (CPU). In the embodiments of the present application, the CPU can be a single operation core or can include multiple operation cores.

[0065] The communication module 330 is configured to establish a communication channel, so that the storage terminal can communicate with other terminals. The communication module 330 receives user data sent by other terminals or sends user data to other terminals.

[0066] The present application also provides a computer storage medium, wherein the computer storage medium can store a program, and the program can include some or all steps in the embodiments of the present application when executed. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0067] Those skilled in the art can clearly understand that the technology in the embodiments of the present application can be realized by means of software and necessary general hardware platforms. Based on such understanding, the technical solutions in the embodiments of the present application can be embodied in the form of a software product, which is stored in a storage medium such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc. The software product includes a plurality of instructions for causing a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the method described in the embodiments of the present application.

[0068] In the present specification, the same or similar parts among various embodiments can be referred to each other. In particular, for the terminal embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

[0069] In several embodiments provided by the present application, it should be understood that the disclosed system and method can be implemented in other manners. For example, the system embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There can be another division manner for the actual implementation. For example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different modules can be indirect couplings or communication connections through some interfaces, and electrical, mechanical or other forms.

[0070] The modules illustrated as separated components can or can not be physically separated, and the components illustrated as modules can or can not be physical modules, i.e., can be located in one place, or can be distributed to a plurality of network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0071] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0072] Although the present application has been described in detail by referring to the preferred embodiments thereof, it is to be understood that the present application is not limited to the embodiments described above. Rather, it should be appreciated that those skilled in the art, upon consideration of the disclosure, can make modifications and / or improvements to the embodiments of the application without deviating from the spirit and scope of the application. Any modifications and / or improvements made to the embodiments of the application by those skilled in the art are to be considered within the scope of the application.

Claims

1. A commercial vehicle speed signal processing method based on TCU multi-source signals, characterized in that, Comprising: S1, collecting ABS speed signal, instrument speed signal and gearbox output shaft speed signal; S2, Kalman filtering processing the collected ABS speed signal to suppress noise and output the optimized speed signal; S3, performing redundancy check and credibility evaluation on the instrument speed signal, the optimized ABS speed signal and the speed signal converted from the output shaft speed; S4, dynamically selecting the optimal speed signal according to the check result and performing smooth switching when the signal source is abnormal; S5, outputting the final speed signal to the vehicle control system.

2. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 1, characterized in that, Step S1 comprises: S11, connecting the vehicle CAN bus through TCU to collect ABS speed signal from ABS control system in real time, which is calculated by ABS system based on front wheel speed sensor data, specifically taking the average of left front wheel and right front wheel speed; S12, connecting the vehicle CAN bus through TCU to collect instrument speed signal from instrument panel control system synchronously, which is derived from GPS module; S13, connecting gearbox sensor through TCU to collect gearbox output shaft speed signal in real time, and converting the output shaft speed signal to corresponding speed value by conversion formula, the conversion formula is: ； wherein, represents the vehicle speed information corresponding to the transmission output shaft speed after conversion, with the unit of kilometer / hour; represents the transmission output shaft speed, with the unit of revolution / minute, which is a direct measurement value from the transmission sensor; represents the vehicle tire radius, with the unit of meter, which is a pre-labeled fixed parameter of the vehicle; represents the vehicle rear axle speed ratio.

3. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 2, characterized in that, Step S2 comprises: S21. Establish the system state equation and observation equation for the Kalman filter, where the system state equation is set as follows: The observation equation is set as In the formula Let A be the ABS vehicle speed prior state estimate at time k, in km / h; A is the state transition matrix. is the posterior state estimate of the ABS vehicle speed at the previous time k-1, in km / h; B is the control input matrix. This is the control input vector for the previous time step k-1; The original ABS vehicle speed signal collected at the current time k, in km / h; The observation matrix; The observation noise at the current time k; S22, calculating the prior covariance matrix in Kalman filtering prediction stage: ； wherein is the prior covariance matrix for the current time instant k, units: ; is the posterior covariance matrix for the previous time instant k-1, units: ; is the transpose of the state transition matrix A; is the process noise covariance matrix; S23, calculating Kalman gain and completing state correction and covariance update in update stage, the calculation formula of Kalman gain is: ； wherein, is the Kalman gain for the current time instant k; is the transpose of the observation matrix H; R is the observation noise covariance matrix; is the inverse of the matrix is the inverse of the matrix According to the formula The ABS vehicle speed posterior state estimation value at the current time k is obtained, and the posterior covariance matrix is updated according to the formula The ABS vehicle speed posterior state estimation value at the current time k is obtained, and the posterior covariance matrix is updated according to the formula The ABS vehicle speed signal optimized at the current time k is The unit matrix is 1. The posterior covariance matrix at the current time k is used for the priori covariance calculation of the next filtering period. S24, judging the filtered and optimized ABS vehicle speed signal whether it is in the preset vehicle speed range, if the actual driving vehicle speed interval of the commercial vehicle, i.e. 0~120km / h; then the filtered and optimized ABS vehicle speed signal is taken as the final output of step S2; if it is out of the interval, the posterior state estimation value of the previous time k-1 is taken as the output. ​ 4. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 3, characterized in that, Step S3 comprises: S31, calculating the first absolute deviation between the optimized ABS speed signal and the instrument speed signal, and calculating the second absolute deviation between the optimized ABS speed signal and the output shaft speed converted speed signal, the calculation formulas of the first absolute deviation and the second absolute deviation are respectively: ； ； wherein, is a first absolute deviation; is an optimized ABS vehicle speed signal at the current time instant k; is an instrument vehicle speed signal; denotes the converted vehicle speed information corresponding to the gearbox output shaft rotational speed; is a second absolute deviation; S32, Based on the preset first deviation threshold For the first absolute deviation Make a judgment when the first absolute deviation occurs within a consecutive preset time period. Less than or equal to the first deviation threshold At that time, configure the instrument's trust flag bit. Otherwise, set to 0; based on the preset second deviation threshold. For the second absolute deviation Make a judgment when the second absolute deviation occurs within a consecutive preset time period. Less than or equal to the second deviation threshold At that time, configure the instrument's trust flag bit. Set to 1 if the value is 1, otherwise set to 0. S33, if or At least one of the above conditions is true, it is determined that the ABS vehicle speed is reliable and the candidate optimal signal; if both are not true, a third absolute deviation between the output shaft speed converted vehicle speed signal and the instrument vehicle speed signal is calculated, and the calculation formula is: ； If the third absolute deviation is less than or equal to the third deviation threshold , then determine that the output shaft speed converted vehicle speed signal is reliable, set the output shaft speed reliable flag to an active state, and set as the lowest priority reliable candidate; otherwise, determine that the output shaft speed converted vehicle speed signal is unreliable, and set the output shaft speed reliable flag to an inactive state.

5. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 4, characterized in that, Step S4 comprises: S41. Output the trust flag according to step S3 , and the ABS optimized vehicle speed determine the candidate vehicle speed in priority order: ； wherein, V is the selected vehicle speed; S42, in the selection process of step S41, introduce a time delay judgment mechanism, when the signal is not trusted state continues to exceed the preset time threshold , trigger signal switching.

6. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 5, characterized in that, Step S4 further comprises: At the signal switching time, the selected vehicle speed signal A first-order low-pass smoothing filter algorithm is applied to output the final vehicle speed signal, and the smoothing filter formula is: ； wherein, is the final vehicle speed output signal at time k, in km / h; is a weight coefficient; is the final vehicle speed output signal at time k-1, in km / h; is the vehicle speed signal selected based on step S41 at time k, in km / h.

7. The TCU multi-source signal fusion based commercial vehicle speed signal processing method according to claim 6, characterized in that, Step S5 comprises: S51, final vehicle speed signal determined in step S4 The data format standardization process is performed to convert the vehicle speed value into a numerical coding format that conforms to the vehicle CAN bus communication protocol, and the calculation formula is ; is the CAN bus coding value of the vehicle speed signal; is the scaling factor; is the offset; is the rounding function, and the formula maps the vehicle speed range of 0-120 km / h to the coding range of 0-240. S52, construct a CAN bus data frame containing the vehicle speed signal, define the data frame structure according to the SAE J1939 protocol, including frame start, arbitration field, control field, data field, CRC field, ACK field and frame end, the arbitration field contains priority, data page and PDU format, wherein the length of the data field is 2 bytes, used to store the vehicle speed signal calculated in step S51 , and determine the data frame identifier by the formula , wherein is an 11-bit identifier of the CAN bus data frame; is the priority; is the data page; is the PDU format; S53. Send the CAN bus data frame to the vehicle control system and verify the transmission validity, then set the sending period. Press via the TCU's CAN controller Data frames are sent periodically.

8. A commercial vehicle vehicle speed signal processing system based on TCU multi-source signals, characterized by, Comprising: A multi-source speed acquisition module for collecting ABS speed signal, instrument speed signal and gearbox output shaft speed signal; A filtering processing module for Kalman filtering processing the collected ABS speed signal to suppress noise and output the optimized speed signal; A speed credibility evaluation module for performing redundancy check and credibility evaluation on the instrument speed signal, the optimized ABS speed signal and the speed signal converted from the output shaft speed; An optimal speed selection module for dynamically selecting the optimal speed signal according to the check result and performing smooth switching when the signal source is abnormal; A speed output module for outputting the final speed signal to the vehicle control system.

9. A terminal, characterized by comprising: Comprising: A processor; A memory for storing the execution instructions of the processor; Wherein the processor is configured to execute the method of any one of claims 1-7.

10. A computer readable storage medium storing a computer program, characterized in that, The program is executed by the processor to implement the method of any one of claims 1-7. The program is executed by the processor to implement the method of any one of claims 1-7.

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