A method for detecting ripple of a direct current motor of an active grille shutter driver of an automobile

Abstract

The application provides a kind of automobile active air intake grille driver DC motor ripple detection method, belong to the field of automobile electronic control technology.The method includes: the instantaneous current of DC brush motor and power voltage are real-time sampled and the current is digitally low-pass filtered;According to the slope sign change of filtered current, the current minimum value of each ripple period is detected and the power voltage is recorded synchronously;Based on the preset extreme value mapping model, the current maximum value of the current minimum value and the power voltage is calculated in the ripple period;According to the current minimum value and maximum value, the dynamic determination condition is set, the subsequent filtered current is judged, and the effective ripple is determined and accumulated when the condition is met;Repeat the above steps until the motor operation ends to get the total ripple number.The application does not need additional sensors and hardware pre-circuit, realizes high-precision counting of ripple through digital filtering and numerical calculation, improves the anti-interference ability and position detection reliability.

Description

Technical Field

[0001] This invention belongs to the field of automotive electronic control technology, and more specifically relates to a method for detecting the ripple of a DC motor in an active grille driver for automobiles. Background Technology

[0002] As a key component in vehicle thermal management and aerodynamic adjustment, the active grille actuator needs to receive commands from the vehicle domain controller to drive a DC brushed motor to perform functions such as grille self-learning (i.e., performing full opening and full closing to obtain the total stroke), running to the target position, self-operation in sleep or fault states, and motor position memorization during sleep. In all these processes, obtaining the precise current position of the motor is a core prerequisite for the stable and reliable operation of the grille system. However, how to achieve accurate motor position detection under low cost and high robustness has always been a technical challenge in this field.

[0003] Currently, traditional motor position detection schemes are mainly divided into two categories. The first category is the encoder sampling scheme, which typically uses Hall encoders or photoelectric encoders. The motor output shaft drives the magnet or photoelectric code disk to rotate, converting the mechanical position into a digital level signal, which is then sampled by a microcontroller (MCU) to obtain the motor's speed and position information. The second category is the hardware ripple sampling scheme, which utilizes the current ripple generated during the commutation of a DC brushed motor. A hardware bandpass filter is used to filter out the DC component and some harmonics, and then a hardware comparator converts the ripple into high and low level signals for the MCU to count. The motor's running position and speed are calculated by counting the ripples.

[0004] However, both of the aforementioned existing technologies have significant drawbacks. For encoder solutions: First, they require additional hardware such as magnets and Hall effect chips, significantly increasing product costs. Second, encoder solutions involve independent power supply for sensors and additional electrical connections, requiring complex mechanical alignment and integration processes, resulting in high overall system complexity and low production assembly efficiency. Third, the magnetic or photoelectric components in the encoder are prone to performance drift or even failure under harsh environmental conditions such as high and low temperatures, reducing the system's reliability in automotive environments. Fourth, in micro-motor applications, encoders occupy a large space, hindering the miniaturization design of the grille driver. For traditional hardware ripple sampling solutions: On the one hand, they require additional electronic components such as resistors, capacitors, and operational amplifiers to construct bandpass filters and comparator circuits, further increasing hardware costs and system complexity. On the other hand, this solution relies on fixed-parameter hardware filtering; when motor load changes or power supply voltage fluctuations cause the ripple waveform to contain various abnormal harmonics, the hardware circuitry struggles to adaptively process these, easily leading to missed or incorrect ripple measurements, resulting in inaccurate position detection and consequently affecting the accuracy of grille self-learning and position closed-loop control. Summary of the Invention

[0005] To address the above problems, the present invention aims to provide a method for detecting ripple in a DC motor of an active grille driver for automobiles. By sampling the motor current and voltage in real time, and combining software low-pass filtering, slope trough detection, peak estimation based on a pre-calibrated extreme value mapping model, and dynamic threshold determination algorithm, a low-cost, high-precision, and highly interference-resistant DC brushed motor ripple detection and position tracking is achieved without the need for additional sensors and hardware front-end circuitry.

[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, embodiments of this application provide a method for detecting ripple in a DC motor of an active grille shutter driver for automobiles, comprising the following steps: S1: Real-time sampling of the instantaneous current and power supply voltage of the DC brushed motor to obtain the original current sampling value and power supply voltage value, and digital low-pass filtering processing of the original current sampling value to output the filtered current value. S2: Calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value of each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected. S3: Based on the preset extreme value mapping model, calculate the maximum current value of this ripple cycle according to the detected minimum current value and the synchronously recorded power supply voltage value. S4: Set dynamic judgment conditions based on the minimum and maximum current values, and make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic judgment conditions are met, determine that a valid ripple has been detected, and increment the valid ripple count once. S5: Repeat steps S1 to S4 until the DC brushed motor finishes running, and obtain the total number of ripples detected during the entire operation.

[0007] In an optional implementation, step S1 includes: The original current sample value is obtained by performing sampling through the 12-bit analog-to-digital converter built into the microcontroller unit. and power supply voltage value Among them, the sampling period Triggered by a 20kHz PWM signal, the sampling frequency is more than 10 times the highest frequency of the DC brushed motor ripple. According to the preset cutoff frequency Through formula Calculate the time constant And according to the sampling period Through formula Calculate the filter coefficients ; The original current sample value is filtered using the following formula. Perform filtering:

[0008] in, For the first The filtered output current value after the second sampling. This is the output current value from the previous filter.

[0009] In an optional implementation, step S2 includes: Through formula The slope is calculated as the difference between the current values ​​after two consecutive filters. ; Real-time monitoring The sign change, when detected When the value changes from negative to positive, the filtered current value at the current moment is determined as the minimum detected current value. And simultaneously record the power supply voltage value at that moment. .

[0010] In an optional implementation, the process of setting the extreme value mapping model includes: Measure the minimum current of a DC brushed motor under different power supply voltages and load conditions. and maximum current And simultaneously record the power supply voltage value. ;Specifically: Multiple voltage points were selected within a voltage range of 9V to 16V. At each voltage point, multiple load points were selected from no-load to heavy-load. The experimental data for each set were measured and recorded. Each set of data included the power supply voltage value. Minimum current and maximum current ; At each fixed voltage point Next, the least squares method is used to analyze the... and Perform linear fitting and calculate the proportional gain at that voltage point using the following formula. and offset :

[0011] in, This represents the number of load points at the current voltage level. All voltage points and their corresponding and Substituting each value into a quadratic polynomial fit, the six global coefficients are obtained by solving the following matrix equation. :

[0012]

[0013] in, The number of voltage points, For the first Voltage value at a fixed voltage point and These are the proportional coefficient and offset obtained by fitting at that voltage point, respectively; The six global coefficients The data is stored in the microcontroller unit, and the following extreme value mapping model is established:

[0014] in, , , This is the power supply voltage value.

[0015] In an optional implementation, step S3 includes: Based on the aforementioned extreme value mapping model, according to the detected minimum current value... and synchronously recorded power supply voltage Using the formula The maximum current value of this ripple cycle is calculated. .

[0016] In an optional implementation, the dynamic determination condition is: Current filtered current value Satisfying inequalities ,in The preset ratio threshold; Different proportional thresholds are selected based on the operating state of the DC brushed motor before the start-up phase of the DC brushed motor. Within each ripple cycle, take During the normal operation, braking, and stall phases of the DC brushed motor, take... The The value represents the number of ripple cycles that need to be compensated during the startup phase.

[0017] In an optional implementation, step S4 further includes: When the minimum current is detected Subsequently, if in subsequent sampling, the dynamic determination condition is not met until the slope changes from a positive value to a negative value, then the current condition is determined to be... If the current is invalid, discard this ripple count and re-detect the next minimum current value.

[0018] In one optional implementation, the total number of ripples detected throughout the entire operation. Through formula or calculate; in, The effective ripple count accumulated during the startup phase of the DC brushed motor, For the effective ripple count accumulated during the operation phase, For the effective ripple count accumulated during the braking phase, Effective ripple count accumulated during the stall phase .

[0019] In an optional implementation, the method further includes: Based on the total ripple count obtained by accumulation The actual rotation angle of the active air intake grille can be calculated using the following formula. :

[0020] in, The number of ripples generated per revolution of the DC brushed motor. This refers to the gearbox transmission ratio; The calculated actual rotation angle With preset grille expected travel If a comparison is made, If so, it is determined to be a mechanical failure of the grille; if If the condition is normal, it is determined to be a grid stall fault; otherwise, it is determined to be normal.

[0021] Secondly, embodiments of this application also provide a DC motor ripple detection system for an active grille shutter driver for automobiles, comprising: The sampling and filtering module is used to sample the instantaneous current and power supply voltage of the DC brushed motor in real time, obtain the original current sampling value and power supply voltage value, and perform digital low-pass filtering on the original current sampling value to output the filtered current value. The minimum value detection module is used to calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value in each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected. The maximum value calculation module is used to calculate the maximum current value of the current in the current ripple cycle based on the detected minimum current value and the synchronously recorded power supply voltage value, according to the preset extreme value mapping model. The effective ripple determination and counting module is used to set dynamic determination conditions based on the minimum and maximum current values, and to make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic determination conditions are met, an effective ripple is detected, and the effective ripple count is incremented. The control module is used to repeatedly trigger the sampling and filtering module, the minimum value detection module, the maximum value calculation module, and the effective ripple determination and counting module to perform operations until the DC brushed motor finishes running, and to obtain the total number of ripples detected during the entire operation.

[0022] As can be seen from the above technical solutions, the present invention has the following advantages: The DC motor ripple detection method for the active grille driver provided in this application achieves high-precision and high-reliability counting of DC brushed motor ripple by sampling motor current and voltage in real time and combining algorithms such as software low-pass filtering, slope valley detection, ripple peak estimation based on a pre-calibrated extreme value mapping model, dynamic threshold determination, and start-up compensation. This allows for accurate acquisition of motor position without adding extra sensors or complex hardware front-end circuits, significantly reducing system cost and space occupation, and greatly improving robustness and ripple counting accuracy in harsh environments.

[0023] This application only requires a current sampling resistor and a 12-bit ADC built into the microcontroller. It does not require sensors such as magnets, Hall chips, or photoelectric encoders, nor does it require hardware bandpass filters, comparators, or operational amplifiers. This significantly reduces the number of electronic components and installation process requirements, thereby reducing material costs, PCB area, and system development difficulty.

[0024] This application establishes an extreme value mapping model between the minimum and maximum current values ​​and uses real-time power supply voltage for parameter compensation, which can adapt to changes in motor load and voltage fluctuations. Combined with slope zero-crossing detection to accurately capture troughs and dynamic threshold to determine effective ripple, it effectively filters out abnormal harmonic interference, improves the position accuracy of a single stroke, and effectively reduces the ripple counting error rate.

[0025] This application does not rely on magnetic or photoelectric components and is unaffected by harsh automotive environments such as high and low temperatures and vibrations, avoiding performance drift or failure caused by environmental factors in traditional encoder solutions. Furthermore, it eliminates the need for sensor power supply and mechanical alignment, improving the long-term reliability of the system.

[0026] This application addresses the nonlinear ripple characteristics during motor startup by implementing a startup compensation mechanism that accurately identifies ripple during the startup phase. It also includes invalid valley rejection logic to avoid miscounting caused by harmonic glitches, ensuring stable and reliable position tracking of the motor throughout the entire process from startup and operation to braking or stall.

[0027] This application, by accumulating the effective ripple during each stage of startup, operation, and braking / stalling, and combining the gearbox transmission ratio and the number of ripples per motor revolution, can accurately calculate the actual rotation angle of the grille, realize the grille's self-learning function, and automatically judge mechanical faults or stall faults, thereby improving the system's intelligence level and maintenance convenience. Attached Figure Description

[0028] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying 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.

[0029] Figure 1 A schematic flowchart illustrating the DC motor ripple detection method for the automotive active grille driver provided in this application.

[0030] Figure 2 A schematic diagram illustrating the principle of current ripple generation in a DC brushed motor provided in this application.

[0031] Figure 3 The curve showing the relationship between the minimum and maximum current ripple values ​​provided in this application.

[0032] Figure 4 The waveform diagram of the current ripple during the start-up phase of the DC brushed motor provided in this application.

[0033] Figure 5 This is a schematic diagram of the fully open state of the active air intake grille provided in this application.

[0034] Figure 6 This is a schematic diagram of the fully closed state of the active grille shutter of the vehicle provided in this application.

[0035] Figure 7 A schematic diagram of the DC motor ripple detection system for the automotive active grille driver provided in this application. Detailed Implementation

[0036] The various embodiments of this disclosure will be described more fully in the following detailed description of the specific steps of the method for detecting ripple in a DC motor of an active grille shutter driver for automobiles. This disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of this disclosure to the specific embodiments disclosed herein, but rather this disclosure should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of this disclosure.

[0037] In the following, the terms “comprising” or “may include”, which may be used in various embodiments of this disclosure, indicate the presence of the disclosed functions, operations, or elements, and do not limit the addition of one or more functions, operations, or elements. Furthermore, as used in various embodiments of this disclosure, the terms “comprising,” “having,” and their cognates are intended only to indicate a particular feature, number, step, operation, element, component, or combination of the foregoing, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing, or the possibility of adding one or more combinations of the foregoing.

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figure 1 The diagram shows a flowchart of a method for detecting ripple in a DC motor of an active grille shutter driver in a specific embodiment. The method includes: S1: Real-time sampling of the instantaneous current and power supply voltage of the DC brushed motor to obtain the original current sampling value and power supply voltage value, and digital low-pass filtering processing of the original current sampling value to output the filtered current value.

[0040] First, the instantaneous current and power supply voltage of the DC brushed motor are sampled in real time. The core cause of the current ripple in the DC brushed motor lies in its mechanical commutation process: when the brushes switch commutator segments, the short-circuited armature winding, due to its inductive characteristics, cannot experience a sudden change in internal current and will continuously decay; simultaneously, the power supply needs to establish new current for other windings. This periodic process of "decay and reconstruction" superimposes a regular pulsating waveform on the macroscopic current, such as... Figure 2 As shown.

[0041] In this specific implementation, sampling is performed using a 12-bit analog-to-digital converter (ADC) built into the microcontroller unit (MCU). The sampling period is set to... The ADC conversion is triggered by a PWM signal with a frequency of 20kHz to ensure that the sampling frequency is greater than 10 times the highest frequency of the motor ripple. The DC brushed motor selected in this embodiment has a 2-carbon-brush, 3-commutator structure. The motor generates 6 ripples per revolution, and the maximum speed is 9000RPM. The corresponding highest ripple frequency is about 900Hz. Therefore, the 50μs sampling period (equivalent to a 20kHz sampling rate) fully meets the requirements of the Nyquist sampling theorem and can completely capture the ripple waveform characteristics.

[0042] Sampling to obtain the original current sample value and power supply voltage value Next, the current signal needs to be digitally low-pass filtered to eliminate high-frequency noise and harmonic interference. The filter design is as follows: First, based on the preset cutoff frequency... Calculate the time constant Seconds. Then based on the sampling period. Calculate the filter coefficients of a first-order low-pass filter. The filtering formula is:

[0043] in, For the first The filtered output current value after the second sampling. This represents the output current value from the previous filter. Through this recursive formula, high-frequency glitches in the original current are effectively suppressed while preserving the main trend of ripple variation.

[0044] S2: Calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value in each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected.

[0045] In a specific implementation, after obtaining the filtered current value Subsequently, it is necessary to detect the minimum current value (trough) of each ripple cycle in real time. This invention employs a slope zero-crossing detection method. Specifically, the difference between two adjacent filtered current values ​​is calculated as the slope:

[0046] This slope reflects the instantaneous trend of current change. When the motor reverses direction, the current first decreases and then increases, so the slope changes from negative to positive. This can be achieved through real-time monitoring. The sign change is determined by the moment the slope changes from negative to positive; the filtered current value at that moment is then identified as the minimum detected current value. And simultaneously record the power supply voltage value at that moment. For example, in a certain sampling, the continuously calculated slope sequence is -0.03A, -0.01A, +0.02A. Then, at the critical point where the slope changes from negative to positive, the current value after filtering is... This method can accurately capture the trough position of each ripple cycle, unaffected by amplitude fluctuations.

[0047] S3: Based on the preset extreme value mapping model, calculate the maximum current value of this ripple cycle according to the detected minimum current value and the synchronously recorded power supply voltage value.

[0048] The core of this invention lies in utilizing the minimum current value. Calculate the maximum current within the same ripple period This avoids potential misjudgments that might result from directly detecting the peak. For example... Figure 3 As shown in the figure, experiments revealed that under different load and voltage conditions, the minimum current ripple value... With the maximum value There exists a stable linear relationship between them, and this relationship is affected by the power supply voltage. Regulation. To this end, it is necessary to establish an extreme value mapping model beforehand through experiments. Therefore, in a specific implementation, this step specifically includes the following two processes: (a) Pre-calibration process.

[0049] Measure the minimum current of a DC brushed motor under different power supply voltages and load conditions. and maximum current And simultaneously record the power supply voltage value. Specifically, multiple voltage points (e.g., 9V, 12V, 16V) were uniformly selected within the voltage range of 9V to 16V. At each voltage point, multiple load points (e.g., no load, 20% load, 40% load, 60% load, 80% load) were uniformly selected from no-load to heavy-load. Experimental data for each set were recorded using a high-bandwidth current sensor and an oscilloscope. Each set of data included the power supply voltage value. Minimum current and maximum current .

[0050] At each fixed voltage point Next, using the least squares method to... and Perform linear fitting and calculate the proportional gain at that voltage point. and offset :

[0051] in, This represents the number of load points at the current voltage point (m=5 in this example). For example, at a 12V voltage point, the result is calculated after obtaining 5 sets of data. , .

[0052] All voltage points and their corresponding and Substituting each value into a quadratic polynomial fit, the six global coefficients are obtained by solving the following matrix equation. :

[0053]

[0054] in This represents the number of voltage points (p=3 in this example). After calculating the global coefficients, they are stored in the microcontroller unit, and an extremum mapping model is established:

[0055] in , , This is the real-time sampled power supply voltage value. This model is essentially a... Figure 3 The mathematical description of the linear relationship is shown, and adaptive adjustment under different voltages is achieved by introducing a quadratic polynomial of voltage.

[0056] (ii) Real-time calculation of maximum current value.

[0057] In actual operation, when step S2 detects the minimum current value And record the power supply voltage Then, immediately use the above model to calculate the maximum current value of this ripple cycle:

[0058] For example, suppose that at a certain moment a detection Synchronously recorded power supply voltage And the pre-stored coefficient is known. , , , , , Substituting into the formula, we get... , ,but This calculated value can be obtained without waiting for the actual peak to appear, greatly improving the real-time performance and anti-interference capability of the detection.

[0059] S4: Set dynamic judgment conditions based on the minimum and maximum current values, and make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic judgment conditions are met, determine that a valid ripple has been detected, and increment the valid ripple count once.

[0060] In a specific implementation, when obtaining the current ripple period... and the calculated Next, dynamic judgment conditions need to be set to confirm whether the current ripple is valid, in order to avoid false counting caused by harmonics or noise. The judgment condition is: the current filtered current value. Satisfying the inequality:

[0061] in This is a preset proportional threshold. The physical meaning of this condition is: a complete ripple cycle is considered to have been entered only when the current rises from the trough to a certain proportion of the peak-trough difference.

[0062] like Figure 4 As shown, considering the nonlinear characteristics of the current waveform during motor startup, this invention employs different proportional thresholds at different operating stages. In the initial stage of motor startup... Within one ripple cycle ( The value is predetermined through motor testing; for example, in this example, it is set to... ),Pick This means using a lower threshold to ensure that ripple during the startup phase can be identified in a timely manner. During normal motor operation, braking, and stall phases, a lower threshold is used. This means using a higher threshold to filter out possible harmonic glitches.

[0063] For example, during normal operation, if , The threshold for judgment is The filtered current value obtained from subsequent sampling When the value exceeds 0.745A for the first time, a valid ripple is detected, and the count is incremented.

[0064] Furthermore, this invention also includes an invalid valley removal mechanism. If an invalid valley is detected... Subsequently, if the slope does not change from a positive to a negative value and the above dynamic judgment condition is not met, it indicates that... This could be caused by noise, rather than a true trough. At this point, determine the current... If the current is an invalid trough, the current ripple count is discarded, and step S2 is repeated to detect the next minimum current value. This mechanism effectively prevents duplicate or erroneous counts caused by current waveform distortion.

[0065] S5: Repeat steps S1 to S4 until the DC brushed motor finishes running, and obtain the total number of ripples detected during the entire operation.

[0066] In a specific implementation, steps S1 to S4 are repeated, namely, continuous sampling, filtering, detecting troughs, calculating peaks, and determining valid ripple. The count is incremented each time a valid ripple is determined, until the DC brushed motor finishes running. The end of motor operation includes completing a specified stroke, receiving a stop command, or experiencing a stall.

[0067] Total ripple count during the entire operation It is obtained by accumulating the effective ripple counts at each stage. Specifically:

[0068] in This is the effective ripple count accumulated during the motor startup phase. This is the effective ripple count accumulated during normal operation. For the effective ripple count accumulated during the braking phase, This is the accumulated effective ripple count for the stall phase. By distinguishing between different phases, the motor's operating status can be analyzed more accurately.

[0069] For example, during an active grille shutter self-learning process, the motor moves from the fully closed position to the fully open position and stalls. Assume the gearbox transmission ratio... The motor generates 6 ripples per revolution. Then, the relationship between the grid rotation angle and the ripple number is:

[0070] If accumulated, it yields... Then the calculation yields If the angle does not match the preset expected stroke of the grille (e.g., 90°), a mechanical fault or a stall fault can be identified. For example, if the actual angle is greater than 110% of the expected stroke, a mechanical fault of the grille is considered; if it is less than 90% of the expected stroke, a stall fault is considered. Using the ripple detection method of this invention, the position accuracy of a single stroke can reach ±0.2°, and the ripple counting error rate is less than 1 / 1000, meeting the control requirements of an active grille shutter system for automobiles.

[0071] In summary, this method, through a series of techniques including digital filtering, slope zero-crossing detection, extreme value mapping model, dynamic threshold determination, and startup compensation, achieves high-precision and high-reliability DC motor ripple detection without the need for additional sensors and hardware pre-amplifier circuitry, providing a solid technical foundation for the closed-loop position control of the active air intake grille. Those skilled in the art should understand that the specific parameters mentioned above (such as sampling period, cutoff frequency, voltage range, number of load points, etc.) are merely examples of this invention, and can be adaptively adjusted according to specific motor characteristics and system requirements in practical applications, without departing from the scope of protection of this invention.

[0072] In this embodiment, by sampling the motor current and voltage in real time and performing digital low-pass filtering, the minimum current value of each ripple cycle is accurately captured using slope zero-crossing detection. Then, based on a pre-calibrated extreme value mapping model, the maximum current value of the current cycle is calculated in real time from the minimum value. Subsequently, a staged dynamic threshold is used to determine the effective ripple and accumulate the count. Without the need for Hall sensors, photoelectric encoders, and hardware filtering and comparison circuits, high-precision and high anti-interference counting of DC brushed motor ripple is achieved, which significantly reduces the system hardware cost, space occupation, and development complexity, while improving the detection reliability and position control accuracy in harsh vehicle environments.

[0073] In one embodiment of the present invention, based on the above method, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0074] Following step S5, the present invention also provides an optional implementation method, namely, calculating the actual rotation angle of the active air intake grille based on the accumulated total ripple count, and performing fault diagnosis accordingly. This implementation method will be described in detail below with specific examples.

[0075] S6: Location calculation and fault diagnosis steps.

[0076] After completing steps S1 to S5 above and obtaining the total ripple count detected throughout the entire operation... Then, this needs to be converted into the actual mechanical rotation angle of the active air intake grille. Since the DC brushed motor is connected to the grille blades via a gearbox, there is a fixed reduction ratio between the motor's rotation angle and the grille's rotation angle. Let the gearbox transmission ratio be... (i.e., the motor rotates) (The grid rotates 1 revolution), the number of ripples generated by the motor per revolution is... (In this embodiment, the motor has a 2-carbon-brush, 3-commutator structure.) The actual rotation angle of the grille. With total ripple count The following relationship must be satisfied:

[0077] in and These are all known constants, stored in the microcontroller unit. For example, in an active grille shutter system, the gearbox transmission ratio... This means the motor needs to rotate 180 times to make the grille rotate one full rotation (360°). Therefore, one rotation of the motor corresponds to one rotation of the grille. Since the motor generates 6 ripples per revolution, the corresponding grid rotation angle for each ripple is... The total ripple count obtained by summing them up... Then the calculation yields:

[0078] This means the grille actually rotated 180°. This calculation is automatically performed by the microcontroller unit after the motor finishes running, requiring no additional hardware.

[0079] During the grid self-learning process, it is necessary to compare the calculated actual rotation angle with the preset grid expected stroke. A comparison is made to determine if the grille system is functioning correctly. The preset expected travel... It is predetermined based on the mechanical design parameters of the grille; for example, the angle difference between the fully open and fully closed positions is typically 90° (e.g., Figure 5 and Figure 6 (As shown). The comparison rules are as follows: like If the actual rotation angle exceeds 110% of the expected stroke, it is considered a mechanical fault in the grille. This fault may be caused by the grille blades being stuck outside the normal range, loose mechanical connections, or a malfunctioning position sensor. For example, the expected stroke... If calculated ,but This triggers a mechanical fault alarm.

[0080] like If the actual rotation angle is less than 90% of the expected stroke, it is considered a grid stall fault. This fault is usually caused by the grid blades being stuck by foreign objects, frozen by ice or snow, or insufficient motor drive force. For example, the expected stroke... If calculated ,but This triggers a stall fault alarm.

[0081] like If the result is normal and self-learning is complete, the controller can use the total number of ripples corresponding to that stroke as the reference for subsequent position control.

[0082] In practical applications, the aforementioned comparison thresholds (110% and 90%) can be appropriately adjusted according to the accuracy requirements and safety margins of the specific system. For example, for systems with higher accuracy requirements, they can be set to 105% and 95%; for systems with larger allowable errors, they can be set to 120% and 80%. Using the ripple detection method of this invention, the position accuracy for a single stroke can reach ±0.2°, far exceeding the 10% error margin, thus enabling reliable fault diagnosis.

[0083] This fault diagnosis step can be integrated into the grille self-learning process. When the vehicle is powered on or receives a self-learning command, the controller drives the grille from the fully open position to the fully closed position (or vice versa) and records the total ripple count throughout the process. After the operation is completed, the controller automatically calculates the actual rotation angle and compares it with the expected stroke. If it is determined to be normal, the total ripple count corresponding to that stroke is stored for subsequent closed-loop position control; if a fault is determined, a fault code is reported via the vehicle bus, and corresponding protection strategies are executed (such as stopping the drive, attempting reverse operation, etc.). In this way, the present invention not only achieves accurate detection of the motor position but also endows the system with self-diagnostic capabilities, improving the intelligence and reliability of the active air intake grille controller.

[0084] Furthermore, as a refinement and extension of the specific implementation methods described above, and to fully illustrate the specific implementation process in this embodiment, in another specific implementation, the present invention, based on actual test data of an active grille shutter actuator for a certain model of automobile, details the complete process from parameter calibration to self-learning fault diagnosis. This implementation method employs the same hardware configuration and algorithm flow as the aforementioned implementation method, but is illustrated below through specific numerical examples.

[0085] (a) Basic parameters of motor and grille.

[0086] The DC brushed motor used in this embodiment has a 2-carbon-brush, 3-commutator structure. The motor generates 6 current ripples per revolution, with a maximum speed of 9000 RPM and a maximum ripple frequency of 900 Hz. The total travel (fully open to fully closed) of the active air intake grille is designed to be 90°, and the gearbox transmission ratio... This means the motor needs to rotate 180 revolutions to rotate the grille 360°. Therefore, each revolution of the motor corresponds to a 2° rotation of the grille, and each ripple corresponds to a 2° rotation of the grille. The grille self-learning process refers to the process where the driver moves the grille from the fully open position to the fully closed position and stalls, and the total stroke is determined by accumulating the ripple count.

[0087] (ii) Pre-calibration: Obtain six global coefficients.

[0088] Following the pre-calibration method described in steps S1 to S3, five load points (no load, 20%, 40%, 60%, and 80%) were applied at three voltage points: 9V, 12V, and 16V. An oscilloscope and current clamp were used to measure and record the data for each set. The measured data are shown in Table 1 below. Table 1: Test Data Comparison Table

[0089] Taking a 12V voltage point as an example, calculate the proportional gain at that voltage. and offset First, calculate the summation values:

[0090]

[0091]

[0092] Substitute into the least squares formula:

[0093]

[0094] Similarly, the fitting coefficients at 9V and 16V were calculated: 9V: ,

[0095] 16V: ,

[0096] Three voltage points and Substituting each value into a quadratic polynomial for fitting, we solve the matrix equation:

[0097] The global coefficients are calculated as follows:

[0098]

[0099] These coefficients are stored in the microcontroller unit to complete the pre-calibration.

[0100] (iii) Real-time ripple detection during the self-learning process.

[0101] During the grid self-learning process, the motor moves from the fully open position to the fully closed position. The microcontroller unit triggers the ADC sampling with 20kHz PWM to obtain the raw current. and power supply voltage After first-order low-pass filtering (cutoff frequency 1000Hz), the result is obtained. Suppose that in a certain sampling, the slope changes from negative to positive, and the current value after filtering is determined to be... Synchronously recorded power supply voltage Calculate using the calibrated global coefficients:

[0102]

[0103] The maximum current during this ripple cycle .

[0104] Because we are currently in the pre-start phase of the motor Within each ripple (assuming) ), using the start-up compensation threshold The judgment criteria are:

[0105] When the filtered current value obtained from subsequent sampling first exceeds 0.646A, a valid ripple is detected, and the count is incremented. After the startup phase, the system switches to the normal threshold. The judgment condition becomes .

[0106] (iv) Total Ripple Count Accumulation and Fault Diagnosis Repeat the above process until the motor reaches the fully off position and stalls. Assume that during the self-learning process, ripple accumulates during the startup phase. Accumulation during the running phase Accumulated during the congestion phase The total ripple count is:

[0107] Using the position calculation formula, the gearbox transmission ratio Ripple count per motor revolution The actual rotation angle of the grille is obtained as follows:

[0108] But the grille is expected to travel... Obviously Much larger Therefore, the controller determines that there is a mechanical fault in the grille (such as slippage of the transmission mechanism or abnormality of the position sensor), reports a fault code, and stops operation.

[0109] If the actual calculation results exist to Between (i.e.) If the self-learning is successful, the total number of ripples corresponding to that stroke will be used as the benchmark for subsequent position control. For example, if ,but The schedule was as planned, and the self-study was completed normally.

[0110] like Figure 7 As shown, the following is an embodiment of the DC motor ripple detection system for an active grille driver of an automobile provided in this disclosure. This system and the DC motor ripple detection method for an active grille driver of an automobile belong to the same inventive concept as the above embodiments. For details not described in detail in the embodiments of the DC motor ripple detection system for an active grille driver of an automobile, please refer to the embodiments of the DC motor ripple detection method for an active grille driver of an automobile.

[0111] A DC motor ripple detection system for an active grille shutter driver in an automotive system includes: The sampling and filtering module is used to sample the instantaneous current and power supply voltage of the DC brushed motor in real time, obtain the original current sampling value and power supply voltage value, and perform digital low-pass filtering on the original current sampling value to output the filtered current value. The minimum value detection module is used to calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value in each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected. The maximum value calculation module is used to calculate the maximum current value of the current in the current ripple cycle based on the detected minimum current value and the synchronously recorded power supply voltage value, according to the preset extreme value mapping model. The effective ripple determination and counting module is used to set dynamic determination conditions based on the minimum and maximum current values, and to make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic determination conditions are met, an effective ripple is detected, and the effective ripple count is incremented. The control module is used to repeatedly trigger the sampling and filtering module, the minimum value detection module, the maximum value calculation module, and the effective ripple determination and counting module to perform operations until the DC brushed motor finishes running, and to obtain the total number of ripples detected during the entire operation.

[0112] The automotive active grille driver DC motor ripple detection system provided in this embodiment acquires motor current and voltage in real time through a sampling and filtering module, eliminates high-frequency noise through filtering, accurately captures ripple troughs using a minimum value detection module with zero-crossing slope detection, calculates the peak of the current cycle in real time based on a pre-calibrated extreme value mapping model using the minimum value and voltage, and identifies effective ripples using a phased dynamic threshold. The control module cyclically triggers each module until the motor finishes running and accumulates the total ripple count. This system does not require Hall sensors, photoelectric encoders, or hardware filtering and comparison circuits; it only relies on the microcontroller's built-in ADC and resistors, significantly reducing hardware costs, PCB space, and system complexity. At the same time, it effectively suppresses harmonic interference through numerical calculation and dynamic threshold mechanisms, improving the position detection accuracy and reliability in harsh environments.

[0113] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting ripple in a DC motor of an active grille shutter driver for automobiles, characterized in that, Includes the following steps: S1: Real-time sampling of the instantaneous current and power supply voltage of the DC brushed motor to obtain the original current sampling value and power supply voltage value, and digital low-pass filtering processing of the original current sampling value to output the filtered current value. S2: Calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value of each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected. S3: Based on the preset extreme value mapping model, calculate the maximum current value of this ripple cycle according to the detected minimum current value and the synchronously recorded power supply voltage value. S4: Set dynamic judgment conditions based on the minimum and maximum current values, and make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic judgment conditions are met, determine that a valid ripple has been detected, and increment the valid ripple count once. S5: Repeat steps S1 to S4 until the DC brushed motor finishes running, and obtain the total number of ripples detected during the entire operation.

2. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 1, characterized in that, Step S1 includes: The original current sample value is obtained by performing sampling through the 12-bit analog-to-digital converter built into the microcontroller unit. and power supply voltage value Among them, the sampling period Triggered by a 20kHz PWM signal, the sampling frequency is more than 10 times the highest frequency of the DC brushed motor ripple. According to the preset cutoff frequency Through formula Calculate the time constant And according to the sampling period Through formula Calculate the filter coefficients ; The original current sample value is filtered using the following formula. Perform filtering: in, For the first The filtered output current value after the second sampling. This is the output current value from the previous filter.

3. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 2, characterized in that, Step S2 includes: Through formula The slope is calculated as the difference between the current values ​​after two consecutive filters. ; Real-time monitoring The sign change, when detected When the value changes from negative to positive, the filtered current value at the current moment is determined as the minimum detected current value. And simultaneously record the power supply voltage value at that moment. .

4. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 3, characterized in that, The process of setting the extreme value mapping model includes: Measure the minimum current of a DC brushed motor under different power supply voltages and load conditions. and maximum current And simultaneously record the power supply voltage value. ;Specifically: Multiple voltage points were selected within a voltage range of 9V to 16V. At each voltage point, multiple load points were selected from no-load to heavy-load. The experimental data for each set were measured and recorded. Each set of data included the power supply voltage value. Minimum current and maximum current ; At each fixed voltage point Next, the least squares method is used to analyze the... and Perform linear fitting and calculate the proportional gain at that voltage point using the following formula. and offset : in, This represents the number of load points at the current voltage level. All voltage points and their corresponding and Substituting each value into a quadratic polynomial fit, the six global coefficients are obtained by solving the following matrix equation. : in, The number of voltage points, For the first Voltage value at a fixed voltage point and These are the proportional coefficient and offset obtained by fitting at that voltage point, respectively; The six global coefficients The data is stored in the microcontroller unit, and the following extreme value mapping model is established: in, , , This is the power supply voltage value.

5. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 4, characterized in that, Step S3 includes: Based on the aforementioned extreme value mapping model, according to the detected minimum current value... and synchronously recorded power supply voltage Using the formula The maximum current value of this ripple cycle is calculated. .

6. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 5, characterized in that, The dynamic determination condition is: Current filtered current value Satisfying inequalities ,in The preset ratio threshold; Different proportional thresholds are selected based on the operating state of the DC brushed motor before the start-up phase of the DC brushed motor. Within each ripple cycle, take ; During the normal operation, braking, and stall phases of the DC brushed motor, take The The value represents the number of ripple cycles that need to be compensated during the startup phase.

7. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 6, characterized in that, Step S4 further includes: When the minimum current is detected Subsequently, if in subsequent sampling, the dynamic determination condition is not met until the slope changes from a positive value to a negative value, then the current condition is determined to be... If the current is invalid, discard this ripple count and re-detect the next minimum current value.

8. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 1, characterized in that, The total ripple count detected throughout the entire operation Through formula or calculate; in, The effective ripple count accumulated during the startup phase of the DC brushed motor, For the effective ripple count accumulated during the operation phase, For the effective ripple count accumulated during the braking phase, Effective ripple count accumulated during the stall phase .

9. The method for detecting DC motor ripple in an active grille shutter driver for automobiles according to claim 1, characterized in that, The method further includes: Based on the total ripple count obtained by accumulation The actual rotation angle of the active air intake grille can be calculated using the following formula. : in, The number of ripples generated per revolution of the DC brushed motor. This refers to the gearbox transmission ratio; The calculated actual rotation angle With preset grille expected travel If a comparison is made, If so, it is determined to be a mechanical failure of the grille; if If the condition is normal, it is determined to be a grid stall fault; otherwise, it is determined to be normal.

10. A DC motor ripple detection system for an active grille shutter driver in an automotive system, characterized in that, The system employs the DC motor ripple detection method for an active grille driver for automobiles as described in any one of claims 1 to 9; The system includes: The sampling and filtering module is used to sample the instantaneous current and power supply voltage of the DC brushed motor in real time, obtain the original current sampling value and power supply voltage value, and perform digital low-pass filtering on the original current sampling value to output the filtered current value. The minimum value detection module is used to calculate the slope based on the filtered current value at two adjacent sampling times, detect the minimum current value in each ripple cycle based on the sign change of the slope, and synchronously record the power supply voltage value when the minimum current value is detected. The maximum value calculation module is used to calculate the maximum current value of the current in the current ripple cycle based on the detected minimum current value and the synchronously recorded power supply voltage value, according to the preset extreme value mapping model. The effective ripple determination and counting module is used to set dynamic determination conditions based on the minimum and maximum current values, and to make real-time judgments on the filtered current values ​​at subsequent sampling times. When the dynamic determination conditions are met, an effective ripple is detected, and the effective ripple count is incremented. The control module is used to repeatedly trigger the sampling and filtering module, the minimum value detection module, the maximum value calculation module, and the effective ripple determination and counting module to perform operations until the DC brushed motor finishes running, and to obtain the total number of ripples detected during the entire operation.

Images