High-pressure oil pump stall fault diagnosis method and device, and electronic equipment

Abstract

The present disclosure provides a high-pressure oil pump stall fault diagnosis method and device and electronic equipment, and relates to the technical field of automobile suspension fault diagnosis. Through real-time collection of multi-dimensional operation parameters and filtering pretreatment, the stall fault is divided into multiple preset grades based on a multi-parameter fusion diagnosis model, the fault grade and parameters are uploaded to a vehicle domain controller and instructions are received, and then a hierarchical fault tolerance protection strategy and hierarchical reset operation are executed for different grades. Therefore, the problem that the existing technology is prone to misjudgment due to single stall diagnosis parameter, lacks cooperative interaction with the domain controller, and has no hierarchical fault tolerance protection logic, which may cause the suspension function to be interrupted, can be solved, and the technical effects of accurately identifying the stall grade, realizing hierarchical flexible protection and vehicle linkage control, and ensuring the continuous working ability of the shock absorber are achieved.

Description

Technical Field

[0001] This disclosure relates to the field of automotive suspension fault diagnosis technology, and in particular to a method and device for diagnosing high-pressure oil pump stall faults, as well as electronic equipment. Background Technology

[0002] As a core component of the automotive suspension system, the fully automatic shock absorber achieves continuously adjustable damping force control through a stable hydraulic oil source output by a high-pressure oil pump. It is widely used to improve overall vehicle ride comfort and handling limits. In related technologies, high-pressure oil pump stall fault diagnosis typically relies on a single motor current parameter, combined with local independent control logic for protection. Its technical system covers the entire process from parameter acquisition to power-off shutdown. However, with the evolution of automotive electronic and electrical architecture towards domain-controlled centralized systems and the widespread adoption of 400-1200V wide-voltage high-voltage platforms, existing technologies are insufficient to meet the demands of multi-parameter fusion diagnostics and vehicle-wide collaborative management.

[0003] However, existing high-pressure oil pump stall fault diagnosis methods directly rely on single-parameter threshold judgments without integrating multi-dimensional parameters such as pump speed, system oil pressure, and high-voltage for comprehensive diagnosis. This can lead to misjudgments and false protection under road bumps or instantaneous load impacts, or the lack of CAN communication with the chassis domain controller prevents real-time fault reporting and vehicle-level safety linkage, thus affecting the continuous operation capability of the fully automatic shock absorbers and driving safety. Furthermore, existing technologies lack tiered fault-tolerant protection and high-voltage safety mechanisms for 400-1200V high-voltage platforms, and lack fault self-recovery and data traceability functions, making it difficult to meet the system reliability and maintainability requirements of automotive functional safety design specifications. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and electronic equipment for diagnosing high-pressure oil pump stall faults. Its main purpose is to at least partially solve one of the technical problems in related technologies.

[0005] According to a first aspect of this disclosure, a method for diagnosing high-pressure oil pump stall faults is provided, comprising: The system collects multi-dimensional operating parameters of the high-pressure oil pump in real time, and performs filtering preprocessing on the collected raw parameters to obtain the preprocessed operating parameters. Based on the preprocessed operating parameters and combined with the preset multi-parameter fusion diagnostic model, the stall fault is determined to be one of several preset fault levels; The determined stall fault level and operating parameters are uploaded to the vehicle domain controller via the bus network, and fault control instructions issued by the vehicle domain controller are received. According to the fault control instructions, the corresponding graded fault-tolerant protection strategy is executed for different stall fault levels, and a graded reset operation is performed according to the parameter recovery status after the fault is cleared.

[0006] According to a second aspect of this disclosure, a high-pressure oil pump stall fault diagnosis device is provided, comprising: The acquisition unit is used to acquire multi-dimensional operating parameters of the high-pressure oil pump in real time, and to filter and preprocess the acquired raw parameters to obtain the preprocessed operating parameters. The determination unit is used to determine the stall fault as one of multiple preset fault levels based on the preprocessed operating parameters and the preset multi-parameter fusion diagnostic model. The receiving unit is used to upload the determined stall fault level and operating parameters to the vehicle domain controller via the bus network, and to receive fault control instructions issued by the vehicle domain controller. The execution unit is used to execute the corresponding graded fault-tolerant protection strategy for different stall fault levels according to the fault control instructions, and to perform graded reset operation according to the parameter recovery state after the fault is cleared.

[0007] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0008] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0009] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0010] The high-pressure oil pump stall fault diagnosis method, device, and electronic equipment disclosed herein acquire multi-dimensional operating parameters in real time and perform filtering preprocessing. Based on a multi-parameter fusion diagnostic model, the stall fault is divided into multiple preset levels. The fault level and parameters are uploaded to the vehicle domain controller and instructions are received. Then, a graded fault-tolerant protection strategy and graded reset operation are executed for different levels. Therefore, it can solve the problems in the prior art where stall fault diagnosis parameters are single and prone to misjudgment, lack of collaborative interaction with the domain controller, and rigid protection that easily leads to suspension function interruption due to the lack of graded fault-tolerant protection logic. It achieves the technical effects of accurately identifying the stall level, realizing graded flexible protection and vehicle linkage control, and ensuring the continuous working capability of the shock absorber.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0012] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A flowchart illustrating a high-pressure oil pump stall fault diagnosis method provided in this embodiment of the present disclosure; Figure 2 This is a schematic diagram of the structure of a high-pressure oil pump stall fault diagnosis device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0013] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0014] The embodiments disclosed herein, at every technical stage of the data lifecycle, including but not limited to data collection, transmission, storage, computation, use, disclosure, and destruction, are fundamentally based on strict adherence to and embedding of current laws, regulations, and regulatory requirements in their system architecture, protocols, and process controls. At the design level, the solution ensures, through systematic rules and strategies, that all processing activities automatically adhere to the principles of legality, legitimacy, necessity, and good faith, and technically implements core rules such as clear purpose, minimum necessity, transparency, and security.

[0015] For any data collection, processing, or other activities involved in the embodiments of this disclosure, corresponding verification, tracking, and constraint mechanisms are implemented at the system level to ensure that their execution has a clear legal basis or contractual foundation, and to automatically trigger and record the corresponding notification process. The processing purpose of related data is bound to its specific use at the metadata layer, and is strictly limited through the system's embedded flow strategy and access control model, thereby ensuring that data is accessed and used only within the scope necessary to achieve the initial collection purpose and as determined by technical criteria. The system has a multi-layered authorization management and compliance audit mechanism to ensure that related data will not be used for any other purpose without separate legal permission or valid separate consent from the information subject. This solution natively supports and protects the information subject's various legal rights to their data in its technical implementation, and provides standardized interfaces and automated processes to achieve efficient exercise of these rights.

[0016] The following describes, with reference to the accompanying drawings, a method and apparatus for diagnosing high-pressure oil pump stall faults, and electronic equipment according to embodiments of the present disclosure.

[0017] Figure 1 This is a flowchart illustrating a high-pressure oil pump stall fault diagnosis method provided in an embodiment of this disclosure.

[0018] like Figure 1 As shown, the method includes the following steps: Step 101: Collect multi-dimensional operating parameters of the high-pressure oil pump in real time, and perform filtering preprocessing on the collected raw parameters to obtain preprocessed operating parameters.

[0019] In the embodiments of this disclosure, the oil pump controller, based on its internally integrated current acquisition module, speed detection module, oil pressure acquisition module, and high-voltage monitoring module, synchronously and in real-time captures the real-time operating current of the three-phase motor of the high-pressure oil pump, the current speed of the oil pump rotor, the real-time pressure in the hydraulic system's oil supply pipeline, the 400-1200V high-voltage bus voltage, and the real-time temperature of the controller housing at a preset high-frequency sampling period, thereby constituting multi-dimensional operating parameters. For the raw electrical signals acquired above, the oil pump controller uses a moving average filtering algorithm to recursively smooth the continuous sampled values ​​to suppress periodic noise interference. At the same time, it performs extreme value elimination processing to filter out transient spike pulses exceeding a reasonable threshold, ultimately generating preprocessed operating parameters that can truly characterize the steady-state and transient operating states of the oil pump, providing an accurate data basis for subsequent fault diagnosis.

[0020] Step 102: Based on the preprocessed operating parameters and combined with the preset multi-parameter fusion diagnostic model, the stall fault is determined to be one of multiple preset fault levels.

[0021] In the embodiments of this disclosure, the oil pump controller embeds or invokes a pre-calibrated and stored multi-parameter fusion diagnostic model. This model uses the preprocessed operating parameters as input vectors and compares the current real-time current value, speed drop rate, oil pressure change gradient, and duration of the aforementioned abnormal states with the preset multi-level threshold conditions in the model. Based on the comprehensive matching results of current multiple, speed drop amplitude, oil pressure change characteristics, and fault duration, the diagnostic model automatically categorizes the stall fault into a unique level among multiple preset fault levels. For example, when a slight increase in current is detected while the speed and oil pressure are not significantly abnormal and the duration is extremely short, it is determined to be instantaneous stall; when the current increases significantly, the speed drops sharply below the rated speed, and the oil pressure rises abnormally and continues for a long period of time, it is determined to be mild stall; when the current reaches its peak, the speed drops to zero, the oil pressure exceeds the limit, or the voltage fluctuates violently and continues for a long time, it is determined to be severe stall. Thus, the multi-parameter fusion judgment result combining qualitative and quantitative methods is transformed into a clear single fault level output.

[0022] Step 103: Upload the determined stall fault level and operating parameters to the vehicle domain controller via the bus network, and receive the fault control instructions issued by the vehicle domain controller.

[0023] In the embodiments of this disclosure, the oil pump controller packages the stall fault level determined in step 102, the preprocessed operating parameters (or key feature parameters extracted from them) generated in step 101, the fault duration, and the fault timestamp with a unified time base, according to a preset data frame format, and uploads them to the vehicle domain controller via the vehicle bus network (e.g., CAN bus or FlexRay bus). After receiving and completing the logical verification and legality confirmation of the fault data, the vehicle domain controller generates corresponding fault control instructions based on the vehicle functional safety policy and the current vehicle operating status, and sends them back to the oil pump controller via the same bus network. Simultaneously, the vehicle domain controller can drive the vehicle instrument system to issue audible and visual fault alarm signals and synchronize the fault information to the vehicle controller, achieving vehicle-level safety linkage response.

[0024] Step 104: According to the fault control instructions, execute the corresponding graded fault-tolerant protection strategy for different stall fault levels, and perform graded reset operation according to the parameter recovery status after the fault is cleared.

[0025] In the embodiments of this disclosure, after receiving a fault control command from the vehicle domain controller, the oil pump controller parses the fault level label and corresponding protection action parameters contained in the command, and calls the pre-configured hierarchical fault-tolerant protection strategy library. For instantaneous stall level, it executes protection actions to reduce the instantaneous output power of the motor and limit the peak current, while maintaining continuous operation of the oil pump and unobstructed hydraulic circuit to avoid false protection leading to shock absorber malfunction. For mild stall level, it executes actions to limit the motor output current and reduce the target speed to a preset proportion (e.g., 20%) of the rated speed, while using an intermittent start-stop trial operation mode to attempt to resolve minor mechanical jamming. For severe stall level, it executes an operation to cut off the high-voltage power supply circuit with a delay (e.g., not less than 300ms), switches to low-voltage auxiliary standby mode, closes the hydraulic oil supply solenoid valve, and activates high-voltage insulation monitoring protection. During the execution of the hierarchical fault-tolerant protection strategy, the oil pump controller continuously monitors core parameters such as motor current, oil pump speed, and system oil pressure. When the above parameters are detected to have returned to the normal range and the fault interference factors have been eliminated, a graded reset operation is performed according to the reset logic corresponding to different fault levels: For momentary stall, the protection mode is automatically exited immediately after the load interference disappears; for mild stall, the current limiting and speed reduction protection is automatically released and the rated operation is gradually restored after the parameters remain stable for a preset time (e.g., 3 seconds) without rebound; for severe stall, the latching state can only be released and the reset is completed after the fault hazard is completely eliminated, the parameters return to normal, and a dedicated reset command is received from the vehicle domain controller or the vehicle is powered off and restarted.

[0026] The high-pressure oil pump stall fault diagnosis method disclosed herein collects multi-dimensional operating parameters in real time and performs filtering preprocessing. Based on a multi-parameter fusion diagnostic model, the stall fault is divided into multiple preset levels. The fault level and parameters are uploaded to the vehicle domain controller and instructions are received. Then, a graded fault-tolerant protection strategy and graded reset operation are executed for different levels. Therefore, it can solve the problems in the prior art where stall fault diagnosis parameters are single and easy to misjudge, lack of collaborative interaction with the domain controller, and rigid protection due to the lack of graded fault-tolerant protection logic, which can easily cause suspension function interruption. It achieves the technical effects of accurately identifying the stall level, realizing graded flexible protection and vehicle linkage control, and ensuring the continuous working capability of the shock absorber.

[0027] In the embodiments involved in this application, there are various feasible specific implementation methods. To clearly and completely illustrate the technical solutions of this disclosure, the implementation methods listed below are merely exemplary and do not constitute a limitation on the scope of protection of this disclosure. That is, in addition to the implementation methods described below, other implementation methods that can be obtained by those skilled in the art based on the technical content disclosed in this disclosure through reasonable logical analysis, reasoning, or limited experimentation should also be covered within the scope of protection of this disclosure. The following specifically describes some exemplary implementation methods: As a specific implementation of this disclosure, based on the basic scheme, multi-dimensional operating parameters of the high-pressure oil pump are collected in real time, and the collected raw parameters are filtered and preprocessed to obtain preprocessed operating parameters. The parameters are further defined as follows: the motor operating current, real-time speed of the oil pump, hydraulic system oil supply pressure, high-pressure bus voltage and controller temperature of the high-pressure oil pump are collected synchronously and in real time at a preset collection frequency. The collected raw electrical signals are subjected to moving average filtering and extreme value removal processing to obtain preprocessed operating parameters.

[0028] Specifically, the oil pump controller configures its internal parameter acquisition frequency to be no less than 100Hz. At this frequency, it synchronously captures the instantaneous operating current of the three-phase motor, the speed pulse output by the Hall sensor, the analog signal from the oil pressure sensor, the voltage divider sampling value of the high-voltage bus, and the resistance value of the thermistor mounted on the controller housing. For the continuously acquired raw electrical signal sequence, the oil pump controller first performs a moving average filter: setting the sliding window length to N (e.g., N=5), for each new data acquisition, the oldest data in the window is discarded, and the arithmetic mean of the remaining data in the window is calculated as the filtered output for the current moment, thereby suppressing periodic random noise. Subsequently, extreme value removal processing is performed on the filtered data: transient abnormal peaks that exceed a preset reasonable range (e.g., current exceeding the rated value by more than 3 times, speed exceeding the rated value by more than 120%) are discarded, and the normal values ​​of the previous moment are used for maintenance or linear interpolation replacement, finally obtaining smooth, continuous preprocessed operating parameters that reflect the real physical process. In some specific embodiments, to ensure diagnostic accuracy and system response speed, the current acquisition accuracy is controlled within ±0.1A, the speed acquisition accuracy within ±5rpm, and the CAN bus communication response time between the oil pump controller and the chassis domain controller is ensured to be no more than 5ms. For example, when the rated current of the high-pressure oil pump is 10A, the acquired current value must accurately reflect the subtle fluctuations of 10A ±0.1A; when the rated speed is 3000rpm, the acquired speed value must be accurate to between 2995rpm and 3005rpm. Through the above-mentioned high-precision, high-frequency filtering preprocessing, a reliable data foundation is provided for the subsequent classification and determination of stall faults. In other implementations, median filtering or first-order low-pass filtering can be used instead of moving average filtering, and the sliding window length can be dynamically adjusted according to the actual operating conditions.

[0029] As a specific implementation of this disclosure, based on the basic scheme and preprocessed operating parameters, combined with a preset multi-parameter fusion diagnostic model, the stall fault is determined as one of several preset fault levels, further defined as follows: when the motor operating current reaches the first current threshold, the oil pump speed does not drop significantly, the system oil pressure does not change abruptly, and the fault duration is less than the first duration threshold, it is determined as an instantaneous stall fault; when the motor operating current reaches the second current threshold, the oil pump speed drops below the first proportional threshold of the rated speed, the system oil pressure rises abnormally, and the fault duration is within the second duration range compared to the first duration threshold, it is determined as a mild stall fault; when the motor operating current reaches the third current threshold or above, the oil pump speed drops to zero, the system oil pressure exceeds the limit or the high voltage fluctuates drastically, and the fault duration is greater than or equal to the third duration threshold, it is determined as a severe stall fault.

[0030] Specifically, the oil pump controller has pre-stored the rated operating current value (e.g., 10A) and rated speed value (e.g., 3000rpm) of the high-pressure oil pump. A multi-parameter fusion diagnostic model acquires the pre-processed current value I, speed value n, oil pressure value P, and their rate of change in real time. The model first determines the fault duration t: if I ≥ 1.5 × I_rated (first current threshold), and the speed n does not drop below 0.9 × n_rated (considered no significant drop), the oil pressure P does not have a sudden change exceeding 20% ​​relative to the normal fluctuation range, and t < 100ms (first duration threshold), then the output judgment result is "instantaneous stall fault". If I ≥ 2 × I_rated (second current threshold), and the speed n drops below 0.3 × n_rated (i.e., the first proportional threshold is 30%), the oil pressure P shows an abnormal increase (e.g., exceeding the normal upper limit by 15%), and t is between 100ms and 500ms (second duration range), then the output is "mild stall fault". If I ≥ 2.5 × I_rated (third current threshold), and the rotational speed n drops to 0 r / min, the oil pressure P exceeds the system's maximum allowable pressure, or the high-voltage bus voltage U experiences a severe fluctuation exceeding ±10% of the rated voltage, and t ≥ 500 ms (third duration threshold), then a "severe stall fault" is output. In some specific embodiments, taking an oil pump with a rated current of 10A and a rated speed of 3000 rpm as an example: when the detected current is 15A, the rotational speed is 2850 rpm, the oil pressure is stable, and the duration is 85 ms, it is determined to be an instantaneous stall; when the current is 20A, the rotational speed is 850 rpm (below 900 rpm), the oil pressure abnormally increases, and the duration is 300 ms, it is determined to be a mild stall; when the current is 25A or higher, the rotational speed is 0 rpm, the oil pressure exceeds the limit, or the voltage fluctuates drastically, and the duration is 500 ms, it is determined to be a severe stall. It should be noted that the above thresholds can be adaptively adjusted according to different oil pump models and vehicle calibration results. For example, the first current threshold can be 1.4 to 1.6 times, and the second duration range can be 80ms to 600ms.

[0031] As a specific implementation of this disclosure, based on the basic scheme and the pre-processed operating parameters, combined with the preset multi-parameter fusion diagnostic model, the stall fault is determined to be one of multiple preset fault levels. It can also be limited to: when an abnormal signal is detected in the sensor used to collect operating parameters, it is directly determined to be a severe stall fault.

[0032] Specifically, the oil pump controller continuously performs self-diagnostic monitoring on the output signals of the current sensor and speed sensor. When it detects that the current sensor output signal continuously exceeds its upper limit or remains zero (i.e., short circuit or open circuit), or the speed sensor outputs a fixed high level or a fixed low level (i.e., unable to generate a valid pulse), the oil pump controller determines that the sensor signal is abnormal. Once this abnormality is confirmed, regardless of the actual values ​​of parameters such as current and speed, the multi-parameter fusion diagnostic model directly bypasses the conventional three-level judgment logic and forcibly outputs a judgment result of "severe stall fault". In some specific embodiments, for example, when the current sensor's collected value is always 0A due to an internal open circuit, but the actual motor has stalled and is generating a large current, relying solely on the current value would misjudge as no fault; through this implementation, the controller immediately determines severe stall after detecting the sensor open circuit abnormality, thereby triggering subsequent delayed power-off and high-voltage safety protection, avoiding the safety risk of missed protection due to sensor failure. Similarly, if the speed sensor signal line is short-circuited to the power supply, and the output is always a 5V high level, the oil pump controller also identifies it as a signal abnormality and directly determines severe stall. In other equivalent alternatives, sensor malfunctions can also be determined by comparing whether the outputs of dual redundant sensors for the same physical quantity are significantly inconsistent.

[0033] As a specific implementation of this disclosure, based on the basic scheme, the determined stall fault level and operating parameters are uploaded to the vehicle domain controller via the bus network, and fault control instructions issued by the vehicle domain controller are received. It is further defined as follows: the determined stall fault level, real-time operating parameters, fault duration and fault timestamp are submitted to the vehicle domain controller via the bus network; after the vehicle domain controller completes the fault data logic verification, it issues a fault control execution instruction to the oil pump controller, and at the same time drives the vehicle instrument to perform audible and visual fault alarms and synchronizes the fault information to the vehicle controller.

[0034] Specifically, the oil pump controller packages the stall fault level (e.g., 01 for instantaneous, 10 for mild, and 11 for severe), the pre-processed real-time operating parameters (current, speed, oil pressure, voltage, and temperature), the duration from the fault's onset to the current moment (in milliseconds), and the fault timestamp generated based on the system clock (e.g., absolute time after power-on or UTC time after global time synchronization) according to the CAN2.0B extended frame data field format, and sends it to the chassis domain controller via the CAN bus. Upon receiving this frame, the chassis domain controller first performs a logical check: verifying the data frame format for completeness, the fault level code for legality, and the duration for consistency with parameter change trends (e.g., the duration of severe stall is not less than 500ms). After successful verification, the chassis domain controller generates the corresponding fault control execution command based on the vehicle's current state (e.g., vehicle speed, braking signal, and suspension mode), and sends it back to the oil pump controller via the CAN bus. Simultaneously, the chassis domain controller sends audible and visual alarm signals to the instrument cluster controller via an internal network (such as CAN or Ethernet), driving the instrument cluster to display a stall fault icon and emit a warning sound. Furthermore, the chassis domain controller synchronizes the fault level and key parameters to the vehicle controller for vehicle energy management or driving mode adjustment. In some specific embodiments, when a mild stall fault occurs, the chassis domain controller can determine the cause based on the vehicle speed signal: if the vehicle speed is higher than 30 km / h, it issues a command to "maintain the current current limiting protection but do not cut off the hydraulic pressure temporarily"; if the vehicle speed is lower than 5 km / h and the vehicle is parked, it issues a command to "allow more aggressive intermittent trial operation". Through this two-way interaction and vehicle-wide linkage, collaborative and intelligent fault handling is achieved.

[0035] As a specific implementation of this disclosure, based on the basic scheme, according to the fault control instructions, a corresponding graded fault-tolerant protection strategy is executed for different stall fault levels, further defined as follows: when the stall fault level is instantaneous stall, the instantaneous output power of the motor is reduced and the peak current is limited to keep the oil pump running continuously; when the stall fault level is mild stall, the motor output current is limited and the oil pump speed is reduced to the second proportional threshold of the rated speed, and an intermittent start-stop trial operation mode is used to try to release the mechanical jamming; when the stall fault level is severe stall, the high-voltage power supply circuit is delayed and switched to low-voltage auxiliary standby mode, the hydraulic oil supply solenoid valve is closed and the high-voltage insulation monitoring protection is activated.

[0036] Specifically, the oil pump controller stores a table of protection action parameters corresponding to three fault levels. For momentary stall, the controller immediately reduces the motor output power to 50%–70% of the current required power using pulse width modulation (PWM) control, clamps the peak current to within 1.8 times the rated current, and keeps the power transistor continuously conducting and the hydraulic oil supply solenoid valve open, allowing the oil pump to continue rotating but with reduced output to avoid momentary impact loads. For mild stall, the controller limits the motor output current to within 1.5 times the rated current and sets the target speed command to 20% of the rated speed (second proportional threshold), while performing intermittent start-stop trial operation: for example, repeating the cycle of "run for 0.5 seconds - stop for 0.5 seconds" 3–5 times, using the impact torque at each start to attempt to break the stall; during this process, the current and speed are continuously monitored, and if the current drops and the speed rises, the trial is terminated and normal control is restored. For severe stall, the controller activates a delay counter. After a delay of no less than 300ms (e.g., a precise delay of 300ms or dynamically adjusted to 320ms based on the high-voltage bus voltage discharge time), it disconnects the high-voltage contactor or relay to break the 400-1200V high-voltage power supply circuit. Simultaneously, it switches to a 12V / 24V low-voltage auxiliary standby mode to maintain power supply to the controller's internal logic. Subsequently, it closes the hydraulic oil supply solenoid valve to prevent high-pressure oil impact and activates the high-voltage insulation monitoring circuit to detect the insulation resistance of the high-voltage circuit to ground. In some specific embodiments, for oil pumps adapted to 800V high-voltage platforms, when severe stall occurs, the high voltage is cut off after a 300ms delay. When the insulation monitoring module detects an insulation resistance below 500Ω / V, a serious leakage fault is reported. This graded protection strategy avoids system shutdown due to minor faults while ensuring high-voltage safety under severe faults.

[0037] As a specific implementation of this disclosure, based on the basic scheme, after the fault is cleared, a graded reset operation is performed according to the parameter recovery status, which is further defined as follows: when the load interference of the instantaneous stall fault disappears and the parameters return to normal, the protection mode is immediately and automatically exited; when the various operating parameters of the mild stall fault return to the normal range and remain stable for a preset time without rebound, the current limiting and speed reduction protection is automatically released and the rated operating condition is gradually restored; when the fault hazard of the severe stall fault is eliminated and the parameters are completely normal, the fault status is latched and can only be reset after receiving a dedicated reset command from the vehicle domain controller or after the vehicle is powered off and restarted.

[0038] Specifically, during fault protection mode, the oil pump controller continuously monitors the motor current, oil pump speed, and system oil pressure at a frequency of no less than 10Hz. For momentary stall, when the current drops below 1.2 times the rated current, the speed recovers to above 90% of the rated speed, and the oil pressure is normal for three consecutive sampling cycles (e.g., 30ms), the controller immediately clears the protection flag, restores the PWM duty cycle to the normal control loop calculation value, and allows the oil pump to seamlessly exit the protection mode. For mild stall, during intermittent testing or current limiting and speed reduction, once the current stabilizes below 1.2 times the rated current, the speed recovers to above 50% of the rated speed, and the above parameters do not rebound within 3 consecutive seconds (preset duration) (i.e., the fluctuation between the maximum and minimum values ​​does not exceed ±5%), the current limit and speed limit are automatically released, and the pump gradually recovers to the target speed at a slope of 10% of the rated speed per second. For severe stall, after the controller cuts off the high voltage and enters a latched state, it will not automatically reset even if the current, speed, and other parameters are subsequently restored to normal by manually clearing the oil circuit. The controller must be cleared of the latched fault state by the vehicle domain controller sending a dedicated reset command via the CAN bus (e.g., a diagnostic message containing a specific ID and data field), or the operator must power off the vehicle (key off) and wait for the high-voltage capacitor to discharge before powering it back on. In some specific embodiments, the preset duration is 3 seconds. The reset conditions for mild stall are: current ≤ 12A, speed ≥ 1500 rpm, oil pressure fluctuation less than ±0.2 MPa for 3 seconds without recurrence. This tiered reset mechanism avoids the risk of secondary damage caused by automatic resetting of severe faults, while ensuring the system's rapid self-recovery capability under minor faults.

[0039] As a specific implementation of this disclosure, in addition to the basic solution, it also includes: writing the fault level, original operating parameters, protection action process and reset status of the stall fault into a non-volatile memory for permanent storage, generating a unique fault code, and supporting the vehicle domain controller to retrieve fault log data at any time to achieve fault source tracing and analysis.

[0040] Specifically, the oil pump controller integrates non-volatile memory (such as EEPROM or embedded Flash). After a stall fault is determined (including after protection actions are executed or a reset operation is completed), the controller automatically writes the following information about the fault into this memory in the form of a structured data frame: the absolute timestamp of the fault occurrence, the fault level code, the fault duration, the original operating parameters (including current, speed, oil pressure, voltage, and temperature) for the 10 sampling cycles prior to the fault occurrence, the action type recorded during the protection action (such as power reduction, current limiting, high voltage cutoff, etc.) and the action execution time, and the reset method (automatic reset / command reset / power-down reset) and reset time. Simultaneously, the controller generates a globally unique fault code (DTC) based on the fault type and occurrence time using a preset algorithm (such as CRC checksum combined with sequential accumulation). This fault code can be read by external diagnostic tools via the UDS protocol. The chassis domain controller or external diagnostic instrument can send a request to the oil pump controller to retrieve the fault log at any time via the CAN bus. Upon response, the oil pump controller outputs the stored fault records one by one for after-sales maintenance personnel to perform source tracing and analysis. In some specific embodiments, the non-volatile memory can cyclically store complete records of the most recent 30 stall faults. Each record is fixed at 64 bytes, including the fault level (1 byte), duration (2 bytes), timestamp (4 bytes), key parameter array (20 bytes), protection action flag (2 bytes), reset status (1 byte), and fault code (4 bytes), with the remaining bytes reserved. This storage and tracing function allows for precise location of the stall condition and cause. In other implementations, fault logs can also be uploaded to a cloud server for remote analysis via a wireless communication module.

[0041] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0042] Corresponding to the above-described high-pressure oil pump stall fault diagnosis method, this disclosure also proposes a high-pressure oil pump stall fault diagnosis device. Since the device embodiments of this disclosure correspond to the above-described method embodiments, details not disclosed in the device embodiments can be referred to the above-described method embodiments, and will not be repeated here.

[0043] Figure 2 This is a schematic diagram of a high-pressure oil pump stall fault diagnosis device provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes: The acquisition unit 21 is used to acquire multi-dimensional operating parameters of the high-pressure oil pump in real time, and to filter and preprocess the acquired raw parameters to obtain the preprocessed operating parameters. The determination unit 22 is used to determine the stall fault as one of multiple preset fault levels based on the preprocessed operating parameters and the preset multi-parameter fusion diagnostic model. The receiving unit 23 is used to upload the determined stall fault level and operating parameters to the vehicle domain controller through the bus network, and to receive fault control instructions issued by the vehicle domain controller. The execution unit 24 is used to execute the corresponding graded fault-tolerant protection strategy for different stall fault levels according to the fault control instructions, and to perform graded reset operation according to the parameter recovery state after the fault is cleared.

[0044] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0045] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0046] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0047] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0048] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0049] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the high-pressure oil pump stall fault diagnosis method. For example, in some embodiments, the high-pressure oil pump stall fault diagnosis method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned high-pressure oil pump stall fault diagnosis method by any other suitable means (e.g., by means of firmware).

[0050] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0051] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0052] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0053] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0054] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0055] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0056] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0057] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0058] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0059] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0060] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for diagnosing stall faults in a high-pressure oil pump, characterized in that, include: The system collects multi-dimensional operating parameters of the high-pressure oil pump in real time, and performs filtering preprocessing on the collected raw parameters to obtain the preprocessed operating parameters. Based on the preprocessed operating parameters and combined with the preset multi-parameter fusion diagnostic model, the stall fault is determined to be one of multiple preset fault levels; The determined stall fault level and the operating parameters are uploaded to the vehicle domain controller via the bus network, and fault control instructions issued by the vehicle domain controller are received. According to the fault control instructions, corresponding graded fault-tolerant protection strategies are executed for different stall fault levels, and graded reset operations are performed according to the parameter recovery status after the fault is cleared.

2. The method according to claim 1, characterized in that, The system acquires multi-dimensional operating parameters of the high-pressure oil pump in real time, and performs filtering preprocessing on the acquired raw parameters to obtain preprocessed operating parameters, including: The motor operating current, real-time speed of the high-pressure oil pump, oil supply pressure of the hydraulic system, voltage of the high-pressure bus, and temperature of the controller are synchronously and in real time at a preset acquisition frequency. The acquired raw electrical signals are then subjected to moving average filtering and extreme value removal to obtain preprocessed operating parameters.

3. The method according to claim 1, characterized in that, Based on the preprocessed operating parameters and combined with a preset multi-parameter fusion diagnostic model, the stall fault is determined to be one of several preset fault levels, including: When the motor operating current reaches the first current threshold, the oil pump speed does not drop significantly, the system oil pressure does not change abruptly, and the fault duration is less than the first duration threshold, it is determined to be an instantaneous stall fault. When the motor operating current reaches the second current threshold, the oil pump speed drops below the first proportional threshold of the rated speed, the system oil pressure rises abnormally, and the duration of the fault is within the second duration range compared to the first duration threshold, it is determined to be a mild stall fault. When the motor operating current reaches the third current threshold or above, the oil pump speed drops to zero, the system oil pressure exceeds the limit, or the high voltage fluctuates violently and the fault duration is greater than or equal to the third duration threshold, it is judged as a severe stall fault.

4. The method according to claim 3, characterized in that, The step of classifying stalled rotor faults into one of multiple preset fault levels based on the preprocessed operating parameters and a preset multi-parameter fusion diagnostic model also includes: When an abnormal signal is detected in the sensor used to collect the operating parameters, it is directly determined to be a severe stall fault.

5. The method according to claim 1, characterized in that, The process of uploading the determined stall fault level and the operating parameters to the vehicle domain controller via the bus network, and receiving fault control instructions issued by the vehicle domain controller, includes: The determined stall fault level, real-time operating parameters, fault duration, and fault timestamp are submitted to the vehicle domain controller via the bus network. After the vehicle domain controller completes the fault data logic verification, it sends a fault control execution command to the oil pump controller, and at the same time drives the vehicle instrument to perform audible and visual fault alarms and synchronizes the fault information to the vehicle controller.

6. The method according to claim 1, characterized in that, The step of executing corresponding graded fault-tolerant protection strategies for different stall fault levels according to the fault control instructions includes: When the stall fault level is instantaneous stall, reduce the instantaneous output power of the motor and limit the peak current to keep the oil pump running continuously; When the stall fault level is mild stall, limit the motor output current and reduce the oil pump speed to the second proportional threshold of the rated speed, and try to release the mechanical jam by using an intermittent start-stop trial operation mode; When the stall fault level is severe stall, the high-voltage power supply circuit is delayed and switched to low-voltage auxiliary standby mode, the hydraulic oil supply solenoid valve is closed and the high-voltage insulation monitoring and protection is activated.

7. The method according to claim 1, characterized in that, The step of performing a graded reset operation based on the parameter recovery status after the fault is cleared includes: When the load disturbance of the momentary stall fault disappears and the parameters return to normal, the protection mode will be automatically exited immediately. When all operating parameters of a mild stall fault return to the normal range and remain stable for a preset time without rebound, the current limiting and speed reduction protection will be automatically released and the rated operating condition will be gradually restored. Once the potential hazards of severe stall faults are eliminated and the parameters are completely normal, the fault state is latched and can only be reset after receiving a dedicated reset command from the vehicle domain controller or after the vehicle is powered off and restarted.

8. The method according to claim 1, characterized in that, Also includes: The fault level, original operating parameters, protection action process, and reset status of the stall fault are written into a non-volatile memory for permanent storage, generating a unique fault code. The vehicle domain controller can retrieve the fault log data at any time to achieve fault source tracing and analysis.

9. A high-pressure oil pump stall fault diagnosis device, characterized in that, include: The acquisition unit is used to acquire multi-dimensional operating parameters of the high-pressure oil pump in real time, and to filter and preprocess the acquired raw parameters to obtain the preprocessed operating parameters. The determination unit is used to determine the stall fault as one of multiple preset fault levels based on the preprocessed operating parameters and a preset multi-parameter fusion diagnostic model. The receiving unit is used to upload the determined stall fault level and the operating parameters to the vehicle domain controller via the bus network, and to receive the fault control instructions issued by the vehicle domain controller. The execution unit is used to execute the corresponding graded fault-tolerant protection strategy for different stall fault levels according to the fault control instructions, and to perform graded reset operation according to the parameter recovery state after the fault is cleared.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

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