Fault detection method and device, vehicle and computer readable storage medium

Abstract

The invention provides a fault detection method and device, a vehicle and a computer readable storage medium, and relates to the technical field of high-voltage interlocking, and the method comprises the steps: obtaining a fault detection signal of a high-voltage interlocking loop; fault analysis is carried out on the fault detection signals through a preset multi-dimensional diagnosis strategy, and the multi-dimensional diagnosis strategy comprises a delay diagnosis strategy for carrying out grading judgment on the duration time of the fault detection signals and an environment self-adaption strategy for dynamically adjusting diagnosis parameters based on the vehicle environment state; the waveform analysis strategy is used for identifying waveform characteristics of the fault detection signals; and according to a comprehensive analysis result of the multi-dimensional diagnosis strategy, determining that the fault type of the fault detection signal is a real fault or instantaneous interference. According to the method, multiple dimension information such as time, environment and signal characteristics is fused, collaborative analysis and cross validation can be carried out on fault types of the loop, and detection modes are rich. And real faults or instantaneous interference can be effectively distinguished, and the detection accuracy is high.

Description

Technical Field

[0001] This application relates to the field of high-voltage interlocking technology, and more specifically, to a fault detection method, apparatus, vehicle, and computer-readable storage medium. Background Technology

[0002] With the development of new energy vehicles, electrification is gradually becoming a trend. Electric vehicles are typically equipped with high-voltage electrical systems to supply power to high-power electrical equipment (such as motors). To monitor the operating status of these high-voltage electrical systems in real time, vehicles are usually equipped with a High Voltage Interlock Loop (HVIL) system. This system contains multiple high-voltage connectors and corresponding low-voltage detection connectors. Each high-voltage connector typically has an interlock contact, and these contacts are connected by wires to form a complete high-voltage interlock circuit. The high-voltage interlock system can promptly cut off the high-voltage power supply in case of an abnormality in the high-voltage electrical system, thereby preventing electric shock accidents and fire risks.

[0003] Currently, high-voltage interlock systems are typically equipped with detection systems to detect faults in the high-voltage interlock detection system. For example, related technologies often use a fixed-delay confirmation method for fault detection. However, this detection method is relatively simple and cannot accurately distinguish the fault types of the high-voltage interlock detection system, resulting in low accuracy of fault detection results. Summary of the Invention

[0004] This application provides a fault detection method, device, vehicle, and computer-readable storage medium, aiming to solve the problems in related technologies where the fault detection method for high-voltage interlock detection systems is relatively simple, unable to accurately distinguish the fault types of high-voltage interlock detection systems, and the accuracy of fault detection results is low.

[0005] Firstly, a fault detection method is provided, applied to a high-voltage interlock circuit with multiple low-voltage detection connectors. The method includes: acquiring a fault detection signal of the high-voltage interlock circuit; performing fault analysis on the fault detection signal using a preset multi-dimensional diagnostic strategy, the multi-dimensional diagnostic strategy including a delay diagnostic strategy that grades the duration of the fault detection signal, an environment adaptive strategy that dynamically adjusts diagnostic parameters based on the vehicle's environmental state, and a waveform analysis strategy that identifies the waveform characteristics of the fault detection signal; and determining whether the fault type of the fault detection signal is a real fault or transient interference based on the comprehensive analysis results of the multi-dimensional diagnostic strategy.

[0006] The aforementioned technical solution integrates information from multiple dimensions, including time, environment, and signal characteristics, to collaboratively analyze and cross-verify fault types in high-voltage interlock circuits, resulting in a rich array of detection methods. Compared to related technologies that rely solely on single-dimensional information for diagnosis, this method significantly reduces the probability of misjudgment due to incomplete information from a single dimension, leading to higher accuracy in fault detection results and effective differentiation of specific fault types in high-voltage interlock circuits. Furthermore, through multi-dimensional diagnosis and confirmation, interference can be quickly eliminated while making more decisive judgments about the actual faults, reducing unnecessary confirmation delays and facilitating the timely triggering of high-voltage system safety measures, thereby improving safety. In addition, this application employs an environmental adaptive strategy, dynamically adjusting its diagnostic "sensitivity" based on the vehicle's environmental conditions. This means the diagnostic reference value is not fixed but changes in real-time according to the vehicle's environmental state to adapt to various complex operating conditions, ensuring high detection compatibility and reliability under diverse circumstances. Furthermore, the aforementioned multi-dimensional diagnostic strategies are implemented through software algorithms, which can upgrade the methods based on existing hardware, reducing the performance and complexity requirements of the front-end hardware filtering circuits and helping to save costs and printed circuit board space.

[0007] In conjunction with the first aspect, in some possible implementations, a time-delay diagnostic strategy for classifying the duration of a fault detection signal includes: starting a timer in response to acquiring a fault detection signal; if the duration of the fault detection signal is less than a first preset duration threshold, it is determined to be transient interference; if the duration of the fault detection signal is equal to or greater than the first preset duration threshold, but less than a second preset duration threshold, it is continuously monitored and marked as pending confirmation; if the duration of the fault detection signal is equal to or greater than the second preset duration threshold, it is determined to be a real fault.

[0008] In the aforementioned technical solution, the delay-based diagnostic strategy, by setting a relatively short first preset duration threshold, can filter out a large amount of high-frequency transient interference with a response speed of nanoseconds to microseconds, achieving near-zero latency. This allows for the initial and rapid filtering of explicit noise, reducing subsequent computational load and improving overall response efficiency. By establishing a pending confirmation state and a second preset duration threshold, diagnostic resources can be precisely focused on those ambiguous signals with moderate durations, thus enabling in-depth analysis of more complex algorithms (such as waveform analysis and environmental judgment) and optimizing the allocation of computational resources. Furthermore, a single delay strategy often faces a dilemma in threshold setting: setting it too short can easily lead to false alarms, while setting it too long can delay the response to real faults. This strategy, through hierarchical processing, treats anomalies of different durations differently, quickly eliminating explicit interference while providing sufficient opportunity for observation and in-depth analysis of suspicious signals, fundamentally reducing the false alarm rate and the missed alarm rate.

[0009] Combining the first aspect and the above implementation methods, in some possible implementation methods, the environmental adaptive strategy for dynamically adjusting diagnostic parameters based on the vehicle's environmental state includes: acquiring the vehicle's current environmental state parameters, which include at least one of vibration intensity, ambient temperature, and vehicle operating mode; and dynamically adjusting the diagnostic parameters in the multi-dimensional diagnostic strategy based on the environmental state parameters, which include a duration threshold in the delay diagnostic strategy and a waveform determination threshold in the waveform analysis strategy.

[0010] In the above technical solution, multiple diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted based on the acquired environmental state parameters. This allows the diagnostic sensitivity and judgment criteria to adapt to changes in the external environment, achieving intelligent diagnosis tailored to specific circumstances. In other words, instead of using a fixed, compromise-based set of parameters to handle all situations, the "tolerance window" is dynamically adjusted according to the acquired environmental state parameters. For example, it maintains high sensitivity and rapid response in stable environments, and automatically enhances immunity to disturbances and maintains stability in harsh environments. This ensures a high level of diagnostic reliability under various extreme and routine operating conditions, improving the overall robustness and reliability of detection in complex and changing environments.

[0011] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted, including: increasing the second preset duration threshold when the vibration intensity is higher than the preset vibration threshold; and / or, performing temperature compensation on the amplitude determination benchmark of the fault detection signal according to the ambient temperature; and / or, calling the anti-interference parameter set corresponding to the vehicle operating mode according to the vehicle operating mode.

[0012] In the above technical solution, the environmental adaptive strategy covers three levels: physical and mechanical environment, basic electrical environment, and vehicle operating environment, realizing deep integration and intelligent matching between the diagnostic system and the actual operating state of the vehicle.

[0013] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the waveform analysis strategy for identifying the waveform characteristics of the fault detection signal includes: extracting the waveform characteristics of the fault detection signal, wherein the waveform characteristics include at least one of pulse width, signal fluctuation amplitude and signal fluctuation frequency; and comparing and analyzing the extracted waveform characteristics with a preset interference feature library, wherein the interference feature library includes the waveform feature range of typical interference.

[0014] In the aforementioned technical solutions, traditional methods only focus on the binary "high / low" state of the signal, while this strategy delves into the physical characteristics of the abnormal signal itself, such as pulse width, fluctuation amplitude, and fluctuation frequency. By using pre-established data containing characteristic ranges of various typical interference waveforms, the system can compare the waveform features extracted in real time with this data, thereby quickly identifying interference signals and further improving detection reliability.

[0015] Combining the first aspect and the above implementation methods, in some possible implementation methods, the extracted waveform features are compared and analyzed with a preset interference feature library, including: if all features in the waveform features fall within the corresponding waveform feature range in the interference feature library, it is determined to be transient interference; if any feature in the waveform features does not fall within the corresponding waveform feature range in the interference feature library, it tends to be determined to be a real fault.

[0016] In the above technical solution, this step essentially treats any abnormal signal that does not conform to the known interference pattern as a potential real physical fault and processes it accordingly. This minimizes the risk of missed detection due to failure to identify new or complex interference combinations, and ensures that any suspicious or unknown anomaly can trigger a higher level of warning or protection, thereby improving detection security.

[0017] In combination with the first aspect and the above implementation methods, in some possible implementation methods, after determining whether the fault type of the fault detection signal is a real fault or a transient interference, the method further includes: if it is determined to be a real fault, storing the fault information in a non-volatile memory and reporting it to the vehicle controller; if it is determined to be a transient interference, clearing the current diagnostic state and continuing to execute the step of acquiring the fault detection signal.

[0018] In the above technical solution, this step initiates a state latching mechanism after determining the fault type to be a genuine fault, and a clearing mechanism after determining the fault type to be a transient interference. Through state latching and clearing mechanisms, genuine faults can be reliably recorded, while avoiding the continuous impact of transient interference on the system. Secondly, only confirmed genuine faults are stored non-volatilely and reported over the network, avoiding the writing of massive amounts of transient interference records to finite-lifespan storage media, and also avoiding the unnecessary occupation of vehicle communication bus bandwidth. This hierarchical strategy optimizes storage and communication resources and extends device lifespan.

[0019] Secondly, embodiments of this application provide a fault detection device applied to a high-voltage interlock circuit with multiple low-voltage detection connectors. The device includes: an acquisition module for acquiring fault detection signals of the high-voltage interlock circuit; a diagnosis module for performing fault analysis on the fault detection signals using a preset multi-dimensional diagnosis strategy, the multi-dimensional diagnosis strategy including a time-delay diagnosis strategy that grades the duration of the fault detection signals, an environmental adaptive strategy that dynamically adjusts diagnostic parameters based on vehicle environmental conditions, and a waveform analysis strategy that identifies the waveform characteristics of the fault detection signals; and a confirmation module for determining whether the fault type of the fault detection signals is a real fault or transient interference based on the comprehensive analysis results of the multi-dimensional diagnosis strategy.

[0020] Thirdly, a vehicle is provided, the vehicle including a memory and a processor; the memory is used to store executable program code; the processor is used to call and run the executable program code from the memory, causing the vehicle to perform the fault detection method in any possible implementation of the second aspect and the second aspect.

[0021] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to execute the fault detection method in any possible implementation of the second aspect and the second aspect described above.

[0022] Fifthly, a computer-readable storage medium is provided, which stores a computer program that, when executed, causes the computer to perform the fault detection method in any possible implementation of the second aspect and the second aspect described above. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a fault detection device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the circuit structure of a fault detection device provided in an embodiment of this application; Figure 4 This is a schematic flowchart of a fault detection method provided in an embodiment of this application; Figure 5 This is a schematic flowchart of another fault detection method provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of another vehicle provided in the embodiments of this application.

[0024] In the attached figures, the following labels are used: 1. Fault detection device; 11. Detection circuit; 111. Detection element; 12. Signal processing module; 13. Control module; 14. Switching module; R1, first resistor; R2, second resistor; R3, third resistor; R4, fourth resistor; C, filter capacitor; VCC, power supply voltage; CCS, current source; 6. Vehicle; 61. Memory; 62. Processor; 611. Executable program code. Detailed Implementation

[0025] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0026] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0027] Currently, new energy vehicles are widely used in various scenarios, replacing internal combustion engine vehicles. Compared to internal combustion engine vehicles, new energy vehicles produce less noise and do not directly emit exhaust fumes, making them more environmentally friendly. At the same time, new energy vehicles are more intelligent, have higher energy conversion efficiency, and lower maintenance costs, leading to a growing number of people using them as their mode of transportation. New energy vehicles typically include a power battery to provide power to the vehicle and drive motor. For example, the power battery outputs direct current (DC) to the motor. The motor control unit (MCU) converts this DC power into three-phase alternating current (AC) to control the motor, according to the target torque and speed sent by the vehicle control unit (VCU). This AC power controls the motor to perform functions such as starting, acceleration, deceleration, braking, and energy recovery, ensuring the normal operation of the vehicle.

[0028] New energy vehicles typically have two electrical systems: a high-voltage system and a low-voltage system. The high-voltage system contains a high-voltage battery (e.g., a power battery) that powers high-power electrical equipment (e.g., motors) to drive the vehicle. Simultaneously, the power battery, under the control of the vehicle controller, charges the low-voltage battery, typically at several hundred volts. To ensure the safety of the driver, passengers, and the vehicle itself, a high-voltage interlock system is usually included. This system consists of high-voltage connectors and a control system. The connectors connect various components in the high-voltage electrical system (e.g., high-voltage batteries, motors, inverters, etc.), ensuring the safe transmission of high-voltage current. Each connector typically has an interlock contact, and these contacts are connected in series to form a complete high-voltage interlock circuit. The high-voltage interlock circuit and control system can promptly cut off the high-voltage power supply in case of an abnormality in the high-voltage electrical system, thus preventing electric shock and fire risks.

[0029] High-voltage connectors may become loose or detached, causing an abnormality in the high-voltage interlock circuit. To monitor the connection status of the high-voltage interlock circuit in real time, high-voltage interlock systems in related technologies are typically equipped with a detection system. Currently, there are generally two high-voltage interlock detection schemes in related technologies: hardware-level and software-level. At the hardware level, an RC low-pass filter network is commonly used to pre-filter the high-voltage interlock circuit to suppress high-frequency electromagnetic interference and conducted noise. However, this method has inherent bandwidth limitations. When facing the complex electromagnetic environment of the vehicle, such as switching noise of DC-DC converters, pulse width modulation (PWM) interference in motor drivers, and radio frequency coupling in wireless communication, the filtering parameters struggle to balance response speed and suppression effectiveness, especially in wide-bandwidth, variable-amplitude interference scenarios where robustness is insufficient.

[0030] At the software level, a fixed-time-window level confirmation mechanism is typically used. Only when the detection signal of the high-voltage interlock circuit maintains a valid level within a set delay is it considered a genuine fault. While this strategy can filter out some millisecond-level transient interference, it lacks the ability to identify the intrinsic characteristics of the interference signal. When the duration of the interference approaches or falls within the typical response range of a genuine open-circuit fault, misjudgment is highly likely, or continuous interference may be mistaken for a genuine fault, leading to unnecessary high-voltage disconnection. Alternatively, insufficient delay may cause a genuine fault to be missed, jeopardizing system safety.

[0031] Further analysis reveals several limitations in the detection systems of these technologies: First, they cannot intelligently distinguish between different types of interference. These technologies rely solely on a single "time" dimension for judgment, failing to effectively differentiate between various interference types. For example, the total duration of a brief pulse burst interference caused by vibration may be similar to the duration of an early, real intermittent contact failure, making accurate differentiation difficult and potentially leading to delayed responses to real faults or misidentification of transient interference as faults. Second, they lack environmental adaptability. These technologies typically employ fixed delay parameters, failing to consider the impact of vehicle operating conditions (such as rapid acceleration, deceleration, and high-intensity vibrations when traversing bumpy roads) and environmental conditions (such as extreme temperatures) on the probability and characteristics of interference. During periods of high interference incidence, fixed delay strategies may be overly sensitive, resulting in false alarms; conversely, under stable operating conditions, they may be slow to react. Third, they rely on a single signal characteristic. Most technologies depend solely on simple logical judgments of whether the high-voltage interlock circuit signal is "high" or "low." This processing method fails to fully exploit the rich features inherent in the signal itself, such as the precise pulse width of the abnormal signal, the slope of the rise / fall rate, the stability of the signal during the abnormal period (fluctuation amplitude and frequency), and timing patterns. These features are often key information for distinguishing different types of interference (such as electromagnetic pulses and mechanical vibration shocks) from actual connector failures.

[0032] In summary, the detection methods used in the relevant technologies are relatively simple and cannot accurately distinguish the fault types of the high-voltage interlock detection system, resulting in low accuracy of fault detection results.

[0033] Therefore, embodiments of this application provide a fault detection method, device, vehicle, and computer-readable storage medium. This method integrates information from multiple dimensions such as time, environment, and signal characteristics, enabling collaborative analysis and cross-verification of fault types in circuits, and offers a variety of detection methods. Furthermore, it can effectively distinguish between real faults and transient interference, achieving high detection accuracy.

[0034] The following description, in conjunction with the accompanying drawings, provides an exemplary description of the fault detection method, apparatus, vehicle, and computer-readable storage medium provided in the embodiments of this application.

[0035] In one example, the fault detection method provided in this application is applied to a vehicle, which includes a high-voltage electrical system and a low-voltage electrical system. The high-voltage electrical system includes a high-voltage battery (e.g., a power battery) that supplies power to high-power electrical equipment (e.g., motors, inverters, and other high-voltage components) in the vehicle to drive it and maintain normal operation. Simultaneously, the power battery, under the control of the vehicle controller, also charges the low-voltage battery in the low-voltage electrical system. The low-voltage electrical system includes a low-voltage battery (e.g., a 12V storage battery) and a DC-DC converter (DCDC). The DC-DC converter converts the high-voltage electricity from the high-voltage battery to low-voltage electricity to meet the signal transmission / control requirements of the vehicle; details of this will not be elaborated further.

[0036] In high-voltage electrical systems, the voltage is typically several hundred volts or higher. When personnel are repairing or inspecting vehicles, they may accidentally come into contact with high-voltage components that are not fully disconnected, leading to electric shock. Furthermore, short circuits or poor connections in high-voltage electrical systems can cause sparks or overheating, potentially leading to fires, posing significant safety hazards. Therefore, the vehicle provided in this application is equipped with a high-voltage interlock system. This system includes high-voltage connectors used to connect various components in the high-voltage electrical system, ensuring the safe transmission of high-voltage current. Each high-voltage connector typically has an interlock contact, and these contacts are connected in series via wires to form a complete high-voltage interlock circuit. This circuit ensures that the high-voltage power supply will not be activated when the high-voltage connector is not fully connected or disconnected, thus preventing personnel from contacting energized high-voltage components. Simultaneously, when the high-voltage electrical system experiences a short circuit or poor connection, the high-voltage interlock circuit can quickly cut off the high-voltage power supply, preventing fires caused by electrical faults.

[0037] In one example, such as Figure 1 As shown, the vehicle provided in this application also includes a fault detection device 1 and multiple low-voltage detection connectors 2. The low-voltage detection connectors 2 are located in the high-voltage interlock circuit (not shown in the figure) and correspond to the high-voltage connectors (not shown in the figure). The fault detection device 1 in this application can realize fault detection and accurate fault location of the high-voltage interlock circuit by detecting the connection status of the low-voltage detection connectors. It is worth noting that the number of low-voltage detection connectors can be equal to or less than the number of high-voltage connectors. When the number of low-voltage detection connectors is equal to the number of high-voltage connectors, the high-voltage connectors and low-voltage detection connectors are in one-to-one correspondence to ensure that the status of each high-voltage connector can be detected independently, thereby improving the safety of the system. When the number of low-voltage detection connectors is less than the number of high-voltage connectors, multiple high-voltage connectors can be connected to the same low-voltage detection connector to save manufacturing costs. The specific configuration can be set according to actual needs, and this application does not impose specific restrictions on this.

[0038] The fault detection device 1 provided in this application can accurately detect the connection status of multiple low-voltage detection connectors 2. In one example, such as Figure 2 As shown, the fault detection device 1 includes a detection circuit 11, multiple signal processing modules 12, and a control module 13. The detection circuit 11 includes multiple detection elements 111 connected in series. Each detection element 111 is connected to a corresponding low-voltage detection connector 2. Each signal processing module 12 is connected to a corresponding detection element 111 and is also connected to the control module 13. The control module 13 can receive signals from the multiple signal processing modules 12.

[0039] The detection element 111 is used to output a corresponding detection signal based on the connection status of the low-voltage detection connector 2. It is worth noting that each detection element 111 can output a corresponding detection signal based on the connection status of the low-voltage detection connector 2 connected to it. Each detection element 111 will output the detection signal to the signal processing module 12 connected to it. After processing the multiple detection signals, the multiple signal processing modules 12 output to the control module 13. The control module 13 can determine the on / off status of the high-voltage interlock circuit and the connection status of the multiple low-voltage detection connectors 2 based on the detection signals processed by the multiple signal processing modules 12, so as to achieve accurate detection of the connection status of the multiple low-voltage detection connectors 2 and the on / off status of the high-voltage interlock circuit.

[0040] The connection status includes normal connection and abnormal connection. When all low-voltage detection connectors 2 are normally connected, the high-voltage interlock circuit is connected, that is, the high-voltage interlock circuit is normal. Abnormal connection refers to situations such as the low-voltage detection connectors 2 being loose or falling off. In this case, the low-voltage detection connectors 2 are abnormally connected, causing the high-voltage interlock circuit to be disconnected, that is, the high-voltage interlock circuit is abnormal.

[0041] For example, when all low-voltage detection connectors 2 are in a normal connection state, multiple detection elements 111 can convert the normal connection state into a corresponding detection signal. This detection signal can be represented by a high-level signal indicating that the low-voltage detection connectors 2 are in a normal connection state. The multiple detection elements 111 send their corresponding high-level detection signals to their respective connected signal processing modules 12. The multiple signal processing modules 12 process these high-level detection signals and then output them to the control module 13. The control module 13 can determine, based on the high-level detection signals from the multiple signal processing modules 12, that all low-voltage detection connectors 2 are normally connected, and the high-voltage interlock circuit remains connected, meaning that the high-voltage interlock circuit has not failed.

[0042] When one of the low-voltage detection connectors 2 is in an abnormal connection state, while the others are in a normal connection state, the detection element 111 corresponding to one of the low-voltage detection connectors 2 can convert the abnormal connection state into a corresponding detection signal. At this time, the detection signal can refer to a low-level signal indicating an abnormal connection state for the low-voltage detection connector 2; that is, the detection signal at this time is a fault detection signal indicating an abnormality. The detection element 111 will send the corresponding fault detection signal to the connected signal processing module 12. The detection elements 111 corresponding to the other low-voltage detection connectors 2 can convert the normal connection state into a corresponding high-level detection signal and send it to their respective connected signal processing modules 12. Multiple signal processing modules 12 process the received low-level fault detection signals and high-level detection signals and output them to the control module 13. The control module 13 can determine that the corresponding low-voltage detection connectors 2 are all abnormally connected based on the low-level fault detection signals, and determine that the corresponding low-voltage detection connectors 2 are all normally connected based on the high-level detection signals.

[0043] It is understood that the detection element 111 provided in this application can convert the connection status of the low-voltage detection connector 2 into a high- or low-level detection signal that can be recognized by the signal processing module 12. The signal processing module 12 then sends the detection signal to the control module 13, so that the control module 13 can determine the connection status of the multiple low-voltage detection connectors 2 and the on / off status of the corresponding high-voltage interlock circuit based on the high-level detection signal and the low-level fault detection signal.

[0044] In one example, such as Figure 3 As shown, the detection element 111 includes a first resistor R1. One end of the first resistor R1 is connected to the first end of the signal processing module 12 and the low-voltage detection connector 2, and the other end of the first resistor R1 is connected to one end of the signal processing module 12 and the second end of the low-voltage detection connector 2.

[0045] In one example, such as Figure 3 As shown, the signal processing module 12 may include an optocoupler. The positive terminal of the light-emitting diode (LED) in the optocoupler is connected to one end of the first resistor R1 and the first end of the low-voltage detection connector 2, while the negative terminal of the LED is connected to the other end of the first resistor R1 and the second end of the low-voltage detection connector 2. A transistor is correspondingly positioned to the LED. The collector of the transistor is connected to the control module 13 through the second resistor R2, and the emitter of the transistor is grounded.

[0046] It is worth noting that each first resistor R1 is equipped with an optocoupler, and the emitters of the transistors in the multiple optocouplers are connected to each other to ground.

[0047] In this example, when the LED and the low-voltage detection connector 2 corresponding to the first resistor R1 are properly connected, the LED will not receive current and will not conduct. Therefore, the LED will not emit light, and the transistor will be turned off. The transistor will output a corresponding high-level detection signal to the control module 13. When the connection between the LED and the low-voltage detection connector 2 corresponding to the first resistor R1 is abnormal, the LED will receive current and will conduct. Therefore, the LED will emit light, and the transistor will conduct. The transistor will output a corresponding low-level fault detection signal to the control module 13, allowing the control module 13 to determine that the low-voltage detection connector 2 is abnormally connected based on this signal.

[0048] Optionally, the signal processing module 12 may be a relay or other device or circuit capable of performing the above functions. This application does not impose specific limitations on this.

[0049] In one example, such as Figure 3 As shown, the fault detection device 1 also includes a filter capacitor C. The first plate of the filter capacitor C is connected to one end of the second resistor R2 and the signal processing module 12, and the second plate of the filter capacitor C is grounded.

[0050] In one example, such as Figure 3 As shown, the fault detection device 1 also includes a third resistor R3. One end of the third resistor R3 is connected to the power supply voltage VCC, and the other end of the third resistor R3 is connected to the first plate of the filter capacitor C, one end of the second resistor R2, and the signal processing module 12.

[0051] The specific implementation schemes of high-voltage interlocking circuits can be classified into voltage source type and current source type according to the circuit excitation source. For example, in one example, such as Figure 3 As shown, the fault detection device 1 also includes a fourth resistor R4, a switching module 14, and a current source CCS. One end of the fourth resistor R4 is connected to the control module 13, the first end of the switching module 14 is connected to the other end of the fourth resistor R4, the second end of the switching module 14 is grounded, and the third end of the switching module 14 is connected to the first detection element 111 among multiple detection elements 111 (e.g., ...). Figure 3 The first resistor R1 in the plurality of first resistors R1 shown is connected to the first resistor R1 in the plurality of first resistors R1 shown. One end of the current source CCS is connected to the fourth end of the switch module 14, and the other end of the current source CCS is connected to the last detection element 111 in the plurality of detection elements 111 (e.g., the first resistor R1 in the plurality of first resistors R1 shown). Figure 3 The last of the multiple first resistors R1 shown is connected.

[0052] In this example, when the detection element 111 in the fault detection device 1 needs to perform detection, the control module 13 controls the switch module 14 to turn on, thus completing the circuit formed by the switch module 14 and the ground terminal. This allows the current source CCS to be applied to the circuit containing the low-voltage detection connector 2, enabling both the low-voltage detection connector 2 and the detection element 111 to operate normally. When the detection element 111 in the fault detection device 1 is not needed, the control module 13 controls the switch module 14 to turn off, preventing the current source CCS from being applied to the circuit containing the low-voltage detection connector 2. In this case, the low-voltage detection connector 2 and the detection element 111 do not operate. Thus, by controlling the switch module 14 to turn off, the control module 13 can reduce the energy consumption of the fault detection device 1 and save energy.

[0053] Optionally, the switch module 14 may be an optocoupler, a relay, or other device or circuit capable of performing the above functions. This application does not impose specific limitations on this.

[0054] The aforementioned low-level fault detection signal only indicates that a fault exists in the low-voltage detection connector 2 at this time. However, the abnormality of the low-voltage detection connector 2 may be a real fault or caused by transient interference. To determine whether the fault type at this time is a real fault or transient interference based on the fault detection signal, this application provides a fault detection method. This fault detection method can be applied to the aforementioned... Figures 1 to 3 The fault detection device 1 shown can also be applied to fault detection devices with other architectures, and this application does not impose any specific limitations on this.

[0055] The fault detection method provided in the embodiments of this application will be described exemplarily below with reference to the accompanying drawings. In one example, Figure 4 This is a schematic flowchart of a fault detection method provided in an embodiment of this application; the method 400 includes S401 to S403; S401 to S403 are described in detail below: S401. Obtain the fault detection signal of the high-voltage interlock circuit.

[0056] This step triggers the fault diagnosis and marks the start of data acquisition. Specifically, when any of the multiple detection elements connected in series in the high-voltage interlock circuit detects an abnormal connection status of its corresponding low-voltage detection connector, it generates and outputs an electrical signal indicating the abnormality. This electrical signal is then converted into a standard digital or analog fault detection signal by the subsequent signal processing module. It is worth noting that the presence of a fault detection signal means that at least one node in the high-voltage interlock circuit has detected an abnormality; the absence of a fault detection signal means that the connection status of all nodes in the high-voltage interlock circuit has been confirmed as normal.

[0057] S402. Fault analysis is performed on the fault detection signal through a preset multi-dimensional diagnostic strategy. The multi-dimensional diagnostic strategy includes a delay diagnostic strategy that classifies the duration of the fault detection signal, an environment adaptive strategy that dynamically adjusts the diagnostic parameters based on the vehicle's environmental state, and a waveform analysis strategy that identifies the waveform characteristics of the fault detection signal.

[0058] In this step, the method abandons the traditional single timing delay judgment paradigm and introduces three complementary diagnostic sub-strategies to form a synergistically enhanced comprehensive criterion system, thereby enhancing the accuracy and robustness of the method's fault diagnosis.

[0059] Among these strategies, the time-delay diagnostic strategy, which classifies the duration of fault detection signals, determines the duration based on the temporal evolution characteristics of the signals. Specifically, it divides the abnormal holding period of the fault detection signal into different response intervals and configures differentiated confirmation logic within each interval to distinguish between transient disturbances, intermittent poor contact, and deterministic open-circuit faults. An environment-adaptive strategy, which dynamically adjusts diagnostic parameters based on vehicle environmental conditions, can dynamically correlate vehicle operating status information. A waveform analysis strategy, which identifies the waveform characteristics of fault detection signals, provides in-depth analysis of the dynamic waveform features of the fault detection signals.

[0060] It is worth noting that the above three strategies do not operate in parallel or independently, but together form a closed-loop feedback joint analysis mechanism.

[0061] S403. Based on the comprehensive analysis results of the multi-dimensional diagnostic strategy, determine whether the fault type of the fault detection signal is a real fault or a transient interference.

[0062] This step is the final decision output stage. Based on the consistency verification results of the outputs of each sub-strategy in S402, it generates a comprehensive analysis result with interpretability. Among these, a real fault refers to a substantial safety risk event that requires immediate triggering of high-voltage power-off, fault reporting, and maintenance prompts. Transient interference refers to non-hazardous signal disturbances that require no intervention and can be automatically recovered from.

[0063] Thus, this application integrates information from multiple dimensions, including time, environment, and signal characteristics, to collaboratively analyze and cross-verify fault types in high-voltage interlocking circuits, resulting in a richer range of detection methods. Compared to related technologies that rely solely on single-dimensional information for diagnosis, this method significantly reduces the probability of misjudgment due to incomplete information from a single dimension, leading to higher accuracy in fault detection results and effectively distinguishing specific fault types in high-voltage interlocking circuits. Furthermore, through multi-dimensional diagnosis and confirmation, a more decisive judgment of the actual fault can be made while interference is quickly eliminated, reducing unnecessary confirmation delays and facilitating the timely triggering of high-voltage system safety measures, thereby improving safety.

[0064] Furthermore, this application employs an environmental adaptive strategy to dynamically adjust its diagnostic "sensitivity" based on the vehicle's environmental conditions. This means the diagnostic reference value is not fixed but changes in real-time according to the vehicle's environmental state, adapting to various complex operating conditions. This ensures the method maintains high detection compatibility and reliability under diverse and complex circumstances. Moreover, the aforementioned multi-dimensional diagnostic strategy is implemented through software algorithms, allowing for upgrades to existing hardware. This reduces the performance and complexity requirements of the front-end hardware filtering circuitry, contributing to cost savings and PCB space efficiency.

[0065] The following is about Figure 4 The implementation methods of each step in the illustrated embodiment are explained in detail below: Regarding step S401, in some embodiments, this application may use the aforementioned first resistor and optocoupler to obtain the fault detection signal, and connect the fault detection signal to the input / output port (I / O port) of the control module to execute subsequent fault detection steps. Other devices or circuits may also be used to implement the above function; this application does not impose specific limitations on this.

[0066] Regarding step S402, in some embodiments, the delay diagnosis strategy for classifying the duration of the fault detection signal includes: starting a timer in response to acquiring a fault detection signal; if the duration of the fault detection signal is less than a first preset duration threshold, it is determined to be transient interference; if the duration of the fault detection signal is equal to or greater than the first preset duration threshold, but less than a second preset duration threshold, it is continuously monitored and marked as pending confirmation; if the duration of the fault detection signal is equal to or greater than the second preset duration threshold, it is determined to be a real fault.

[0067] In this step, when a fault detection signal indicating an abnormality in the high-voltage interlock circuit is first detected (e.g., a level transition from high to low), a high-precision timer (e.g., an internal timer of the control module) is immediately triggered to begin timing. It is worth noting that this timing start point is strictly synchronized with the effective edge of the signal to ensure the consistency of the time measurement reference.

[0068] After timing begins, the duration is compared with at least two preset duration thresholds to determine whether the fault type is a real fault or a transient disturbance. If the duration is less than the first preset duration threshold, the signal is determined to be a transient disturbance. This mainly corresponds to millisecond-level non-steady-state disturbances caused by electromagnetic pulses, contact jitter, power supply transients, or bus noise. Its duration is insufficient to pose a substantial threat to the safety boundary of the high-voltage system; therefore, it does not need to trigger protection action and can be ignored. If the duration is equal to or greater than the first preset duration threshold but less than the second preset duration threshold, the signal is marked as an intermediate state awaiting confirmation, and high-frequency sampling of the high-voltage interlock circuit and continuous acquisition of associated environmental parameters are maintained. This intermediate state is designed to avoid the rigidity of a single threshold decision, providing a buffer window and decision redundancy for subsequent integration of environmental adaptive strategies and waveform analysis strategies, preventing misjudgments caused by short-term sudden changes in operating conditions (such as micro-vibration of the wiring harness due to rapid vehicle acceleration). If the duration is equal to or greater than the second preset duration threshold, the signal is initially determined to represent a real fault. This situation indicates that the abnormal state has exceeded the transient tolerance of the high-voltage interlocking system and may be a physical fault of a typical high-voltage interlocking circuit, such as an open circuit, a loose connection, or insulation failure. This triggers the deep intervention of the multi-dimensional comprehensive judgment process in step S403.

[0069] For example, assuming the first preset duration threshold is 5ms and the second preset duration threshold is 10ms~50ms, if the duration is less than 5ms, it is ignored immediately; if the duration is less than 10ms but greater than 5ms, it remains in the pending confirmation state and continues to monitor; if the duration is greater than 10ms, it is initially determined to be a real fault.

[0070] It is worth noting that the first preset duration threshold and the second preset duration threshold are not fixed constants. Their value range can be constrained by the electrical topology of the high-voltage interlock circuit, cable distribution parameters, expected shortest fault evolution cycle, and vehicle functional safety objectives.

[0071] In this step, the delay-based diagnostic strategy, by setting a relatively short first preset duration threshold, can filter out a large amount of high-frequency transient interference with a response speed of nanoseconds to microseconds, achieving near-zero latency. This allows for the initial and rapid filtering of explicit noise, reducing subsequent computational load and improving overall response efficiency. By establishing a pending confirmation state and a second preset duration threshold, diagnostic resources can be precisely focused on those difficult signals with moderate duration and ambiguous nature, thereby enabling in-depth analysis for subsequent calls to more complex algorithms (such as waveform analysis and environmental judgment), and achieving optimized allocation of computational resources.

[0072] Furthermore, a single delay strategy often faces a dilemma in threshold setting: a short delay easily leads to false alarms, while a long delay delays the response to genuine faults. This strategy, through tiered processing, treats anomalies of different durations differently, quickly eliminating obvious interference while providing ample opportunity for observation and in-depth analysis of suspicious signals, fundamentally reducing false alarm and false negative rates. Secondly, for early intermittent faults with durations similar to certain interferences, traditional single delays may directly ignore or misjudge them. This strategy, by introducing a pending confirmation state, provides the system with a better observation window and trigger conditions for initiating multi-dimensional collaborative diagnosis, enabling the system to distinguish between the two through other characteristics, thus enhancing robustness against complex interferences.

[0073] In some embodiments, the environmental adaptive strategy for dynamically adjusting diagnostic parameters based on vehicle environmental conditions includes: acquiring current environmental state parameters of the vehicle, the environmental state parameters including at least one of vibration intensity, ambient temperature, and vehicle operating mode; and dynamically adjusting diagnostic parameters in a multi-dimensional diagnostic strategy based on the environmental state parameters, the diagnostic parameters including a duration threshold in a time-delay diagnostic strategy and a waveform determination threshold in a waveform analysis strategy.

[0074] This involves acquiring the vehicle's current environmental state parameters, specifically a set of environmental state parameters reflecting the current operating environment and conditions, obtained in real-time from the vehicle network or dedicated sensors. These parameters include at least: vibration intensity, acquired through the vehicle domain controller or inertial measurement units and acceleration sensors installed in key locations, quantifying the intensity of mechanical vibration currently experienced by the vehicle; ambient temperature, monitored by monitoring the temperature in the area where the high-voltage interlock circuit is located, for example, indirectly obtained through the battery management system or cabin temperature sensors; and vehicle operating mode, obtained from the vehicle controller or powertrain system, such as "start," "rapid acceleration," "constant speed driving," "braking," "charging," and "idling." These environmental state parameters establish an external "scenario awareness" for the diagnostic system, understanding the objective physical and operating context of the vehicle when abnormal signals occur.

[0075] Based on the acquired environmental state parameters, the diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted. Specifically, this method obtains a set of "environmental parameter-diagnostic parameter" mapping relationships or adjustment rules through pre-setting or algorithmic learning, enabling real-time and dynamic modification of key judgment parameters used by other diagnostic strategies based on the acquired environmental state parameters.

[0076] In this step, multiple diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted based on the acquired environmental state parameters. This allows the sensitivity and judgment criteria of the diagnosis to adapt to changes in the external environment, achieving intelligent diagnosis tailored to specific circumstances. In other words, instead of using a fixed, compromise-based set of parameters to handle all situations, the "tolerance window" is dynamically adjusted according to the acquired environmental state parameters. For example, it maintains high sensitivity and rapid response in stable environments, and automatically enhances immunity to disturbances and maintains stability in harsh environments. This ensures a high level of diagnostic reliability under various extreme and routine operating conditions, improving the overall robustness and reliability of detection in complex and changing environments.

[0077] It is worth noting that under stable operating conditions, this method can employ stricter (i.e., shorter) delay thresholds and more sensitive waveform thresholds. This means that when the vehicle is running smoothly and the interference background is small, once an abnormal signal appears, the system can capture it more quickly and sensitively and tend to identify it as a fault, thereby potentially improving the detection rate of early, intermittent real faults.

[0078] For example, the duration threshold in the delay diagnostic strategy can be dynamically adjusted based on the acquired vibration intensity. For instance, when the vibration intensity exceeds a preset vibration threshold (indicating the vehicle is traversing a bumpy road surface), the second preset duration threshold is increased. For example, the "second preset duration threshold" in the delay diagnostic strategy can be automatically increased from a standard value (e.g., 50ms) to an upper limit value (e.g., 80ms or 100ms). This means that in this environment, the system needs to observe a longer period of stable anomaly before classifying it as a real fault, thus relaxing the judgment criteria and avoiding false alarms caused by momentary connector vibration due to continuous vibration.

[0079] This method directly addresses transient connection fluctuations in high-voltage interlock circuits caused by mechanical vibration. When the system detects that the vehicle is in a high-intensity vibration environment (such as driving over bumpy roads, off-roading, or high-speed driving through jointed roads) through sensors, it achieves precise fault tolerance by increasing the "second preset duration threshold" (i.e., the minimum stable abnormal duration required to determine a real fault) in the delay diagnosis strategy.

[0080] It's worth noting that high-intensity vibrations can easily cause microscopic vibrations at connector terminals, potentially leading to unstable contact resistance changes lasting from tens to hundreds of milliseconds, which can be detected as intermittent abnormal signals. If the traditional fixed delay is set too short, this phenomenon is easily misdiagnosed as a fault. This solution dynamically extends the time required for judgment, essentially providing the system with a longer "cooling-off period" to observe abnormal signals in vibration environments. This ensures that only truly stable and persistent physical disconnections are ultimately confirmed, thus accurately distinguishing between transient intermittent vibrations and genuine faults. Secondly, this adjustment essentially increases the diagnostic time redundancy dynamically based on environmental risks within safety boundaries. It doesn't change the physical nature of fault diagnosis but provides a more comprehensive observation window by extending the confirmation time to eliminate high-probability interference. This significantly reduces the frequency of false alarms under harsh driving conditions such as bumpy roads without sacrificing ultimate safety, improving the driving experience and system reliability.

[0081] For example, the waveform judgment threshold in the waveform analysis strategy can be dynamically adjusted based on the acquired ambient temperature. For instance, temperature compensation can be applied to the amplitude judgment benchmark of the fault detection signal based on the ambient temperature. In extreme low-temperature environments, changes in the physical characteristics of wires and connectors may cause signal amplitude drift. In this case, temperature compensation (e.g., by looking up a table or calculating a formula) can be applied to the "amplitude threshold" used in waveform analysis to determine whether the signal amplitude is abnormal, ensuring that the judgment standard for the same physical fault is consistent at different temperatures and avoiding misjudgments caused by temperature drift.

[0082] It is worth noting that the parameters of resistors, semiconductor devices, and other components constituting the high-voltage interlock circuit change with ambient temperature, causing a slow drift in the amplitude of the output detection signal (such as the voltage reference or comparator threshold) under the same physical connection conditions. Without compensation, under extreme high or low temperatures, normal signals may be misjudged as abnormal (false positives), or minor anomalies may be masked (false negatives). To address this, this solution uses a software algorithm to perform reverse compensation calibration on the amplitude judgment reference based on the real-time ambient temperature, effectively offsetting the temperature drift of hardware characteristics and the systematic errors introduced by temperature drift, ensuring the long-term stability of the diagnostic reference. Secondly, temperature compensation significantly improves reliability and availability under extreme climatic conditions such as severe cold and extreme heat, avoiding seasonal false alarms or performance degradation caused by changes in ambient temperature, and exhibiting strong regional and seasonal environmental adaptability.

[0083] For example, based on the acquired vehicle operating mode, the corresponding anti-interference parameter set can be invoked. It is worth noting that different vehicle operating modes (such as "high-power charging," "rapid acceleration / regenerative braking," "high-speed motor operation," and "low idling") are accompanied by vastly different electrical loads, power converter switching states, and the resulting unique electromagnetic interference spectra. This solution pre-configures or learns the optimal "anti-interference parameter set" for different typical operating modes. This parameter set may comprehensively include: specific delay threshold combinations applicable to the current mode, waveform filtering parameters (such as filter coefficients for specific frequency bands) targeting typical electromagnetic noise characteristics of that mode, etc. When the system recognizes that it has entered a certain mode, it automatically invokes the corresponding parameter set.

[0084] For example, when the vehicle is operating in "high-power DC charging" mode, the charger may introduce specific conducted interference; when the vehicle is operating in "rapid acceleration" mode, the high-frequency switching noise of the drive motor controller may be aggravated. By calling the parameter set corresponding to the mode, the system can proactively enhance its immunity to known, frequent, and specific types of interference, providing forward-looking protection rather than a passive response. Compared to general fixed parameter settings, this solution has stronger targeting, higher anti-interference efficiency, and a lower false alarm rate.

[0085] Thus, the environmental adaptive strategy provided in this application covers three levels: physical and mechanical environment, basic electrical environment, and vehicle operating environment, realizing deep integration and intelligent matching between the diagnostic system and the actual operating state of the vehicle.

[0086] In some embodiments, a waveform analysis strategy for identifying waveform features of a fault detection signal includes: extracting waveform features of the fault detection signal, wherein the waveform features include at least one of pulse width, signal fluctuation amplitude, and signal fluctuation frequency; and comparing and analyzing the extracted waveform features with a preset interference feature library, wherein the interference feature library includes the waveform feature range of typical interference.

[0087] It should be understood that the interference signature database is not a closed, static database. It can be continuously updated and expanded with the testing of new vehicle models, the introduction of new components, or the collection of massive amounts of data through the Internet of Vehicles, constantly enriching its identification capabilities to adapt to new electromagnetic environments and new types of interference.

[0088] Traditional solutions only focus on the binary "high / low" state of a signal, while this strategy delves into the physical characteristics of the abnormal signal itself, such as pulse width, amplitude, and frequency. By using pre-established data encompassing the characteristic ranges of various typical interference waveforms, the system can compare the real-time extracted waveform features with this data. For example, a back EMF spike generated by the switching off of a relay coil typically has an extremely narrow pulse width and an extremely high instantaneous amplitude; while intermittent contact caused by connector vibration may manifest as a continuous pulse group with varying amplitudes within a specific frequency range. Through comparison, the system can effectively identify signals that highly match known interference patterns, thus classifying them as transient interference and achieving accurate identification of the essential characteristics of the interference signal.

[0089] For interference signals that are prolonged and difficult to distinguish using traditional delay strategies (such as electromagnetic interference envelopes lasting tens of milliseconds or intermittent interference caused by mechanical vibration), waveform analysis provides a crucial distinguishing factor. For example, the waveform of a real fault (such as a stable disconnection) typically exhibits a stable level transition followed by a prolonged period of low volatility. In contrast, the waveform of the aforementioned persistent interference often displays characteristic fluctuations or oscillations during its duration. By analyzing the stability (fluctuation amplitude and frequency) of the signal during the abnormal period, the two can be effectively distinguished.

[0090] For genuine but early-stage, unstable faults (such as low-voltage connectors starting to loosen, manifesting as irregular, momentary disconnections), their waveform characteristics may not conform to any known typical interference patterns and exhibit irregular randomness. This "unclassifiable" characteristic, combined with its duration and environmental information, can serve as important supporting evidence to suggest a genuine fault. This strategy demonstrates superior ability to distinguish between camouflaged interference and early-stage faults.

[0091] In some embodiments, the extracted waveform features are compared and analyzed with a preset interference feature library, including: if all features in the waveform features fall within the corresponding waveform feature range in the interference feature library, it is determined to be transient interference; if any feature in the waveform features does not fall within the corresponding waveform feature range in the interference feature library, it is likely to be determined to be a real fault.

[0092] It should be understood that only signals that perfectly match known interference patterns are explicitly classified as interference. This requires that all extracted features of the signal (such as pulse width, fluctuation amplitude, and frequency) must simultaneously fall within the allowable range of each feature defined for that type of interference in the interference feature library. This "unanimous approval" mechanism sets extremely high interference confirmation standards, ensuring that only known interferences with highly typical and deterministic features are safely filtered out. If any feature of the signal exceeds the range of all known interference feature libraries, it is considered "feature mismatch or unknown." In this case, it is more likely to be judged as a real fault. This step essentially treats any abnormal signal that does not conform to known interference patterns as a potential real physical fault, minimizing the risk of missed detection due to failure to identify new or complex interference combinations, and ensuring that any suspicious or unknown anomalies trigger higher-level warnings or protections, thereby improving detection security.

[0093] In some embodiments, after determining whether the fault type of the fault detection signal is a real fault or a transient interference, the method further includes: if it is determined to be a real fault, storing the fault information in a non-volatile memory and reporting it to the vehicle controller; if it is determined to be a transient interference, clearing the current diagnostic state and continuing to execute the step of acquiring the fault detection signal.

[0094] In this embodiment, after completing multi-dimensional diagnosis and judgment of fault types, a differentiated, closed-loop post-processing procedure is executed for different judgment results (real faults or transient interference). For example, a complete safety closed loop of "confirmation, recording, reporting, and handling" is implemented for real faults, greatly improving system security; and intelligent processing of "silent reset and seamless regression" is implemented for transient interference, ensuring continuous system availability.

[0095] Once a fault is determined to be genuine, the fault record, containing key information such as fault location, fault timestamp, and relevant environmental conditions, is immediately latched into non-volatile memory. This ensures that fault information is completely preserved even after system power loss or reset, preventing the loss of fault evidence due to temporary power outages and providing reliable data for subsequent maintenance and diagnosis. Secondly, while storing the fault information, it is immediately reported to the vehicle controller via the vehicle communication network to trigger the vehicle-level rapid safety response mechanism. The vehicle controller can be pre-set with a tiered safety protection strategy, such as: Level 1 Alarm: Displaying a clear high-voltage system fault warning on the instrument panel, prompting the driver to stop safely. Level 2 Power Limiting: Limiting the output power of the drive motor or charging system to reduce risk. Level 3 High-Voltage Cut-off: Controlling the high-voltage main relay or fuse to actively cut off the high-voltage power supply, achieving the highest level of physical isolation.

[0096] This millisecond-level automated closed loop, from detection and judgment to reporting and handling, upgrades the function of the high-voltage interlock system from simple "monitoring" to proactive "safety protection," greatly shortening the time window from the occurrence of a fault to the effectiveness of safety measures, and providing the highest level of safety protection for drivers, passengers and the vehicle itself.

[0097] When an incident is determined to be transient, all diagnostic status variables, timers, and intermediate buffers allocated and used for this abnormal event are automatically cleared. This means the system instantly and cleanly switches back from "diagnostic analysis mode" to "normal monitoring mode." The steps for acquiring fault detection signals continue, restoring real-time, uninterrupted monitoring of the high-voltage interlock circuit.

[0098] Thus, this step initiates a state latching mechanism after determining the fault type to be a genuine fault, and a clearing mechanism after determining the fault type to be a transient disturbance. Through state latching and clearing mechanisms, genuine faults can be reliably recorded, while preventing transient disturbances from causing lasting impacts on the system. Secondly, only confirmed genuine faults are stored non-volatilely and reported over the network, avoiding the writing of massive amounts of transient disturbance records to finite-lifespan storage media and preventing the unnecessary occupation of vehicle communication bus bandwidth. This hierarchical strategy optimizes storage and communication resources and extends device lifespan.

[0099] It is worth noting that for latched faults, even if the I / O port status returns to normal, the fault code will be retained until the system's next power-on self-test. If the high-voltage interlock circuit is found to be completely normal, the historical fault code can be cleared, or it can be manually cleared using diagnostic tools. This application does not impose specific restrictions on this.

[0100] In summary, in one example, Figure 5 This is a schematic flowchart of another fault detection method provided in an embodiment of this application; the method 500 includes S501 to S5017; S501 to S5017 are described below: S501, Start detecting / periodically reading the I / O port status.

[0101] S502. Has a low-level fault detection signal been detected? If yes, proceed to S503; otherwise, return to step S501.

[0102] In this step, when any of the multiple detection elements connected in series in the high-voltage interlock circuit detects an abnormal connection status of its corresponding low-voltage detection connector, an electrical signal representing the abnormality will be generated and output. This electrical signal is then converted into a standard digital or analog fault detection signal by the subsequent signal processing module. It is worth noting that the presence of a fault detection signal means that at least one node in the high-voltage interlock circuit has detected an abnormality; if no fault detection signal is detected, it means that the connection status of all nodes in the high-voltage interlock circuit has been confirmed as normal.

[0103] S503, triggering multi-dimensional diagnostic strategies.

[0104] S504, Delayed Diagnostic Strategy.

[0105] S505, Start the delay timer.

[0106] S506. Continuously monitor the duration of fault detection signals.

[0107] In this step, the delay-based diagnostic strategy, by setting a relatively short first preset duration threshold, can filter out a large amount of high-frequency transient interference with a response speed of nanoseconds to microseconds, achieving near-zero latency. This allows for the initial and rapid filtering of explicit noise, reducing subsequent computational load and improving overall response efficiency. By establishing a pending confirmation state and a second preset duration threshold, diagnostic resources can be precisely focused on those difficult signals with moderate duration and ambiguous nature, thereby enabling in-depth analysis for subsequent calls to more complex algorithms (such as waveform analysis and environmental judgment), and achieving optimized allocation of computational resources.

[0108] Furthermore, a single delay strategy often faces a dilemma in threshold setting: a short delay easily leads to false alarms, while a long delay delays the response to genuine faults. This strategy, through tiered processing, treats anomalies of different durations differently, quickly eliminating obvious interference while providing ample opportunity for observation and in-depth analysis of suspicious signals, fundamentally reducing false alarm and false negative rates. Secondly, for early intermittent faults with durations similar to certain interferences, traditional single delays may directly ignore or misjudge them. This strategy, by introducing a pending confirmation state, provides the system with a better observation window and trigger conditions for initiating multi-dimensional collaborative diagnosis, enabling the system to distinguish between the two through other characteristics, thus enhancing robustness against complex interferences.

[0109] S507, Environment Adaptive Strategy.

[0110] S508, Obtain environmental status parameters.

[0111] S509, Adjust the threshold.

[0112] In this step, multiple diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted based on the acquired environmental state parameters. This allows the sensitivity and judgment criteria of the diagnosis to adapt to changes in the external environment, achieving intelligent diagnosis tailored to specific circumstances. In other words, instead of using a fixed, compromise-based set of parameters to handle all situations, the "tolerance window" is dynamically adjusted according to the acquired environmental state parameters. For example, it maintains high sensitivity and rapid response in stable environments, and automatically enhances immunity to disturbances and maintains stability in harsh environments. This ensures a high level of diagnostic reliability under various extreme and routine operating conditions, improving the overall robustness and reliability of detection in complex and changing environments.

[0113] S5010, waveform analysis strategy.

[0114] S5011, Waveform Feature Analysis.

[0115] S5012, Identify interference characteristics.

[0116] In this step, traditional methods only focus on the binary "high / low" state of the signal, while this strategy delves into the physical characteristics of the abnormal signal itself, such as pulse width, fluctuation amplitude, and fluctuation frequency. By using pre-established data containing characteristic ranges of various typical interference waveforms, the system can compare the waveform features extracted in real time with this data, thereby quickly identifying interference signals and further improving detection reliability.

[0117] S5013, Decision Factors.

[0118] S5014. Make a comprehensive decision to determine whether the fault is a real fault or a transient disturbance. If it is a real fault, proceed to S5015; if it is a transient disturbance, return to step S501.

[0119] In this step, this application integrates information from multiple dimensions such as time, environment, and signal characteristics to conduct collaborative analysis and cross-verification of fault types in high-voltage interlock circuits, resulting in a relatively rich array of detection methods.

[0120] S5015, Fault Reporting and Latching / Triggering Safety Policy.

[0121] S5016, System power-on or diagnostic tool command. If yes, execute S5017; otherwise, repeat S5016.

[0122] S5017, Perform power-on self-test or diagnostic clearing.

[0123] In summary, this application integrates information from multiple dimensions, including time, environment, and signal characteristics, to collaboratively analyze and cross-validate fault types in high-voltage interlocking circuits, resulting in a rich array of detection methods. Compared to related technologies that rely solely on single-dimensional information for diagnosis, this method significantly reduces the probability of misjudgment due to incomplete information from a single dimension, achieving higher accuracy in fault detection results and effectively distinguishing specific fault types in high-voltage interlocking circuits. Furthermore, through multi-dimensional diagnosis and confirmation, a more decisive judgment of the actual fault can be made while interference is quickly eliminated, reducing unnecessary confirmation delays and facilitating the timely triggering of high-voltage system safety measures, thereby improving safety.

[0124] In some embodiments, this application also provides a fault detection device applied to a high-voltage interlock circuit having multiple low-voltage detection connectors. The device includes: an acquisition module, a diagnostic module, and a confirmation module.

[0125] The acquisition module is used to acquire fault detection signals of the high-voltage interlock circuit.

[0126] The diagnostic module is used to perform fault analysis on fault detection signals through preset multi-dimensional diagnostic strategies. The multi-dimensional diagnostic strategies include a time-delay diagnostic strategy that classifies the duration of fault detection signals, an environment adaptive strategy that dynamically adjusts diagnostic parameters based on vehicle environmental conditions, and a waveform analysis strategy that identifies the waveform characteristics of fault detection signals.

[0127] The confirmation module is used to determine whether the fault type of the fault detection signal is a real fault or transient interference based on the comprehensive analysis results of the multi-dimensional diagnostic strategy.

[0128] Figure 6 This is a schematic diagram of the structure of another vehicle provided in the embodiments of this application.

[0129] For example, such as Figure 6 As shown, vehicle 6 includes a memory 61 and a processor 62. The memory 61 stores executable program code 611, and the processor 62 is used to call and execute the executable program code 611 to perform a fault detection method.

[0130] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0131] When each functional module is divided according to its corresponding function, the device may also include a judgment module, an activation module, and a control module. It should be noted that all relevant content regarding the steps involved in the above method embodiments can be referenced from the functional descriptions of the corresponding functional modules, and will not be repeated here.

[0132] It should be understood that the apparatus provided in this embodiment is used to perform the above-described fault detection method, and therefore can achieve the same effect as the above-described implementation method.

[0133] When using an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module can be used to control and manage the vehicle's movements. The storage module can be used to support the vehicle in executing relevant program code and data.

[0134] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits shown in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0135] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a fault detection method provided in the above embodiments.

[0136] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to implement a fault detection method provided in the above embodiment.

[0137] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement a fault detection method provided in the above embodiment.

[0138] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0139] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0140] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0141] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A fault detection method, applied to a high-voltage interlock circuit with multiple low-voltage detection connectors, characterized in that, The method includes: Obtain the fault detection signal of the high-voltage interlock circuit; The fault detection signal is analyzed by a preset multi-dimensional diagnostic strategy. The multi-dimensional diagnostic strategy includes a time delay diagnostic strategy that classifies the duration of the fault detection signal, an environment adaptive strategy that dynamically adjusts diagnostic parameters based on the vehicle environment status, and a waveform analysis strategy that identifies the waveform characteristics of the fault detection signal. Based on the comprehensive analysis results of the multi-dimensional diagnostic strategy, the fault type of the fault detection signal is determined to be either a real fault or transient interference.

2. The fault detection method according to claim 1, characterized in that, The time-delay diagnostic strategy for classifying and determining the duration of the fault detection signal includes: In response to receiving the fault detection signal, a timer is started; If the duration of the fault detection signal is less than the first preset duration threshold, it is determined to be transient interference; If the duration of the fault detection signal is equal to or greater than the first preset duration threshold, but less than the second preset duration threshold, then it will continue to be monitored and marked as pending confirmation. If the duration of the fault detection signal is equal to or greater than the second preset duration threshold, it is determined to be a real fault.

3. The fault detection method according to claim 1, characterized in that, The environmental adaptive strategy based on dynamically adjusting diagnostic parameters according to vehicle environmental conditions includes: Obtain the current environmental state parameters of the vehicle, including at least one of vibration intensity, ambient temperature, and vehicle operating mode; Based on the environmental state parameters, the diagnostic parameters in the multi-dimensional diagnostic strategy are dynamically adjusted. The diagnostic parameters include the duration threshold in the delay diagnostic strategy and the waveform determination threshold in the waveform analysis strategy.

4. The fault detection method according to claim 3, characterized in that, The dynamic adjustment of diagnostic parameters in the multi-dimensional diagnostic strategy includes: When the vibration intensity is higher than the preset vibration threshold, the second preset duration threshold is increased; And / or, Temperature compensation is applied to the amplitude determination benchmark of the fault detection signal based on the ambient temperature. And / or, Based on the vehicle operating mode, call the anti-interference parameter set corresponding to the vehicle operating mode.

5. The fault detection method according to claim 1, characterized in that, The waveform analysis strategy for identifying the waveform features of the fault detection signal includes: The waveform features of the fault detection signal are extracted, and the waveform features include at least one of pulse width, signal fluctuation amplitude, and signal fluctuation frequency; The extracted waveform features are compared and analyzed with a preset interference feature library, which includes the waveform feature range of typical interferences.

6. The fault detection method according to claim 5, characterized in that, The step of comparing and analyzing the extracted waveform features with a preset interference feature library includes: If all the waveform features fall within the corresponding waveform feature range in the interference feature library, then it is determined to be transient interference; If any of the waveform features does not fall within the corresponding waveform feature range in the interference feature library, it is likely to be judged as a real fault.

7. The fault detection method according to any one of claims 1-6, characterized in that, After determining whether the fault type of the fault detection signal is a real fault or transient interference, the method further includes: If the fault is determined to be a genuine fault, the fault information is stored in non-volatile memory and reported to the vehicle controller. If the interference is determined to be transient, the current diagnostic status is cleared, and the steps to acquire fault detection signals are continued.

8. A fault detection device, applied to a high-voltage interlock circuit having multiple low-voltage detection connectors, characterized in that, The device includes: The acquisition module is used to acquire the fault detection signal of the high-voltage interlock circuit; The diagnostic module is used to perform fault analysis on the fault detection signal through a preset multi-dimensional diagnostic strategy. The multi-dimensional diagnostic strategy includes a delay diagnostic strategy that classifies the duration of the fault detection signal, an environment adaptive strategy that dynamically adjusts diagnostic parameters based on the vehicle environment status, and a waveform analysis strategy that identifies the waveform characteristics of the fault detection signal. The confirmation module is used to determine whether the fault type of the fault detection signal is a real fault or transient interference based on the comprehensive analysis results of the multi-dimensional diagnostic strategy.

9. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor is configured to call and run the executable program code from the memory, causing the vehicle to perform the fault detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the fault detection method as described in any one of claims 1 to 7.

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