A method, device, equipment and storage medium for judging frequent contact of a relay

Abstract

The present invention discloses a method, device, equipment, and storage medium for determining whether a relay is frequently engaged. The method comprises: obtaining relay status parameters in real time, determining an adjustment factor based on the relay status parameters, and determining a sliding time window based on the adjustment factor; within the sliding time window, determining whether the number of times the relay is engaged is greater than a set threshold; if so, generating a relay frequent engagement alarm instruction. In the method for determining whether a relay is frequently engaged, the sliding time window can be dynamically adjusted based on the relay status parameters obtained in real time. Based on the dynamically determined sliding time window, when the use status of the relay changes, it is still possible to accurately determine whether the relay has a frequent engagement fault, thereby improving the safety and reliability of the system configured with the relay.

Description

Technical Field

[0001] The embodiments of the present invention relate to control technology, and in particular to a method, device, equipment and storage medium for judging whether a relay is frequently engaged. Background Art

[0002] Relays are a crucial component in powering pure electric vehicles. Existing technologies primarily address relay sticking, closure failure, overload during the pre-charging process, and short circuits. However, limited diagnostics exist to prevent the relay from frequently engaging in conditions of repeated power cycling. Frequent relay engagement under these conditions can shorten the lifespan of the relay and potentially damage components such as capacitors, fuses, and DC contactors in the vehicle.

[0003] Based on the above, if the number of times the relay is energized is simply limited, this may affect the vehicle's repeated power-on and power-off functions. In order to improve the safety and reliability of electric vehicles, it is very necessary to accurately determine whether the relay is frequently energized. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for judging frequent closing of a relay, so as to achieve the purpose of accurately judging a frequent closing fault of a relay, thereby improving the safety and reliability of a system equipped with relays.

[0005] In a first aspect, an embodiment of the present invention provides a method for determining whether a relay is frequently engaged, comprising:

[0006] Acquire relay state parameters in real time, determine an adjustment factor according to the relay state parameters, and determine a sliding time window according to the adjustment factor;

[0007] In the sliding time window, it is determined whether the number of times the relay is engaged is greater than a set threshold. If it is greater than the set threshold, a relay frequent engagement alarm instruction is generated.

[0008] Optionally, the relay status parameter includes at least one of relay temperature, relay life, and relay load cut-off times;

[0009] Determining the adjustment factor according to the relay state parameter includes:

[0010] The relay state parameters are input into an adjustment factor model to obtain the adjustment factor.

[0011] Optionally, determining the sliding time window according to the adjustment factor includes:

[0012] If the adjustment factor is greater than the first limit, setting the sliding time window to the sliding time window upper limit;

[0013] If the adjustment factor is less than the second limit, setting the sliding time window to the sliding time window lower limit;

[0014] If the adjustment factor is greater than the second limit and less than the first limit, the sliding time window is determined by the sliding time window upper limit, the sliding time window lower limit, the adjustment factor, the first limit, and the second limit.

[0015] Optionally, if the adjustment factor is greater than the second limit value and less than the first limit value, the sliding time window is determined by the following formula:

[0016]

[0017] In the above formula, M is the sliding time window, M min is the lower limit of the sliding time window, M max is the upper limit of the sliding time window, a is the adjustment factor, f min is the first limit, f max is the second limit, and int represents the rounding function.

[0018] Optionally, when the relay is first closed, the sliding time window is started, and within the sliding time window, it is determined whether the number of times the relay is closed is greater than a set threshold.

[0019] Optionally, the method for determining whether a relay is frequently engaged is used for controlling relays in an electric vehicle battery system.

[0020] Optionally, the relay includes one or more of a pre-charge relay, a main positive relay, a main negative relay, a fast charge positive relay, and a slow charge negative relay.

[0021] In a second aspect, an embodiment of the present invention further provides a relay frequent energization judgment device, including a relay control unit, wherein the relay control unit is configured to:

[0022] Acquire relay state parameters in real time, determine an adjustment factor according to the relay state parameters, and determine a sliding time window according to the adjustment factor;

[0023] In the sliding time window, it is determined whether the number of times the relay is engaged is greater than a set threshold. If it is greater than the set threshold, a relay frequent engagement alarm instruction is generated.

[0024] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising at least one processor, and a memory communicatively connected to the at least one processor;

[0025] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the relay frequent energization judgment method described in the embodiment of the present invention.

[0026] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the frequent energization of a relay recorded in an embodiment of the present invention when executed.

[0027] Compared with the prior art, the beneficial effect of the present invention is that: the present invention proposes a method for judging whether a relay is frequently attracted, the method comprising acquiring relay status parameters in real time, determining an adjustment factor according to the relay status parameters, determining a sliding time window according to the adjustment factor, and then determining whether the relay has a frequent attraction fault according to the sliding time window. Based on the relay status parameters acquired in real time, the sliding time window can be dynamically adjusted. Based on the dynamically determined sliding time window, when the use status of the relay changes, it can still be accurately determined whether the relay has a frequent attraction fault, thereby improving the safety and reliability of the system configured with the relay. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 1 is a flow chart of a method for determining if a relay is frequently engaged in an embodiment;

[0029] Figure 2 is a flow chart of a method for determining a sliding time window in an embodiment;

[0030] Figure 3 This is a flow chart of another method for determining if a relay is frequently engaged in an embodiment;

[0031] Figure 4 is a schematic diagram of an electronic device in an embodiment. DETAILED DESCRIPTION

[0032] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0033] Example 1

[0034] Figure 1 This is a flow chart of the relay frequent energization judgment method in the embodiment, refer to Figure 1 , the relay frequent energization judgment method includes:

[0035] S101. Acquire relay state parameters in real time, determine an adjustment factor based on the relay state parameters, and determine a sliding time window based on the adjustment factor.

[0036] Illustratively, in this embodiment, the relay state parameter may be acquired once in each sampling period, and subsequent calculations may be performed based on the most recently acquired relay state parameter.

[0037] For example, in this embodiment, the relay status parameters include parameters that can be used to reflect the physical characteristics of the relay when it is working (such as temperature, input current, input voltage, output current, output voltage, etc.), parameters that can be used to reflect the remaining life of the relay (such as the number of historical attraction times, the number of load disconnection times, etc.), etc.

[0038] For example, in this embodiment, the adjustment factor can be determined by using a neural network model, a data fitting model, an empirical model, etc. according to the relay state parameter.

[0039] Illustratively, in this embodiment, according to the adjustment factor, a linear function, a MAP graph, or the like may be used to determine the sliding time window (the duration corresponding to the sliding time window).

[0040] S102. Within the sliding time window, determine whether the number of times the relay is engaged is greater than a set threshold. If it is greater than the set threshold, generate a relay frequent engagement alarm instruction.

[0041] For example, in this embodiment, when the relay is working, the number of times the relay is engaged is determined. If the number of times the relay is engaged is greater than a set threshold within the time interval corresponding to the sliding time window, a relay frequent engagement alarm instruction is generated.

[0042] For example, in this embodiment, the relay frequent energization alarm instruction is mainly used to indicate that a relay frequent energization fault occurs.

[0043] This embodiment proposes a method for determining whether a relay is frequently engaged. The method includes acquiring relay status parameters in real time, determining an adjustment factor based on the relay status parameters, determining a sliding time window based on the adjustment factor, and then determining whether the relay has a frequent engagement fault based on the sliding time window. Based on the relay status parameters acquired in real time, the sliding time window can be dynamically adjusted. Based on the dynamically determined sliding time window, when the use status of the relay changes, it can still be accurately determined whether the relay has a frequent engagement fault, thereby improving the safety and reliability of the system configured with the relay.

[0044] exist Figure 1 On the basis of the scheme shown, as a feasible solution, the relay status parameters include relay temperature, relay life and relay load disconnection times.

[0045] Exemplarily, in this solution, the relay temperature is the temperature of the relay in the current sampling period, which can be directly obtained by measurement. For example, the measurement value of the relay temperature sensor can be used as the relay temperature;

[0046] The relay life is the remaining life of the relay. The relay life can be determined based on the total usage history of the relay (the total history up to the current sampling period). The method for determining the relay life based on the total usage history is not specifically limited.

[0047] The relay life (total usage history) can be stored in the relay controller or vehicle controller, and the relay life can be read from the relay controller or vehicle controller;

[0048] The number of load cut-offs of the relay is the total number of historical load cut-offs of the relay (the total number of historical load cut-offs up to the current sampling period), which can be determined by reading the historical record data of the relay;

[0049] The number of relay on-load cut-offs (the total number of historical on-load cut-offs) can be stored in the relay controller or the vehicle controller, and the number of relay on-load cut-offs can be read from the relay controller or the vehicle controller.

[0050] In this scheme, the relay temperature, relay life, and relay load disconnection times are used to determine the adjustment factor through an adjustment factor model. That is, the relay state parameters (relay temperature, relay life, and relay load disconnection times) are input into the adjustment factor model to obtain the adjustment factor.

[0051] Illustratively, in this solution, the adjustment factor model can be constructed through experience, calibration experiments, etc.

[0052] Figure 2 This is a flow chart of the sliding time window determination method in the embodiment, refer to Figure 2 ,exist Figure 1 Based on the scheme shown, determining the sliding time window includes:

[0053] S1011. If the adjustment factor is greater than the first limit, the sliding time window is set to the sliding time window upper limit.

[0054] Exemplarily, in this solution, the first limit value and the upper limit value of the sliding time window are set values, which can be determined through experience or calibration tests.

[0055] S1012. If the adjustment factor is less than the second limit, set the sliding time window to the sliding time window lower limit.

[0056] Exemplarily, in this solution, the second limit value, the lower limit value of the sliding time window is a set value, which can be determined through experience or calibration tests.

[0057] S1013. If the adjustment factor is greater than the second limit and less than the first limit, the sliding time window is determined by the sliding time window upper limit, the sliding time window lower limit, the adjustment factor, the first limit, and the second limit.

[0058] Illustratively, in this solution, the sliding time window upper limit value, the sliding time window lower limit value, the adjustment factor, the first limit value, and the second limit value can be determined by a time window model, wherein the time window model can be determined by a calibration test.

[0059] exist Figure 2 On the basis of the scheme shown, as an implementable solution, based on the sliding time window upper limit value, the sliding time window lower limit value, the adjustment factor, the first limit value, and the second limit value, the sliding time window can be determined by the following formula;

[0060]

[0061] In the above formula, M is the sliding time window, M min is the lower limit of the sliding time window, M max is the upper limit of the sliding time window, a is the adjustment factor, f min is the first limit, f max is the second limit, and int represents the rounding function.

[0062] Figure 3 This is another flow chart of the method for judging the frequent energization of relays in the embodiment, refer to Figure 3 As a feasible solution, the method for judging the frequent energization of the relay can be:

[0063] S201. Obtain the relay temperature, relay life, and relay load cut-off times in real time, and determine an adjustment factor based on the relay temperature, relay life, and relay load cut-off times.

[0064] In this solution, the relay temperature, relay life, and relay load disconnection times are used to determine the adjustment factor through an adjustment factor model, wherein the adjustment factor model is constructed through a calibration test.

[0065] S202. Determine the sliding time window according to the sliding time window upper limit value, the sliding time window lower limit value, the adjustment factor, the first limit value, and the second limit value.

[0066] Exemplarily, in this solution, if the adjustment factor is greater than or equal to the first limit, the sliding time window is set to the sliding time window upper limit value; if the adjustment factor is less than or equal to the second limit value, the sliding time window is set to the sliding time window lower limit value; if the adjustment factor is greater than or equal to the second limit value and less than or equal to the first limit value, the sliding time window is determined by the sliding time window upper limit value, the sliding time window lower limit value, the adjustment factor, the first limit value, and the second limit value. That is, in this solution, the sliding time window is determined by the following formula:

[0067]

[0068] In the above formula, M is the sliding time window, M min is the lower limit of the sliding time window, M max is the upper limit of the sliding time window, a is the adjustment factor, f min is the first limit, f max is the second limit, and int represents the rounding function.

[0069] S203. Within the sliding time window, determine whether the number of times the relay is engaged is greater than a set threshold. If it is greater than the set threshold, generate a relay frequent engagement alarm instruction.

[0070] Exemplarily, in this solution, the method for judging whether the relay is frequently engaged is applicable to the relay control in the battery system of an electric vehicle. Specifically, the relay includes one or more of a pre-charging relay, a main positive relay, a main negative relay, a fast charging positive relay, and a slow charging negative relay.

[0071] For example, in this solution, for a relay, when the relay is first energized, a sliding time window is started, and within a time interval corresponding to the sliding time window, it is determined whether the number of times the relay is energized is greater than a set threshold;

[0072] After the duration corresponding to the sliding time window has passed, the sliding time window is shifted along the time axis by its corresponding duration, and then it is determined whether the number of times the relay is engaged within the time interval corresponding to the current sliding time window is greater than the set threshold.

[0073] Example 2

[0074] This embodiment provides a relay frequent energization judgment device, including a relay control unit, which is configured to:

[0075] Obtain relay status parameters in real time, determine adjustment factors based on the relay status parameters, and determine the sliding time window based on the adjustment factors;

[0076] In the sliding time window, it is determined whether the number of times the relay is engaged is greater than the set threshold. If it is greater than the set threshold, a relay frequent engagement alarm instruction is generated.

[0077] Specifically, in this embodiment, the relay control unit can be configured to implement any one of the relay frequent energization judgment methods recorded in Example 1. Its specific implementation process and beneficial effects are the same as the corresponding contents recorded in Example 1 and will not be repeated here.

[0078] For example, in this embodiment, the relay frequent energization determination device can be implemented by software. For example, the software can be configured to determine whether the number of times the relay is energized within the sliding time window is greater than a set threshold in the following manner:

[0079] Initialization EnFlg=1;i=1,trigger relay pickup signal ConCmd,relay frequent pickup fault FqtClsdErr;

[0080]

[0081]

[0082] Example 3

[0083] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention 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 can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0084] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0085] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0086] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for determining whether a relay is frequently engaged.

[0087] In some embodiments, the relay frequent energization determination method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the relay frequent energization determination method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the relay frequent energization determination method by any other appropriate means (e.g., by means of firmware).

[0088] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0090] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0091] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, voice input, or tactile input).

[0092] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0093] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0094] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the concept of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for judging whether a relay is frequently engaged, characterized in that: include: Acquire relay state parameters in real time, determine an adjustment factor according to the relay state parameters, and determine a sliding time window according to the adjustment factor; In the sliding time window, determining whether the number of times the relay is engaged is greater than a set threshold, and if so, generating a relay frequent engagement alarm instruction; The relay status parameter includes at least one of relay temperature, relay life, and relay load cut-off times; Determining the adjustment factor according to the relay state parameter includes: Inputting the relay state parameter into an adjustment factor model to obtain the adjustment factor, wherein the adjustment factor model is one of a neural network model, a data fitting model, and an empirical model; Determining the sliding time window according to the adjustment factor includes: If the adjustment factor is greater than the first limit, setting the sliding time window to the sliding time window upper limit; If the adjustment factor is less than the second limit, setting the sliding time window to the sliding time window lower limit; If the adjustment factor is greater than the second limit and less than the first limit, the sliding time window is determined by the sliding time window upper limit, the sliding time window lower limit, the adjustment factor, the first limit, and the second limit.

2. The method for determining if a relay is frequently engaged according to claim 1, wherein: If the adjustment factor is greater than the second limit value and less than the first limit value, the sliding time window is determined by the following formula; In the above formula, M is the sliding time window, M min is the lower limit of the sliding time window, M max is the upper limit of the sliding time window, a is the adjustment factor, f min is the first limit, f max is the second limit, and int represents the rounding function.

3. The method for determining if a relay is frequently engaged as claimed in claim 1, wherein: When the relay is first closed, the sliding time window is enabled, and within the sliding time window, it is determined whether the number of times the relay is closed is greater than a set threshold.

4. The method for determining if a relay is frequently engaged as claimed in claim 1, wherein: The relay control method is used for controlling relays in an electric vehicle battery system.

5. The method for determining if a relay is frequently engaged as claimed in claim 4, wherein: The relay includes one or more of a pre-charge relay, a main positive relay, a main negative relay, a fast charge positive relay, and a slow charge negative relay.

6. A relay frequent energization judgment device, characterized in that: A relay control unit is included, wherein the relay control unit is used to: Acquire relay state parameters in real time, determine an adjustment factor according to the relay state parameters, and determine a sliding time window according to the adjustment factor; In the sliding time window, determining whether the number of times the relay is engaged is greater than a set threshold, and if so, generating a relay frequent engagement alarm instruction; The relay status parameter includes at least one of relay temperature, relay life, and relay load cut-off times; Determining the adjustment factor according to the relay state parameter includes: Inputting the relay state parameter into an adjustment factor model to obtain the adjustment factor; Determining the sliding time window according to the adjustment factor includes: If the adjustment factor is greater than the first limit, setting the sliding time window to the sliding time window upper limit; If the adjustment factor is less than the second limit, setting the sliding time window to the sliding time window lower limit; If the adjustment factor is greater than the second limit and less than the first limit, the sliding time window is determined by the sliding time window upper limit, the sliding time window lower limit, the adjustment factor, the first limit, and the second limit.

7. An electronic device, characterized in that: comprising at least one processor, and a memory communicatively connected to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the relay frequent energization judgment method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the relay frequent energization judgment method according to any one of claims 1 to 5 when executed.

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