Electric bus blast pump system fault detection method, electronic equipment and medium

Abstract

The invention provides an electric bus blast pump system fault detection method, electronic equipment and a medium, electric bus blast pump operation data and the fault detection method are stored based on a cloud platform, and according to the air pressure state of an air cylinder, fault detection is carried out on a blast pump motor, the air cylinder and a dryer at the same time; according to the method, computing resources of a whole vehicle controller are not occupied, centralized fault detection of the inflation pumps of the multiple electric buses can be achieved at the same time through the cloud platform, regular troubleshooting can be conducted on inflation pump systems of the electric buses, the method is simple, universality is high, and driving safety and stability are improved.

Description

Technical Field

[0001] The invention belongs to the field of air pump systems, and in particular relates to a fault detection method, electronic equipment and medium for an air pump system of an electric bus. Background Art

[0002] The air pump system of pure electric buses is the power supply component for vehicle braking and door opening. The normal operation of the air pump system is of great significance to the normal operation of door opening and closing and vehicle braking. The existing air pump system fault reporting relies on the decision of the vehicle VCU (vehicle control unit) and mainly focuses on the air pump motor fault monitoring. Failures of other components in the air pump system often need to directly or indirectly affect vehicle control to be discovered, resulting in problems that affect driving safety and stable operation.

[0003] Patent application CN11807549A discloses a method for detecting air leakage in the air circuit of a pure electric bus, which collects and records the operating parameters of the air pump system through the vehicle controller to perform air pump leakage fault detection; its air pump leakage fault detection based on the vehicle controller will occupy the computing resources of the vehicle controller, and can only detect the air pump leakage fault of this vehicle, and has poor versatility. Summary of the invention

[0004] The purpose of the present invention is to address the deficiencies in the prior art and to provide an electric bus air pump system fault detection method, electronic equipment and medium, which can realize centralized detection of air pump system faults of multiple electric buses and has strong versatility.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for detecting faults in an air pump system of an electric bus includes the following implementation processes:

[0007] The operation data of the electric buses are sent to a cloud platform in real time, and the cloud platform stores the real-time operation data of all the electric buses in operation;

[0008] Set the number of electric buses to be tested n, n ≥ 1;

[0009] Extracting the air pump system operation data of n electric buses to be tested, wherein the air pump system operation data includes the air pump motor state and the air tank pressure, to form a test sample;

[0010] Based on the detection sample, the air pump system fault detection of n electric buses to be detected is performed on the cloud platform:

[0011] After receiving the air pump shutdown command, if the air tank pressure does not rise, it is determined that the air pump motor is faulty;

[0012] If the air pressure in the air reservoir rises, but the air pressure in the air reservoir is lower than the first threshold or the time taken for the air pressure in the air reservoir to rise to the first threshold is greater than the second threshold, it is determined that the air reservoir has a gas leakage fault;

[0013] If the air pressure in the air cylinder is higher than the first threshold, and after the air cylinder is unloaded, the air pressure in the air cylinder is still higher than the first threshold, or the time for the air pressure in the air cylinder to drop to the first threshold is greater than the third threshold, it is determined that the dryer is faulty.

[0014] The present invention saves the electric bus air pump operation data and fault detection method based on a cloud platform, and simultaneously performs fault detection of the air pump motor, the air cylinder and the dryer according to the air pressure state of the air cylinder; the present invention does not occupy the computing resources of the whole vehicle controller, and can realize centralized fault detection of multiple electric bus air pumps at the same time through the cloud platform, and can regularly check the air pump system of the electric bus; the method is simple, has strong versatility, and improves driving safety and stability.

[0015] Furthermore, the first threshold is a pump shutdown threshold. Preferably, the first threshold is 1050 kPa.

[0016] Preferably, the second threshold is 4 minutes.

[0017] Preferably, the third threshold is 8s.

[0018] Based on the same inventive concept, the present invention also provides an electronic device, including:

[0019] one or more processors;

[0020] A memory having one or more programs stored thereon, which, when executed by the one or more processors, enables the one or more processors to implement the steps of fault detection of the air pump system of an electric bus.

[0021] Based on the same inventive concept, the present invention also provides a computer-readable storage medium storing a computer program, which implements the steps of fault detection of an electric bus air pump system when executed by a processor.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention saves and extracts the operating data of multiple electric bus air pumps based on a cloud platform, and simultaneously performs fault detection of the air pump motor, air tank and dryer according to the air pressure state of the air tank; the present invention does not occupy the computing resources of the whole vehicle controller, and can simultaneously realize centralized fault detection of multiple electric bus air pumps through the cloud platform, and can regularly check the air pump system of the electric bus; the method is simple, has strong versatility, and improves driving safety and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the fault detection method of the electric bus air pump system of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be described in detail below in conjunction with the embodiments. It should be noted that the embodiments and features of the embodiments of the present invention can be combined with each other without conflict. For the convenience of description, if the words "upper", "lower", "left" and "right" appear in the following, they only indicate that the upper, lower, left and right directions are consistent with the drawings themselves, and do not limit the structure.

[0026] Example

[0027] This embodiment provides a method for batch fault detection of on-board air pumps suitable for electric buses. First, based on the vehicle operation big data uploaded from the on-board T-BOX to the cloud platform database, the relevant status data of the air pump system and the vehicle status data are extracted to form a detection sample; the detection sample includes the vehicle driving status, air pump motor status, air tank pressure, dryer status, air pump fan status, etc.; secondly, an air pump fault detection model is established based on the working mechanism of the air pump system to detect whether there is a fault in the vehicle air pump system components; finally, by deploying the model on the cloud platform, accessing the relevant status quantities of the air pump system in the vehicle operation big data database to form a batch of detection samples, and inputting the detection samples into the detection model, the vehicle air pump fault batch detection is realized.

[0028] The technical solution for batch detection of electric bus air pump failures based on vehicle big data is as follows:

[0029] 1. Extraction of test samples: Relying on the VCU (vehicle control unit) to monitor the message feedback of the vehicle's CAN network uplink vehicle operation data, the driving data is sent remotely to the cloud platform in real time through the on-board T-BOX (vehicle communication terminal system). The cloud platform database stores the operation data of all vehicles; the air pump system operation data of the vehicle to be tested is obtained from the cloud platform database. The data includes vehicle driving status, air pump motor status, air tank pressure, dryer status, air pump fan status, etc., to form a diagnostic sample as the data basis for air pump system fault detection.

[0030] 2. Detection model establishment: The establishment of the pump system fault detection mechanism model is based on the pump system component composition and software control logic. The pump system components mainly include the pump motor, air tank, dryer, etc. The software control logic defines the functional relationship between the components. The principle flow chart of the batch detection of the pump system fault is as follows: Figure 1 As shown; a detection mechanism is formed by combining the composition of the air pump system components and the software control logic, and a detection model is established according to the state changes of the air pump system components and their action relationship mechanism.

[0031] 3. Model detection: The detection samples are input into the detection model, and the model analyzes and outputs the detection results. The detection results include two parts: normal system and abnormal system. For vehicles judged to be abnormal, the names of abnormal parts are output.

[0032] 4. Batch testing: Deploy the detection model on the cloud platform to meet the needs of large-scale on-demand testing.

[0033] The purpose of the batch detection model method of the air pump system fault is to conduct centralized fault detection on a large number of vehicles. The detection model based on the air pump system mechanism and control logic takes into account the interaction mode and effect between the air pump system components, and organizes the process into a detection method. The fault location logic of the air pump system components is as follows:

[0034] Air pump motor failure: The main failure point of the motor is that it does not work. The phenomenon is that after the vehicle sends the air pump stop command, the air tank pressure does not rise.

[0035] Air cylinder failure: The main failure point of the air cylinder is leakage. The phenomenon is that the air pump motor receives the shutdown command, but the air cylinder air pressure is still lower than the air pump motor shutdown threshold or the air pump motor runs for 4 minutes or more at a time. Under normal circumstances, the time for the motor to inflate the air pump to the shutdown threshold is less than 4 minutes. This threshold is used to determine whether the air cylinder has leakage or other faults. The air pump start threshold is 850kpa, and the shutdown threshold is 1050kpa. The air pump start threshold and shutdown threshold are determined through laboratory load tests.

[0036] Dryer failure: The main failure point of the dryer is unloading failure. The phenomenon is that after the VCU sends an unloading command, the air pressure in the air tank does not drop or drops slowly without braking or door switching (the air pressure is not lower than the air pump shutdown threshold within 8 seconds of unloading time). The unloading time is obtained from the unloading experiment.

[0037] The acquisition of test samples and the test model are deployed on the cloud platform at the same time, realizing one-stop model data acquisition, model operation, and conclusion output. On this basis, large-scale on-demand testing can be achieved, that is, the task volume can be set according to needs, and one-time diagnosis can be performed for a batch of vehicles or for all vehicles on the network.

[0038] The method of this embodiment effectively solves the problem that some components of the air pump system do not have the conditions or mechanisms for reporting faults, which threatens driving safety.

[0039] This fault monitoring method is not sensitive to the workload and can achieve regular inspection of the air pump systems of all vehicles in operation.

[0040] This embodiment is based on cloud big data diagnosis technology. The cloud platform is the carrier for monitoring vehicle operation data and stores the real-time operation data of the vehicle. By deploying the air pump system mechanism detection model on the cloud platform, the model is used to call the vehicle operation history data on the cloud to realize system fault detection. The advantages of this method include the following points: first, it does not occupy the computing resources of the vehicle controller; second, it can detect the health status of the air pump system of multiple vehicles at one time and centrally push fault processing; third, this method is not affected by the production age of the vehicle and is universal for air pump fault diagnosis of new and old vehicles.

[0041] Another embodiment of the present invention provides an electronic device, including:

[0042] one or more processors;

[0043] A memory stores one or more programs, and when the one or more programs are executed by one or more processors, the one or more processors implement the steps of fault detection of the electric bus air pump system.

[0044] In some implementations, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0045] In some other implementations, the processor may be a central processing unit (CPU), a digital signal processor (DSP), or other general-purpose processors of various types, which are not limited herein.

[0046] Another embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the steps of fault detection of an electric bus air pump system when the computer program is executed by a processor.

[0047] The contents explained in the above embodiments should be understood as these embodiments are only used to more clearly illustrate the present invention, and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

Claims

1. A method for detecting faults in an electric bus air pump system, characterized in that: The implementation process includes the following: The operation data of the electric buses are sent to a cloud platform in real time, and the cloud platform stores the real-time operation data of all the electric buses in operation; Set the number of electric buses to be tested n, n ≥ 1; Extracting the air pump system operation data of n electric buses to be tested, wherein the air pump system operation data includes the air pump motor state and the air tank pressure, to form a test sample; Based on the detection sample, the air pump system fault detection of n electric buses to be detected is performed on the cloud platform: After receiving the air pump shutdown command, if the air tank pressure does not rise, it is determined that the air pump motor is faulty; If the air pressure in the air reservoir rises, but the air pressure in the air reservoir is lower than the first threshold or the time taken for the air pressure in the air reservoir to rise to the first threshold is greater than the second threshold, it is determined that the air reservoir has a gas leakage fault; If the air pressure in the air cylinder is higher than the first threshold, and after the air cylinder is unloaded, the air pressure in the air cylinder is still higher than the first threshold, or the time for the air pressure in the air cylinder to drop to the first threshold is greater than the third threshold, it is determined that the dryer is faulty.

2. The electric bus air pump system fault detection method according to claim 1, characterized in that: The first threshold is the air pump shutdown threshold.

3. The electric bus air pump system fault detection method according to claim 2, characterized in that: The first threshold is 1050 kpa.

4. The electric bus air pump system fault detection method according to claim 1, characterized in that: The second threshold is 4 minutes.

5. The electric bus air pump system fault detection method according to claim 1, characterized in that: The third threshold is 8s.

6. An electronic device, characterized in that: include: one or more processors; A memory having one or more programs stored thereon, which, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the steps of the method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that: The computer program is stored therein, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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