Whole vehicle load intelligent power distribution method and system based on big data model

Abstract

The invention relates to the technical field of intelligent network connection automobiles, and provides a whole vehicle load intelligent power distribution method and system based on a big data model. An intelligent power distribution module is integrated on a PCB of a ZCU, and real-time data of a whole vehicle power distribution load is acquired through a data acquisition assembly; the real-time data of the whole vehicle power distribution load is preprocessed through a data preprocessing module, the real-time data of the whole vehicle power distribution load and the preprocessed real-time data of the whole vehicle power distribution load are transmitted to a data pool to be stored, and the preprocessed real-time data of the whole vehicle power distribution load is diagnosed in real time through an intelligent power distribution module; and comparing the real-time diagnosis data with power management big data by using a background big data model library AI calculation engine so as to predict the resource state of a whole vehicle power distribution power supply and manage the power supply in real time, so that intelligent power distribution, real-time diagnosis and prediction are performed according to load requirements, and a lean design of process data driven research and development is generated. And the reliability test of research and development is expanded from a laboratory to a full life cycle.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent networked vehicles, and more specifically, to a method and system for intelligent power distribution of vehicle loads based on a big data model. Background Art

[0002] In the context of the great changes in the intelligent connected vehicle industry, the fuse boxes used in traditional vehicles cannot meet the current development needs of automotive power distribution due to bottlenecks such as insufficient diagnostic capabilities, insufficient accuracy of power overcurrent capabilities, and lack of support for software upgrades. The upgrade of vehicle power distribution has become the key to the development of intelligent connected vehicles. In the existing technology, vehicle power distribution is often based on offline power design and large redundancy of load function requirements, and the vehicle power distribution is gradually divided into domains / subsystems, and then the logical modules are divided into physical modules. Starting from the actual functional logic of the vehicle, this solution does not give priority to the precise configuration of hardware resource requirements. Under the centralized electronic and electrical architecture, this allocation method will lead to insufficient or squeezed hardware resources, or waste of hardware resources, and it is impossible to perform real-time online power management diagnosis, and it is impossible to predict working conditions through big data, real-time data combined with artificial intelligence.

[0003] In summary, the existing vehicle power distribution technology has technical problems such as not giving priority to the precise configuration of hardware resource requirements, being unable to perform real-time online power management diagnosis, and being unable to predict operating conditions through big data, real-time data combined with artificial intelligence. Summary of the invention

[0004] The technical problem to be solved by the present invention is that, in view of the shortcomings of the above-mentioned technical solutions, a vehicle load intelligent power distribution method and related equipment based on a big data model are provided to realize intelligent power distribution according to load demand, real-time online diagnosis, working condition prediction, and generate process data to drive the lean design of R&D, so that the reliability testing of R&D can be extended from the laboratory to the entire life cycle.

[0005] In a first aspect, the present invention provides a vehicle load intelligent power distribution method based on a big data model, comprising the following steps:

[0006] An intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series to the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which connects the power distribution of the vehicle and the load;

[0007] Configure a data acquisition component and a data preprocessing module, collect real-time data of the vehicle power distribution load through the data acquisition component, and preprocess the real-time data of the vehicle power distribution load through the data preprocessing module;

[0008] The real-time data of the vehicle power distribution load collected by the data collection component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage;

[0009] The intelligent power distribution module performs real-time diagnosis on the pre-processed real-time data of the vehicle power distribution load, and uploads the real-time diagnostic data to the background. The background big data model library AI computing engine is used to compare the real-time diagnostic data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0010] Furthermore, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overcurrent data of the vehicle's power distribution load, and the real-time overcurrent data of the vehicle's power distribution load is preprocessed by the data preprocessing module.

[0011] Furthermore, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the collected real-time overcurrent data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overcurrent data of the vehicle power distribution load to the data pool for storage.

[0012] Furthermore, the intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, including: the intelligent power distribution module performs real-time diagnosis on the real-time overcurrent data of the vehicle power distribution load after preprocessing, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0013] Furthermore, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overvoltage data of the vehicle's power distribution load, and the real-time overvoltage data of the vehicle's power distribution load is preprocessed by the data preprocessing module.

[0014] Furthermore, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the collected real-time overvoltage data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overvoltage data of the vehicle power distribution load to the data pool for storage.

[0015] Furthermore, the intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, including: the intelligent power distribution module performs real-time diagnosis on the real-time overvoltage data of the vehicle power distribution load after preprocessing, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0016] Furthermore, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time low-voltage data of the vehicle's power distribution load, and the real-time low-voltage data of the vehicle's power distribution load is preprocessed by the data preprocessing module.

[0017] Furthermore, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the collected real-time low-voltage data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time low-voltage data of the vehicle power distribution load to the data pool for storage.

[0018] In a second aspect, the present invention provides a vehicle load intelligent power distribution system based on a big data model, comprising:

[0019] A data acquisition component is connected to the vehicle power distribution load for communication, and the data acquisition component is used to collect real-time data of the vehicle power distribution load;

[0020] A data preprocessing module, which is in communication with the data acquisition component and is used to preprocess the real-time data of the vehicle power distribution load collected by the data acquisition component;

[0021] A data pool, which is in communication with the data acquisition component and the data preprocessing module, and is used to obtain the real-time data of the vehicle power distribution load collected by the data acquisition component and the preprocessed real-time data of the vehicle power distribution load for storage;

[0022] The intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which connects the power distribution and load of the vehicle. The intelligent power distribution module performs real-time diagnosis on the pre-processed real-time data of the power distribution load of the vehicle, and uploads the real-time diagnosis data to the background;

[0023] The background runs the big data model library AI computing engine to compare the real-time diagnostic data with the power management big data to predict the resource status of the vehicle's power distribution power supply and manage the power supply in real time.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The vehicle load intelligent power distribution method and system based on the big data model provided by the present invention integrates an intelligent power distribution module on the PCB board of the ZCU, and the intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle, and the main power supply circuit includes multiple power supply lines, each of which is connected to the vehicle power distribution and load, and a data acquisition component and a data preprocessing module are configured. The real-time data of the vehicle power distribution load is collected by the data acquisition component, and the real-time data of the vehicle power distribution load is preprocessed by the data preprocessing module. The real-time data of the vehicle power distribution load collected by the data acquisition component and the preprocessing module are The real-time data of the vehicle power distribution load is transmitted to the data pool for storage, the real-time data of the vehicle power distribution load after preprocessing is diagnosed in real time through the intelligent power distribution module, and the real-time diagnosis data is uploaded to the background, and the real-time diagnosis data is compared with the power management big data using the background big data model library AI computing engine to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, thereby realizing intelligent power distribution according to load demand, real-time online diagnosis, working condition prediction, generating process data-driven R&D lean design, and extending the reliability test of R&D from the laboratory to the entire life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of the vehicle load intelligent power distribution method based on the big data model of the present invention;

[0027] Figure 2 It is a schematic diagram of the architecture of the vehicle load intelligent power distribution system based on the big data model of the present invention;

[0028] Figure 3It is a schematic diagram of the architecture of the vehicle end of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein.

[0031] Embodiment 1

[0032] See also Figure 1-Figure 3 Embodiment 1 provides a vehicle load intelligent power distribution method based on a big data model. The vehicle load intelligent power distribution method based on a big data model includes steps S1, S2, S3 and S4. An intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series to the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which is connected to the vehicle power distribution and the load. A data acquisition component and a data preprocessing module are configured. The real-time data of the vehicle power distribution load is collected by the data acquisition component, and the real-time data of the vehicle power distribution load is preprocessed by the data preprocessing module. The data acquisition component is used to collect the real-time data of the vehicle power distribution load. The real-time data of the vehicle power distribution load collected by the integrated component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, the pre-processed real-time data of the vehicle power distribution load is diagnosed in real time through the intelligent power distribution module, and the real-time diagnosis data is uploaded to the background, and the real-time diagnosis data is compared with the power management big data using the background big data model library AI computing engine to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, thereby realizing intelligent power distribution according to load demand, real-time online diagnosis, working condition prediction, generating process data to drive the lean design of R&D, and extending the reliability testing of R&D from the laboratory to the entire life cycle.

[0033] It should be noted that the vehicle load intelligent power distribution method based on the big data model provided in this embodiment can be run on the vehicle end. The vehicle end is the execution subject of all or part of the steps in the vehicle load intelligent power distribution method based on the big data model. In addition to executing steps S1, S2, S3 and S4 in this embodiment, it can also run some or all of the steps of the method involved below. It should be noted that the vehicle end includes a memory, a processor, and a network interface that communicate with each other through a system bus. It should be pointed out that only some components of the vehicle end are shown in the figure, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the vehicle end here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc. The vehicle end can interact with the user through a touch panel or voice control device. The memory includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory can be an internal storage unit of the vehicle end, such as a hard disk or memory of the vehicle end. In other embodiments, the memory can also be an external storage device of the vehicle end, such as a plug-in hard disk equipped on the vehicle end, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory can also include both the internal storage unit of the vehicle end and its external storage device.

[0034] Specifically in step S1, the vehicle end integrates an intelligent power distribution module on the PCB board of the ZCU, and the intelligent power distribution module is used to be connected in series to the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, and each power supply line connects the vehicle power distribution and the load.

[0035] It should be noted that smart power distribution refers to an integrated circuit that protects the power supply circuit by integrating MOSFET, drive, detection circuit, logic circuit and diagnosis modules on a single chip. When the smart power distribution module is connected in series to the main power supply circuit, it can detect overcurrent, overvoltage and other conditions and respond quickly to them.

[0036] It should also be noted that in the prior art, at least one distribution box is usually provided in the front cabin and the passenger cabin, which occupies too much cabin space. In this embodiment, the intelligent distribution module is integrated on the PCB board, which can save cabin space compared to the distribution box solution in the prior art.

[0037] It should also be noted that in the prior art, the power supply circuit protection mainly adopts the fuse solution, and the fuse protects the power circuit of the whole vehicle by irreversible self-destruction. In this embodiment, the intelligent power distribution has the ability of self-recovery, which means that the probability of intelligent power distribution being damaged by circuit abnormalities such as overvoltage, overcurrent, and low voltage is extremely small. Regardless of the failure of the chip itself, the intelligent power distribution can almost be used until the vehicle is scrapped, thereby reducing the maintenance cost of the whole vehicle life cycle and providing a better user experience.

[0038] It should also be noted that, in this embodiment, since the intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle, the main power supply circuit includes multiple power supply lines, so by detecting and diagnosing each power supply line, faults can be discovered early and the probability of major faults can be reduced. In addition, the intelligent power distribution module can flexibly adjust the functional logic through online upgrades and repair bugs in a timely manner.

[0039] Specifically in step S2, the vehicle side is configured with a data acquisition component and a data preprocessing module, the real-time data of the vehicle power distribution load is collected by the data acquisition component, and the real-time data of the vehicle power distribution load is preprocessed by the data preprocessing module.

[0040] In some preferred embodiments, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module. It may include: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overcurrent data of the vehicle's power distribution load, and the real-time overcurrent data of the vehicle's power distribution load is preprocessed by the data preprocessing module.

[0041] In some preferred embodiments, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module. It may include: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overvoltage data of the vehicle's power distribution load, and the real-time overvoltage data of the vehicle's power distribution load is preprocessed by the data preprocessing module.

[0042] In some preferred embodiments, a data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected by the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed by the data preprocessing module. It may include: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time low-voltage data of the vehicle's power distribution load, and preprocesses the real-time low-voltage data of the vehicle's power distribution load through the data preprocessing module.

[0043] It should be noted that the data acquisition component can collect CAN data, vehicle Ethernet data, onboard sensor data and other vehicle data. Among them, the CAN, vehicle Ethernet and onboard sensor modules are connected to the data acquisition component in communication, and the data acquisition component is also connected to the data preprocessing module in communication, and the data that needs to be preprocessed collected by the data acquisition component is transmitted to the data preprocessing module for preprocessing by the data preprocessing module.

[0044] Specifically in step S3, the vehicle end transmits the real-time data of the vehicle power distribution load collected by the data collection component and the pre-processed real-time data of the vehicle power distribution load to the data pool for storage.

[0045] In some preferred embodiments, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, which may include: the data acquisition component transmits the collected real-time overcurrent data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overcurrent data of the vehicle power distribution load to the data pool for storage.

[0046] In some preferred embodiments, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, which may include: the data acquisition component transmits the collected real-time overvoltage data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overvoltage data of the vehicle power distribution load to the data pool for storage.

[0047] In some preferred embodiments, the real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, which may include: the data acquisition component transmits the collected real-time low-voltage data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time low-voltage data of the vehicle power distribution load to the data pool for storage.

[0048] It should be noted that the vehicle side transmits the real-time data of the vehicle's power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle's power distribution load to the data pool for storage, and can transmit the data generated in the intelligent power distribution process to the R&D side to drive the lean design of R&D and expand the reliability testing of R&D from the laboratory to the entire life cycle.

[0049] It should also be noted that the data stored in the data pool can be transmitted to the TCU end through a network connection channel, and the TCU end is then transmitted to the backend through a mobile network. Among them, the network connection channel may include USB, ETH, etc.

[0050] In some other preferred embodiments, the preprocessed real-time data of the vehicle power distribution load is transmitted to a mobile smart terminal, so that the user can view and process the real-time data of the vehicle power distribution load and the preprocessed real-time data of the vehicle power distribution load through the mobile smart terminal.

[0051] Specifically in step S4, the vehicle side performs real-time diagnosis on the pre-processed real-time data of the vehicle power distribution load through the intelligent power distribution module, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0052] In some preferred embodiments, the intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time. It may include: the intelligent power distribution module performs real-time diagnosis on the real-time overcurrent data of the vehicle power distribution load after preprocessing, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0053] In some preferred embodiments, the intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time. It may include: the intelligent power distribution module performs real-time diagnosis on the real-time overvoltage data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

[0054] In some improved embodiments, the real-time diagnostic data is compared with the power management big data using the background big data model library AI computing engine to predict the resource status of the vehicle power distribution power supply, which includes: sending the predicted resource status of the vehicle power distribution power supply to a large monitoring screen, and the user monitors the power supply in real time through the large monitoring screen, realizing power status prediction and real-time power management, and meeting the growing demand for reliability and functional safety of smart car power distribution.

[0055] In some improved embodiments, when an overload occurs, the vehicle end will limit the output current to a user-defined safety value; if the abnormal overload condition persists, the vehicle end will enter a disconnection state to disconnect the load from the power supply, meeting the growing demand for reliability and functional safety of smart vehicle power distribution.

[0056] Embodiment 2

[0057] See also Figure 1-Figure 3 This embodiment provides a vehicle load intelligent power distribution system based on a big data model, including:

[0058] A data acquisition component is connected to the vehicle power distribution load for communication, and the data acquisition component is used to collect real-time data of the vehicle power distribution load;

[0059] A data preprocessing module, which is in communication with the data acquisition component and is used to preprocess the real-time data of the vehicle power distribution load collected by the data acquisition component;

[0060] A data pool, which is in communication with the data acquisition component and the data preprocessing module, and is used to obtain the real-time data of the vehicle power distribution load collected by the data acquisition component and the preprocessed real-time data of the vehicle power distribution load for storage;

[0061] The intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which connects the power distribution and load of the vehicle. The intelligent power distribution module performs real-time diagnosis on the pre-processed real-time data of the power distribution load of the vehicle, and uploads the real-time diagnosis data to the background;

[0062] The background runs the big data model library AI computing engine to compare the real-time diagnostic data with the power management big data to predict the resource status of the vehicle's power distribution power supply and manage the power supply in real time.

[0063] It should be noted that the vehicle load intelligent power distribution system based on the big data model provided in this embodiment integrates an intelligent power distribution module on the PCB board of the ZCU, and the intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle, and the main power supply circuit includes multiple power supply lines, each of which is connected to the vehicle power distribution and load, and a data acquisition component and a data preprocessing module are configured. The real-time data of the vehicle power distribution load is collected by the data acquisition component, and the real-time data of the vehicle power distribution load is preprocessed by the data preprocessing module, and the real-time data of the vehicle power distribution load collected by the data acquisition component and the data preprocessing module are preprocessed. The pre-processed real-time data of the vehicle power distribution load is transmitted to the data pool for storage. The pre-processed real-time data of the vehicle power distribution load is diagnosed in real time through the intelligent power distribution module, and the real-time diagnosis data is uploaded to the background. The real-time diagnosis data is compared with the power management big data using the background big data model library AI computing engine to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, thereby realizing intelligent power distribution according to load demand, real-time online diagnosis, working condition prediction, generating process data-driven R&D lean design, and extending the reliability testing of R&D from the laboratory to the entire life cycle.

[0064] It should be pointed out that the above embodiments are only preferred specific implementation modes of the present invention, and the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A vehicle load intelligent power distribution method based on a big data model, characterized in that: The following steps are involved: An intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series to the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which connects the power distribution of the vehicle and the load; Configure a data acquisition component and a data preprocessing module, collect real-time data of the vehicle power distribution load through the data acquisition component, and preprocess the real-time data of the vehicle power distribution load through the data preprocessing module; The real-time data of the vehicle power distribution load collected by the data collection component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage; The intelligent power distribution module performs real-time diagnosis on the pre-processed real-time data of the vehicle power distribution load, and uploads the real-time diagnostic data to the background. The background big data model library AI computing engine is used to compare the real-time diagnostic data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

2. The vehicle load intelligent power distribution method based on the big data model according to claim 1, characterized in that: A data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected through the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed through the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overcurrent data of the vehicle's power distribution load, and the real-time overcurrent data of the vehicle's power distribution load is preprocessed through the data preprocessing module.

3. The vehicle load intelligent power distribution method based on big data model as claimed in claim 2, characterized in that: The real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the collected real-time overcurrent data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overcurrent data of the vehicle power distribution load to the data pool for storage.

4. The vehicle load intelligent power distribution method based on big data model as claimed in claim 3 is characterized in that: The intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, including: the intelligent power distribution module performs real-time diagnosis on the real-time overcurrent data of the vehicle power distribution load after preprocessing, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

5. The vehicle load intelligent power distribution method based on big data model as claimed in claim 1, characterized in that: A data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected through the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed through the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time overvoltage data of the vehicle's power distribution load, and the real-time overvoltage data of the vehicle's power distribution load is preprocessed through the data preprocessing module.

6. The vehicle load intelligent power distribution method based on big data model as claimed in claim 5, characterized in that: The real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the real-time overvoltage data of the vehicle power distribution load collected by it to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time overvoltage data of the vehicle power distribution load to the data pool for storage.

7. The vehicle load intelligent power distribution method based on big data model as claimed in claim 6, characterized in that: The intelligent power distribution module performs real-time diagnosis on the real-time data of the vehicle power distribution load after preprocessing, uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time, including: the intelligent power distribution module performs real-time diagnosis on the real-time overvoltage data of the vehicle power distribution load after preprocessing, and uploads the real-time diagnosis data to the background, and uses the background big data model library AI computing engine to compare the real-time diagnosis data with the power management big data to predict the resource status of the vehicle power distribution power supply and manage the power supply in real time.

8. The vehicle load intelligent power distribution method based on big data model as claimed in claim 1, characterized in that: A data acquisition component and a data preprocessing module are configured, and real-time data of the vehicle's power distribution load is collected through the data acquisition component, and the real-time data of the vehicle's power distribution load is preprocessed through the data preprocessing module, including: configuring a data acquisition component and a data preprocessing module; when the intelligent power distribution module is connected in series to the main power supply circuit, the data acquisition component collects real-time low-voltage data of the vehicle's power distribution load, and the real-time low-voltage data of the vehicle's power distribution load is preprocessed through the data preprocessing module.

9. The vehicle load intelligent power distribution method based on the big data model as claimed in claim 8, characterized in that: The real-time data of the vehicle power distribution load collected by the data acquisition component and the pre-processed real-time data of the vehicle power distribution load are transmitted to the data pool for storage, including: the data acquisition component transmits the collected real-time low-voltage data of the vehicle power distribution load to the data pool for storage, and the data preprocessing module transmits the pre-processed real-time low-voltage data of the vehicle power distribution load to the data pool for storage.

10. A vehicle load intelligent power distribution system based on big data model, characterized in that: include: A data acquisition component is connected to the vehicle power distribution load for communication, and the data acquisition component is used to collect real-time data of the vehicle power distribution load; A data preprocessing module, which is in communication with the data acquisition component and is used to preprocess the real-time data of the vehicle power distribution load collected by the data acquisition component; A data pool, which is in communication with the data acquisition component and the data preprocessing module, and is used to obtain the real-time data of the vehicle power distribution load collected by the data acquisition component and the preprocessed real-time data of the vehicle power distribution load for storage; The intelligent power distribution module is integrated on the PCB board of the ZCU. The intelligent power distribution module is used to be connected in series with the main power supply circuit of the vehicle. The main power supply circuit includes multiple power supply lines, each of which connects the power distribution and load of the vehicle. The intelligent power distribution module performs real-time diagnosis on the pre-processed real-time data of the power distribution load of the vehicle, and uploads the real-time diagnosis data to the background; The background runs the big data model library AI computing engine to compare the real-time diagnostic data with the power management big data to predict the resource status of the vehicle's power distribution power supply and manage the power supply in real time.

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