A smart vehicle-mounted terminal suitable for special vehicles used in power production

Abstract

This utility model discloses an intelligent vehicle-mounted terminal suitable for special vehicles used in power production, comprising: an interface unit for collecting chassis information, generator set status data, and environmental data of the special vehicle used in power production, and uploading them to a main control unit; a main control unit for fusing the chassis information, generator set status data, and environmental data of the special vehicle used in power production, calculating the special vehicle status index by calling the chassis control algorithm unit and the power generation control algorithm unit, and determining whether the current chassis operating status of the special vehicle used in power production meets the control requirements for synchronous grid connection based on the special vehicle status index, and uploading the status result to the dispatch and command cloud main station through the communication unit; and an AI chip unit for interacting with the main control unit in real time, predicting task types, calculating time costs, scheduling computing resources, and rationally allocating tasks.

Description

Technical Field

[0001] This utility model relates to the field of new power system technology, and more specifically, to an intelligent vehicle-mounted terminal suitable for special vehicles used in power production. Background Technology

[0002] With the rapid development of the social economy and the continuous improvement of people's living standards, users have increasingly higher requirements for power supply reliability. To improve power supply reliability, it is necessary to reduce power outages, and carrying out live-line distribution work is the most direct and effective measure to improve power supply reliability.

[0003] On the other hand, the connection between the new power system and special vehicles for power production is becoming closer. Taking emergency power supply vehicles as an example, they can provide power support in the event of main power failure or emergencies, ensuring the continuous operation of critical facilities and services. The new power system has increasingly higher requirements for intelligence and automation. By being equipped with advanced control systems and monitoring equipment, special vehicles for power production can realize functions such as remote monitoring and automated control, improving the intelligence level of the power system. The two can be interdependent and mutually reinforcing.

[0004] Efficient system design methods for vehicle-mounted terminals enable products to win in market competition. Due to the diversification of user requirements for embedded system performance, the factors to be considered during the design process are also increasing. The design method must not only consider performance factors such as system operating speed, cost, size, and power consumption, but also factors such as system storage capacity, real-time performance, and reliability.

[0005] Existing power production special vehicle terminals have limited and customized functions, mostly designed for specific scenarios, such as vehicle controllers, generator controllers, vehicle location monitoring and communication units, etc. They have poor scalability and cannot meet the functional requirements of various power production vehicles.

[0006] Existing intelligent terminal data fusion control systems lack the rapid response capabilities required for power generation special vehicles, manifesting in insufficient task computation and control capabilities and a lack of multi-task coordination. Current vehicle-mounted terminals often employ a sequential approach to business processing, and computational resources cannot be efficiently allocated or offloaded. A comprehensive optimization control process for tiered and rapid response to power business needs is also lacking. How to combine the performance of dedicated power vehicles with business requirements, and achieve optimal task matching for dedicated power vehicles through intelligent terminal optimization, is a significant challenge.

[0007] Therefore, there is a need for an intelligent vehicle-mounted terminal suitable for special vehicles used in power production. Utility Model Content

[0008] This utility model proposes an intelligent vehicle-mounted terminal suitable for special vehicles used in power production, in order to solve the problem of how to realize an intelligent vehicle-mounted terminal suitable for special vehicles used in power production.

[0009] To address the aforementioned problems, according to one aspect of this utility model, an intelligent vehicle-mounted terminal suitable for special vehicles used in power generation is provided. The intelligent vehicle-mounted terminal includes: a main control unit, an AI chip unit, a chassis control algorithm unit, and a power generation control algorithm unit mounted on a core board platform; and an interface unit and a communication unit mounted on the main control board.

[0010] The interface unit is connected to the main control unit and is used to collect chassis information, generator set status data and environmental data of special vehicles for power production, and upload them to the main control unit.

[0011] The main control unit is used to integrate and process the chassis information, generator set status data and environmental data of the special power production vehicle. It calculates the special power production vehicle status index by calling the chassis control algorithm unit and the power generation control algorithm unit, and determines whether the current chassis operation status of the special power production vehicle meets the control requirements for synchronous grid access based on the special power production vehicle status index. The status result is then uploaded to the dispatch and command cloud main station through the communication unit.

[0012] The AI ​​chip unit is connected to the main control unit and is used to interact with the main control unit in real time to predict task types, calculate time costs, schedule computing resources, and allocate tasks reasonably.

[0013] Preferably, the main control unit is further configured to:

[0014] Receive algorithm update and control commands issued by the scheduling and command cloud master station.

[0015] Preferably, the intelligent vehicle terminal further includes: a power supply unit, a storage unit, and a shared memory unit; wherein,

[0016] The power supply unit is mounted on the main control board and is used to supply power to the core board platform.

[0017] The storage unit is mounted on the core platform board and connected to the main control unit for data interaction with the main control unit.

[0018] The shared memory unit is mounted on the core platform board and connected to the main control unit for data interaction with the main control unit.

[0019] Preferably, the main control unit, storage unit and shared memory unit are internally divided into resources, and the storage resources are divided into free resources, controllable resources and fixed resources. When the controllable resources and fixed resources are fully occupied, the free resources are called.

[0020] Preferably, the proportions of free resources, controllable resources, and fixed resources are 40%, 30%, and 30%, respectively.

[0021] This utility model provides an intelligent vehicle-mounted terminal suitable for special vehicles used in power production, comprising: an interface unit for collecting chassis information, generator set status data, and environmental data of the special vehicle used in power production, and uploading them to a main control unit; a main control unit for fusing the chassis information, generator set status data, and environmental data of the special vehicle used in power production, calculating the special vehicle status index by calling the chassis control algorithm unit and the power generation control algorithm unit, and determining whether the current chassis operating status of the special vehicle used in power production meets the control requirements for synchronous grid connection based on the special vehicle status index, and uploading the status result to the dispatch and command cloud main station through the communication unit; and an AI chip unit connected to the main control unit for real-time interaction with the main control unit, predicting task types, calculating time costs, scheduling computing resources, and rationally allocating tasks. This invention provides board-level basic hardware support for vehicle-mounted terminals; it proposes a core platform computing resource scheduling method, which achieves optimal resource allocation through the interaction between the AI ​​chip and the main control chip, providing computing power for the acquisition and control tasks of the vehicle-mounted terminal; and it proposes a vehicle-mounted terminal control algorithm suitable for special vehicles used in power production, including chassis control and generator control, to achieve the optimal working state of special vehicles used in power production, which helps to promote the rapid development and further application of vehicle-mounted terminals. Attached Figure Description

[0022] The exemplary embodiments of this utility model can be more fully understood by referring to the following figures:

[0023] Figure 1 This is a schematic diagram of the structure of an intelligent vehicle-mounted terminal 100 for special vehicles used in power production, according to an embodiment of the present invention.

[0024] Figure 2 This is an architecture diagram of an intelligent vehicle-mounted terminal suitable for special vehicles used in power production, according to an embodiment of the present utility model.

[0025] Figure 3 This is a schematic diagram illustrating the interaction between the AI ​​chip unit, storage unit, main control unit, and memory unit according to an embodiment of the present invention.

[0026] Figure 4This is a system application diagram according to an embodiment of the present utility model. Detailed Implementation

[0027] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the present invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the present invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0028] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0029] This invention provides board-level basic hardware support for vehicle-mounted terminals of special power production vehicles by constructing a core board platform consisting of a core board and an AI chip module. It proposes a computing resource scheduling method for the core board platform, achieving optimal resource allocation through the interaction between the AI ​​chip and the main control chip, thus providing computing power for the data acquisition and control tasks of the vehicle-mounted terminal. Furthermore, it proposes a vehicle-mounted terminal control algorithm suitable for special power production vehicles, including chassis control and generator control, to achieve the optimal working state of the special power production vehicles.

[0030] Figure 1 This is a structural schematic diagram of an intelligent vehicle-mounted terminal 100 suitable for special vehicles used in power production, according to an embodiment of the present invention. Figure 1 As shown, the intelligent vehicle-mounted terminal for special vehicles used in power production provided by this utility model provides board-level basic hardware support for the vehicle-mounted terminal; it proposes a computing resource scheduling method for the core platform, achieving optimal resource allocation through the interaction between the AI ​​chip and the main control chip, providing computing power for the data acquisition and control tasks of the vehicle-mounted terminal; it proposes a vehicle-mounted terminal control algorithm suitable for special vehicles used in power production, including chassis control and generator control, to achieve the optimal working state of the special vehicles used in power production, which helps to promote the rapid development and further application of the vehicle-mounted terminal. The intelligent vehicle-mounted terminal 100 for special vehicles used in power production provided by this utility model includes: a main control unit 101, an AI chip unit 102, a chassis control algorithm unit 103, and a generator control algorithm unit 104, all mounted on the core board platform, as well as an interface unit 105 and a communication unit 106 mounted on the main control board.

[0031] Preferably, the interface unit 105 is connected to the main control unit and is used to collect chassis information, generator set status data and environmental data of special vehicles for power production, and upload them to the main control unit.

[0032] Preferably, the main control unit 101 is used to fuse the chassis information, generator set status data and environmental data of the special power production vehicle, and calculate the special power production vehicle status index by calling the chassis control algorithm unit 103 and the power generation control algorithm unit 104. Based on the special power production vehicle status index, it determines whether the current chassis operation status of the special power production vehicle meets the control requirements for synchronous grid access, and uploads the status result to the dispatch and command cloud main station through the communication unit 106.

[0033] Preferably, the AI ​​chip unit 102 is connected to the main control unit and is used to interact with the main control unit in real time to predict task types, calculate time costs, schedule computing resources, and allocate tasks reasonably.

[0034] Preferably, the main control unit 101 is further configured to:

[0035] Receive algorithm update and control commands issued by the scheduling and command cloud master station.

[0036] Preferably, the intelligent vehicle terminal further includes: a power supply unit, a storage unit, and a shared memory unit; wherein,

[0037] The power supply unit is mounted on the main control board and is used to supply power to the core board platform.

[0038] The storage unit is mounted on the core platform board and connected to the main control unit for data interaction with the main control unit.

[0039] The shared memory unit is mounted on the core platform board and connected to the main control unit for data interaction with the main control unit.

[0040] Combination Figure 2 As shown, the vehicle-mounted intelligent terminal hardware system of this utility model mainly includes a core board platform and a main control board. The core board platform is equipped with a main control unit, a shared memory unit, a storage unit, an AI chip unit, a chassis control algorithm unit, and a power generation control algorithm unit. The main control board is equipped with an interface unit, a communication unit, and a power supply unit. The main control unit includes a kernel scheduling unit and multiple kernels.

[0041] The interface unit collects chassis information of special power production vehicles, generator set status data of special power production vehicles, and environmental data, and uploads them to the main control unit.

[0042] The main control unit integrates and processes the collected data, and calculates the status index of the special power production vehicle by calling the chassis control algorithm unit and the power generation control algorithm unit. This determines the current operating status of the special power production vehicle chassis and whether it meets the control requirements for synchronous grid connection. The status results are then uploaded to the dispatch and command cloud main station through the communication interface, while the system also receives algorithm updates and control commands from the cloud main station.

[0043] Through real-time interaction between the AI ​​chip unit and the main control unit, the AI ​​chip predicts the type of task and calculates the time cost, and schedules computing resources and allocates tasks reasonably.

[0044] Preferably, the main control unit, storage unit and shared memory unit are internally divided into resources, and the storage resources are divided into free resources, controllable resources and fixed resources. When the controllable resources and fixed resources are fully occupied, the free resources are called.

[0045] Preferably, the proportions of free resources, controllable resources, and fixed resources are 40%, 30%, and 30%, respectively.

[0046] In this invention, to achieve rapid task-resource mapping and respond to the computing resource demands of different services, a computing resource allocation method is proposed. First, internal resource allocation is performed, with main control and storage resources divided into free resources, controllable resources, and fixed resources. When controllable and fixed resources are fully occupied, free resources are utilized.

[0047] 1) Free resources, which can be mapped to any business; 2) Controllable resources, which can be converted between free resources and fixed resources; 3) Fixed resources, which are used only for specific businesses and require rapid response to the highest priority businesses, such as protection and control businesses.

[0048] The percentage thresholds for the other three types of resources can be dynamically adjusted. Ideally, free resources should account for 40%, while controllable and fixed resources should each account for 30%. This achieves a balance between resource utilization and high-priority business operations.

[0049] Preferably, the main control unit includes multiple kernels, and for any kernel i, the average utilization rate of resource j is:

[0050]

[0051] C ij =Zc(E ij ),

[0052] S ij =Zz(E ij )+Zk(E ij)+Zg(E ij ),

[0053] in, R represents the average utilization rate of resource j; i j Let be the utilization rate of resource type j in kernel i; N be the number of kernels on the platform, i∈N; M be the total number of resource types, j∈M, including but not limited to processors, memory, storage, and communication bandwidth; C ij The minimum resources required to perform business operations; Zc(E ij S represents the minimum resources required to perform business operations. ij Physical resources provided for kernel i; Zz(E ij Zk(E) represents free resources; ij Zg(E) is a controllable resource; ij ) is a fixed resource.

[0054] Preferably, the AI ​​chip unit, based on the prediction of task types and the calculation of time costs, uses an iterative optimization algorithm to convert the system's resource allocation into resource utilization R. j avg With task execution time th ki The optimal solution is:

[0055]

[0056] Because smart terminals are limited by various resources, such as processors, memory, and storage, mapping may fail due to insufficient resources, thus reducing the efficiency of the algorithm. Therefore, this invention proposes a mapping algorithm based on resource utilization to ensure the remaining amount of controllable and fixed resources, thereby improving the mapping success rate.

[0057] Evaluating the free, controllable, and fixed resources in kernel i, physical resources can be provided: S ij =Zz(E ij )+Zk(E ij )+Zg(E ij ),

[0058] The minimum resource required to execute the business is: C ij =Zc(E ij ),

[0059] The utilization rate R in kernel i corresponds to resource type j. i j Represents: R i j =C ij / S ij ,

[0060] The average utilization rate of resource j on the platform is calculated as follows:

[0061] Where N is the number of cores on the platform, i∈N. M is the total number of resource types, j∈M, including but not limited to processors, memory, storage, communication bandwidth, etc.

[0062] Combination Figure 3 As shown, the utilization rate of free resources, controllable resources, and fixed resources in kernel i determines the execution time of each task. After all services are mapped to a resource group, the partitioning result can be evaluated. The algorithm ends when the partitioning result achieves a good balance in terms of execution speed and power consumption; otherwise, the algorithm continues to generate a new partition and evaluate it again. The runtime overhead of all tasks on the platform is expressed as:

[0063]

[0064] The total cost is expressed as:

[0065] Among them, th ki This represents the time cost of task k running within the core i, where k ∈ K and K is the number of tasks.

[0066] By using AI chips to predict task types and calculate time costs, the system's resource allocation can be transformed into resource utilization R through iterative optimization algorithms. j avg With task execution time th ki The optimal solution is:

[0067]

[0068] Among them, R j avg阈值 th is the threshold for the allowed utilization of resource type j. k阈值 The maximum execution time for task k.

[0069] Among them, iterative optimization algorithms that can be used for traversal include loop traversal, deductive traversal, and recursive traversal.

[0070] Preferably, the main control unit determines whether the current chassis operating status of the special power production vehicle meets the control requirements for synchronous grid connection based on the power production special vehicle status index, including:

[0071]

[0072] D=(a1*D1+a2*D2+a3*D3+a4*D4),

[0073] F=(b1*F1+b2*F2+b3*F3+b4*F4+b5*F5+b6*F6+b7*F7+b8*F8+b9*F9),

[0074] H=(c1*H1+c2*H2+c3*H3+c4*H4),

[0075] a+b+c=1,

[0076] a1+a2+a3+a4=1,

[0077] b1 + b2 + ... + b9 = 1,

[0078] c1 + c2 + c3 + c4 = 1,

[0079] Among them, Z 综合 Z is the condition index for special vehicles used in power production. 综合 ∈(0-1) represents whether the special vehicle for power production is suitable for the current scenario task; the collected chassis information includes: engine oil temperature D1, oil level D2, vehicle speed D3, fault code D4; generator set status data includes: voltage F1, current F2, power F3, frequency F4, power generation F5, circuit breaker open / close position F6, engine oil pressure F7, coolant temperature F8, working time F9; environmental data includes: temperature and humidity H1, smoke detector H2, noise sensor H3; z 阈值 The minimum index is set; a, b, and c are weighting coefficients; oil level D2, fault code D4, oil pressure F7, and coolant temperature F8 are selected as core parameters. When any one of them fails to meet the requirements, the comprehensive index Z is reduced. 综合 =0, indicating that the special vehicle for power production does not meet the business requirements and does not meet the control requirements for synchronous grid connection.

[0080] This utility model collects chassis information of special power production vehicles via the CAN bus of the interface unit, acquires generator set status data via RS-485, and collects environmental data via sensors. The chassis information includes engine oil temperature D1, oil level D2, vehicle speed D3, and fault code D4; the generator set status data includes voltage F1, current F2, power F3, frequency F4, power generation F5, circuit breaker open / close position F6, oil pressure F7, coolant temperature F8, and operating time F9; the environmental data includes temperature and humidity H1, smoke detection H2, and noise sensor H3. Based on the above data, a comprehensive index is calculated as follows:

[0081]

[0082] in,

[0083] D=(a1*D1+a2*D2+a3*D3+a4*D4),

[0084] F=(b1*F1+b2*F2+b3*F3+b4*F4+b5*F5+b6*F6+b7*F7+b8*F8+b9*F9),

[0085] H=(c1*H1+c2*H2+c3*H3+c4*H4),

[0086] a+b+c=1,

[0087] a1+a2+a3+a4=1,

[0088] b1 + b2 + ... + b9 = 1,

[0089] c1 + c2 + c3 + c4 = 1,

[0090] Among them, Z 综合 Z represents the comprehensive index of all collected data. 综合 ∈(0-1) represents whether the special vehicle for power production is suitable for the current scenario and task, z 阈值 The minimum index is set, preferably 0.8. The weighting coefficients are adjusted by the dispatching and command platform based on the application scenario. Preferably, during the vehicle dispatching phase, a = 0.4, b = 0.4, c = 0.2. During the power generation phase, a = 0.2, b = 0.7, c = 0.1. This patent selects oil level D2, fault code D4, oil pressure F7, and coolant temperature F8 as core parameters. When any one of these parameters fails to meet the requirements, the comprehensive index Z... 综合 =0, the special vehicle for power production does not meet the business requirements.

[0091] In this utility model, the core board platform can be used to develop and apply an on-board Internet of Things terminal (hereinafter referred to as: terminal) for electric special vehicles. Through the systematic transformation of the power supply vehicle, information perception and decision support for special vehicles such as power supply vehicles and bucket trucks can be realized.

[0092] (I) Upgrading of Terminals and Supporting Equipment

[0093] like Figure 4 As shown, the vehicle is equipped with an onboard IoT terminal, cameras, and intelligent sensors for smoke, temperature, humidity, and noise monitoring. The terminal collects information from these devices, as well as information from the generator set controller and chassis, to achieve comprehensive perception of vehicle operation information.

[0094] (II) Data Application and Main Site Interaction

[0095] The terminal interacts and communicates with cameras, intelligent sensors, vehicle chassis, generator sets / grid controllers, etc., and can comprehensively analyze and judge the electrical data information of the vehicle generator set, the generator set and grid status information, vehicle chassis information, and the operating environment status of the generator set and vehicle.

[0096] 1. Generator set condition monitoring and operation optimization

[0097] Performance Evaluation and Optimization: The on-board terminal system analyzes data such as the generator set's output voltage, frequency, and power to assess whether it remains stable within the specified range. If voltage fluctuations or frequency deviations are detected, it can issue adjustment suggestions for parameters such as engine speed and excitation system to the generator set controller to optimize power generation performance and ensure stable power supply.

[0098] Fault prediction and diagnosis: The on-board terminal system can monitor the generator set's operating status parameters, such as oil temperature, water temperature, oil pressure, and vibration. By analyzing the trends in these data, and using fault diagnosis models, potential faults can be predicted in advance, allowing for timely maintenance and reducing downtime.

[0099] Fuel consumption analysis and management: The on-board terminal system analyzes the fuel consumption characteristics under different operating conditions by statistically analyzing the fuel consumption data of the generator set and combining it with the load conditions. It works in conjunction with the generator set controller to optimize load distribution, adjust the operating mode, etc., thereby reducing fuel consumption, improving fuel utilization, and extending the continuous power supply time of the power vehicle.

[0100] Load matching analysis: The on-board terminal system analyzes the matching degree between the load and the generator set based on the generator set's rated power and actual output power data, as well as the power demand of the load. This avoids overload or underload operation, rationally allocates the load, and fully utilizes the generator set's power supply capacity.

[0101] The terminal uploads the collected information and locally calculated and analyzed information to the main station system via 4G / 5G, enabling transparent management and digital decision-making for special vehicle operations and improving emergency supply capabilities.

[0102] The present invention has been described with reference to a few embodiments. However, it will be known to those skilled in the art that other embodiments besides those disclosed above fall equivalently within the scope of the present invention.

[0103] Generally, all terms used in this invention are interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0104] Those skilled in the art will understand that embodiments of this invention can be provided as methods, systems, or computer program products. Therefore, this invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0106] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of this utility model and not to limit it. Although the utility model has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this utility model. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this utility model should be covered within the protection scope of this utility model.

Claims

1. An intelligent vehicle-mounted terminal suitable for special vehicles used in power generation, characterized in that, The intelligent vehicle terminal includes: a main control unit, an AI chip unit, a chassis control algorithm unit, and a power generation control algorithm unit mounted on a core board platform, as well as an interface unit and a communication unit mounted on the main control board; wherein, The interface unit is connected to the main control unit and is used to collect chassis information, generator set status data and environmental data of special vehicles for power production, and upload them to the main control unit. The main control unit is used to integrate and process the chassis information, generator set status data and environmental data of the special power production vehicle. It calculates the special power production vehicle status index by calling the chassis control algorithm unit and the power generation control algorithm unit, and determines whether the current chassis operation status of the special power production vehicle meets the control requirements for synchronous grid access based on the special power production vehicle status index. The status result is then uploaded to the dispatch and command cloud main station through the communication unit. The AI ​​chip unit is connected to the main control unit and is used to interact with the main control unit in real time to predict task types, calculate time costs, schedule computing resources, and allocate tasks reasonably.

2. The intelligent vehicle terminal according to claim 1, characterized in that, The main control unit is also used for: Receive algorithm update and control commands issued by the scheduling and command cloud master station.

3. The intelligent vehicle terminal according to claim 1, characterized in that, The intelligent vehicle terminal further includes: a power supply unit, a storage unit, and a shared memory unit; wherein, The power supply unit is mounted on the main control board and is used to supply power to the core board platform. The storage unit is located on the core board platform and connected to the main control unit for data interaction with the main control unit. The shared memory unit is located on the core board platform and connected to the main control unit for data interaction with the main control unit.

4. The intelligent vehicle terminal according to claim 3, characterized in that, The main control unit, storage unit and shared memory unit are internally divided into resources. The storage resources are divided into free resources, controllable resources and fixed resources. When the controllable resources and fixed resources are fully occupied, the free resources are called.

5. The intelligent vehicle terminal according to claim 4, characterized in that, The proportions of free resources, controllable resources, and fixed resources are 40%, 30%, and 30%, respectively.

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