Electronic and electrical architecture, method for backup of functions, method for adjusting a seat, vehicle

Abstract

The application relates to the technical field of intelligent sports products, and discloses an electronic and electrical architecture, a function backup method, a seat adjustment method and a vehicle. The edge node is connected with the first perception and interaction component in the same distribution area, and the power distribution and data transmission module is connected with the first edge node corresponding to the same power distribution and communication area, so that the components are sequentially associated according to the area and the power distribution and communication, the complexity and length of the wire harness in the whole device are greatly reduced, and the cost is saved. The power distribution and data transmission module is simultaneously connected with the central computing platform and the power component, so that the data interaction between the central computing platform and the perception and interaction component can be completed by relying on the edge node, and power distribution is realized. The problems of component connection confusion and complex data transmission path in the traditional architecture are avoided, data interaction is more efficient, power distribution is more accurate, a foundation is laid for subsequent software reuse, and the cost of repeated development of different AI sports equipment architectures is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent sports products, in particular to an electronic and electrical architecture, a function backup method, a seat adjustment method and a vehicle. BACKGROUND

[0002] Traditional electronic and electrical architectures are solutions proposed for single-type products, such as the electronic and electrical architecture of intelligent electric vehicles, the electronic and electrical architecture of intelligent robots, etc. With the development of intelligent technology, the AI sports product ecosystem is gradually enriched, and traditional automobile enterprises gradually turn into comprehensive technology companies of multiple ecological products. Various products under the support of AI show more rich and intelligent functions, and behind the products is the increasing proportion of software in the value of the product. Previous architecture solutions require repeated design and development of electronic and electrical architectures for each type of AI sports product, which cannot realize high-value software reuse and inevitably leads to a large amount of repeated development investment. SUMMARY

[0003] The present application provides an electronic and electrical architecture, a function backup method, a seat adjustment method and a vehicle to solve the problem in the related art that the electronic and electrical architecture is a solution proposed for single-type products, each type of AI sports product requires repeated design and development of electronic and electrical architectures, resulting in a large amount of repeated development investment.

[0004] In a first aspect, the present application provides an electronic and electrical architecture applied to an artificial intelligence sports device, the electronic and electrical architecture comprising: a central computing platform, a power component, a plurality of power distribution and data transmission modules, a plurality of edge nodes and a plurality of sensing and interaction components, wherein the edge nodes are connected with at least a first sensing and interaction component, and the first sensing and interaction component is a sensing and interaction component in the same distribution area in the device.

[0005] The power distribution and data transmission module is connected with at least a first edge node, and the first edge node is an edge node connected by sensing and interaction components in the same power distribution and communication area in the device.

[0006] The power distribution and data transmission module is further connected with the central computing platform and the power component, respectively, for realizing data interaction between the central computing platform and each sensing and interaction component through the edge nodes, and distributing power in the electronic and electrical architecture.

[0007] The application realizes the ordered association of components according to regions and power distribution and communication, greatly reduces the complexity and length of the wire harness in the entire device, and saves costs. And by connecting the power distribution and data transmission module with the central computing platform and the power component at the same time, it can not only rely on the edge node to complete the data interaction between the central computing platform and the sensing and interaction component, but also realize power distribution. This structure avoids the problems of component connection confusion and complex data transmission path in the traditional architecture, makes data interaction more efficient and power distribution more accurate, also lays a foundation for subsequent software reuse, and reduces the cost of repeated development of different AI sports device architectures.

[0008] In a second aspect, the application provides a function backup method, which is applied to a vehicle adopting the electronic and electrical architecture provided in the first aspect or any of the corresponding embodiments thereof, and the method comprises:

[0009] Based on the driving functions of the vehicle, the software function modules of the vehicle control function software are divided to obtain a plurality of software function modules, and each software function module and its corresponding redundant backup module are respectively deployed in different computing power centers of the central computing platform, wherein the computing power center comprises a main computing power center and at least one secondary computing power center;

[0010] Based on the calling relationship between the software functions contained in each software function module, a software scheduling table is generated, which comprises the deployment address information of the software function module corresponding to the redundant backup module, and a scheduling link for representing the scheduling order between the software functions contained in the software function module, so that each software function module is scheduled and run according to the scheduling link;

[0011] When it is detected that any software function module appears abnormal during operation, the scheduling link is updated based on the software function associated with the abnormality and the deployment address information, to obtain an updated scheduling link;

[0012] The software function module that appears abnormal is controlled to be scheduled and run according to the updated scheduling link.

[0013] The application divides software function modules according to driving functions according to a specific electronic and electrical architecture, and deploys the software function modules and corresponding redundant backup modules in different computing centers of a central computing platform, generates a scheduling link in combination with software function call relations, updates the scheduling link based on functions associated with an exception and deployment addresses of redundant backup modules when an exception occurs, and the software function module that has the exception is scheduled and runs according to the updated scheduling link. The whole vehicle control function redundancy implementation scheme does not need to reprocess data in full, but only needs to dynamically adjust and update the scheduling link, greatly reduces the lag of control command output, and guarantees the continuity of functions in a high-level assisted driving scene; meanwhile, the deployment of different computing centers realizes the dispersed backup of each software function module at the hardware level, cooperates with the dynamic adjustment of the scheduling link, ensures the integrity and reliability of the whole vehicle control function, meets the real-time requirement of high-level assisted driving on the basis of realizing the safety redundancy of the whole vehicle control function, and further guarantees the driving safety of the vehicle.

[0014] In a third aspect, the application provides a seat adjustment method, which is applied to a vehicle adopting the electronic and electrical architecture provided in the first aspect or any of the corresponding embodiments thereof, and the method comprises the following steps.

[0015] Obtaining a current signal of a steering assist motor of the vehicle;

[0016] Extracting feature data related to road roughness from the current signal;

[0017] Classifying the feature data to determine the road type of the current driving road of the vehicle;

[0018] When the road type is an abnormal roughness road, determining the relative position relationship between the abnormal roughness road and the vehicle;

[0019] Based on the relative position relationship, adjusting at least one seat in the vehicle to increase the support force of the seat in the direction of the abnormal roughness road.

[0020] The application obtains a steering assist motor current signal by using a specific electronic and electrical architecture, extracts road roughness related feature data, and classifies and determines the road type, adjusts the seat support force according to the relative position between the abnormal roughness road and the vehicle when the abnormal roughness road is identified, and realizes the linkage adjustment of different control domains of the vehicle. This scheme does not need to rely on steering operation, can actively perceive various rough roads, can also adjust the seat support force in the corresponding direction, effectively alleviates the discomfort of the passenger on one side of the rough road, significantly improves the riding experience and comfort in different road conditions, and improves the driving experience of the user.

[0021] In a fourth aspect, the application provides a vehicle adopting the electronic and electrical architecture provided in the first aspect or any of the corresponding embodiments thereof.

[0022] In some optional embodiments, the vehicle comprises:

[0023] a memory and a processor, which are connected to each other for communication, and the memory stores computer instructions, and the processor executes the computer instructions to perform the method provided in the second aspect or any of the corresponding embodiments thereof, or performs the method provided in the third aspect or any of the corresponding embodiments thereof.

[0024] In a fifth aspect, the present application provides a computer readable storage medium, which stores computer instructions for causing a computer to perform the method provided in the second aspect or any of the corresponding embodiments thereof, or perform the method provided in the third aspect or any of the corresponding embodiments thereof.

[0025] In a sixth aspect, the present application provides a computer program product comprising computer instructions for causing a computer to perform the method provided in the second aspect or any of the corresponding embodiments thereof, or perform the method provided in the third aspect or any of the corresponding embodiments thereof.

[0026] Advantages of the present application:

[0027] The present application connects the edge node with the first perception and interaction component in the same distribution area, and connects the power distribution and data transmission module with the first edge node corresponding to the same power distribution and communication area, thereby realizing the ordered association of components according to areas and power distribution and communication, greatly reducing the complexity and length of the wire harness in the entire device, and saving costs. By simultaneously connecting the central computing platform and the power component through the power distribution and data transmission module, data interaction between the central computing platform and the perception and interaction component can be completed by relying on the edge node, and power distribution can also be realized. This structure avoids the problems of component connection confusion and complex data transmission path in the traditional architecture, makes data interaction more efficient and power distribution more accurate, and also lays a foundation for subsequent software reuse, reducing the cost of repeated development of different AI sports device architectures. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the specific embodiments or prior art of the present application, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0029] Figure 1 is a schematic diagram of an electronic and electrical architecture according to an embodiment of the present application;

[0030] Figure 2 is a schematic diagram of control logic business flow of electronic and electrical architecture of embodiments of the present application;

[0031] Figure 3 is a structural schematic diagram of central computing platform of embodiments of the present application;

[0032] Figure 4 is a structural schematic diagram of electrical & digital hub of embodiments of the present application;

[0033] Figure 5 is a schematic diagram of working principle of data exchange module of embodiments of the present application;

[0034] Figure 6 is a schematic diagram of principle of chip power distribution module of embodiments of the present application;

[0035] Figure 7 is a schematic diagram of principle of data and power distribution coupling module of embodiments of the present application;

[0036] Figure 8 is a structural schematic diagram of edge node of embodiments of the present application;

[0037] Figure 9 is a structural schematic diagram of integration of electrical & digital hub and edge node of embodiments of the present application;

[0038] Figure 10 is a communication network schematic diagram of electronic and electrical architecture of embodiments of the present application;

[0039] Figure 11A is a power supply network schematic diagram of electronic and electrical architecture of embodiments of the present application;

[0040] Figure 11B is a structural schematic diagram of power supply system of electronic and electrical architecture of embodiments of the present application;

[0041] Figure 12 is a first flow schematic diagram of function backup method according to embodiments of the present application;

[0042] Figure 13 is a second flow schematic diagram of function backup method according to embodiments of the present application;

[0043] Figure 14 is a third flow schematic diagram of function backup method according to embodiments of the present application;

[0044] Figure 15 is a first flow schematic diagram of seat adjustment method according to embodiments of the present application;

[0045] Figure 16 is a second flow schematic diagram of seat adjustment method according to embodiments of the present application;

[0046] Figure 17 is a third flowchart of a seat adjustment method according to an embodiment of the present application;

[0047] Figure 18 is a hardware structure diagram of a vehicle according to an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0049] It can be understood that, before using the technical solutions disclosed in the embodiments of the present application, the type, use range, use scenario and the like of the personal information involved in the present application should be informed to the user and the authorization of the user should be obtained according to relevant laws and regulations through appropriate means.

[0050] The terms "first", "second" are only used for descriptive purpose, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "plurality" is two or more than two, unless otherwise specifically limited.

[0051] In addition, it should be noted in the description of the present application that, unless otherwise specifically defined and limited, the terms "mounting", "connecting", "connecting" should be understood in a broad sense, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through intermediate medium, or the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0052] The electronic and electrical architecture in the related art is a solution for a single type of product. Each type of AI motion product needs to repeat the design and development of the electronic and electrical architecture, resulting in a large amount of repeated development investment. Embodiments of the present application are based on the common characteristics of intelligent electric vehicles, robots, unmanned aircraft, unmanned agricultural machines and other motion AI intelligent products. Taking a vehicle as an example, an integrated electronic and electrical architecture solution is designed around the AI intelligence core from the top-level architecture concept design. All motion AI intelligent products can be composed of the following components: 1) a computing and control center, that is, a central computing platform with high computing power, similar to the size of the brain, which can also include a communication module connected to the outside world; 2) a power distribution and data hub, composed of several electric and data hubs, responsible for power distribution of all electrical equipment in the vehicle and exchange of different types of data; 3) sensing and interaction components, such as cameras, radar sensors, screens, speakers and other interaction components. Sensing and interaction components can be connected to the central computing platform or the electric and data hub; 4) power components, including high-voltage power supply and low-voltage power supply, the high-voltage power supply provides power source for the entire AI product, and the low-voltage power supply provides power for other controllers, sensors / execution components in the vehicle; 5) edge nodes, connected to various motor, light and other drive modules, as well as diagnostic, data recovery related sensors, and automobile electric drive, braking, steering components, unmanned aircraft propellers, and humanoid robot limbs, responsible for data interaction nodes; 6) power network, providing power to computing and control, sensing and execution components, based on redundant power supply to ensure power supply safety; 7) communication network, transmitting camera, radar and various sensor data to the central computing platform, and feeding back the results of computing and control to the drive module, based on data loop to ensure safe and redundant data exchange.

[0053] The above architecture solution hierarchically designs the computing and control, sensing components, and drive and execution components, achieving high separation of drive and control. The control algorithm is highly concentrated in the central computing platform, based on high-performance chips to realize AI, thereby improving software development efficiency and OTA upgrade efficiency; edge nodes use MCU technology for data transmission only, simplifying hardware composition, reducing cost and improving component standardization. The electronic and electrical architecture (Electrical / Electronic Architecture) is referred to as EE architecture solution, which is not only applicable to the field of intelligent electric vehicles, but also applicable to robots, unmanned aircraft, unmanned agricultural machines and other different AI motion products.

[0054] In the present embodiment, an electronic and electrical architecture is provided for artificial intelligence motion equipment, such as Figure 1 As shown in the figure, the electronic and electrical architecture includes a central computing platform 101, a power component 102, and a plurality of power distribution and data transmission modules 103 (in the figure, only one power distribution and data transmission module 103 is shown). Figure 1The device comprises a central computing platform 101, a power supply component 102, a plurality of power distribution and data transmission modules 103, a plurality of edge nodes 104 and a plurality of sensing and interaction components 105, wherein the edge node 104 is connected with at least a first sensing and interaction component, and the first sensing and interaction component is the sensing and interaction component 105 in the same distribution area in the device;

[0055] The power distribution and data transmission module 103 is connected with at least a first edge node, and the first edge node is the edge node 104 connected with the sensing and interaction component 105 in the same power distribution and communication area in the device;

[0056] The power distribution and data transmission module 103 is also connected with the central computing platform 101 and the power supply component 102 respectively, so as to realize data interaction between the central computing platform 101 and each sensing and interaction component 105 through the edge node 104, and to realize power distribution of the power supply component 102 in the electronic and electrical architecture.

[0057] The artificial intelligence sports device can be an intelligent electric vehicle, a robot, a unmanned aerial vehicle, an unmanned agricultural machine and the like, and in the embodiment of the application, the artificial intelligence sports device is taken as an example of a vehicle integrated with artificial intelligence. The sensing and interaction components include sensing components and execution components, the sensing components include radar, sensors and the like, and the execution components include microphones, loudspeakers, electric seats and the like.

[0058] It should be noted that the entire device can be divided into a plurality of power distribution and communication areas according to the communication and power distribution component requirements in different positions of the artificial intelligence sports device, and one power distribution and data transmission module is configured in each power distribution and communication area. For example, the entire vehicle can be divided into a front, a body and a tail, and each of the body, the front and the tail can be divided into a plurality of distribution areas according to the specific distribution positions of the sensing and interaction components in the area, and each distribution area is configured with an edge node. For example, the body is divided into an inner door, a front, middle and rear passenger compartment, a roof and a rear door area, and the edge node is connected with each sensing and interaction component in the corresponding distribution area, so as to maximize the simplification of the harness complexity and the harness length of the data and power distribution in the artificial intelligence device, save the cost and improve the data transmission and power distribution efficiency.

[0059] The embodiment achieves the ordered association of components according to regions and power distribution and communication, greatly reduces the complexity and length of the wire harness in the entire device, and saves costs by connecting the edge node with the first perception and interaction component in the same distribution region, and connecting the power distribution and data transmission module with the first edge node corresponding to the same power distribution and communication region. And by connecting the power distribution and data transmission module with the central computing platform and the power component at the same time, the data interaction between the central computing platform and the perception and interaction component can be completed relying on the edge node, and power distribution can also be realized. This structure avoids the problems of component connection confusion and complex data transmission path in the traditional architecture, makes data interaction more efficient and power distribution more accurate, lays a foundation for subsequent software reuse, and reduces the cost of repeated development of different AI sports device architectures.

[0060] Specifically, the control logic flow of the electronic and electrical result provided by the embodiment is as shown in the figure Figure 2 As shown in the figure, the control logic service is simplified into two levels of central computing platform and edge node, data is converted through the data gateway, that is, the above-mentioned power distribution and data transmission module, the gateway only forwards data and does not do logical processing. The edge node is responsible for sensing data collection and returns to the central computing platform for processing, and the central computing platform centrally processes and then sends execution instructions to the related edge node to drive the actuator to complete the instruction action.

[0061] In some optional embodiments, the perception and interaction component includes a sensing component and an execution component.

[0062] Each edge node collects the operation data of the sensing component in the same distribution region and transmits the operation data to the corresponding power distribution and data transmission module.

[0063] The power distribution and data transmission module transmits the operation data to the central computing platform.

[0064] The central computing platform processes the operation data transmitted by each power distribution and data transmission module, generates a control instruction corresponding to the first execution component, and transmits the control instruction to the first edge node through the first power distribution and data transmission module connected with the first edge node. The first edge node is an edge node connected with the first execution component.

[0065] The embodiment realizes a complete closed loop of sensing data collection, processing and execution instruction issuing by collecting the operation data of the sensing component in the same region by the edge node and transmitting the operation data to the central computing platform through the power distribution and data transmission module, and generating the control instruction by the central computing platform after processing and returning to the edge node to drive the execution component. This process not only improves the data processing efficiency and the accuracy of instruction execution, but also simplifies the edge node structure and reduces the hardware cost, and at the same time facilitates the central computing platform to optimize the algorithm uniformly, improves the software development and OTA upgrade efficiency.

[0066] In some optional embodiments, the central computing platform is connected with at least one sensing and interaction component, so as to realize redundant data interaction between the central computing platform and the sensing and interaction component.

[0067] Specifically, for the important sensing and interaction components in the above artificial intelligence sports equipment, such as radar, camera, screen, microphone, speaker, etc., which are directly connected with the central computing platform, the redundant data interaction between the central computing platform and the important sensing and interaction components can be realized, so as to avoid the problem that important data is lacking or important functions cannot be normally used due to communication failure of the power distribution and data transmission module.

[0068] The embodiment directly connects the central computing platform with at least one sensing and interaction component, and on the basis of the original connection through the power distribution and data transmission module and the edge node, a direct connection path is added. The double connection forms a redundant data interaction channel. When one path fails, the other path can guarantee normal data interaction, avoid the sensing and interaction interruption problem caused by the failure of a single connection path, and significantly improve the reliability and security of the architecture data interaction, meeting the high requirements of AI sports equipment on data transmission stability.

[0069] In some optional embodiments, the central computing platform and each power distribution and data transmission module are connected through Ethernet communication to form a ring-shaped Ethernet communication connection structure.

[0070] Specifically, each power distribution and data transmission module communicates through Ethernet to form an Ethernet communication link between the power distribution and data transmission modules, and then the central computing platform and each power distribution and data transmission module are also connected through Ethernet communication, so as to form a single or multiple Ethernet communication loops between the central computing platform and each power distribution and data transmission module, and realize the redundant communication function between the central computing platform and each power distribution and data transmission module.

[0071] The embodiment forms a ring-shaped communication structure of the central computing platform and each power distribution and data transmission module through Ethernet. The ring-shaped structure makes each node have two communication links. Compared with the traditional linear structure, when a certain section of Ethernet has a problem, data can be immediately switched to another path for transmission, so as to guarantee uninterrupted communication and improve the redundancy and security of communication. At the same time, Ethernet has high-speed transmission characteristics, can meet the efficient transmission demand of a large amount of data between the central computing platform and the power distribution and data transmission module, and the ring-shaped structure is flexible in networking, can increase or decrease nodes according to the equipment demand, does not affect the original node hardware, and is suitable for different architecture scales of AI sports equipment.

[0072] In some optional embodiments, the central computing platform comprises: a main computing center and at least one vice computing center, and the main computing center and the vice computing center are redundant backups of each other.

[0073] It should be noted that the main computing center and the vice computing center can be completely redundant backups, that is, when the main computing center fails, the vice computing center is switched to run, or can be partially redundant backups, that is, when the main computing center partially fails, the function corresponding to the failure is switched to the vice computing center to run, in addition, according to the demand of each function of the device for computing resources and the importance of the function, only part of the function can be redundantly backed up in the vice computing center, only as an example, the present application is not limited thereto.

[0074] In this embodiment, the central computing platform is divided into a main computing center and at least one vice computing center, and the two are redundant backups of each other. The main computing center is responsible for computing and control under normal circumstances, and when the main computing center fails, the vice computing center can immediately take over the work to ensure that the core computing function of the architecture does not interrupt. This redundant design improves the reliability of the central computing platform, avoids the paralysis of the entire architecture due to the failure of a single computing center, meets the demand of the AI sports device for high availability of the core computing unit, and is especially suitable for unmanned control and other scenes with extremely high safety requirements, providing a core guarantee for stable operation of the device.

[0075] Exemplarily, as Figure 3As shown, the central computing platform is composed of a brain, i.e., a main computing center, also referred to as a main brain, and a cerebellum, i.e., a secondary computing center, also referred to as a secondary brain, and further includes a communication module. In the brain, the cerebellum and the communication module, a high-computing SOC chip is correspondingly arranged. Compared with the traditional central + regional architecture, the central computing platform of the embodiment has higher control logic integration, all control logic and algorithms are responsible by the central computing platform, and other modules are only responsible for sensing, execution and necessary diagnosis. The main brain uses a high-computing chip as a processor, is responsible for the whole function computing and control of the vehicle, the secondary brain uses a high-computing chip as a processor, is responsible for the basic functions of the product, is a redundant backup when the main brain fails, realizes the ability of limping, and guarantees the basic safety. The main brain and the secondary brain have independent networks, power supplies and chips, and have the ability of independent work. The communication module communicates with external facilities of the product through 4G, 5G or WIFI and other communication modes, realizes the interconnection of the AI sports product and other AI sports products, the cloud and the device end, and thus realizes the functions of remote control and monitoring, autonomous network and the like. The radar, the camera, the screen, the microphone, the loudspeaker and other sensing and interactive components can be directly connected with the central computing platform, or can be connected through the power distribution and data transmission module to transmit information to the central computing platform, realize the sensing data access and HMI interaction. The architecture realizes the redundant safety of the architecture level by adding a redundant central computing platform in the backbone network and realizing the redundant collocation of the necessary sensing and execution modules, and cooperates with the redundant communication and power supply design, so as to meet the high safety requirements of unmanned control.

[0076] In some optional embodiments, the power distribution and data transmission module is also connected with the electronic control units belonging to the same device function in the device and other second sensing and interactive components not connected with the edge node, for realizing the data interaction of the electronic control units and the second sensing and interactive components with the central computing platform.

[0077] The power distribution and data transmission module is also used for realizing the data exchange between the electronic control units connected with the power distribution and data transmission module.

[0078] Specifically, in actual application, based on the design principle of the simplified wire harness, if the distance between certain sensing and interactive components and the power distribution and data transmission module is less than the distance between the sensing and interactive components and the edge node of the region where the sensing and interactive components are located, the sensing and interactive components can be directly connected with the power distribution and data transmission module without passing through the edge node. The present application is not limited in this regard.

[0079] It should be noted that taking the vehicle as an example, part of the electronic control units (ECUs) in the existing vehicle cannot evolve into edge nodes at the current stage, and a small amount of data exchange is still needed between the ECUs. Such nodes can also be directly connected with the power distribution and data transmission module to realize data exchange function by using the power distribution and data transmission module, so as to ensure the integrity of the overall artificial intelligence sports equipment architecture and function.

[0080] The embodiment makes the power distribution and data transmission module additionally connect the electronic control units of the same device function and the second sensing and interaction components not connected with the edge nodes, which realizes data interaction of these components with the central computing platform and supports data exchange between the connected electronic control units. This design covers different types of components in the architecture, ensures efficient transmission of all types of data, avoids the problem of data island caused by the inability of some components to access the central computing platform, meets the data interaction needs between electronic control units, improves the compatibility of the architecture and the integrity of data flow, and adapts to the scene of various types of components in different AI sports equipment.

[0081] In some optional embodiments, the power supply component includes a main power supply and a redundant power supply.

[0082] The power distribution and data transmission modules are connected in sequence to form a ring network, and the main power supply and the redundant power supply are arranged on the ring network.

[0083] The power distribution and data transmission module distributes the main power supply or the redundant power supply to each structure connected with the power distribution and data transmission module, and the structure includes a central computing platform, an edge node, an electronic control unit, and a second sensing and interaction component.

[0084] The edge node distributes the power supply distributed by the power distribution and data transmission module to each sensing and interaction component connected with the edge node.

[0085] Among them, the main power supply and the redundant power supply in the power supply component can include high-voltage power supply and low-voltage power supply according to the power demand of different power equipment in the artificial intelligence sports equipment, so as to realize the redundant backup of all power supplies. The power distribution and data transmission module and the edge node jointly realize two-stage power distribution, realize the integrated design of power distribution and data transmission, and further reduce the complexity and cost of wire harness in the artificial intelligence sports equipment.

[0086] The embodiment divides the power supply component into a main power supply and a redundant power supply, each power distribution and data transmission module constitutes a ring network, and the main power supply and the redundant power supply are arranged on the ring network. The power distribution and data transmission module and the edge node are hierarchically implemented power distribution. The dual power supply design combines with the ring power distribution network to form a redundant power supply system. When the main power supply or a certain power distribution link fails, the redundant power supply and other power distribution links can ensure normal power supply of each structure. The hierarchical power distribution of the power distribution and data transmission module and the edge node makes the power distribution more accurate, avoids power waste, and improves the stability and safety of power supply, solving the problem of operation interruption of AI sports equipment caused by power supply failure.

[0087] In some optional embodiments, the power distribution and data transmission module comprises: a power and data coupling processing circuit, which is used for coupling processing of power provided by the power supply component and data received by the power distribution and data transmission module, and outputting the coupling processing result to a corresponding connection object through a twisted pair, the connection object comprising: a central computing platform, an edge node, an electronic control unit, and a second perception and interaction component;

[0088] A power and data decoupling circuit is arranged in the connection object, and the coupling processing result is decoupled through the power and data decoupling circuit to obtain power and transmission data.

[0089] The embodiment sets a power and data coupling processing circuit in the power distribution and data transmission module, transmits the coupling result to the connection object through a twisted pair, and separates the power and data through a decoupling circuit in the connection object. This design realizes the co-linear transmission of power and data, reduces the number of power harnesses and data harnesses, and reduces the hardware cost and internal wiring complexity of the equipment. At the same time, the twisted pair transmission method has strong anti-interference ability, which guarantees the stability of power transmission and the accuracy of data transmission, and is especially suitable for small power components such as radars and cameras, improving the integration and practicability of the architecture.

[0090] Further, as shown in Figure 4 The power distribution and data transmission module, i.e., the electric & data hub, can be composed of a data exchange module and a chip power distribution module, and in actual application, can also be composed of a data and power distribution coupling module. The data exchange module realizes data routing between different communication types or different communication nodes, and also realizes signal type data of the edge node, or data transmitted by the ECU node connected to the electric & data hub is transmitted to the central computing platform through Ethernet. The chip power distribution module adopts an electronic fuse E-Fuse or a high-side driver switch chip HSD to distribute power to the electrical appliances. The electric & data hub module is deployed according to regions in the product, which can maximize the saving of power and data harnesses. The number of electric & data hubs can be set to more than one according to the requirements of the equipment.

[0091] The working principle of the data exchange module is shown in Figure 5 The data exchange module mainly realizes two functions. One is to access the data exchange of all network nodes of the data exchange module. Due to the limitations of software and hardware technologies, some electronic control units (ECUs) cannot evolve into edge nodes at the current stage, and a small amount of data exchange is still needed between the ECUs. The data exchange module is connected with these ECUs through LIN, CAN, CANFD, CANXL and other types of interfaces to realize the data exchange between the ECUs. The other function is to transmit the data of the edge nodes and the ECUs connected to the data hub to the central computing platform. For the edge nodes, a 10-BaseT1 Ethernet data interface with a speed of 10M is used, and the RCP (Remote Control Protocol) protocol or other similar remote control protocols can be used. The protocol standardizes the data transmission of the edge nodes, the data exchange module of the data hub and the central computing platform. For other LIN / CAN ECU nodes, the data protocol needs to be converted into Ethernet data protocol and then forwarded to the central computing platform. The data exchange module can also access audio devices such as speakers and microphones through a dedicated interface DSP, convert audio data into Ethernet and then transmit it to the central computing platform.

[0092] As shown in Figure 6 The function of the chip power distribution module is to provide power supply for the ECUs, sensing components and execution components. Based on safety considerations, the power supply output is a low-voltage power supply below 60V, which can be any combination of 48V, 24V, 12V and 5V power supplies. The power supply of the vehicle power supply components is provided to the data hub, which is configured by chips, including electronic fuses and high-side drive switches to supply power to the electrical load. The intelligent power management program of the central computing platform can turn on and off the power supply to each power supply component according to different functional scene requirements, thereby realizing intelligent power distribution. E-Fuse is used for customizable scene power distribution, and HSD is used for fixed scene power distribution. The chip power distribution technology using E-Fuse and HSD is more flexible, energy-saving, reliable and precise in overcurrent protection compared with the traditional relay + fuse power distribution method. It should be noted that the power distribution technology used by the chip power distribution module is a prior art, and its specific implementation process is not described here.

[0093] In addition, as shown in Figure 7As shown, the above data and power distribution coupling module is an Ethernet data transmission and power distribution collocation solution based on PoDL technology, which can support a maximum power output of 5W (12V) or 50W (48V) system, and can realize power line and data line collocation for small power consumption loads such as radar and camera, thereby further saving cost. Specifically, the power and data lines in the module are coupled and processed by a power and data coupling processing circuit, and then output through a pair of twisted wires. Then, at the power consumer end, a power and data decoupling circuit is used to realize power distribution and data exchange for the power consumer.

[0094] As shown in the example, Figure 8 Each edge node includes a power supply module and a communication module. The power supply module further distributes the power provided by the electric & data hub according to the modules of the edge node, and distributes power to the components of the edge node through an LDO / DCDC power supply module chip. The communication module of the edge node uses RCP or other similar remote control protocols. The central computing platform issues remote control protocols, which are transmitted through the electric & data hub and then enter the edge node. The remote protocol directly implements driving instructions for various loads such as motors, valves, and lights. Compared with traditional controllers, the edge node has moved the logic algorithm to the central computing platform, and the function of no logic operation is replaced by an RCP Server module instead of a traditional MCU, thereby reducing hardware costs. The edge node can be a seat motor driving module of a car, a rotor motor driving module of a drone, a servo motor driving module of a humanoid robot, or a driving module of a harvesting mechanical device of an unmanned agricultural machine. However, they all have the same structure, including a driving circuit and a sensing and collecting circuit. Through the edge node, various types of signals are converted by an analog-to-digital converter and transmitted to the central brain through the RCP protocol, thereby greatly improving efficiency.

[0095] In addition, in actual applications, the electric & data hub and the edge node can also be integrated in one body, for example, Figure 9 As shown, the integrated form has both the data exchange and power distribution capabilities of the electric & data hub and the driving and sensing information collection capabilities of the edge node. If the sensing and executing modules connected to the edge node are basic configurations and have been standardized, the integrated form with the electric & data hub can be used to form a larger standardized component, thereby saving cost.

[0096] As shown in the example, Figure 10As shown, the central computing platform and the electric & digital hub constitute a ring network with high-speed Ethernet ETH as the backbone network. It can be a single Ethernet ring network, or multiple Ethernet ring networks, which are connected through the Switch of the central computing platform. The Ethernet ring network is a high-speed communication backbone network with a bandwidth of 100M or higher communication rate. The central computing platform and the electric & digital hub both have Ethernet communication chips, and are composed of Switch + transceiver or Brigde + transceiver, supporting Ethernet ring network transmission; the central computing platform can be composed of one high-performance SOC chip, or n SOC chips, n is greater than or equal to 2; if it is in the form of one SOC chip, it is directly connected with the nearest two electric & digital hub nodes through Ethernet to form a ring network. The number of nodes of the electric & digital hub can also be one or more, and the multiple nodes are connected by Ethernet. All the central computing platforms and the electric & digital hubs constitute a ring Ethernet network. The ring network has flexibility, and the number of nodes can be increased or decreased according to actual needs, without affecting the original node hardware. The topology form always remains ring-shaped, meeting the needs of different numbers of nodes of various AI sports products.

[0097] The central computing platform and the electric & digital hub constitute a high-speed Ethernet ring network. Based on the technical characteristics of the ring network redundancy, each node has two communication link transmission paths to other nodes. When a certain section of Ethernet has a problem, it will immediately switch to another transmission path to ensure communication safety.

[0098] As shown in the example, Figure 11A The power supply network of the electronic and electrical architecture provided by the embodiment adopts a redundant power supply. It is composed of a main power supply, a redundant power supply and an electric & digital hub. The main power supply and the redundant power supply form two independent power supply systems for the power module. Each independent power supply system can be a direct current-direct current converter DCDC or a low-voltage battery. It can also be a combination of the two. Figure 11BAs shown, the redundant power supply can be in the following forms: DCDC1 and low-voltage battery 1, DCDC1+low-voltage battery 2 and low-voltage battery 2, DCDC1+low-voltage battery 2 and DCDC2, DCDC1+low-voltage battery 2 and DCDC2+low-voltage battery 1. The two power supply and power supply networks are isolated by a power supply isolation module. Each power supply hub has two power supply interfaces, and the two power supply interfaces are connected by a MOS circuit to realize power supply monitoring and rapid shutdown. The specific working principle is as follows: under normal circumstances, the two power supply interfaces of the power supply hub are in a connected state, and the DCDC can normally supply power to the low-voltage battery and the power supply hub. When the power grid at any position has an under-voltage or over-voltage problem, the power supply hub can quickly cut off the connection between the two power supply networks through the internal MOS device, and the microsecond-level shutdown can be realized. The other power supply interface of the power supply hub can also ensure continuous normal power supply. At the same time, through the current and voltage monitoring characteristics of the MOS device, the abnormal power supply problem of the power grid at that link can be quickly located.

[0099] For power supply safety requirements of high-power devices, the power supply can be connected to two power supply hubs at the same time. This scheme can solve the problem of abnormal situation of a power supply hub and immediately maintain power supply by another power supply hub.

[0100] Combining the above two schemes, any problem in the power supply network, power supply, power supply harness and power supply hub can be solved to realize normal power supply. A high-safety power supply solution and a diagnosis scheme are provided.

[0101] Exemplarily, the vehicle using the above electronic and electrical architecture can support the realization of intelligent driving safety redundancy and human driving safety redundancy. The high-computing SOC chip as the main chip of the brain respectively deploys the control redundancy strategy required by the high-computing automatic driving, and the cerebellum realizes the redundancy control of intelligent driving; at the same time, the basic vehicle body, power and chassis function logic related to human driving function can also be deployed in the cerebellum, and the brain and the cerebellum form backup redundancy with each other, so as to realize safer human driving redundancy control. Based on this software deployment strategy, backup redundancy is formed between the brain and the cerebellum in the central computing platform.

[0102] According to the embodiment of the present application, a function backup method embodiment is provided. It should be noted that the steps shown in the flowchart can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0103] In this embodiment, a function backup method is provided, which can be used for a software function safety redundancy strategy module of a vehicle using an electronic and electrical architecture as shown in Figure 1 ​Figure 12 is a flowchart of a whole vehicle control function redundancy implementation method according to an embodiment of the present application, as shown in the figure, the flow includes the following steps: Figure 12

[0104] Step S201, based on the driving function of the whole vehicle, the software function modules of the whole vehicle control function software are divided, a plurality of software function modules are obtained, and each software function module and the corresponding redundant backup module are respectively deployed in different computing power centers of the central computing platform.

[0105] Specifically, the computing power center is the hardware with computing power in the whole vehicle, including a main computing power center and at least one auxiliary computing power center, exemplarily, taking two computing power centers as an example, a brain and a cerebellum can be constituted as shown in Figure 3 In actual application, the computing platform can also be constituted by 3 or more computing power centers, one or more software function modules of different driving functions are deployed in different computing power centers, each software function module includes: a software function module corresponding to a different driving function. Exemplarily, the driving function can be functionally divided according to the whole vehicle system, such as power system, steering system, braking system, body system, and part of the sensing system, each system corresponds to a type of driving function, such as: the steering function corresponding to the driving function of the steering system, and the braking function corresponding to the driving function of the braking system. Only this is an example, and the present application is not limited thereto. Accordingly, the whole vehicle control function software is divided, and the software related to each driving function is packaged as a software function module. Specifically, the process of dividing the whole vehicle control function software into a plurality of software function modules is itself a prior art, which will not be described here.

[0106] Specifically, by deploying each software function module and its corresponding redundant backup module in different computing power centers, the redundant backup of each software function module is realized.

[0107] Step S202, based on the calling relationship between the software functions contained in each software function module, a software scheduling table is generated.

[0108] The software scheduling table includes: deployment address information of the software function module corresponding to the redundant backup module, and a scheduling link for representing the scheduling order between the software functions contained in the software function module, so that each software function module is scheduled and run according to the scheduling link. The scheduling link is the calling order of the corresponding calling interface address between the software functions contained in the software function module, the working order of each software function can be controlled through the calling order of the corresponding calling interface address between the software functions, and the software function of the software function module is realized.

[0109] ​Specifically, the deployment address information includes: calling interface addresses of different backup sub-software function modules included in the redundant backup module, and calling interface addresses corresponding to different software functions, wherein each redundant backup module is composed of a plurality of backup sub-software function modules, and is respectively used to implement a sub-function related to a driving function, such as a steering function including a parameter acquisition sub-function of acquiring a steering parameter, a calculation sub-function of processing a steering parameter, and the like. Each backup sub-software function module is composed of a plurality of software functions. The software function is the smallest unit of software implementation. The specific software function type and the software function quantity can be set according to the sub-function corresponding to the different backup sub-software function module, and will not be described here.

[0110] In step S203, when it is detected that any software function module has an exception in the running process, the scheduling link is updated based on the software function associated with the exception and the deployment address information, to obtain an updated scheduling link.

[0111] Specifically, the calling interface address of the software function with an exception in the scheduling link is replaced by the calling interface address of the corresponding redundant software function to obtain the updated scheduling link, so as to ensure that the software function with an exception can be backed up for normal operation.

[0112] In step S204, the software function module with an exception is controlled to schedule and run according to the updated scheduling link.

[0113] Specifically, since the software function with an exception has been redundantly replaced in the updated scheduling link, the updated scheduling link can be normally scheduled and run, so as to ensure that the entire software function module is normally and stably operated.

[0114] The function backup method provided in the embodiment divides the software function module according to the specific electronic and electrical architecture by driving function, deploys it and the corresponding redundant backup module in different computing power centers of the central computing platform, generates a scheduling link in combination with the software function calling relationship, updates the scheduling link based on the function associated with the exception and the deployment address of the redundant backup module when there is an exception, and schedules and runs the software function module with an exception according to the updated scheduling link. The whole vehicle control function redundancy implementation scheme does not need to reprocess data in full amount, but only needs to dynamically adjust and update the scheduling link, greatly reduces the lag of control command output, and ensures the continuity of the function in the high-level assisted driving scene. At the same time, the deployment of different computing power centers realizes the dispersed backup of each software function module at the hardware level, cooperates with the dynamic adjustment of the scheduling link, ensures the integrity and reliability of the whole vehicle control function, meets the real-time requirement of high-level assisted driving on the basis of realizing the safety redundancy of the whole vehicle control function, and further ensures the driving safety of the vehicle.

[0115] A function backup method is provided in the embodiment, which can be used for a software function safety redundancy strategy module of a vehicle, Figure 13 is a flowchart of the function backup method according to the embodiment of the application, as Figure 13 shown, the flow includes the following steps:

[0116] Step S301, based on the driving function of the whole vehicle, the software function modules of the whole vehicle control function software are divided, a plurality of software function modules are obtained, and each software function module and the corresponding redundancy backup module are respectively deployed in different computing power centers of the central computing platform.

[0117] Specifically, the computing power center includes: a main computing power center and at least one secondary computing power center. In the above step S301, each software function module and the corresponding redundancy backup module are respectively deployed in different computing power centers of the whole vehicle, which includes:

[0118] Exemplarily, the A software function module can be respectively deployed in the main computing power center and the secondary computing power center, so as to realize the redundancy setting of the A software function module; in addition, more redundancy settings can be made according to the importance of the driving function, and the scheduling priority of the different redundancy backup modules is set correspondingly.

[0119] Among them, the scheduling priority can be set correspondingly according to the size of the computing power resource of different computing power centers, and the richer the computing power resource, the higher the corresponding scheduling priority, for example: because the main computing power center has the most abundant computing power, it can support the synchronous running of multiple software function modules, therefore, the scheduling priority of the redundancy backup module deployed in the main computing power center can be set to the highest.

[0120] Step S302, based on the calling relationship between the software functions contained in each software function module, a software scheduling table is generated, the software scheduling table includes: the deployment address information of the software function module corresponding redundancy backup module, and the scheduling link used to represent the scheduling order between the software functions contained in the software function module, so that each software function module is scheduled and run according to the scheduling link. For details, see the related description of step S202 as Figure 12 shown, which will not be repeated here.

[0121] Step S303, when detecting that any software function module appears abnormal in the running process, the scheduling link is updated based on the software function associated with the abnormality and the deployment address information, and the updated scheduling link is obtained.

[0122] Specifically, the above step S303 includes:

[0123] Step S3031, when detecting that any software function module has an exception in the running process, determining the link update mode based on the function type of the software function associated with the exception, and / or the quantity relationship between the first quantity of the software function associated with the exception and the total quantity of software functions contained in the software function module where the exception occurs.

[0124] Specifically, the above step S3031 comprises:

[0125] Step a1, when the function type of the software function associated with the exception is a key function function, and / or the first proportion of the first quantity to the total quantity of software functions exceeds the first preset proportion value, determining that the link update mode is a function update mode; the key function function is a function that implements the core function of the software function module where the exception occurs.

[0126] Step a2, when the function type of the software function associated with the exception is not a key function function, and / or the first proportion of the first quantity to the total quantity of software functions does not exceed the first preset proportion value, determining that the link update mode is a function update mode.

[0127] Specifically, through the atomization and hierarchical design of the vehicle control software, the key function function and the non-key function function in each software function module are determined. The key function function herein is a function that directly implements the core control logic of the software function module, for example, the motor torque precise control function in the power system software function module (directly determines the vehicle power output precision and affects the driving stability), the brake pressure regulation function in the brake system software function module (directly relates to the vehicle deceleration braking effect and is related to the driving safety), which all belong to the key function function. The non-key function function refers to a function that does not directly affect the core control logic of the software function module and only undertakes auxiliary tasks, for example, the "sensor data backup function" in the sensing system software function module (only used for data storage and does not affect the real-time sensing result output), the "window control log function" in the vehicle body system software function module (only records the operation record and does not affect the window lifting control), etc.

[0128] Further, after monitoring that a certain software function module runs abnormally, firstly, the software functions associated with the abnormality are identified: on the one hand, it is judged whether these functions belong to the above-mentioned key function functions; on the other hand, the first number of the software functions associated with the abnormality is counted, and the first proportion of the total number of the software functions contained in the software function module is calculated, and a first preset proportion value (such as 50%, which can be adjusted according to the importance of different function modules, in combination with the safety requirements of high-order auxiliary driving function) is preset. When any of the following conditions is met, it is determined that the scheduling link update mode is a function update mode: condition one, at least one key function function exists in the software functions associated with the abnormality; condition two, the first proportion of the software functions associated with the abnormality exceeds the first preset proportion value (such as 50%). If the above two conditions are not met, it is determined that the scheduling link update mode is a function update mode.

[0129] The embodiment realizes accurate matching of the scheduling update mode by distinguishing between key function functions and non-key function functions and whether the abnormal function quantity proportion exceeds the preset value. The function update mode is adopted for key function abnormality and / or multi-function abnormality, which can completely avoid the risk of core function failure and quickly contain abnormality spread. The function update mode is adopted for non-key function or a small number of function abnormalities, which can minimize the influence of the update on the operation of the software function module, reduce the time consumption of software function processing without interrupting the continuous operation of the overall function guarantee function, guarantee the safety of the high-order auxiliary driving core function, and also consider the efficiency of the software function operation.

[0130] In step S3032, the scheduling link is updated based on the scheduling link update mode and the deployment address information to obtain an updated scheduling link.

[0131] The embodiment determines the update mode of the scheduling link by analyzing the type and / or quantity proportion of the software functions associated with the abnormality, so that the scheduling update is more targeted, the problem of not timely processing caused by the mode of replacing the entire function software regardless of the severity of the abnormality is avoided, the flexibility and effectiveness of the vehicle control redundancy strategy are further improved, and the complex software operation requirements in the high-order auxiliary driving scene can be better adapted.

[0132] Further, when the scheduling link update mode is a function update mode, the above step S3032 includes:

[0133] In step b1, based on the deployment address information, the calling interface address of the redundant software function corresponding to the software function associated with the abnormality is determined.

[0134] In step b2, the calling interface address of the software function associated with the abnormality in the scheduling link is replaced by the calling interface address of the corresponding redundant software function, and an updated scheduling link is obtained.

[0135] Specifically, in the software deployment phase, the atomized functions (including normal functions and redundant functions) of each software function module have been deployed in different computing power centers (such as main computing power center, secondary computing power center), and each function is assigned a unique calling interface address (such as IP + port identification based on Ethernet protocol), and the correspondence between the function, the redundant function and the corresponding calling interface address is stored in the address mapping library of the vehicle control software. After locating the software function associated with the exception, the calling interface address of the redundant software function is finally extracted through the matching query of the address mapping library. After obtaining the calling interface address of the redundant software function, there is no need to reconstruct the entire scheduling link, and only the interface address field corresponding to the software function associated with the exception in the scheduling table is replaced: the calling interface address of the original abnormal function is deleted, and the determined redundant function calling interface address is filled in, while the calling order and interface address of other normal functions in the scheduling link remain unchanged. After the replacement is completed, the scheduling table automatically generates the updated scheduling link, which only corrects the abnormal node, and the rest of the logic is exactly the same as the original link, which can be directly called and executed by the vehicle control software.

[0136] In the function update mode of the present embodiment, the calling interface address of the redundant software function is located by deploying address information, and the interface address of the abnormal function is directly replaced to complete the scheduling link update. This method does not need to replace the entire software function module, but only needs to accurately replace the abnormal function, maximally retains the original software logic and data processing results of normal operation, avoids the delay caused by full data recalculation, and ensures the real-time output of control instructions. At the same time, the direct replacement of the interface address simplifies the update process of the scheduling link, reduces the system resource occupation, makes the fault-tolerant response of the software function in the high-level auxiliary driving scene more rapid, and ensures the continuity and safety of the driving process.

[0137] Further, when the scheduling link update mode is the function update mode, the above step S3032 comprises:

[0138] Step c1, determining the target sub-software function module corresponding to the software function associated with the exception.

[0139] Wherein, the software function module comprises a plurality of sub-software function modules, and the target sub-software function module is at least one sub-software function module in the software function module that appears abnormal. Each software function module of the vehicle control is divided into a plurality of sub-software function modules according to the function subdivision logic, each sub-software function module is composed of a group of associated software functions, and the mapping relationship between the software function and the sub-software function module (such as function belonging to sub-module identifier, sub-module core function definition, etc.) is stored in advance.

[0140] Step c2, determining the second number of corresponding sub-software function modules in the target sub-software function module;

[0141] Step c3, when the second proportion of the second number to the total number of sub-software function modules included in the software function module with an abnormality exceeds the second preset proportion value, if the current driving mode of the vehicle is the intelligent driving mode, the current driving mode is switched from the intelligent driving mode to the human driving mode, and based on the deployment address information, the corresponding redundant backup module is switched to run.

[0142] Specifically, according to the safety requirement of ensuring human driving takeover when the high-level assisted driving system itself is abnormal, the second preset proportion value is set for each software function module in advance (the second preset proportion value of the core function module is usually 50% according to the influence degree of the sub-module on the overall function, which can be flexibly adjusted). If the second proportion exceeds the second preset proportion value, it indicates that the abnormal range of the software function module has affected the core control logic, and the driving safety needs to be prioritized. At this time, the current driving mode (intelligent driving mode or human driving mode) is obtained through the vehicle control bus: if it is currently in the intelligent driving mode, the driving mode switching instruction is triggered immediately, the driver is prompted to take over the vehicle through the cabin interaction system, and at the same time, based on the pre-stored deployment address information of the sub-software function module and the redundant backup module, the corresponding redundant backup module is switched to run, avoiding the safety risk caused by the expansion of the abnormality; if it is currently in the human driving mode, only the redundant backup module is started to run to ensure the basic control function of the vehicle.

[0143] Step c4, when the second proportion of the second number to the total number of sub-software function modules included in the software function module with an abnormality does not exceed the second preset proportion value, step c5 is executed.

[0144] Specifically, if the calculated second proportion does not exceed the second preset proportion value, it indicates that the abnormality of the software function module is only limited to a small number of non-core sub-modules, and there is no need to interrupt the current driving mode or switch the redundant module as a whole. The redundant backup of the abnormal sub-module can be replaced to realize function recovery. At this time, the system automatically jumps to step c5 to perform address positioning operation of the target backup sub-software function module to ensure that the abnormal problem is solved at the minimum cost.

[0145] After determining the target sub-software function module, the number proportion is judged and combined with the current driving mode for differential processing: when the proportion exceeds the preset value and is in the intelligent driving mode, the human driving mode is switched and the redundant backup module is enabled to ensure driving safety; when the proportion does not exceed the preset value, the sub-module replacement is continued. This design not only considers the severity of the sub-module abnormality, but also combines the safety requirement of the driving mode, avoiding the danger caused by the expansion of the abnormality. The timely switching from the intelligent driving mode to the human driving mode in the intelligent driving mode meets the safety requirement of human driving takeover in the high-level assisted driving scene when the abnormality occurs; and the sub-module replacement when the abnormality is slight ensures the continuity of the function, achieving the balance between safety and practicability.

[0146] Step c5, based on the deployment address information, determine the calling interface address of the target backup sub-software function module corresponding to the target sub-software function module.

[0147] Step c6, replace the calling interface address of the target sub-software function module in the scheduling link with the calling interface address of the corresponding target backup sub-software function module to obtain the updated scheduling link.

[0148] Specifically, the redundant backup of each sub-software function module (i.e. the target backup sub-software function module) is pre-deployed in a different computing power center from the original module, and the association information of the target sub-software function module and the calling interface address is stored in the address mapping library. By calling the address mapping library, the deployment location of the corresponding target backup sub-software function module is queried according to the determined target sub-software function module identifier and the deployment address information of the original module, and then the unique calling interface address thereof is extracted. After obtaining the calling interface address of the target backup sub-software function module, the entire scheduling link does not need to be reconstructed, and only the interface address field corresponding to the target sub-software function module in the link table is replaced: the calling interface address of the original target sub-module is deleted, the determined backup sub-module interface address is filled in, and the calling order and interface address of other normal sub-modules remain unchanged. After the replacement is completed, the link table automatically generates an updated scheduling link, which can be immediately called by the vehicle control software to realize function recovery.

[0149] In the function update mode, the target sub-software function module corresponding to the abnormal associated function is taken as the replacement unit, and the interface address of the target backup sub-software function module is located and replaced through deployment address information. Compared with the overall function module replacement, the replacement at the sub-function module level is more accurate, reduces unnecessary software switching, and reduces software running fluctuations. This makes it possible to quickly solve abnormal problems while maintaining the stable operation of the high-level assisted driving system, avoiding the decline in driving experience or safety risks caused by overall function replacement.

[0150] Step S304, control the software function module that appears abnormal to run according to the updated scheduling link. For details, refer to the related description of step S204 as shown in Figure 12 The detailed description of step S204 will not be repeated here.

[0151] Step S305, during the process of controlling the software function module that appears abnormal to run according to the updated scheduling link, in response to the software function module that appears abnormal returning to normal, the updated scheduling link is restored to the initial state, and the running according to the scheduling link of the initial state is continued.

[0152] Specifically, after monitoring that all software functions of the original abnormal software function module run normally and the deployment hardware state is stable, it is determined that the module has recovered to normal. At this time, the system automatically triggers the scheduling link reset mechanism: calls the pre-stored initial scheduling link backup (including the function call sequence, interface address, etc. of the original abnormal module when running normally); replaces the current updated redundant scheduling link with the initial scheduling link, deletes the calling logic of the redundant module, and restores the normal position of the original abnormal module in the scheduling link; after resetting, the vehicle control software immediately runs according to the initial scheduling link, the original abnormal module resumes the corresponding control function, and the redundant module returns to the standby state, waiting for the next abnormal trigger.

[0153] After the abnormal software function module recovers to normal, the scheduling link is restored to the initial state and continues to run in this embodiment. The dynamic reversible adjustment of the scheduling link is realized, the waste of resources caused by still running with the redundant link after the abnormality is recovered is avoided, the optimal running state of each software function module is ensured; at the same time, the automatic execution of the recovery mechanism does not need manual intervention, the continuity of the vehicle control function is ensured, the high-level auxiliary driving system can quickly recover to the best performance after the abnormality is solved, and the efficiency and user experience of system running are improved.

[0154] In this embodiment, a vehicle control function redundancy implementation method is provided, which can be used for a software function safety redundancy strategy module of a vehicle, Figure 14 is a flowchart of the vehicle control function redundancy implementation method according to the embodiment of the application, as Figure 14 shown, the flow includes the following steps:

[0155] Step S401, based on the driving function of the vehicle, the vehicle control function software is divided into software function modules to obtain a plurality of software function modules, and each software function module and its corresponding redundant backup module are respectively deployed in different computing power centers of the central computing platform. For details, see the related description of step S301 as Figure 13 shown, which will not be repeated here.

[0156] Step S402, based on the calling relationship between the software functions contained in each software function module, a software scheduling table is generated, which includes: deployment address information of the software function module corresponding to the redundant backup module, and a scheduling link for representing the scheduling order between the software functions contained in the software function module, so that each software function module runs according to the scheduling link. For details, see the related description of step S302 as Figure 13 shown, which will not be repeated here.

[0157] Step S403, during the running of each software function module, the running state of the software functions contained in the software function module is monitored.

[0158] The running state includes at least one of stack usage, static variable and / or global variable usage, array access out-of-bound condition, function running time length, and being called by multiple parties.

[0159] For example, the used amount, the remaining amount, and the peak value of the stack space of the function running time can be counted in real time by embedding stack monitoring code of the function running, to determine whether there is a risk of stack overflow (such as the stack space usage continuously approaches the upper limit); the assignment frequency, the value range, and whether there is illegal modification of the variable (such as a static variable being tampered by an unauthorized function) are recorded to avoid calculation errors caused by abnormal variables; boundary check logic is added at the array read and write operation to monitor whether the array index exceeds the preset subscript range (such as whether the index is greater than or equal to 10 when the array length is 10), to prevent out-of-bound access from damaging memory data; the time from the start to the completion of the function is recorded by a timer, and compared with a preset normal running time threshold (set according to the function complexity), to identify running lag or dead loop; the number of calls per unit time, the call source (such as which upper function calls the function), and whether there is abnormal call (such as the call frequency far exceeds the normal business requirement, or comes from an unauthorized caller) are counted, which are only examples, and the present application is not limited thereto.

[0160] In step S404, whether the running state of each software function is abnormal is determined based on the function logic corresponding to the software function module.

[0161] Specifically, by combining the specific function logic of the software function module (such as the core control target of the module and the cooperative relationship between functions), multi-dimensional abnormality determination rules are established to comprehensively determine the running state of each function. When the function running state data violates the determination rules based on the function logic, it is preliminarily determined that the function is abnormal. The specific determination rules can be flexibly set according to actual conditions, and will not be described here.

[0162] In step S405, when the running state of at least one software function is abnormal, it is determined that the software function module is abnormal, and the software function that is abnormal is marked to obtain the software function associated with the abnormality.

[0163] Exemplarily, if at least one software function of a software function module is determined to be abnormal, and the abnormal function belongs to the core running link of the module, it is determined that the software function module as a whole is abnormal (if the abnormal function is an independent auxiliary function and does not affect the core function, the module can be temporarily determined not to be abnormal, and only the function is marked as abnormal); for all software functions determined to be abnormal, an abnormality mark is added to the function identifier (such as function ID, function name), and information such as abnormal type (such as running timeout, array out-of-bound, etc.), abnormal occurrence time, abnormal data (such as timeout duration, out-of-bound index value) is recorded to form an abnormal function list and stored in a database, providing a clear target object for subsequent updating of the scheduling link based on the abnormal function.

[0164] The embodiment monitors the running state of the software function, such as stack usage, variable usage, array access, running duration and calling condition, and judges whether the software function module is abnormal in combination with the function logic and marks the abnormal function. Early identification and accurate positioning of the abnormality are achieved, and function failure or system crash caused by continuous running of the abnormal function is avoided; the abnormality determination based on the function logic ensures the accuracy of the abnormality identification and reduces unnecessary updates caused by misjudgment. Timely marking of the abnormal function provides a clear basis for subsequent scheduling link updating, makes the response of the redundancy strategy more rapid, and provides a guarantee for stable operation of the high-order auxiliary driving system.

[0165] Step S406, when detecting that any software function module appears abnormal during running, updating the scheduling link based on the software function and deployment address information associated with the abnormality, to obtain an updated scheduling link. For details, refer to the related description of step S303 as shown in Figure 13 The related description of step S303 as shown in

[0166] Step S407, controlling the software function module that appears abnormal to schedule and run according to the updated scheduling link. For details, refer to the related description of step S304 as shown in Figure 13 The related description of step S304 as shown in

[0167] Step S408, during the process of controlling the software function module that appears abnormal to schedule and run according to the updated scheduling link, if it is monitored that the software function module appears abnormal again, determining whether the software function associated with the abnormality again is the same as the software function associated with the abnormality last time.

[0168] Specifically, the function list of the last abnormality and the function list of the current abnormality can be called from the database, and then the function lists of the two abnormalities are compared through the unique identification of the function (such as function ID, function name), to determine whether there is a function that is completely the same. If the function identifiers of the two abnormalities are completely the same, it is determined that the associated function of the current abnormality is the same as the last time; if the identifiers are different, it is determined that the associated function of the current abnormality is different from the last time.

[0169] Step S409, when the software function associated with the current abnormality is the same as the software function associated with the last abnormality, it is determined whether the current driving mode of the whole vehicle is the intelligent driving mode.

[0170] Specifically, when it is determined that the function of the current abnormality is the same as the last time, it indicates that the function function (including the original function and the redundant function) may have a persistent fault (such as a hardware carrier fault causing repeated function abnormalities), and the driving mode needs to be verified first to ensure safety.

[0171] Step S410, when the current driving mode of the whole vehicle is the intelligent driving mode, the current driving mode is switched from the intelligent driving mode to the human driving mode.

[0172] Specifically, when it is determined that the current driving mode is the intelligent driving mode, the system immediately triggers the driving mode switching process and sends a takeover prompt: through the cabin interaction system (such as instrument panel pop-up window, voice broadcast "auxiliary driving function abnormal, please take over the vehicle immediately") to the driver, and at the same time, the hazard warning light is on to remind the surrounding vehicles; at the same time, the intelligent driving mode exit instruction is sent to the whole vehicle control bus, and the control right of the high-level auxiliary driving system to the power, steering and braking systems is cut off, and the control right is handed over to the driver; the mode switching result is synchronized to all regional controllers to ensure that all systems respond to the driver's operation in the human driving mode (such as when the driver steps on the accelerator, the power system directly executes the accelerator instruction without going through the auxiliary driving algorithm).

[0173] In this embodiment, when the software function module abnormally again, it is determined whether the associated functions of the two abnormalities are the same to identify persistent faults, and when they are the same and in the intelligent driving mode, it is switched to the human driving mode. Therefore, switching to the human driving mode for repeated abnormal scenarios can completely avoid the safety risks caused by the failure of the intelligent driving function, and further enhances the driving safety in the high-level auxiliary driving scenario.

[0174] Step S411, when the software function associated with the current abnormality is different from the software function associated with the last abnormality, it is determined whether the updated scheduling link contains the redundant software function corresponding to the software function module that abnormally appears again.

[0175] Specifically, when it is determined that the function of the re-occurring exception is different from the last time, it indicates that the exception spreads to a new function, and it is necessary to verify whether the updated scheduling link already contains the redundant resource of the new exception function, such as by determining the function identifier of the re-occurring exception and the module to which it belongs, calling the address mapping library, checking whether the new exception function is pre-configured with a redundant software function, and whether the redundant function has been accessed to the current updated scheduling link (such as whether the calling interface address of the redundant function is contained in the link); if the corresponding redundant function is contained in the link, it is determined that the redundant software function corresponding to the exception is contained; if it is not contained (such as no redundant function is configured, or the redundant function is not accessed to the current link), it is determined that the redundant software function corresponding to the exception is not contained.

[0176] Step S412, when the redundant software function corresponding to the software function module exception re-occurring in the updated scheduling link is not contained, returning to execute step S406.

[0177] Specifically, when it is determined that the updated link does not contain the redundant function of the new exception function, it indicates that the current link cannot cope with the new exception, and it is necessary to re-execute the link updating process: the system automatically returns to step S406, takes the new exception function as the exception associated function, combines the deployment address information (the deployment position of the redundant function) of the new exception function, and performs secondary updating on the scheduling link; updating the link storage: replacing the original updated link with the secondary updated link, and storing it in the scheduling table, to ensure that the vehicle control software runs according to the new link.

[0178] In the embodiment, when the twice exception associated functions are different, it is determined whether there is a corresponding redundant software function in the updated link, and when there is no corresponding redundant software function, the scheduling link updating is re-executed. Thus, for complex multiple different exception scenarios, the existence of the redundant software function is determined to ensure that each exception can be effectively responded: when there is no corresponding redundant software function, the link is updated in time to avoid the interruption of functions due to the lack of redundant software function support; at the same time, the driving mode is not blindly switched, but the problem is solved by updating the scheduling, which guarantees the maximum availability of high-level assisted driving functions and balances safety and functional continuity.

[0179] Step S413, when the redundant software function corresponding to the software function module exception re-occurring in the updated scheduling link is contained, executing step S409.

[0180] Specifically, when it is determined that the updated link contains a redundant function of a new abnormal function, it indicates that the current link can cope with the new abnormality by activating the redundant function, but needs to be combined with the driving mode to determine whether to need a safety bottom, by directly executing the logic of step S409, that is, obtaining the current driving mode (intelligent driving / human driving) through the vehicle control bus; if it is an intelligent driving mode, step S410 is executed to switch to a human driving mode; if it is a human driving mode, a function abnormality reminder is performed, and timely software and hardware maintenance is performed.

[0181] When the updated link contains a redundant software function corresponding to the same abnormality, the driving mode judgment step is executed. This design is aimed at the scene where there are redundant software functions but different abnormalities still occur. By driving mode judgment, it is determined whether to switch to human driving, avoiding the risk that the redundant software function exists but the abnormality still affects safety. The execution of the vehicle control function redundancy strategy is more in line with the actual driving scene, and the safety and flexibility of the vehicle control are improved.

[0182] The software function safety redundancy strategy module is structured and designed to complete the vehicle control function redundancy implementation scheme. In actual application, the software function safety redundancy strategy software is not a software module independent of each software module in the current vehicle software system, but a complete set of software development rules (including function definition, and of course including entity independent software code). It is defined and integrated into each software function module layer by layer according to the hierarchical division from system to module to function. Specifically, it includes the following levels:

[0183] (1) Function level:

[0184] In the code development work of a single function function implementation, the code with the following functions needs to be developed synchronously:

[0185] Monitor the stack usage;

[0186] Monitor the static variable / global variable usage;

[0187] Monitor the array access out-of-bounds situation.

[0188] Monitor the function runtime length and the situation of being called by multiple parties.

[0189] By monitoring the function runtime data access and calculation, it is represented whether the function is normally running.

[0190] (2) Module level:

[0191] The module level summarizes the running state of each function under it, and after checking the function logic of itself, it is determined whether the module is normally executed when performing a certain task.

[0192] When the module determines that its function execution is abnormal, it will send a notification to the upper-level monitoring module, informing the level and reason of the abnormality.

[0193] (3) System level:

[0194] The system level aggregates the running status of each module, and determines whether the overall running status of the system is normal through the check of its own function logic.

[0195] When the system level detects an abnormal notification from the module level, it will decide whether to continue using the module or request to call the redundant module according to the abnormal level and reason.

[0196] In this embodiment, by borrowing the concepts of hardware hot plug technology and network node automatic identification technology, each software module is registered, called, suspended, and unregistered, and access permissions can be set. First, each software module is labeled according to the function logic to determine the running mode and upstream and downstream data transmission link of each software module. The label content is determined in the software detailed design stage. In the initial state (default vehicle software system is normal), the system generates a software scheduling table according to the software labels and state feedback. The scheduling table specifies the software module scheduling link and redundant backup module under normal circumstances. When a software module is abnormal, the system modifies the scheduling table and reorganizes the software module scheduling link. The exception is recorded and reported. When the abnormal software module is repaired, the system modifies the scheduling table and reorganizes the software module scheduling link.

[0197] In actual operation, the system constantly monitors the running status of the software module, manages in layers according to the hierarchical division from function to module to system, aggregates and integrates the information of each layer, and provides a basis for scheduling table modification. The software module is only a carrier for implementing a function or performing a task, and the execution of a function or a task is actually the transmission and calculation of data. Therefore, when the system detects that a software module is abnormal, the scheduling table is modified in real time according to the reason and level of the abnormality, that is, the data transmission path is modified, so that the execution of a function or a task can continue.

[0198] In this embodiment, by fully exposing the vehicle control (dynamic and static) capabilities to the upper level, using the powerful computing power of SOC and the AI large model capability, a high-level assisted driving with more powerful functions and better performance is realized. The high-level assisted driving system function can still guarantee the integrity of its function and the reliability of its performance in the case of vehicle network failure or abnormality of a certain regional controller. When the high-level assisted driving system as a whole is abnormal, it can ensure that the human driver can completely take over the control of the vehicle to ensure driving safety.

[0199] According to the embodiment of the present application, a seat adjustment method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0200] In this embodiment, a seat adjustment method is provided for a vehicle using an electronic and electrical architecture as shown in Figure 1 , the method can be particularly applied to the central computing platform of the vehicle, Figure 15 , the flowchart of the seat adjustment method according to the embodiment of the present application, as shown in Figure 15 , the flowchart includes the following steps:

[0201] Step S1501, obtaining a current signal of a steering assist motor of the vehicle.

[0202] Specifically, the above step S1501 includes receiving a current signal of a steering assist motor sent by a target power distribution and data transmission module through Ethernet, the current signal being a current signal collected by a target sensing component corresponding to the steering assist motor from a steering assist motor driver, the current signal being uploaded to the target power distribution and data transmission module through a target edge node connected to the target sensing component. Wherein, the target sensing component is a current collecting device such as a current sensor, the target sensing component is arranged on the steering assist motor driver, the target edge node is arranged in the area where the steering assist motor is located, the target power distribution and data transmission module is arranged in the same power distribution and communication area as the steering assist motor, and the transmission of the current signal is carried out in the form of Ethernet communication through the target power distribution and data transmission module.

[0203] Exemplarily, during the driving of the vehicle, the sensing component collects the current signal from the steering assist motor driver in real time, transmits it to the electric & data hub through the corresponding edge node, and then uploads it to the central computing platform for processing by the electric & data hub through Ethernet. Considering that the roughness change of the road surface will directly cause the load fluctuation of the motor when the steering assist motor is working, and then produce a small current fluctuation, in order to accurately capture this fluctuation, the collection period can be flexibly set, such as 30 , and the collection object is the three-phase current of the motor; if the three-phase current has been converted to d / q axis current (a common current form for subsequent control and calculation), the d / q axis current can also be collected directly.

[0204] In practical applications, after the current signal is acquired, it also needs to be preprocessed: such as filtering the high-frequency noise (such as the noise generated by motor electromagnetic interference) in the current signal by using a low-pass filter, and then smoothing the filtered signal by using a sliding average algorithm to eliminate the influence of instantaneous pulse interference on subsequent analysis, and to ensure that the current signal used for feature extraction finally accurately reflects the changes caused by road roughness.

[0205] Step S1502, extracting feature data related to road roughness from the current signal.

[0206] Specifically, the feature data related to road roughness can be extracted from time domain, frequency domain, envelope and other multiple dimensions based on the preprocessed current signal, and the influence of road roughness on the current signal is captured through multiple dimensions, so as to avoid missing key information by single dimension feature.

[0207] Step S1503, classifying the feature data to determine the road surface type of the current driving road surface of the vehicle.

[0208] Specifically, the feature comparison can be performed by using the historical feature data extracted during the historical driving of the vehicle on different road surface types and the current feature data, the road surface type corresponding to the historical feature data with the highest feature similarity is determined as the road surface type of the current driving road surface, and the historical feature data can also be trained by using a deep learning method, and the trained model is used to classify the current feature data.

[0209] Step S1504, in response to the road surface type being a roughness abnormal road surface, determining the relative position relationship between the roughness abnormal road surface and the vehicle.

[0210] Specifically, when the road surface type is determined to be a roughness abnormal road surface such as a road shoulder or a lane line, a position judgment module is started, the relative position relationship between the abnormal road surface and the vehicle is determined by comparing the vibration signals collected by the left and right side vibration sensors of the vehicle, in addition, the pose of the vehicle body can also be collected by using an inertial measurement unit, and the pose of the vehicle body will fluctuate obviously when the roughness is abnormal, the fluctuation direction of the pose is consistent with the relative position relationship between the roughness abnormal road surface and the vehicle, so that the relative position relationship between the roughness abnormal road surface and the vehicle is determined by analyzing the change of the pose of the vehicle body, and the specific analysis process is the prior art, which will not be described in detail here.

[0211] Step S1505, based on the relative position relationship, adjusting at least one seat in the vehicle to increase the support force of the seat in the direction of the roughness abnormal road surface.

[0212] Specifically, the central computing platform generates corresponding seat adjustment instructions according to the determined relative position relationship, and transmits the seat adjustment instructions to the electric & numerical hub through Ethernet. The electric & numerical hub transmits the seat adjustment instructions to the motors corresponding to the seat positions through corresponding edge nodes, so as to drive and control the motors corresponding to the seat positions, such as driving the cushion motor, the waist support motor and the side wing motor to work. Thus, the mechanical structure is adjusted by the motor to increase the support force in the direction of the abnormal road surface, and the discomfort of the driver caused by the road bump is relieved. Among them, the seat to be adjusted can be flexibly set according to the configuration requirements of the vehicle, such as adjusting only the seat of the main driver position for a low configuration version vehicle, adjusting the seats of the main and vice driver positions at the same time for a medium configuration version vehicle, and adjusting all the seats of the vehicle for a high configuration version vehicle. This is only an example, and the present application is not limited thereto.

[0213] Among them, the cushion motor is a cushion support air pump motor, the waist support motor is a seat waist support air pump motor, and the side wing motor is a side wing support air pump motor. There are two side wing support air pump motors on each seat, which can make the entire seat actively fit the body posture of the driver, so that the driver feels the protection action of the vehicle after the wheels press on the road shoulder or the lane line, forming an intuitive tactile care.

[0214] In this embodiment, the steering assist motor current signal is obtained, the roughness related feature data of the road surface is extracted and classified to determine the type of the road surface. When the roughness abnormal road surface is identified, the seat support force is adjusted according to the relative position of the vehicle. This scheme does not need to rely on steering operation, can actively perceive various rough road surfaces, and can adjust the seat support force in the corresponding direction, effectively relieving the discomfort of the passenger on one side of the rough road surface, significantly improving the riding experience and comfort in different road conditions, and improving the driving experience of the user.

[0215] In this embodiment, a seat adjustment method is provided, which is applied to a vehicle adopting an electronic and electrical architecture as shown in Figure 1 The method can be specifically applied to the central computing platform of the vehicle, Figure 16 The flowchart of the seat adjustment method according to the embodiment of the present application is shown in Figure 16 The flowchart includes the following steps:

[0216] In step S1601, the current signal of the steering assist motor of the vehicle is obtained. For details, refer to the related description of step S1501 as shown in Figure 15 The detailed description is not repeated here.

[0217] In step S1602, the feature data related to the roughness of the road surface is extracted from the current signal.

[0218] Specifically, the step S1602 includes:

[0219] Step S16021, the root mean square value, peak value, peak-to-peak value of the current signal is calculated to obtain the time domain feature.

[0220] Specifically, the root mean square value, peak value, peak-to-peak value of the current signal in a preset time window (such as 50ms) is calculated. The root mean square value can reflect the average energy size of the current signal, the rougher the road surface, the more intense the motor load fluctuation, and the larger the root mean square value; the peak value is the maximum value of the current signal in the time window, which can reflect the instantaneous load impact strength; the peak-to-peak value is the difference between the peak value and the valley value, which can directly reflect the fluctuation amplitude of the current signal, and is also positively correlated with the road roughness.

[0221] Step S16022, the current signal is converted to frequency domain, and the energy of the preset frequency band is extracted to obtain the frequency domain feature.

[0222] The preset frequency band is the frequency range corresponding to the roughness abnormal road surface, which can be determined through a large number of experiments.

[0223] Specifically, the short-time Fourier transform (STFT) is performed on the preprocessed current signal to convert the time domain signal to the frequency domain signal. In order to accurately capture the impact event when the wheel presses the roughness abnormal road surface such as the road shoulder or the lane line, the analysis period of STFT is set to 100ms (which can completely cover the duration of a typical impact event), and the adjacent analysis periods overlap by 50% to avoid missing the impact signal; at the same time, the frequency resolution is set to 25Hz to ensure that the signal components of different frequencies can be clearly distinguished. Through experiments, it is determined that the frequency range corresponding to the vibration caused by the roughness abnormal road surface such as the road shoulder and the lane line is 50-200Hz, and then the signal energy in this frequency band is extracted as the frequency domain feature. The higher the energy value, the more likely the vehicle is to travel on the roughness abnormal road surface such as the road shoulder or the lane line.

[0224] Step S16023, envelope analysis is performed on the current signal to extract the amplitude envelope to obtain the envelope feature.

[0225] Specifically, the Hilbert transform can be used to perform envelope analysis on the current signal. First, the analytic signal of the signal is obtained by Hilbert transform, and then the modulus of the analytic signal is calculated to obtain the amplitude envelope of the current signal. The amplitude envelope can highlight the impact component in the current signal. When the wheel presses the road protrusion (such as the edge of the road shoulder or the protruding part of the lane line), the amplitude envelope will have obvious sharp peaks. By identifying these sharp peaks, the impact event can be accurately located, which further assists in judging the road roughness.

[0226] The embodiment realizes multi-dimensional capture of signal information related to the road roughness by extracting time domain features (root mean square value, peak value, peak-to-peak value), frequency domain features (preset frequency band energy) and envelope features (amplitude envelope) from the current signal respectively. The time domain features can intuitively reflect the intensity change of the current signal, the frequency domain features can accurately lock the frequency range corresponding to the roughness abnormal road, and the envelope features can highlight the impact events in the current signal. The combination of the three makes the extracted feature data more comprehensive and accurate, provides reliable data support for subsequent accurate classification of road types, reduces the misjudgment of road types caused by single feature, and ensures the accuracy of subsequent seat adjustment.

[0227] In step S1603, the feature data is classified to determine the road type of the current driving road of the vehicle.

[0228] Specifically, the above step S1603 inputs the feature data into a pre-trained road type classification model to obtain the road type of the current driving road of the vehicle.

[0229] The road type classification model is used to predict the road type based on the feature data related to the road roughness, and the road type at least includes a road shoulder, a lane line and a normal road.

[0230] Further, the above road type classification model can be trained by using a support vector machine (SVM), a decision tree or a simple neural network. The specific training process includes: first, a large amount of feature data in different road scenes (including normal asphalt road, cement road, road shoulder, worn lane line, intact lane line, etc.) is collected, the data is labeled with road types, 70% of the data is used as a training set and 30% is used as a test set, the training set is used to train the SVM model, the kernel function parameter (such as radial basis kernel function) is adjusted to optimize the model performance, and the classification accuracy of the model on the test set is above 95%. The output result of the model includes three types of normal road, road shoulder and lane line, which can accurately distinguish different road types and provide a basis for subsequent judgment of whether to adjust the seat.

[0231] The embodiment determines the road type by inputting the feature data into a pre-trained road type classification model, and the model can distinguish between a road shoulder, a lane line and a normal road. The pre-trained model has stronger pattern recognition ability after being trained by a large amount of data, can more accurately identify different types of roughness abnormal roads, avoids confusing road shoulders, lane lines and normal roads, and can also accurately distinguish different abnormal road types, thereby providing a basis for subsequent development of more suitable seat adjustment strategies according to different road types, and further improving the pertinence and rationality of seat adjustment.

[0232] In step S1604, when the road type is a roughness abnormal road, the relative position relationship between the roughness abnormal road and the vehicle is determined.

[0233] Specifically, the step S1604 includes:

[0234] Step S16041, acquiring vibration signals collected by two vibration sensors on the vehicle.

[0235] The two vibration sensors are respectively arranged at the left side region and the right side region of the vehicle. For example, the vibration sensors are respectively arranged at the left side and the right side of the front suspension of the vehicle to collect vibration signals to obtain vibration acceleration.

[0236] Step S16042, determining a relative position relationship between the roughness abnormal road and the vehicle based on the size and difference of the vibration signals collected by the two vibration sensors on the vehicle.

[0237] The relative position relationship includes that the roughness abnormal road is located at the left side, the right side, or both sides of the vehicle.

[0238] Specifically, when the left front wheel presses the roughness abnormal road, the vibration acceleration peak value collected by the left side vibration sensor is 30%-50% higher than that of the right side, and the signal arrival time is 5-10 ms earlier than that of the right side; conversely, when the right front wheel presses the roughness abnormal road, the vibration acceleration peak value of the right side vibration sensor is higher, and the signal arrival time is earlier. By comparing the peak value size and difference of the signals of the two side vibration sensors, it can be accurately judged whether the abnormal road is located at the left side or the right side of the vehicle. Of course, if the peak value arrival time and size of both sides are similar, it is considered that the roughness abnormal road is located at both sides of the vehicle.

[0239] For example, after judging that the road type is a road shoulder, it is analyzed that the vibration acceleration peak value collected by the left side vibration sensor is 2.5 m / s², the right side is 1.2 m / s², and the left side signal arrives 8 ms earlier than the right side. It is determined that the road shoulder is located at the left side of the vehicle.

[0240] The embodiment determines the relative position relationship (left, right, and both sides) between the roughness abnormal road and the vehicle based on the size and difference of the vibration signals of the left and right side vibration sensors of the vehicle. This method can accurately locate the position of the abnormal road, and after determining the position, the subsequent seat adjustment is more directional, and only the seat support force in the direction of the abnormal road is adjusted, avoiding resource waste and poor adjustment effect caused by indiscriminate adjustment, and improving the accuracy and efficiency of seat adjustment.

[0241] Step S1605, based on the relative position relationship, adjusting at least one seat in the vehicle to increase the support force of the seat in the direction of the roughness abnormal road.

[0242] Specifically, the step S1605 includes:

[0243] Step S16051, when the relative position relationship is that the roughness abnormal road surface is located on the left side of the vehicle, the seat cushion, waist support and right side wing motors of the seat are activated.

[0244] Step S16052, when the relative position relationship is that the roughness abnormal road surface is located on the right side of the vehicle, the seat cushion, waist support and left side wing motors of the seat are activated.

[0245] Step S16053, when the relative position relationship is that the roughness abnormal road surface is located on both sides of the vehicle, the seat cushion, waist support, left side wing and right side wing motors of the seat are activated.

[0246] Exemplarily, if the abnormal road surface is located on the left side of the vehicle (the left front wheel presses the abnormal road surface), the seat cushion motor, waist support motor and right side wing motor of the seat are activated, for example, the seat cushion motor drives the right side of the seat cushion to protrude upward by 5-8 mm, increases the right side hip support force; the waist support motor drives the right side of the waist support to push forward by 3-5 mm, fits the right side of the driver's waist; the right side wing motor drives the left side wing to tighten inward by 2-3 cm, wraps the right side of the driver's body, and reduces the body roll caused by the bump. If the abnormal road surface is located on the right side of the vehicle (the right front wheel presses the abnormal road surface), the seat cushion motor, waist support motor and left side wing motor are activated, and the left side support structure of the seat is adjusted according to the same amplitude, and the left side support force is increased. If the abnormal road surface is located on both sides of the vehicle, the seat cushion motor, waist support motor, left side wing motor and right side wing motor are activated at the same time, so as to adjust the overall support structure of the seat at the same time, and increase the support force on both sides.

[0247] It should be noted that, in actual application, in order to avoid the relative position between the roughness abnormal road surface and the vehicle changing in a short time, such as the vehicle changing from the left side wheel pressing the lane line to the right side wheel pressing the lane line, after the above position relationship is determined, the seat cushion motor, waist support motor, left side wing motor and right side wing motor of the seat can be directly activated, so as to provide the greatest protection to the driver and passenger, and reduce the bump feeling.

[0248] The embodiment activates the motors (seat cushion, waist support, left side and / or right side wing motor) of different parts of the seat according to different relative position relationships (left, right, both sides) between the vehicle and the roughness abnormal road surface. This precise corresponding adjustment mode can provide more human body fitting support force on the direction of the abnormal road surface. For example, when the left side is abnormal, the right side wing motor is activated, which can effectively balance the discomfort brought by the left side rough road, and provide targeted support protection for the passenger. Compared with non-discriminatory adjustment, it can more accurately relieve the discomfort of the passenger in a specific direction, and further improve the comfort and safety of the ride.

[0249] In the embodiment, a seat adjustment method is provided, which is applied to a vehicle. Figure 1As shown in the electronic and electrical architecture, the method can be particularly applied to a central computing platform of a vehicle, Figure 17 is a flowchart of a seat adjustment method according to an embodiment of the application, as shown, the flow includes the following steps: Figure 17

[0250] Step S1701, monitor the current vehicle speed and / or the starting state of the turn signal.

[0251] Specifically, the vehicle speed signal can be collected through the vehicle CAN bus, and the collection period of the speed signal can be set as needed, such as 10ms, which ensures that the change of the vehicle speed can be reflected in real time, and the system operation load is not increased due to too high sampling frequency. The starting state of the turn signal is determined by reading the turn signal control signal output by the body control module, and the signal sampling period can be set as needed, such as 50ms, which can quickly capture the on-off change of the turn signal, and will not increase the system resource consumption due to too high sampling frequency.

[0252] Step S1702, when the current vehicle speed is higher than the preset vehicle speed threshold, and / or the turn signal is in the unstarted state, step S1704 is executed.

[0253] Exemplarily, the preset vehicle speed threshold can be set according to the influence of road roughness on the driving experience, and in this embodiment, it is explained by taking the preset vehicle speed threshold of 40km / h as an example. When driving at low speed (such as below 40km / h), the influence of road roughness on the driver's riding experience is small, and the driver's control of the vehicle is more precise, so the seat adjustment function does not need to be activated; when the vehicle speed is higher than 40km / h, the road is prone to cause obvious bumps, and the system needs to be involved. If the turn signal is started, it means that the driver has a clear operation intention, and it is normal to press the lane line, and the seat adjustment function under the roughness abnormal road is not activated, but the existing seat adjustment function during the steering process of the vehicle can be normally triggered, and if the turn signal is not started, it means that the driver has no steering or lane changing intention, and the seat adjustment function needs to be activated.

[0254] In actual application, in order to ensure the accuracy of the activation of the seat adjustment function, the vehicle speed and the starting state of the turn signal need to be jointly detected, and only when both meet the triggering condition, the seat adjustment function will be activated.

[0255] Step S1703, when the current vehicle speed is not higher than the preset vehicle speed threshold, and / or the turn signal is in the started state, return to step S1701.

[0256] ​Exemplarily, when the vehicle speed is less than or equal to 40 km / h, no matter the state of the turn signal, return to step S1701 to continue monitoring, at this time, the road surface has little effect, and the subsequent process does not need to be started; when the turn signal is in the starting state, no matter whether the vehicle speed is higher than 40 km / h, return to step S1701, when the driver actively changes lanes, pressing the lane line is normal operation, so the system needs to be temporarily inhibited from further processing, and then re-judgment is made after the turn signal is turned off.

[0257] The embodiment controls the execution of seat adjustment by monitoring the vehicle speed and the state of the turn signal. The current signal is obtained to execute the seat adjustment logic only when the vehicle speed is higher than a preset threshold and / or the turn signal is not started, otherwise, return to the monitoring step. At low speed (such as parking), the road roughness has little effect on the occupant, and seat adjustment is not needed, which can avoid invalid operation of the system at low speed and save energy consumption; when the turn signal is started, the driver actively changes lanes, pressing the lane line and the like is normal operation, and seat adjustment does not need to be triggered. This setting makes the seat adjustment work only in the scene that really needs it, improves the rationality and efficiency of system operation, and avoids unnecessary adjustment affecting the driving and riding experience.

[0258] In step S1704, the current signal of the steering assist motor of the vehicle is obtained. For details, refer to the related description of step S1601 shown in FIG. 16, which will not be repeated here. Figure 16

[0259] In step S1705, the feature data related to the road roughness is extracted from the current signal. For details, refer to the related description of step S1602 shown in FIG. 16, which will not be repeated here. Figure 16

[0260] In step S1706, whether the feature values of the time domain feature, the frequency domain feature and the envelope feature respectively exceed the feature threshold values of the corresponding features is detected.

[0261] The feature threshold value is the minimum feature value that characterizes the event of the vehicle driving on the roughness abnormal road surface. Specifically, the feature of each dimension corresponds to the setting of the corresponding feature threshold value, which is the critical value for judging whether the roughness abnormal road surface event occurs. When the feature value exceeds the threshold value, it indicates that the change of the current signal has reached the judgment standard of the abnormal road surface, and the event needs to be further confirmed; when the feature value does not exceed the threshold value, it is determined that the road surface is normal, and no subsequent operation is needed. When specifically setting, the statistical amount (mean + 3 times standard deviation) of historical data can be adaptively adjusted to avoid false positives of the fixed threshold value in different road conditions.

[0262] ​​Exemplarily, the time-domain feature threshold value can be based on the current signal statistics of a large number of normal road driving, such as the root mean square value threshold being set to 1.2 A, the peak value threshold being set to 1.8 A, and the peak-to-peak value threshold being set to 1.5 A. The frequency-domain feature threshold value can be set to 25 dB by referring to the energy value (usually ≤25 dB) of the 50-200 Hz frequency band on the normal road, and the frequency-domain feature threshold value is set to 25 dB, when the wheel presses the road shoulder / road line, the energy of the frequency band will be significantly increased, exceeding 25 dB; the envelope feature threshold value can be based on the peak value (usually ≤0.8 V) of the amplitude envelope of the normal road, and the envelope feature threshold value is set to 0.8 V, and the impact event caused by the road bump will cause the peak value to exceed the threshold.

[0263] Specifically, the determination of whether the feature value of the time-domain feature, the frequency-domain feature, and the envelope feature exceeds the feature threshold value of the corresponding feature comprises:

[0264] Step d1, acquiring the current speed of the vehicle.

[0265] Step d2, determining the feature threshold value corresponding to each of the time-domain feature, the frequency-domain feature, and the envelope feature based on the current speed, and the feature threshold value corresponding to each of the time-domain feature, the frequency-domain feature, and the envelope feature is negatively correlated with the current speed.

[0266] Specifically, the higher the vehicle speed, the higher the sensitivity of the motor to road roughness, and slight road changes will cause the feature value to fluctuate significantly, so the threshold value needs to be lowered (for example, when the vehicle speed is 60 km / h, the root mean square value threshold is lowered to 1.1 A); the lower the vehicle speed, the lower the sensitivity of the motor, and the threshold value needs to be increased (for example, when the vehicle speed is 45 km / h, the root mean square value threshold is increased to 1.3 A) to avoid misjudgment at different speeds.

[0267] The embodiment determines the feature threshold value corresponding to each feature by combining the current speed of the vehicle, and the threshold value is negatively correlated with the vehicle speed. Because the degree of influence of the steering assist motor current signal on road roughness is different at different speeds, the higher the speed, the slighter the road roughness change that can cause the current signal to fluctuate significantly, and a lower threshold value can capture abnormalities in time; the lower the speed, only a more severe road roughness change will cause the current signal to fluctuate significantly, and a higher threshold value can avoid misjudgment. This dynamic threshold setting method makes the feature detection more suitable for the actual speed, and improves the accuracy of abnormal road detection.

[0268] Step S1707, when any feature value exceeds the feature threshold value of the corresponding feature, it is determined that the vehicle is driving on a roughness abnormal road event occurs, and step S1709 is performed.

[0269] Specifically, as long as any of the feature values in the above three dimensions of time domain, frequency domain and envelope exceeds the corresponding threshold, it is determined that the vehicle is driving on a roughness abnormal road event. Since some road abnormalities (such as slight lane line wear) may only cause the frequency domain feature to exceed the threshold, and the time domain and envelope features do not change significantly; some road abnormalities (such as road shoulder protrusions) may cause the features in the three dimensions to exceed the threshold. Thus, various abnormal scenarios can be covered to the greatest extent to ensure that there is no omission. After determining that an abnormal event occurs, there is no need to further wait for the detection results of other feature values, and step S1709 is directly executed to enter the road type classification link, thereby shortening the event response time and gaining time for subsequent seat adjustment.

[0270] In actual application, before executing the above step S1709, the seat adjustment method further comprises:

[0271] Step e1, when it is determined that the vehicle is driving on a roughness abnormal road event, returning to step S1704 again until the cumulative duration or cumulative number of consecutive determinations that the vehicle is driving on a roughness abnormal road event reaches a preset duration or a preset number, and then executing step S1709.

[0272] Specifically, after determining in step S1707 that the vehicle is driving on a roughness abnormal road event, instead of directly executing step S1709, an abnormal event accumulation verification process is started, and step S1704 is returned to again. The current signal of the steering assist motor is continuously collected, and steps S1705, S1706 and S1707 are repeated until the cumulative duration of consecutive determinations of roughness abnormal road events reaches a preset duration or the cumulative number reaches a preset number, and then step S1709 is executed.

[0273] Exemplarily, the preset duration can be set to 0.5s, and the preset number is set to 3 times. A single abnormal event determination may be caused by transient interference (such as a short current fluctuation caused by a wheel pressing a small stone), and is not a continuous roughness abnormal road. The cumulative duration of 0.5s can cover the typical time of the wheel continuously pressing the roughness abnormal road surface such as the lane line / road shoulder, to ensure the capture of continuous abnormalities. At the same time, considering the current signal collection and processing period, the preset number can complement the preset duration to avoid verification errors caused by single determination period deviation. In actual application, a single parameter verification (such as only cumulative duration) can also be selected according to the actual application scenario, and the present application is not limited thereto.

[0274] The embodiment needs to continuously detect the cumulative duration or number of the event to reach the standard before classifying the road surface after determining that the rough road surface event occurs. This setting can effectively filter out false judgments caused by transient and accidental current signal fluctuations, such as signal fluctuations caused by the vehicle briefly pressing over small stones, which are not truly sustained rough road surface conditions. Through cumulative detection, it is ensured that only when the roughness abnormal road surface is truly sustained, the subsequent process is started, unnecessary seat adjustment caused by single false judgment is avoided, the reliability and stability of the system are improved, and the passenger riding experience is not disturbed.

[0275] Step S1708, when none of the feature values exceeds the feature threshold of the corresponding feature, return to step S1704.

[0276] Specifically, if the feature values of the above three dimensions do not exceed the corresponding threshold, it indicates that the current road surface is a normal road surface, and the subsequent road surface classification and seat adjustment process does not need to be started. At this time, return to step S1704, continue to collect the current signal of the steering assist motor, and enter the next round of signal analysis cycle. Thus, invalid operation of the system on the normal road surface can be avoided, CPU resource consumption and power consumption are reduced, and at the same time, the system continuously monitors the road surface state, and once the subsequent road surface is abnormal, the subsequent process can be triggered in time.

[0277] Before classifying the road surface type, the embodiment first detects whether the time domain, frequency domain, and envelope feature values exceed the corresponding feature threshold. Only when any feature value exceeds the limit, the classification step is continued, otherwise the current signal acquisition step is returned. This step can filter out signal data without abnormalities in advance, avoid unnecessary classification processing of normal road surface signals, reduce system operation amount, and improve processing efficiency. At the same time, by preliminarily judging the abnormal event through the feature threshold, some interference signals can be excluded in advance, the false judgment probability in the subsequent classification process is reduced, and only when the roughness abnormal road surface really exists, the seat adjustment is performed, and the influence of false adjustment on the riding experience is avoided.

[0278] Step S1709, classifying the feature data to determine the road surface type of the current driving road surface of the vehicle. For details, refer to the related description of step S1603 as shown in Figure 16 The detailed content is not described here.

[0279] Step S1710, in response to the road surface type being a roughness abnormal road surface, determining the relative position relationship between the roughness abnormal road surface and the vehicle. For details, refer to the related description of step S1604 as shown in Figure 16 The detailed content is not described here.

[0280] Step S1711, based on the relative position relationship, adjusting at least one seat in the vehicle to increase the support force of the seat in the direction of the roughness abnormal road surface. For details, refer to the related description of step S1605 as shown in Figure 16The description related to the illustrated step S1605 will not be repeated here.

[0281] Figure 18 A structural schematic diagram of a vehicle is provided for an embodiment of the present application.

[0282] Reference will now be made in detail to Figure 18 which shows a structural schematic diagram of a vehicle suitable for implementing an embodiment of the present application. The vehicle can include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 1801, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 1802 or programs loaded from a storage 1808 into a random access memory (RAM) 1803. Various programs and data required for vehicle operation are also stored in the RAM 1803. The processor 1801, the ROM 1802, and the RAM 1803 are connected to each other through a bus 1804. An input / output (I / O) interface 1805 is also connected to the bus 1804.

[0283] Generally, the following devices can be connected to the I / O interface 1805: an input device 1806 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 1807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage 1808 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1809. The communication device 1809 can allow the vehicle to communicate wirelessly or by wire with other devices to exchange data. Although Figure 18 The vehicle is shown with various devices, but it should be understood that all of the shown devices are not required to be implemented or possessed, and more or fewer devices can be alternatively implemented or possessed.

[0284] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for executing the method shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device 1809, or installed from the storage 1808, or installed from the ROM 1802. When the computer program is executed by the processor 1801, the above-mentioned functions defined in the function backup method or the seat adjustment method of embodiments of the present application are performed.

[0285] Figure 18 The vehicle shown is merely an example and should not impose any limitation on the functions and use range of embodiments of the present application.

[0286] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded to a local storage medium through network, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the above-mentioned backup method or seat adjustment method is implemented.

[0287] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, the operation of the computer can invoke or provide the method and / or technical solutions according to the present application. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source file, executable file, installation package file, etc. Correspondingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0288] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. An electronic and electrical architecture applied to an artificial intelligence sports device, characterized in that, The electronic and electrical architecture comprises a central computing platform, a power supply component, a plurality of power distribution and data transmission modules, a plurality of edge nodes and a plurality of sensing and interaction components, wherein, The edge node is connected with at least a first sensing and interaction component, and the first sensing and interaction component is a sensing and interaction component in the same distribution area in the device; The power distribution and data transmission module is connected with at least a first edge node, and the first edge node is an edge node connected with sensing and interaction components in the same power distribution and communication area in the device; The power distribution and data transmission module is also connected with the central computing platform and the power supply component respectively, for realizing data interaction between the central computing platform and each sensing and interaction component through the edge node, and for distributing power in the electronic and electrical architecture by the power supply component.

2. The electronic and electrical architecture according to claim 1, characterized in that, The sensing and interaction component comprises a sensing component and an execution component; Each edge node collects operation data of the sensing components in the same distribution area and transmits the operation data to the corresponding power distribution and data transmission module; The power distribution and data transmission module transmits the operation data to the central computing platform; The central computing platform processes the operation data transmitted by each power distribution and data transmission module, generates control instructions corresponding to the first execution component, and transmits the control instructions to the first edge node through the first power distribution and data transmission module connected with the first edge node, and the first edge node is an edge node connected with the first execution component.

3. The electronic and electrical architecture of claim 1, wherein, The power distribution and data transmission module is also connected with electronic control units belonging to the same device function in the device and other second sensing and interaction components not connected with the edge node, for realizing data interaction between the electronic control units, the second sensing and interaction components and the central computing platform; The power distribution and data transmission module is also used for realizing data exchange between each electronic control unit connected with the power distribution and data transmission module.

4. The electronic and electrical architecture according to claim 1, characterized in that, The central computing platform is connected with at least one sensing and interaction component, for realizing redundant data interaction between the central computing platform and the sensing and interaction component.

5. The electronic and electrical architecture according to claim 1, characterized in that, The central computing platform and each power distribution and data transmission module are connected through Ethernet communication to form a ring-shaped Ethernet communication connection structure.

6. The electronic and electrical architecture according to claim 3, characterized in that, The power supply component comprises a main power supply and a redundant power supply; Each power distribution and data transmission module is connected in sequence to form a ring network, and the main power supply and the redundant power supply are arranged on the ring network respectively; The power distribution and data transmission module distributes the main power supply or the redundant power supply to each structure connected with the power distribution and data transmission module, and the structure comprises a central computing platform, an edge node, an electronic control unit and a second sensing and interaction component; The edge node distributes the power supply distributed by the power distribution and data transmission module to each sensing and interaction component connected with the edge node.

7. The electronic and electrical architecture according to claim 3, characterized in that, The power distribution and data transmission module comprises a power and data coupling processing circuit, which is configured to perform coupling processing on power provided by the power component and data received by the power distribution and data transmission module, and output the coupling processing result to a corresponding connection object through a twisted pair, wherein the connection object comprises a central computing platform, an edge node, an electronic control unit and a second perception and interaction component. The connection object is provided with a power and data decoupling circuit, which is configured to decouple the coupling processing result to obtain power and transmission data.

8. The electronic and electrical architecture according to any one of claims 1-6, characterized in that, The central computing platform comprises a main computing center and at least one auxiliary computing center, and the main computing center and the auxiliary computing center are redundant backups of each other.

9. A functional backup method characterized by comprising: The method is applied to a vehicle, the vehicle adopts the electronic and electrical architecture of claim 8, and the method comprises: Dividing software function modules of vehicle control function software based on driving functions of the vehicle to obtain a plurality of software function modules, and deploying each software function module and a corresponding redundant backup module in different computing centers of the central computing platform, wherein the computing centers comprise a main computing center and at least one auxiliary computing center; Generating a software scheduling table based on the calling relationship between software functions in each software function module, wherein the software scheduling table comprises deployment address information of the software function module corresponding to the redundant backup module, and a scheduling link representing the scheduling order between software functions in the software function module, so that each software function module is scheduled and runs according to the scheduling link; When detecting that any software function module has an exception during operation, updating the scheduling link based on the software function associated with the exception and the deployment address information to obtain an updated scheduling link; Controlling the software function module with the exception to be scheduled and run according to the updated scheduling link.

10. The method of claim 9, wherein, The updating of the scheduling link based on the software function associated with the exception and the deployment address information to obtain an updated scheduling link comprises: Determining a scheduling link update mode based on the function type of the software function associated with the exception, and / or the quantity relationship between the first number of the software function associated with the exception and the total number of software functions contained in the software function module with the exception; Updating the scheduling link based on the scheduling link update mode and the deployment address information to obtain an updated scheduling link.

11. The method of claim 10, wherein, The determination of the scheduling link update mode based on the function type of the software function associated with the exception, and / or the quantity relationship between the first number of the software function associated with the exception and the total number of software functions contained in the software function module with the exception comprises: When the function type of the software function associated with the exception is a key function function, and / or the first proportion of the first number to the total number of software functions exceeds a first preset proportion value, determining that the scheduling link update mode is a function update mode; the key function function is a function that implements the corresponding core function of the software function module with the exception. When the function type of the software function associated with the exception is not a critical function, and / or the first proportion of the first quantity to the total number of software functions does not exceed a first preset proportion value, it is determined that the scheduling link update mode is a function update mode.

12. The method of claim 11, wherein, When the scheduling link update mode is a function update mode, the scheduling link is updated based on the scheduling link update mode and the deployment address information to obtain an updated scheduling link, including: Based on the deployment address information, the calling interface address of the redundant software function corresponding to the software function associated with the exception is determined; The calling interface address of the software function associated with the exception in the scheduling link is replaced with the calling interface address of the corresponding redundant software function to obtain the updated scheduling link.

13. The method of claim 11, wherein, When the scheduling link update mode is a function update mode, the scheduling link is updated based on the scheduling link update mode and the deployment address information to obtain an updated scheduling link, including: The target sub-software function module corresponding to the software function associated with the exception is determined, the software function module includes a plurality of sub-software function modules, and the target sub-software function module is at least one sub-software function module in the software function module with the exception; Based on the deployment address information, the calling interface address of the target backup sub-software function module corresponding to the target sub-software function module is determined; The calling interface address of the target sub-software function module in the scheduling link is replaced with the calling interface address of the corresponding target backup sub-software function module to obtain the updated scheduling link.

14. The method of claim 13, wherein, After determining the target sub-software function module corresponding to the software function associated with the exception, the method further includes: The second quantity of corresponding sub-software function modules in the target sub-software function module is determined; When the second proportion of the second quantity to the total number of sub-software function modules included in the software function module with the exception exceeds a second preset proportion value, if the current driving mode of the vehicle is an intelligent driving mode, the current driving mode is switched from the intelligent driving mode to the manual driving mode, and the corresponding redundant backup module is switched to run based on the deployment address information; When the second proportion of the second quantity to the total number of sub-software function modules included in the software function module with the exception does not exceed a second preset proportion value, the step of determining the calling interface address of the target backup sub-software function module corresponding to the target sub-software function module based on the deployment address information is performed.

15. The method of claim 9, wherein, The method further includes: During the running of each software function module, the running state of the software function included in the software function module is monitored, and the running state includes at least one of stack usage, static variable and / or global variable usage, array access out-of-bounds, function running time, and being called by multiple parties; Based on the function logic corresponding to the software function module, it is determined whether the running state of each software function is abnormal; When an abnormality exists in a running state of at least one software function, it is determined that the software function module is abnormal, and the software function that is abnormal is marked to obtain a software function associated with the abnormality.

16. The method of claim 9, wherein, The method further includes: During the process of controlling the software function module that is abnormal to run according to the updated scheduling link, when the software function module that is abnormal returns to normal, the updated scheduling link is restored to the initial state, and the running is continued according to the scheduling link in the initial state.

17. The method according to any one of claims 9-16, characterized in that, The method further includes: During the process of controlling the software function module that is abnormal to run according to the updated scheduling link, if it is monitored that the software function module that is abnormal appears abnormal again, it is determined whether the software function associated with the abnormality again is the same as the software function associated with the last abnormality; When the software function associated with the abnormality again is the same as the software function associated with the last abnormality, it is determined whether the current driving mode of the vehicle is an intelligent driving mode; When the current driving mode of the vehicle is the intelligent driving mode, the current driving mode is switched from the intelligent driving mode to a human driving mode.

18. The method of claim 17, wherein, When the software function associated with the abnormality again is different from the software function associated with the last abnormality, the method further includes: It is determined whether the updated scheduling link contains a redundant software function corresponding to the abnormality of the software function module that appears again; When the updated scheduling link does not contain the redundant software function corresponding to the abnormality of the software function module that appears again, the step of updating the scheduling link based on the software function associated with the abnormality and the deployment address to obtain the updated scheduling link is returned.

19. The method of claim 18, wherein, The method further includes: When the updated scheduling link contains the redundant software function corresponding to the abnormality of the software function module that appears again, the step of determining whether the current driving mode of the vehicle is the intelligent driving mode is executed.

20. A method of adjusting a seat, characterized by, The method is applied to a vehicle, the vehicle adopts the electronic and electrical architecture according to any one of claims 1-8, and the method includes: Obtaining a current signal of a steering assist motor of the vehicle; Extracting feature data related to road roughness from the current signal; Classifying the feature data to determine a road type of a current driving road of the vehicle; In response to the road type being a roughness abnormal road, determining a relative position relationship between the roughness abnormal road and the vehicle; Based on the relative position relationship, adjusting at least one seat in the vehicle to increase support force of the seat in a direction of the roughness abnormal road.

21. The method of claim 20, wherein, The feature data related to road roughness is extracted from the current signal, including: Calculating a root mean square value, a peak value and a peak-to-peak value of the current signal to obtain time domain features; Converting the current signal to a frequency domain, and extracting energy of a preset frequency band to obtain frequency domain features, the preset frequency band being a frequency range corresponding to the roughness abnormal road; Performing envelope analysis on the current signal to extract an amplitude envelope to obtain envelope features.

22. The method of claim 20, wherein, The feature data is classified to determine the road type of the current driving road of the vehicle, including: inputting the feature data into a pre-trained road surface type classification model to obtain a road surface type of a current driving road surface of the vehicle, the road surface type classification model being configured to predict a road surface type based on feature data related to road surface roughness, the road surface type including at least a shoulder, a lane line, and a normal road surface.

23. The method of claim 20, wherein, The determining the relative positional relationship between the roughness abnormal road surface and the vehicle comprises: obtaining vibration signals collected by two vibration sensors on the vehicle, the two vibration sensors being arranged at left and right side regions of the vehicle respectively; determining the relative positional relationship between the roughness abnormal road surface and the vehicle based on the magnitudes and differences of the vibration signals collected by the two vibration sensors on the vehicle, the relative positional relationship including that the roughness abnormal road surface is located at the left side, the right side, or both sides of the vehicle.

24. The method of claim 23, wherein, The adjusting at least one seat in the vehicle based on the relative positional relationship comprises: when the relative positional relationship is that the roughness abnormal road surface is located at the left side of the vehicle, activating a seat cushion, a waist support, and a right side wing motor of the seat; when the relative positional relationship is that the roughness abnormal road surface is located at the right side of the vehicle, activating a seat cushion, a waist support, and a left side wing motor of the seat; when the relative positional relationship is that the roughness abnormal road surface is located at both sides of the vehicle, activating a seat cushion, a waist support, a left side wing motor, and a right side wing motor of the seat.

25. The method of claim 21, wherein, Before the classifying the feature data to determine the road surface type of the current driving road surface of the vehicle, the method further comprises: respectively detecting whether the feature values of the time domain feature, the frequency domain feature, and the envelope feature exceed corresponding feature thresholds, the feature thresholds being minimum feature values representing a vehicle driving on a roughness abnormal road surface event; when any feature value exceeds the corresponding feature threshold, determining that the vehicle driving on the roughness abnormal road surface event occurs, and performing the step of classifying the feature data to determine the road surface type of the current driving road surface of the vehicle; when none of the feature values exceeds the corresponding feature threshold, returning to the step of obtaining the current of the steering assist motor of the vehicle.

26. The method of claim 25, wherein, The method further comprises: obtaining a current vehicle speed of the vehicle; respectively determining the feature thresholds corresponding to the time domain feature, the frequency domain feature, and the envelope feature based on the current vehicle speed, the feature thresholds corresponding to the time domain feature, the frequency domain feature, and the envelope feature being negatively correlated with the current vehicle speed respectively.

27. The method of claim 25, wherein, The method further comprises: when it is determined that the vehicle driving on the roughness abnormal road surface event occurs, returning to the step of obtaining the current of the steering assist motor of the vehicle until the cumulative duration or cumulative frequency of continuously determining that the vehicle driving on the roughness abnormal road surface event occurs reaches a preset duration or a preset frequency, and then performing the step of classifying the feature data to determine the road surface type of the current driving road surface of the vehicle.

28. The method of claim 20, wherein, The obtaining the current of the steering assist motor of the vehicle comprises: The target power distribution and data transmission module receives a current signal of the steering assist motor transmitted by Ethernet, the current signal is a current signal collected by a target sensing component corresponding to the steering assist motor from a steering assist motor driver, and the current signal is uploaded to the target power distribution and data transmission module through a target edge node connected to the target sensing component.

29. The method of any one of claims 20-28, wherein, The method further comprises: monitoring a current vehicle speed and / or a starting state of a steering lamp of the vehicle; when it is monitored that the current vehicle speed is higher than a preset vehicle speed threshold, and / or the steering lamp is in an unstarted state, performing the step of acquiring the current signal of the steering assist motor of the vehicle; when it is monitored that the current vehicle speed is not higher than the preset vehicle speed threshold, and / or the steering lamp is in a started state, returning to the step of monitoring the current vehicle speed and / or the starting state of the steering lamp of the vehicle.

30. A vehicle characterized by The vehicle adopts the electronic and electrical architecture according to any one of claims 1-8.

31. The vehicle of claim 30, wherein, The vehicle comprises: a memory and a processor, which are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the method according to any one of claims 9-29.

32. A computer-readable storage medium, comprising: The computer readable storage medium stores computer instructions for causing a computer to perform the method according to any one of claims 9-29.

33. A computer program product, characterised in that, The computer readable storage medium stores computer instructions for causing a computer to perform the method according to any one of claims 9-29. The computer readable storage medium stores computer instructions for causing a computer to perform the method according to any one of claims 9-29.

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