Agile development method, device and equipment of vehicle air conditioner control software and medium

Abstract

This application provides an agile development method, apparatus, equipment, and medium for vehicle air conditioning control software, effectively addressing several shortcomings of existing vehicle air conditioning software development models. The method includes: constructing a visual model of multiple components of the vehicle air conditioning system in a modeling module according to requirements, and configuring the corresponding visual model by dragging and dropping core air conditioning components and connecting them; a central data dictionary responding to requests from an intelligent code generation engine, providing standardized data entities, enabling the intelligent code generation engine to map the standardized data entities to the visual model through a three-layer mapping architecture to obtain target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer; verifying the target code based on a three-layer verification structure to obtain verification results, and then implementing agile development of the vehicle air conditioning control software based on the verified target code.

Description

Technical Field

[0001] This application relates to the field of software development technology, and more specifically, to agile development methods, apparatus, equipment, and media for vehicle air conditioning control software. Background Technology

[0002] As the automotive industry rapidly evolves towards intelligence and platformization, in-vehicle air conditioning systems have evolved from traditional temperature control devices into intelligent electronic systems that integrate multi-hardware collaboration, complex control strategies, and multi-scenario adaptation. This has significantly increased the complexity and iteration frequency of their software functions. Currently, the development model for in-vehicle air conditioning software still relies on hand-writing code based on requirements documents, resulting in numerous technical challenges.

[0003] Low development efficiency: Software engineers need to manually write a large amount of repetitive code such as low-level drivers, bus signal parsing, and state machine control. Especially when facing multiple vehicle platforms (sedans, SUVs, MPVs) and multiple air conditioning configurations (single-zone, dual-zone, four-zone), the code reuse rate is extremely low, the platform development cost is high, and handwritten code is prone to syntax errors and logical loopholes, making subsequent maintenance difficult.

[0004] Decoupling between requirements and implementation: Requirements are communicated in the form of Natural Language Specifications (SRS), and communication between system engineers, architects, and application engineers relies on documents, which can easily lead to misunderstandings. When requirements change, multiple related code sections need to be manually traced and modified, which can easily result in omissions and inconsistencies between the implemented functionality and the requirements.

[0005] Poor platform compatibility: Different car manufacturers or models often use different ECU hardware platforms (such as NXPS32K144, Infineon AURIX), which have significant differences in computing power, memory resources and interface protocols. Traditional hand-written code needs to be adapted separately for different platforms, resulting in poor portability and making it difficult to meet the platform strategy needs of car manufacturers to cover multiple models with one architecture.

[0006] Quality assurance is lagging behind: Code quality (such as memory safety, logical completeness, and security compliance) depends on later code review and testing verification. The defect discovery cycle is long. Moreover, as a core safety-related system of a vehicle, the vehicle air conditioning system must meet strict safety standards such as ISO26262 ASIL-B. Under the traditional development model, compliance rectification is costly and time-consuming.

[0007] High collaborative development costs: Engineers in different roles are scattered in their respective development stages, lacking a unified collaboration platform, resulting in high communication costs, slow feedback loops, and difficulty in adapting to the rapid iteration and product launch requirements of the automotive industry.

[0008] Therefore, there is an urgent need for a vehicle air conditioning software development technology that can bridge the gap between requirements and implementation, improve development efficiency and code reusability, adapt to multiple platforms, and have built-in security and compliance guarantees, in order to address the many shortcomings of existing technologies. Summary of the Invention

[0009] In view of this, the purpose of this application is to provide an agile development method, apparatus, equipment and medium for vehicle air conditioning control software, which effectively solves the problems of various shortcomings in the existing vehicle air conditioning software development model.

[0010] In a first aspect, embodiments of this application provide an agile development method for vehicle air conditioning control software, applied to an agile development system. The agile development system includes a modeling module, a central data dictionary, and an intelligent code generation engine. The method includes:

[0011] In the modeling module, a visual model of multiple components based on the vehicle air conditioner is built according to the requirements, and the corresponding visual model is configured by dragging and dropping the core components of the air conditioner and connecting them with lines.

[0012] The central data dictionary responds to the request of the intelligent code generation engine by providing standardized data entities, which enable the intelligent code generation engine to map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer;

[0013] A three-layer verification structure based on virtual climate chamber simulation, hardware-in-the-loop verification, and shadow mode verification is used to verify the target code and obtain verification results. Agile development of vehicle air conditioning control software is then achieved based on the verified target code.

[0014] In conjunction with the first aspect, this application provides a first possible implementation of the first aspect, wherein the intelligent code generation engine maps the standardized data entities and the visualization model through a three-layer mapping architecture to obtain target code, including:

[0015] Pre-configured mapping methods include those for the semantic-data mapping layer, the platform adaptation layer, and the security and compliance layer;

[0016] The corresponding mapping method is executed to complete the multi-dimensional mapping between the standardized data entities and the visualization model.

[0017] In conjunction with the first aspect, this application provides a second possible implementation of the first aspect, wherein the three-layer mapping architecture includes at least a semantic-data mapping layer;

[0018] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0019] The high-level control concepts in the visualization model are analyzed using an air conditioning domain semantic analyzer to obtain the analysis results;

[0020] The parsing results are automatically mapped to standardized data entities in the central data dictionary and configuration management library to bind the visualization model to the standardized data entities.

[0021] In conjunction with the first aspect, this application provides a third possible implementation of the first aspect, wherein the three-layer mapping architecture includes at least a platform adaptation layer;

[0022] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0023] Obtain the hardware characteristic parameters of the target ECU platform on the vehicle, and dynamically select the corresponding code generation strategy based on the hardware characteristic parameters;

[0024] Initial code is generated based on the selected code generation strategy and the bound visualization model and standardized data entities, and then the initial code is optimized.

[0025] In conjunction with the first aspect, this application provides a fourth possible implementation of the first aspect, wherein the three-layer mapping architecture includes at least a security compliance layer;

[0026] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0027] Based on the pre-built vehicle air conditioning safety rule library, static verification is performed on the optimized initial code to obtain the static verification results;

[0028] Based on the static verification results, a preset target code generation strategy is executed on the initial code to obtain the target code.

[0029] In conjunction with the first aspect, this application provides a fifth possible implementation of the first aspect, wherein a three-layer verification structure based on virtual climate chamber simulation, hardware-in-the-loop verification, and shadow mode verification verifies the target code to obtain verification results, including:

[0030] A three-layer verification structure is pre-constructed, consisting of virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification;

[0031] The target code is verified based on the three-layer verification structure to obtain the verification results, and dynamic adjustments are made based on the verification results.

[0032] In conjunction with the first aspect, this application provides a sixth possible implementation of the first aspect, wherein the step of constructing a visual model of multiple components based on the vehicle air conditioner in the modeling module according to requirements, and configuring the corresponding visual model by dragging and dropping the core components of the air conditioner and connecting them, includes:

[0033] Load the pre-built library of core components for vehicle air conditioning, which includes a variety of visual components, and drag and drop the target visual component onto the modeling canvas;

[0034] Based on the architecture, functions, and wiring methods of the vehicle air conditioning system, the target visualization components are configured to obtain the corresponding visualization model.

[0035] Secondly, embodiments of this application provide an agile development device for vehicle air conditioning control software, applied to an agile development system. The agile development system includes a modeling module, a central data dictionary, and an intelligent code generation engine. The device includes:

[0036] The building module is used to construct visual models of multiple components based on the vehicle air conditioner according to the requirements in the modeling module, and to configure the corresponding visual models by dragging and dropping the core components of the air conditioner and connecting them with lines.

[0037] The generation module is used by the central data dictionary to respond to the requests of the intelligent code generation engine and provide standardized data entities, so that the intelligent code generation engine can map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer.

[0038] The development module is used to verify the target code based on a three-layer verification structure built on virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification to obtain verification results, so as to realize agile development of vehicle air conditioning control software based on the verified target code.

[0039] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the agile development method for vehicle air conditioning control software described in any one of the claims are executed.

[0040] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the agile development method for vehicle air conditioning control software as described in any one of the claims.

[0041] This application provides an agile development method for vehicle air conditioning control software, applied to an agile development system. The agile development system includes a modeling module, a central data dictionary, and an intelligent code generation engine. In the modeling module, a visual model of multiple components of the vehicle air conditioning system is constructed according to requirements. The corresponding visual model is configured by dragging and dropping core air conditioning components and connecting them. Then, the central data dictionary responds to the intelligent code generation engine's request, providing standardized data entities. The intelligent code generation engine then maps these standardized data entities to the visual model using a three-layer mapping architecture to obtain target code. This three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer. Finally, a three-layer verification structure based on virtual climate chamber simulation, hardware-in-the-loop verification, and shadow mode verification verifies the target code to obtain verification results. Agile development of the vehicle air conditioning control software is then achieved based on the verified target code. Based on the above methods, this application not only solves the various shortcomings of the existing vehicle air conditioning software development model, thus significantly improving development efficiency and shortening the iteration cycle; the visual model can be directly viewed as a structured and unambiguous requirement specification, achieving zero deviation between requirements and implementation and ensuring functional consistency; based on the intelligent code generation engine, this application has strong multi-platform adaptability and significantly improved portability; it also achieves compliance with software quality standards through built-in software quality and security compliance; and it optimizes the collaborative development experience of multiple roles based on the agile development system, reducing communication costs, thereby adapting to multiple scenarios and customized needs and enhancing market responsiveness. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This illustration shows a flowchart of an agile development method for vehicle air conditioning control software provided in an embodiment of this application;

[0044] Figure 2 An architecture diagram of the agile development system provided in an embodiment of this application is shown;

[0045] Figure 3 This illustration shows another flowchart of an agile development method for vehicle air conditioning control software provided in an embodiment of this application;

[0046] Figure 4 This diagram illustrates a structural block diagram of an agile development apparatus for vehicle air conditioning control software provided in an embodiment of this application.

[0047] Figure 5 A structural block diagram of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0049] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0050] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0051] Existing automotive air conditioning software development largely relies on hand-writing code based on requirements documents, which results in low development efficiency, poor code reusability, and difficulty in adapting to multiple ECU platforms. Furthermore, natural language requirements and code implementation are prone to misunderstandings, and when requirements change, multiple code sections need to be manually traced and modified, which is prone to omissions and errors. At the same time, the cost of later quality verification and safety compliance rectification is high, making it difficult to meet the development needs of car companies for intelligentization, platformization, and rapid iteration.

[0052] Based on this, embodiments of this application provide an agile development method, apparatus, device, and medium for vehicle air conditioning control software, which will be described below through embodiments.

[0053] Example 1

[0054] To facilitate understanding of this embodiment, a detailed description of an agile development method for vehicle air conditioning control software disclosed in this application embodiment will be provided first. For example... Figure 1 The diagram illustrates a flowchart of an agile development method for vehicle air conditioning control software. Figure 2 The architecture diagram of the agile development system shown is as follows: Figure 3 The diagram illustrates another flowchart of an agile development method for vehicle air conditioning control software. This application provides an agile development method for vehicle air conditioning control software, applied to an agile development system. The agile development system includes a modeling module, a central data dictionary, and an intelligent code generation engine. The method includes:

[0055] S101. In the modeling module, construct a visual model of multiple components based on the vehicle air conditioner according to the requirements, and configure the corresponding visual model by dragging and dropping the core components of the air conditioner and connecting them.

[0056] S102. The central data dictionary responds to the request of the intelligent code generation engine by providing standardized data entities, so that the intelligent code generation engine can map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer.

[0057] S103. The target code is verified by a three-layer verification structure based on virtual climate cabin simulation, hardware-in-the-loop verification and shadow mode verification to obtain the verification result, so as to realize the agile development of vehicle air conditioning control software based on the target code after verification.

[0058] In step S101, this application sets up a modeling module in the agile development system, based on Eclipse Sirius or Web-based Blockly. The modeling module automatically loads a preset visual core component library for vehicle air conditioning. The component library contains standardized graphic components that correspond one-to-one with the actual components of the vehicle air conditioning system. It covers all types of air conditioning components, including sensing components such as temperature sensors, humidity sensors, and sunlight intensity sensors; execution components such as compressors, mixing dampers, mode dampers, blowers, and electronic expansion valves; interaction components such as HMI control buttons / touchscreens and vehicle-to-everything communication terminals; and control components such as air conditioning ECU core control units. Each component is pre-associated with basic attribute identifiers such as component model, hardware interface matching code, and basic function definition. Engineers can filter and load the corresponding component subset according to actual development needs, such as single-zone / dual-zone / four-zone air conditioning, air purification / intelligent defogging functions, etc., and eliminate redundant components to reduce canvas operation interference. In the modeling module, system engineers can use the pre-defined requirements and an initialized canvas framework to drag and drop selected air conditioning core components from the loaded core component library onto the corresponding areas of the canvas, completing the visual physical layout of multiple components of the vehicle air conditioning system. Using the modeling module's dedicated connection tool (supporting logic connections, data connections, and control command connections), engineers can connect the deployed air conditioning core components on the canvas by clicking with the mouse. Through operations involving components, connections, and more, the physical relationships and functional control logic between components are defined, thereby constructing a visual representation of multiple components based on the vehicle air conditioning system. The model contains all component information, logical association rules, and data binding parameters. It can directly interact with the intelligent code generation engine and serve as the sole logical basis for subsequent model-to-code conversion. It also provides a set of graphical modeling languages ​​specifically designed for automotive air conditioning, as well as a structured and unambiguous requirements specification. System engineers can directly drag and drop components such as "temperature sensor," "mixing damper," "compressor," and "HMI button" in the modeling module and define the logical relationships between them based on the logical relationships in actual operation, such as "turn on the compressor when the target temperature > the current temperature."

[0059] In the specific implementation of step S101, one embodiment is as follows: The modeling module constructs a visual model of multiple components based on the vehicle air conditioner according to requirements, and configures the corresponding visual model by dragging and dropping the core components of the air conditioner and connecting them with lines, including:

[0060] S1011. Load the preset in-vehicle air conditioning core component library, which includes a variety of visual components, and drag and drop the target visual component onto the modeling canvas.

[0061] S1012. Based on the architecture, functions, and wiring method of the vehicle air conditioner, configure the target visualization component to obtain the corresponding visualization model.

[0062] In steps S1011-S1012, the system engineer of this application, based on the pre-obtained requirements and the initialized canvas framework, drags and drops selected air conditioning core components from the loaded core component library onto the corresponding areas of the modeling canvas. During the dragging process, the modeling module provides auxiliary functions such as magnetic alignment, equidistant arrangement, and hierarchical anti-overlap to ensure that the components are arranged neatly. The engineer can adjust the size and position of the components according to the actual system connection relationship to accurately restore the actual physical relationship layout of each component of the vehicle air conditioner (e.g., arranging the left and right temperature sensors on the left and right sides of the canvas sensing layer respectively, corresponding to the actual sensing layout of the dual-zone air conditioner), completing the basic component construction of the visualization model. The module supports three types of dedicated connection tools: logic connections, data connections, and control command connections. Users can connect to the corresponding air conditioning core components of the deployed target visual components on the canvas using mouse clicks. This defines the physical relationships and functional control logic between components. Physical connections define the actual hardware connections between components, such as the signal transmission connection between the temperature sensor and the air conditioning ECU core control unit, and the control command transmission connection between the ECU and the compressor. Functional logic connections define the triggering and execution rules between target visual components. Connections can be configured by double-clicking to open the attribute configuration box and set specific logical conditions. For example, when the temperature sensor detection value > the target temperature threshold (e.g., 26℃), the ECU is triggered to send a start command to the compressor. When the HMI defogging button is triggered, the ECU control mode damper switches to the defogging duct, and the blower is adjusted to medium-high speed. Priority settings for connections are also supported, such as emergency defogging logic taking precedence over normal temperature control logic, ensuring that logic execution conforms to the actual working rules of the vehicle air conditioning system. After completing the component drag-and-drop and connection configuration, the engineer clicked on the air conditioning components and connections in the canvas one by one to open the attribute editing panel. This allowed them to refine the attributes of the target visualization components and the connections. For example, for connection attributes, they configured signal transmission rates, instruction execution delays, and abnormal triggering conditions such as fault alarm logic when the connection signal was interrupted. This ensured that the visualization model not only contained visualization logic but also accurately bound it to the underlying hardware and communication data, providing complete data support for subsequent code generation. After completing all configurations, the system engineer triggered the automatic verification function of the modeling module to verify the completeness and rationality of each visualization model. Upon successful verification, the visualization models of multiple target visualization components in the vehicle air conditioning system were determined.

[0063] The above process requires no coding from system engineers. It involves only visual drag-and-drop, connection, and attribute configuration operations to build a visual model of multiple components of the vehicle air conditioning system. This significantly lowers the modeling threshold, allowing system engineers and other non-low-level coders to directly participate in the definition of vehicle air conditioning software requirements and model building. Application software engineers can then continuously refine complex vehicle air conditioning operating logic, such as intelligent defogging algorithms and air purification strategies, within the modeling module, without needing to concern themselves with low-level details.

[0064] In step S102, this application ensures that the hardware abstraction layer and signal database in the agile development system are compatible with the latest hardware of the vehicle air conditioner through the maintenance and expansion of the hardware abstraction layer and signal database by the software architect. After obtaining the visualization models of multiple target visualization components in the vehicle air conditioner, the intelligent code generation engine sends an access request to extract the data entities corresponding to the visualization models from the central data dictionary. The intelligent code generation engine is composed of a template engine (such as Apache Velocity) and a rule engine (such as Drools). The central data dictionary supports SQL databases or versioned JSON files. When integrated with an enterprise PLM system, the central data dictionary responds to the request from the intelligent code generation engine after receiving the request and provides standardized data entities. The standardized data entities include all referenced and necessary subset data. The central data dictionary transforms all air conditioner-related concepts into structured data objects and assigns them globally unique identifiers, thereby obtaining data entities with rich relational networks, including hierarchical relationships and actual relationships. This allows the intelligent code generation engine to map the standardized data entities and visualization models through the three-layer mapping architecture pre-set in this application to obtain high-quality, error-free target code. The target code is C that conforms to the AutoSAR standard. The code covers the entire implementation chain from the underlying driver to the upper-layer application logic. This application adopts an incremental generation strategy, regenerating only the parts of the target code that need to be changed, further reducing the workload of code generation.

[0065] The central data dictionary and its connected configuration management library store all standardized data entities related to vehicle air conditioning, including: Hardware Abstraction Layer (HAL): the drive interfaces of all supported sensors and actuators; Signal Database: all air conditioning-related signals on the CAN / LIN bus, such as ID, length, byte order, and physical value conversion formulas; Vehicle Configuration Templates: predefined air conditioning function sets for different vehicle models, such as sedans, SUVs, and configurations such as single-zone and dual-zone.

[0066] In a specific implementation of step S102, one embodiment is as follows: the intelligent code generation engine maps the standardized data entities and the visualization model through a three-layer mapping architecture to obtain the target code, including:

[0067] S1021. Pre-configure the mapping methods corresponding to the semantic-data mapping layer, platform adaptation layer, and security compliance layer;

[0068] S1022. Execute the corresponding mapping method to complete the multi-dimensional mapping of the standardized data entities and the visualization model.

[0069] In steps S1021-S1022, this application sets up a three-layer mapping architecture in the intelligent code generation engine, including a semantic-data mapping layer, a platform adaptation layer, and a security compliance layer, and configures a corresponding mapping method for each type of layer. In traditional automotive air conditioning software development, there is a significant gap between requirement descriptions (natural language) and code implementation (low-level coding). Advanced logic defined by system engineers, such as dual-zone independent control and intelligent defogging, requires software engineers to manually translate into underlying hardware interface calls and bus signal parsing. This is not only inefficient but also prone to misunderstandings and binding errors. Therefore, after obtaining the standardized data entities, a semantic-data mapping layer is first used to understand the core intent of the visual model logic. Then, a platform adaptation layer is used to ensure that a single basic model can adapt to multiple brands and configurations of ECU platforms, significantly improving software portability and aligning with automakers' platform strategy (i.e., a single architecture covering sedans / SUVs / MPVs). Finally, a safety and compliance layer is used to integrate safety and compliance requirements into the code generation process. This is a necessary design for code generation technology in automotive scenarios, ensuring that every logic in the visual model is accurately mapped to the underlying executable data source. This is the core technical support for the visual model as code and the foundation for subsequent automatic code generation. The three-layer architecture is then executed sequentially using the corresponding mapping methods to complete the multi-dimensional mapping of the standardized data entities, the visual model, and the air conditioning-specific language, thereby obtaining the target code. This application adopts an incremental generation strategy, which only regenerates the code for the parts corresponding to the changes in the visualization model. The final output is complete C code that conforms to the AutoSAR standard and can be directly compiled. The C code covers the underlying driver adaptation, middleware communication and upper-layer application logic.

[0070] In the specific implementation of step S102, one embodiment is as follows: the three-layer mapping architecture includes at least a semantic-data mapping layer;

[0071] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0072] A1. The high-level control concepts in the visualization model are analyzed using an air conditioning domain semantic analyzer to obtain the analysis results;

[0073] A2. Automatically map the parsing results to standardized data entities in the central data dictionary and configuration management library to bind the visualization model to the standardized data entities.

[0074] In steps A1-A2, after receiving the structured visualization model of the vehicle air conditioner output by the modeling module, the intelligent code generation engine described in this application automatically calls the built-in semantic analyzer in the air conditioning domain within the semantic-data mapping layer. This initiates a model parsing command. The semantic analyzer reads all component information, connection logic rules, and attribute configuration parameters from the visualization model, forming a full dataset of the model to be parsed. Based on a dedicated semantic rule library for vehicle air conditioning, the air conditioning domain semantic analyzer performs semantic recognition and structured parsing on the full dataset, accurately extracting advanced control concepts in the air conditioning domain, including temperature control loops, etc. Features include dual-zone / quad-zone independent temperature control, intelligent defogging linkage, airflow distribution strategy, compressor start / stop logic, and HMI command response rules. The analyzer standardizes and decomposes the extracted high-level control concepts, forming a structured parsing result containing control objectives, trigger conditions, execution objects, parameter thresholds, and logical relationships. This ensures the parsing result is unambiguous and machine-readable. Using this structured parsing result as the retrieval basis, the analyzer automatically connects to the central data dictionary and configuration management library. Through preset data mapping rules in the air conditioning field, it performs precise searches within the library, matching corresponding standardized data entities. The semantic analyzer then performs searches based on the matching results. The system establishes a one-to-one mapping between each high-level control concept in the analysis results and the standardized data entities in the library. For example, the concept of dual-zone independent temperature control in the analysis results is automatically mapped to standardized data entities such as the drive interfaces of the left and right zone temperature sensors, the bus parameters of the dual-zone temperature signals, and the actuator control parameters of the left and right zone mixing dampers. The compressor start-stop logic in the analysis results is automatically mapped to standardized data entities such as the compressor hardware drive interface, the signal parameters of the refrigerant pressure sensor, and the compressor start-stop threshold configuration parameters, achieving accurate conversion from high-level control concepts to underlying standardized data. Based on the above mapping relationship, the intelligent code generation engine reverse-links the standardized data entity information in the central data dictionary and configuration management library to the corresponding components and logical connections in the visualization model, completing the deep binding between the visualization model and the standard data entities. After binding, the visualization model not only contains intuitive graphical control logic but also integrates all standardized data information such as underlying hardware drivers, bus communication, and parameter configuration, forming an integrated model with visible logic, traceable data, and matching interfaces. This ensures that during subsequent code generation, each control logic in the visualization model can accurately correspond to the underlying executable data source. The system also allows for validity checks after binding, including verifying the uniqueness of the mapping relationship, the integrity of standardized data entities, and the compatibility between the model logic and the data entities. Binding is confirmed complete upon successful verification. This achieves automated and precise mapping and binding from high-level control concepts in the air conditioning field to underlying standardized data entities, completely replacing the cumbersome process of manual translation and binding in traditional development. This significantly improves binding efficiency and accuracy, ensuring the quality and compatibility of subsequent code generation from the source.

[0075] In the specific implementation of step S102, another embodiment exists in which the three-layer mapping architecture includes at least a platform adaptation layer.

[0076] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0077] B1. Obtain the hardware characteristic parameters of the target ECU platform on the vehicle, and dynamically select the corresponding code generation strategy based on the hardware characteristic parameters;

[0078] B2. Generate initial code based on the selected code generation strategy and the bound visualization model and standardized data entities, and optimize the initial code.

[0079] In steps B1-B2, after receiving the bound visualization model, the platform adaptive layer of this application establishes a data interaction connection with the target ECU platform of the vehicle's air conditioning software to be deployed via vehicle bus communication (CAN / LIN) or a hardware adapter interface. It automatically scans and obtains all hardware characteristic parameters of the ECU. These parameters are core hardware indicators affecting code execution efficiency and compatibility, including but not limited to: the ECU's chip model, such as NXP. The engine analyzes and structures the acquired parameters, including S32K144, InfineonAURIX, CPU computing power, available memory capacity, bus communication bandwidth, hardware interface protocol type, peripheral driver support range, and real-time response benchmark values. It then removes invalid and redundant data to generate a standardized set of ECU hardware characteristic parameters, which serves as the sole basis for subsequent strategy selection. The intelligent code generation engine invokes the built-in ECU platform-code generation strategy mapping library. This library predefines multiple sets of dedicated code generation strategies for automotive air conditioning systems, matching different hardware characteristics. These strategies cover mainstream types such as resource-constrained, balanced adaptation, and high-performance optimization, and each strategy corresponds to specific hardware characteristic thresholds. For example, memory capacity < 512KB indicates resource-constrained performance, CPU... A clock speed of ≥800MHz is considered high performance. Using the ECU hardware characteristic parameter set as the search criteria, the intelligent code generation engine dynamically selects a unique code generation strategy that matches the target ECU platform through threshold matching and characteristic clustering analysis. For example, for economical ECUs with limited memory / computing resources, a strategy of code simplification and prioritizing core logic is selected; for high-performance, resource-intensive mid-to-high-end ECUs, a strategy of full-function implementation, algorithm optimization, and experience improvement is selected; and for standard configuration ECUs, a strategy of full functionality and balanced resources is selected. The intelligent code generation engine uses a dynamically selected code generation strategy as its execution criterion. It simultaneously loads a deeply bound in-vehicle air conditioning visualization model and standardized data entities from the central data dictionary, initiating an automated code generation process. Following the strategy's preset code structure, syntax rules, and functional trade-offs, it transforms the graphical control logic in the visualization model—such as compressor start / stop, damper switching, and dual-zone temperature control—into code statements precisely associated with standardized data entities (hardware driver interfaces, bus signal parameters, and actuator thresholds). The generated initial code comprehensively covers the underlying driver adaptation, middleware bus communication, and upper-layer application control logic of the in-vehicle air conditioning software, fully complying with the AutoSAR in-vehicle software standard. It is directly compilable C language code, ensuring the initial code logic is error-free, data is mismatched, and the platform is compatible. Through a built-in air conditioning constraint solver, it verifies and optimizes the code execution latency of key control commands such as damper adjustment and compressor start / stop, ensuring that the response time of all commands meets the real-time requirements of in-vehicle air conditioning, such as <200ms. Simultaneously, it adapts to the hardware interface protocol of the target ECU platform, correcting any potential interface incompatibility issues in the code.

[0080] In the specific implementation of step S102, there is another embodiment in which the three-layer mapping architecture includes at least a security compliance layer;

[0081] Execute the corresponding mapping method to complete the multi-dimensional mapping between the standardized data entities and the visualization model, including:

[0082] C1. Based on the pre-built vehicle air conditioning safety rule library, perform static verification on the optimized initial code to obtain the static verification results;

[0083] C2. Based on the static verification results, execute a preset target code generation strategy on the initial code to obtain the target code.

[0084] In steps C1-C2, at the safety compliance layer, the intelligent code generation engine calls the built-in pre-built vehicle air conditioning safety rule library. This rule library is specific to the vehicle air conditioning scenario and is built based on the ISO 26262 ASIL-B vehicle functional safety standard. It covers extreme operating conditions such as -40℃ cold start and +80℃ direct sunlight protection; key component safety rules for compressor overload / undervoltage protection, refrigerant pressure abnormal shutdown, and damper jamming fault handling; logic completeness rules with no control command dead zone, no contradictory logic, and full-scenario trigger condition coverage; and bus communication safety rules for CAN / LIN signal anomaly tolerance and data transmission verification. All rules are implemented in a machine-recognizable structured encapsulation. At the same time, the intelligent code generation engine loads the platform adaptive optimization rules. The optimized vehicle air conditioning control code completes the basic resource preparation for static verification. The intelligent code generation engine uses a pre-built vehicle air conditioning safety rule library as the verification basis to perform static verification on the optimized code without execution and across the entire chain. It directly scans and matches the code's syntax structure, logic flow, parameter configuration, and interface calls line by line, without needing to deploy the code to the hardware platform. According to the classification dimensions of the safety rule library, it verifies whether the code meets the corresponding rule requirements, such as whether the compressor control logic contains a high-pressure shutdown instruction, whether there is hardware preheating protection logic during extreme low-temperature startup, and whether dual... The system checks for issues such as whether there are any command conflicts in the temperature control zone; it focuses on verifying key modules related to vehicle air conditioning safety in the code (such as fault diagnosis, actuator drive, and bus signal parsing) to ensure that the core safety logic is complete and without deviation; the verification process automatically records the verification results, forming a structured static verification result containing compliant, non-compliant, and pending confirmation items. For non-compliant items, it accurately locates the code line, clarifies the type of violation rule, and provides preliminary correction suggestions. It also automatically classifies and judges the static verification results, dividing them into three categories based on the severity and scope of the non-compliant items: fully compliant, slightly non-compliant, and severely non-compliant. Based on the judgment conclusions of the above verification results, the intelligent code generation engine executes the preset target code generation strategy to generate vehicle air conditioning control target code that meets safety and compliance requirements and can be directly deployed. For example, if the direct generation strategy is for fully compliant or slightly non-compliant cases that have been corrected to compliance, but for severely non-compliant results, it is necessary to regenerate the initial code to generate the target code. The intelligent code generation engine standardizes and encapsulates the optimized code (or the automatically corrected code), retaining the complete functional logic, platform adaptability, and safety and compliance attributes of the code, generating AutoSAR compliant code. Standard, directly compileable and deployable target code;During strategy execution, metadata such as security compliance identifiers, verification records, and version information are automatically added to the target code. Simultaneously, a code security verification report is generated and output along with the target code, enabling traceability of code security compliance. The final generated target code not only meets the hardware adaptation requirements of the target ECU platform but also fully complies with the pre-built vehicle air conditioning safety rule library and the ISO 26262 ASIL-B standard, balancing platform compatibility, functional completeness, and security compliance.

[0085] This application moves security compliance verification to the code generation stage through a security compliance layer, achieving built-in security rather than post-development remediation. This effectively avoids the problems of high rework costs and long cycles caused by security compliance issues in traditional development. At the same time, through a pre-defined target code generation strategy, the verification results and code generation are automatically linked, ensuring that the final output target code is both compatible with the target ECU platform and meets the stringent safety requirements of the automotive air conditioning scenario, significantly improving the reliability and compliance of the code.

[0086] In step S103, after obtaining the target code, this application verifies the target code based on a three-layer verification structure constructed by virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification to obtain verification results. Following the verification logic from virtual to real vehicle, from function to performance, and from conventional to extreme, the target code is subjected to three-layer progressive multi-dimensional verification. The functional integrity, logical correctness, performance compliance, safety stability, and real vehicle adaptability of the code are verified layer by layer. Each layer of verification generates detailed sub-verification results, and the sub-verification results corresponding to each verification structure are collected and fused to obtain the verification result of the target code. If the verification result is passed, agile development of vehicle air conditioning control software is realized based on the verified target code. By employing a multi-dimensional and layered verification approach, the effectiveness of the target code is comprehensively verified from virtual to real vehicles, thus avoiding functional failures, performance issues, and security risks after software deployment from the source. At the same time, relying on the rapid deployment and incremental iteration characteristics of the code after verification, the shortcomings of traditional in-vehicle air conditioning software development, such as long development cycles, difficult collaboration, and slow iteration, are solved, truly realizing agile development of in-vehicle air conditioning control software and meeting the platform-based and rapid product development needs of car manufacturers.

[0087] In the specific implementation of step S103, one embodiment is as follows: a three-layer verification structure based on virtual climate chamber simulation, hardware-in-the-loop verification, and shadow mode verification is used to verify the target code and obtain the verification result, including:

[0088] S1031. A three-layer verification structure of virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification is pre-constructed.

[0089] S1032. The target code is verified based on the three-layer verification structure to obtain the verification results, and dynamic adjustments are made based on the verification results.

[0090] In steps S1031 - S1032, the present application pre - constructs a three - layer verification structure of virtual climate chamber simulation, hardware - in - the - loop verification, and shadow mode verification. In the virtual climate chamber simulation, a high - precision vehicle air - conditioner thermodynamic model and a vehicle environment model are loaded to simulate environmental temperatures from - 40°C to + 65°C, humidity from 10% to 95%, and different driving conditions such as idling, high - speed driving, and climbing. The target code is deployed to the virtual ECU for operation. The core dimensions for verification include: whether the core functions of the air - conditioner, such as temperature control, air - outlet mode switching, and HMI instruction response, are fully implemented; whether the control logic, such as compressor start - stop and damper position adjustment, is consistent with the visualization model; whether the code under extreme conditions, such as cold start at - 30°C and direct sunlight at + 80°C, triggers the preset safety protection logic; for electric vehicle models, additionally verifying the accuracy of air - conditioner energy consumption control to ensure that the energy consumption parameters meet the design requirements. Hardware - in - the - loop verification is denoted by HIL. The target code is downloaded to the real ECU prototype and deployed to the HIL hardware - in - the - loop verification platform, and real vehicle air - conditioner hardware components such as sensors, actuators, and HMI panels are connected. HMI refers to human - machine interaction, including the HMI panel and HMI operation buttons / touch screens, to achieve the linked operation from code to real hardware and then to the virtual vehicle. The core dimensions for verification include: the running performance of the target code on the real ECU, such as the response time of key control instructions < 200ms and the CPU / memory occupancy rate meeting the platform requirements; the action accuracy of hardware actuators, such as the damper switching position error and compressor speed control accuracy; user - experience - related indicators, such as the smoothness of damper switching and no jerks in temperature adjustment, and quantitatively evaluating the experience effect through an ergonomics model; at the same time, verifying the stability of bus communication (CAN / LIN) to ensure that there is no packet loss or delay in signal transmission. Shadow mode verification is to deploy the target code to the real - vehicle ECU and start the shadow mode operation, that is, the target code and the original vehicle air - conditioner control software execute in parallel, independently complete control decisions but do not actually drive the actuators, only record the control decision differences between the target code and the original vehicle code. The core dimensions for verification include: the adaptability of the target code in the real - vehicle real environment, such as the cooling / heating efficiency at different altitudes and air pressures; the communication compatibility with other vehicle systems, such as the body control module and the powertrain system; the stability of the target code operation under complex road conditions, such as bumps and vibrations; at the same time, automatically analyzing the reasons for decision differences to determine whether they are points for optimizing and upgrading the target code. If the verification result of any verification structure fails, the verification result is considered to fail, and dynamic adjustment is made according to the reasons for failure, and the root causes of the problems are detailedly marked, such as logical deviation, improper platform adaptation, and omission of safety rules, prompting the software engineer to return to the visualization model construction or code generation link for targeted correction. After correction, the entire process of code generation, safety verification, and multi - dimensional verification is re - executed until the verification passes.

[0091] In this environment, developers can verify the correctness of logic in real time by simulating inputs (such as changing the virtual in-vehicle temperature or clicking the HMI) without waiting for the hardware to be ready.

[0092] This application is also specifically designed for the high-frequency change requirements of in-vehicle air conditioning software, providing precise impact analysis:

[0093] Requirements - Achieving Two-Way Traceability: The agile development system establishes a visual traceability matrix. When a user modifies the "defogging performance requirements," such as increasing the time to clear fog from the windshield from 5 minutes to 3 minutes, the affected code areas (humidity sensor sampling frequency, damper switching strategy, blower maximum speed, etc.) are automatically highlighted.

[0094] Cross-model impact assessment: For platform-based development, when a basic function is changed, such as the control parameters of a new refrigerant R1234yf, the agile development system automatically calculates the degree of impact on different vehicle configurations. For example, a single-zone air conditioner only needs to adjust the compressor control parameters, while a four-zone air conditioner also needs to modify the temperature coupling compensation algorithm for all zones.

[0095] Configuration variant management: The agile development system uses a "feature switch tree" mechanism to manage regulatory compliance requirements in different global markets. For example, the EU market requires air conditioning systems to have refrigerant leak detection, while the North American market focuses on energy efficiency label certification. The agile development system can automatically generate software variants that comply with the regulations of each region.

[0096] Change Risk Warning: Based on historical data learning, when a specific function is modified, such as the compressor start-stop logic, the system will automatically issue a warning of related risks, such as "This change may affect the heating performance in environments below -20℃. It is recommended to verify it in a virtual climate chamber."

[0097] When requirements change, the system can accurately locate the affected code area and regenerate it by simply modifying the visualization model, ensuring consistency.

[0098] This application achieves the following technical effects:

[0099] Doubled development efficiency: Through model-driven and automated code generation, engineers are freed from repetitive hand-written coding, and the development cycle is shortened by more than 50%.

[0100] Zero deviation between requirements and implementation: The visual model is code, which fundamentally eliminates the problems of misunderstanding requirements and omissions in implementation;

[0101] Extreme code reuse: Through a central data dictionary and configuration templates, the air conditioning software reuse rate between different models can reach 90%, which greatly reduces the cost of platform development.

[0102] Built-in quality: The generated code undergoes rigorous verification by the engine, naturally avoiding common coding errors such as memory leaks and null pointers, significantly improving software reliability;

[0103] Seamless collaboration: All roles work on a unified agile development system, significantly reducing communication costs and making the development process more agile.

[0104] Example 2

[0105] This application also provides an agile development apparatus for vehicle air conditioning control software, such as... Figure 4 The diagram shows a block diagram of an agile development device for vehicle air conditioning control software. The functions implemented by this device correspond to the steps described above in executing an agile development method for vehicle air conditioning control software on a terminal device. This device can be understood as a server component including a processor. The agile development device for vehicle air conditioning control software described in this application is applied to an agile development system, which includes a modeling module, a central data dictionary, and an intelligent code generation engine. The device includes:

[0106] Module 401 is used to build a visual model of multiple components based on the vehicle air conditioner in the modeling module according to the requirements, and to configure the corresponding visual model by dragging and dropping the core components of the air conditioner and connecting them with lines.

[0107] The generation module 402 is used to respond to the request of the intelligent code generation engine from the central data dictionary and provide standardized data entities so that the intelligent code generation engine can map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer.

[0108] Development module 403 is used to verify the target code based on a three-layer verification structure built on virtual climate cabin simulation, hardware-in-the-loop verification and shadow mode verification to obtain verification results, so as to realize agile development of vehicle air conditioning control software based on the target code that has passed verification.

[0109] In one feasible implementation, the generation module includes:

[0110] Pre-configured mapping methods include those for the semantic-data mapping layer, the platform adaptation layer, and the security and compliance layer;

[0111] The corresponding mapping method is executed to complete the multi-dimensional mapping between the standardized data entities and the visualization model.

[0112] In one feasible implementation, the generation module further includes:

[0113] The high-level control concepts in the visualization model are analyzed using an air conditioning domain semantic analyzer to obtain the analysis results;

[0114] The parsing results are automatically mapped to standardized data entities in the central data dictionary and configuration management library to bind the visualization model to the standardized data entities.

[0115] In one feasible implementation, the generation module also includes:

[0116] Obtain the hardware characteristic parameters of the target ECU platform on the vehicle, and dynamically select the corresponding code generation strategy based on the hardware characteristic parameters;

[0117] Initial code is generated based on the selected code generation strategy and the bound visualization model and standardized data entities, and then the initial code is optimized.

[0118] In one feasible implementation, the generation module further includes:

[0119] Based on the pre-built vehicle air conditioning safety rule library, static verification is performed on the optimized initial code to obtain the static verification results;

[0120] Based on the static verification results, a preset target code generation strategy is executed on the initial code to obtain the target code.

[0121] In one feasible implementation, the development module includes:

[0122] A three-layer verification structure is pre-constructed, consisting of virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification;

[0123] The target code is verified based on the three-layer verification structure to obtain the verification results, and dynamic adjustments are made based on the verification results.

[0124] In one feasible implementation, the building module includes:

[0125] Load the pre-built library of core components for vehicle air conditioning, which includes a variety of visual components, and drag and drop the target visual component onto the modeling canvas;

[0126] Based on the architecture, functions, and wiring methods of the vehicle air conditioning system, the target visualization components are configured to obtain the corresponding visualization model.

[0127] Example 3

[0128] This application also provides an electronic device, such as Figure 5As shown, it includes: a processor 501, a memory 502, and a bus 503. The memory 502 stores machine-readable instructions that can be executed by the processor 501. When the electronic device is running, the processor 501 and the memory 502 communicate through the bus 503. When the machine-readable instructions are executed by the processor 501, the steps of the agile development method of vehicle air conditioning control software described in any one of the above descriptions are executed.

[0129] Example 4

[0130] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the agile development method for vehicle air conditioning control software as described in any one of the claims.

[0131] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0132] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0134] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0135] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An agile development method for vehicle air conditioning control software, characterized by, Applied to an agile development system, the agile development system including a modeling module, a central data dictionary, and an intelligent code generation engine, the method includes: In the modeling module, a visual model of multiple components based on the vehicle air conditioner is built according to the requirements, and the corresponding visual model is configured by dragging and dropping the core components of the air conditioner and connecting them with lines. The central data dictionary responds to the request of the intelligent code generation engine by providing standardized data entities, which enable the intelligent code generation engine to map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer; A three-layer verification structure based on virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification is used to verify the target code and obtain verification results. Agile development of vehicle air conditioning control software is then achieved based on the verified target code. The semantic-data mapping layer parses the high-level control concepts in the visualization model using an air conditioning domain semantic analyzer to obtain the parsing results, and automatically maps the parsing results to standardized data entities in the central data dictionary and configuration management library to bind the visualization model to the standardized data entities; The platform adaptive layer obtains the hardware characteristic parameters of the target ECU platform on the vehicle, dynamically selects the corresponding code generation strategy based on the hardware characteristic parameters, generates initial code based on the selected code generation strategy and the bound visualization model and standardized data entities, and optimizes the initial code. The safety compliance layer performs static verification on the optimized initial code based on the pre-built vehicle air conditioning safety rule library to obtain the static verification result. Based on the static verification result, the layer executes the pre-built target code generation strategy on the initial code to obtain the target code.

2. The method of claim 1, wherein, The intelligent code generation engine uses a three-layer mapping architecture to map the standardized data entities and visualization models to obtain target code, including: Pre-configured mapping methods include those for the semantic-data mapping layer, the platform adaptation layer, and the security and compliance layer; The corresponding mapping method is executed to complete the multi-dimensional mapping between the standardized data entities and the visualization model.

3. The method of claim 1, wherein, A three-layer verification structure based on virtual climate chamber simulation, hardware-in-the-loop verification, and shadow mode verification was used to verify the target code and obtain verification results, including: A three-layer verification structure is pre-constructed, consisting of virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification; The target code is verified based on the three-layer verification structure to obtain the verification results, and dynamic adjustments are made based on the verification results.

4. The method of claim 1, wherein, The process involves constructing a visual model of multiple components of the vehicle air conditioner in the modeling module according to requirements, and configuring the corresponding visual model by dragging and dropping the core components of the air conditioner and connecting them with lines. Load the pre-built library of core components for vehicle air conditioning, which includes a variety of visual components, and drag and drop the target visual component onto the modeling canvas; Based on the architecture, functions, and wiring methods of the vehicle air conditioning system, the target visualization components are configured to obtain the corresponding visualization model.

5. An agile development device of vehicle-mounted air conditioner control software, characterized by, Applied to an agile development system, the agile development system including a modeling module, a central data dictionary, and an intelligent code generation engine, the device includes: The building module is used to construct visual models of multiple components based on the vehicle air conditioner according to the requirements in the modeling module, and to configure the corresponding visual models by dragging and dropping the core components of the air conditioner and connecting them with lines. The generation module is used by the central data dictionary to respond to the requests of the intelligent code generation engine and provide standardized data entities, so that the intelligent code generation engine can map the standardized data entities to the visualization model through a three-layer mapping architecture to obtain the target code; the three-layer mapping architecture includes a semantic-data mapping layer, a platform adaptation layer, and a security and compliance layer. The development module is used to verify the target code based on a three-layer verification structure built on virtual climate cabin simulation, hardware-in-the-loop verification, and shadow mode verification to obtain verification results, so as to realize agile development of vehicle air conditioning control software based on the target code that has passed verification. The generation module further includes: The semantic-data mapping layer parses the high-level control concepts in the visualization model using an air conditioning domain semantic analyzer to obtain the parsing results, and automatically maps the parsing results to standardized data entities in the central data dictionary and configuration management library to bind the visualization model to the standardized data entities; The platform adaptive layer obtains the hardware characteristic parameters of the target ECU platform on the vehicle, dynamically selects the corresponding code generation strategy based on the hardware characteristic parameters, generates initial code based on the selected code generation strategy and the bound visualization model and standardized data entities, and optimizes the initial code. The safety compliance layer performs static verification on the optimized initial code based on the pre-built vehicle air conditioning safety rule library to obtain the static verification result. Based on the static verification result, the layer executes the pre-built target code generation strategy on the initial code to obtain the target code.

6. An electronic device, comprising: include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of an agile development method for vehicle air conditioning control software as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of an agile development method for vehicle air conditioning control software as described in any one of claims 1 to 4.

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