An airborne maintenance method and device for electric vertical takeoff and landing aircraft

Abstract

This disclosure relates to an airborne maintenance method and apparatus for electric vertical takeoff and landing (EVTOL) aircraft. The method includes: acquiring multi-source data from the EVTOL aircraft; the multi-source data includes: actual operational data and simulation test data; the actual operational data represents data from the actual flight process of the EVTOL aircraft, and the simulation test data represents data obtained from simulation tests using an engineering simulator; fusing the multi-source data of the EVTOL aircraft to generate fused data; and generating fault prediction, health status assessment, and maintenance recommendations based on the fused data. This disclosure utilizes a predictive maintenance mechanism that links data from the actual flight process of the EVTOL aircraft with data obtained from simulation tests using an engineering simulator, improving early fault warning and intelligent health management capabilities, and enhancing the maintenance capabilities and reliability of the EVTOL aircraft.

Description

Technical Field

[0001] This disclosure relates to the field of aircraft technology, and in particular to an airborne maintenance method and apparatus suitable for electric vertical take-off and landing aircraft. Background Technology

[0002] Vertical takeoff and landing (VTOL) aircraft, especially electric vertical takeoff and landing (eVTOL) aircraft, have become a key technological carrier for solving low-altitude three-dimensional transportation problems. With the rapid development of electric vertical takeoff and landing aircraft technology, the commercialization of electric aviation is gradually entering the implementation stage.

[0003] Onboard Maintenance System (OMS) is one of the core technologies to ensure the safe and efficient operation of aircraft; however, existing OMS cannot meet the needs of electric vertical takeoff and landing aircraft. Summary of the Invention

[0004] In view of this, this disclosure presents an airborne maintenance method, apparatus, electronic equipment, storage medium, and computer program product applicable to electric vertical takeoff and landing aircraft.

[0005] According to one aspect of this disclosure, an airborne maintenance method suitable for electric vertical takeoff and landing (EVTOL) aircraft is provided, applied to the airborne maintenance system of EVTOL aircraft, the method comprising:

[0006] Acquire multi-source data of an electric vertical takeoff and landing (EVTOL) aircraft; wherein, the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents the data during the actual flight of the EVTOL aircraft, and the simulation test data represents the data obtained by simulation testing using an engineering simulator;

[0007] The multi-source data of the electric vertical takeoff and landing aircraft are fused to generate fused data;

[0008] Based on the fused data, one or more of the following operations are performed: fault prediction, health status assessment, and maintenance recommendation generation.

[0009] In one possible implementation, acquiring multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft includes: acquiring multi-source data of a target system in the EVTOL aircraft, wherein the target system includes one or more of the following: flight control system, energy system, power system, and environmental control system.

[0010] In one possible implementation, the actual operational data includes one or more of the following: real-time flight parameters, preset key parameters of the target system, and event or fault information of the target system:

[0011] The method further includes:

[0012] When the airborne maintenance system is in flight mode, it continuously monitors the real-time flight parameters and the preset key parameters of the target system, and collects and records the event or fault information reported by the target system.

[0013] In one possible implementation, the simulation test data includes: normal operating condition simulation data and / or fault simulation data;

[0014] The method further includes:

[0015] The normal operating conditions of the electric vertical takeoff and landing aircraft are simulated using the engineering simulator, and the normal operating condition simulation data is generated.

[0016] And / or,

[0017] The engineering simulator is used to simulate the faults of the electric vertical takeoff and landing aircraft and generate the fault simulation data.

[0018] In one possible implementation, the step of performing one or more of the following operations based on the fused data: fault prediction, health status assessment, and maintenance recommendation generation, including:

[0019] During the operation of the airborne maintenance system, a trained fault prediction model is used to process the fused data to predict potential faults of the electric vertical takeoff and landing aircraft.

[0020] Based on the predicted results of potential failures, maintenance recommendations and / or health status assessment reports for the electric vertical takeoff and landing aircraft are generated; wherein, in the process of generating maintenance recommendations, one or more of the aircraft maintenance manual, safety constraints, and priority rules are incorporated.

[0021] In one possible implementation, the method further includes:

[0022] When the airborne maintenance system is in maintenance mode, it performs one or more of the following operations in response to user commands: fault report query, manual inspection, data loading, and configuration management.

[0023] According to another aspect of this disclosure, an airborne maintenance device suitable for electric vertical takeoff and landing (EVTOL) aircraft is provided, applied to the airborne maintenance system of EVTOL aircraft, the device comprising:

[0024] The acquisition module is used to acquire multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft; wherein, the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents the data during the actual flight process of the EVTOL aircraft, and the simulation test data represents the data obtained by simulation testing using an engineering simulator;

[0025] The data fusion module is used to fuse multi-source data from the electric vertical takeoff and landing aircraft to generate fused data.

[0026] The predictive maintenance module is used to perform one or more of the following operations based on the fused data: fault prediction, health status assessment, and maintenance recommendation generation.

[0027] According to another aspect of this disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0028] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described method.

[0029] According to another aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0030] In various aspects of this disclosure, multi-source data of an electric vertical takeoff and landing (EVTOL) aircraft is acquired. This multi-source data includes at least: actual operational data and simulation test data. The actual operational data represents data from the actual flight process of the EVTOL aircraft, and the simulation test data represents data obtained through simulation testing using an engineering simulator. The multi-source data of the EVTOL aircraft is fused to generate fused data. Based on the fused data, one or more of the following operations are performed: fault prediction, health status assessment, and maintenance recommendation generation. Thus, by fusing data from the actual flight process of the EVTOL aircraft and data obtained through simulation testing using an engineering simulator to perform operations such as fault prediction, health status assessment, and maintenance recommendation generation, predictive maintenance of the EVTOL aircraft can be achieved. This significantly improves the ability to provide early fault warning and intelligent health management, enhances the maintenance capability and reliability of the EVTOL aircraft, and better meets the high-frequency, high-reliability operation requirements of the EVTOL aircraft. In some examples, multi-source data of target systems in the electric vertical takeoff and landing aircraft are acquired, wherein the target systems include one or more of the following: flight control system, energy system, propulsion system, and environmental control system; thus, by acquiring multi-source data of target systems such as flight control system, energy system, propulsion system, and environmental control system, these systems can be used as maintenance objects, thereby enabling predictive maintenance to more comprehensively cover all target systems in the electric vertical takeoff and landing aircraft.

[0031] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0032] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0033] Figure 1 A flowchart is shown illustrating an airborne maintenance method for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure.

[0034] Figure 2 A structural diagram of an airborne maintenance device for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure is shown.

[0035] Figure 3 A structural diagram of an airborne maintenance system for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure is shown.

[0036] Figure 4 This diagram illustrates the functionality of an airborne maintenance system for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure.

[0037] Figure 5 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. Detailed Implementation

[0038] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0039] As used herein, the terms “comprising,” “including,” “having,” or variations thereof are open-ended and include one or more of the stated features, integrals, elements, steps, components, or functions, but do not exclude the presence or addition of one or more other features, integrals, elements, steps, components, functions, or groups thereof.

[0040] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0041] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another. Therefore, without departing from the teachings of the inventive concept, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0042] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0043] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0044] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0045] In related technologies, airborne maintenance systems, when applied to electric vertical takeoff and landing (EVL) aircraft, suffer from limited data sources, lack of simulation data support, and a passive maintenance mode with limited predictive capabilities, thus failing to meet the needs of EVL aircraft. Specifically, regarding the limited data sources and lack of simulation data support: airborne maintenance systems in related technologies primarily rely on actual aircraft flight data, failing to incorporate engineering simulator simulation test data, making high-precision fault prediction difficult, especially regarding the early fault warning capabilities for unique new systems such as batteries and motors in EVL aircraft. Regarding the passive maintenance mode and limited predictive capabilities: most airborne maintenance systems in related technologies rely on threshold alarms and post-event diagnosis, which is reactive maintenance, unable to predict faults in advance or dynamically assess health trends, making it difficult to adapt to the high-frequency, high-reliability operation requirements of EVL aircraft.

[0046] To address the aforementioned technical issues, this disclosure provides an airborne maintenance method applicable to electric vertical takeoff and landing (eVTOL) aircraft (detailed description below). This method employs a predictive maintenance mechanism that links data from actual flight of the eVTOL aircraft with data obtained from simulation testing using an engineering simulator. This significantly improves early fault warning and intelligent health management capabilities, enhances the maintenance capabilities and reliability of eVTOL aircraft, and better meets the high-frequency, high-reliability operation requirements of eVTOL aircraft.

[0047] Furthermore, there is a mismatch between the maintenance targets of airborne maintenance systems in related technologies and their application to electric vertical takeoff and landing (EVL) aircraft. For example, related technologies focus on fuel engines and hydraulic systems, neglecting battery state of charge (SOC) monitoring and multi-motor health status assessment, which are core energy sources for EVL aircraft. In some examples disclosed herein, multi-source data from target systems such as flight control systems, energy systems, propulsion systems, and environmental control systems can be acquired. These target systems can then be used as maintenance targets, enabling predictive maintenance to more comprehensively cover all target systems within the EVL aircraft.

[0048] For example, the airborne maintenance method for electric vertical takeoff and landing (EVTOL) aircraft provided in this disclosure can be executed by electronic devices such as terminal devices and servers, or by a portion of an electronic device (such as a processor). The terminal device can be a desktop or mobile terminal, such as a laptop, tablet, desktop computer, smartphone, smart speaker, smartwatch, smart TV, vehicle terminal, or other types of electronic devices. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0049] The following is a detailed description of the airborne maintenance method for electric vertical takeoff and landing aircraft provided by the embodiments of this disclosure.

[0050] This method can be applied to the airborne maintenance system of electric vertical takeoff and landing aircraft.

[0051] In some scenarios, the operating modes of the airborne maintenance system of an electric vertical takeoff and landing (EVTOL) aircraft can include: flight mode and maintenance mode. Flight mode refers to the operating mode of the airborne maintenance system when the EVTOL aircraft is in actual flight, while maintenance mode refers to the operating mode of the airborne maintenance system when the EVTOL aircraft is being maintained on the ground.

[0052] For example, the airborne maintenance system automatically enters flight mode after powering on and completing a self-test.

[0053] For example, when the airborne maintenance system is in flight mode, it can continuously monitor the buses of various target systems of the electric vertical takeoff and landing aircraft, collect actual operating data, and thus monitor key components such as batteries, motors, and flight control systems in real time.

[0054] For example, when the airborne maintenance system is in flight mode, it monitors the health status of critical components such as batteries, motors, and flight control systems in real time. If an anomaly is detected, the airborne maintenance system can immediately generate a fault report with timestamps and flight phase labels, and generate alarms based on the severity. For instance, alarm messages can be issued through the cockpit crew warning system to alert the pilots. For example, the airborne maintenance system can determine the level of the current fault or anomaly, generate alarm messages of the corresponding level, and display the alarm messages to the pilots.

[0055] For example, the actual operational data collected by the airborne maintenance system in flight mode and the fault reports generated can be encrypted and stored for subsequent analysis.

[0056] For example, when the electric vertical takeoff and landing (EVTOL) aircraft is on the ground and meets preset safety constraints, authorized maintenance personnel can activate the maintenance mode of the airborne maintenance system, thereby putting the airborne maintenance system into maintenance mode. These safety constraints may include disconnecting the high-voltage power supply, locking the propellers, etc., to prevent accidental start-up of the EVTOL aircraft or other safety risks, ensuring that the maintenance mode of the airborne maintenance system can be safely activated.

[0057] For example, when the airborne maintenance system is in maintenance mode, maintenance personnel can view fault reports, perform manual inspections, and load data through the cockpit maintenance terminal.

[0058] For example, when the airborne maintenance system is in maintenance mode, it supports software updates, configuration file injection, and system function verification to ensure that the health status of critical components such as batteries and motors is assessed in real time.

[0059] Figure 1 A flowchart illustrating an airborne maintenance method for an electric vertical takeoff and landing (EVTOL) aircraft according to an embodiment of this disclosure is shown. Figure 1 As shown, the method may include the following steps:

[0060] Step 101: Obtain multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft; wherein, the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents the data during the actual flight of the EVTOL aircraft, and the simulation test data represents the data obtained by simulation testing using an engineering simulator.

[0061] Multi-source data refers to data from different data sources. An engineering simulator (also known as a physical simulation machine) is a human-in-the-loop semi-physical simulation system that can completely and realistically simulate the cockpit environment, handling characteristics, and system functions of an electric vertical takeoff and landing aircraft, thereby generating various simulation test data.

[0062] For example, data from multiple actual flights of an electric vertical takeoff and landing aircraft can be acquired, as well as data obtained from multiple simulation tests using an engineering simulator, thereby collecting rich multi-source data.

[0063] In one possible implementation, acquiring multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft includes: acquiring multi-source data of target systems in the EVTOL aircraft, wherein the target systems include one or more of the following: flight control system, energy system (also known as battery system), power system (also known as motor system), and environmental control system (ECS).

[0064] The target system can be referred to as the member system. For example, each target system can provide necessary maintenance information to the airborne maintenance system, and users can access each target system through the interactive interface of the airborne maintenance system.

[0065] For example, actual operating data and simulation test data of various target systems such as the flight control system, energy system, power system, and environmental control system of an electric vertical takeoff and landing (EVT) aircraft can be obtained. In this way, multi-source data of target systems such as the flight control system, energy system, power system, and environmental control system can be obtained. Subsequently, operations such as fault prediction, health status assessment, and maintenance suggestion generation can be performed based on multi-source data. Thus, each target system can be treated as a maintenance object for predictive maintenance, so that predictive maintenance can more comprehensively cover each target system in the EVT aircraft.

[0066] In one possible implementation, the actual operational data includes one or more of the following: real-time flight parameters, preset key parameters of the target system, and event or fault information of the target system. As an example, the actual operational data may include real-time flight parameters, preset key parameters of each target system, and event or fault information of each target system.

[0067] For example, real-time flight parameters may include the actual flight speed, acceleration, attitude, etc. of the electric vertical takeoff and landing aircraft.

[0068] For example, the preset key parameters can be set as needed for different target systems, and there is no limitation on this. For example, the preset key parameters of an energy system may include battery voltage, current, temperature, battery state of charge, etc.; as another example, the preset key parameters of a power system may include motor speed, temperature, etc.

[0069] For example, the event or fault information of the target system may include: event or fault information reported by the target system, such as the built-in test equipment (BITE), initiated built-in test (IBIT), built-in test (BIT) status, fault code, alarm level, and occurrence time of the Line Replaceable Unit (LRU) of the target system, fault information actively reported by the target system, and alarm trigger records of the Crew Alerting System (CAS), etc.

[0070] In one possible implementation, the method further includes: continuously monitoring the real-time flight parameters and preset key parameters of the target system while the airborne maintenance system is in flight mode, and collecting and recording event or fault information reported by the target system.

[0071] For example, when the airborne maintenance system is in flight mode, it continuously monitors the buses of each target system, thereby continuously collecting real-time flight parameters such as speed, acceleration, and attitude of the electric vertical takeoff and landing aircraft, preset key parameters of the energy system such as battery voltage, current, temperature, and battery state of charge, key parameters of the power system such as motor speed and temperature, etc. At the same time, it can collect and record event or fault information reported by the target system during the actual flight of the electric vertical takeoff and landing aircraft, thereby collecting event or fault information of the target system.

[0072] For example, the preset key parameters of the target system and the event or fault information reported by the target system can be transmitted to the airborne maintenance system via the data bus.

[0073] In one possible implementation, the simulation test data includes: normal operating condition simulation data and / or fault simulation data. As an example, the simulation test data includes: normal operating condition simulation data and fault simulation data.

[0074] For example, normal operating condition simulation data may include: simulated flight parameters (such as the speed, acceleration, attitude, etc. of simulated flight of an electric vertical take-off and landing aircraft), preset key parameters of each target module (corresponding to the target system) (such as the voltage, current, temperature, and state of charge of the battery in the energy module; the speed and temperature of the motor in the power module), etc.

[0075] For example, the fault simulation data may include: fault injection data and operational data during the fault cross-system transmission process; wherein, the fault injection data may include fault triggering conditions, fault type, fault code, fault injection time, etc.; the operational data during the fault cross-system transmission process may include: transmission logs (such as transmission path) during the cross-system transmission process, event or fault information of each target module (such as actively reported fault information and cockpit crew alarm system alarm trigger records), simulated flight parameters, preset key parameters of each target module, etc.

[0076] In one possible implementation, the method further includes: simulating the normal operating conditions of the electric vertical takeoff and landing (EVTOL) aircraft using the engineering simulator to generate normal operating condition simulation data; and / or simulating faults of the EVTOL aircraft using the engineering simulator to generate fault simulation data. Thus, the engineering simulator, as a hardware-in-the-loop (HIL) simulation system, based on the architecture and flight performance of the EVTOL aircraft, simulates both the normal operating conditions and faults of the EVTOL aircraft by simulating the cockpit environment, control characteristics, and system functions, thereby generating various simulation test data, including normal operating condition simulation data and fault simulation data.

[0077] As an example, the engineering simulator could be the VE25-100 passenger electric vertical takeoff and landing aircraft engineering simulator. This engineering simulator is a human-in-the-loop hardware-in-the-loop simulation system, developed based on the VE25-100 passenger electric vertical takeoff and landing aircraft 101 model. It can completely and realistically simulate the cockpit environment, handling characteristics and system functions of the VE25-100 passenger electric vertical takeoff and landing aircraft, and has the ability to perform performance verification and validation of engineering simulators and conduct flight test training.

[0078] For example, a simulation model of the system on a real electric vertical takeoff and landing (EVT) aircraft can be built using Simulink or other simulation software. This simulation model can then be deployed to an engineering simulator using software tools like Simulink. This, along with the actual airborne system components of the EVT, creates a hardware-in-the-loop (HIL) simulation environment. It is understood that there is a correspondence between the target module and the target system; the target system is the actual system on the EVT, while the target module is a module in the engineering simulator, which can be either a simulation model of the actual EVT target system or the actual target system itself.

[0079] For example, an engineering simulator can be used to inject faults into a target module, simulating fault conditions and generating fault simulation data. This provides data support for subsequent fault prediction and health management of the airborne maintenance system. As an example, the engineering simulator integrates a fault injection module to simulate fault conditions and record relevant fault data, thereby generating fault simulation data. The injected faults can be represented in the form of fault codes. Fault codes serve as codes for identifying and describing specific faults; each fault code typically corresponds to a specific fault to ensure accurate fault identification.

[0080] For example, the timing, level, and type of fault injection can be selected according to testing requirements. For instance, the flight process of an electric vertical takeoff and landing (EVT) aircraft can be simulated in an engineering simulator, and fault injection can be performed at a specific moment when the EVT aircraft is in normal flight. Fault types can also include: battery faults, motor faults, navigation and positioning faults, communication system faults, attitude faults, environmental control system faults, etc. Motor faults can include excessive motor temperature, failure of a single motor winding, thrust failure, etc.; battery faults can include battery overpowering, battery interlocking faults, battery thermal runaway, etc. Fault levels can also be "alert level," "standby level," "warning level," etc.

[0081] For example, taking a motor overheating fault as an example, a motor overheating fault can be injected into the motor module of an electric vertical takeoff and landing (EVTOL) aircraft in an engineering simulator. For instance, the motor temperature and its validity parameters can be used as injection parameters for the motor overheating fault. Based on the validity parameters indicating that the motor temperature value is valid (e.g., sensors are working normally, communication lines are connected normally, and the circuit is functioning correctly), adjusting the motor temperature value of the motor module to exceed a preset threshold will inject a motor overheating fault. The preset temperature can be set according to requirements and is not limited. Furthermore, based on adjusting the motor temperature value in the motor module to be higher than the preset temperature, the adjusted motor temperature value can be flexibly set to achieve the injection of motor overheating faults of different fault levels. Taking a battery thermal runaway fault as an example, a battery thermal runaway fault can be injected into the battery module of an EVTOL aircraft in an engineering simulator. For example, the thermal runaway parameter can be set to trigger a battery thermal runaway fault when a "Fault" condition is met.

[0082] Step 102: Perform fusion processing on the multi-source data of the electric vertical take-off and landing aircraft to generate fused data.

[0083] In this step, the data obtained from the actual flight process of the electric vertical take-off and landing aircraft and the data obtained from simulation tests using an engineering simulator are fused together to form data that conforms to a unified data standard and is correlated, i.e., fused data.

[0084] In one possible implementation, data from the actual flight of the electric vertical takeoff and landing (EVTOL) aircraft and data obtained from simulation tests using engineering simulators can be standardized by using unified fields, units, and sampling rates to ensure that the data conforms to a unified data standard. For example, the source and reliability of each data point can also be labeled. Furthermore, data conforming to the unified data standard can be correlated according to timestamps and flight phases (takeoff / transition / cruise / approach, etc.) to obtain fused data from different flight phases. The fused data for the same flight phase includes data from the actual flight of the EVTOL aircraft and data from simulation tests using engineering simulators for that flight phase. In this way, multi-source data is standardized and correlated by flight phase to obtain fused data from different flight phases for subsequent analysis and processing.

[0085] For example, the data obtained from simulation testing using an engineering simulator can be calibrated or corrected for differences in environment, load, sensor bias, etc., between the data obtained from simulation testing using an engineering simulator and the data from the actual flight process of the electric vertical take-off and landing aircraft, so that the data obtained from simulation testing using an engineering simulator can be transferred to the actual flight process of the electric vertical take-off and landing aircraft.

[0086] One possible implementation approach is a layered fusion method: based on the data source, data originating from the same target system are first fused to obtain fused data for each target system. This fused data for the same target system includes data from the target system during actual flight of the electric vertical takeoff and landing (EVA) and data from the same target system obtained through simulation testing using an engineering simulator. Furthermore, cross-target system fusion (such as battery-electric drive-thermal management) can be performed to obtain cross-target system fused data. The fused data for the target system can serve as a health indicator for that system; the cross-target system fused data can serve as the data foundation for health status, risk level, and maintenance recommendations.

[0087] It should be noted that the above fusion method is only an example. Other existing data fusion methods can be used as needed to fuse data from the actual flight process of the electric vertical take-off and landing aircraft with data obtained from simulation tests using engineering simulators, so that the fused data conforms to a unified data standard and is correlated.

[0088] Step 103: Perform one or more of the following operations based on the fused data: fault prediction, health status assessment, and maintenance recommendation generation.

[0089] In this step, based on data from the actual flight process of the electric vertical takeoff and landing aircraft and data obtained from simulation tests using an engineering simulator, operations such as fault prediction, health status assessment, and maintenance suggestion generation are performed to achieve predictive maintenance of the electric vertical takeoff and landing aircraft, thereby greatly improving the ability to provide early fault warning and intelligent health management.

[0090] Predictive maintenance is a data-driven intelligent maintenance strategy that predicts the failures of electric vertical takeoff and landing (EVTOL) aircraft, conducts health status assessments, and provides maintenance recommendations to enable precise maintenance of EVTOL aircraft before failures occur.

[0091] In one possible implementation, the step of performing one or more of the following operations based on the fused data—fault prediction, health status assessment, and maintenance recommendation generation—includes: during the operation of the airborne maintenance system, processing the fused data using a trained fault prediction model to predict potential faults of the electric vertical takeoff and landing (EVTOL) aircraft; and generating maintenance recommendations and / or health status assessment reports for the EVTOL aircraft based on the prediction results of the potential faults; wherein, in the process of generating maintenance recommendations, one or more of the aircraft maintenance manual, safety constraints, and priority rules are incorporated.

[0092] For example, a fault prediction model can predict the type of potential fault and provide prediction results such as the probability of fault occurrence, time window, and risk level. Furthermore, based on aircraft maintenance manuals, safety constraints, and priority rules, the prediction results can be analyzed to determine actionable maintenance recommendations, thereby supporting proactive maintenance and achieving predictive maintenance. For example, maintenance recommendations may include: inspection items, handling priorities, suggested maintenance windows, etc.

[0093] For example, there can be one or more trained fault prediction models. According to actual needs, a trained fault prediction model with corresponding fault prediction capabilities can be selected to predict potential faults of the electric vertical take-off and landing aircraft. For example, predicting potential faults for a certain flight phase of the electric vertical take-off and landing aircraft, predicting potential faults for a certain target system of the electric vertical take-off and landing aircraft, predicting potential faults for the electric vertical take-off and landing aircraft across target systems, etc.

[0094] For example, during the operation of the airborne maintenance system, processing the fused data using a trained fault prediction model to predict potential faults of the electric vertical takeoff and landing (EVTOL) aircraft can include: during the operation of the airborne maintenance system, using the trained fault prediction model to process fused data generated from real-time sampled actual operating data of the EVTOL aircraft and historical simulation test data of EVTOL aircraft, thereby predicting potential faults of the EVTOL aircraft. The fused data can include multi-dimensional data such as real-time flight parameters, preset key parameters of multiple target systems, and event or fault information of multiple target systems. This allows the fault prediction model to analyze and process the multi-dimensional data, more accurately predicting potential faults of the EVTOL aircraft.

[0095] As an example, when an EVTOL aircraft is in flight mode, real-time operational data of the EVTOL aircraft can be acquired. This data can then be processed in real-time using a trained fault prediction model, or by processing fused data generated from this operational data and historical simulation test data of EVTOL aircraft. This allows for real-time prediction of potential faults in the EVTOL aircraft and real-time assessment of its health status. Furthermore, based on the predicted potential faults, maintenance recommendations and / or health status assessment reports for the EVTOL aircraft can be generated.

[0096] As another example, when an EVTOL aircraft is in maintenance mode, the actual operational data of the EVTOL aircraft during its latest flight is acquired. This operational data is then processed using a fault prediction model, or fused with historical simulation test data of EVTOL aircraft, to predict potential faults in the EVTOL aircraft. Based on these potential fault predictions, maintenance recommendations and / or health status assessment reports for the EVTOL aircraft can then be generated.

[0097] For example, when the electric vertical takeoff and landing (EVTOL) aircraft is in maintenance mode, maintenance recommendations and health status assessment reports are provided to the user. The user can be a maintenance personnel, who can then refer to the maintenance recommendations and health assessments generated by the fault prediction model to perform maintenance on the EVTOL aircraft.

[0098] For example, based on the prediction of potential faults, maintenance personnel can be provided with necessary maintenance advice while also receiving fault alerts.

[0099] In one possible implementation, the method further includes: when the airborne maintenance system is in maintenance mode, responding to user instructions to perform one or more of the following operations: fault report query, manual inspection, data loading, and configuration management.

[0100] For example, users can use the airborne maintenance system to query fault information, perform manual inspections, load data, and manage the configuration of various target systems.

[0101] For example, during manual inspection, IBIT (Initialize Built-in Test) commands can be sent to designated target systems, such as battery balancing tests and motor winding insulation tests. During data loading, software updates or configuration file injections can be performed on systems such as flight control and batteries. During configuration management, the physical composition, software version, installation status, and interconnections of each target system of the electric vertical takeoff and landing aircraft can be viewed.

[0102] In one possible implementation, the method further includes: when the airborne maintenance system is in maintenance mode, maintenance personnel can query historical data, perform manual inspections, and load and update data based on the predicted results of potential faults and / or maintenance recommendations.

[0103] In this embodiment, multi-source data of an electric vertical takeoff and landing (EVTOL) aircraft is acquired. This multi-source data includes at least: actual operational data and simulation test data. The actual operational data represents data from the actual flight process of the EVTOL aircraft, and the simulation test data represents data obtained through simulation testing using an engineering simulator. The multi-source data of the EVTOL aircraft is fused to generate fused data. Based on the fused data, one or more of the following operations are performed: fault prediction, health status assessment, and maintenance suggestion generation. Thus, by fusing data from the actual flight process of the EVTOL aircraft and data obtained through simulation testing using an engineering simulator to perform operations such as fault prediction, health status assessment, and maintenance suggestion generation, predictive maintenance of the EVTOL aircraft can be achieved. This significantly improves the ability to provide early fault warning and intelligent health management, enhances the maintenance capability and reliability of the EVTOL aircraft, and better meets the high-frequency, high-reliability operation requirements of the EVTOL aircraft. In some examples, multi-source data of target systems in the electric vertical takeoff and landing aircraft are acquired, wherein the target systems include one or more of the following: flight control system, energy system, propulsion system, and environmental control system; thus, by acquiring multi-source data of target systems such as flight control system, energy system, propulsion system, and environmental control system, these systems can be used as maintenance objects, thereby enabling predictive maintenance to more comprehensively cover all systems in the electric vertical takeoff and landing aircraft.

[0104] The training process of the above-mentioned fault prediction model will be explained in detail below.

[0105] The type of fault prediction model can be selected based on requirements and is not limited thereto; for example, it can be a machine learning model (such as random forest or neural network) or a statistical model (such as regression analysis). As an example, the fault prediction model can be a machine learning model.

[0106] In one possible implementation, the above can be executed. Figure 1 Before step 101, historical multi-source data from the electric vertical take-off and landing aircraft are used to train the machine learning model to obtain a trained fault prediction model, which can then be used to perform fault prediction when executing step 103.

[0107] The historical multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft includes actual operational data from historical flights and simulation test data from historical simulations. The actual operational data from historical flights and the simulation test data from historical simulations are fused together, and the resulting fused data is used as training samples to train the machine learning model, thereby improving the prediction accuracy of the trained fault prediction model.

[0108] Because the data from each actual flight of an electric vertical takeoff and landing (EVTOL) aircraft may reflect scenarios without faults or scenarios where some target systems have failed, similarly, the data obtained from each simulation test using an engineering simulator may reflect normal operating conditions without faults or failure simulations where some target systems have failed. This multi-source data provides more reliable data support for predictive maintenance. Using fused data from historical multi-source EVTOL data as the basis for training the fault prediction model expands the number of fault samples, enabling the training of a high-precision fault prediction model. The trained fault prediction model has the ability to accurately predict faults in each target system, allowing each target system to be treated as a maintenance object for high-precision predictive maintenance, thus providing more comprehensive coverage of all target systems within the EVTOL aircraft.

[0109] For example, the training samples may include normal operating condition samples and fault operating condition samples; the fault operating condition samples may further include label information such as fault type, fault occurrence stage, risk level and corresponding maintenance records.

[0110] As an example, the model can be trained using normal operating condition samples and faulty operating condition samples to ensure that the model can learn the differences between normal and faulty operating conditions. Furthermore, it can be further supervised by using label information such as fault type, fault occurrence stage, risk level, and corresponding maintenance records to improve the model's ability to predict fault type, fault occurrence stage, risk level, and corresponding maintenance records. In this way, the trained fault prediction model has the ability to predict faults and determine fault type, fault occurrence stage, risk level, and corresponding maintenance records.

[0111] For example, the fused data generated from historical multi-source data of electric vertical takeoff and landing (EVTOL) aircraft can be divided into a training set, a validation set, and a test set. The fault prediction model can then be trained, validated, and tested based on these sets. The training method uses existing techniques and will not be elaborated upon here.

[0112] For example, the number of fault prediction models can be one or more, and can be configured as needed without limitation. When multiple fault prediction models are configured, different models can be trained using different training samples to achieve specific fault prediction capabilities. For instance, fused data from the same flight phase can be used as training samples and input into the fault prediction model. The model outputs the type of potential fault, as well as the probability of occurrence, time window, and risk level. After training, the trained fault prediction model has the ability to predict potential faults for different flight phases. As another example, fused data from the same target system can be used as training samples and input into the fault prediction model. The model outputs the type of potential fault, as well as the probability of occurrence, time window, and risk level. After training, the trained fault prediction model has the ability to predict potential faults for different target systems. Yet another example is that fused data from multiple target systems can be used as training samples and input into the fault prediction model. The model outputs the type of potential fault, as well as the probability of occurrence, time window, and risk level. After training, the trained fault prediction model has the ability to predict potential faults across target systems.

[0113] In one possible implementation, after executing the above... Figure 1 Following step 103, the fused data acquired during the operation of the airborne maintenance system is used to retrain the trained fault prediction model, thereby continuously updating the performance of the fault prediction model and improving the accuracy of fault prediction. The specific training process can be found in the preceding description.

[0114] Based on the same inventive concept of the above method embodiments, the present disclosure also provides an airborne maintenance device suitable for electric vertical take-off and landing aircraft, which can be used to perform the technical solutions described in the above method embodiments.

[0115] Figure 2 This diagram shows a structural diagram of an airborne maintenance device for an electric vertical takeoff and landing (EVTOL) aircraft according to an embodiment of the present disclosure. The device is applied to the airborne maintenance system of the EVTOL aircraft, such as... Figure 2 As shown, the device may include: an acquisition module 201, used to acquire multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft; wherein the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents data during the actual flight process of the EVTOL aircraft, and the simulation test data represents data obtained by simulation testing using an engineering simulator; a data fusion module 202, used to fuse the multi-source data of the EVTOL aircraft to generate fused data; and a predictive maintenance module 203, used to perform one or more of the following operations based on the fused data: fault prediction, health status assessment, and maintenance suggestion generation.

[0116] In this embodiment, multi-source data of an electric vertical takeoff and landing (EVTOL) aircraft is acquired. This multi-source data includes at least: actual operational data and simulation test data. The actual operational data represents data from the actual flight process of the EVTOL aircraft, and the simulation test data represents data obtained through simulation testing using an engineering simulator. The multi-source data of the EVTOL aircraft is fused to generate fused data. Based on the fused data, one or more of the following operations are performed: fault prediction, health status assessment, and maintenance suggestion generation. Thus, by fusing data from the actual flight process of the EVTOL aircraft and data obtained through simulation testing using an engineering simulator to perform operations such as fault prediction, health status assessment, and maintenance suggestion generation, predictive maintenance of the EVTOL aircraft can be achieved. This significantly improves the ability to provide early fault warning and intelligent health management, enhances the maintenance capability and reliability of the EVTOL aircraft, and better meets the high-frequency, high-reliability operation requirements of the EVTOL aircraft. In some examples, multi-source data of target systems in the electric vertical takeoff and landing aircraft are acquired, wherein the target systems include one or more of the following: flight control system, energy system, propulsion system, and environmental control system; thus, by acquiring multi-source data of target systems such as flight control system, energy system, propulsion system, and environmental control system, these systems can be used as maintenance objects, thereby enabling predictive maintenance to more comprehensively cover all target systems in the electric vertical takeoff and landing aircraft.

[0117] In one possible implementation, the acquisition module 201 is further configured to: acquire multi-source data of the target system in the electric vertical take-off and landing aircraft, wherein the target system includes one or more of the following: flight control system, energy system, power system, and environmental control system.

[0118] In one possible implementation, the actual operating data includes one or more of the following: real-time flight parameters, preset key parameters of the target system, and event or fault information of the target system. The acquisition module 201 is further configured to: continuously monitor the real-time flight parameters and preset key parameters of the target system when the airborne maintenance system is in flight mode, and collect and record the event or fault information reported by the target system.

[0119] In one possible implementation, the simulation test data includes: normal operating condition simulation data and / or fault simulation data; the acquisition module 201 is further configured to: simulate the normal operating conditions of the electric vertical take-off and landing aircraft using the engineering simulator to generate the normal operating condition simulation data; and / or, simulate the faults of the electric vertical take-off and landing aircraft using the engineering simulator to generate the fault simulation data.

[0120] In one possible implementation, the predictive maintenance module 203 is further configured to: process the fused data using a trained fault prediction model during the operation of the airborne maintenance system to predict potential faults of the electric vertical takeoff and landing aircraft; and generate maintenance recommendations and / or health status assessment reports for the electric vertical takeoff and landing aircraft based on the prediction results of the potential faults; wherein, in the process of generating maintenance recommendations, one or more of the aircraft maintenance manual, safety constraints, and priority rules are incorporated.

[0121] In one possible implementation, when the airborne maintenance system is in maintenance mode, it performs one or more of the following operations in response to user instructions: fault report query, manual inspection, data loading, and configuration management.

[0122] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0123] This disclosure also provides an airborne maintenance system suitable for electric vertical takeoff and landing aircraft, which can be used to perform the technical solutions described in the above method embodiments.

[0124] Figure 3This diagram illustrates a structural diagram of an airborne maintenance system for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure, such as... Figure 3 As shown, the airborne maintenance system may include: airborne maintenance system functional modules (such as a central maintenance functional module, an aircraft status monitoring functional module, an aircraft configuration reporting module, etc.), aircraft status monitoring system sensors, remote data interface units (ports), an electronic library system, built-in test equipment (BITE) for each member system (i.e., target system), data loading devices, maintenance access terminals, a maintenance access terminal writing system, data links, etc. Among these, the aircraft status monitoring system sensors are used to directly measure the aircraft's flight parameters; the remote data interface unit realizes the transmission and processing of data from member systems, supporting real-time data monitoring and fault report generation; the maintenance access terminal provides an interactive interface between the user and the airborne maintenance system for functions such as fault querying, manual inspection, and data loading; the maintenance access terminal is a terminal used to write / modify maintenance programs and configuration files; and the electronic library system is a database storing maintenance manuals / knowledge bases, fault isolation programs, historical maintenance records, etc.

[0125] Figure 4 This diagram illustrates the functional characteristics of an airborne maintenance system for an electric vertical takeoff and landing aircraft according to an embodiment of the present disclosure. Figure 4 As shown, the airborne maintenance system can perform central maintenance, flight status monitoring, maintenance reporting, flight configuration reporting, data loading / unloading, and crew system in-flight self-testing. It also features airborne maintenance display via an Integrated Display Unit (IDU) for user interaction.

[0126] Combination Figure 3 and Figure 4 In the actual operation of the airborne maintenance system, the central maintenance function includes: The central maintenance module is responsible for automatic testing and fault isolation, continuously monitoring the status of each member system, and generating maintenance recommendations based on system fault reports. The flight status monitoring module monitors and records aircraft maintenance, performance, fault analysis, and trends through ground support software (GBSS). The maintenance reporting function reports potential functional failures in advance based on aircraft status data, facilitating timely maintenance actions. The flight configuration reporting module receives and displays the configuration status of each member system, identifies changes in system configuration, and provides a configuration management interface. The data loading / unloading function allows maintenance personnel to issue commands through the human-machine interface and suspends data loading under conditions such as data packet timeouts, software component corruption, or incompatibility.

[0127] In some embodiments, the components (such as the aforementioned central maintenance module) of the airborne maintenance system for electric vertical takeoff and landing aircraft provided in this disclosure can be used to execute the methods described in the above method embodiments. The specific implementation and achieved technical effects can be referred to the description of the above method embodiments, and for brevity, will not be repeated here. The processing device can be implemented using general-purpose or dedicated chips and can perform corresponding operations by executing computer program instructions.

[0128] This disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0129] This disclosure also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0130] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0131] Figure 5 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. For example, the electronic device 1900 may be provided as a server or a terminal device. (Refer to...) Figure 5 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0132] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). Electronic device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM Mac OS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0133] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of an electronic device 1900 to perform the above-described method.

[0134] Computer-readable storage media can be tangible devices capable of holding and storing programs / instructions used by instruction execution devices. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0135] The computer program (or computer-readable program instructions) described herein can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage medium in the respective computing / processing device.

[0136] The computer program (or computer program instructions) used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions to implement various aspects of this disclosure.

[0137] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0138] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0139] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0140] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0141] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. An airborne maintenance method suitable for electric vertical takeoff and landing aircraft, characterized in that, An airborne maintenance system applied to electric vertical takeoff and landing (EVTOL) aircraft, the method comprising: Acquire multi-source data of an electric vertical takeoff and landing (EVTOL) aircraft; wherein, the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents the data during the actual flight of the EVTOL aircraft, and the simulation test data represents the data obtained by simulation testing using an engineering simulator; The multi-source data of the electric vertical takeoff and landing aircraft are fused to generate fused data; Based on the fused data, one or more of the following operations are performed: fault prediction, health status assessment, and maintenance recommendation generation.

2. The method according to claim 1, characterized in that, The acquisition of multi-source data of the electric vertical takeoff and landing aircraft includes: acquiring multi-source data of the target system in the electric vertical takeoff and landing aircraft, wherein the target system includes one or more of the following: flight control system, energy system, power system, and environmental control system.

3. The method according to claim 2, characterized in that, The actual operational data includes one or more of the following: real-time flight parameters, preset key parameters of the target system, and event or fault information of the target system: The method further includes: When the airborne maintenance system is in flight mode, it continuously monitors the real-time flight parameters and the preset key parameters of the target system, and collects and records the event or fault information reported by the target system.

4. The method according to claim 1, characterized in that, The simulation test data includes: normal operating condition simulation data and / or fault simulation data; The method further includes: The normal operating conditions of the electric vertical takeoff and landing aircraft are simulated using the engineering simulator, and the normal operating condition simulation data is generated. And / or, The engineering simulator is used to simulate the faults of the electric vertical takeoff and landing aircraft and generate the fault simulation data.

5. The method according to claim 1, characterized in that, The following operations are performed based on the fused data: fault prediction, health status assessment, and maintenance recommendation generation, including: During the operation of the airborne maintenance system, a trained fault prediction model is used to process the fused data to predict potential faults of the electric vertical takeoff and landing aircraft. Based on the predicted results of potential failures, maintenance recommendations and / or health status assessment reports for the electric vertical takeoff and landing aircraft are generated; wherein, in the process of generating maintenance recommendations, one or more of the aircraft maintenance manual, safety constraints, and priority rules are incorporated.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: When the airborne maintenance system is in maintenance mode, it performs one or more of the following operations in response to user commands: fault report query, manual inspection, data loading, and configuration management.

7. An airborne maintenance device suitable for electric vertical takeoff and landing aircraft, characterized in that, An airborne maintenance system for electric vertical takeoff and landing (EVTOL) aircraft, the device comprising: The acquisition module is used to acquire multi-source data of the electric vertical takeoff and landing (EVTOL) aircraft; wherein, the multi-source data of the EVTOL aircraft includes at least: actual operation data and simulation test data; the actual operation data represents the data during the actual flight process of the EVTOL aircraft, and the simulation test data represents the data obtained by simulation testing using an engineering simulator; The data fusion module is used to fuse multi-source data from the electric vertical takeoff and landing aircraft to generate fused data. The predictive maintenance module is used to perform one or more of the following operations based on the fused data: fault prediction, health status assessment, and maintenance recommendation generation.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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