Passive electro-hydraulic rotor brake control system based on "fail-safe" mode

Abstract

This invention discloses a passive electro-hydraulic wheel brake control system based on a "fail-safe" mode, relating to the field of wheel brake control technology. The system comprises the following components: a wheel brake subsystem module, an internal communication network module, and a blockchain state sharing module. By introducing an intelligent mutual backup and cooperation mechanism, this invention enables adjacent wheel brake systems to quickly identify and adjust their braking force distribution strategies when a wheel brake system fails, thus sharing some of the braking pressure on the failed wheel. This effectively avoids safety issues such as reduced overall braking performance or aircraft deviation caused by the failure of individual wheel brake systems, significantly improving the reliability and safety of the UAV wheel brake system. Simultaneously, the system's dynamic load balancing capability continuously adjusts the mutual backup and cooperation strategy according to changes in the load of each wheel, ensuring that the braking system is always in an optimal collaborative working state.

Description

Technical Field

[0001] This invention relates to the field of wheel brake control technology, specifically a passive electro-hydraulic wheel brake control system based on a "fail-safe" mode. Background Technology

[0002] With the rapid development of drone technology, drones have been widely used in many fields such as military reconnaissance, civilian aerial photography, and cargo transportation. Especially in the field of large drones, multi-wheel design has become a key factor in improving flight stability and load-bearing capacity. As an important system to ensure the safe landing of drones, the performance and reliability of the drone wheel braking system are directly related to the overall safety and stability of the drone. Traditional wheel braking systems mostly adopt mechanical or electronic control methods, but when faced with complex and ever-changing flight environments and mission requirements, these systems have gradually exposed problems such as insufficient control precision, poor information interaction, and weak fault response capabilities.

[0003] Traditional wheel braking systems have significant shortcomings when dealing with large, multi-wheeled UAVs. On the one hand, a failure in one wheel braking system often leads to the failure of the entire braking system, causing serious safety issues such as aircraft veering off course. This propagation and amplification effect of a single point of failure seriously threatens the safe landing of UAVs. On the other hand, the lack of an effective information exchange mechanism between the various wheel braking systems results in poor inter-system cooperation, making it difficult to cope with braking demands under complex operating conditions. Furthermore, traditional systems lack effective measures to ensure the authenticity and reliability of information exchange, making them susceptible to external interference or malicious attacks, further reducing the system's safety and stability. Therefore, traditional wheel braking systems can no longer meet the high reliability and safety requirements of modern UAVs.

[0004] To address the aforementioned issues, it is necessary to optimize the existing passive electro-hydraulic wheel brake control system. By introducing innovative elements such as multiple wheel brake subsystems, internal communication networks, and blockchain state sharing modules, an intelligent mutual backup and cooperation mechanism and a state sharing trust mechanism between wheel brake systems can be achieved. Therefore, developing a passive electro-hydraulic wheel brake control system based on a "fail-safe" mode that can comprehensively achieve the above characteristics is of great significance. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a passive electro-hydraulic wheel brake control system based on a "fail-safe" mode. By introducing an intelligent mutual backup and cooperation mechanism, each wheel brake system can independently complete its braking control task during normal operation. When a wheel brake system malfunctions, adjacent wheels can quickly identify and adjust their braking force distribution strategies to share some of the braking pressure on the faulty wheel, thereby ensuring that the overall braking effect is not affected. Furthermore, this invention utilizes blockchain technology to construct a state sharing and trust mechanism, enabling encrypted recording, real-time querying, and verification of state information between wheel brake systems, effectively improving the authenticity and reliability of information interaction.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a passive electro-hydraulic wheel brake control system based on a "fail-safe" mode, the system comprising the following components: a wheel brake subsystem module, an internal communication network module, and a blockchain status sharing module;

[0007] The wheel brake subsystem module consists of a passive electro-hydraulic actuator submodule, a sensor unit submodule, a controller unit submodule, and a brake actuator submodule.

[0008] The passive electro-hydraulic actuator submodule adopts a hydraulic and electrical integrated structure. It relies on an external power supply for normal power supply or the energy storage element to release energy when the power is off to drive the hydraulic pump. The hydraulic valve adjusts the direction and pressure of the fluid flow. According to the control command, the hydraulic pressure is output to the brake actuator to realize the control of the wheel braking force.

[0009] The sensor unit submodule uses Hall effect speed sensors and strain gauge pressure sensors, which are located on the wheel rotation shaft and the hydraulic pipeline of the brake actuator. The wheel speed and brake pressure parameters are collected at a preset sampling frequency, and after analog-to-digital conversion, they are transmitted to the controller unit in real time through a high-speed data bus to provide a data basis for brake control decisions.

[0010] The controller unit submodule is built on a hardware platform based on a high-performance microcontroller and integrates multiple communication interfaces. During normal braking, it uses a control algorithm to calculate control signals based on sensor data. During a fault, it uses a braking force distribution algorithm based on dynamic load balancing and combines load data obtained from the blockchain to redistribute braking force, generate control commands to drive the actuators, and periodically collects and organizes its own operating status information and transmits it to the blockchain module for recording.

[0011] The brake actuator submodule adopts a friction braking structure of brake pads and brake discs. It is connected to the hydraulic line of a passive electro-hydraulic actuator through a hydraulic piston. The hydraulic piston is driven by the hydraulic pressure output by the actuator to push the brake pads against the brake discs and use the friction between the two to brake the wheel. The friction force can be flexibly adjusted according to the change of hydraulic pressure to achieve different degrees of braking effect.

[0012] The internal communication network module adopts a star network topology, with the core switch as the center connecting each wheel brake subsystem. A custom Ethernet application layer communication protocol is formulated to ensure accurate message identification and format specifications, and a checksum mechanism is used to ensure data accuracy. At the same time, the hardware adopts a redundant design, and the software implements message retransmission and adaptive timeout processing mechanisms. Based on an adaptive timeout calculation formula that takes into account network congestion, the length of the message to be transmitted, and the average network communication bandwidth, the message retransmission timeout is dynamically adjusted to ensure the reliability and real-time performance of communication between subsystems.

[0013] The blockchain state sharing module includes an information encryption and recording submodule and an information query and verification submodule;

[0014] The information encryption recording submodule uses an asymmetric encryption algorithm combined with a hash function to encrypt the operating status information of the wheel brake system. At the same time, a key management server is used to centrally manage and periodically update the keys of all subsystems to ensure the security and timeliness of the encryption keys.

[0015] The information query and verification submodule resolves the target query request initiated by the wheel brake subsystem, retrieves encrypted information from the blockchain node, decrypts it using the sender's public key to obtain the original information and digest, recalculates the digest of the original information according to the verification formula and compares it with the decrypted digest. If they match, the verification is successful. The information can be used for collaborative decision-making, and operation logs are recorded for auditing and maintenance, thereby ensuring the authenticity and reliability of the information obtained from the blockchain.

[0016] Furthermore, in the wheel brake subsystem module, the controller unit submodule is built on a hardware platform based on a high-performance microcontroller, integrating multiple communication interfaces, including a high-speed data interface connected to the sensor unit, a control signal output interface connected to the passive electro-hydraulic actuator, and a network communication interface connected to the internal communication network.

[0017] Furthermore, in the aforementioned wheel brake subsystem module, the controller unit submodule uses a control algorithm during normal braking to calculate the control signal based on sensor data. The algorithm formula is as follows: Where u(t) is the control signal output by the controller to the passive electro-hydraulic actuator, and K p K i K dThese are the proportional coefficient, integral coefficient, and differential coefficient, respectively; e(t) is the target rotational speed and actual rotational speed of the wheels at the current moment; α is the aircraft speed influence coefficient; v aircruft β is the aircraft's real-time speed, β is the wheel load influence coefficient, and F is... load It is the real-time load of the wheel.

[0018] Furthermore, in the aforementioned wheel braking subsystem module, when the controller unit submodule determines that its own system has malfunctioned based on sensor data or receives a fault signal from other wheel braking systems via the internal communication network, it enters a fault response mode, marks its own fault status, and sends fault information through the internal communication network. Based on the real-time load status of each wheel obtained from the blockchain state sharing module and the preset cooperation strategy model, it calculates the braking force distribution strategy for itself and adjacent wheels, generates new control commands, and sends them to the passive electro-hydraulic actuator submodule to share some of the braking pressure of the faulty wheel. During braking, each wheel braking system continuously monitors its own and other wheels' real-time load status and continuously adjusts the mutual backup cooperation strategy based on the dynamic load balancing algorithm to adapt to the changes in wheel load caused by cargo movement and center of gravity changes during aircraft braking, ensuring overall braking effectiveness.

[0019] Furthermore, in the wheel braking subsystem module, the controller unit submodule calculates the braking force distribution strategy for itself and adjacent wheels based on the real-time load status of each wheel obtained from the blockchain state sharing module and the preset cooperation strategy model. The calculation formula is as follows: in, This refers to the adjusted braking force of the adjacent wheel i after a malfunction in the braking system of one of the wheels. F is the braking force that the adjacent wheel i originally borne before the accident occurred. fault It is the braking force borne by the faulty wheel at the moment of the accident, n adjacent It refers to the number of adjacent wheels that can help share the braking force of a faulty wheel. It is the real-time load of the adjacent wheel i. It is the sum of the loads of all adjacent wheels that participate in sharing the braking force of the faulty wheel.

[0020] Furthermore, in the wheel brake subsystem module, the controller unit submodule continuously adjusts the mutual backup cooperation strategy based on a dynamic load balancing algorithm, the algorithm formula of which is: in, λ is the initial base braking force set for the i-th wheel, and λ is the braking force adjustment coefficient. It represents the change in the load on the i-th wheel at time t relative to the previous time. This represents the real-time braking force of the i-th wheel at time t after dynamic load balancing adjustment. It is the sum of the load changes of all n participating wheels at time t, ΔF total (t) is the total amount of adjustment required for the overall braking force at time t, based on the current state of the aircraft.

[0021] Furthermore, in the aforementioned wheel brake subsystem module, the brake actuator submodule utilizes the friction between the two to brake the wheel, and flexibly adjusts the magnitude of the friction force according to changes in hydraulic pressure. The adjustment formula is as follows: Among them, f braking P represents the actual braking friction force generated during wheel braking, μ is the coefficient of friction between the brake pads and the brake disc, and P is the friction coefficient between the brake pads and the brake disc. hydraulic It is the hydraulic oil pressure output from the passive electro-hydraulic actuator to the hydraulic chamber of the brake actuator, A pistom It is the effective working area of ​​the hydraulic piston in the brake actuator, k load It is the wheel load influencing factor, α v It is the correlation coefficient of aircraft speed, v aircraft It is the aircraft's real-time flight speed, v ref This is a reference speed.

[0022] Furthermore, the internal communication network module dynamically adjusts the message retransmission timeout based on an adaptive timeout calculation formula that considers factors such as network congestion level, message length to be transmitted, and average network bandwidth. The formula is as follows: Among them, T timeout It is the timeout period for message retransmission, T base γ is the basic timeout setting, L is the network congestion adjustment coefficient, C is the length of the message to be transmitted, and C is the average communication bandwidth of the current network.

[0023] Furthermore, in the blockchain state sharing module, the information encryption record submodule uses an asymmetric encryption algorithm combined with a hash function to encrypt the operating status information of the wheel brake system. The calculation formula is: E message =RSA public (Hash(SHA-256(message))||message), where E message It is the final encrypted operating status information of the wheel braking system, RSA. public This indicates that the encryption operation is performed using the recipient's RSA public key. Hash(SHA-256(message)) is a hash operation performed on the original wheel brake system operating status information using the SHA-256 hash function to obtain a fixed-length message digest. message is the original operating status information of the wheel brake system. || indicates a concatenation operation, which concatenates the hashed message digest with the original information for encryption.

[0024] Furthermore, in the blockchain state sharing module, the information query and verification submodule recalculates the digest of the original information according to the verification formula and compares it with the decrypted digest. The formula is as follows: Here, Verify represents the result of information verification. If it is True, it proves that the information is complete and has not been tampered with; if it is False, it indicates that the information may have encountered problems during transmission or storage and should not be used. Hash(SHA-256(message)) d The message contains the decrypted operating status information of the wheel braking system. d The SHA-256 hash function is used again to perform a hash operation, resulting in a recalculated message digest. digest It is the original message digest separated from the encrypted information obtained from the blockchain node after decryption.

[0025] Compared with existing technologies, this passive electro-hydraulic wheel brake control system based on "fail-safe" mode has the following advantages:

[0026] I. This invention introduces an intelligent mutual backup and cooperation mechanism, enabling adjacent wheel braking systems to quickly identify and adjust their braking force distribution strategies when a wheel braking system fails, thus sharing some of the braking pressure on the faulty wheel. This effectively avoids safety issues such as reduced overall braking performance or aircraft deviation caused by the failure of individual wheel braking systems, significantly improving the reliability and safety of the UAV wheel braking system. Simultaneously, the system's dynamic load balancing capability continuously adjusts the mutual backup and cooperation strategy based on changes in the load of each wheel, ensuring the braking system is always in an optimal collaborative working state, further enhancing the system's stability and safety.

[0027] Second, this invention utilizes blockchain technology to construct a state sharing and trust mechanism for wheel braking systems. Through encryption and blockchain recording, the operational status information of each wheel braking system is authentically and completely preserved and is tamper-proof. When other wheel braking systems need to know the status of a particular wheel braking system, they can send a query request to the blockchain in real time and obtain verified and accurate information. This mechanism not only improves the authenticity and integrity of information interaction but also effectively prevents the transmission of erroneous information due to communication failures or malicious attacks, thereby ensuring the security and stability of cooperation between wheel braking systems. This is of great significance for improving the fault response capability and overall performance of UAVs under complex working conditions.

[0028] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0030] Figure 1 The flowchart shows the operation of a passive electro-hydraulic impeller brake control system based on a "fail-safe" mode.

[0031] Figure 2 This is a schematic diagram of a passive electro-hydraulic rotor brake control system based on a "fail-safe" mode. Detailed Implementation

[0032] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0033] Example 1

[0034] In the logistics industry, multi-wheeled transport drones are used to transport various goods between cities and suburbs, especially in areas with inconvenient transportation or those requiring rapid delivery. For example, a transport drone used for logistics delivery in suburban areas has a maximum takeoff weight of 300 kg and six wheels. It needs to frequently take off and land at different logistics distribution points. The ground materials and flatness of these takeoff and landing sites vary, which places extremely high demands on the reliability and accuracy of the wheel braking system. This ensures that the drone can safely and accurately load and unload goods and take off and land smoothly, thus ensuring the efficient completion of logistics delivery tasks.

[0035] Each wheel is equipped with a passive electro-hydraulic actuator using a large-capacity accumulator as its energy storage element. Testing has shown that its energy storage is sufficient to maintain wheel braking operation for at least 30 seconds in the event of a sudden external power failure, meeting the needs of handling potential power supply issues during logistics transportation. The hydraulic pumps and valves are high-precision, high-durability models, professionally calibrated to accurately adjust hydraulic pressure under varying environmental temperatures, humidity levels, and frequent use, ensuring stable and reliable braking force output. A high-precision Hall effect speed sensor with an accuracy of ±0.5 rpm is installed on the wheel's rotating shaft to precisely monitor wheel speed changes. A high-precision capacitive pressure sensor with an accuracy of ±5 Pascals is installed in the hydraulic lines of the brake actuator to accurately monitor brake pressure in real time. Simultaneously, a weight sensor is installed on the bottom of the drone, combined with a cargo loading information system, to accurately obtain the real-time load on the wheels, providing crucial data for brake control. The hardware platform is built on a high-performance ARM architecture microcontroller with 1000MB of RAM and 15GB of storage, providing powerful computing and data storage capabilities. On the software side, the proportional coefficient K in the normal braking control algorithm is preset. p =0.6, Integral coefficient K i =0.1, differential coefficient K d =0.2, aircraft speed influence coefficient α=0.3, wheel load influence coefficient β=0.25. The relevant parameters in the fault response collaborative control algorithm are set according to the wheel layout and logistics transportation characteristics, such as the braking force adjustment coefficient λ=0.8 (this value is determined through a large number of actual logistics delivery flight tests and simulation analysis, and is used to dynamically adjust the braking force). The brake pads of the brake actuator are made of high wear-resistant and high friction coefficient ceramic matrix composite material, which is suitable for frequent braking in logistics transportation. The brake disc is made of high-strength alloy steel, and the friction coefficient between the two is stable between 0.4-0.5. The effective working area of ​​the hydraulic piston is 0.01 square meters, which can efficiently convert hydraulic pressure into braking friction force to achieve smooth and effective braking of the wheels.

[0036] The internal communication network module is configured with a star network topology. The core switch is an industrial-grade switch with shock and interference resistance, and is equipped with dual power supply modules, each with a rated power of 100 watts and redundant network ports. This allows it to adapt to complex environments such as bumps and electromagnetic interference that may be encountered during logistics transportation, ensuring stable and reliable communication. The custom Ethernet application layer communication protocol specifies detailed parameters for various messages. For example, in cargo weight information messages, data for different weight ranges occupies a specific number of bytes, and in fault signal messages, the fault location code occupies 4 bytes, ensuring the accuracy of information transmission. A basic timeout T is set. base=500 milliseconds, network congestion adjustment coefficient γ=0.5, adaptively adjust the message retransmission timeout according to the actual network status to ensure smooth communication between the wheel brake subsystems and meet the real-time collaboration needs in logistics and distribution operations.

[0037] For the configuration of the blockchain state sharing module, each wheel brake subsystem generates an RSA public-private key pair. The public key is used for information verification and public sharing, while the private key is strictly kept and used to encrypt its own state information. The key management server is set to update the key every 40 days and adopts a rigorous key update verification process to ensure the continuity and security of encryption and decryption. Blockchain nodes are constructed one-to-one with each wheel and data synchronization is achieved through a stable and reliable P2P protocol. The system securely stores and shares the operating status information of the wheel brake system (including sensor data, fault information, control command execution status, etc.), providing an accurate and reliable basis for collaborative decision-making among the wheel brake systems.

[0038] After the drone is loaded with cargo and takes off, it flies along the preset delivery route and arrives at the logistics distribution point at its destination to prepare for landing. During the landing rollout phase, the sensor unit of the wheel brake subsystem collects data in real time, including wheel speed, brake pressure, and wheel load obtained through weight sensors combined with cargo loading information. This data is then transmitted to the controller unit, which calculates control signals based on the control algorithm. For example, the current actual rotational speed of the wheel is 100 rpm, the target rotational speed is set to 40 rpm (determined based on the landing requirements of the logistics transport drone), the aircraft speed is 8 m / s, and the wheel load is estimated to be 800 Newtons (calculated by considering factors such as cargo weight and aircraft attitude). The control signal u(t) is calculated using the above algorithm, which drives the passive electro-hydraulic actuator to output the corresponding hydraulic pressure to the brake actuator, so that the wheel generates appropriate braking friction, achieving smooth deceleration and braking of the wheel, ensuring the safe landing of the drone, ensuring that the cargo can be loaded and unloaded smoothly, and not affecting subsequent logistics and delivery tasks.

[0039] Suppose that during a landing, one wheel braking system malfunctions, for example, due to a blockage in the hydraulic lines causing an abnormally high pressure detected by the pressure sensor. The malfunctioning wheel braking system immediately enters a safety mode and sends a fault signal to other wheel braking systems via the internal communication network. Upon receiving the signal, the other wheel braking systems obtain accurate information such as the real-time load of each wheel from the blockchain state sharing module, and then recalculate their respective braking force distribution based on the fault response collaborative control algorithm. Assuming the braking force F borne by the faulty wheel at the moment of failure fault = 300 Newtons, n is the number of adjacent wheels participating in the load sharing. adjacent =4 (determined based on wheel layout), real-time load F of adjacent wheel i load，iThe loads are 700 Newtons, 750 Newtons, 650 Newtons, and 800 Newtons respectively (accurate data obtained through weight sensors and related calculations, verified by blockchain), and the total load of each adjacent wheel. Newton, the braking force originally borne by each adjacent wheel. Based on the normal braking control algorithm, the calculated braking forces are 220 Newtons, 240 Newtons, 200 Newtons, and 260 Newtons, respectively. Using the above formula, the adjusted braking force can be calculated for each adjacent wheel. The controller unit drives the passive electro-hydraulic actuator to adjust the output hydraulic pressure, sharing the braking pressure of the faulty wheel, ensuring the aircraft can brake smoothly, guaranteeing the safe landing of the logistics drone, and not affecting subsequent logistics delivery processes. Furthermore, during subsequent braking, if the cargo shifts during landing (causing changes in wheel load), the braking force of each wheel system is adjusted in real time according to a dynamic load balancing algorithm. For example, the load change of wheel 1 is detected at a certain moment. Newton, the sum of all changes in load on the wheels Newton, the total adjustment ΔF required for the overall braking force. total (t) = 400 Newtons (determined through comprehensive analysis of changes in cargo position and aircraft attitude), the initial braking force of wheel 1. Given Newton's law and a braking force adjustment coefficient λ = 0.8, the adjusted braking force of wheel 1 at that moment can be calculated. The same principle applies to other wheels, which are adjusted in real time to ensure that the braking force always adapts to changes in the aircraft's condition, maintains good braking performance, and guarantees the smooth operation of logistics and distribution.

[0040] Example 2

[0041] In the field of surveying and mapping, multi-wheeled drones are often used to conduct high-precision surveying and mapping operations on large areas of terrain, landforms, and urban planning areas. For example, a drone used for topographic surveying in mountainous areas has a maximum takeoff weight of 250 kg and four wheels. It needs to take off and land in various complex mountainous terrains and at different altitudes, facing many challenges such as large terrain undulations and changing wind directions. Therefore, there are strict requirements for the adaptability and safety of the wheel braking system to ensure that the drone can land stably and accurately collect surveying and mapping data, thus ensuring the smooth progress of the surveying and mapping mission.

[0042] Each wheel's passive electro-hydraulic actuator is equipped with a high-performance accumulator as an energy storage element. Its energy storage can ensure that the wheel braking operation can be maintained for at least 28 seconds in the event of an external power failure, which is sufficient to cope with the power instability that may be encountered during mountain surveying. The hydraulic pump and hydraulic valve are specially designed to adapt to air pressure changes at different altitudes and the bumps and tilts caused by complex terrain, and to precisely adjust the hydraulic pressure to ensure the accuracy and stability of the braking force output. A high-precision magnetoelectric speed sensor with an accuracy of ±0.7 rpm is installed on the wheel's rotating shaft, and a high-precision fiber optic pressure sensor with an accuracy of ±7 Pascals is installed in the hydraulic lines of the braking actuator to accurately monitor the braking pressure. At the same time, the UAV is equipped with high-precision meteorological sensors and terrain measurement sensors. Combined with Geographic Information System (GIS) data, the terrain slope, wind direction and speed at the wheel's location and the resulting changes in wheel load are accurately analyzed, providing a comprehensive and accurate reference for braking control.

[0043] The hardware platform is built using a high-performance microcontroller, with 900MB of RAM and 13GB of storage, capable of meeting complex computational and data storage requirements. On the software side, the proportional coefficient K in the normal braking control algorithm is preset. p =0.58, integral coefficient K i =0.095, differential coefficient K d =0.17, aircraft speed influence coefficient α =0.27, wheel load influence coefficient β =0.23. The relevant parameters in the fault response collaborative control algorithm are set according to the wheel layout and the characteristics of mountainous surveying, such as the braking force adjustment coefficient λ =0.78 (this value was obtained through multiple simulated flights and actual surveying operations in mountainous areas). The brake pads of the brake actuator are made of silicon carbide composite material that is resistant to high temperature and wear and adaptable to different road conditions. The brake disc is made of high-strength titanium alloy. The friction coefficient between the two is stable between 0.35 and 0.45. The effective working area of ​​the hydraulic piston is 0.0095 square meters, which can effectively convert hydraulic pressure into braking friction force, realize stable braking of the wheels in complex mountainous environments, and meet the requirements of surveying operations.

[0044] The internal communication network module adopts a star network topology. The core switch is an industrial-grade switch with high anti-interference capability and a wide operating temperature range. It is equipped with dual power supply modules, each with a rated power of 90 watts and redundant network ports, ensuring normal operation of the communication network in the complex electromagnetic environment and variable temperature conditions of mountainous areas. The custom Ethernet application layer communication protocol specifies various messages in detail. For example, different terrain parameters occupy a specific number of bytes in terrain measurement data messages, and the fault altitude information occupies 6 bytes in fault signal messages, ensuring accurate information transmission. A basic timeout T is set. base=480 milliseconds, network congestion adjustment coefficient γ=0.48, adaptively adjust the message retransmission timeout according to the actual network status to ensure the reliability of communication between the wheel brake subsystems and meet the collaborative needs in the surveying process.

[0045] For the blockchain state sharing module, each wheel brake subsystem is configured to generate RSA public-private key pairs. The public key is used to verify information externally, while the private key is strictly kept safe to encrypt its own operating status information. The key management server is set to update the key every 38 days and adopts a rigorous key update process to ensure the continuity and security of information encryption and decryption. Blockchain nodes are constructed one-to-one with each wheel and data synchronization is achieved through a reliable P2P protocol. This ensures that the operating status information of the wheel brake system (including sensor data, fault information, control command execution status, etc.) can be stored and shared securely and reliably, providing strong support for collaborative decision-making among the wheel brake systems.

[0046] After takeoff, the drone flies along a predetermined surveying route. Once it has completed the surveying of an area, it prepares to land at a designated landing point in the mountainous region. During the landing roll, the sensor unit of the wheel brake subsystem collects real-time data on wheel speed, brake pressure, and wheel load based on terrain slope, wind direction, and wind speed obtained from meteorological sensors, terrain measurement sensors, and GIS data. This data is then transmitted to the controller unit, which calculates the control signal based on the control algorithm. For example, if the current actual rotational speed of the landing gear is 95 revolutions per minute, the target rotational speed is set to 32 revolutions per minute (based on the landing safety requirements of the mapping UAV), the aircraft speed is 7.5 meters per second, and the estimated load on the landing gear is 700 Newtons (calculated using relevant data considering factors such as terrain, weather, and aircraft attitude), the control signal u(t) can be calculated using the above algorithm. This drives the passive electro-hydraulic actuator to output appropriate hydraulic pressure to the brake actuator, generating suitable friction between the brake pads and brake disc to achieve smooth braking of the landing gear, gradually reducing the aircraft speed until it safely stops in the landing area, ensuring a safe landing for the UAV and facilitating subsequent takeoffs to continue the mapping mission. If, during a landing, the braking system of one landing gear malfunctions, for example, due to sensor moisture caused by extreme weather, resulting in data deviation, the malfunctioning landing gear braking system immediately enters a safe mode and broadcasts a fault signal to other landing gear braking systems via the internal communication network. Upon receiving the fault signal, other landing gear braking systems query the blockchain state sharing module for information such as the real-time load of each landing gear, and then recalculate their respective braking force distribution based on the fault response collaborative control algorithm. Assuming the braking force F borne by the faulty wheel at the moment of failure fault = 260 Newtons, n is the number of adjacent gears participating in the load sharing. adjacent =3 (determined based on wheel layout), real-time load of adjacent wheel i The loads are 650 Newtons, 700 Newtons, and 600 Newtons respectively (accurate data calculated using a combination of data from meteorological sensors, topographic sensors, etc., and verified by blockchain), representing the total load of each adjacent rotor. Newton, the braking force originally borne by each adjacent wheel. Based on the normal braking control algorithm, the calculated braking forces are 200 Newtons, 220 Newtons, and 180 Newtons respectively. Using the above formula, the adjusted braking force can be calculated for each adjacent wheel. The controller unit drives the passive electro-hydraulic actuator to adjust the output hydraulic pressure to share the braking pressure of the faulty wheel, ensuring the aircraft can brake smoothly and guaranteeing the safe landing of the mapping UAV. This prevents wheel failure from affecting mapping work and equipment safety. Furthermore, during subsequent braking, if the wheel load changes due to changes in terrain slope (such as a local steep slope in the landing area), the braking force of each wheel system is adjusted in real time according to a dynamic load balancing algorithm. For example, the load change of wheel 1 is detected at a certain moment. Newton, the sum of all changes in load on the wheels Newton, the total adjustment ΔF required for the overall braking force. total (t) = 360 Newtons, the initial braking force of wheel 1 Given Newton's law and a braking force adjustment coefficient λ = 0.78, the adjusted braking force of wheel 1 at that moment can be calculated. The other wheels are adjusted in real time in the same way to ensure that the braking force always adapts to changes in the aircraft's condition, maintain good braking performance, and ensure surveying operations.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A passive electro-hydraulic gear brake control system based on a "fail-safe" mode, characterized in that, The system comprises the following components: a wheel brake subsystem module, an internal communication network module, and a blockchain status sharing module; The wheel brake subsystem module consists of a passive electro-hydraulic actuator submodule, a sensor unit submodule, a controller unit submodule, and a brake actuator submodule. The passive electro-hydraulic actuator submodule adopts a hydraulic and electrical integrated structure. It relies on an external power supply for normal power supply or the energy storage element to release energy when the power is off to drive the hydraulic pump. The hydraulic valve adjusts the direction and pressure of the fluid flow. According to the control command, the hydraulic pressure is output to the brake actuator to realize the control of the wheel braking force. The sensor unit submodule uses Hall effect speed sensors and strain gauge pressure sensors, which are located on the wheel rotation shaft and the hydraulic pipeline of the brake actuator. The wheel speed and brake pressure parameters are collected at a preset sampling frequency, and after analog-to-digital conversion, they are transmitted to the controller unit in real time through a high-speed data bus to provide a data basis for brake control decisions. The controller unit submodule is built on a hardware platform based on a high-performance microcontroller and integrates multiple communication interfaces. During normal braking, it uses a control algorithm to calculate control signals based on sensor data. During a fault, it uses a braking force distribution algorithm based on dynamic load balancing and combines load data obtained from the blockchain to redistribute braking force, generate control commands to drive the actuators, and periodically collects and organizes its own operating status information and transmits it to the blockchain module for recording. The brake actuator submodule adopts a friction braking structure of brake pads and brake discs. It is connected to the hydraulic line of a passive electro-hydraulic actuator through a hydraulic piston. The hydraulic piston is driven by the hydraulic pressure output by the actuator to push the brake pads against the brake discs and use the friction between the two to brake the wheel. The friction force can be flexibly adjusted according to the change of hydraulic pressure to achieve different degrees of braking effect. The internal communication network module adopts a star network topology, with the core switch as the center connecting each wheel brake subsystem. A custom Ethernet application layer communication protocol is formulated to ensure accurate message identification and format specifications, and a checksum mechanism is used to ensure data accuracy. At the same time, the hardware adopts a redundant design, and the software implements message retransmission and adaptive timeout processing mechanisms. Based on an adaptive timeout calculation formula that takes into account network congestion, the length of the message to be transmitted, and the average network communication bandwidth, the message retransmission timeout is dynamically adjusted to ensure the reliability and real-time performance of communication between subsystems. The blockchain state sharing module includes an information encryption and recording submodule and an information query and verification submodule; The information encryption recording submodule uses an asymmetric encryption algorithm combined with a hash function to encrypt the operating status information of the wheel brake system. At the same time, a key management server is used to centrally manage and periodically update the keys of all subsystems to ensure the security and timeliness of the encryption keys. The information query and verification submodule resolves the target query request initiated by the wheel brake subsystem, retrieves encrypted information from the blockchain node, decrypts it using the sender's public key to obtain the original information and digest, recalculates the digest of the original information according to the verification formula and compares it with the decrypted digest. If they match, the verification is successful. The information can be used for collaborative decision-making, and operation logs are recorded for auditing and maintenance, thereby ensuring the authenticity and reliability of the information obtained from the blockchain.

2. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the aforementioned wheel brake subsystem module, the controller unit submodule is built on a hardware platform based on a high-performance microcontroller, integrating multiple communication interfaces, including a high-speed data interface connected to the sensor unit, a control signal output interface connected to the passive electro-hydraulic actuator, and a network communication interface connected to the internal communication network.

3. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the wheel brake subsystem module, the controller unit submodule uses a control algorithm to calculate the control signal based on sensor data during normal braking. The algorithm formula is as follows: Where u(t) is the control signal output by the controller to the passive electro-hydraulic actuator, and K p K i K d These are the proportional coefficient, integral coefficient, and differential coefficient, respectively; e(t) is the target rotational speed and actual rotational speed of the wheels at the current moment; α is the aircraft speed influence coefficient; v aircruft β is the aircraft's real-time speed, β is the wheel load influence coefficient, and F is... load It is the real-time load of the wheel.

4. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the aforementioned wheel braking subsystem module, when the controller unit submodule determines that its own system has malfunctioned based on sensor data or receives a fault signal from other wheel braking systems via the internal communication network, it enters a fault response mode, marks its own fault status, and sends fault information through the internal communication network. Based on the real-time load status of each wheel obtained from the blockchain state sharing module and the preset cooperation strategy model, it calculates the braking force distribution strategy for itself and adjacent wheels, generates new control commands, and sends them to the passive electro-hydraulic actuator submodule to share some of the braking pressure of the faulty wheel. During braking, each wheel braking system continuously monitors its own and other wheels' real-time load status and continuously adjusts the mutual backup cooperation strategy based on the dynamic load balancing algorithm to adapt to the changes in wheel load caused by cargo movement and center of gravity changes during aircraft braking, ensuring overall braking effectiveness.

5. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 4, characterized in that, In the aforementioned wheel braking subsystem module, the controller unit submodule calculates the braking force distribution strategy for itself and adjacent wheels based on the real-time load status of each wheel obtained from the blockchain state sharing module and a preset cooperation strategy model. The calculation formula is as follows: in, This refers to the adjusted braking force of the adjacent wheel i after a malfunction in the braking system of one of the wheels. F is the braking force that the adjacent wheel i originally borne before the accident occurred. fault It is the braking force borne by the faulty wheel at the moment of the accident, n adjacent It refers to the number of adjacent wheels that can help share the braking force of a faulty wheel. It is the real-time load of the adjacent wheel i. It is the sum of the loads of all adjacent wheels that participate in sharing the braking force of the faulty wheel.

6. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 4, characterized in that, In the aforementioned wheel brake subsystem module, the controller unit submodule continuously adjusts the mutual backup cooperation strategy based on a dynamic load balancing algorithm. The algorithm formula is as follows: in, λ is the initial base braking force set for the i-th wheel, and λ is the braking force adjustment coefficient. It represents the change in the load on the i-th wheel at time t relative to the previous time. This represents the real-time braking force of the i-th wheel after dynamic load balancing adjustment at time t. It is the sum of the load changes of all n participating wheels at time t, ΔF total (t) is the total amount of adjustment required for the overall braking force at time t, based on the current state of the aircraft.

7. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the aforementioned wheel brake subsystem module, the brake actuator submodule utilizes the friction between the wheel and the brake actuator to brake the wheel, and flexibly adjusts the magnitude of the friction force according to changes in hydraulic pressure. The adjustment formula is as follows: Among them, f braking P represents the actual braking friction force generated during wheel braking, μ is the coefficient of friction between the brake pads and the brake disc, and P is the friction coefficient between the brake pads and the brake disc. hydraulic It is the hydraulic oil pressure output from the passive electro-hydraulic actuator to the hydraulic chamber of the brake actuator, A pistom It is the effective working area of ​​the hydraulic piston in the brake actuator, k load It is the wheel load influencing factor, α v It is the correlation coefficient of aircraft speed, v aircraft It is the aircraft's real-time flight speed, v ref This is a reference speed.

8. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, The internal communication network module dynamically adjusts the message retransmission timeout based on an adaptive timeout calculation formula that considers factors such as network congestion, the length of the message to be transmitted, and the average network bandwidth. The formula is as follows: Among them, T timeout It is the timeout period for message retransmission, T base γ is the basic timeout setting, γ is the network congestion adjustment coefficient, l is the length of the message to be transmitted, and C is the average communication bandwidth of the current network.

9. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the blockchain state sharing module, the information encryption record submodule uses an asymmetric encryption algorithm combined with a hash function to encrypt the operating status information of the wheel brake system. The calculation formula is: E message =RSA public (Hash)SHA-256(message))||message), where E message It is the final encrypted operating status information of the wheel braking system, RSA. public This indicates that the encryption operation is performed using the recipient's RSA public key. Hash(SHA-256(message)) is a hash operation performed on the original wheel brake system operating status information using the SHA-256 hash function to obtain a fixed-length message digest. message is the original operating status information of the wheel brake system. || indicates a concatenation operation, which concatenates the hashed message digest with the original information for encryption.

10. The passive electro-hydraulic wheel brake control system based on "fail-safe" mode according to claim 1, characterized in that, In the blockchain state sharing module, the information query and verification submodule recalculates the digest of the original information according to the verification formula and compares it with the decrypted digest. The formula is as follows: Here, Verify represents the result of information verification. If it is True, it proves that the information is complete and has not been tampered with; if it is False, it indicates that the information may have encountered problems during transmission or storage and should not be used. Hash(SHA-256(message)) d The message contains the decrypted operating status information of the wheel braking system. d The SHA-256 hash function is used again to perform a hash operation, resulting in a recalculated message digest. digest It is the original message digest separated from the encrypted information obtained from the blockchain node after decryption.

Images