Rail crane control method, electronic equipment and rail crane

Abstract

The invention provides a control method of a rail crane, electronic equipment and the rail crane. According to the method, the running state data and the road condition data of the rail crane are obtained in real time, and the corresponding control parameters are generated according to the preset running strategy set, so that the running state of the rail crane is intelligently adjusted. According to the method, the adaptability of the rail crane to the complex environment in the automatic running process is achieved, control signals can be dynamically adjusted according to different road conditions and running states, and therefore it is ensured that the crane stably runs under the conditions of ramps, turning, obstacles and the like, and the safety and stability in the transportation process are remarkably improved. In addition, through accurate coordination of the control module and the operation module, the control method has a high automation level, the requirement for human intervention is reduced, and the overall operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rail cranes, and in particular to a control method of a rail crane, electronic equipment and a rail crane. Background Art

[0002] Underground monorail crane is a kind of rail transportation equipment suitable for mine tunnels, mainly used for the transportation of materials, equipment and personnel in mines. Its operation relies on the rail system installed on the top of the tunnel. The crane travels along the rail, which is efficient, safe and flexible. It is an important part of the modern mine transportation system.

[0003] In the related art, there is a technical problem that the automatic driving of the rail crane in the tunnel is not stable enough. Summary of the invention

[0004] The purpose of the present invention is to overcome the above technical deficiencies and provide a control method for a rail crane, an electronic device and a rail crane to solve the technical problem in the related art that the automatic driving of the rail crane in the tunnel is not stable enough.

[0005] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a control method for a rail crane, wherein the rail crane comprises at least a control module and an operation module electrically connected thereto, wherein the control method is performed by the control module, and the method comprises: During the automatic driving of the rail crane, the running state data and the road condition data of the rail crane are respectively obtained; Inputting the operation data and road condition data into a preset operation strategy set to obtain control parameter data; wherein the control parameter data is parameter data for controlling the operation state of the rail crane; Based on the control parameter data, a control signal is generated, and the control signal is sent to the operation module, so that the operation module adjusts the operation state of the rail crane.

[0006] Furthermore, the rail crane further comprises a first detection module and a second detection module electrically connected to the control module, wherein the first detection module is used to detect the running state data of the rail crane, and the second detection module is used to detect the road condition data of the rail crane; The steps of respectively acquiring the running status data and the road condition data of the rail crane include: Sending data acquisition requests to the first detection module and the second detection module respectively; The operating status data returned by the first detection module and the road condition data returned by the second detection module are received respectively.

[0007] Further, the operating state data at least includes driving force data, the road condition data at least includes slope data; the operating strategy set at least includes a first operating strategy, and the first operating strategy is an operating strategy for characterizing an uphill stage of the rail crane; wherein the step of inputting the operating data and the road condition data into a preset operating strategy set to obtain control parameter data includes: Matching the slope data with a first pre-matching condition in the first operation strategy; wherein the first pre-matching condition is a matching condition for determining whether the current road section is an uphill section based on the current slope data; When the matching result indicates that the current road section is an uphill road section, the driving force data is matched with the first post-matching condition in the first operation strategy; wherein the first post-matching condition is a matching condition at least used to determine whether the current driving force meets the uphill requirement; At least when the matching result indicates that the current driving force does not meet the uphill requirement, the first control parameter data is generated; wherein the first control parameter data is the control parameter data of the rail crane representing the uphill section; the first control parameter data at least includes the driving force control parameter.

[0008] Furthermore, the operating status data also includes driving speed data, load data and operating power data; the second pre-matching condition also includes: a judgment condition for judging whether the driving speed data is adapted to the uphill stage and a judgment condition for judging whether the operating power data is overloaded; wherein the step of generating the first control parameter data includes: Update the current speed control parameters according to the preset uphill safety speed range; Update current driving force control parameters according to slope data, load data and driving speed data; Update the current power control parameters according to the preset device safety threshold.

[0009] Furthermore, the operation strategy set also includes a second operation strategy, and the second operation strategy is an operation strategy for characterizing a downhill stage of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: Matching the slope data with a second pre-matching condition in the second operation strategy; wherein the second pre-matching condition is a matching condition for determining whether the current road section is a downhill section based on the current slope data; When the matching result indicates that the current road section is a downhill section, the driving force data is matched with the second post-matching condition in the second operation strategy; wherein the second post-matching condition is a matching condition for at least determining whether the current driving force meets the downhill requirement; At least when the matching result indicates that the current driving force does not meet the downhill requirement, second control parameter data is generated; wherein the second control parameter data is control parameter data of the rail crane representing the downhill section; the second control parameter data at least includes a driving force control parameter.

[0010] Furthermore, the road condition data also includes track curve information; The operation strategy set also includes a third operation strategy, and the third operation strategy is an operation strategy for characterizing a turning phase of a rail crane; wherein the step of inputting the operation data and the road condition data into a preset operation strategy set to obtain control parameter data includes: Matching the track curve information with the third pre-matching condition in the third operation strategy; wherein the third pre-matching condition is a matching condition for determining whether the current section is a turning section based on the current track curve information; When the matching result indicates that the current road section is a turning road section, matching the driving speed data with the third post-matching condition in the third operation strategy; wherein the third post-matching condition is a matching condition at least used to determine whether the current driving speed data meets the turning requirement; When the matching result indicates that the current driving speed does not meet the turning requirement, third control parameter data is generated; wherein the third control parameter data is control parameter data of the rail crane representing the turning section; the third control parameter data at least includes a speed control parameter.

[0011] Furthermore, the road condition data also includes image information in front of the vehicle; The operation strategy set also includes a fourth operation strategy, and the fourth operation strategy is an operation strategy for characterizing that there is an obstacle in front of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: Matching the image information in front of the vehicle with the fourth pre-matching condition in the fourth operation strategy; wherein the fourth pre-matching condition is a matching condition for determining whether the current road section has an obstacle based on the current image information in front of the vehicle; When the matching result indicates that there is an obstacle in front of the vehicle, the driving speed data is matched with the fourth post-matching condition in the fourth operation strategy; wherein the fourth post-matching condition is at least used to determine whether the current driving speed data meets the matching condition when there is an obstacle in front of the vehicle; At least when the matching result indicates that the current driving speed does not meet the requirements, fourth control parameter data is generated; wherein the fourth control parameter data is control parameter data of the rail crane when there is an obstacle in front of the vehicle; the fourth control parameter data at least includes a speed control parameter.

[0012] Furthermore, the road condition data also includes obstacle distance information; the operation status data also includes braking force control parameters; The running state data also includes braking force data; the fourth post-matching condition also includes: a matching condition for determining whether the current obstacle distance information is within a safe distance; wherein the step of generating the fourth control parameter data includes: Based on the obstacle distance information, a braking force control parameter is updated.

[0013] In a second aspect, the present invention provides an electronic device, comprising: a memory, and one or more processors communicatively coupled to the memory; The memory stores instructions that can be executed by the one or more processors. The instructions are executed by the one or more processors to enable the one or more processors to implement the above method.

[0014] In a third aspect, the present invention provides a rail crane, which is used to execute the above method or includes the above electronic device.

[0015] Beneficial effects: The present invention obtains the operating status data and road condition data of the rail crane in real time, and generates corresponding control parameters according to a preset operating strategy set, thereby intelligently adjusting the operating status of the rail crane. The method realizes the adaptability of the rail crane to complex environments during automatic driving, and can dynamically adjust the control signal according to different road conditions and operating states, thereby ensuring the smooth operation of the crane in ramps, turns, obstacles, etc., and significantly improving the safety and stability during transportation. In addition, through the precise coordination of the control module and the operating module, the control method has a high level of automation, reduces the need for human intervention, and improves the overall operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a control method of a rail crane provided by an embodiment of the present invention; Figure 2 It is a flow chart of a control method of a rail crane provided by an embodiment of the present invention; Figure 3 It is a block diagram of an electronic device used in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0018] In the related art, there is a technical problem that the automatic driving of the rail crane in the tunnel is not stable enough.

[0019] Specifically, it is particularly evident in complex roadway environments (such as those with ramps, curves or other obstacles). Traditional autonomous driving technology is difficult to accurately perceive changes in the roadway environment, resulting in the following defects in the operation of the crane: When the crane passes through ramps or complex sections, the speed may not be adjusted in time, which may lead to unstable operation. The power system is not well adapted to the operating environment, and it is difficult to adjust the driving force in time according to the slope or load, which may cause insufficient power or overload. In the event of obstacles ahead or emergencies, the crane's deceleration and braking are not smooth enough, posing a safety hazard.

[0020] like Figure 1 As shown, a control method for a rail crane, the rail crane at least comprises a control module and an operation module electrically connected thereto, the control module is an execution subject of the control method, and the method comprises: Step S12: During the automatic driving of the rail crane, the running status data and the road condition data of the rail crane are respectively obtained.

[0021] In this implementation, the control module may be an embedded control system (Embedded Control System), a programmable logic controller (PLC), or a vehicle control unit (VCU).

[0022] In this implementation, the control module may be an MCU or a DSP.

[0023] In this implementation, the operation module may be: The motor drive module, that is, when the power system of the rail crane is driven by the motor.

[0024] The brake module can be used to control the deceleration and parking of the rail crane.

[0025] The light and signal module can alarm when encountering obstacles.

[0026] The fuel injection and engine management module, that is, when the power system of the rail crane is driven by an internal combustion engine, the fuel injection and engine management module can manage the fuel injection amount and injection timing of the diesel engine or gasoline engine. During the uphill stage, the fuel injection amount is increased to increase the torque output and ensure sufficient power.

[0027] The clutch and transmission module, that is, when the power system of the rail crane is driven by an internal combustion engine, can adjust the power output to match the actual needs through the clutch and transmission to achieve smooth power transmission.

[0028] Heat dissipation and cooling module, that is, when the power system of the rail crane is driven by an internal combustion engine, since the internal combustion engine will generate a lot of heat when running at high load, a heat dissipation system is required to ensure that the engine operates within a normal temperature range.

[0029] In this embodiment, the rail crane may be a rail crane running on a single track, or may be a rail crane running on double tracks or even multiple tracks.

[0030] In this embodiment, the control module can obtain the running status data and road condition data of the rail crane respectively by the following methods: Step S122: Sending data acquisition requests to the first detection module and the second detection module respectively.

[0031] Step S124: receiving the operating status data returned by the first detection module and the road condition data returned by the second detection module respectively.

[0032] In this embodiment, the operating status data may include driving force data, driving speed data, load data and operating power data.

[0033] In this embodiment, the road condition data may include slope data, track curve information, vehicle front image information and obstacle distance information.

[0034] In this embodiment, the first detection module may be a driving force data sensor (for example, a torque sensor, a force sensor, etc.). Specifically, the driving force data sensor may monitor the output driving force of a motor or an internal combustion engine, capture torque changes, and thereby obtain driving force data.

[0035] In this embodiment, the first detection module may be a speed sensor (eg, an encoder, a tachometer, etc.), which can detect the travel speed of the rail crane in real time.

[0036] In this embodiment, the first detection module may be a load sensor (eg, a strain gauge, a force sensor, etc.) The load sensor may acquire current load data by detecting the load of the crane.

[0037] In this embodiment, the first detection module may be a power sensor, which can monitor the power output of the motor or engine in real time and calculate the current operating power.

[0038] In this embodiment, the second detection module may be a slope sensor (for example, an inclination sensor, an acceleration sensor, etc.). The slope sensor may determine the magnitude of the slope by monitoring the inclination angle of the track. When the rail crane runs on a slope, the slope sensor may help the control device determine whether it is necessary to increase the driving force or adjust the speed.

[0039] In this embodiment, the second detection module may be a track curve information detection module (eg, a laser radar, a GPS, an accelerometer, etc.). The track curve information detection module may detect track curve information of the track (eg, curvature and angle).

[0040] In this embodiment, the second detection module may be a vehicle front image information sensor (eg, a camera, a visual sensor, an image processing module, etc.) Specifically, the image information in front of the rail crane may be acquired in real time through a vehicle-mounted camera or other image sensors.

[0041] In this embodiment, the second detection module may be an obstacle distance sensor (eg, a laser radar, an ultrasonic sensor, an infrared sensor, etc.) Specifically, a laser radar, an ultrasonic sensor or an infrared sensor may be used to detect the distance of the obstacle ahead in real time.

[0042] In some embodiments, the operating status data may also include: temperature data, battery charge data (eg, an electric rail crane), rotation speed data (eg, the rotation speed of a motor or an engine, etc.), and the like.

[0043] In some implementations, the road condition data may also include: road surface flatness data, slipperiness data, obstacle type data, and the like.

[0044] Step S14: inputting the operation data and road condition data into a preset operation strategy set to obtain control parameter data; wherein the control parameter data is parameter data for controlling the operation state of the rail crane.

[0045] In this embodiment, the operation strategy set may include: a first operation strategy, wherein the first operation strategy is an operation strategy for characterizing an uphill phase of a rail crane.

[0046] In this embodiment, the operation strategy set may include: a second operation strategy, wherein the second operation strategy is an operation strategy for characterizing a downhill phase of the rail crane.

[0047] In this embodiment, the operation strategy set may include: a third operation strategy, and the third operation strategy is an operation strategy for characterizing a turning phase of a rail crane.

[0048] In this embodiment, the operation strategy set may include: a fourth operation strategy, and the fourth operation strategy is an operation strategy for characterizing that there is an obstacle in front of the rail crane.

[0049] In this embodiment, each operation strategy may further include pre-matching conditions, post-matching conditions and control parameter data, wherein the control parameter data may be pre-set or generated in real time based on operation data and road condition data (for example, it may be generated based on machine learning, deep learning, or optimization algorithm).

[0050] Specifically, in this embodiment, the pre-matching condition can be a judgment condition for judging whether the rail crane meets the judgment condition for entering the corresponding operation strategy. Once the pre-condition is met, the control module will enter the subsequent processing of the operation strategy.

[0051] More specifically, the pre-matching condition of the first operation strategy may be: whether the slope of the current road section is greater than 0 (i.e., whether it is uphill). If the slope data indicates that the current road section is an uphill section, the match is successful and the operation strategy of the uphill stage is entered.

[0052] The pre-matching condition of the second operation strategy may be: whether the slope of the current road section is less than 0 (i.e., whether it is downhill). If the slope data indicates that the current road section is a downhill section, the match is successful and the operation strategy of the downhill stage is entered.

[0053] The pre-matching condition of the third operation strategy may be: whether the current track is a curve. If the curve radius of the track is less than a preset threshold, it means that the track is a curve section, then the match is successful and the operation strategy of the curve phase is entered.

[0054] The pre-matching condition of the fourth operation strategy may be: whether there is an obstacle at present. If the obstacle distance information indicates that there is an obstacle ahead (eg, the distance is less than the set safety distance), the match is successful and the operation strategy of obstacle detection is entered.

[0055] The post-matching condition is that after the pre-condition is met, the control module can further verify and judge the specific operating status. The post-matching condition can be based on real-time operating data (such as vehicle speed, driving force, load, etc.) and road condition data (such as slope, turning information, obstacle information, etc.) to ensure that the response of the rail crane can adapt to the actual operating needs. If the post-matching condition is met, the control module can adjust the control parameters based on the current actual situation to execute the corresponding control strategy.

[0056] More specifically, the post-matching conditions of the first operation strategy may be: whether the current driving force is sufficient to cope with the uphill demand. Whether the current vehicle speed is suitable for the uphill stage to avoid loss of control due to too fast or too slow. If the current driving force is insufficient, or the vehicle speed is not suitable for the uphill condition (for example, too fast or too slow), the driving force and speed need to be adjusted to ensure safe uphill.

[0057] The post-matching conditions of the second operation strategy may be: whether the current driving force is suitable for downhill demand; whether the current vehicle speed is too fast and needs to be decelerated; if the vehicle speed is too fast or the driving force is not suitable, deceleration processing or adjustment of the driving force is required.

[0058] The post-matching condition of the third operation strategy may be: when turning, whether the vehicle speed is within a safe range and whether it needs to be decelerated. If the vehicle speed is too fast, it is necessary to decelerate and adjust the steering angle to ensure that the crane turns stably.

[0059] The post-matching conditions of the fourth operation strategy may be: whether the vehicle speed is suitable for obstacle avoidance operation. Whether the current distance of the obstacle is within a safe range. If the obstacle is too close or the vehicle speed is too fast, braking or deceleration measures must be taken immediately to ensure safe parking or avoidance.

[0060] In this embodiment, during the automatic driving of the rail crane, after the control device obtains the operating data and road condition data, the current operating data and road condition data can be matched with the above-mentioned first operating strategy, second operating strategy, third operating strategy and fourth operating strategy respectively. When a certain operating strategy is hit and matched, the control parameter data of the hit operating strategy is executed.

[0061] For example, during the automatic driving of the rail crane, at a certain moment, the first operation strategy is hit and matched, indicating that the rail crane has driven to an uphill section. Therefore, the control device can generate a corresponding control signal based on the control parameter data corresponding to the first operation strategy.

[0062] In this embodiment, different operation strategies may correspond to control parameters. For example, the speed control parameters, driving force control parameters and power control parameters that the rail crane should adopt in the uphill stage may be pre-set. In other words, these control parameters may be pre-set, and when a certain operation strategy is triggered, the control device switches the current control parameters to the control parameters corresponding to the triggered operation strategy.

[0063] In some embodiments, the control parameters may not be pre-set, but may be generated in real time based on current operation data and / or road condition data, and a preset generation rule or generation algorithm. In other words, corresponding generation rules or generation algorithms are preset for different operation strategies, so as to generate corresponding control parameters in real time.

[0064] Specifically, the operation data and road condition data of the rail crane in different environments can be collected in advance to establish fuzzy rules. For example, by defining the fuzzy rules for the "uphill" stage, the slope data (such as small, medium, and large slopes) can be fuzzified into several levels, and then the corresponding control parameter range can be determined. The control module can perform fuzzy reasoning based on the operation data and road condition data in different environments to obtain appropriate control parameters.

[0065] Specifically, the operation data and road condition data of the rail crane in different environments can be collected in advance, and these data can be used to train machine learning models (for example, decision trees, neural networks, etc.) so that they can identify the operation strategies to be adopted under different conditions. When the rail crane is in motion, the control module first inputs the operation data and road condition data into a preset operation strategy set, and first determines the corresponding operation strategy (target operation strategy). Then, based on the model corresponding to the target operation strategy, control parameters are generated. That is, the control module inputs the operation data and / or road condition data into the trained model, and the model predicts the most suitable control parameters based on the current input data.

[0066] In some embodiments, part of the above control parameters may be pre-set, for example, the driving force control parameter may be pre-set, and when a certain operation strategy is triggered, the current driving force control parameter is directly switched to the control parameter corresponding to the operation strategy. Another part of the control parameters may be generated in real time based on the current operation data and / or road condition data, and a preset generation rule or generation algorithm. For example, it may be a power control parameter, etc.

[0067] Step S16: Based on the control parameter data, a control signal is generated, and the control signal is sent to the operation module, so that the operation module adjusts the operation state of the rail crane.

[0068] In this embodiment, the control module can generate control signals based on the control parameter data. These control signals can be digital or analog signals, and the control signals can instruct the operation module how to perform corresponding operations, such as adjusting the power output of the motor, adjusting the braking system, changing the vehicle speed, etc.

[0069] Specifically, the control signal may be a speed control signal, and the speed control signal may instruct the motor drive module to control the vehicle speed, which may include changing the rotation speed of the motor.

[0070] The control signal may be a driving force control signal, which may be used to adjust the traction of the motor or the internal combustion engine to ensure that the crane has sufficient driving force on different road sections (such as uphill, downhill, turning, etc.).

[0071] The control signal may be a power control signal, which can ensure that the operation of the device does not exceed its power upper limit, thereby avoiding overload operation.

[0072] The control signal may be a brake signal, and the brake signal may instruct the brake module to perform a deceleration or parking operation.

[0073] After the control signal is generated, the control module can send the control signal to the corresponding operation module through the communication interface to ensure that the rail crane can perform the task as expected. The operation module can include multiple subsystems responsible for controlling various components of the rail crane, such as the motor drive module, brake module, fuel injection and engine management module, clutch and transmission module, and heat dissipation and cooling module.

[0074] Specifically, the motor drive module can adjust the output power, speed or torque of the motor according to the received control signal, so that the rail crane can run stably on different sections such as uphill, downhill, and turning. For example, in the uphill stage, if the control signal requires an increase in driving force, the motor drive module will increase the motor power output to provide greater traction.

[0075] The brake module can activate the brake system according to the control signal, control the brake pressure, braking force, etc., and smoothly slow down or stop the vehicle. When encountering obstacles or emergencies, the brake module can respond quickly to avoid accidents.

[0076] When the rail crane uses an internal combustion engine, the fuel injection and engine management module receives power control and driving force signals from the control module. For example, during the uphill phase, according to the control signal, the fuel injection and engine management module adjusts the fuel injection amount and injection timing to ensure that the engine produces sufficient torque output to meet the uphill demand and avoid insufficient power.

[0077] This implementation method obtains the operating status data and road condition data of the rail crane in real time, and generates corresponding control parameters according to a preset operating strategy set, thereby intelligently adjusting the operating status of the rail crane. This method realizes the adaptability of the rail crane to complex environments during automatic driving, and can dynamically adjust the control signal according to different road conditions and operating states, thereby ensuring the smooth operation of the crane in ramps, turns, obstacles, etc., significantly improving the safety and stability during transportation. In addition, through the precise coordination of the control module and the operation module, the control method has a high level of automation, reduces the need for human intervention, and improves overall operating efficiency.

[0078] In some embodiments, the rail crane further comprises a first detection module and a second detection module electrically connected to the control module, wherein the first detection module is used to detect the running state data of the rail crane, and the second detection module is used to detect the road condition data of the rail crane; The steps of respectively acquiring the running status data and the road condition data of the rail crane include: Step S122: Send data acquisition requests to the first detection module and the second detection module respectively.

[0079] Step S124: receiving the operating status data returned by the first detection module and the road condition data returned by the second detection module respectively.

[0080] This implementation method can realize comprehensive monitoring of the rail crane by setting up a first detection module and a second detection module, which are responsible for collecting the operating status data and road condition data of the rail crane respectively. The first detection module focuses on the internal status of the rail crane (such as driving force, speed, load, etc.) to ensure that the power system and operating status of the crane are normal; the second detection module is responsible for collecting road condition information (such as slope, track curve, obstacle distance, etc.) to help the control system evaluate changes in the external environment in real time. By acquiring and processing these two types of data separately in the control module, the driving status of the crane can be accurately adjusted and the control strategy can be optimized, thereby improving the operating stability and safety of the rail crane in complex environments and ensuring more efficient and reliable operations during automatic driving.

[0081] like Figure 2 As shown, in some embodiments, the operating state data at least includes driving force data, and the road condition data at least includes slope data; the operating strategy set at least includes a first operating strategy, and the first operating strategy is an operating strategy for characterizing an uphill stage of the rail crane; wherein the step of inputting the operating data and the road condition data into a preset operating strategy set to obtain control parameter data includes: Step S142: Match the slope data with the first pre-matching condition in the first operation strategy; wherein the first pre-matching condition is a matching condition for determining whether the current road section is an uphill section based on the current slope data.

[0082] In this embodiment, the rail crane can obtain the slope data of the current road section in real time, and can obtain the inclination angle or slope size of the road surface through a slope sensor (e.g., an acceleration sensor, an inclination sensor, etc.) installed on the vehicle. The first pre-matching condition can be used to determine whether the current slope exceeds a certain set value, and then determine whether the rail crane is traveling on an uphill section. The first pre-matching condition can be defined as: IF slope>0, it is considered to be an uphill section. If the slope data is greater than 0, it meets the first pre-matching condition, and the control module will determine that the current section is an uphill section and continue to execute subsequent matching conditions. If the slope data is less than or equal to 0, the current section does not meet the uphill condition, and the control module will skip the subsequent processing of the first operation strategy. For example, the control module can match the slope data with the pre-matching conditions of other operation strategies.

[0083] Step S144: When the matching result indicates that the current road section is an uphill section, the driving force data is matched with the first post-matching condition in the first operation strategy; wherein the first post-matching condition is at least a matching condition for determining whether the current driving force meets the uphill requirement.

[0084] In this embodiment, the control module can monitor the output torque of the engine or motor through a sensor (e.g., a torque sensor) to infer the driving force. The first post-matching condition can be used to verify whether the current driving force meets the minimum driving force requirement required for the uphill section. Specifically, if the current driving force is less than the preset uphill driving force threshold, the driving force does not meet the uphill requirement.

[0085] In this embodiment, the first post-matching condition can also be used to verify whether the current speed or power meets the speed requirement or power requirement required for the uphill section. Specifically, if the current speed is too fast or too slow, or the power is insufficient to maintain a smooth uphill, the control module will also consider that these parameters do not meet the uphill requirement. For example, if the current speed does not meet the uphill requirement or the current power is insufficient, it is considered that the uphill requirement is not met.

[0086] Step S146: At least when the matching result indicates that the current driving force does not meet the uphill requirement, generate first control parameter data; wherein the first control parameter data is control parameter data of the rail crane representing the uphill section; the first control parameter data at least includes a driving force control parameter.

[0087] In this embodiment, the first control parameter data may be generated when the matching result indicates that the current driving force does not meet the uphill requirement.

[0088] In this embodiment, the first control parameter data may be generated under the premise that the matching result indicates that the current driving force does not meet the uphill requirement, and further, the current speed or power does not meet the uphill requirement.

[0089] In this embodiment, the first control parameter data may also be generated when the matching result indicates that the front driving force, speed and power do not meet the uphill requirement.

[0090] In this embodiment, if the matching result indicates that the current driving force is insufficient, control parameters (such as driving force control parameters) can be generated according to the current information such as slope, load and speed, and the power output of the motor or internal combustion engine can be adjusted to increase the driving force. If the current speed or power does not meet the uphill requirements, the control module can also generate corresponding control parameters (such as speed control parameters or power control parameters) to adjust the speed or power output to ensure that the crane maintains stable operation during the uphill process. If the driving force, speed and power do not meet the uphill requirements, the control module can simultaneously generate multiple control parameters (such as driving force, speed, power control parameters) to ensure that the crane can operate smoothly during the uphill stage.

[0091] In this embodiment, the first control parameter data at least includes a driving force control parameter.

[0092] In this embodiment, the first control parameter data may also include a speed control parameter. It is understandable that in the uphill stage, if the vehicle speed is too fast, it may lead to loss of control, so the control module may reduce the speed.

[0093] In this embodiment, the first control parameter data may also include a power control parameter. It is understandable that in the uphill phase, since more driving force is required, the control module may provide sufficient support by increasing the power output.

[0094] In this embodiment, the first control parameter data may also include torque control parameters, fuel injection control parameters, temperature control parameters, and the like.

[0095] This implementation method can realize comprehensive monitoring of the rail crane by setting up a first detection module and a second detection module, which are responsible for collecting the operating status data and road condition data of the rail crane respectively. The first detection module focuses on the internal status of the rail crane (such as driving force, speed, load, etc.) to ensure that the power system and operating status of the crane are normal; the second detection module is responsible for collecting road condition information (such as slope, track curve, obstacle distance, etc.) to help the control module evaluate changes in the external environment in real time. By acquiring and processing these two types of data separately in the control module, the driving status of the crane can be accurately adjusted and the control strategy can be optimized, thereby improving the operating stability and safety of the rail crane in complex environments and ensuring more efficient and reliable operations during automatic driving.

[0096] In some embodiments, the operating state data further includes driving speed data, load data, and operating power data; the second pre-matching condition further includes: a judgment condition for judging whether the driving speed data is adapted to the uphill stage and a judgment condition for judging whether the operating power data is overloaded; wherein the step of generating the first control parameter data includes: Step S1462: Update the current speed control parameters according to the preset uphill safety speed range.

[0097] In this embodiment, a safe speed range for the uphill phase can be preset, and the safe speed range can be determined according to the slope of the track, the load, the power limit of the equipment and other factors (such as the friction coefficient, the vehicle type, etc.).

[0098] In this embodiment, the current driving speed can be compared with the preset safe speed range. If the current driving speed exceeds the preset uphill safe speed range (for example, the vehicle speed is too fast), the control module will generate a lower speed control parameter, and then generate a corresponding control signal to reduce the vehicle speed to ensure that the vehicle speed is within the safe range; if the current speed is lower than the safe range (for example, the vehicle speed is too slow), the control module will generate a higher speed control parameter, and then generate a corresponding control signal to increase the vehicle speed to ensure that the vehicle speed is within the safe range.

[0099] Step S1464: Update the current driving force control parameters according to the slope data, load data and driving speed data.

[0100] In this embodiment, the control module can input the slope data, load data and driving speed data into a preset function model to obtain the target driving force control parameters.

[0101] In this embodiment, the control module can input the slope data, load data and driving speed data into a data table (different slope data, load data and driving speed data can correspond to different target driving force control parameters) to obtain the target driving force control parameters.

[0102] In this embodiment, the control module can input the slope data, load data and driving speed data into a pre-trained machine learning model or a deep learning model to obtain the target driving force control parameters.

[0103] Step S1466: Update the current power control parameters according to the preset device safety threshold.

[0104] In this embodiment, a device safety threshold for the uphill stage may be preset, and the device safety threshold may be the maximum power limit that the device (such as a motor, an engine, a control system, etc.) can withstand. Exceeding this threshold may cause the device to be overloaded, overheated, or even damaged. The device safety threshold may be a power safety threshold for devices such as motors and engines.

[0105] In this embodiment, if the current power output is close to or exceeds the preset safety threshold, the control module will generate a smaller power control parameter. If the power output is lower than the power required for going uphill, the control module will increase the power output to provide sufficient driving force. At this time, the control module will dynamically calculate the required power based on information such as the slope, load and vehicle speed, and increase the power output by adjusting the speed of the motor or the fuel injection amount of the engine.

[0106] In this embodiment, the control module can input the slope data, load data and driving speed data into a preset function model to obtain the target power control parameters.

[0107] In this embodiment, the control module can input the slope data, load data and driving speed data into a data table (different slope data, load data and driving speed data can correspond to different target driving force control parameters) to obtain the target power control parameters.

[0108] In this embodiment, the control module can input the slope data, load data and driving speed data into a pre-trained machine learning model or a deep learning model to obtain the target power control parameters.

[0109] This implementation method optimizes the control strategy for the uphill stage by combining the travel speed data, load data and operating power data. First, the current speed control parameters are updated through the preset uphill safety speed range to ensure that the crane maintains a safe and stable speed during the uphill process. Secondly, the driving force control parameters are updated in real time based on the slope data, load data and travel speed data to ensure that the rail crane provides sufficient power during the uphill process to avoid insufficient power or instability. Finally, the power control parameters are updated according to the preset equipment safety threshold to prevent overload and ensure that the crane can run smoothly when going uphill without damaging the equipment. Through this series of dynamic adjustments, the control module can accurately control the operation of the crane under complex uphill conditions to ensure its efficient, safe and reliable operation.

[0110] In some embodiments, the operation strategy set further includes a second operation strategy, and the second operation strategy is an operation strategy for characterizing a downhill stage of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: The slope data is matched with a second pre-matching condition in the second operation strategy; wherein the second pre-matching condition is a matching condition for determining whether the current road section is a downhill section based on the current slope data.

[0111] In this embodiment, the purpose of this step is to determine whether the rail crane is traveling on a downhill section. By comparing with the preset downhill matching condition, the control module can determine whether it has entered the downhill stage, thereby triggering the downhill control strategy. The second pre-matching condition is to determine whether the current slope data indicates that the section is a downhill section. For example, if the slope data is less than 0 (i.e., the slope is a negative value), the current section is considered to be downhill.

[0112] When the matching result indicates that the current road section is a downhill section, the driving force data is matched with the second post-matching condition in the second operation strategy; wherein the second post-matching condition is a matching condition at least used to determine whether the current driving force meets the downhill requirement.

[0113] In this embodiment, the second post-matching condition may be to determine whether the current driving force meets the requirement of the downhill stage. For example, if the current driving force>the maximum driving force threshold required for downhill, the driving force does not meet the downhill requirement.

[0114] In this embodiment, the second post-matching condition may be to determine whether the current driving force meets the load condition.

[0115] In this embodiment, the second post-matching condition may be whether the coordination between the current driving force and the vehicle speed is reasonable.

[0116] In this implementation, the second post-matching condition may be that the current speed or power does not meet the downhill requirement.

[0117] At least when the matching result indicates that the front driving force does not meet the downhill requirement, second control parameter data is generated; wherein the second control parameter data is control parameter data of the rail crane representing the downhill section; the second control parameter data at least includes a driving force control parameter.

[0118] In this embodiment, the first control parameter data may be generated when the matching result indicates that the current driving force does not meet the downhill requirement.

[0119] In this embodiment, the first control parameter data may be generated under the premise that the matching result indicates that the current driving force does not meet the downhill requirement, and further, the current speed or power does not meet the downhill requirement.

[0120] In this embodiment, the first control parameter data may also be generated when the matching result indicates that the front driving force, speed and power do not meet the downhill requirement.

[0121] In this embodiment, the second control parameter data at least includes a driving force control parameter.

[0122] In this embodiment, the second control parameter data may further include a speed control parameter.

[0123] In this implementation manner, the second control parameter data may also include a power control parameter.

[0124] In this embodiment, the second control parameter data may also include torque control parameters, fuel injection control parameters, temperature control parameters, and the like.

[0125] In this embodiment, the control module can generate the second control parameter data through a function model. The control module can generate the corresponding control parameter data using a preset mathematical model according to real-time driving force, speed, power and other data.

[0126] In this embodiment, the control module can quickly generate control parameters through a preset lookup table. The control module can quickly obtain corresponding control parameters based on real-time input data such as slope, load, speed, etc. through the lookup table.

[0127] In this embodiment, the control module can generate the second control parameter data through a machine learning model.

[0128] This implementation method can accurately adjust the operating state of the rail crane when it is going downhill by setting the second operating strategy in the downhill stage, ensuring that the crane travels safely and stably during the downhill process. Through the real-time collection of slope data, the control module can determine whether it has entered a downhill section, thereby triggering the downhill strategy. Next, the control module checks the driving force data to ensure that the current driving force meets the downhill requirements and avoids loss of control or instability caused by excessive or insufficient power. If the driving force does not meet the downhill requirements, the control module will generate corresponding second control parameter data, including driving force control parameters, to adjust the power output of the motor or engine to ensure smooth deceleration or travel during the downhill process. Therefore, this implementation method can optimize the control of the rail crane in the downhill stage, avoid safety hazards when going downhill too quickly, and improve the safety, stability and energy efficiency of the equipment.

[0129] In some embodiments, the road condition data further includes track curve information; The operation strategy set also includes a third operation strategy, and the third operation strategy is an operation strategy for characterizing a turning phase of a rail crane; wherein the step of inputting the operation data and the road condition data into a preset operation strategy set to obtain control parameter data includes: The track curve information is matched with the third pre-matching condition in the third operation strategy; wherein the third pre-matching condition is a matching condition for determining whether the current section is a turning section based on the current track curve information.

[0130] In this embodiment, the track curve information may be the radius, angle, curvature, etc. of the curve.

[0131] In this embodiment, the track image can be captured by an image capture terminal to determine the track curve information.

[0132] In this embodiment, the third pre-matching condition can be used to determine whether the current track is a turning section. Specifically, if the current curve radius is less than the set turning radius threshold, the current section is a turning section.

[0133] When the matching result indicates that the current road section is a turning section, the driving speed data is matched with the third post-matching condition in the third operation strategy; wherein the third post-matching condition is a matching condition at least used to determine whether the current driving speed data meets the turning requirement.

[0134] In this embodiment, the third post-matching condition may be a matching condition for determining whether the current driving speed data meets the turning requirement.

[0135] On this basis, the third post-matching condition may be to determine whether the current driving force meets the turning requirement.

[0136] On this basis, the third post-matching condition may be to determine whether the current load meets the turning requirement.

[0137] In this embodiment, the third post-matching condition may be: IF the current speed is greater than the upper limit of the safe speed in the turning phase, the speed is not suitable for turning.

[0138] At least when the matching result indicates that the current driving speed does not meet the turning requirement, third control parameter data is generated; wherein the third control parameter data is control parameter data of the rail crane representing the turning section; the third control parameter data at least includes a speed control parameter.

[0139] In this embodiment, the control module may generate third control parameter data when the matching result indicates that the current driving speed does not meet the turning requirement.

[0140] On this basis, the control module can generate the third control parameter data when the matching result indicates that the driving force does not meet the turning requirement. The control module can generate the third control parameter data when the matching result indicates that the power does not meet the turning requirement. The control module can generate the third control parameter data when the matching result indicates that the load does not meet the turning requirement.

[0141] In this embodiment, the control module determines that the current driving speed does not meet the turning requirement (ie, the speed is too fast or too slow), and the control module triggers the control parameter adjustment.

[0142] In this embodiment, the control module can generate the third control parameter data through a function model. The control module can generate corresponding control parameter data using a preset mathematical model according to real-time driving force, speed, power and other data.

[0143] In this embodiment, the control module can quickly generate control parameters through a preset lookup table. The control module can quickly obtain corresponding control parameters based on real-time track curve information, load, speed and other input data through the lookup table.

[0144] In this embodiment, the control module can generate the third control parameter data through a machine learning model.

[0145] In this embodiment, in addition to the speed control parameter, the control module may also generate other control parameters, which may be: Driving force control parameters: If the current driving force is not sufficient to support stability during cornering, the control module will adjust the driving force control parameters.

[0146] Power control parameters: If more power is needed to maintain vehicle speed or accelerate when turning, the control module increases power output.

[0147] Torque control parameters: Depending on the needs of turning, the torque can be increased or decreased to maintain steering stability.

[0148] Temperature control parameters: If the device temperature rises due to increased power output, the control module can keep the temperature within a safe range by dissipating heat.

[0149] This implementation method can effectively control the driving state of the rail crane during the turning process by introducing track curve information and the operation strategy of the turning stage. By acquiring and analyzing the track curve information in real time, the system can accurately determine whether it has entered the turning section, and adjust the control parameters according to the real-time driving speed data to ensure that the driving speed of the crane meets the safety requirements when turning. Specifically, if the current speed is not suitable for turning, the control module will generate corresponding third control parameter data, such as speed control parameters, to adjust the speed to ensure that the crane turns smoothly and avoid loss of control or instability caused by too fast or too slow speed, thereby improving the safety and stability of the rail crane under complex turning conditions.

[0150] In some embodiments, the road condition data also includes vehicle front image information; The operation strategy set also includes a fourth operation strategy, and the fourth operation strategy is an operation strategy for characterizing that there is an obstacle in front of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: The vehicle front image information is matched with the fourth pre-matching condition in the fourth operation strategy; wherein the fourth pre-matching condition is a matching condition for determining whether a current road section has an obstacle based on the current vehicle front image information.

[0151] In this embodiment, the control module can collect the road condition image in front of the vehicle in real time through the camera or image processing sensor installed in front of the vehicle. The image information in front of the vehicle may include the shape and size of the obstacle.

[0152] In this embodiment, the fourth pre-matching condition can be used to determine whether there is an obstacle based on the image information in front of the vehicle. For example, if an obstacle is identified in the image information in front of the vehicle, then there is an obstacle in the current road section.

[0153] When the matching result indicates that there is an obstacle in front of the vehicle, the driving speed data is matched with the fourth post-matching condition in the fourth operation strategy; wherein the fourth post-matching condition is at least used to determine whether the current driving speed data meets the matching condition when there is an obstacle in front of the vehicle.

[0154] In this embodiment, the fourth post-matching condition may be a matching condition for determining whether the current driving speed data meets the condition when there is an obstacle in front of the vehicle.

[0155] On this basis, the fourth post-matching condition may be used to determine whether the current driving force meets the matching condition when there is an obstacle in front of the vehicle. The fourth post-matching condition may be used to determine whether the current braking force meets the matching condition when there is an obstacle in front of the vehicle.

[0156] At least when the matching result indicates that the current driving speed does not meet the requirements, fourth control parameter data is generated; wherein the fourth control parameter data is control parameter data of the rail crane when there is an obstacle in front of the vehicle; the fourth control parameter data at least includes a speed control parameter.

[0157] In this embodiment, the fourth control parameter data may be generated when the matching result indicates that the current driving speed does not meet the requirements.

[0158] On this basis, in this embodiment, when the matching result indicates that the current driving force does not meet the requirements, the fourth control parameter data may be generated. When the matching result indicates that the braking force does not meet the requirements, the fourth control parameter data may be generated.

[0159] In this embodiment, the fourth control parameter data may include a speed control parameter, a braking force control parameter, a driving force control parameter, and the like.

[0160] In this embodiment, the control module can generate the fourth control parameter data through the function model. Specifically, through the function model, the control module can calculate and generate the fourth control parameter data according to real-time data (such as the image information in front of the vehicle, the vehicle speed, the obstacle distance, etc.). For example, the control module can use a formula based on the safe speed range to calculate the speed control parameter suitable for the current environment.

[0161] In this embodiment, the control module can quickly generate control parameters through a preset lookup table. Control parameters for multiple different situations can be preset based on historical data. For example, a lookup table of vehicle speed and obstacle distance is preset, and the table stores the control parameters required under different vehicle speeds and obstacle distances. The control module compares the current vehicle speed, obstacle distance and other data with the preset conditions in the lookup table to quickly find the corresponding control parameters.

[0162] In this embodiment, the control module can generate the fourth control parameter data through a machine learning model.

[0163] This implementation method can detect in real time whether there is an obstacle in front of the rail crane by introducing the image information in front of the vehicle, thereby triggering the fourth operation strategy to ensure that the crane can respond promptly to environmental changes. When an obstacle is detected, the control module analyzes the current driving speed data to determine whether the vehicle speed needs to be adjusted to avoid collision with the obstacle or other safety hazards. If the vehicle speed does not meet the safety requirements, the control module will generate corresponding fourth control parameter data, such as speed control parameters, to avoid accidents by slowing down or stopping. Through this intelligent adjustment, the rail crane can operate more safely and efficiently in a complex operating environment, improving the safety and reliability of automated operations.

[0164] In some embodiments, the road condition data further includes obstacle distance information; the operating state data further includes braking force control parameters; The running state data also includes braking force data; the fourth post-matching condition also includes: a matching condition for determining whether the current obstacle distance information is within a safe distance; wherein the step of generating the fourth control parameter data includes: Based on the obstacle distance information, a braking force control parameter is updated.

[0165] In this embodiment, the control module obtains the distance information of the obstacle in real time through devices such as a front image sensor, a laser radar, an ultrasonic sensor or a laser rangefinder.

[0166] In this embodiment, the fourth post-matching condition also includes: determining whether the current obstacle distance information is within the matching condition of the safe distance. The safe distance threshold can be set according to the dynamic characteristics of the vehicle (such as acceleration, braking performance, road conditions, etc.). For example, if the distance between the obstacle and the crane is less than a certain set value (such as 2 meters), it means that emergency deceleration or parking measures need to be taken; if the obstacle is far away, the crane can continue to drive.

[0167] In this implementation, the control module may calculate the required braking force according to the obstacle distance and the current vehicle speed.

[0168] This implementation achieves precise control of the rail crane by combining obstacle distance information and braking force data. By obtaining the distance between the obstacle and the crane in real time and comparing it with the preset safety distance, the control module can determine whether the braking force needs to be adjusted. If the obstacle is too close, the control module will automatically update the braking force control parameters to ensure that the crane can slow down or stop in time to avoid a collision. Through this intelligent adjustment, the control module can improve the safety and stability of the crane in complex environments, avoid accidents caused by obstacles that are too close, and thus improve the safety and efficiency of automated operations.

[0169] According to an embodiment of the present invention, an electronic device is provided. Figure 3 The electronic device in this embodiment may include one or more of the following components: a processor, a network interface, a memory, a non-volatile memory, and one or more applications, wherein the one or more applications may be stored in the non-volatile memory and configured to be executed by one or more processors, and the one or more programs are configured to execute the method described in the aforementioned method embodiment.

[0170] According to an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer, the computer executes the method described in any of the above embodiments.

[0171] According to an embodiment of the present invention, a computer program product including instructions is also provided. When the instructions are executed by a computer, the computer executes a method in any one of the above embodiments.

[0172] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0173] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0174] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0175] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0176] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A control method for a rail crane, characterized in that: The rail crane at least includes a control module and an operation module electrically connected thereto, the control module is the execution subject of the control method, and the method includes: During the automatic driving of the rail crane, the running state data and the road condition data of the rail crane are respectively obtained; Inputting the operation data and road condition data into a preset operation strategy set to obtain control parameter data; wherein the control parameter data is parameter data for controlling the operation state of the rail crane; Based on the control parameter data, a control signal is generated, and the control signal is sent to the operation module, so that the operation module adjusts the operation state of the rail crane.

2. The method according to claim 1, characterized in that The rail crane further comprises a first detection module and a second detection module electrically connected to the control module, wherein the first detection module is used to detect the running state data of the rail crane, and the second detection module is used to detect the road condition data of the rail crane; The steps of respectively acquiring the running status data and the road condition data of the rail crane include: Sending data acquisition requests to the first detection module and the second detection module respectively; The operating status data returned by the first detection module and the road condition data returned by the second detection module are received respectively.

3. The method according to claim 1, characterized in that The operating state data at least includes driving force data, and the road condition data at least includes slope data; the operating strategy set at least includes a first operating strategy, and the first operating strategy is an operating strategy for characterizing an uphill stage of the rail crane; wherein the step of inputting the operating data and the road condition data into a preset operating strategy set to obtain control parameter data includes: Matching the slope data with a first pre-matching condition in the first operation strategy; wherein the first pre-matching condition is a matching condition for determining whether the current road section is an uphill section based on the current slope data; When the matching result indicates that the current road section is an uphill road section, the driving force data is matched with the first post-matching condition in the first operation strategy; wherein the first post-matching condition is a matching condition at least used to determine whether the current driving force meets the uphill requirement; At least when the matching result indicates that the current driving force does not meet the uphill requirement, the first control parameter data is generated; wherein the first control parameter data is the control parameter data of the rail crane representing the uphill section; the first control parameter data at least includes the driving force control parameter.

4. The method according to claim 3, characterized in that The operating status data also includes driving speed data, load data and operating power data; The second pre-matching condition also includes: a judgment condition for judging whether the driving speed data is adapted to the uphill stage and a judgment condition for judging whether the operating power data is overloaded; wherein the step of generating the first control parameter data includes: Update the current speed control parameters according to the preset uphill safety speed range; Update current driving force control parameters according to slope data, load data and driving speed data; Update the current power control parameters according to the preset device safety threshold.

5. The method according to claim 4, characterized in that The operation strategy set also includes a second operation strategy, which is an operation strategy for characterizing a downhill stage of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: Matching the slope data with a second pre-matching condition in the second operation strategy; wherein the second pre-matching condition is a matching condition for determining whether the current road section is a downhill section based on the current slope data; When the matching result indicates that the current road section is a downhill section, the driving force data is matched with the second post-matching condition in the second operation strategy; wherein the second post-matching condition is a matching condition for at least determining whether the current driving force meets the downhill requirement; At least when the matching result indicates that the current driving force does not meet the downhill requirement, second control parameter data is generated; wherein the second control parameter data is control parameter data of the rail crane representing the downhill section; the second control parameter data at least includes a driving force control parameter.

6. The method according to claim 4, characterized in that The road condition data also includes track curve information; The operation strategy set also includes a third operation strategy, and the third operation strategy is an operation strategy for characterizing a turning phase of a rail crane; wherein the step of inputting the operation data and the road condition data into a preset operation strategy set to obtain control parameter data includes: Matching the track curve information with the third pre-matching condition in the third operation strategy; wherein the third pre-matching condition is a matching condition for determining whether the current section is a turning section based on the current track curve information; When the matching result indicates that the current road section is a turning road section, matching the driving speed data with the third post-matching condition in the third operation strategy; wherein the third post-matching condition is a matching condition at least used to determine whether the current driving speed data meets the turning requirement; When the matching result indicates that the current driving speed does not meet the turning requirement, third control parameter data is generated; wherein the third control parameter data is control parameter data of the rail crane representing the turning section; the third control parameter data at least includes a speed control parameter.

7. The method according to claim 4, characterized in that The road condition data also includes vehicle front image information; The operation strategy set also includes a fourth operation strategy, and the fourth operation strategy is an operation strategy for characterizing that there is an obstacle in front of the rail crane; wherein the step of inputting the operation data and the road condition data into the preset operation strategy set to obtain the control parameter data includes: Matching the image information in front of the vehicle with the fourth pre-matching condition in the fourth operation strategy; wherein the fourth pre-matching condition is a matching condition for determining whether the current road section has an obstacle based on the current image information in front of the vehicle; When the matching result indicates that there is an obstacle in front of the vehicle, the driving speed data is matched with the fourth post-matching condition in the fourth operation strategy; wherein the fourth post-matching condition is at least used to determine whether the current driving speed data meets the matching condition when there is an obstacle in front of the vehicle; At least when the matching result indicates that the current driving speed does not meet the requirements, fourth control parameter data is generated; wherein the fourth control parameter data is control parameter data of the rail crane when there is an obstacle in front of the vehicle; the fourth control parameter data at least includes a speed control parameter.

8. The method according to claim 7, characterized in that The road condition data also includes obstacle distance information; The operating status data also includes braking force control parameters; The running state data also includes braking force data; the fourth post-matching condition also includes: a matching condition for determining whether the current obstacle distance information is within a safe distance; wherein the step of generating the fourth control parameter data includes: Based on the obstacle distance information, a braking force control parameter is updated.

9. An electronic device, characterized in that: include: a memory, and one or more processors communicatively coupled to the memory; Instructions executable by the one or more processors are stored in the memory. The instructions are executed by the one or more processors to enable the one or more processors to implement the method according to any one of claims 1 to 8.

10. A rail crane, characterized in that: The rail crane is used to perform the method according to any one of claims 1 to 8 or comprises the electronic equipment according to claim 9.

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