Methods, devices, equipment and media for the operation control of engineering equipment

Abstract

This invention discloses a method, apparatus, device, and medium for controlling the operation of engineering equipment. The method includes: acquiring the road conditions to be traveled by the engineering equipment; determining the target load of the engineering equipment based on the road conditions; collecting the operating conditions of the engineering equipment while it is performing operations based on the target load; and determining the current operating parameters for controlling the engineering equipment based on the matching result of the operating conditions and reference operating conditions. This invention dynamically determines the target load by combining the road conditions to be traveled, making the load configuration more closely match the path characteristics and avoiding efficiency losses caused by overloading or underloading. By introducing historical operating conditions of other engineering equipment as a reference, the current engineering equipment can reuse other efficient operating experiences. Furthermore, by automatically generating suitable current operating parameters through matching the operating conditions with the reference operating conditions, the invention improves the equipment's adaptability to complex operating scenarios and the level of intelligent control.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for engineering machinery, and in particular to a method, device, equipment, and medium for controlling the operation of engineering equipment. Background Technology

[0002] Engineering equipment, such as loaders, excavators, and mining trucks, is widely used in mining, infrastructure construction, and other fields. It primarily relies on high-powered diesel engines, resulting in high energy consumption, with fuel costs accounting for over 30% of total operating costs. During operation, it emits large amounts of nitrogen oxides (NOx, such as NO2), particulate matter (PM), and carbon dioxide (CO2), significantly impacting the environment and health.

[0003] Existing control technologies are mostly based on traditional mechanical hydraulic systems or simple electronic control units (ECUs), using preset parameters or static characteristic diagrams for management, lacking the ability to adapt to real-time operating conditions and road conditions. While there are after-treatment emission control methods such as EGR and SCR for reducing emissions, they fail to optimize energy utilization at the source and increase system complexity.

[0004] Current control technologies generally suffer from problems such as low energy efficiency, insufficient emission control, and poor adaptability to operating conditions, making it difficult to meet increasingly stringent environmental regulations and the urgent need for efficient and low-carbon equipment. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and medium for controlling the operation of engineering equipment, in order to solve the problems of low energy utilization, high nitrogen oxide emissions, and lack of adaptability to changing working conditions in existing engineering machinery control technologies.

[0006] According to one aspect of the present invention, an operation control method for engineering equipment is provided, comprising: Obtain the road conditions for the engineering equipment to be driven on, and determine the target load of the engineering equipment based on the road conditions. When engineering equipment performs operations based on the target load, the operating conditions of the engineering equipment are collected; Based on the matching results of the operating conditions and the reference operating conditions, the current operating parameters for controlling the engineering equipment are determined; wherein, the reference operating conditions include at least the historical operating conditions of other engineering equipment.

[0007] According to another aspect of the present invention, an operation control device for engineering equipment is provided, comprising: The target load determination module is used to obtain the road conditions to be traveled by the engineering equipment and determine the target load of the engineering equipment based on the road conditions to be traveled. The operating condition acquisition module is used to collect the operating conditions of engineering equipment when the equipment is performing operations based on the target load. The operation control module is used to determine the current operation parameters for controlling the engineering equipment based on the matching results of the operating conditions and reference conditions; wherein, the reference conditions include at least the historical operating conditions of other engineering equipment.

[0008] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory that is communicatively connected to at least one processor; wherein, The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the operation control method of the engineering equipment according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute an operation control method for an engineering device according to any embodiment of the present invention.

[0010] According to another aspect of this application, a computer program product is provided, which includes a computer program that, when executed by a processor, implements the operation control method of the engineering equipment according to any embodiment of this application.

[0011] The technical solution of this invention dynamically determines the target load by combining the road conditions to be traveled, making the load configuration more in line with the path characteristics and avoiding efficiency losses caused by overloading or underloading. By introducing the historical operating conditions of other engineering equipment as a reference, the current engineering equipment can reuse other efficient operating experiences. Furthermore, by matching the operating conditions with the reference conditions, the appropriate current operating parameters are automatically generated, improving the equipment's adaptability to complex operating scenarios and the level of intelligent control, thereby increasing the machine's operating efficiency and reducing energy waste. This solves the technical problems of low operating efficiency, energy waste, and poor operational adaptability of existing engineering machinery during operation due to the disconnect between load setting and actual road conditions and the lack of utilization of historical collaborative experience in control strategies.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of an operation control method for engineering equipment according to an embodiment of the present invention; Figure 2 This is a flowchart of another operation control method for engineering equipment provided according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an operation control device for engineering equipment according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the operation control method for engineering equipment according to an embodiment of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0016] It should be noted that the terms "candidate," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] Figure 1This invention provides a flowchart of an operation control method for engineering equipment. This embodiment is applicable to situations requiring auxiliary control of efficient and energy-saving operation of engineering machinery. The method can be executed by an operation control device for the engineering equipment, which can be implemented in hardware and / or software. This operation control device can be configured in a server or other device with computing and communication capabilities. Figure 1 As shown, the method includes: S110. Obtain the road conditions for the engineering equipment to be driven on, and determine the target load of the engineering equipment based on the road conditions.

[0018] Engineering equipment refers to heavy-duty mobile machinery used in mines, construction sites, ports, and other similar locations, such as mining trucks, loaders, and dump trucks. This type of equipment typically handles material transport or earthmoving tasks, and its operating efficiency and energy consumption are closely related to load capacity and road conditions. The road conditions to be traveled refer to the road environment information of the planned route for the engineering equipment in this task. For example, the road conditions to be traveled include structured data at the road segment level, including: the length of each segment, gradient (uphill / downhill), turning radius, and road surface type. The target load refers to the pre-determined and recommended weight of materials to be loaded for the engineering equipment in this task. This target load is not the equipment's maximum rated load, but rather an optimized load value derived after comprehensively considering information such as the road conditions to be traveled.

[0019] Specifically, before engineering equipment performs transportation or operation tasks, road information of its intended route is obtained. Then, based on this road information and the equipment's power performance, the optimal load weight that can ensure safe and efficient operation while maximizing transportation efficiency is calculated and used as the target load.

[0020] For example, the process of determining the target load in the embodiments of the present invention can be executed by a cloud server, a vehicle-side controller, or a mobile terminal, and is not limited thereto. For example, taking the execution by a cloud server as an example, the vehicle-side controller determines the task to be executed, sends the task to be executed to the mobile terminal, and the mobile terminal forwards it to the cloud server. The cloud server determines the pre-mapped road conditions to be driven based on the task to be executed. The correspondence between the task to be executed and the road conditions to be driven can be pre-uploaded and stored based on the historical task execution information of the engineering equipment.

[0021] The road conditions to be traveled are represented in the form of structured data, specifically including the division of the entire route into multiple continuous road segments. Each segment is associated with road feature information describing its geometric and physical characteristics, such as: the geographic coordinates (e.g., latitude and longitude) of the segment's start and end points, the segment length, the average slope (positive numbers indicate uphill, negative numbers indicate downhill), the absolute value of the slope, the turning radius, and the road surface type (e.g., gravel road, paved road). This road condition data can be sourced from historical task records, high-precision map databases, or shared road condition information uploaded by other engineering equipment within the same work site and aggregated and updated by a cloud server.

[0022] Based on the characteristics of each road segment in the test road conditions, such as slope, length, and curves, and combined with the energy consumption characteristics of the equipment's power system, the total energy consumption required to complete the entire route under different loads is evaluated, and the average energy consumption per ton of effective load is calculated. Based on this, the load that minimizes energy consumption per unit load is selected as the target load. Alternatively, the target load can be determined based on a pre-set energy efficiency optimization model. For example, for each road segment type, the maximum safe driving speed achievable by the engineering equipment under different load conditions is calculated. This speed is limited by the maximum output power of the engine or motor within its efficient operating range, vehicle dynamics constraints such as turning centrifugal force limitations, and safety regulations such as downhill braking capability. Subsequently, combining the length of each road segment and the corresponding speed, the transportation time required to complete the entire journey is estimated. Using transportation efficiency = load capacity / transportation time as the objective function, the optimal load value that maximizes this efficiency is solved. The target load of the engineering equipment is then determined comprehensively based on the optimized load values ​​for each road segment.

[0023] In addition, the target load can be dynamically adjusted by combining the operating status of other engineering equipment in the current operation scenario, such as the density of vehicles traveling in the same direction and interference from cross-operations, and finally form the target load for this operation task, which serves as the basis for loading control and driving strategy formulation.

[0024] S120. When the engineering equipment is performing operations based on the target load, collect the operating conditions of the engineering equipment.

[0025] The engineering equipment loads materials according to the target load and begins to perform transportation or operation tasks, such as traveling from the loading point to the unloading point or carrying out cyclical operations in a designated area. During the operation, the actual working status of the engineering equipment is monitored in real time, for example, by continuously acquiring multi-dimensional data reflecting the current operating status of the engineering equipment through various sensors and on-board communication modules connected to the vehicle-end controller.

[0026] For example, the operating conditions include at least one of the following two types of information: road condition related data and operating condition related data. The road condition related data includes the vehicle's real-time location, driving speed, acceleration, gradient, turning status, and abnormal road surface features. The operating condition related data includes the engine or motor's speed, output power, fuel consumption rate or current and voltage, coolant temperature, hydraulic system pressure, the movement trajectory of the engineering equipment, actual load, gearbox gear, braking status, etc.

[0027] Optionally, the operating condition data of the engineering equipment is uniformly collected, synchronized in time, and preliminarily processed by the vehicle-side controller. This data is used for real-time energy-saving control, such as dynamically adjusting throttle opening, gear position, or operating speed to maintain the power system operating within its high-efficiency range. Simultaneously, it is uploaded to a cloud server via a mobile terminal to update the historical operating condition database, optimize load decisions for subsequent tasks, or enable multi-machine collaborative scheduling. This data collection mechanism not only verifies the actual effectiveness of the target load strategy but also provides a data foundation for continuous learning and adaptive optimization, thus forming a closed-loop intelligent control system of planning, execution, feedback, and iteration.

[0028] S130. Based on the matching results of the operating conditions and the reference operating conditions, determine the current operating parameters for controlling the engineering equipment.

[0029] Operating conditions refer to the comprehensive status information collected in real time by the engineering equipment currently in operation during task execution, including its driving status, power system operating status, load status, and operational action characteristics. Reference conditions refer to prior or collaborative operating condition data stored in a cloud server database that can be used to assist decision-making. For example, reference conditions should at least include the historical operating conditions of other engineering equipment, that is, at least the operating conditions recorded by other similar or identical engineering equipment when performing tasks in the same or similar operational scenarios. This historical data is typically cleaned, structured, and tagged, and stored according to dimensions such as operation type (e.g., ore transportation, earthmoving loading), equipment model, road condition characteristics, and environmental conditions.

[0030] During operation, the vehicle-mounted controller or cloud server matches the current operating conditions of the engineering equipment with reference operating conditions in the database. The matching can be based on multi-dimensional feature similarity judgment, such as identifying whether the current road segment overlaps with a certain historical path through positioning information; calculating the Euclidean distance with historical operating conditions through key parameters such as slope, turning radius, and load range; or using machine learning models to determine the most similar reference operating condition.

[0031] If one or more highly similar reference operating conditions are identified, a successful match is determined, and the historically optimal operating parameters corresponding to the successfully matched reference operating condition are extracted as the current operating parameters. For example, the current operating parameters include, but are not limited to: engine target speed, transmission gear, driving speed setpoint, operating speed of engineering equipment, hydraulic system pressure limit, load distribution strategy, etc. The historically optimal operating parameters are control configurations that have been verified in historical tasks to achieve high efficiency, energy saving, low wear, or low emissions under such operating conditions.

[0032] In one feasible embodiment, the reference operating conditions also include the current operating conditions of other engineering equipment in the same work site.

[0033] Furthermore, the reference operating conditions can be extended to the current operating conditions of other equipment within the same work site, i.e., synchronous operating conditions, to reflect the real-time collaborative environment. That is, in addition to utilizing historically accumulated operating condition data, it also acquires and utilizes in real time the operating status information of other engineering equipment in the same work site as the current engineering equipment, such as the same mining area, construction site, or port storage yard, as an important reference for auxiliary decision-making.

[0034] The current operating condition is dynamic data uploaded in real time to the cloud server by the vehicle-mounted controllers of other engineering equipment via mobile devices, such as wireless communication modules. This data includes, but is not limited to: the real-time location, direction and speed of other equipment, road segment, load status, engineering equipment actions (such as whether it is loading, unloading, or running empty), engine load, and whether there is congestion, shutdown, or abnormal operation. For example, when multiple mining trucks are running on the same transport road, if there are vehicles ahead of a certain vehicle moving at low speed due to queuing for unloading, this information can be identified as part of the current operating condition. For instance, the vehicle-mounted controllers of the engineering equipment can also search and obtain shared road condition or operating condition information stored by other nearby operating equipment via wireless communication modules as a reference operating condition.

[0035] By incorporating real-time collaborative information into the reference working conditions, it is possible not only to predict static road conditions (such as slope and curves) but also to perceive dynamic traffic and operational interference, thereby more accurately predicting the actual feasible speed, waiting time, or working window of the equipment in the future road section.

[0036] This embodiment, by introducing the historical operating experience of other engineering equipment and the current real-time operating experience, not only breaks through the limitations of isolated single-machine control and realizes adaptive optimization control based on swarm intelligence, but also significantly improves the operating efficiency and energy utilization of engineering equipment in complex and ever-changing operating environments. Furthermore, it enhances environmental perception capabilities and collaborative intelligence levels, enabling control decisions to move from single-machine optimality to swarm collaborative optimality, effectively improving overall operating efficiency and the rationality of resource scheduling.

[0037] In one feasible embodiment, S130 includes: Based on the matching results between the operating conditions and the reference conditions, determine the matching conditions in the reference conditions; The target operating parameters are determined based on the reference operating parameters corresponding to the matching operating conditions, and the current operating parameters of the engineering equipment are adjusted according to the target operating parameters.

[0038] When engineering equipment performs its tasks, its vehicle-mounted controller collects real-time operating data, including the equipment's position, speed, gradient, turning status, engine / motor operating point, actual load, equipment trajectory, and hydraulic system pressure. Simultaneously, the cloud server stores a large amount of structured reference operating data, which includes at least one of the following: first, operating data recorded by other similar engineering equipment during historical task execution in the same or similar work scenarios; and second, real-time operating data currently being uploaded by other engineering equipment within the same work area.

[0039] The current operating conditions of the engineering equipment are matched with reference operating conditions. The matching process can be based on geolocation, such as determining whether they are on the same road segment, or calculating the similarity of key features such as slope, curve radius, load range, equipment type, and operation mode. For example, multi-point positioning information can be used to determine whether the current path falls within the geofence of a known path, or feature vector comparison (such as using cosine similarity or clustering algorithms) can be used to filter out the closest historical or real-time operating condition samples. After a successful match, one or more matching operating conditions are selected, that is, matching operating condition instances whose similarity to the current operating conditions of the engineering equipment is greater than a preset similarity threshold.

[0040] Each matching working condition is associated with corresponding reference operating parameters in the database. The reference operating parameters are the control parameters of the engineering equipment when the matching working condition occurs. For example, the engine target speed, gearbox gear, driving speed, operating speed of the engineering equipment, hydraulic pump output flow, load, etc., when the engineering equipment is working under the matching working condition are stored as reference operating parameters on the cloud server.

[0041] After obtaining one or more matching operating conditions and their reference operating parameters, the target operating parameters are further determined. Specific methods include one or more of the following strategies: If there is only one matching operating condition, its reference operating parameters are directly used as the target operating parameters; if there are multiple matching operating conditions, their reference operating parameters are weighted and fused, with the weights dynamically calculated based on factors such as matching similarity, time freshness, or equipment model consistency; based on the fusion, the parameters can also be fine-tuned by considering the individual characteristics of the current equipment (such as aging level, maintenance status) or environmental constraints (such as current oil temperature, battery SOC) to ensure applicability and safety.

[0042] The final target operating parameters are the optimized control commands recommended for the current operation of the engineering equipment. Based on these commands, the vehicle-mounted controller automatically adjusts the current operating parameters of the engineering equipment, such as adjusting the throttle opening to maintain the target speed, switching gearboxes, limiting the lifting speed to reduce energy consumption, or prompting the operator to adopt a new operating rhythm.

[0043] This embodiment achieves a closed-loop control upgrade from experience-driven to data-driven combined with collaborative intelligence through a matching mechanism, significantly improving energy utilization efficiency, operational safety, and overall scheduling coordination.

[0044] The technical solution of this embodiment dynamically determines the target load by combining the road conditions to be traveled, making the load configuration more in line with the path characteristics and avoiding efficiency losses caused by overloading or underloading. By introducing the historical operating conditions of other engineering equipment as a reference, the current engineering equipment can reuse other efficient operating experiences. Furthermore, by matching the operating conditions with the reference conditions, the appropriate current operating parameters are automatically generated, which improves the equipment's adaptability to complex operating scenarios and the level of intelligent control, thereby increasing the machine's operating efficiency and reducing energy waste. This solves the technical problems of low operating efficiency, energy waste, and poor operational adaptability of existing engineering machinery during operation due to the disconnect between load setting and actual road conditions and the lack of utilization of historical collaborative experience in control strategies.

[0045] Figure 2 This is a flowchart of another operation control method for engineering equipment provided by an embodiment of the present invention. This embodiment further refines the process of determining the target load of the engineering equipment in the above embodiments. Figure 2 As shown, the method includes: S210. Obtain the road feature information corresponding to each segment of the path to be traveled by the engineering equipment.

[0046] The planned route for the engineering equipment to travel in the upcoming task typically consists of a starting point (e.g., loading point), intermediate points, and an ending point (e.g., unloading point). To achieve refined energy efficiency optimization and intelligent control, the route is not treated as a whole but is divided into multiple continuous and non-overlapping segments. These segments can be automatically divided based on preset rules, abrupt changes in road geometry (e.g., slope changes, curve start and end points), or by combining topological nodes in a high-precision map.

[0047] For each segment after segmentation, its corresponding road feature information is obtained from the cloud server. This road feature information is a set of structured parameters used to describe the physical and geometric attributes of the segment, including but not limited to the following: segment location information: such as the geographical coordinates of the starting and ending points, such as latitude and longitude or coordinates in a local coordinate system; longitudinal slope characteristics: including average slope, maximum slope, slope length and slope aspect, used to assess climbing resistance or braking requirements; lateral alignment characteristics: such as turning radius, curvature, and curve length, used to determine the stability and speed limit when vehicles pass through; road surface attributes: such as road surface type, such as hardened road surface, gravel road, mud road, etc., adhesion coefficient or roughness, which affect rolling resistance and traction performance; special area markings: such as speed limit zones, intersections, loading and unloading areas, blind spots, etc., which may impose additional safety or operational constraints.

[0048] Among them, road feature information can come from multiple channels: (1) high-precision work site map data pre-stored in the cloud server database, which is generated by the aggregation of measured road conditions uploaded by multiple devices in historical tasks and is continuously updated; (2) information imported from external high-precision map services or engineering digitization platforms; (3) real-time perception systems on the vehicle, such as LiDAR, cameras, IMU and other sensor devices, identify and upload road features in the early exploration or current driving.

[0049] S220. Determine the speed limit for each road segment based on the road characteristic information of each segment.

[0050] The speed limit for a road section refers to the maximum safe speed at which engineering equipment is allowed to travel within a specific road section. This limit is not a speed limit in the sense of fixed traffic regulations, but a technical constraint value that is dynamically determined after comprehensively considering the physical characteristics of the road, the dynamic performance of the equipment, operational safety, and energy efficiency targets.

[0051] For example, based on a pre-trained prediction model, the calculated speed limit for each road segment can be predicted to ensure safe and efficient operation.

[0052] Further speed limits for road sections can be dynamically adjusted based on real-time environmental factors, such as lowering the limit in rainy or snowy weather, or temporarily reducing the speed when abnormal features such as potholes or bumps are detected on the road surface.

[0053] In one feasible embodiment, S220 includes: If the road segment is a horizontal straight road segment, the speed limit for the horizontal straight road segment shall be determined based on the maximum power output of the engineering equipment within the preset high-efficiency working range and the transmission efficiency of the engineering equipment. If the road section is uphill, the speed limit for the uphill section shall be determined based on the maximum power, transmission efficiency and the gradient of the uphill section. If the road section is a downhill section, the speed limit for the downhill section shall be determined according to the slope of the downhill section. If the road segment is a turning segment, the speed limit for the turning segment is determined based on the turning radius of the turning segment.

[0054] After obtaining road feature information for each segment of the route to be traveled, such as slope, turning radius, road surface type, and segment length, the speed limit for each segment is calculated for different types of segments.

[0055] If the road segment is a horizontal straight road segment, its speed limit is mainly constrained by the power system capacity and economy of the equipment. Based on the maximum output power that the engine or motor can provide in the high-efficiency operating range, combined with the total vehicle weight, rolling resistance coefficient and transmission efficiency, the highest feasible speed under the premise of ensuring that the power system operates in the high-efficiency range is calculated, and this speed limit is used as the speed limit of the road segment.

[0056] If the road section is uphill, the speed limit is determined by the power balance. The steeper the slope and the higher the load, the greater the required traction force and the lower the maintainable speed. Based on the slope, total vehicle mass, and powertrain output characteristics, the maximum climbing speed without causing engine stall or overload is calculated and used as the limit.

[0057] If the road segment is downhill, the speed limit is primarily based on braking safety. A safe downhill speed is set based on the gradient, length, and road surface adhesion conditions to ensure effective braking and prevent brake fade. If the downhill segment ends immediately after a turn, and the slope length is less than a preset threshold (which increases with the safe downhill speed), the downhill speed limit is further coordinated with the safe speed of the subsequent turn. This could be done by averaging the two or using a stricter limit to ensure driving stability on the continuous road segment.

[0058] If the road segment is a curve, the speed limit is mainly determined by the turning radius and the road surface friction coefficient. Based on the vehicle's center of gravity height, wheelbase, and lateral stability model, the maximum safe speed to pass through without skidding or overturning is calculated and used as the speed limit for that curve.

[0059] For example, the maximum unloaded vehicle speed corresponding to the engine or motor operating in the high-efficiency zone is used as the road segment speed limit. The formula for determining the road segment speed limit for a horizontal straight road segment is as follows: Where P represents the maximum output power (kW) of the engine or motor when it is operating in the high-efficiency range. This indicates the transmission efficiency (generally 0.8~0.85 for trucks / construction vehicles). This indicates the speed limit for a road segment. The formula for determining the speed limit for an uphill road segment is: ,in, G represents the gradient, and G represents the load. Downhill sections use pre-defined safe driving speeds for different gradients as the speed limit for that section; that is, a mapping relationship is pre-established between different candidate gradient ranges and their corresponding speed limits. Curving sections use pre-defined safe driving speeds for different turning radii as the speed limit for that section; that is, a mapping relationship is pre-established between different candidate turning radii and their corresponding speed limits.

[0060] Furthermore, if a downhill section is immediately followed by a curve, and the slope length is less than a set value, then the average of the set safe downhill driving speed and the safe turning speed is used as the speed limit for the downhill section. The set slope length increases as the set safe downhill speed value increases.

[0061] This embodiment realizes the transformation from static, uniform speed limits to dynamic, differentiated speed limit generation based on refined road characteristics, which not only ensures operational safety but also provides basic support for efficient energy utilization.

[0062] S230. Determine the reference load of the road segment based on the speed limit and road characteristic information of the road segment.

[0063] The reference load for a road segment refers to the recommended load capacity that allows engineering equipment to operate safely and efficiently under specific road segment conditions. This load capacity is not the rated maximum load capacity of the equipment, but rather an optimized load value derived by back-calculating through an energy efficiency or dynamic performance model after comprehensively considering the speed limit and road characteristic information of that road segment. It is used to guide the target load decision for the entire route.

[0064] Specifically, based on the known speed limits and road characteristics of a given road segment, a load-speed-power feasibility relationship is established. Since the traction power required by engineering equipment under a specific total mass (weight + load) is determined by road resistance, for example, on an uphill section, the required power increases linearly with load and gradient; on a curve, excessive load exacerbates lateral instability and limits feasible speed. Therefore, for a given speed limit, there exists a maximum permissible load limit. Exceeding this limit will result in: inability to maintain the speed limit, increased safety risks, or forcing the power system out of its efficient operating range (e.g., engine overload).

[0065] For example, on a straight, level road section, given the speed limit, the maximum total mass that the engine / motor can support within its efficient operating range is calculated by combining the rolling resistance coefficient and transmission efficiency. This yields the effective load (minus the equipment's own weight) as the reference load for that section. On an uphill section, the maximum total mass satisfying the power constraint is calculated using the gradient, speed limit, and maximum output power, based on the vehicle dynamics equilibrium equations. This determines the reference load for the section. Steeper gradients and lower speed limits generally correspond to smaller reference loads. On a downhill section, although the power demand is lower, the thermal load and stability of the braking system must be considered. The system sets a safe upper load limit based on the gradient and speed limit, combined with the braking capacity model, to prevent brake failure due to heavy loads. This upper limit is the reference load for the section. On a curved section, the maximum permissible total mass without skidding or overturning is calculated based on the turning radius and speed limit, according to lateral stability conditions (e.g., centrifugal force ≤ adhesion × safety factor), thus determining the reference load. The sharper the turn (the smaller the radius), the higher the speed limit, and the lower the reference load of the road section.

[0066] After the above analysis, a reference load for each road segment is generated that matches its road conditions. This value represents the optimal or maximum feasible load when the road segment is running independently.

[0067] Optionally, obtain road condition information, determine the initial load based on the road condition information of each road segment, including uphill, downhill, and curves; calculate the speed limit for each road segment based on the initial load; calculate the estimated transportation time for the entire transportation segment based on the speed limit for each road segment under the initial load; calculate the first estimated transportation efficiency based on the initial load and the corresponding estimated transportation time; transportation efficiency is determined by the ratio of load to transportation time. When the load decreases, the theoretical transportation speed increases, thus shortening the transportation time. Optimize the initial load with the goal of maximizing transportation efficiency, and determine the target load based on the optimization result; further, after determining the optimized load, adjust the optimized load according to the status of other engineering equipment in the work site to obtain the final target load.

[0068] For example, the following calculation relationship can be used to optimize the load capacity to maximize transportation efficiency: the greater the load capacity, the higher the approximate maximum vehicle speed. ,in, Maximum speed when unloaded. : Load attenuation coefficient, , Load capacity (tons) Vehicle drag coefficient (measured and calibrated, typically 0.05~0.15 / ton); one-way transport time. Where S represents the one-way transport distance. Loading and unloading time; transportation efficiency The target load is: .

[0069] In one feasible embodiment, S230 includes: Obtain the current travel segment and corresponding current speed of other engineering equipment in the same work site, and adjust the speed limit of the road segment according to the current travel segment and corresponding current speed to obtain the predicted speed of the engineering equipment in each road segment; The reference load for a road segment is determined based on the predicted vehicle speed and road characteristic information.

[0070] To improve the real-time performance and accuracy of speed prediction and load determination, this embodiment not only relies on static road features and theoretical dynamic models, but also introduces group collaborative perception information in the work site to dynamically correct the original road segment speed limit, thereby generating a predicted road segment speed that is closer to the actual operating environment, and determining the reference load of the road segment accordingly.

[0071] Specifically, real-time operational data of other engineering equipment within the same work site is acquired via cloud servers or vehicle-mounted communication modules. This data includes: the current travel route, such as the specific road segment markers or location coordinates of other equipment, which can be obtained through GNSS positioning and high-precision map matching; and the corresponding current road speed, i.e., the actual travel speed of the other engineering equipment on the current road segment, collected and uploaded by vehicle-mounted sensors. This data reflects the real traffic conditions at the work site, such as an uphill section where the actual speed is far below the theoretical speed limit due to queuing vehicles ahead, or a turning area where frequent deceleration is caused by overlapping operations.

[0072] Speed ​​limits are dynamically adjusted based on the operational data of group equipment to generate predicted road segment speeds. For example, the current travel segment of the aforementioned collaborative vehicles is compared with the planned travel path of the engineering equipment. If overlapping or adjacent road segments are found, the actual traffic capacity of that road segment is considered to be affected by the current operating environment. Based on this, the theoretical road segment speed limits calculated based on road features are dynamically adjusted. If the actual speeds of multiple other engineering equipment on a certain road segment are significantly lower than the original limits, it is determined that the road segment has congestion, temporary obstacles, or collaborative scheduling constraints. The average speed of the current road segment corresponding to the current travel segment of other engineering equipment matching that road segment is directly used as the predicted road segment speed; or, the original limits and measured speeds are weighted and fused. This makes the predicted road segment speed a more realistic and feasible speed estimate that integrates road physical constraints and real-time operational dynamics, used to replace idealized limits in subsequent load planning.

[0073] After obtaining the predicted vehicle speed for each road segment, the maximum feasible load that the equipment can safely and efficiently operate at that predicted speed is derived by combining the road characteristic information of that road segment. This is the road segment reference load. For example, in the embodiment described above that determines the road segment reference load based on the road segment speed limit and road characteristic information, the road segment speed limit is replaced with the predicted road segment speed to obtain the updated road segment reference load.

[0074] This embodiment achieves a leap from single-machine static planning to multi-machine collaborative dynamic prediction by introducing the real-time driving status of other equipment in the same work site. The predicted road speed more accurately reflects the on-site traffic capacity, effectively avoiding the problem of excessive or insufficient load caused by ignoring on-site dynamic interference, and significantly improving the overall work efficiency and energy utilization level.

[0075] S240. Determine the target load based on the reference load and road characteristic information of each road segment.

[0076] The determination of the target load requires comprehensive consideration of the traffic capacity and energy efficiency constraints of all road segments along the entire route. Based on the road segment reference load calculated independently for each road segment and the corresponding road characteristic information, the load is obtained through fusion and optimization strategies to ensure that the equipment can travel safely throughout the entire journey and achieve the global optimal transportation efficiency or energy consumption performance.

[0077] Specifically, a reference load has first been calculated for each segment of the route to be traveled. This reference load represents the maximum recommended load that the equipment can safely and efficiently operate under specific road characteristics (such as gradient, turning radius, and length) and predicted vehicle speed conditions for that segment. Based on this, and combining road characteristic information for each segment (such as segment length, type weight, and degree of impact on the overall task), one or more of the following strategies are used to determine the final target load according to scenario and task characteristics.

[0078] For example, the minimum reference load among all road segments can be taken as the target load. This strategy ensures that the equipment will not suffer from insufficient power, brake failure, or stability risks due to overloading on any road segment, making it suitable for scenarios with extremely high safety requirements and significant bottleneck sections (such as long steep slopes) in the route. Alternatively, an optimization model can be constructed with the objective function of transport efficiency = load capacity / total transport time. The total transport time is obtained by dividing the length of each road segment by its feasible speed under different loads (constrained by the reference load of each road segment). Under the premise that the actual load of any road segment is less than or equal to the reference load of that segment, the load value that maximizes transport efficiency is searched as the target load. This strategy is suitable for tasks sensitive to operational timeliness. Alternatively, if the task prioritizes energy saving over speed, the system can estimate the total energy consumption under different total loads based on the road characteristics and reference loads of each road segment, and select the load that minimizes energy consumption per unit effective load as the target load.

[0079] In one feasible embodiment, S240 includes: The influence weight of each road segment is determined based on the road characteristic information of each road segment; The target load is determined by the weighted result of the reference load and influence weight of each road segment.

[0080] Since different road sections have different impacts on overall operational performance, they should be assigned corresponding impact weights based on their road characteristic information, and the reference load of each road section should be weighted accordingly to obtain the target load for global optimization.

[0081] After acquiring road feature information (including but not limited to slope, turning radius, segment length, road surface type, and whether it is an intersection) for each segment of the route to be traveled, an influence weight is assigned to each segment according to a preset weighting rule or mapping model. This influence weight reflects the strength or importance of the segment's constraint on the overall load decision for the entire trip. For example, the influence weight is assigned based on the segment type: for uphill segments, the steeper the slope, the higher the influence weight; for turning segments, the smaller the turning radius, the higher the weight; for horizontal straight segments, the influence weight is lower than that of other types of segments; for downhill segments, if the slope is steep or there are consecutive curves, the corresponding influence weight is increased.

[0082] Furthermore, the influence weights are normalized based on the road segment length. For example, since a longer road segment of the same type has a greater impact on the total journey, a basic influence weight is determined according to the road segment type. This basic influence weight is then multiplied by the proportion of the road segment's length to the total journey length, or adjusted using an exponential decay / enhancement function, to obtain the final influence weight for each road segment. This ensures that long bottleneck road segments receive greater influence.

[0083] The target load is calculated by weighting the reference load of each road segment and its influence weight. The final target load fully respects the strong constraints of critical road segments while making reasonable use of the carrying potential of non-critical road segments, achieving coordinated optimization of safety, efficiency, and economy.

[0084] This embodiment realizes intelligent load decision based on path structure perception, which is especially suitable for operation scenarios with complex road conditions and significant path differences, such as mines and large construction sites. It can significantly improve the effective load rate of a single transport, reduce the energy consumption of transporting materials per unit, and ensure safe and reliable operation throughout the process.

[0085] S250. When engineering equipment is performing operations based on the target load, collect the operating conditions of the engineering equipment.

[0086] S260. Based on the matching results of the operating conditions and the reference operating conditions, determine the current operating parameters for controlling the engineering equipment.

[0087] The technical solution of this embodiment upgrades the load decision from fixed load to road condition adaptive load, so that the determination of the target load not only respects the physical and safety constraints of each road section, but also takes into account the power performance of the equipment. This significantly improves the intelligence level and resource utilization efficiency of engineering equipment in complex and dynamic operating environments, and effectively avoids problems such as insufficient power, excessive energy consumption or safety hazards caused by improper load.

[0088] This invention also provides an operation control system for engineering equipment. By controlling the machine based on road or work condition data, the system improves machine operating efficiency and reduces energy waste.

[0089] The operation control system includes a mobile terminal, a vehicle-mounted controller, and a cloud server. The mobile terminal is electrically connected to the vehicle-mounted controller and is used for vehicle positioning, as well as uploading and downloading road condition or operating condition data. The vehicle-mounted controller is used to collect road condition or operating condition and energy consumption data from sensors, analyze the collected road condition or operating condition data, and upload the collected road condition or operating condition data to the cloud server via the mobile data terminal. The cloud server is used to analyze the collected road condition or operating condition data and energy consumption data, match corresponding road condition or operating condition data from the database on the cloud server based on the positioning information of the equipment, and push the matched road condition or operating condition information to the mobile terminal or vehicle-mounted controller for energy-saving control of the operation or movement of the engineering equipment.

[0090] The vehicle-mounted controller collects road condition information, names the road conditions, and uploads them to the cloud server. When a change in the road condition of a certain road segment is detected, the corresponding road condition information for that segment is uploaded to the cloud server for updating. Furthermore, the road condition information update process is as follows: the road condition data stored in the cloud server contains information on several road segments with different characteristics, and these segments are recorded with consecutive numbers. When a change occurs in a road condition segment collected by the vehicle-mounted controller, the information uploaded to the cloud server includes the road condition name, the location information of the corresponding road segment, and the road condition characteristic information. After receiving the updated road condition data, the cloud server matches it with the relevant information. The corresponding road condition names and road segments are updated; the vehicle-side data processing is performed before uploading the collected road condition information to the cloud server. The road condition information includes, but is not limited to, location information and gradient. The data processing includes dividing the entire route into multiple road segments, each of which can be described by specific information, such as the location of the start and end points of the road segment, the gradient of the road segment, the length of the road segment, and the turning radius of the road segment; the vehicle-side controller uploads the collected road condition data to the cloud server, and the cloud server analyzes the road condition data to identify horizontal road segments, sloping road segments, and turning road segments, and records the relevant information of each road segment.

[0091] The vehicle-mounted controller uploads the collected driving and operation data to the cloud server. The cloud server analyzes the historical driving and operation data to derive the best historical driving and operation parameters as reference parameters, and compares and updates the best driving and operation parameters for the corresponding working conditions stored in the cloud server.

[0092] Optionally, before matching road conditions or working conditions, the equipment category is identified first. The equipment category is identified by the identification code uploaded by the vehicle-side controller. The equipment category includes transportation machinery and operating machinery. More specifically, the specific product is identified, and road condition identification or working condition identification and matching are performed according to different products.

[0093] Optionally, based on the motion trajectory and load information of the engineering equipment uploaded by the vehicle-mounted controller, the cloud server performs existing working condition matching in the database. After successful matching, the cloud server sends a list of selectable working conditions to the vehicle-mounted controller for the user to choose from and download. Optionally, the vehicle-mounted controller can select the required road condition information through the instrument panel.

[0094] Optionally, based on the multi-point positioning information uploaded by the vehicle-mounted controller, the cloud server performs existing road condition matching in the database. After successful matching, the cloud server sends a list of selectable road condition downloads to the vehicle-mounted controller for the user to choose from and download. Optionally, the vehicle-mounted controller can select the required road condition information through the instrument panel.

[0095] Furthermore, the road condition or work condition data stored in the cloud server's database contains location information. Based on the multi-point location information uploaded by the vehicle controller, the database is queried to see if there is road condition or work condition data that makes all the multi-point location information of the vehicle controller fall within the location range of the road condition or work condition data. If so, the match is successful.

[0096] Optionally, the vehicle-mounted terminal can also search for and obtain road condition information or working condition information stored and shared by other nearby operating equipment through a wireless communication module.

[0097] The energy-saving control at the equipment end matches the machine's driving speed, gearbox gear, and load based on road condition information, so that each component of the machine operates in the high-efficiency range, enabling the engineering equipment to operate in an energy-saving manner; it also matches the machine's working weight, operating speed, and other parameters based on working condition data, so that the engineering equipment operates efficiently.

[0098] Furthermore, the cloud server stores efficient driving or efficient operation parameters under different road conditions or working conditions, and the optional efficient driving or efficient operation parameters are obtained through experiments.

[0099] The system collects new road or work condition data from the device and uploads it to the cloud server. It also updates the existing road or work condition data based on the differences between the collected data and the new data. Simultaneously, it can match the corresponding road or work condition data from the cloud server's database based on the device's location information and push the matched data to the device. The device then matches the appropriate driving or operating parameters based on the road or work condition data, enabling the engineering equipment to operate efficiently. This significantly improves the equipment's operational efficiency and reduces energy waste.

[0100] Figure 3 This is a schematic diagram of the structure of an operation control device for engineering equipment provided in an embodiment of the present invention. Figure 3 As shown, the device includes: The target load determination module 310 is used to acquire the road conditions to be traveled by the engineering equipment and determine the target load of the engineering equipment based on the road conditions to be traveled. The operating condition acquisition module 320 is used to acquire the operating condition of the engineering equipment when the engineering equipment performs operations based on the target load; The operation control module 330 is used to determine the current operation parameters for controlling the engineering equipment based on the matching result of the operating conditions and the reference operating conditions; wherein the reference operating conditions include at least the historical operating conditions of other engineering equipment.

[0101] The technical solution of this embodiment dynamically determines the target load by combining the road conditions to be traveled, making the load configuration more in line with the path characteristics and avoiding efficiency losses caused by overloading or underloading. By introducing the historical operating conditions of other engineering equipment as a reference, the current engineering equipment can reuse other efficient operating experiences. Furthermore, by matching the operating conditions with the reference conditions, the appropriate current operating parameters are automatically generated, which improves the equipment's adaptability to complex operating scenarios and the level of intelligent control, thereby increasing the machine's operating efficiency and reducing energy waste. This solves the technical problems of low operating efficiency, energy waste, and poor operational adaptability of existing engineering machinery during operation due to the disconnect between load setting and actual road conditions and the lack of utilization of historical collaborative experience in control strategies.

[0102] Optionally, the road conditions to be traveled include road feature information corresponding to each road segment of the travel path to be divided; The target load determination module 310 includes: A road segment speed limit determination unit is used to determine the road segment speed limit based on the road characteristic information of each road segment. The road segment reference load determination unit is used to determine the road segment reference load based on the road segment speed limit and the road characteristic information; The target load determination unit is used to determine the target load based on the road segment reference load and the road characteristic information of each road segment.

[0103] Optional, the road segment speed limit determination unit is specifically used for: If the road segment is a horizontal straight road segment, the speed limit of the horizontal straight road segment is determined based on the maximum power output of the engineering equipment within the preset high-efficiency working range and the transmission efficiency of the engineering equipment. If the road segment is an uphill segment, the speed limit for the uphill segment is determined based on the maximum power, the transmission efficiency, and the slope of the uphill segment. If the road section is a downhill section, the speed limit for the downhill section shall be determined according to the slope of the downhill section. If the road segment is a turning segment, the speed limit for the turning segment is determined based on the turning radius of the turning segment.

[0104] Optionally, the road segment reference load determination unit is specifically used for: The current travel segment and corresponding current speed of other engineering equipment in the same work site are obtained, and the speed limit of the road segment is adjusted according to the current travel segment and corresponding current speed to obtain the predicted road segment speed of the engineering equipment in each road segment. The reference load of the road segment is determined based on the predicted vehicle speed and the road characteristic information.

[0105] Optional, target load determination unit, specifically used for: The influence weight of each road segment is determined based on the road characteristic information of each road segment; The target load is determined by the weighted sum of the reference load of each road segment and the influence weight.

[0106] Optional, the job control module 330 is specifically used for: Based on the matching result between the operating conditions and the reference conditions, the matching conditions in the reference conditions are determined. The target operating parameters are determined based on the reference operating parameters corresponding to the matching operating conditions, and the current operating parameters of the engineering equipment are adjusted based on the target operating parameters.

[0107] Optionally, the reference operating conditions may also include the current operating conditions of other engineering equipment in the same work site.

[0108] The operation control device for engineering equipment provided in the embodiments of the present invention can execute the operation control method for engineering equipment provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0109] The acquisition, storage, use, and processing of data in this application comply with relevant national laws and regulations and do not violate public order and good morals.

[0110] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0111] Figure 4 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0112] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0113] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0114] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods described above, such as the operation control methods for engineering equipment.

[0115] In some embodiments, the operation control method for the engineering equipment may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the operation control method for the engineering equipment described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the operation control method for the engineering equipment by any other suitable means (e.g., by means of firmware).

[0116] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific reference products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0118] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0119] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0120] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data servers), or computing systems that include switching components (e.g., application servers), or computing systems that include front-end components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such back-end, switching, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0121] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0122] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0123] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the operation control method for engineering equipment as provided in any embodiment of this application.

[0124] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0125] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0126] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for controlling the operation of engineering equipment, characterized in that, The method includes: Obtain the road conditions for the engineering equipment to be driven on, and determine the target load of the engineering equipment based on the road conditions. When the engineering equipment performs operations based on the target load, the operating conditions of the engineering equipment are collected; Based on the matching results of the operating conditions and the reference operating conditions, the current operating parameters for controlling the engineering equipment are determined; wherein, the reference operating conditions include at least the historical operating conditions of other engineering equipment.

2. The method according to claim 1, characterized in that, in, The road conditions to be traveled include road feature information corresponding to each segment of the route to be traveled. Determining the target load of the engineering equipment based on the road conditions to be traveled includes: The speed limit for each road segment is determined based on the road characteristic information of each road segment; The reference load of the road segment is determined based on the speed limit of the road segment and the road characteristic information; The target load is determined based on the reference load of each road segment and the road characteristic information.

3. The method according to claim 2, characterized in that, The step of determining the speed limit for each road segment based on the road characteristic information of each road segment includes: If the road segment is a horizontal straight road segment, the speed limit of the horizontal straight road segment is determined based on the maximum power output of the engineering equipment within the preset high-efficiency working range and the transmission efficiency of the engineering equipment. If the road segment is an uphill segment, the speed limit for the uphill segment is determined based on the maximum power, the transmission efficiency, and the slope of the uphill segment. If the road section is a downhill section, the speed limit for the downhill section shall be determined according to the slope of the downhill section. If the road segment is a turning segment, the speed limit for the turning segment is determined based on the turning radius of the turning segment.

4. The method according to claim 2, characterized in that, The step of determining the reference load of the road segment based on the speed limit of the road segment and the road characteristic information includes: The current travel segment and corresponding current speed of other engineering equipment in the same work site are obtained, and the speed limit of the road segment is adjusted according to the current travel segment and corresponding current speed to obtain the predicted road segment speed of the engineering equipment in each road segment. The reference load of the road segment is determined based on the predicted vehicle speed and the road characteristic information.

5. The method according to claim 2, characterized in that, The step of determining the target load based on the road segment reference load and the road characteristic information includes: The influence weight of each road segment is determined based on the road characteristic information of each road segment; The target load is determined by the weighted sum of the reference load of each road segment and the influence weight.

6. The method according to claim 1, characterized in that, The step of determining the current operating parameters for controlling the engineering equipment based on the matching result of the operating conditions and the reference operating conditions includes: Based on the matching result between the operating conditions and the reference conditions, the matching conditions in the reference conditions are determined. The target operating parameters are determined based on the reference operating parameters corresponding to the matching operating conditions, and the current operating parameters of the engineering equipment are adjusted based on the target operating parameters.

7. The method according to claim 1 or 6, characterized in that, in, The reference operating conditions also include the current operating conditions of other engineering equipment in the same work site.

8. An operation control device for engineering equipment, characterized in that, The device includes: The target load determination module is used to acquire the road conditions to be traveled by the engineering equipment and determine the target load of the engineering equipment based on the road conditions to be traveled. The operating condition acquisition module is used to acquire the operating condition of the engineering equipment when the engineering equipment performs operations based on the target load; The operation control module is used to determine the current operation parameters for controlling the engineering equipment based on the matching result of the operating conditions and the reference operating conditions; wherein the reference operating conditions include at least the historical operating conditions of other engineering equipment.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the operation control method for the engineering equipment according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the operation control method for the engineering equipment as described in any one of claims 1-7.

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