Optimization method, system, electronic device, medium and program product for excavator

Abstract

This disclosure provides an optimization method, system, electronic device, medium, and program product for an excavator, relating to the field of excavator technology. The optimization method includes: acquiring excavator operation data; dividing each work cycle of the excavator into multiple work stages based on the operation data; evaluating the operation performance of the excavator in each work stage based on the operation data of each work stage; and optimizing at least one of the excavator's components and operating level based on the evaluation results of each work stage.

Description

Technical Field

[0001] This disclosure relates to the field of excavator technology, and more particularly to an optimization method, system, electronic device, medium, and program product for an excavator. Background Technology

[0002] The relevant technologies evaluate the entire operation process of excavators, but lack guidance on optimization methods. Summary of the Invention

[0003] One technical problem this disclosure aims to solve is to provide an optimization method, system, electronic device, medium, and program product for excavators that can improve the accuracy of excavator optimization.

[0004] According to one aspect of this disclosure, an optimization method for an excavator is proposed, comprising: acquiring excavator operation data; dividing each work cycle of the excavator into multiple work stages based on the operation data; evaluating the operation performance of the excavator in each work stage based on the operation data of each work stage; and optimizing at least one of the excavator's components and operating level based on the evaluation results of each work stage.

[0005] In some embodiments, dividing each work cycle of the excavator into multiple work stages based on work data includes: dividing each work cycle of the excavator into a digging stage, a lifting and slewing stage, an unloading stage, and an empty bucket return stage based on work data.

[0006] In some embodiments, dividing each work cycle of the excavator into a digging phase, a lifting and slewing phase, an unloading phase, and an empty bucket return phase based on the work data includes at least one of the following: distinguishing between the digging phase and the lifting and slewing phase based on bucket angle data in the work data; distinguishing between the lifting and slewing phase, the unloading phase, and the empty bucket return phase based on bucket trajectory data in the work data; and distinguishing between the empty bucket return phase and the digging phase based on bucket force data in the work data.

[0007] In some embodiments, distinguishing between the digging stage and the hoisting and slewing stage based on bucket angle data in the operation data includes: distinguishing between the digging stage and the hoisting and slewing stage based on bucket angle thresholds and bucket angle change trends.

[0008] In some embodiments, distinguishing between the lifting and slewing stage, the unloading stage, and the empty bucket return stage based on the bucket trajectory data in the operation data includes: dividing the bucket trajectory data into an upward trajectory, a horizontal trajectory, and a downward trajectory in sequence, wherein the upward trajectory corresponds to the lifting and slewing stage, the horizontal trajectory corresponds to the unloading stage, and the downward trajectory corresponds to the empty bucket return stage.

[0009] In some embodiments, distinguishing between the empty bucket return phase and the digging phase based on bucket force data in the operation data includes: distinguishing between the empty bucket return phase and the digging phase based on bucket force threshold and bucket force change trend.

[0010] In some embodiments, evaluating the excavator's operational performance at each operational stage based on operational data for each operational stage includes at least one of the following: determining the excavator's energy consumption evaluation result based on energy consumption data in the operational data; determining the excavator's efficiency evaluation result based on at least one of output data, efficiency data, and operational level data in the operational data; and determining the excavator's corresponding soil condition evaluation result based on soil condition data.

[0011] In some embodiments, optimizing at least one of the components and operating level of the excavator based on the evaluation results of each working stage includes optimizing at least one of the engine, hydraulic pump, hydraulic system, mechanism system and operating level of the excavator based on the evaluation results of each working stage.

[0012] In some embodiments, optimizing the operational level includes at least one of the following: optimizing the action connection process of multiple work stages; optimizing the consistency between the bucket digging angle and the digging trajectory angle.

[0013] In some embodiments, optimizing the mechanism system includes at least one of the following: optimizing the mechanism hinge points of the excavator; optimizing the bucket shape of the excavator.

[0014] In some embodiments, optimizing the engine includes optimizing the engine's operating distribution points based on a universal characteristic diagram.

[0015] In some embodiments, optimizing the hydraulic pump includes optimizing the operating distribution points of the hydraulic pump based on a pump efficiency diagram.

[0016] In some embodiments, optimizing the hydraulic system includes optimizing at least one of the valve opening characteristics and piping connection specifications of the hydraulic system.

[0017] In some embodiments, optimizing at least one of the components and operating level of the excavator based on the evaluation results of each working stage includes: determining the working mode of the excavator; determining the key evaluation index results in the evaluation results based on the working mode; and optimizing at least one of the components and operating level of the excavator based on the key evaluation index results.

[0018] In some embodiments, optimizing at least one of the components and operating level of the excavator based on the evaluation results of each work stage includes: determining the work stage that needs optimization based on the evaluation results of each work stage; and optimizing at least one of the components and operating level of the excavator for the work stage that needs optimization.

[0019] In some embodiments, job data includes collected data, derived calculation data, and calculation result data.

[0020] According to another aspect of this disclosure, an optimization system for an excavator is also proposed, comprising: a data acquisition module configured to acquire excavator operation data; a stage division module configured to divide each work cycle of the excavator into multiple work stages based on the operation data; an evaluation module configured to evaluate the operation performance of the excavator in each work stage based on the operation data of each work stage; and an optimization module configured to optimize at least one of the excavator's components and operating level based on the evaluation results of each work stage.

[0021] According to another aspect of this disclosure, an electronic device is also proposed, comprising: a processor; and a memory coupled to the processor for storing instructions, which, when executed by the processor, cause the processor to perform the excavator optimization method as described above.

[0022] According to another aspect of this disclosure, a computer-readable storage medium is also proposed, on which computer instructions are stored, wherein the computer instructions, when executed by a processor, implement the above-described optimization method.

[0023] According to another aspect of this disclosure, a computer program product is also proposed, comprising: computer instructions that, when executed by a processor, implement the above-described optimization method.

[0024] In this embodiment of the disclosure, by acquiring complete operational data and dividing the excavator's working process into multiple working stages, the operational performance of the excavator is evaluated for each working stage. Based on the evaluation results, the components and operational level of the excavator are optimized. Since the optimization of the excavator is based on the evaluation results of each working stage, compared with the optimization of the excavator based on the evaluation results of the entire working process, the optimization is more precise.

[0025] Other features and advantages of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0026] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the specification, serve to explain the principles of this disclosure.

[0027] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein:

[0028] Figure 1 This is a flowchart illustrating some embodiments of the excavator optimization method disclosed herein;

[0029] Figure 2 These are schematic diagrams illustrating some embodiments of the operational data system disclosed herein;

[0030] Figure 3 This is a diagram showing the main operational variables for the working stages in some embodiments of this disclosure;

[0031] Figure 4 This is a schematic diagram showing the change of the bucket opening angle during the working stage in some embodiments of this disclosure;

[0032] Figure 5 This is a schematic diagram showing the changes in the bucket trajectory during the working phase in some embodiments of this disclosure;

[0033] Figure 6 This is a schematic diagram showing the change of bucket cylinder force during the working stage in some embodiments of this disclosure;

[0034] Figure 7 This is a schematic diagram of the energy efficiency evaluation system in some embodiments of this disclosure;

[0035] Figure 8 This is a schematic diagram showing the changes in the bucket bottom angle and trajectory angle during the excavation stage in some embodiments of this disclosure;

[0036] Figure 9 This is a schematic diagram of the comprehensive optimization system in some embodiments of this disclosure;

[0037] Figure 10 Block diagrams of some embodiments of the excavator optimization system of this disclosure;

[0038] Figure 11 Block diagrams showing some embodiments of the electronic devices disclosed herein. Detailed Implementation

[0039] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0040] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0041] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0042] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0043] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0044] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0045] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0046] Figure 1 This is a flowchart illustrating some embodiments of the excavator optimization method disclosed herein, which includes steps S11-S14.

[0047] In step S11, the excavator's operating data is obtained.

[0048] In some embodiments, the excavator's operational data includes collected data, derived calculation data, and calculation result data.

[0049] In related technologies, only excavator operation data is involved, without forming a data system. This embodiment, however, involves three types of data. For example... Figure 2 As shown, Figure 2 This is a schematic diagram illustrating some embodiments of the operational data system disclosed herein. For example, the first type of data is collected data, which includes time data, engine data, reserved battery data, reserved motor data, hydraulic pump data, hydraulic valve oil supply data, mechanism motion data, vehicle body and reserved attachment data, hydraulic valve return oil data, radiator and return oil back pressure data, etc. From another perspective, collected data can also be divided into power data, operation data, work data, motion data, etc. Engine data and hydraulic pump data belong to power data, pilot data belong to operation data, pressure data belong to work data, and cylinder and motor data, mechanism data, etc. belong to motion data.

[0050] The second category of data includes derived computational data, which refers to the data generated during the cleaning, calibration, and derivation processes of the original collected data. Derivative computational data can be pre-loaded with a 7-layer middleware platform. For example, original data typically contains noise and occasional defects, and may not meet the requirements for subsequent analysis. Noise reduction is generally required; defects are typically corrected by tracing back to the original data and applying algorithms; deficiencies are addressed through derivation based on algorithms. Based on this, approximately 3 layers of middleware are needed to correct and supplement the original data. Additionally, original data generally only contains operational data and not inherent electromechanical and hydraulic control mechanism data, requiring 1 layer of middleware for setting inherent characteristic data. Furthermore, the process from original data to result data involves multiple steps of derived calculations, including displacement to velocity, velocity to flow rate, and flow rate to power, generally requiring 3 layers of middleware. In summary, including the data correction, inherent characteristic calculations, and derived calculations mentioned above, approximately 7 layers of middleware are needed. Those skilled in the art should understand that this 7-layer middleware platform is merely an example, and multiple middleware platforms can be set up according to actual circumstances.

[0051] The third category of data includes calculation result data, such as energy consumption data, production data, efficiency data, operational data, and soil condition data. For example, energy consumption data can be determined based on one or more of the following: engine data, reserved battery data, reserved motor data, hydraulic valve return oil data, and radiator and return oil back pressure data. Production and efficiency data can be determined based on one or more of the following: mechanism motion data, vehicle body frame and reserved attachment data. Soil condition and operational data can be determined based on one or more of the following: hydraulic pump data and hydraulic valve oil supply data.

[0052] In some embodiments, boom data, stick data, bucket data, boom tilt angle sensor data, and vehicle body angle encoder data can also be used as the basis for calculation and analysis.

[0053] In other embodiments, data such as cylinder displacement sensing data and vehicle body gyroscope data can be used as the basis for subsequent segmentation and evaluation.

[0054] In this step, by establishing a complete system of operational data variables, it is possible to support the comprehensive calculation of energy efficiency evaluation indicators; the hierarchical operational data platform system supports the integration of energy efficiency algorithms and evaluation processes. Therefore, this operational data system has strong engineering value.

[0055] In step S12, based on the work data, each work cycle of the excavator is divided into multiple work stages.

[0056] In this step, a work cycle of the excavator is divided into multiple work stages, facilitating subsequent analysis of data from each stage. Furthermore, this step divides the excavator's work process based on its operational data, which is more realistic than manual division or division using fixed thresholds, resulting in more accurate segmentation. Additionally, segmenting the work process based on bucket video is susceptible to environmental factors such as lighting, dust, obstructions, angle, shadows, rain, and snow, leading to misjudgments. Video data also suffers from delays in image acquisition, transmission, and recognition. In this embodiment, segmenting the work process based on operational data more closely reflects actual work characteristics, resulting in more accurate, stable, and realistic segmentation that naturally aligns with subsequent optimization goals. This creates a more complete data chain, thereby improving the accuracy of subsequent optimization.

[0057] In step S13, the excavator's performance in each working stage is evaluated based on the work data of each working stage.

[0058] This step involves evaluating and quantifying the operational performance of each work stage, facilitating subsequent optimization of the excavator. Evaluating the excavator's performance throughout the entire work process makes it difficult to pinpoint specific weaknesses. This embodiment, however, uses a phased evaluation approach to more accurately identify issues related to energy consumption, efficiency, response, and control at each stage.

[0059] In step S14, based on the evaluation results of each work stage, at least one of the excavator's components and operating level is optimized.

[0060] In some embodiments, the excavator's components include an engine, hydraulic pump, hydraulic system, and mechanical system. The operating level includes the consistency between the bucket digging angle and the digging trajectory angle.

[0061] Optimizing the excavator based on the evaluation results of its entire working process would smooth out the differences in load, speed, and power at each stage, resulting in sacrificing performance during critical operational phases. However, in this approach, for example, if the evaluation indicators for a particular stage of the excavator's operation are poor, the reasons for these poor indicators can be identified stage by stage, allowing for optimization of the excavator. This makes the optimization direction clearer and the control strategy more refined.

[0062] In this embodiment, by acquiring complete operational data and dividing the excavator's working process into multiple working stages, the operational performance of the excavator is evaluated for each working stage. Based on the evaluation results, the components and operational level of the excavator are optimized. Since the optimization of the excavator is based on the evaluation results of each working stage, it is more precise than the optimization based on the evaluation results of the entire working process of the excavator.

[0063] In some embodiments of this disclosure, each work cycle of the excavator is divided into a digging phase, a lifting and slewing phase, an unloading phase, and an empty bucket return phase based on work data.

[0064] Based on the characteristics of its movements, the excavator's digging cycle can be divided into the digging stage, the lifting and slewing stage, the unloading stage, and the empty bucket return stage. For example... Figure 3 As shown, Figure 3 This diagram illustrates the main operational variables for the working stages in some embodiments of this disclosure. Curve 31 corresponds to the boom digging leader value, curve 32 corresponds to the boom raising leader value, curve 33 corresponds to the bucket unloading leader value, and curve 34 corresponds to the boom lowering leader value. During the digging stage, the boom digging leader value is more significant; during the lifting and slewing stage, the boom raising leader value is more significant; during the unloading stage, the bucket unloading leader value is more significant; and during the empty bucket return stage, the boom lowering leader value is more significant. Therefore, in embodiments of this disclosure, each working cycle of the excavator is sequentially divided into a digging stage, a lifting and slewing stage, an unloading stage, and an empty bucket return stage.

[0065] In this embodiment, the excavator's operation process is divided based on the operation data, which can support subsequent system optimization.

[0066] In some embodiments of this disclosure, the digging stage and the hoisting and slewing stage are distinguished based on bucket angle data in the operation data.

[0067] For example, bucket angle data can be determined based on mechanism motion data. For instance, by collecting the stroke of the bucket cylinder, the bucket angle can be calculated from the mechanism system model based on the characteristics of the mechanism system during data processing and analysis. Additionally, the bucket boom tilt angle can also be collected and calculated from the mechanism system model.

[0068] The bucket angle is also called the bucket mouth angle. For example... Figure 4 As shown, Figure 4 This is a schematic diagram showing the change of the bucket opening angle during the working stage in some embodiments of this disclosure. Figure 4 The horizontal axis represents the sequence of working stages, and the vertical axis represents the angle of the bucket opening. 41 represents the boundary angle of the bucket opening. As shown in the attached figure, the change in bucket angle is more obvious from the digging stage to the lifting and slewing stage. Therefore, in this embodiment of the present disclosure, bucket angle data is used to determine the turning point between the digging stage and the lifting and slewing stage, thereby improving the accuracy of the division between the digging stage and the lifting and slewing stage.

[0069] In some embodiments, the digging stage and the lifting and slewing stage are distinguished based on a bucket angle threshold and a bucket angle change trend. The bucket angle changes dramatically from a digging posture to a lifting posture.

[0070] For example, before and after the bucket angle threshold, the change in bucket angle exhibits a downward trend, and the bucket angle will increase after reaching a certain angle. The period before the bucket angle threshold corresponds to the digging phase, while the period after the bucket angle threshold corresponds to the hoisting and slewing phase.

[0071] In other embodiments of this disclosure, the lifting slewing stage, unloading stage, and empty bucket return stage are distinguished based on the bucket trajectory data in the operation data.

[0072] The bucket trajectory refers to the movement path of the bucket teeth tip on the longitudinal plane of the working device during the transition from the lifting and slewing stage to the unloading stage, and from the unloading stage to the empty bucket return stage. For example, the working trajectory of the bucket teeth tip can be calculated based on the stroke data of each hydraulic cylinder or the tilt angle data of each structural component.

[0073] like Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the changes in the bucket trajectory during the working phase in some embodiments of this disclosure. Figure 5 The horizontal axis represents the abscissa of the bucket tooth tip, and the vertical axis represents the ordinate of the bucket tooth tip. Trajectory 51 represents the trajectory during the digging stage, trajectory 52 represents the trajectory during the hoisting and slewing stage, trajectory 53 represents the trajectory during the unloading stage, and trajectory 54 represents the trajectory during the empty bucket return stage. There is a critical point 55 between the hoisting and slewing trajectory and the unloading trajectory, and a critical point 56 between the unloading trajectory and the empty bucket return trajectory. 57 represents the standing profile, and 58 represents the material profile. At critical points 55 and 56, the bucket trajectory has obvious turning points. Therefore, in this embodiment, the transition from the hoisting and slewing stage to the unloading stage, and from the unloading stage to the empty bucket return stage, is distinguished based on the change in the motion angle of the trajectory coordinates in the operation data. Compared with other methods of distinguishing the hoisting and slewing stage, the unloading stage, and the empty bucket return stage, this embodiment's division method is more accurate.

[0074] In some embodiments, the bucket trajectory data is sequentially divided into an upward trajectory, a translational trajectory, and a downward trajectory, wherein the upward trajectory corresponds to the lifting and turning stage, the translational trajectory corresponds to the unloading stage, and the downward trajectory corresponds to the empty bucket return stage.

[0075] like Figure 5 As shown, the bucket trajectory, during the lifting and slewing phase, the unloading phase, and the empty bucket return phase, transitions from primarily upward movement to primarily horizontal movement, and then from primarily horizontal movement to primarily downward movement, thus distinguishing the lifting and slewing phase from the unloading phase, and the unloading phase from the empty bucket return phase. Those skilled in the art, based on... Figure 5It should be understood that the bucket trajectory also includes the trajectory during the digging stage. However, since the trajectory changes from the digging stage to the lifting and slewing stage, and from the empty bucket return stage to the digging stage are not significant, the bucket trajectory was not used to distinguish between the digging stage to the lifting and slewing stage, and from the empty bucket return stage to the digging stage.

[0076] In other embodiments of this disclosure, the empty bucket return phase and the digging phase are distinguished based on the bucket force data in the operation data.

[0077] The bucket force data can be calculated based on the cylinder pressure in the working data and the cylinder diameter and rod diameter in the setting data. Alternatively, the bucket force data can be determined based on the bucket cylinder force and the lever arm data in the bucket four-bar linkage.

[0078] like Figure 6 As shown, Figure 6 This diagram illustrates the changes in bucket cylinder force during the working stages in some embodiments of this disclosure. The horizontal axis represents the sequence of working stages, and the vertical axis represents the value of the bucket cylinder force. From the empty bucket return stage to the digging stage, the bucket undergoes a significant change from being empty to being loaded. Therefore, in this embodiment, the empty bucket return stage and the digging stage are distinguished based on the critical force value of the bucket digging force, thereby improving the accuracy of the division.

[0079] In some embodiments, the empty bucket return stage and the digging stage are distinguished based on the bucket force threshold and the bucket force change trend.

[0080] For example, 61 represents the critical value of the bucket cylinder force, i.e., the bucket force threshold. Before and after the bucket force threshold, the bucket force has an increasing trend. The stage before the bucket force threshold is divided into the empty bucket return stage, and the stage after the bucket force threshold is divided into the digging stage.

[0081] In the above embodiments, the work stage division system based on work data supports the analysis of the reasons for the advantages and disadvantages of energy efficiency evaluation indicators, thereby screening out the work action stages that need to be optimized, and supporting the focused optimization of complex electromechanical and hydraulic control systems.

[0082] In some embodiments of this disclosure, the energy consumption evaluation result of the excavator is determined based on energy consumption data in the operation data.

[0083] Energy consumption data includes fuel consumption and electricity consumption. For example... Figure 7 As shown, Figure 7 This is a schematic diagram of the energy efficiency evaluation system in some embodiments of this disclosure. The energy consumption quantification evaluation of traditional fuel power mainly refers to fuel consumption; the energy consumption quantification evaluation of new energy electric power mainly refers to electrical energy consumption.

[0084] For example, by comparing the energy consumption data of an excavator during a certain working phase with the energy consumption data of a calibrated excavator during the same working phase, it can be determined whether the excavator's energy consumption evaluation result meets the energy consumption requirements. Alternatively, the energy consumption data of an excavator during a certain working phase can be compared with an energy consumption threshold to determine whether the excavator's energy consumption evaluation result meets the energy consumption requirements.

[0085] In some embodiments, the efficiency evaluation result of the excavator is determined based on at least one of the production data, efficiency data, and operational level data in the operation data.

[0086] like Figure 6 As shown, the efficiency quantification evaluation includes the output index of material weight, the single cycle duration index of the excavation operation cycle, and the excavation operation level index of the consistency between the bucket excavation angle and the excavation trajectory angle.

[0087] The bucket angle can be calculated based on the stroke of the bucket cylinder; the position of the bucket teeth tip and the movement trajectory and trajectory angle can be calculated based on the stroke of each cylinder; by comparing the bucket angle and trajectory angle, the operator's skill level can be determined.

[0088] For example, by comparing the excavator's output, efficiency, and operational level data at a certain working stage with the output, efficiency, and operational level data of a calibrated excavator at the same working stage, it can be determined whether the excavator's efficiency evaluation result meets the efficiency requirements. Alternatively, the excavator's output, efficiency, and operational level data at a certain working stage can be compared with output thresholds, efficiency thresholds, and operational level thresholds, respectively, to determine whether the excavator's efficiency evaluation result meets the efficiency requirements.

[0089] In some embodiments, the soil condition evaluation result corresponding to the excavator is determined based on soil condition data.

[0090] like Figure 7 As shown, the soil condition is quantitatively evaluated, including material density and hardness indices.

[0091] In some embodiments, when the soil condition evaluation results are consistent, the operational performance of the excavator at each working stage can be evaluated based on the energy consumption evaluation results and the efficiency evaluation results.

[0092] The energy efficiency evaluation index system in the above embodiments, including energy consumption, efficiency, and soil conditions, is comprehensive and complete. It considers both the impact of material density and hardness on energy efficiency, as well as the impact of operational level, resulting in more accurate quantitative evaluation results. Furthermore, the above energy efficiency evaluation indicators are evaluated according to different work stages, allowing for more precise identification of actions and systems requiring optimization.

[0093] In other embodiments of this disclosure, at least one of the excavator's engine, hydraulic pump, hydraulic system, mechanism system, and operating level is optimized based on the evaluation results of each working stage.

[0094] For example, based on the energy consumption evaluation results, if the energy consumption evaluation results of the excavator at a certain stage do not meet the energy consumption requirements, it can be determined which aspect—engine, hydraulic pump, hydraulic system, mechanism system, or operating level—consumes more energy. Therefore, the component or operating level that consumes more energy can be optimized.

[0095] For example, regarding the efficiency evaluation results, if the excavator's efficiency evaluation results at a certain stage do not meet the efficiency requirements, it can be determined which aspect—engine, hydraulic pump, hydraulic system, mechanism system, or operating level—affects the efficiency, and then the components or operating level can be optimized accordingly.

[0096] For example, different working stages have significantly different power requirements. The digging stage requires high load and high torque; the hoisting and slewing stage requires complex actions and flow matching; the unloading stage requires high pressure and low flow; and the empty bucket return stage requires low load and high efficiency. In this embodiment, staged optimization allows the engine, hydraulic pump, hydraulic system, and actuator to be at the high-efficiency matching point in each stage, resulting in better overall energy saving, responsiveness, and controllability.

[0097] In this embodiment, a comprehensive optimization system covering complex electromechanical and hydraulic control systems is implemented, including the engine, hydraulic pump, driving operation level, hydraulic system, and mechanism system. It fully corresponds to the energy efficiency evaluation results and optimization strategies and methods for each working stage. By optimizing the excavator components and operating level, the energy efficiency index of the excavator's digging operation cycle can be improved.

[0098] In some embodiments, optimizing the operational level includes at least one of the following: optimizing the action connection process of multiple work stages; optimizing the consistency between the bucket digging angle and the digging trajectory angle.

[0099] Optimizing the four-stage motion connection process of compound operation can improve the efficiency of excavators. Additionally, such as... Figure 8 As shown, Figure 8 This diagram illustrates the changes in the bucket bottom angle and trajectory angle during the excavation phase in some embodiments of this disclosure. The horizontal axis represents time, and the vertical axis represents the angle value. Curve 81 represents the bucket bottom angle, and curve 82 represents the excavation trajectory angle. Instructing the driver to maintain consistency between the bucket excavation angle and the excavation trajectory angle can reduce soil resistance during the excavation phase, thereby reducing energy consumption and improving operational efficiency, achieving low-energy, high-efficiency control.

[0100] In some embodiments, if the excavator is a fully electric excavator, the bucket angle can be directly controlled by an intelligent control program. If the excavator is a conventional excavator without intelligent control functions, the driver can be prompted to optimize their driving habits via a display screen on the vehicle side.

[0101] In some embodiments of this disclosure, optimizing the mechanism system includes at least one of the following: optimizing the mechanism hinge points of the excavator; optimizing the bucket shape of the excavator.

[0102] For example, based on the lever mechanism, the system can be optimized. The ratio of the load arm to the cylinder arm is the primary factor; a larger ratio means the load travels a greater distance after the cylinder extends a certain length, resulting in higher efficiency. Simultaneously, under the same load conditions, the cylinder force will also be greater. The absolute length of the arm is a secondary factor; a shorter arm results in greater stress on the structural components under the same load conditions, and the structural durability and reliability are related to the strength of the structural component materials. In summary, optimizing a mechanism system is neither about maximizing the arm ratio nor maximizing the absolute length. It requires considering the balance between efficiency and force in complex systems, typically exhibiting a quadratic form, meaning the optimal settings can be extracted.

[0103] In this embodiment, the optimization of the mechanism system includes not only the optimization of the structural hinge points, but also the optimization of the bucket shape. The bucket shape mainly includes the bucket opening height, bucket opening width, and bucket depth. Among them, the bucket height affects the digging depth and is related to the bucket digging force. It is necessary to balance the bucket cylinder force and the bucket digging speed to achieve the best bucket digging energy efficiency. In addition, the bucket width affects the eccentric load and is related to the strength of the bucket root shaft and friction loss. It is necessary to balance the working efficiency of the effective bucket opening width and the performance of the bucket root shaft. Finally, the bucket depth is related to the volume of material per bucket and needs to balance the material density and the boom lifting force to take into account the output per bucket and the material lifting efficiency.

[0104] In some embodiments, optimizing the engine includes optimizing the engine's operating distribution points based on a universal characteristic diagram.

[0105] Universal characteristic diagrams can be obtained from engine suppliers or through engine bench testing. For example, by applying steady-state loads at various operating points, corresponding data on speed, torque, and fuel consumption can be obtained, allowing the creation of a universal characteristic diagram. Based on this diagram, the engine's operating points can be optimized. For instance, by analyzing the position and corresponding efficiency of the original operating points on the universal characteristic diagram, points with lower efficiency can be identified. Then, constant power lines are plotted at these points, and the corresponding high-efficiency points on the universal characteristic diagram are found. Based on speed or pressure control, the original operating points can be shifted along the constant power line to new operating points, improving efficiency without affecting operating power and efficiency.

[0106] Since the energy efficiency evaluation results of this application are quantitative indicators that are sliced ​​at the component level and the working stage level, the distribution points that need to be worked on can be screened more effectively, making the optimization work more focused and efficient.

[0107] In some embodiments, optimizing the hydraulic pump includes optimizing the operating distribution points of the hydraulic pump based on a pump efficiency diagram.

[0108] Pump efficiency diagrams can be obtained from hydraulic pump suppliers or through hydraulic pump bench tests. For example, by applying a steady-state load at various operating points, corresponding data on pressure, displacement ratio, and overall efficiency can be obtained. Overall efficiency = output power / input power, output power = output pressure * output flow rate, and input power = input speed * input torque. Based on the data collected from the bench test, the overall efficiency data for each point can be obtained, and thus, an overall efficiency diagram can be plotted.

[0109] Similar to the optimization of the engine's operating point distribution, this embodiment optimizes the hydraulic pump's operating point distribution based on the pump efficiency diagram. The position of the original operating point distribution on the pump efficiency diagram and its corresponding efficiency are analyzed, and points with lower efficiency are identified. Then, a constant power line is drawn for these points, and the points with higher efficiency in the corresponding pump efficiency diagram are found. Based on speed control or pressure control, the original operating point distribution is shifted to a new operating point distribution on the constant power line, thereby improving efficiency without affecting operating power and efficiency.

[0110] In some embodiments, optimizing the hydraulic system includes optimizing at least one of the valve opening characteristics and piping connection specifications of the hydraulic system.

[0111] In this embodiment, by optimizing the valve opening characteristics and pipeline connection specifications of the hydraulic system, system pressure loss can be reduced.

[0112] In some embodiments, such as Figure 9 As shown, Figure 9 This diagram illustrates a comprehensive optimization system in some embodiments of the present disclosure. The system includes engine optimization, hydraulic pump optimization, operational level optimization, hydraulic system optimization, and mechanism system optimization. Engine optimization includes optimizing the working point distribution based on universal characteristics; hydraulic pump optimization includes optimizing the working point distribution based on pump efficiency maps; operational level optimization includes the four-stage connection of compound actions and the consistency between bucket angle and trajectory angle; hydraulic system optimization includes optimizing hydraulic valve opening characteristics to mitigate pipeline system damage; and mechanism system optimization includes optimizing mechanism hinge points and optimizing bucket size and bucket shape. In this embodiment, this comprehensive optimization system can improve the excavator's energy efficiency.

[0113] In other embodiments of this disclosure, optimizing at least one of the components and operating level of the excavator based on the evaluation results of each working stage includes: determining the working mode of the excavator; determining the key evaluation index results in the evaluation results based on the working mode; and optimizing at least one of the components and operating level of the excavator based on the key evaluation index results.

[0114] For example, excavators have various modes, commonly including P mode, H mode, E mode, and C mode. P mode is the power mode, requiring high operating efficiency; H mode is the heavy-duty mode, requiring high digging force, i.e., high working pressure and torque; E mode is the energy-saving mode, requiring low energy consumption; and C mode is the normal mode, requiring moderate energy consumption and moderate efficiency. Therefore, the key evaluation indicators differ depending on the mode. For instance, in P mode, the focus is more on output evaluation indicators; in H mode, the focus is on soil condition evaluation indicators; in E mode, the focus is more on energy consumption evaluation indicators; and in C mode, the focus is more on both energy consumption and efficiency evaluation indicators.

[0115] Based on the results of key performance indicators (KPIs), it can be determined which components or operational levels of the excavator are optimized to improve those KPIs. Furthermore, this embodiment optimizes the excavator separately for each work stage based on the KPI results, which improves the accuracy of the optimization objectives. The specific methods for optimizing excavator components and operational levels have been described in the above embodiments and will not be elaborated further here.

[0116] In some embodiments of this disclosure, based on the evaluation results of each work stage, the work stages that need to be optimized are determined; at least one of the components and operating level of the excavator for the work stages that need to be optimized is optimized.

[0117] Evaluating an excavator's performance throughout the entire work process makes it difficult to pinpoint the specific weakness. This embodiment, however, uses a phased evaluation approach, which more accurately identifies issues related to energy consumption, efficiency, response, and control at each stage. By identifying a specific work stage and optimizing the excavator's components and operational level based on the evaluation results for that stage, the excavator can be brought into a highly efficient and well-matched state during that stage.

[0118] The above describes some embodiments of the excavator optimization method of this disclosure. Below, the excavator optimization system of this disclosure will be further described with reference to the accompanying drawings.

[0119] like Figure 10 As shown, Figure 10The diagram shows some embodiments of the excavator optimization system disclosed herein, which includes a data acquisition module 101, a stage division module 102, an evaluation module 103, and an optimization module 104.

[0120] The data acquisition module 101 is configured to acquire the excavator's work data; the stage division module 102 is configured to divide each work cycle of the excavator into multiple work stages based on the work data; the evaluation module 103 is configured to evaluate the excavator's work performance in each work stage based on the work data of each work stage; and the optimization module 104 is configured to optimize at least one of the excavator's components and operating level based on the evaluation results of each work stage.

[0121] In this embodiment, by acquiring complete operational data and dividing the excavator's working process into multiple working stages, the operational performance of the excavator is evaluated for each working stage. Based on the evaluation results, the components and operational level of the excavator are optimized. Since the optimization of the excavator is based on the evaluation results of each working stage, it is more precise than the optimization based on the evaluation results of the entire working process of the excavator.

[0122] In some embodiments of this disclosure, the phase division module 102 is configured to divide each work cycle of the excavator into a digging phase, a lifting and slewing phase, an unloading phase, and an empty bucket return phase based on work data.

[0123] In some embodiments, the phase division module 102 is configured to distinguish between the digging phase and the hoisting and slewing phase based on the bucket angle data in the operation data.

[0124] In some embodiments, the phase division module 102 is configured to distinguish between the lifting and slewing phase, the unloading phase, and the empty bucket return phase based on the bucket trajectory data in the operation data.

[0125] In some embodiments, the phase division module 102 is configured to distinguish between the empty bucket return phase and the digging phase based on the bucket force data in the operation data.

[0126] In some embodiments, the stage division module 102 is configured to distinguish between the digging stage and the hoisting and slewing stage based on the bucket angle threshold and the bucket angle change trend.

[0127] In some embodiments, the stage division module 102 is configured to divide the bucket trajectory data into an upward trajectory, a translational trajectory, and a downward trajectory in sequence, wherein the upward trajectory corresponds to the lifting and turning stage, the translational trajectory corresponds to the unloading stage, and the downward trajectory corresponds to the empty bucket return stage.

[0128] In some embodiments, the stage division module 102 is configured to distinguish between the empty bucket return stage and the digging stage based on the bucket force threshold and the bucket force change trend.

[0129] In some embodiments of this disclosure, the evaluation module 103 is configured to determine the energy consumption evaluation result of the excavator based on the energy consumption data in the operation data; determine the efficiency evaluation result of the excavator based on at least one of the output data, efficiency data, and operation level data in the operation data; and determine the soil condition evaluation result corresponding to the excavator based on the soil condition data.

[0130] In some embodiments of this disclosure, the optimization module 104 is configured to optimize at least one of the excavator's engine, hydraulic pump, hydraulic system, mechanism system, and operating level based on the evaluation results of each working stage.

[0131] In some embodiments, the optimization module 104 is configured to optimize the action connection process of multiple working stages and optimize the consistency between the bucket digging angle and the digging trajectory angle.

[0132] In some embodiments, the optimization module 104 is configured to optimize the mechanism hinge points of the excavator and optimize the bucket shape of the excavator.

[0133] In some embodiments, the optimization module 104 is configured to optimize the engine's operating distribution points based on a universal characteristic map.

[0134] In some embodiments, the optimization module 104 is configured to optimize the operating distribution points of the hydraulic pump based on the pump efficiency map.

[0135] In some embodiments, the optimization module 104 is configured to optimize at least one of the valve opening characteristics and piping connection specifications of the hydraulic system.

[0136] In some embodiments, the optimization module 104 is configured to determine the working mode of the excavator; based on the working mode, determine the key evaluation index results in the evaluation results; and based on the key evaluation index results, optimize at least one of the components and operating level of the excavator.

[0137] In some embodiments, the optimization module 104 is configured to determine the work phases that need optimization based on the evaluation results of each work phase; and to optimize at least one of the components and operating level of the excavator for the work phases that need optimization.

[0138] In some embodiments, job data includes collected data, derived calculation data, and calculation result data.

[0139] It should be noted that the above modules are logical modules divided according to their specific functions, and are not used to restrict the specific implementation method. For example, they can be implemented in software, hardware, or a combination of software and hardware. In actual implementation, the above modules can be implemented as independent physical entities, or they can be implemented by a single entity (e.g., a processor (CPU or DSP, etc.), integrated circuit, etc.).

[0140] In other embodiments of this disclosure, the optimization system may also be programmed in the form of an electronic device, such as... Figure 11 As shown, Figure 11 Block diagrams showing some embodiments of the electronic devices disclosed herein.

[0141] The electronic device 11 includes a memory 111 and a processor 112. The memory 111 is coupled to the processor 112 and is used to store instructions. When the instructions are executed by the processor 112, the processor 112 performs the optimization method described above.

[0142] Memory 111 is used to store one or more computer-readable instructions. Memory 111 may include any combination of various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory, including but not limited to random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), and flash memory. Memory 111 may, for example, store operating systems, applications, bootloaders, databases, and other programs, as well as various applications and various data.

[0143] The processor 112 is configured to execute computer-readable instructions to implement the optimized method of any of the foregoing embodiments. Specific implementations of each step of the method can be found in the above embodiments; repeated details will not be elaborated upon here.

[0144] Processor 112 can be configured to perform the steps described above. Processor 112 can be various processing devices, such as a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The central processing unit (CPU) can be an X116 or ARM architecture, etc.

[0145] The processor 112 and the memory 111 can communicate with each other directly or indirectly. For example, the processor 112 and the memory 111 can communicate via a network. The network can include a wireless network, a wired network, and / or any combination of wireless and wired networks. The processor 112 and the memory 111 can also communicate with each other via a system bus, which is not limited in this disclosure.

[0146] It should be noted that Figure 11 The components of the electronic device 11 shown are merely exemplary and not limiting; the electronic device 11 may have other components as needed for the actual application. The processor 112 can control other components in the electronic device 11 to perform desired functions.

[0147] In some embodiments, the processor 112 is coupled to the memory 111 via a BUS bus 113. The electronic device 11 can also be connected to an external storage device 115 via a storage interface 114 to access external data, and can also be connected to a network or another computer system (not shown) via a network interface 116. Further details are omitted here.

[0148] In the above embodiments, data instructions are stored in the memory and then processed by the processor, which optimizes the pointing accuracy.

[0149] In other embodiments, a computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the steps of the methods described above. Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, apparatus, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] In some embodiments, a computer program product is protected, comprising a computer program or instructions that, when executed by a processor, implement the methods described above. The computer program product includes a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from ROM. When the computer program is executed by a CPU, it performs the functions defined in the methods of embodiments of this disclosure.

[0151] In some embodiments, a computer program is protected, the computer program comprising: instructions that, when executed by a processor, cause the processor to perform the methods described in any of the foregoing embodiments. For example, the instructions may be embodied in computer program code.

[0152] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0153] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0155] This concludes the detailed description of the present disclosure. To avoid obscuring the concept of the disclosure, some details known in the art have not been described. Those skilled in the art will fully understand how to implement the technical solutions disclosed herein based on the above description.

[0156] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0157] While specific embodiments of this disclosure have been described in detail by way of example, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of this disclosure. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this disclosure. The scope of this disclosure is defined by the appended claims.

Claims

1. An optimization method for an excavator, comprising: Obtain the operating data of the excavator; Based on the operation data, each work cycle of the excavator is divided into multiple work stages; The excavator's performance in each work phase is evaluated based on the operational data from each work phase. Based on the evaluation results of each work stage, at least one of the components and operating level of the excavator is optimized.

2. The optimization method according to claim 1, wherein, Based on the aforementioned work data, each work cycle of the excavator is divided into multiple work stages, including: Based on the aforementioned operational data, each work cycle of the excavator is divided into the digging stage, the lifting and slewing stage, the unloading stage, and the empty bucket return stage.

3. The optimization method according to claim 2, wherein, Based on the aforementioned operational data, each work cycle of the excavator is divided into a digging phase, a hoisting and slewing phase, an unloading phase, and an empty bucket return phase, including at least one of the following: Based on the bucket angle data in the operational data, the digging stage and the lifting and slewing stage are distinguished. Based on the bucket trajectory data in the operation data, the lifting and rotation stage, the unloading stage, and the empty bucket return stage are distinguished. Based on the bucket force data in the operation data, the empty bucket return stage and the digging stage are distinguished.

4. The optimization method according to claim 3, wherein, Based on the bucket angle data in the operational data, distinguishing between the digging stage and the hoisting and slewing stage includes: Based on the bucket angle threshold and the bucket angle change trend, the digging stage and the lifting and slewing stage are distinguished.

5. The optimization method according to claim 3, wherein, Based on the bucket trajectory data in the operational data, distinguishing between the lifting and slewing phase, the unloading phase, and the empty bucket return phase includes: The bucket trajectory data is divided into an upward trajectory, a horizontal trajectory, and a downward trajectory, wherein the upward trajectory corresponds to the lifting and slewing stage, the horizontal trajectory corresponds to the unloading stage, and the downward trajectory corresponds to the empty bucket return stage.

6. The optimization method according to claim 3, wherein, Based on the bucket force data in the operational data, distinguishing between the empty bucket return phase and the digging phase includes: Based on the bucket force threshold and the bucket force change trend, the empty bucket return stage and the digging stage are distinguished.

7. The optimization method according to any one of claims 1 to 6, wherein, The evaluation of the excavator's operational performance at each working stage, based on operational data from each stage, includes at least one of the following: Based on the energy consumption data in the operation data, the energy consumption evaluation result of the excavator is determined; The efficiency evaluation result of the excavator is determined based on at least one of the output data, efficiency data, and operational level data in the operation data. Based on the soil condition data, the soil condition evaluation result corresponding to the excavator is determined.

8. The optimization method according to any one of claims 1 to 6, wherein, Based on the evaluation results of each working stage, optimizing at least one of the excavator's components and operating level includes: Based on the evaluation results of each working stage, at least one of the excavator's engine, hydraulic pump, hydraulic system, mechanism system, and operating level is optimized.

9. The optimization method according to claim 8, wherein, Optimizing the operational level includes at least one of the following: Optimize the action connection process of the multiple working stages; The consistency between the bucket digging angle and the digging trajectory angle is optimized.

10. The optimization method according to claim 8, wherein, Optimizing the aforementioned mechanism system includes at least one of the following: The mechanism hinge points of the excavator are optimized; The shape of the bucket of the excavator is optimized.

11. The optimization method according to claim 8, wherein, Optimizing the engine includes: Based on the universal characteristic diagram, the operating distribution points of the engine are optimized.

12. The optimization method according to claim 8, wherein, Optimizing the hydraulic pump includes: Based on the pump efficiency diagram, the working distribution points of the hydraulic pump are optimized.

13. The optimization method according to claim 8, wherein, Optimizing the hydraulic system includes: At least one of the valve opening characteristics and pipeline connection specifications of the hydraulic system shall be optimized.

14. The optimization method according to any one of claims 1 to 6, wherein, Based on the evaluation results of each working stage, optimizing at least one of the excavator's components and the operating level includes: Determine the operating mode of the excavator; Based on the aforementioned working mode, the key evaluation indicators in the evaluation results are determined; Based on the results of the key evaluation indicators, at least one of the components of the excavator and the operating level is optimized.

15. The optimization method according to any one of claims 1 to 6, wherein, Based on the evaluation results of each working stage, optimizing at least one of the excavator's components and the operating level includes: Based on the evaluation results of each work stage, the work stages that need to be optimized are determined; At least one of the components of the excavator and the operating level is optimized for the operational phase that requires optimization.

16. The optimization method according to any one of claims 1 to 6, wherein, The operational data includes collected data, derived calculation data, and calculation result data.

17. An optimization system for an excavator, comprising: The data acquisition module is configured to acquire the excavator's operating data; The phase division module is configured to divide each work cycle of the excavator into multiple work phases based on the work data. The evaluation module is configured to evaluate the excavator's operational performance at each work stage based on the operational data at each work stage. An optimization module is configured to optimize at least one of the excavator's components and operating level based on the evaluation results of each working stage.

18. An electronic device, comprising: processor; as well as A memory coupled to the processor is used to store instructions that, when executed by the processor, cause the processor to perform the optimization method for the excavator as described in any one of claims 1 to 16.

19. A computer-readable storage medium having stored thereon computer instructions, wherein, When executed by a processor, the computer instructions implement the optimization method according to any one of claims 1 to 16.

20. A computer program product comprising: It includes computer instructions that, when executed by a processor, implement the optimization method according to any one of claims 1 to 16.

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