Hybrid construction machine control method and system based on job load identification

Abstract

The application discloses a kind of based on job load identification's hybrid engineering machinery control method and system, belong to engineering machinery technical field, calculate driver target torque and target time's hydraulic pump predicted torque;Calculate torque difference;Based on fuzzy control algorithm, consider engine optimal fuel consumption torque interval and ISG motor optimal efficiency torque interval, according to driver target torque, the difference of driver target torque and hydraulic pump predicted torque and battery SOC, determine engine target torque and ISG motor target torque;Utilize engine target torque and ISG motor target torque to control hydraulic pump pressure jointly.The advantages are: by Markov to build job load prediction model, predict future time's job load, introduce driver target torque and the difference of both, consider battery SOC state to build engine and ISG motor torque distribution fuzzy controller, dynamically adjust engine and ISG motor target torque.

Description

Technical Field

[0001] This invention relates to a control method and system for hybrid power construction machinery based on work load identification, belonging to the field of construction machinery technology. Background Technology

[0002] While pure electric construction machinery has the advantages of low operating costs and no pollution, it has obvious disadvantages such as short operating time and long refueling time. Hybrid excavators combine the advantages of continuous operation of traditional excavators and low operating costs of pure electric excavators. Therefore, hybrid construction machinery has become an important part of the new energy construction machinery field.

[0003] Because excavator operating conditions are complex and varied, the engine and motor need to respond to frequently changing loads, which seriously affects the efficiency and energy consumption of the motor and engine. To ensure that the engine and motor can respond quickly to the excavator's operating conditions, it is necessary to identify the excavator's operating conditions and formulate different engine and motor control strategies based on these conditions. Therefore, quickly identifying the excavator's operating conditions and formulating matching engine and motor control strategies has become an urgent problem to be solved.

[0004] In existing technologies, although the working modes of engineering vehicles can be predicted online, the prediction accuracy is limited by the output accuracy of deep learning models, resulting in significant biases in working condition identification. Other existing technologies acquire working condition data at preset time intervals and use feature value analysis to determine the excavator's working conditions. However, multiple working conditions may coexist within a given time interval; identifying them as a single condition leads to low accuracy. Existing technologies also collect acceleration data of engineering vehicles in any direction by adding sensors and gyroscopes, increasing costs and hindering patent application. Current plans often focus on identifying the excavation and platform-building phases, neglecting other excavator working conditions.

[0005] Therefore, quickly identifying the operating conditions of excavators and developing matching engine and motor control strategies has become an urgent problem to be solved. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a control method and system for hybrid power engineering machinery based on work load identification.

[0007] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution.

[0008] In one aspect, the present invention discloses a control method for hybrid power construction machinery based on work load identification, comprising:

[0009] The driver's target torque is calculated based on the obtained handle opening degree and opening change rate;

[0010] Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery.

[0011] The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque.

[0012] Based on the fuzzy control algorithm, considering the optimal fuel consumption torque range of the engine and the optimal efficiency torque range of the ISG motor, the target torque of the engine and the target torque of the ISG motor are determined according to the difference between the driver's target torque, the driver's target torque and the hydraulic pump's predicted torque, and the battery's SOC.

[0013] The hydraulic pump pressure is controlled by using the target torque of the engine and the target torque of the ISG motor.

[0014] Furthermore, the step of calculating the driver's target torque based on the acquired handle opening degree and the rate of change of opening degree includes:

[0015] Collect the lever opening degree k and the rate of change of opening degree operated by the driver. By the handle opening degree k and the rate of change of opening degree Calculate the driver's target torque.

[0016] Furthermore, the prediction of the hydraulic pump predicted pressure at the target time based on the currently collected hydraulic pump pressure includes:

[0017] The pressure sets of the regulating hydraulic pump under various operating conditions are collected. Outliers are removed from the pressure sets, and the pressure distribution of the pressure sets after outlier removal is statistically analyzed to obtain the overall pressure range [0, ]. p max ], p max This indicates the maximum pressure of the hydraulic pump;

[0018] The overall pressure range is [0, p max Based on the difference of discrete intervals Divided into n Discrete intervals, hydraulic pump pressure p Represented as:

[0019] ;

[0020] The determined pressure distribution state is as follows:

[0021] ;

[0022] In the formula, Indicates the first i The states corresponding to each discrete interval i= 1,2,3,…, n ;

[0023] Based on the defined pressure distribution states, the transition probabilities between states are calculated, and the statistics for any given state are statistically analyzed. After a change, it transitions to another state. The probability is calculated by Transferred to The transition probability is ;

[0024] After calculating all state transition probabilities, the state transition probability matrix is ​​composed of all state transition probabilities. P For the Markov chain operation load prediction model, the predicted hydraulic pump pressure at the next moment is obtained from the Markov chain operation load prediction model based on the currently collected hydraulic pump pressure.

[0025] ;

[0026] State transition probability matrix P It satisfies the following properties:

[0027] .

[0028] Furthermore, the expression for calculating the predicted hydraulic pump torque at the target time based on the predicted hydraulic pump pressure at the target time is as follows:

[0029]

[0030] In the formula: T Predict the hydraulic pump torque at the target time; p f Predict the hydraulic pump pressure at the target time; V This refers to the displacement of the hydraulic pump. η This refers to the volumetric efficiency of the hydraulic pump.

[0031] Furthermore, the expression for the difference between the driver's target torque and the hydraulic pump's predicted torque is as follows:

[0032] ;

[0033] In the formula: Δ is the difference between the driver's target torque and the hydraulic pump's predicted torque. T t For the driver's target torque, T Predict the hydraulic pump torque at the target time.

[0034] Furthermore, based on the fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, the target torque of the engine and the target torque of the ISG motor are determined according to the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC, including:

[0035] Set the driver's target torque The fuzzy subset and the corresponding driver target torque The first linguistic variable of each element in the fuzzy subset;

[0036] Set the driver's target torque The difference between the predicted torque and the hydraulic pump torque The fuzzy subset and the corresponding difference The second linguistic variable of the elements in the fuzzy subset;

[0037] Set the fuzzy subset of the battery SOC and the third linguistic variable for each element in the corresponding fuzzy subset of the battery SOC;

[0038] Set engine target torque Fuzzy subsets and corresponding engine target torque The fourth linguistic variable for each element in the fuzzy subset;

[0039] Set the target torque for the ISG motor Fuzzy subsets and corresponding target torque of ISG motors The fifth linguistic variable for each element in the fuzzy subset;

[0040] Construct fuzzy control rules based on first language variables, second language variables, third language variables, fourth language variables, and fifth language variables;

[0041] Based on the constructed fuzzy control rules, when the battery SOC is lower than the preset charge level, the target torque of the ISG motor is controlled. The value of makes the target torque of the ISG motor... The value is such that it can simultaneously meet the vehicle load and the ISG motor power generation requirements;

[0042] According to the constructed fuzzy control rules, when the battery SOC is not lower than the preset charge level, the target torque of the driver is determined. The difference between the predicted torque and the hydraulic pump torque The subset to which it belongs determines the engine target torque and ISG motor target torque .

[0043] Secondly, the present invention discloses a hybrid power engineering machinery control system based on work load identification, comprising:

[0044] Engine module, ISG motor module, hydraulic system, operating device and control module;

[0045] The hydraulic system includes a hydraulic pump, hydraulic valves, a hydraulic actuator, and a hydraulic circuit; the hydraulic pump provides a power source for the hydraulic actuator of the hydraulic system of the construction machinery; the hydraulic valves control the movement of the hydraulic actuator; and the hydraulic circuit is a hydraulic pipeline connecting the hydraulic pump, the hydraulic valves, and the hydraulic actuator.

[0046] The engine module is used to provide a power source for the construction machinery and to provide power input to the hydraulic pump;

[0047] The ISG motor is used to provide a power source for the construction machinery, provide power input to the hydraulic pump, and absorb excess energy from the engine module to charge the battery;

[0048] The control module includes an engine control unit, an ISG motor control unit, a hydraulic system control unit, and a coordination control unit. The engine control unit controls the engine to respond to operator changes in speed or torque. The ISG motor control unit controls the ISG motor to respond to operator changes in speed or torque. The hydraulic system control unit controls the on / off state of the hydraulic system according to operator commands. The coordination control unit is used for power or torque distribution between the engine module and the ISG motor module, and for coordinated control of the engine module, the ISG motor module, and the hydraulic system.

[0049] The operating device is a mechanism used by the driver to operate the excavator, including a travel operating mechanism, a slewing operating mechanism, and a work operating handle.

[0050] Thirdly, the present invention discloses a hybrid power engineering machinery control device based on work load identification, comprising:

[0051] The calculation module is used for:

[0052] The driver's target torque is calculated based on the obtained handle opening degree and opening change rate;

[0053] Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery.

[0054] The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque.

[0055] The fuzzy control module is used to determine the engine target torque and ISG motor target torque based on the fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, and according to the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC.

[0056] The control module is used to control the hydraulic pump pressure by utilizing the target torque of the engine and the target torque of the ISG motor.

[0057] Fourthly, the present invention discloses a computer-readable storage medium for storing one or more programs, characterized in that the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the method of the first aspect.

[0058] Fifthly, the present invention discloses a computer device, characterized in that it comprises:

[0059] One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing the method of the first aspect.

[0060] The beneficial effects achieved by this invention are as follows:

[0061] The control method of this invention enables dynamic adjustment of the target torque of the engine and ISG motor based on the driver's target torque, the predicted value of the operating system, and the battery's state of charge (SOC), thus solving the problem of slow response speed of the engine and ISG motor. This invention considers the issue of work load lag. A work load prediction model is built using Markov logic to predict the work load at future moments. To avoid excessively low prediction accuracy, the driver's target torque and the difference between the two are introduced. A fuzzy controller for engine and ISG motor torque distribution is built considering the battery's SOC state to dynamically adjust the target torque of the engine and ISG motor. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the modules of the hybrid excavator control system based on work load identification of the present invention;

[0063] Figure 2 This invention relates to a hybrid excavator workload allocation method based on workload identification. - - Fuzzy rule graph

[0064] Figure 3 This invention relates to a hybrid excavator workload allocation method based on workload identification. - - Fuzzy rule graph

[0065] Figure 4 This invention relates to a hybrid excavator workload allocation method based on workload identification. - - Fuzzy rule graph

[0066] Figure 5 This invention relates to a hybrid excavator workload allocation method based on workload identification. - - Fuzzy rule graph. Detailed Implementation

[0067] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0068] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0069] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0070] Example 1: This example introduces a control method for hybrid power construction machinery based on work load identification, including:

[0071] The driver's target torque is calculated based on the obtained handle opening degree and opening change rate;

[0072] Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery.

[0073] The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque.

[0074] Based on the fuzzy control algorithm, considering the optimal fuel consumption torque range of the engine and the optimal efficiency torque range of the ISG motor, the target torque of the engine and the target torque of the ISG motor are determined according to the difference between the driver's target torque, the driver's target torque and the hydraulic pump's predicted torque, and the battery's SOC.

[0075] The hydraulic pump pressure is controlled by using the target torque of the engine and the target torque of the ISG motor.

[0076] The step of calculating the driver's target torque based on the acquired handle opening degree and opening change rate includes:

[0077] Collect the lever opening degree k and the rate of change of opening degree operated by the driver. By the handle opening degree k and the rate of change of opening degree Calculate the driver's target torque.

[0078] The step of predicting the hydraulic pump pressure at a target time based on the currently collected hydraulic pump pressure includes:

[0079] The pressure sets of the regulating hydraulic pump under various operating conditions are collected. Outliers are removed from the pressure sets, and the pressure distribution of the pressure sets after outlier removal is statistically analyzed to obtain the overall pressure range [0, ]. p max ], p max This indicates the maximum pressure of the hydraulic pump;

[0080] The overall pressure range is [0, p max Based on the difference of discrete intervals Divided into n Discrete intervals, hydraulic pump pressure p Represented as:

[0081]

[0082] The pressure distribution is as follows:

[0083]

[0084] In the formula, Indicates the first i The states corresponding to each discrete interval i= 1,2,3,…, n ;

[0085] Based on the defined pressure distribution states, the transition probabilities between states are calculated, and the statistics for any given state are statistically analyzed. After a change, it transitions to another state. The probability is calculated by Transferred to The transition probability is ;

[0086] After calculating all state transition probabilities, the state transition probability matrix is ​​composed of all state transition probabilities. P For the Markov chain operation load prediction model, the predicted hydraulic pump pressure at the next moment is obtained from the Markov chain operation load prediction model based on the currently collected hydraulic pump pressure.

[0087]

[0088] State transition probability matrix P It satisfies the following properties:

[0089] .

[0090] The expression for calculating the predicted hydraulic pump torque at the target time based on the predicted hydraulic pump pressure at the target time is as follows:

[0091] In the formula: T Predict the hydraulic pump torque at the target time; p f Predict the hydraulic pump pressure at the target time; V This refers to the displacement of the hydraulic pump. η This refers to the volumetric efficiency of the hydraulic pump.

[0092] The expression for the difference between the driver's target torque and the hydraulic pump's predicted torque is as follows:

[0093]

[0094] In the formula: Δ is the difference between the driver's target torque and the hydraulic pump's predicted torque. T t For the driver's target torque, T Predict the hydraulic pump torque at the target time.

[0095] The fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, determines the engine's target torque and the ISG motor's target torque based on the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC. This includes:

[0096] Driver target torque The fuzzy subset is defined as The corresponding language variable is ;

[0097] The difference between the driver's target torque and the hydraulic pump's predicted torque The fuzzy subset is defined as The corresponding language variable is ;

[0098] Define the fuzzy subset of battery SOC as The corresponding language variable is ;

[0099] engine target torque The fuzzy subset is defined as The corresponding language variable is ;

[0100] The target torque of the ISG motor The fuzzy subset is defined as The corresponding language variable is ;

[0101] Based on engine target torque The difference between the driver's target torque and the hydraulic pump's predicted torque Different subsets of SOC define dynamic adjustment of engine target torque and ISG motor target torque The specific rules are as follows:

[0102] (1) When SOC is in or When a subset is selected, the fuzzy controller determines that the ISG motor should be in generating state, and its torque is... or Subset, rapid compensation of battery power, engine target torque Should be in or The subset must satisfy both the overall vehicle load and the ISG motor's generating torque.

[0103] (2) When SOC is in or At that time, the fuzzy controller determines the target torque of the engine. The difference between the driver's target torque and the hydraulic pump's predicted torque Determine the target torque of the engine by its subset. and ISG motor target torque .when When the value is negative, it means the current predicted value is less than the driver's target torque. In this case, the ISG motor torque should be increased to meet the driver's torque requirements. A positive value indicates that the predicted torque is greater than the driver's target torque, and the ISG motor torque should be reduced in this case. The difference between the driver's target torque and the hydraulic pump's predicted torque is used to calculate this. The magnitude of the target torque of the ISG motor is adjusted to optimize the prediction model.

[0104] The specific fuzzy control rules are shown in Table 1:

[0105] Table 1

[0106] ;

[0107] ;

[0108]

[0109] Example 2, based on the same inventive concept as Example 1, introduces a hybrid excavator control method based on work load identification, including a work load calculation module, a work load prediction module, and a work load allocation module;

[0110] (1) Job load prediction module:

[0111] The job load prediction model is based on Markov chains. The steps of a Markov prediction model generally consist of data sample collection, discretization processing, state transition probability calculation, and state transition probability matrix calculation.

[0112] a. Data acquisition and processing:

[0113] Data on the operating load of the hydraulic pump under various working conditions is collected. The collected sample data is used as historical data. First, the pressure data is analyzed. Preprocessing is performed to remove outliers and to calculate stress. Distribution.

[0114] b. Data discretization processing:

[0115] Assume the pressure range of the sample data is [0, p max The sample data is discretized, dividing the pressure into different pressure ranges. The discrete range is... Divide the sample data into nThe discrete intervals are shown below:

[0116]

[0117] That is, the state of the sample data is determined as follows:

[0118]

[0119] c. Calculation of state transition probability:

[0120] Based on the defined states, the transition probabilities between states are calculated, and the statistics for any given state are statistically analyzed. After a change, it transitions to another state. The probability (i.e., the one-step state transition probability) is calculated by... Transferred to The transition probability is For example, by pressure range Jump to the pressure zone The probability is 0.2, then ;

[0121] .

[0122] d. Calculation of the state transition probability matrix:

[0123] After calculating all state transition probabilities, the transition probability matrix is ​​composed of all state transition probabilities. This constitutes the required Markov chain work load prediction model. The predicted pressure for the next time step can be obtained from the state transition probability matrix based on the current real-time pressure of the hydraulic pump.

[0124]

[0125] The state transition probability matrix P satisfies the following property:

[0126]

[0127] e. Stress prediction:

[0128] At time t, the real-time pressure of the hydraulic pump is... The input is fed into the job load prediction model, which calculates the predicted load at time t+1 based on the state probability transition matrix, i.e.:

[0129] .

[0130] (2) Workload Calculation Module:

[0131] a. Target torque calculation:

[0132] Target torque calculation refers to collecting data on the opening degree of the joystick operated by the driver. By adjusting the handle opening and its rate of change Calculate the driver's target torque.

[0133] .

[0134] b. Predicted torque calculation:

[0135] Predictive torque calculation refers to calculating the required torque of a hydraulic pump by using information such as the pump's mechanical efficiency and displacement. The calculation formula is shown below.

[0136] ;

[0137] In the formula: The predicted torque of the hydraulic pump; The predicted load output by the job load prediction module; This refers to the displacement of the hydraulic pump. This refers to the volumetric efficiency of the hydraulic pump.

[0138] c. Torque difference calculate:

[0139] Torque difference The difference between the driver's target torque and the hydraulic pump's predicted torque is used as the basis for torque allocation by the work responsibility allocation module. Its calculation formula is as follows:

[0140] .

[0141] (3) Job load distribution module:

[0142] The workload distribution module is mainly used for torque distribution between the engine and the ISG motor, to achieve the driver's target torque. Torque difference Using battery SOC as input and engine target torque and ISG motor target torque as output, a fuzzy controller is designed using a fuzzy control algorithm to calculate the engine target torque in real time. and ISG motor target torque .

[0143] The input variable for the fuzzy control algorithm is the driver's target torque. Torque difference And battery SOC, the output variables are engine target torque and ISG motor target torque. The driver target torque... The fuzzy subset is defined as The corresponding language variable is ; to torque difference The fuzzy subset is defined as The corresponding language variable is Define the fuzzy subset of battery SOC as The corresponding language variable is ; to achieve the target torque of the engine The fuzzy subset is defined as The corresponding language variable is ; to achieve the target torque of the ISG motor The fuzzy subset is defined as The corresponding language variable is The established fuzzy control rules are as follows: Figures 2-5 As shown.

[0144] The engine target torque output by the fuzzy controller and ISG motor target torque The torque command is used to drive the hydraulic pump together, which in turn adjusts the hydraulic pump pressure in real time, serving as the torque command for both the engine model and the ISG motor model.

[0145] Example 3, based on the same inventive concept as other examples, introduces a hybrid excavator control system based on work load identification, including an engine module, an ISG motor module, a hydraulic system, an operating device, and a control module.

[0146] The engine is the power source for the excavator and provides power input to the hydraulic pump;

[0147] The ISG motor is the power source for the excavator. In addition to providing power input to the hydraulic pump, it can also act as a generator to absorb the excess energy of the engine.

[0148] The hydraulic system includes a hydraulic pump, hydraulic valves, hydraulic actuators, and hydraulic circuits. The hydraulic pump is the power source of the excavator's hydraulic system, providing power for the excavator's overall operation. The hydraulic valves are the control elements of the excavator's hydraulic system, used to control the actions of the hydraulic actuators. The hydraulic actuators are the actuators that control the actions of various mechanisms within the excavator. The hydraulic circuits are the hydraulic lines connecting the hydraulic pump, the hydraulic valves, and the hydraulic actuators, used for the transmission of hydraulic oil.

[0149] The control module includes engine control, ISG motor control, hydraulic system control, and coordination control. Engine control refers to the engine responding to operator-initiated speed or torque changes; ISG motor control refers to the ISG motor responding to operator-initiated speed or torque changes; hydraulic system control refers to the control module controlling the on / off state of the hydraulic system according to operator commands to achieve overall vehicle operation control; coordination control refers to the power or torque distribution between the engine and the ISG motor, as well as the coordinated control of the engine, ISG motor, and hydraulic system.

[0150] The operating device refers to the mechanism used by the driver to operate the excavator, including the traveling operating mechanism, the slewing operating mechanism, and the working operating handle.

[0151] Example 4, based on the same inventive concept as other examples, introduces a hybrid power construction machinery control device based on work load identification, comprising:

[0152] The calculation module is used for:

[0153] The driver's target torque is calculated based on the obtained handle opening degree and opening change rate;

[0154] Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery.

[0155] The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque.

[0156] The fuzzy control module is used to determine the engine target torque and ISG motor target torque based on the fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, and according to the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC.

[0157] The control module is used to control the hydraulic pump pressure by utilizing the target torque of the engine and the target torque of the ISG motor.

[0158] Example 5, based on the same inventive concept as other examples, describes a computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform the method described in Example 1.

[0159] Example 6, based on the same inventive concept as other examples, describes a computer device, including,

[0160] One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing the method described in Embodiment 1.

[0161] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0162] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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, generate instructions 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.

[0163] 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.

[0164] 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.

[0165] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A control method for hybrid power construction machinery based on work load identification, characterized in that, include: The driver's target torque is calculated based on the obtained handle opening degree and opening change rate; Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery. The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque. Based on the fuzzy control algorithm, considering the optimal fuel consumption torque range of the engine and the optimal efficiency torque range of the ISG motor, the target torque of the engine and the target torque of the ISG motor are determined according to the difference between the driver's target torque, the driver's target torque and the hydraulic pump's predicted torque, and the battery's SOC. The hydraulic pump pressure is controlled by combining the target torque of the engine and the target torque of the ISG motor. The step of predicting the hydraulic pump pressure at a target time based on the currently collected hydraulic pump pressure includes: The pressure sets of the regulating hydraulic pump under various operating conditions are collected. Outliers are removed from the pressure sets, and the pressure distribution of the pressure sets after outlier removal is statistically analyzed to obtain the overall pressure range [0, ]. p max ], p max This indicates the maximum pressure of the hydraulic pump; The overall pressure range is [0, p max Based on the difference of discrete intervals Divided into n Discrete intervals, hydraulic pump pressure p Represented as: ； The state of the pressure distribution is as follows: ； In the formula, Indicates the first i The states corresponding to each discrete interval i= 1,2,3,…, n ; Based on the defined pressure distribution states, the transition probabilities between states are calculated, and the statistics for any given state are statistically analyzed. After a change, it transitions to another state. The probability is calculated by Transferred to The transition probability is ; After calculating all state transition probabilities, the state transition probability matrix is ​​composed of all state transition probabilities. P For the Markov chain operation load prediction model, the predicted hydraulic pump pressure at the next moment is obtained from the Markov chain operation load prediction model based on the currently collected hydraulic pump pressure. ； State transition probability matrix P It satisfies the following properties: 。 2. The hybrid power engineering machinery control method based on work load identification according to claim 1, characterized in that, The step of calculating the driver's target torque based on the acquired handle opening degree and opening change rate includes: Collect the lever opening degree k and the rate of change of opening degree operated by the driver. By the handle opening degree k and the rate of change of opening degree Calculate the driver's target torque.

3. The hybrid power engineering machinery control method based on work load identification according to claim 1, characterized in that, The expression for calculating the predicted hydraulic pump torque at the target time based on the predicted hydraulic pump pressure at the target time is as follows: ； In the formula: T Predict the hydraulic pump torque at the target time; p f Predict the hydraulic pump pressure at the target time; V This refers to the displacement of the hydraulic pump. η This refers to the volumetric efficiency of the hydraulic pump.

4. The hybrid power engineering machinery control method based on work load identification according to claim 1, characterized in that, The expression for the difference between the driver's target torque and the hydraulic pump's predicted torque is as follows: ； In the formula: Δ is the difference between the driver's target torque and the hydraulic pump's predicted torque. T t For the driver's target torque, T Predict the hydraulic pump torque at the target time.

5. The hybrid power engineering machinery control method based on work load identification according to claim 1, characterized in that, The fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, determines the engine's target torque and the ISG motor's target torque based on the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC. This includes: Set the driver's target torque The fuzzy subset and the corresponding driver target torque The first linguistic variable of each element in the fuzzy subset; Set the driver's target torque The difference between the predicted torque and the hydraulic pump torque The fuzzy subset and the corresponding difference The second linguistic variable of the elements in the fuzzy subset; Set the fuzzy subset of the battery SOC and the third linguistic variable for each element in the corresponding fuzzy subset of the battery SOC; Set engine target torque Fuzzy subsets and corresponding engine target torque The fourth linguistic variable for each element in the fuzzy subset; Set the target torque for the ISG motor Fuzzy subsets and corresponding target torque of ISG motors The fifth linguistic variable for each element in the fuzzy subset; Construct fuzzy control rules based on first language variables, second language variables, third language variables, fourth language variables, and fifth language variables; Based on the constructed fuzzy control rules, when the battery SOC is lower than the preset charge level, the target torque of the ISG motor is controlled. The value of makes the target torque of the ISG motor... The value is such that it can simultaneously meet the vehicle load and the ISG motor power generation requirements; According to the constructed fuzzy control rules, when the battery SOC is not lower than the preset charge level, the target torque of the driver is determined. The difference between the predicted torque and the hydraulic pump torque The subset to which it belongs determines the engine target torque and ISG motor target torque .

6. A system based on the hybrid power engineering machinery control method based on work load identification as described in any one of claims 1-5, characterized in that, include: Engine module, ISG motor module, hydraulic system, operating device and control module; The hydraulic system includes a hydraulic pump, hydraulic valves, a hydraulic actuator, and a hydraulic circuit; the hydraulic pump provides a power source for the hydraulic actuator of the hydraulic system of the construction machinery; the hydraulic valves control the movement of the hydraulic actuator; and the hydraulic circuit is a hydraulic pipeline connecting the hydraulic pump, the hydraulic valves, and the hydraulic actuator. The engine module is used to provide a power source for the construction machinery and to provide power input to the hydraulic pump; The ISG motor is used to provide a power source for the construction machinery, provide power input to the hydraulic pump, and absorb excess energy from the engine module to charge the battery; The control module includes an engine control unit, an ISG motor control unit, a hydraulic system control unit, and a coordination control unit. The engine control unit controls the engine to respond to operator changes in speed or torque. The ISG motor control unit controls the ISG motor to respond to operator changes in speed or torque. The hydraulic system control unit controls the on / off state of the hydraulic system according to operator commands. The coordination control unit is used for power or torque distribution between the engine module and the ISG motor module, and for coordinated control of the engine module, the ISG motor module, and the hydraulic system. The operating device is a mechanism used by the driver to operate the excavator, including a travel operating mechanism, a slewing operating mechanism, and a work operating handle.

7. A hybrid power engineering machinery control device based on work load identification, characterized in that, include: The calculation module is used for: The driver's target torque is calculated based on the obtained handle opening degree and opening change rate; Based on the currently collected hydraulic pump pressure, the predicted hydraulic pump pressure at the target time is predicted, and the predicted hydraulic pump torque at the target time is calculated based on the predicted hydraulic pump pressure at the target time. The hydraulic pump is used to provide a power source for the hydraulic actuator of the hydraulic system of the construction machinery. The difference between the driver's target torque and the hydraulic pump's predicted torque is calculated based on the driver's target torque and the hydraulic pump's predicted torque. The fuzzy control module is used to determine the engine target torque and ISG motor target torque based on the fuzzy control algorithm, considering the engine's optimal fuel consumption torque range and the ISG motor's optimal efficiency torque range, and according to the difference between the driver's target torque, the hydraulic pump's predicted torque, and the battery's SOC. The control module is used to jointly control the hydraulic pump pressure using the target torque of the engine and the target torque of the ISG motor; The step of predicting the hydraulic pump pressure at a target time based on the currently collected hydraulic pump pressure includes: The pressure sets of the regulating hydraulic pump under various operating conditions are collected. Outliers are removed from the pressure sets, and the pressure distribution of the pressure sets after outlier removal is statistically analyzed to obtain the overall pressure range [0, ]. p max ], p max This indicates the maximum pressure of the hydraulic pump; The overall pressure range is [0, p max Based on the difference of discrete intervals Divided into n Discrete intervals, hydraulic pump pressure p Represented as: ； The state of the pressure distribution is as follows: ； In the formula, Indicates the first i The states corresponding to each discrete interval i= 1,2,3,…, n ; Based on the defined pressure distribution states, the transition probabilities between states are calculated, and the statistics for any given state are statistically analyzed. After a change, it transitions to another state. The probability is calculated by Transferred to The transition probability is ; After calculating all state transition probabilities, the state transition probability matrix is ​​composed of all state transition probabilities. P For the Markov chain operation load prediction model, the predicted hydraulic pump pressure at the next moment is obtained from the Markov chain operation load prediction model based on the currently collected hydraulic pump pressure. ； State transition probability matrix P It satisfies the following properties: 。 8. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1 to 5.

9. A computer device, characterized in that, include, One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing the method of any of claims 1 to 5.

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