Cooperative control method and system for hydraulic system and engine of bulldozer

Abstract

The invention discloses a cooperative control method and system for a bulldozer hydraulic system and an engine, and belongs to the field of engineering machinery. The method comprises the steps that the minimum ratio of the fuel consumption rate of an engine to the working efficiency of a hydraulic pump serves as a target condition, an optimized target function is obtained in combination with the target condition, a bulldozer whole vehicle transmission formula and universal characteristics, and instantaneous optimization is conducted in an engine rotating speed optimization interval through a particle swarm optimization algorithm; the optimal engine rotating speed and the optimal hydraulic pump motor displacement ratio are obtained; wherein the engine rotating speed optimization interval is a range from the minimum engine rotating speed to the maximum engine rotating speed. According to the method, the engine oil consumption rate and the working efficiency of the hydraulic pump are comprehensively considered, the engine rotating speed and the displacement ratio of the hydraulic pump and the hydraulic motor are optimized at the same time, and the particle swarm optimization is adopted for instantaneous optimization, so that the optimal result is quickly and accurately optimized on the basis of meeting the working requirements of the bulldozer, the whole vehicle operation oil consumption is greatly reduced, and the working efficiency of the bulldozer is improved. And the operation economy of the whole vehicle is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical engineering, and in particular to a coordinated control method and system of a bulldozer hydraulic system and an engine. Background Art

[0002] The engines matched with the current hydraulic closed system bulldozers are all controlled by calibrating a fixed engine speed. Therefore, when the bulldozer is working in a stable walking condition, the engine speed also runs at a fixed speed according to the knob operated by the driver, and cannot work at the optimal economic point of the engine speed, resulting in low efficiency, high fuel consumption and poor economy.

[0003] For example, CN116906198A discloses a speed control method, device, equipment and medium for a roller engine, the method comprising: when the current working condition of the roller engine is a stable working condition, obtaining the current actual torque of the engine; and obtaining the current actual power and the current load rate according to the current actual torque; when the current load rate is less than the first load rate, calculating the first engine speed corresponding to the engine when the displacement ratio of the travel system is the largest under the current set vehicle speed; calculating the second engine speed corresponding to the engine when the displacement ratio of the vibration system is the largest under the current set vibration frequency; and obtaining the third engine speed corresponding to the second load rate based on the engine equal power curve corresponding to the current actual power; obtaining the engine speed with the lowest fuel consumption value between the current set engine speed and the maximum engine speed among the three. Under stable working conditions, the engine speed has the lowest fuel consumption and high efficiency on the basis of meeting the current power demand. This scheme is limited by the final speed of the engine under stable working conditions, and the optimal point may be higher than the final speed and therefore cannot be found.

[0004] For example, WO2025001862A1 discloses a fuel consumption self-optimization control method, device and operating machinery, the method comprising: obtaining multiple actual operating points of the engine in the current gear within a preset time; determining the concentrated operating point of the engine based on the speed detection value and torque detection value of each actual operating point; determining the target fuel consumption area of ​​the engine based on the preset fuel consumption model and the speed detection value and torque detection value of each actual operating point, and determining the fuel consumption corresponding to the concentrated operating point based on the preset fuel consumption model; if the fuel consumption corresponding to the concentrated operating point does not meet the target fuel consumption area, determining the candidate speed of the engine based on the target fuel consumption area, and determining the target speed of the engine based on the candidate speed and the maximum power point among the multiple actual operating points. This solution can only find the optimal fuel consumption area to ensure that the engine works under the premise of meeting the current working conditions of the engine, and does not take into account the impact of the hydraulic pump on the system.

[0005] For another example, CN114263083A discloses a road roller energy-saving control method, system and road roller, wherein the control method includes: monitoring the real-time driving speed of the road roller when the road roller is statically pressed; based on the correspondence between the preset first driving speed interval and the engine speed, adjusting the engine to the corresponding speed according to the first driving speed interval into which the real-time driving speed falls. This is used to solve the defects of the prior art that the engine of the road roller is always kept at the highest speed, resulting in low load rate, high fuel consumption and high noise. Although this solution enables the engine of the road roller to work in the optimal fuel consumption area and reduces the fuel consumption of the road roller, it seeks the correspondence between the preset first driving speed interval and the engine speed when the road roller is statically pressed, which is different from the vehicle transmission formula used in this bulldozer.

[0006] When the bulldozer is operating in bulldozing conditions, the working conditions are complex, the load is large, and the power demand is large. At this time, it is difficult to simultaneously meet the economy and power of the vehicle by only considering the adjustment of the engine system. Therefore, it is also necessary to synchronously adjust the hydraulic unit to improve the working efficiency of the hydraulic pump, so as to optimize the economy of the vehicle while meeting the power of the vehicle. It can be seen that it is urgent to develop a control method for the coordination of the engine and the hydraulic system, while considering the universal characteristics of the engine and the working efficiency of the hydraulic unit, to solve the current defects and deficiencies. Summary of the invention

[0007] In view of this, the main purpose of the present invention is to provide a method and system for coordinated control of a bulldozer hydraulic system and an engine, in order to at least partially solve the above technical problems.

[0008] While optimizing the engine fuel consumption, it also optimizes the working efficiency of the hydraulic unit, thereby improving the operating economy of the entire vehicle and reducing the operating cost of the entire vehicle.

[0009] In order to achieve the above object, as a first aspect of the present invention, a method for coordinated control of a bulldozer hydraulic system and an engine is proposed, comprising the following steps:

[0010] Collect bulldozer operation data;

[0011] Setting constraint conditions according to the operating data, taking the ratio of the engine fuel consumption rate to the hydraulic pump working efficiency as the minimum as the target condition, so that the optimization objective function pre-constructed by combining the target condition, the bulldozer vehicle transmission formula and the universal characteristics satisfies the constraint conditions;

[0012] A particle swarm algorithm is used to perform instantaneous optimization within the engine speed optimization range to obtain the optimal engine speed and the optimal hydraulic pump motor displacement ratio, and the corresponding parameters are controlled in real time to achieve coordinated control of the bulldozer hydraulic system and the engine; wherein the engine speed optimization range is the range from the minimum engine speed to the maximum engine speed.

[0013] As a second aspect of the present invention, a coordinated control system of a bulldozer hydraulic system and an engine is also proposed, comprising:

[0014] A data collection unit, used for collecting operation data of the bulldozer;

[0015] an optimization constraint condition setting unit, configured to set constraint conditions of the optimization objective function based on the operation data collected by the data collection unit, and transmit the constraint conditions to the particle swarm algorithm optimization unit; and

[0016] The particle swarm algorithm optimization unit is used to optimize the engine speed and the hydraulic pump motor displacement ratio by using the above-mentioned coordinated control method of the bulldozer hydraulic system and the engine.

[0017] Based on the above technical solution, it can be seen that the method and system for coordinated control of the bulldozer hydraulic system and the engine of the present invention have at least one of the following beneficial effects compared with the prior art:

[0018] 1. Optimize the setting of the objective function, taking into account the engine system and the hydraulic unit at the same time. The optimization target needs to be combined with the universal characteristics of the engine matching and the transmission principle of the hydraulic unit to ensure the rationality and accuracy of the optimization target;

[0019] 2. Setting of constraints: Relevant constraints must be met during the optimization process to ensure that the stable operating conditions of the vehicle are not destroyed and the required power can be met;

[0020] 3. Use the particle swarm algorithm to instantly find the best result, quickly and accurately optimize the best result on the basis of meeting the working requirements of the bulldozer, reduce the fuel consumption of the whole vehicle, and improve the economic efficiency of the whole vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 It is a schematic diagram of the engine universal characteristic curve of the cooperative control method of the bulldozer hydraulic system and the engine of the present invention. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0024] The terms used in the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0025] The inventor found that when the bulldozer is operating in a bulldozing condition, the working conditions are complex, the load is large, and the power demand is large. At this time, it is difficult to simultaneously meet the economy and power of the whole vehicle by only considering the adjustment of the engine system. Therefore, it is also necessary to synchronously adjust the hydraulic unit to improve the working efficiency of the hydraulic pump, so as to optimize the economy of the whole vehicle while meeting the power of the whole vehicle. After in-depth research, it was found that based on the bulldozer hydraulic transmission principle and the bulldozer operating conditions, the engine fuel consumption rate and the working efficiency of the hydraulic unit were considered at the same time, and the engine speed and the hydraulic pump motor displacement ratio were optimized at the same time, and the particle swarm algorithm was used for instant optimization, so as to achieve the best result on the basis of meeting the working needs of the bulldozer, reduce the fuel consumption of the whole vehicle, and improve the economy of the whole vehicle.

[0026] The bulldozer is mainly controlled for walking control and bulldozing work control. The bulldozer has a large load and the engine speed fluctuates greatly during bulldozing work. Therefore, this working condition is not suitable for finding the optimal speed based on the universal characteristics of the engine. When the bulldozer is in walking condition, the working condition is stable, and the engine load rate and required output power are reduced. At this time, the engine speed can be reduced, the displacement ratio of the hydraulic pump and hydraulic motor can be increased, and the efficiency of the hydraulic pump can be improved. Finding the optimal point on the equal power curve can meet the power demand for stable work and reduce working fuel consumption at the same time.

[0027] Therefore, the inventor proposes a method for coordinated control of a bulldozer hydraulic system and an engine, comprising the following steps:

[0028] Collect bulldozer operation data;

[0029] According to the above operating data, constraint conditions are set, and the ratio of the engine fuel consumption rate to the hydraulic pump working efficiency is minimized as the target condition, so that the optimization objective function pre-constructed by combining the above target conditions, the bulldozer vehicle transmission formula and the universal characteristics satisfies the above constraint conditions;

[0030] A particle swarm algorithm is used to perform instantaneous optimization within the engine speed optimization range to obtain the optimal engine speed and the optimal hydraulic pump motor displacement ratio, and the corresponding parameters are controlled in real time to achieve coordinated control of the bulldozer hydraulic system and the engine; wherein the engine speed optimization range is the range from the minimum engine speed to the maximum engine speed; the optimization accuracy is high and the optimization speed is fast.

[0031] Figure 1 It is a schematic diagram of the engine universal characteristic curve, such as Figure 1 As shown, the horizontal axis is the engine speed, the vertical axis is the engine torque, the dotted line part is the equal power curve, the solid line part is the equal fuel consumption curve, and the top is the external characteristic curve.

[0032] Among them, the optimization objective function satisfies the following constraints at the same time:

[0033] The difference between the required vehicle speed and the actual vehicle speed is less than the first threshold; the required engine speed and the actual engine speed are less than the second threshold; the required motor speed and the actual motor speed are less than the third threshold; the output power is greater than or equal to the required power; and the engine load rate is less than 90%.

[0034] The engine load factor is preferably obtained by calculating the ratio of the required torque under stable operating conditions to the maximum torque at the current required engine speed.

[0035] The actual vehicle speed, the actual engine speed and the actual motor speed are preferably acquired through a data acquisition unit.

[0036] Furthermore, the transmission formula of the bulldozer is as follows: ,in, Expressed as the hydraulic pump-motor displacement ratio, Expressed as vehicle speed, Expressed as the transmission ratio from the engine to the hydraulic pump, Expressed as the transmission ratio from motor to wheel, Expressed as wheel radius, Expressed as the hydraulic pump efficiency, Expressed as engine speed.

[0037] The expression of the optimization objective function is as follows: ,in, Expressed as the objective function, Indicates the engine speed is The actual torque is The corresponding engine fuel consumption rate.

[0038] From the above formula, we can see that the efficiency of the hydraulic pump is mainly related to the engine speed, the displacement ratio of the hydraulic pump and the hydraulic motor, and the pressure difference. When the engine speed decreases, the mechanical efficiency of the hydraulic pump will increase. At the same time, when the engine speed is stable, the greater the displacement ratio of the hydraulic pump and the hydraulic motor, the higher the mechanical efficiency and volumetric efficiency of the hydraulic pump. Therefore, under the condition of meeting the power matching requirements, reducing the engine speed and increasing the displacement ratio of the hydraulic pump and the hydraulic motor can make the hydraulic pump more efficient.

[0039] The required torque is preferably obtained by collecting several actual torques of the engine under stable operating conditions and calculating the average value.

[0040] The required power is preferably calculated by combining the required torque with the current required engine speed using the following formula: ,

[0041] In the formula, The engine power requirement is The engine demands torque.

[0042] The minimum engine speed is preferably calculated based on the bulldozer vehicle transmission formula when the hydraulic pump motor displacement ratio is maximum and the hydraulic pump operating efficiency is maximum.

[0043] The specific optimization process is as follows:

[0044] (1) Data collection: When the vehicle is running normally, the actual engine speed, actual travel motor speed, actual vehicle speed, actual torque and other data are collected first.

[0045] (2) Calculation of required torque and required power: When the operating conditions are stable, the actual engine torque within a certain time range is collected and the average is calculated as the required torque. The required power is obtained by combining the current set engine speed with the power formula;

[0046] (3) Calculation of engine load rate: The load rate under the stable operating condition is obtained by dividing the required torque under the above stable operating condition by the maximum torque under the current set speed;

[0047] (4) Calculation of minimum engine speed when displacement ratio is maximum: Calculate the minimum engine speed that can meet the current required vehicle speed when the hydraulic pump and hydraulic motor displacement ratio is maximum and the hydraulic pump efficiency is maximum based on the bulldozer vehicle transmission formula;

[0048] (5) Setting of optimization constraints: In order to ensure that the optimized results meet the vehicle power requirements and stable operation, the following constraints must be met when optimizing the objective function: the difference between the required vehicle speed and the actual vehicle speed is less than the first threshold; the required engine speed and the actual engine speed are less than the second threshold; the motor required speed and the actual speed are less than the third threshold; the output power is greater than or equal to the required power; the engine load rate is less than 90%; in order to meet the maximum engine operating capacity and better balance the engine's optimal fuel consumption rate and the hydraulic pump's optimal working efficiency, the engine speed optimization range must be greater than or equal to the minimum engine speed and less than or equal to the maximum engine speed.

[0049] (6) Set the particle swarm optimization parameters: call the particle swarm optimization algorithm and set the number of particles, maximum number of iterations, inertia weight, and acceleration constant of the particle swarm algorithm;

[0050] (7) Result output: The optimal engine set speed and the optimal hydraulic pump-to-hydraulic motor displacement ratio that meet the conditions are optimized and output through the particle swarm algorithm.

[0051] In a preferred embodiment, the present invention further discloses a coordinated control system of a bulldozer hydraulic system and an engine, comprising:

[0052] A data acquisition unit, used to collect data of actual vehicle speed, actual engine speed and actual motor speed and transmit the data to the particle swarm algorithm optimization unit;

[0053] The actual vehicle speed is obtained through the wheel speed collected by the vehicle wheel speed sensor, and the required vehicle speed is calculated according to the opening of the handle. The actual engine speed is obtained through the engine motor speed sensor, and the required engine speed is obtained according to the rotation angle of the throttle knob. The actual motor speed is obtained through the speed sensor on the motor.

[0054] An optimization constraint condition setting unit is used to set the constraint conditions of the optimization objective function and transmit the constraint conditions to the particle swarm algorithm optimization unit;

[0055] The particle swarm algorithm optimization unit is used to optimize the engine speed and the hydraulic pump motor displacement ratio by using the above-mentioned coordinated control method of the bulldozer hydraulic system and the engine.

[0056] The present invention will be further described below by specific embodiments. It should be noted that the following embodiments are only illustrative and are not intended to limit the present invention. Based on the embodiments of the present invention shown below, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present invention.

[0057] Example 1

[0058] When the vehicle is running normally, we need to collect some key data. Assume that we use sensors to obtain this data and collect the following actual data at a certain moment:

[0059] Actual engine speed ,

[0060] Actual speed of travel motor ,

[0061] Actual speed ,

[0062] Actual torque ,

[0063] When the working condition is stable, collect the actual torque data of the engine within a certain time range (for example, 10 seconds). Assume that the collected data is: , , ,……, .

[0064] Required torque is the average value of the actual torque during this period, and the calculation formula is: ;

[0065] in The number of collected data.

[0066] ,

[0067] The current required engine speed is assumed to be ,Will Substitute this formula , where The engine power requirement is is the engine torque requirement, Engine speed, required power .

[0068] Among them, the basic physical definition formula of power is (in Indicates power, Indicates work, Indicates time).

[0069] For the work done on a rotating object, ( is the torque, is the angle of rotation). In unit time, that is, considering the speed In the case of , the angle and speed have the following relationship:

[0070] We know the speed (The unit is usually revolutions per minute, i.e. ), and in one minute, the angle that the rotating object rotates (Units are radians: ), since one turn is radians, then the speed is (Rpm), the angle turned in one minute (here is the number of revolutions per minute).

[0071] So the merit (work per unit time, one minute), power , since we consider the time It's just one minute, so , at this time the power The unit is (Nm / min), because the commonly used unit of power in the International System of Units is Watt ( ), (Joule / second), and 1 minute = 60 seconds, 1 joule = (Nm), in order to change the power unit from Convert to (Watt), unit conversion is required.

[0072] Unit conversion to get coefficient (Unit: ), , The value is about 6.28. , further calculation , for the convenience of calculation, 9549 is usually taken (that is, The unit from Convert to ), so we have ( The unit is , The unit is , The unit is ).

[0073] Assuming the current set speed Maximum torque under .

[0074] Engine load rate under stable conditions is the ratio of required torque to maximum torque:

[0075] .

[0076] Based on the formula ,in, is the pump-motor displacement ratio, is the vehicle speed, is the transmission ratio from the engine to the hydraulic pump, is the gear ratio from motor to wheel, is the wheel radius, The working efficiency of the hydraulic pump is is the engine speed; then the minimum engine speed when the displacement ratio is maximum .

[0077] The difference between the required speed and the actual speed is less than the first threshold, which is set to 2. ;

[0078] The required engine speed and the actual engine speed are less than the second threshold, which is set to 100. .

[0079] The motor required speed and actual speed are less than the third threshold, which is set to 50. .

[0080] The output power is greater than or equal to the required power. ,Right now .

[0081] The engine load rate is less than 90%, that is .

[0082] Engine speed optimization range, preset maximum engine speed , then the engine speed optimization range is .

[0083] Particle swarm optimization is an optimization algorithm based on swarm intelligence. It simulates the group behavior of bird flocks or fish schools to find the optimal solution. Each particle represents a potential solution, flying in the search space, constantly adjusting its position based on its own experience and the experience of the group, and finally finding the optimal solution.

[0084] Next, we set the optimization parameters of the particle swarm algorithm. The number of particles determines the search range and search capability of the algorithm. Generally speaking, the more particles there are, the more likely the algorithm is to find the global optimal solution, but the amount of calculation will also increase accordingly. In this embodiment, the number of particles is set to ;

[0085] The maximum number of iterations limits the running time of the algorithm. When the maximum number of iterations is reached, the algorithm stops searching. In this embodiment, the maximum number of iterations is set to ;

[0086] The inertia weight is used to control the influence of the particle's previous velocity on the current velocity. A larger inertia weight is beneficial to global search, while a smaller inertia weight is beneficial to local search. In this embodiment, the inertia weight is set to ;

[0087] Acceleration constant and They are used to control the acceleration of the particle flying towards its own historical optimal position and the global optimal position, and the value is generally between 1.5 and 2.5. In this embodiment, the acceleration constant is set to .

[0088] The goal is to find the optimal engine speed setting and optimum hydraulic pump motor displacement , so that a certain objective function is minimized while satisfying the constraints. Assume that the objective function is:

[0089] ,in, is the weight coefficient, and According to the engine speed setting And displacement ratio The actual vehicle speed, actual travel motor speed, output power and engine load rate are calculated.

[0090] In each iteration, the speed and position of the particles are updated according to the update formula of the particle swarm algorithm, and the individual optimal position and the global optimal position are updated.

[0091] Particle velocity update formula: ;

[0092] The particle position update formula is:

[0093] ;in, Represents particles In the The speed of iterations, Represents particles In the The position of the iteration, Represents particles The individual optimal position of represents the global optimal position, and express A random number between .

[0094] go through After iterations, the global optimal position That is, the optimal engine set speed and the optimal hydraulic pump-motor displacement ratio required by this scheme.

[0095] Through the above steps, starting from data collection, the required torque, required power, engine load rate and minimum engine speed are calculated step by step, the optimization constraints are set, and then the particle swarm algorithm is used for optimization, and finally the optimal engine set speed and the optimal hydraulic pump motor displacement ratio that meet the conditions are obtained. In actual applications, the above calculation process and parameters need to be adjusted and optimized according to the specific vehicle and system characteristics.

[0096] This scheme comprehensively considers the two factors of engine fuel consumption rate and hydraulic unit working efficiency based on the bulldozer hydraulic transmission principle and bulldozer operating conditions, optimizes the engine speed and hydraulic pump hydraulic motor displacement ratio, and uses particle swarm algorithm for instantaneous optimization, so as to achieve fast and accurate optimization of the best result on the basis of meeting the working requirements of the bulldozer, greatly reducing the fuel consumption of the whole vehicle, thereby improving the operating economy of the whole vehicle.

[0097] The above describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0098] In the description of the embodiments of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In the embodiments of the present invention, the schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in the embodiments of the present invention and the features of the different embodiments or examples, without contradiction.

[0099] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the embodiments of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0100] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred implementation of the embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0101] In the several embodiments provided in the embodiments of the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0102] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0103] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for coordinated control of a bulldozer hydraulic system and an engine, characterized in that: The following steps are involved: Collect bulldozer operation data; Setting constraint conditions according to the operating data, taking the ratio of the engine fuel consumption rate to the hydraulic pump working efficiency as the minimum as the target condition, so that the optimization objective function pre-constructed by combining the target condition, the bulldozer vehicle transmission formula and the universal characteristics satisfies the constraint conditions; A particle swarm algorithm is used to perform instantaneous optimization within the engine speed optimization range to obtain the optimal engine speed and the optimal hydraulic pump motor displacement ratio, and the corresponding parameters are controlled in real time to achieve coordinated control of the bulldozer hydraulic system and the engine; wherein the engine speed optimization range is the range from the minimum engine speed to the maximum engine speed.

2. The collaborative control method according to claim 1, characterized in that: The constraints are as follows: The difference between the required vehicle speed and the actual vehicle speed is less than a first threshold value; wherein the required vehicle speed is calculated according to the opening degree of the handle; The required engine speed and the actual engine speed are less than a second threshold; wherein the required engine speed is obtained according to the rotation angle of the throttle knob; The required speed of the hydraulic pump motor and the actual speed of the motor are less than a third threshold value; wherein the required speed of the hydraulic pump motor is calculated based on the required vehicle speed; The output power is greater than or equal to the required power; The engine load factor is less than 90%.

3. The collaborative control method according to claim 2, characterized in that: The engine load rate is obtained by calculating the ratio of the required torque under stable working conditions to the maximum torque under the current required engine speed.

4. The collaborative control method according to claim 2, characterized in that: The operating data includes actual vehicle speed, actual engine speed and actual motor speed; the actual vehicle speed, actual engine speed and actual motor speed are all acquired through a data acquisition unit.

5. The collaborative control method according to claim 3, characterized in that: The transmission formula of the bulldozer vehicle is as follows: ,in, Expressed as the hydraulic pump-motor displacement ratio, Expressed as vehicle speed, Expressed as the transmission ratio from the engine to the hydraulic pump, Expressed as the transmission ratio from motor to wheel, Expressed as wheel radius, Expressed as the hydraulic pump efficiency, Expressed as engine speed.

6. The collaborative control method according to claim 5, characterized in that: The expression of the optimization objective function is as follows: ,in, Expressed as the objective function, Indicates the engine speed is The actual torque is The corresponding engine fuel consumption rate.

7. The collaborative control method according to claim 6, characterized in that: The required torque is obtained by collecting several actual torques of the engine under stable working conditions and calculating the average value.

8. The collaborative control method according to claim 6, characterized in that: The required power is calculated by combining the required torque with the current required engine speed through the following formula: ， In the formula, The engine power requirement is The engine demands torque.

9. The collaborative control method according to claim 1, characterized in that: The minimum engine speed is calculated according to the bulldozer vehicle transmission formula when the hydraulic pump motor displacement ratio is maximum and the hydraulic pump working efficiency is maximum.

10. A coordinated control system of a bulldozer hydraulic system and an engine, characterized in that: include: A data collection unit, used for collecting operation data of the bulldozer; An optimization constraint condition setting unit, used for setting the constraint conditions of the optimization objective function based on the operation data collected by the data collection unit, and transmitting the constraint conditions to the particle swarm algorithm optimization unit; as well as A particle swarm algorithm optimization unit is used to optimize the engine speed and the hydraulic pump motor displacement ratio by using the coordinated control method of the bulldozer hydraulic system and the engine as described in any one of claims 1 to 9.

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