Simulation method of electric drive system and engineering machinery

Abstract

The invention provides a simulation method of an electric drive system and engineering machinery. The simulation method comprises the steps that speed loop parameters, average given power and average output power of different responses of a motor controller under the fixed working condition are obtained, and the speed loop parameters meet preset parameter limitation; the speed loop parameter, the average given power and the average output power are simulated, multi-gradient speed loop parameters are obtained, and the multi-gradient speed loop parameters comprise a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; verifying the first multi-gradient velocity loop parameter and the second multi-gradient velocity loop parameter, and determining a target velocity loop parameter; and the target speed ring parameter is imported into the motor controller, so that the technical problem that the energy consumption of the electric drive system is difficult to actually improve is solved.

Description

Technical Field

[0001] The present application relates to the technical field of electric drive systems, and in particular to a simulation method and engineering machinery for electric drive systems. Background Art

[0002] At present, the requirements for emission pollution of non-road mobile engineering machinery are becoming increasingly stringent. Excavators, loaders, etc. are also gradually being electrified. Electric-driven engineering machinery has solved the problems of high fuel consumption, high pollution and high noise of traditional diesel engines. It represents the future of engineering machinery and has zero emissions of the whole machine, making it the first choice for environmentally friendly engineering machinery.

[0003] However, in the process of improving the energy consumption of electric construction machinery, the existing technology only optimizes energy-saving control at the framework and structural levels, and has not completed the experimentation and improvement of specific components such as motors or controllers. It has not actually achieved the goal of reducing energy consumption through control, resulting in difficulty in actually improving the energy consumption of the electric drive system. Summary of the invention

[0004] In view of this, the present application provides a simulation method of an electric drive system and an engineering machine, which solves the technical problem that it is difficult to actually improve the energy consumption of the electric drive system.

[0005] As a first aspect of the present application, the present application provides a simulation method for an electric drive system, including: obtaining speed loop parameters, average given power and average output power of different responses of a motor controller under fixed working conditions, wherein the speed loop parameters satisfy preset parameter restrictions, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions; simulating the speed loop parameters, average given power and average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; verifying the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters to determine target speed loop parameters, wherein the energy consumption of the motor controller under the target speed loop parameters is the lowest; and importing the target speed loop parameters into the motor controller.

[0006] In a possible implementation of the present application, the speed loop parameters include a speed loop proportional gain, a speed feedback filter coefficient, and a speed loop filter time constant. The multi-gradient speed loop parameters are obtained by simulating the speed loop parameters, the average given power, and the average output power, including: taking the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant, the average given power, and the average output power as input variables to construct a four-dimensional simulation model; based on the four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve; based on the fitting curve, the multi-gradient speed loop parameters are determined.

[0007] In a possible implementation of the present application, a speed loop proportional gain, a speed feedback filter coefficient, a speed loop filter time constant, an average given power and an average output power are used as input variables to construct a four-dimensional simulation model, including: constructing a first four-dimensional simulation model based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average given power; constructing a second four-dimensional simulation model based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average output power.

[0008] In a possible implementation of the present application, based on a four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve, including: based on a first four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a first fitting curve, wherein the first fitting curve is used to characterize the fitting curve corresponding to the average given power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant; based on a second four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a second fitting curve, wherein the second fitting curve is used to characterize the fitting curve corresponding to the average output power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant.

[0009] In a possible implementation of the present application, a multi-gradient speed loop parameter is determined based on a fitting curve, including: obtaining a first-order speed loop parameter corresponding to a minimum average given power by performing minimum value screening on a first fitting curve; performing step-by-step increasing gradient division on the remaining average given power value on the first fitting curve based on the first-order speed loop parameter corresponding to the minimum average given power to obtain a first multi-gradient speed loop parameter, wherein the energy consumption gradient corresponding to the first multi-gradient speed loop parameter increases step by step; obtaining a first-order speed loop parameter corresponding to a minimum average output power by performing minimum value screening on a second fitting curve; performing step-by-step increasing gradient division on the remaining average output power value on the second fitting curve based on the first-order speed loop parameter corresponding to the minimum average output power to obtain a second multi-gradient speed loop parameter, wherein the energy consumption gradient corresponding to the second multi-gradient speed loop parameter increases step by step.

[0010] In a possible implementation of the present application, the average given power and the average output power of the motor controller with different responses under fixed operating conditions are obtained, including: obtaining electric drive parameters of the motor controller with different responses under fixed operating conditions, wherein the electric drive parameters include at least given electric drive parameters and actual electric drive parameters; determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0011] In a possible implementation of the present application, given electric drive parameters include given speed and given torque, actual electric drive parameters include actual speed, actual torque, bus voltage and bus current, and average given power and average output power are determined based on the given electric drive parameters and the actual electric drive parameters, including: calculating the average given power based on the given speed and the given torque; calculating the average output power based on the actual speed and the actual torque, or the bus voltage and the bus current.

[0012] In a possible implementation of the present application, before determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters, the method includes: obtaining a waveform diagram corresponding to the electric drive parameters; based on the waveform diagram, judging whether there is an abnormal mutation in the actual electric drive parameters; if there is an abnormal mutation in the actual electric drive parameters, eliminating the electric drive parameters with the abnormal mutation; if there is no abnormal mutation in the actual electric drive parameters, determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0013] In a possible implementation of the present application, the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters are verified to determine the target speed loop parameters, including: based on the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters, collecting verification bus data of different responses of the motor controller under fixed working conditions, wherein the verification bus data includes verification electric drive parameters; by simulating the verification electric drive parameters, obtaining energy consumption calculation results of the motor controller under the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters; determining whether the energy consumption calculation result is within the target energy consumption gradient, wherein the target energy consumption gradient is used to characterize the energy consumption gradient corresponding to the first multi-gradient speed loop parameters or the second multi-gradient speed loop parameters; if the energy consumption calculation result is within the target energy consumption gradient, determining the speed loop parameters corresponding to the energy consumption calculation result as the target speed loop parameters.

[0014] As a second aspect of the present application, the present application also provides a simulation device for an electric drive system, including: an acquisition module, used to obtain speed loop parameters, average given power and average output power of different responses of a motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter restrictions, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions; a simulation module, used to simulate the speed loop parameters, average given power and average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; a verification module, used to verify the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters to determine the target speed loop parameters, wherein the energy consumption of the motor controller under the target speed loop parameters is the lowest; and importing the target speed loop parameters into the motor controller.

[0015] As a third aspect of the present application, the present application further provides an engineering machinery, including: a motor controller, wherein control parameters of the motor controller are obtained by simulation using any of the above-mentioned simulation methods.

[0016] The simulation method of the electric drive system provided in the present application includes: obtaining speed loop parameters, average given power and average output power of different responses of a motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter restrictions, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions; simulating the speed loop parameters, the average given power and the average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; verifying the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine the target speed loop parameter, wherein the energy consumption of the motor controller under the target speed loop parameter is the lowest; and importing the target speed loop parameter into the motor controller. It is easy to notice that by simulating the speed loop parameters, average given power and average output power with different responses under fixed working conditions, and verifying the simulation results, the target speed loop parameters corresponding to the lowest energy consumption point of the motor controller are obtained, and the target speed loop parameters are imported into the motor controller to control the motor controller to operate in a high-efficiency range. In this way, the purpose of completing the response change of the motor controller by changing the speed loop parameters of the motor controller is achieved, so that the motor controller continues to operate in a high-efficiency range, thereby achieving the technical effect of reducing the energy consumption of the electric drive system in construction machinery, thereby solving the technical problem that it is difficult to actually improve the energy consumption of the electric drive system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0018] Figure 1 Shown is a flow chart of a simulation method for an electric drive system provided in one embodiment of the present application.

[0019] Figure 2 The figure is a flow chart of a process for realizing energy consumption reduction of an electric drive system provided in one embodiment of the present application.

[0020] Figure 3 Shown is a schematic diagram of a simulation device for an electric drive system provided in one embodiment of the present application.

[0021] Figure 4 Shown is a device block diagram of a motor controller provided in one embodiment of the present application. DETAILED DESCRIPTION

[0022] In the description of the application, the meaning of "multiple" is at least two, for example, two, three, etc., unless otherwise clearly and specifically limited. In the embodiment of the present application, all directional indications (such as up, down, left, right, front, back, top, bottom ...) are only used to explain the relative position relationship, motion conditions, etc. between the components under a certain specific posture (as shown in the drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their deformations are intended to cover non-exclusive inclusions. For example, the process, method, system, product or equipment comprising a series of steps or units are not limited to the steps or units listed, but optionally also include the steps or units not listed, or optionally also include other steps or units inherent to these processes, methods, products or equipment.

[0023] In addition, the reference to "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0024] Exemplary Methods

[0025] As a first aspect of the present application, the present application provides a simulation method for an electric drive system. Figure 1 FIG. 1 is a flow chart of a simulation method for an electric drive system provided in an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0026] S101, obtaining speed loop parameters, average given power, and average output power of different responses of the motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter limits, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions;

[0027] Specifically, the motor controller can represent an electric drive controller used in engineering machinery. Generally, the engineering machinery can be an excavator or a forklift. The engineering machinery is not specifically limited here and can be determined according to actual conditions. In the embodiment of the present application, the engineering machinery can be exemplarily represented as an excavator.

[0028] The above-mentioned fixed working conditions can be used to represent the working state of the excavator in different working environments. According to the environment and working type of the excavator, the working conditions can be divided into the following types: conventional working state, mountain working state, ditch working state and ocean working state, etc. The fixed working conditions are not specifically limited here.

[0029] The above speed loop parameters are the key to achieve accurate speed control in the motor controller. The speed loop parameters mainly include proportional gain, speed feedback filter coefficient and speed loop filter time constant.

[0030] It should be noted that the above speed loop parameters satisfy the preset parameter limits, wherein the preset parameter limits can be used to indicate the upper and lower numerical limits of the preset speed loop parameters, which can be specifically set according to the different responses of the motor controller under fixed working conditions. The preset parameter limits are not specifically set here, but the preset parameter limits need to ensure the normal operation of the construction machinery and will not have too much impact on the working efficiency of the construction machinery.

[0031] The above average given power can be used to indicate that the given power of the motor controller is calculated by averaging.

[0032] The above average output power can be used to indicate that the output power of the motor controller is calculated by averaging.

[0033] In an optional embodiment, in order to reduce the energy consumption of the electric drive system, the present application may simulate the electric drive system. Specifically, the speed loop parameters of the motor controller may be pre-set based on different responses under fixed working conditions, so as to control the operation of the motor controller under the speed loop parameters, and collect bus data of different responses of the motor controller under fixed working conditions, so as to calculate the average given power and average output power of the motor controller based on the bus data.

[0034] Furthermore, in order to reduce the internal friction of the electric drive system in the construction machinery in the present application, bus data of different responses of the construction machinery under fixed working conditions can be collected, and the speed parameters, torque parameters, voltage parameters and current parameters corresponding to the motor controller can be obtained by extracting the electric drive parameters in the bus data. Then, by calculating the above-mentioned electric drive parameters, the average given power and average output power of the above-mentioned motor controller can be obtained.

[0035] S102, simulating the speed loop parameters, the average given power, and the average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power;

[0036] Specifically, the above-mentioned multi-gradient speed loop parameters can be used to represent multiple groups of speed loop parameters that increase step by step based on the minimum power value, wherein the energy consumption corresponding to the minimum power value is the lowest, and the energy consumption gradients corresponding to the multi-gradient speed loop parameters increase step by step. The number of gradients of the multi-gradient speed loop parameters is not specifically limited here, and it can be 4 groups of speed loop parameters or 5 groups of speed loop parameters. The number of gradients of the multi-gradient speed loop parameters can be adjusted according to actual conditions.

[0037] The multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power.

[0038] In an optional embodiment, the above-mentioned simulation process can be carried out by establishing a simulation model, simulating an image based on a function, finding a response point with low energy consumption under the above-mentioned preset parameter constraints, and outputting the speed loop parameters corresponding to the response point.

[0039] Specifically, a first fitting curve of the average given power responding to changes in different speed loop parameters can be obtained by performing uniform fitting images on the speed loop parameters and the average given power. The speed loop parameters corresponding to the lowest point of the average given power can be screened out based on the first fitting curve. At the same time, other groups of speed loop parameters are searched based on the speed loop parameter gradient to obtain the above-mentioned first multi-gradient speed loop parameters. At the same time, a second fitting curve of the average output power responding to changes in different speed loop parameters can be obtained by performing uniform fitting images on the speed loop parameters and the average output power. The speed loop parameters corresponding to the lowest point of the average output power can be screened out based on the second fitting curve. At the same time, other groups of speed loop parameters are searched based on the speed loop parameter gradient to obtain the above-mentioned second multi-gradient speed loop parameters.

[0040] S103, verifying the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine the target speed loop parameter, wherein the energy consumption of the motor controller under the target speed loop parameter is the lowest;

[0041] Specifically, after the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters are obtained by simulation, in order to determine the target speed loop parameters from the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters, that is, to determine the speed loop parameters corresponding to the lowest energy consumption point of the motor controller, the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters can be verified and determined.

[0042] Specifically, the speed loop parameters in the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters can be used in turn as the current speed loop parameters of the motor controller, so that the motor controller can be controlled to work under the current speed loop parameters, and verification bus data of different responses of the motor controller under fixed working conditions under the current speed loop parameters can be collected, and then the verification bus data can be simulated to obtain the energy consumption calculation results of the motor controller under the current speed loop parameters. By determining whether the energy consumption calculation results meet the energy consumption gradient corresponding to the current speed loop parameters, the target speed loop parameters can be determined, that is, the speed loop parameters that meet the energy consumption gradient corresponding to the current speed loop parameters are determined as the above-mentioned target speed loop parameters.

[0043] S104, importing the target speed loop parameters into the motor controller.

[0044] Specifically, after determining the target speed loop parameters, it means that the motor controller has the lowest energy consumption under the control of the target speed loop parameters. Therefore, the target speed loop parameters can be imported into the motor controller. Specifically, the target speed loop parameters and the program can be imported into the motor controller so that the motor controller works under the target speed loop parameters.

[0045] Figure 2 FIG. 1 is a flow chart of a process for realizing energy consumption reduction of an electric drive system provided by an embodiment of the present application. Figure 2 As shown in FIG. 1 , the energy consumption reduction process of the electric drive system includes the following steps:

[0046] Collect bus data of different responses under fixed working conditions and collect the specific output of the motor at the same time;

[0047] Extract data for analysis, separate speed setting, speed, torque setting, torque, bus voltage, bus current, calculate the average given power and average output power of the motor controller, and preliminarily calculate the energy consumption;

[0048] Establish a four-dimensional simulation model, simulate the image based on the function, find the response point with low energy consumption in the fitting curve under the preset parameter limit, and output the corresponding parameters;

[0049] Four groups of energy consumption corresponding parameters were selected in a gradient manner for experimental verification;

[0050] Whether the energy consumption target is achieved, if so, the test ends and the corresponding parameters and program of the response are imported into the controller. If not, return to the step of "collecting bus data of different responses under fixed working conditions and collecting motor output at the same time", enrich the data base and test again to get the result.

[0051] In summary, the present application reduces the energy consumption of the electric drive system in construction machinery by changing the motor responsiveness, that is, by changing the speed loop parameters of the motor controller so that the motor controller operates in a more efficient range when the equipment is continuously working. The response of the motor controller to different speed loop parameters under fixed working conditions is tested in groups, the working data and actual working output of the motor controller are collected, the consumption of the electric drive system and the motor are quantitatively analyzed, a model is established for simulation, the optimal result is output, and the equipment is carried out for experimental verification to achieve the goal of reducing energy consumption.

[0052] The simulation method of the electric drive system provided in the present application includes: obtaining speed loop parameters, average given power and average output power of different responses of a motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter restrictions, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions; simulating the speed loop parameters, the average given power and the average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; verifying the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine the target speed loop parameter, wherein the energy consumption of the motor controller under the target speed loop parameter is the lowest; and importing the target speed loop parameter into the motor controller. It is easy to notice that by simulating the speed loop parameters, average given power and average output power with different responses under fixed working conditions, and verifying the simulation results, the target speed loop parameters corresponding to the lowest energy consumption point of the motor controller are obtained, and the target speed loop parameters are imported into the motor controller to control the motor controller to operate in a high-efficiency range. In this way, the purpose of completing the response change of the motor controller by changing the speed loop parameters of the motor controller is achieved, so that the motor controller continues to operate in a high-efficiency range, thereby achieving the technical effect of reducing the energy consumption of the electric drive system in construction machinery, thereby solving the technical problem that it is difficult to actually improve the energy consumption of the electric drive system.

[0053] In a possible implementation of the present application, the speed loop parameters include a speed loop proportional gain, a speed feedback filter coefficient, and a speed loop filter time constant. The speed loop parameters, the average given power, and the average output power are simulated to obtain multi-gradient speed loop parameters, including: taking the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant, the average given power, and the average output power as input variables to construct a four-dimensional simulation model; based on the four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve; based on the fitting curve, the multi-gradient speed loop parameters are determined.

[0054] Specifically, the speed loop proportional gain mentioned above is a proportional term in the motor controller, which directly amplifies the speed deviation (i.e., the difference between the target speed and the actual speed). The larger the proportional gain, the faster the response to the deviation, but too large a proportional gain may cause the system to respond too sensitively, causing system oscillation or even instability. The main function of the proportional gain is to reduce the speed deviation and increase the response speed of the system.

[0055] The above speed feedback filter coefficients usually contain some high-frequency noise. If these noises are used directly for control, they may cause fluctuations in the control signal and affect the stable operation of the motor. Therefore, it is necessary to filter the speed feedback signal. The filter coefficient determines the characteristics of the filter. Choosing a suitable filter coefficient can effectively remove noise while maintaining the system's ability to respond to speed changes.

[0056] The above speed loop filter time constant determines the degree of attenuation of the high-frequency components in the signal by the filter. The smaller the time constant, the stronger the filter's attenuation effect on high-frequency noise, but it will also slow down the system's response to speed changes. Therefore, when selecting the filter time constant, it is necessary to strike a balance between suppressing noise and maintaining response speed.

[0057] In an optional embodiment, in the process of simulating the speed loop parameters, the average given power and the average output power to obtain the multi-gradient speed loop parameters, a four-dimensional simulation model can be constructed based on the average given power and the average output power, that is, the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average given power are used as input variables to construct a four-dimensional simulation model related to the average given power; at the same time, the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average output power are used as input variables to construct a four-dimensional simulation model related to the average output power. After the four-dimensional simulation model is constructed, the input parameters corresponding to the input variables can be uniformly fitted to obtain a fitting curve related to the average given power and a fitting curve related to the average output power, and finally the multi-gradient speed loop parameters are determined based on the fitting curve, that is, the speed loop proportional gain, the speed feedback filter coefficient and the speed loop filter time constant corresponding to the lowest power consumption point in the fitting curve are screened out, and the screened speed loop proportional gain, the speed feedback filter coefficient and the speed loop filter time constant are screened step by step to obtain the above-mentioned multi-gradient speed loop parameters.

[0058] In a possible implementation of the present application, a speed loop proportional gain, a speed feedback filter coefficient, a speed loop filter time constant, an average given power and an average output power are used as input variables to construct a four-dimensional simulation model, including: constructing a first four-dimensional simulation model based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average given power; constructing a second four-dimensional simulation model based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average output power.

[0059] Specifically, in the process of constructing a four-dimensional simulation model, a first four-dimensional simulation model can be constructed based on the speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant and average given power, that is, the speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant and average given power are used as data input to construct a first four-dimensional simulation model (K, S, T, P1), wherein K represents the speed loop proportional gain, S represents the speed feedback filter coefficient, T represents the speed loop filter time constant, and P1 represents the average given power. At the same time, based on the speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant and average output power, a second four-dimensional simulation model is constructed, that is, the speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant and average output power are used as data input to construct a second four-dimensional simulation model (K, S, T, P2), wherein P2 represents the average output power.

[0060] In a possible implementation of the present application, based on a four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve, including: based on a first four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a first fitting curve, wherein the first fitting curve is used to characterize the fitting curve corresponding to the average given power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant; based on a second four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a second fitting curve, wherein the second fitting curve is used to characterize the fitting curve corresponding to the average output power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant.

[0061] Specifically, the first fitting curve reflects the trend of the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant changing in response to the average given power.

[0062] The second fitting curve reflects the trend of the average output power changing in response to the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant.

[0063] In an optional embodiment, after the four-dimensional simulation model is constructed, the input parameters corresponding to the input variables can be curve-fitted based on the four-dimensional simulation model to obtain a fitting curve. Specifically, based on the first four-dimensional simulation model, the input parameters corresponding to the input variables can be curve-fitted to obtain a first fitting curve, that is, the input parameters corresponding to the input variables can be uniformly fitted, that is, the image data can be modeled and fitted using a uniform distribution (also called a rectangular distribution). Similarly, based on the second four-dimensional simulation model, the input parameters corresponding to the input variables can be curve-fitted to obtain a second fitting curve.

[0064] In a possible implementation of the present application, a multi-gradient speed loop parameter is determined based on a fitting curve, including: obtaining a first-order speed loop parameter corresponding to a minimum average given power by performing minimum value screening on a first fitting curve; performing step-by-step increasing gradient division on the remaining average given power value on the first fitting curve based on the first-order speed loop parameter corresponding to the minimum average given power to obtain a first multi-gradient speed loop parameter, wherein the energy consumption gradient corresponding to the first multi-gradient speed loop parameter increases step by step; obtaining a first-order speed loop parameter corresponding to a minimum average output power by performing minimum value screening on a second fitting curve; performing step-by-step increasing gradient division on the remaining average output power value on the second fitting curve based on the first-order speed loop parameter corresponding to the minimum average output power to obtain a second multi-gradient speed loop parameter, wherein the energy consumption gradient corresponding to the second multi-gradient speed loop parameter increases step by step.

[0065] Specifically, the first-order speed loop parameters corresponding to the above minimum average given power can be used to represent the speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant corresponding to the minimum value of the average given power.

[0066] The first-order speed loop parameters corresponding to the above minimum average output power can be used to represent the speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant corresponding to the minimum value of the average output power.

[0067] In an optional embodiment, after obtaining the fitting curve, it is necessary to determine the multi-gradient speed loop parameters based on the fitting curve. Specifically, since the first fitting curve roughly reflects the trend of the average given power response speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant to change, the minimum value of the average given power can be obtained by screening the lowest point of the first fitting curve, and then the speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant corresponding to the minimum value of the average given power can be determined. At the same time, the remaining average given power values ​​on the first fitting curve are divided into increasing gradients step by step, and the above-mentioned first multi-gradient speed loop parameters can be obtained.

[0068] Similarly, since the second fitting curve roughly reflects the trend of the average output power changing in response to the speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant, the minimum value of the average output power can be obtained by screening the lowest point of the second fitting curve, and then the speed loop proportional gain, speed feedback filter coefficient, and speed loop filter time constant corresponding to the minimum value of the average output power can be determined. At the same time, the remaining average output power values ​​on the second fitting curve are divided into increasing gradients step by step to obtain the above-mentioned second multi-gradient speed loop parameters.

[0069] In a possible implementation of the present application, the average given power and the average output power of the motor controller with different responses under fixed operating conditions are obtained, including: obtaining electric drive parameters of the motor controller with different responses under fixed operating conditions, wherein the electric drive parameters include at least given electric drive parameters and actual electric drive parameters; determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0070] Specifically, the above-mentioned electric drive parameters can be used to represent the drive parameters during the operation of the motor controller, and at least include given electric drive parameters and actual electric drive parameters, wherein the given electric drive parameters can be used to represent the given drive parameters during the operation of the motor controller, and the given electric drive parameters at least include parameters such as given speed and given torque. The actual electric drive parameters can be used to represent the actual drive parameters during the operation of the motor controller, and the actual electric drive parameters at least include parameters such as speed, torque, bus voltage, and bus current.

[0071] In an optional embodiment, in the process of obtaining the average given power and average output power of the motor controller with different responses under fixed operating conditions, it is necessary to collect bus parameters of the motor controller with different responses under fixed operating conditions, wherein the bus data includes but is not limited to information such as current, voltage, switch state and relay state, drive parameters, etc., and by extracting the bus data, the electric drive parameters of the motor controller with different responses under fixed operating conditions can be obtained, wherein the electric drive parameters include parameters such as given speed, given torque, speed, torque, bus voltage and bus current, and then based on the above-mentioned given electric drive parameters and actual electric drive parameters, the average given power and average output power can be determined.

[0072] In a possible implementation of the present application, given electric drive parameters include given speed and given torque, actual electric drive parameters include actual speed, actual torque, bus voltage and bus current, and average given power and average output power are determined based on the given electric drive parameters and the actual electric drive parameters, including: calculating the average given power based on the given speed and the given torque; calculating the average output power based on the actual speed and the actual torque, or the bus voltage and the bus current.

[0073] Specifically, in the process of determining the average given power and the average output power according to the given electric drive parameters and the actual electric drive parameters, since the given electric drive parameters include the given speed and the given torque, and the actual electric drive parameters include the actual speed, the actual torque, the bus voltage, and the bus current, the calculation process of the average given power P1 can be implemented by the following formula (1):

[0074] P1=V1*T1 / 9550(1),

[0075] Among them, V1 represents the given speed and T1 represents the given torque.

[0076] The calculation process of the average output power P2 can be achieved by the following formula (2) or formula (3):

[0077] P2=U*I(2),

[0078] P2=V2*T2 / 9550(3),

[0079] Among them, U represents the target voltage, I represents the bus current, V2 represents the actual speed, and T2 represents the actual torque.

[0080] In a possible implementation of the present application, before determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters, the method includes: obtaining a waveform diagram corresponding to the electric drive parameters; based on the waveform diagram, judging whether there is an abnormal mutation in the actual electric drive parameters; if there is an abnormal mutation in the actual electric drive parameters, eliminating the electric drive parameters with the abnormal mutation; if there is no abnormal mutation in the actual electric drive parameters, determining the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0081] Specifically, in order to ensure the accuracy of the calculation results of the average given power and the average output power, it is necessary to verify the given electric drive parameters and the actual electric drive parameters, that is, after confirming that the given electric drive parameters and the actual electric drive parameters are correct, determine the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0082] In the process of verifying the given electric drive parameters and the actual electric drive parameters, the verification can be performed based on the waveform graphs corresponding to the given electric drive parameters and the actual electric drive parameters, that is, the waveform graph corresponding to the electric drive parameters is obtained. Specifically, it can be viewed by replaying the message file graphics, and the values ​​can be quickly viewed using the software toolbar to check whether there are abnormal mutations in the actual electric drive parameters in the waveform graph. Specifically, the torque mutation information and the speed drop information can be viewed. If there is no abnormal mutation in the actual electric drive parameters, that is, the torque mutation is small, and the speed drop meets the standard requirements, then the average given power and the average output power can be determined based on the given electric drive parameters and the actual electric drive parameters; conversely, if there is an abnormal mutation in the actual electric drive parameters, that is, there may be abnormal information such as a large torque mutation and the speed drop does not meet the standard requirements, then the electric drive parameters with abnormal mutations are eliminated, so as to ensure the data accuracy of the given electric drive parameters and the actual electric drive parameters, thereby improving the calculation accuracy of the average given power and the average output power.

[0083] In a possible implementation of the present application, the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters are verified to determine the target speed loop parameters, including: based on the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters, collecting verification bus data of different responses of the motor controller under fixed working conditions, wherein the verification bus data includes verification electric drive parameters; by simulating the verification electric drive parameters, obtaining energy consumption calculation results of the motor controller under the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters; determining whether the energy consumption calculation result is within the target energy consumption gradient, wherein the target energy consumption gradient is used to characterize the energy consumption gradient corresponding to the first multi-gradient speed loop parameters or the second multi-gradient speed loop parameters; if the energy consumption calculation result is within the target energy consumption gradient, determining the speed loop parameters corresponding to the energy consumption calculation result as the target speed loop parameters.

[0084] Specifically, the verification bus data can be used to represent data for verifying the speed loop parameters obtained by controlling the motor controller to respond differently under fixed working conditions using the first multi-gradient speed loop parameters or the second multi-gradient speed loop parameters. The verification bus data includes verification electric drive parameters.

[0085] The above-mentioned verified electric drive parameters include but are not limited to the electric drive parameters such as the verified given speed, speed, given torque, torque, bus voltage, bus current, average given power and average output power.

[0086] It should be noted that each group of speed loop parameters in the above-mentioned first multi-gradient speed loop parameters or the second multi-gradient speed loop parameters has its corresponding target energy consumption gradient. By judging whether the energy consumption calculation result is within the target energy consumption gradient, it can be determined whether the speed loop parameter corresponding to the energy consumption calculation result is the target speed loop parameter.

[0087] Specifically, for the first multi-gradient speed loop parameters, the minimum value of the average given power can be set as the first-order energy consumption gradient, the slightly larger value slightly greater than the minimum value can be set as the second-order energy consumption gradient, the larger value greater than the slightly larger value can be set as the third-order energy consumption gradient, and so on; similarly, for the second multi-gradient speed loop parameters, the minimum value of the average output power can be set as the first-order energy consumption gradient, the slightly larger value slightly greater than the minimum value can be set as the second-order energy consumption gradient, the larger value greater than the slightly larger value can be set as the third-order energy consumption gradient, and so on.

[0088] In an optional embodiment, in the process of determining the target speed loop parameters, any set of speed loop parameters in the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters can be used to control the operation of the motor controller one by one, and at the same time, verification bus data of different responses of the motor controller under fixed working conditions under each set of speed loop parameters are collected, and the verification electric drive parameters are simulated, that is, the verification electric drive parameters are used as input data, and the input data is associated with energy consumption to establish the above-mentioned four-dimensional simulation model. By simulating the fitting curve, the energy consumption calculation results of different responses of the motor controller under fixed working conditions under each set of speed loop parameters can be obtained. Since each set of speed loop parameters Each of them has its corresponding target energy consumption gradient. Therefore, it can be determined whether the above energy consumption calculation result is within the target energy consumption gradient. If the energy consumption calculation result is within the target energy consumption gradient, it means that under the control of the speed loop parameters corresponding to the energy consumption calculation result, the motor controller can be placed in a high-efficiency working range, thereby achieving the purpose of reducing energy consumption. Therefore, the speed loop parameters corresponding to the energy consumption calculation result can be determined as the target speed loop parameters. On the contrary, if the energy consumption calculation result is not within the corresponding target energy consumption gradient, it means that under the control of the speed loop parameters corresponding to the energy consumption calculation result, the motor controller cannot be placed in a high-efficiency working range, and it is necessary to enrich the data base for re-simulation verification.

[0089] Exemplary Devices

[0090] As a second aspect of the present application, the present application also provides a simulation device for an electric drive system. Figure 3 FIG. 1 is a schematic diagram of a simulation device for an electric drive system provided in an embodiment of the present application. Figure 3 As shown, the device comprises:

[0091] An acquisition module 301 is used to acquire speed loop parameters, average given power, and average output power of different responses of the motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter limits, and the speed loop parameters can be pre-set according to different responses of the motor controller under fixed working conditions;

[0092] A simulation module 302 is used to simulate the speed loop parameters, the average given power and the average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power;

[0093] A verification module 303 is used to verify the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine the target speed loop parameter, wherein the energy consumption of the motor controller under the target speed loop parameter is the lowest;

[0094] The import module 304 is used to import the target speed loop parameters into the motor controller.

[0095] In a possible implementation of the present application, the simulation module includes: a construction module, which is used to construct a four-dimensional simulation model by taking the speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant, average given power and average output power as input variables; a fitting module, which is used to perform curve fitting on the input parameters corresponding to the input variables based on the four-dimensional simulation model to obtain a fitting curve; and a determination module, which is used to determine the multi-gradient speed loop parameters based on the fitting curve.

[0096] In a possible implementation of the present application, the construction module includes: a first construction module, which is used to construct a first four-dimensional simulation model based on a speed loop proportional gain, a speed feedback filter coefficient, a speed loop filter time constant and an average given power; a second construction module, which is used to construct a second four-dimensional simulation model based on a speed loop proportional gain, a speed feedback filter coefficient, a speed loop filter time constant and an average output power.

[0097] In a possible implementation of the present application, the fitting module includes: a first fitting module, which is used to perform curve fitting on the input parameters corresponding to the input variables based on the first four-dimensional simulation model to obtain a first fitting curve, wherein the first fitting curve is used to characterize the fitting curve corresponding to the average given power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant; a second fitting module, which is used to perform curve fitting on the input parameters corresponding to the input variables based on the second four-dimensional simulation model to obtain a second fitting curve, wherein the second fitting curve is used to characterize the fitting curve corresponding to the average output power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant.

[0098] In a possible implementation of the present application, the determination module includes: a first screening module, which is used to obtain the first-order speed loop parameters corresponding to the minimum average given power by performing minimum value screening on the first fitting curve; a first division module, which is used to perform step-by-step increasing gradient division on the remaining average given power value on the first fitting curve based on the first-order speed loop parameters corresponding to the minimum average given power, to obtain the first multi-gradient speed loop parameters, wherein the energy consumption gradient corresponding to the first multi-gradient speed loop parameters increases step by step; a second screening module, which is used to obtain the first-order speed loop parameters corresponding to the minimum average output power by performing minimum value screening on the second fitting curve; a second division module, which is used to perform step-by-step increasing gradient division on the remaining average output power value on the second fitting curve based on the first-order speed loop parameters corresponding to the minimum average output power, to obtain the second multi-gradient speed loop parameters, wherein the energy consumption gradient corresponding to the second multi-gradient speed loop parameters increases step by step.

[0099] In a possible implementation of the present application, the acquisition module includes: an electric drive parameter acquisition module, which is used to obtain the electric drive parameters of different responses of the motor controller under fixed working conditions, wherein the electric drive parameters at least include given electric drive parameters and actual electric drive parameters; a power determination module, which is used to determine the average given power and the average output power based on the given electric drive parameters and the actual electric drive parameters.

[0100] In a possible implementation of the present application, the power determination module includes: a first calculation module, used to calculate the average given power based on a given speed and a given torque; a second calculation module, used to calculate the average output power based on the actual speed and the actual torque, or the bus voltage and the bus current.

[0101] In a possible implementation of the present application, the device includes: a waveform acquisition module, used to acquire a waveform corresponding to an electric drive parameter; a first judgment module, used to judge whether there is an abnormal mutation in the actual electric drive parameter based on the waveform; a rejection module, used to reject the electric drive parameter with abnormal mutation if the actual electric drive parameter has an abnormal mutation; and a power determination module, used to determine the average given power and the average output power based on the given electric drive parameter and the actual electric drive parameter if the actual electric drive parameter does not have an abnormal mutation.

[0102] In a possible implementation of the present application, the verification module includes: an acquisition module, which is used to acquire verification bus data of different responses of the motor controller under fixed working conditions based on the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters, wherein the verification bus data includes verification electric drive parameters; a parameter simulation module, which is used to obtain the energy consumption calculation results of the motor controller under the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters by simulating the verification electric drive parameters; a second judgment module, which is used to determine whether the energy consumption calculation result is within the target energy consumption gradient, wherein the target energy consumption gradient is used to characterize the energy consumption gradient corresponding to the first multi-gradient speed loop parameters or the second multi-gradient speed loop parameters; a target speed loop parameter determination module, which is used to determine the speed loop parameters corresponding to the energy consumption calculation result as the target speed loop parameters if the energy consumption calculation result is within the target energy consumption gradient.

[0103] Exemplary construction machinery

[0104] As a third aspect of the present application, the present application further provides an engineering machinery, including: a motor controller, wherein control parameters of the motor controller are obtained by simulation using any of the above-mentioned simulation methods.

[0105] Figure 4 Shown is a device block diagram of a motor controller provided in one embodiment of the present application.

[0106] like Figure 4 As shown, the motor controller includes one or more processors 41 and a memory 42 .

[0107] The processor 41 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the forklift to perform desired functions.

[0108] The memory 42 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on a computer-readable storage medium, and the processor 41 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage medium.

[0109] In one example, the engineering machine may further include: an input device 43 and an output device 44 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0110] When the engineering machine is a stand-alone device, the input device 43 may be a communication network connector for receiving collected input signals from the first device and the second device.

[0111] In addition, the input device 43 may also include, for example, a keyboard, a mouse, etc.

[0112] The output device 44 can output various information to the outside, including the determined distance information, direction information, etc. The output device 44 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0113] Of course, to simplify, Figure 4 Only some of the components in the engineering machine related to the present application are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the engineering machine may further include any other appropriate components according to specific application conditions.

[0114] Exemplary computer-readable storage media

[0115] As a fourth aspect of the present application, the present application provides a computer-readable storage medium, the storage medium storing a computer program, the computer program being used to perform the following steps:

[0116] S1, obtaining speed loop parameters, average given power, and average output power of different responses of the motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter limits, and the speed loop parameters can be pre-set through different responses of the motor controller under fixed working conditions;

[0117] S2, simulating the speed loop parameters, the average given power and the average output power to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power;

[0118] S3, verifying the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters to determine target speed loop parameters, wherein the energy consumption of the motor controller under the target speed loop parameters is the lowest; and importing the target speed loop parameters into the motor controller.

[0119] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program information, which, when executed by a processor, enables the processor to execute the steps in the simulation method of the electric drive system according to various embodiments of the present application described in this specification.

[0120] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0121] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program information is stored. When the computer program information is executed by a processor, the processor executes the steps in the simulation method of the electric drive system according to various embodiments of the present application in this specification.

[0122] Computer readable storage media can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0123] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0124] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0125] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

Claims

1. A simulation method for an electric drive system, characterized in that: include: Obtaining speed loop parameters, average given power, and average output power of different responses of the motor controller under fixed working conditions, wherein the speed loop parameters meet preset parameter limits, and the speed loop parameters can be pre-set according to different responses of the motor controller under fixed working conditions; The speed loop parameters, the average given power and the average output power are simulated to obtain multi-gradient speed loop parameters, wherein the multi-gradient speed loop parameters include a first multi-gradient speed loop parameter corresponding to the lowest point of the average given power and a second multi-gradient speed loop parameter corresponding to the lowest point of the average output power; Verifying the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine a target speed loop parameter, wherein the energy consumption of the motor controller under the target speed loop parameter is the lowest; The target speed loop parameters are imported into the motor controller.

2. The simulation method of the electric drive system according to claim 1, characterized in that: The speed loop parameters include a speed loop proportional gain, a speed feedback filter coefficient, and a speed loop filter time constant. The speed loop parameters, the average given power, and the average output power are simulated to obtain multi-gradient speed loop parameters, including: The speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant, average given power and average output power are used as input variables to construct a four-dimensional simulation model; Based on the four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve; Based on the fitting curve, the multi-gradient velocity loop parameters are determined.

3. The simulation method of the electric drive system according to claim 2, characterized in that: The speed loop proportional gain, speed feedback filter coefficient, speed loop filter time constant, average given power and average output power are used as input variables to construct a four-dimensional simulation model, including: Constructing a first four-dimensional simulation model based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average given power; A second four-dimensional simulation model is constructed based on the speed loop proportional gain, the speed feedback filter coefficient, the speed loop filter time constant and the average output power.

4. The simulation method of the electric drive system according to claim 3, characterized in that: Based on the four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a fitting curve, including: Based on the first four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a first fitting curve, wherein the first fitting curve is used to characterize a fitting curve corresponding to an average given power in response to changes in a speed loop proportional gain, a speed feedback filter coefficient, and a speed loop filter time constant; Based on the second four-dimensional simulation model, curve fitting is performed on the input parameters corresponding to the input variables to obtain a second fitting curve, wherein the second fitting curve is used to characterize the fitting curve corresponding to the average output power in response to changes in the speed loop proportional gain, the speed feedback filter coefficient, and the speed loop filter time constant.

5. The simulation method of the electric drive system according to claim 4, characterized in that: Determining the multi-gradient velocity loop parameters based on the fitting curve includes: By performing minimum value screening on the first fitting curve, a first-order speed loop parameter corresponding to the minimum average given power is obtained; Based on the first-order speed loop parameter corresponding to the minimum average given power, the remaining average given power value on the first fitting curve is divided into increasing gradients step by step to obtain a first multi-gradient speed loop parameter, wherein the energy consumption gradient corresponding to the first multi-gradient speed loop parameter increases step by step; By performing minimum value screening on the second fitting curve, a first-order speed loop parameter corresponding to the minimum average output power is obtained; Based on the first-order speed loop parameters corresponding to the minimum average output power, the remaining average output power value on the second fitting curve is divided into increasing gradients step by step to obtain second multi-gradient speed loop parameters, wherein the energy consumption gradients corresponding to the second multi-gradient speed loop parameters increase step by step.

6. The simulation method of the electric drive system according to claim 1, characterized in that: Get the average given power and average output power of the motor controller under different responses under fixed working conditions, including: Acquire electric drive parameters of different responses of the motor controller under fixed working conditions, wherein the electric drive parameters at least include given electric drive parameters and actual electric drive parameters; An average given power and an average output power are determined according to the given electric drive parameters and the actual electric drive parameters.

7. The simulation method of the electric drive system according to claim 6, characterized in that: The given electric drive parameters include a given speed and a given torque, the actual electric drive parameters include an actual speed, an actual torque, a bus voltage, and a bus current, and according to the given electric drive parameters and the actual electric drive parameters, determining an average given power and an average output power includes: Calculating the average given power according to the given speed and the given torque; The average output power is calculated according to the actual speed and the actual torque, or the bus voltage and the bus current.

8. The simulation method of the electric drive system according to claim 6, characterized in that: Before determining the average given power and the average output power according to the given electric drive parameters and the actual electric drive parameters, the method includes: Obtaining a waveform diagram corresponding to the electric drive parameter; Based on the waveform diagram, determining whether the actual electric drive parameter has an abnormal mutation; If the actual electric drive parameters have abnormal mutations, the electric drive parameters with abnormal mutations are eliminated; If there is no abnormal mutation in the actual electric drive parameter, the average given power and the average output power are determined according to the given electric drive parameter and the actual electric drive parameter.

9. The simulation method of the electric drive system according to claim 1, characterized in that: Verifying the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter to determine the target speed loop parameter includes: Based on the first multi-gradient speed loop parameter and the second multi-gradient speed loop parameter, collecting verification bus data of different responses of the motor controller under fixed working conditions, wherein the verification bus data includes verification electric drive parameters; By simulating the verification electric drive parameters, an energy consumption calculation result of the motor controller under the first multi-gradient speed loop parameters and the second multi-gradient speed loop parameters is obtained; Determining whether the energy consumption calculation result is within a target energy consumption gradient, wherein the target energy consumption gradient is used to characterize the energy consumption gradient corresponding to the first multi-gradient speed loop parameter or the second multi-gradient speed loop parameter; If the energy consumption calculation result is within the target energy consumption gradient, the speed loop parameter corresponding to the energy consumption calculation result is determined as the target speed loop parameter.

10. An engineering machine, characterized in that: The engineering machinery includes a motor controller, and control parameters of the motor controller are obtained by simulation using the simulation method described in any one of claims 1 to 9.

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