A visual optimization control management method and system for permanent magnet synchronous motor

Abstract

The present invention provides a visual optimization control management method and system for a permanent magnet synchronous motor, which relates to the technical field of new energy vehicles, wherein the method includes: determining the target operating condition to be optimized based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles; generating an operating simulation model of the target operating condition; assisting users in deciding the optimal control scheme for the target operating condition based on the operating simulation model; and performing OTA upgrades on the permanent magnet synchronous motor based on the optimized control scheme. The present invention determines the target operating condition to be optimized based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles, automatically discovers the operating condition for which the permanent magnet synchronous motor needs to be optimized; assists the expert group in visually deciding the optimal control scheme for the target operating condition based on the operating simulation model, and engineers can make decisions on the optimal control scheme online, which improves convenience and timeliness of the optimized control.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and in particular to a visualized optimization control management method and system for a permanent magnet synchronous motor. Background Art

[0002] At present, in the drive system of new energy vehicles, permanent magnet synchronous motors have become the mainstream type of motors due to their high efficiency, stability and reliability.

[0003] However, due to the complexity and variability of real road conditions, in actual driving of new energy vehicles, permanent magnet synchronous motors may encounter operating conditions that require optimized control. These operating conditions often require user feedback or engineers to discover through independent experiments. Secondly, when such operating conditions are discovered, multiple engineers are required to make offline decisions on the optimal control plan for the operating condition. The lack of convenience in decision-making may lead to insufficient timeliness in the optimization control of permanent magnet synchronous motors. In addition, after the decision on the optimal control plan is made, the new energy vehicle needs to be recalled and its permanent magnet synchronous motor needs to be optimized accordingly. The lack of convenience in optimization reduces the user experience.

[0004] Therefore, a solution is urgently needed. Summary of the invention

[0005] One of the purposes of the present invention is to provide a visual optimization control management method for a permanent magnet synchronous motor. Based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles, the target operating conditions to be optimized and controlled are determined, and the operating conditions of the permanent magnet synchronous motor that need to be optimized and controlled are automatically discovered. The expert group is assisted in visually deciding the optimal control scheme for the target operating conditions based on the operating simulation model, and engineers can make decisions on the optimal control scheme online, which improves convenience and timeliness of the optimal control. Finally, based on the optimized control scheme, the permanent magnet synchronous motor is OTA upgraded, which improves the convenience of optimization and improves user experience.

[0006] An embodiment of the present invention provides a visual optimization control management method for a permanent magnet synchronous motor, comprising:

[0007] Based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles, determine the target operating conditions to be optimized and controlled;

[0008] Generate an operational simulation model of the target operational scenario;

[0009] Assist the expert group to visualize the decision-making target operation situation based on the operation simulation model to optimize the control plan;

[0010] Based on the optimized control scheme, the permanent magnet synchronous motor is upgraded OTA.

[0011] Optionally, the auxiliary expert group determines the optimal control scheme of the target operation situation based on the operation simulation model visualization decision, including:

[0012] Activate a first visualization interface for all experts in the expert group to jointly view the running simulation model;

[0013] When at least one expert starts to perform simulation demonstration control on the running simulation model in the first visual interface, continuously obtain the communication records between the experts within the most recent preset time;

[0014] Extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods;

[0015] Based on the trigger degree table, the trigger degree is determined according to the characteristic value set;

[0016] When the trigger degree exceeds the trigger degree threshold, based on the communication record, a plurality of simulation demonstration objects and a simulation demonstration control timeline among the experts are attempted to be determined in real time;

[0017] Whenever the attempt is determined to be successful, a second visualization interface is activated for each simulation demonstration object to view the running simulation model together;

[0018] Based on the simulation demonstration control timeline, start to perform corresponding simulation demonstration control on the running simulation model in the second visual interface;

[0019] Receive the optimal control plan based on the final decision of each expert.

[0020] Optionally, the real-time attempt to determine multiple simulation demonstration objects and simulation demonstration control timeline among the experts based on the communication records includes:

[0021] Extract semantics from communication records to obtain semantic sets;

[0022] Match the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree;

[0023] When the maximum matching degree exceeds the matching degree threshold, the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set are obtained;

[0024] Based on the object determination rule, multiple candidate experts are determined from among the experts according to their expert portraits;

[0025] When multiple candidate experts meet the target personnel conditions, an attempt is made to determine success, and each candidate expert meeting the target personnel conditions is used as a plurality of simulation demonstration objects; wherein the target personnel conditions include: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer;

[0026] Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters;

[0027] Based on the sequence of each simulation demonstration stage and the duration of each simulation demonstration, the time interval of each simulation demonstration stage is divided on the initial time axis;

[0028] Assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0029] Based on the simulation configuration parameters corresponding to each simulation demonstration stage, a virtual camera shooting trajectory of each simulation demonstration stage is generated;

[0030] Assigning the shooting trajectory of the virtual camera in each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0031] Different time intervals are assigned different simulation configuration parameters and the initial timeline of the virtual camera shooting trajectory is used as the simulation demonstration control timeline.

[0032] Optionally, generating a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage includes:

[0033] Traverse each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage;

[0034] During each traversal, a plurality of reaction areas and a plurality of reaction contents of each reaction area after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured are determined;

[0035] Planning the shooting position of the virtual camera in the running simulation model; wherein, when the virtual camera is located at the shooting position to shoot the simulation subject, the entire reaction area can be clearly captured;

[0036] Generate shooting constraints for shooting positions;

[0037] Assign shooting constraints to the shooting position to obtain the position to be put into orbit;

[0038] After each simulation demonstration phase is completed, the positions to be put into orbit obtained by each traversal are connected in sequence according to the order of traversal to obtain the shooting trajectory of the virtual camera;

[0039] The shooting constraints include:

[0040] Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area;

[0041] The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area;

[0042] The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set;

[0043] The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

[0044] Optionally, after starting to perform corresponding simulation demonstration control on the running simulation model in the second visualization interface based on the simulation demonstration control timeline, the method further includes:

[0045] Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface;

[0046] Based on the interaction records, try to determine auxiliary knowledge in real time;

[0047] Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

[0048] An embodiment of the present invention provides a visual optimization control management system for a permanent magnet synchronous motor, comprising:

[0049] A determination module is used to determine a target operating condition to be optimized based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles;

[0050] A generation module, used for generating an operation simulation model of a target operation situation;

[0051] Auxiliary module, used to assist the expert group in making optimal control plans for target operation situations based on the operation simulation model visualization decision;

[0052] The upgrade module is used to perform OTA upgrades on permanent magnet synchronous motors based on optimized control schemes.

[0053] Optionally, the auxiliary module assists the expert group in determining an optimal control solution for a target operation situation based on a visual decision-making operation simulation model, including:

[0054] Activate a first visualization interface for all experts in the expert group to jointly view the running simulation model;

[0055] When at least one expert starts to perform simulation demonstration control on the running simulation model in the first visual interface, continuously obtain the communication records between the experts within the most recent preset time;

[0056] Extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods;

[0057] Based on the trigger degree table, the trigger degree is determined according to the characteristic value set;

[0058] When the trigger degree exceeds the trigger degree threshold, based on the communication record, a plurality of simulation demonstration objects and a simulation demonstration control timeline among the experts are attempted to be determined in real time;

[0059] Whenever the attempt is determined to be successful, a second visualization interface is activated for each simulation demonstration object to view the running simulation model together;

[0060] Based on the simulation demonstration control timeline, start to perform corresponding simulation demonstration control on the running simulation model in the second visual interface;

[0061] Receive the optimal control plan based on the final decision of each expert.

[0062] Optionally, the auxiliary module attempts to determine multiple simulation demonstration objects and simulation demonstration control timelines among the experts in real time based on the communication records, including:

[0063] Extract semantics from communication records to obtain semantic sets;

[0064] Match the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree;

[0065] When the maximum matching degree exceeds the matching degree threshold, the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set are obtained;

[0066] Based on the object determination rule, multiple candidate experts are determined from among the experts according to their expert portraits;

[0067] When multiple candidate experts meet the target personnel conditions, an attempt is made to determine success, and each candidate expert meeting the target personnel conditions is used as a plurality of simulation demonstration objects; wherein the target personnel conditions include: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer;

[0068] Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters;

[0069] Based on the sequence of each simulation demonstration stage and the duration of each simulation demonstration, the time interval of each simulation demonstration stage is divided on the initial time axis;

[0070] Assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0071] Based on the simulation configuration parameters corresponding to each simulation demonstration stage, a virtual camera shooting trajectory of each simulation demonstration stage is generated;

[0072] Assigning the shooting trajectory of the virtual camera in each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0073] Different time intervals are assigned different simulation configuration parameters and the initial timeline of the virtual camera shooting trajectory is used as the simulation demonstration control timeline.

[0074] Optionally, the auxiliary module generates a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage, including:

[0075] Traverse each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage;

[0076] During each traversal, a plurality of reaction areas and a plurality of reaction contents of each reaction area after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured are determined;

[0077] Planning the shooting position of the virtual camera in the running simulation model; wherein, when the virtual camera is located at the shooting position to shoot the simulation subject, the entire reaction area can be clearly captured;

[0078] Generate shooting constraints for shooting positions;

[0079] Assign shooting constraints to the shooting position to obtain the position to be put into orbit;

[0080] After each simulation demonstration phase is completed, the positions to be put into orbit obtained by each traversal are connected in sequence according to the order of traversal to obtain the shooting trajectory of the virtual camera;

[0081] The shooting constraints include:

[0082] Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area;

[0083] The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area;

[0084] The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set;

[0085] The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

[0086] Optionally, the auxiliary module further performs the following operations after starting to perform corresponding simulation demonstration control on the running simulation model in the second visual interface based on the simulation demonstration control timeline:

[0087] Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface;

[0088] Based on the interaction records, try to determine auxiliary knowledge in real time;

[0089] Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

[0090] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0091] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0093] Figure 1A schematic diagram of a visualized optimization control management method for a permanent magnet synchronous motor according to an embodiment of the present invention;

[0094] Figure 2 It is a schematic diagram of a visualized optimization control management system of a permanent magnet synchronous motor in an embodiment of the present invention. DETAILED DESCRIPTION

[0095] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0096] The embodiment of the present invention provides a visual optimization control management method for a permanent magnet synchronous motor, such as Figure 1 As shown, including:

[0097] S1. Determine the target operating condition to be optimized based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles;

[0098] In S1, the operation big data includes: the operation performance data of the same type of permanent magnet synchronous motor under different operating conditions, such as: current, voltage, speed, control strategy, load condition, environmental condition and energy efficiency evaluation condition; the target operation condition is the operation condition where the permanent magnet synchronous motor needs to be optimized and controlled, such as: the condition of excessive operating temperature, the condition of instantaneous load change (sudden acceleration, ramp start, traction of large load, etc.); the operation big data reflects the comprehensive operation performance of the permanent magnet synchronous motor after it is put into use, so the operation condition such as poor operation performance can be analyzed based on it as the target operation condition;

[0099] S2. Generate an operation simulation model of the target operation situation;

[0100] In S2, the operation simulation model is a visual model that can perform operation simulation on the target operation situation, which can be implemented based on three-dimensional simulation technology;

[0101] S3, assist the expert group to make an optimal control plan for the target operation situation based on the operation simulation model visualization decision;

[0102] In S3, the expert group includes several engineers who specialize in the optimization control of permanent magnet synchronous motors. Based on the running simulation model, the expert group can visualize the optimization control scheme for the target operating conditions, and the system assists them in making decisions.

[0103] S4. Perform OTA upgrade on the permanent magnet synchronous motor based on the optimized control scheme.

[0104] In S4, finally, the permanent magnet synchronous motor is optimized based on the optimized control scheme in the form of OTA upgrade.

[0105] This application is based on a large amount of big data on the operation of permanent magnet synchronous motors of new energy vehicles to determine the target operating conditions to be optimized and automatically discover the operating conditions of the permanent magnet synchronous motors that need to be optimized; the expert group is assisted in visually deciding the optimal control plan for the target operating conditions based on the operation simulation model, and engineers can make decisions on the optimal control plan online, which improves convenience and timeliness of the optimal control; finally, based on the optimized control plan, the permanent magnet synchronous motor is OTA upgraded, which improves the convenience of optimization and improves user experience.

[0106] In one embodiment, the S3, assisting the expert group in determining the optimal control scheme for the target operation situation based on the operation simulation model visualization decision, includes:

[0107] S31, activating a first visualization interface for all experts in the expert group to jointly view the running simulation model;

[0108] In S31, the experts can jointly view and operate the simulation model through the first visualization interface;

[0109] S32, when at least one expert starts to perform simulation demonstration control on the running simulation model in the first visualization interface, continuously obtain the communication records between the experts within the recent preset time;

[0110] In S32, the most recent preset time may be the most recent 10 minutes; when at least one expert performs simulation demonstration control on the running simulation model, it indicates that the expert group has begun to make decisions on the optimization control scheme and is ready to provide assistance; the communication record refers to the record of the conversation between the experts, etc.;

[0111] S33, extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods;

[0112] In S33, the number of dialoguers refers to the total number of experts who participated in the dialogue and generated the communication record; the dialogue time period refers to the time period in which the experts participated in the dialogue; the overlapping time length is the sum of the overlapping time lengths between two dialogue time periods;

[0113] S34, determining the trigger degree based on the trigger degree table and the characteristic value set;

[0114] In S34, the triggering degree table has triggering degrees corresponding to different feature value sets that are preset. The triggering degree represents the degree to which the feature value set reflects the need to further determine the specific way to assist the expert group based on the communication record. For example, the features in the feature value set are the number of conversations in the communication record, 25, the number of people in the conversation, and the overlapping time of the conversation time period is 100 seconds, indicating that the amount of communication dialogues is large, the number of people participating in the communication is large, and the communication debate is obvious. Therefore, the degree to which the specific way to assist the expert group needs to be further determined based on the communication record is large, and the corresponding triggering degree is 20;

[0115] S35, when the trigger degree exceeds the trigger degree threshold, based on the communication record, trying to determine multiple simulation demonstration objects and simulation demonstration control time axis among the experts in real time;

[0116] In S35, the trigger degree threshold may be, for example, 10; when the trigger degree exceeds the trigger degree threshold, it means that the degree of need to further determine the specific way of assisting the expert group based on the communication record is relatively large, and further determine the specific way of assisting the expert group; this way is to conduct targeted simulation demonstration for the expert personnel who currently need to have a local in-depth understanding of the target operation situation to facilitate further participation in the subsequent communication, that is, the simulation demonstration object, and the simulation demonstration control timeline can control the operation of the simulation model to implement the targeted simulation demonstration;

[0117] S36, whenever the attempt is determined to be successful, activating a second visualization interface for each simulation demonstration object to jointly view the running simulation model;

[0118] In S36, when the attempt is determined to be successful, it indicates that a targeted simulation demonstration is required, and each simulation demonstration object can jointly view and operate the simulation model in the second visualization interface;

[0119] S37, based on the simulation demonstration control timeline, starting to perform corresponding simulation demonstration control on the running simulation model in the second visualization interface;

[0120] In S37, each simulation demonstration object can view the simulation demonstration process in the second visualization interface to achieve a local and in-depth understanding of the target operation status; at this time, it can also view the first visualization interface to facilitate further participation in communication at any time.

[0121] S38. Receive the optimal control plan finally decided by the experts.

[0122] In S38, after each expert makes a decision, an optimized control plan for the final decision will be input.

[0123] In the embodiment of the present invention, each expert can view the first visualization interface together, and each party can control and demonstrate the operation simulation model in the first visualization interface at any time, participate in the communication, and conveniently make decisions on the optimization control scheme; when necessary, the system will determine multiple simulation demonstration objects and simulation demonstration control timelines based on the communication record, and implement targeted simulation demonstrations for experts who need to have a local and in-depth understanding of the target operation situation to facilitate further participation in the communication, so as to achieve assistance, which does not delay the experts from continuing to communicate in the first visualization interface, and also enables the simulation demonstration objects to better participate in the communication later, thereby improving the decision-making efficiency of the optimization control scheme and improving humanization; secondly, by conducting targeted simulation demonstrations on each simulation demonstration object, the rhythm of the decision-making optimization control scheme of each expert can be optimized, so that they can all complete appropriate decision-making work at an appropriate time; in addition, by introducing the characteristic value set, the trigger degree table and the trigger degree, the degree to which the specific method of assisting the expert group needs to be further determined based on the communication record can be quickly and accurately determined. When the trigger degree exceeds the trigger degree threshold, the specific method of assisting the expert group is further determined, thereby reducing the auxiliary resources of the system and improving the auxiliary efficiency of the system.

[0124] In one embodiment, in S35, based on the communication record, trying to determine multiple simulation demonstration objects and simulation demonstration control time axis among the experts in real time includes:

[0125] S3501, extracting semantics from the communication records to obtain a semantic set;

[0126] In S3501, the semantic set includes multiple conversation semantics of the communication record;

[0127] S3502, matching the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree;

[0128] In S3502, the standard semantic set is a semantic set representing the need for experts to have a local in-depth understanding of the target operating situation in order to facilitate further participation in subsequent exchanges, such as: "abnormal motor load", "whether the high operating temperature is caused by the load", etc., which requires experts to analyze the causes of abnormal motor load and the causes of excessive motor operation in batches, that is, to have a local in-depth understanding of the target operating situation; the maximum matching degree is the maximum value of the matching degrees between the standard semantic set and each standard semantic set;

[0129] S3503, when the maximum matching degree exceeds the matching degree threshold, obtaining the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set;

[0130] In S3503, the matching degree threshold may be, for example, 95%; when the maximum matching degree exceeds the matching degree threshold, it indicates that the situation represented by the communication record is highly matched with the situation represented by the corresponding standard semantic set, and preset contents such as the object determination rule of the corresponding standard semantic set may be used; the object determination rule indicates how to determine the experts who need to have a local and in-depth understanding of the target operating situation in the situation represented by the standard semantic set to facilitate further participation in the communication, such as: selecting experts with rich experience in motor load research; the simulation demonstration expectation indicates how to demonstrate the simulation demonstration object, such as: performing operation simulation demonstrations on the motor under loads of different abnormalities; the simulation demonstration constraint indicates how to specifically implement the simulation demonstration of the operation simulation model;

[0131] S3504, based on the object determination rule and according to the expert portraits of the experts, determine a plurality of candidate experts from the experts;

[0132] In S3504, the expert portrait includes: the expert's position, field of expertise, etc.; under the instruction of the object determination rule, multiple candidate experts can be determined from each expert;

[0133] S3505. When multiple candidate experts meet the target personnel condition, an attempt is made to determine success, and each candidate expert meeting the target personnel condition is used as a plurality of simulation demonstration objects; wherein the target personnel condition includes: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer;

[0134] In S3505, the historical simulation demonstration expectation is the simulation demonstration expectation of the corresponding standard semantic set obtained when the simulation demonstration object and the simulation demonstration control timeline were tried in history. The expected association relationship refers to the appropriate association relationship of the simulation demonstration of two simulation demonstration expectations in succession, such as: respectively simulating and demonstrating the operation of the motor under loads of different abnormal degrees, and respectively simulating and demonstrating the operation abnormalities of the motor caused by load abnormalities, that is, performing the simulation demonstration of the two simulation demonstration expectations in this row facilitates the simulation demonstration object to study the relevant problems of the motor operation load; when multiple candidate experts meet the target personnel conditions, it means that the current simulation demonstration expectation is appropriate and the attempt is determined to be successful;

[0135] S3506. Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters;

[0136] In S3506, the simulation demonstration stage is a plurality of demonstration stages for performing simulation demonstration on the running simulation model according to the specific implementation of the simulation demonstration constraint indication, the simulation demonstration duration is the duration of performing simulation demonstration at different demonstration stages, and the simulation configuration parameters are parameters for performing simulation configuration on the running simulation model according to performing simulation demonstration at different demonstration stages;

[0137] S3507, dividing the time intervals of each simulation demonstration stage on the initial time axis based on the sequence of the stages of each simulation demonstration stage and the corresponding simulation demonstration durations;

[0138] In S3507, the order of the stages is the order of the simulation demonstrations of each simulation demonstration stage; the initial time axis is a time axis without content set; on the initial time axis, the divided time intervals are adjacent in sequence, the order of the time intervals is the order of the stages of each simulation demonstration, and the length of the time interval is the simulation demonstration duration of the corresponding simulation demonstration stage;

[0139] S3508, assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0140] In S3508, each time interval corresponds to a simulation demonstration stage, and the simulation configuration parameters corresponding to the simulation demonstration stage are assigned to the corresponding time interval;

[0141] S3509, generating a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage;

[0142] In S3509, the virtual camera shooting trajectory is a shooting movement trajectory of the running process of the running simulation model configured with simulation configuration parameters by using the virtual camera;

[0143] S3510, assigning the virtual camera shooting trajectory of each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0144] In S3510, similarly, the virtual camera shooting trajectory of each simulation demonstration stage is assigned to the corresponding time interval;

[0145] S3511. Different time intervals are assigned different simulation configuration parameters and an initial time axis of the virtual camera shooting trajectory as a simulation demonstration control time axis.

[0146] In S3511, when the simulation demonstration control timeline is in use, the progress pointer moves from the starting point of the simulation demonstration control timeline according to the actual speed of time passage. When entering a time interval, the running simulation model is simulated and configured based on the simulation configuration parameters assigned to the time interval. Then, based on the virtual camera shooting trajectory assigned to the time interval, the virtual camera is controlled to shoot the running process of the running simulation model, and the shooting picture is sent back to the second visualization interface for display in real time.

[0147] The embodiment of the present invention realizes the full automation of targeted simulation demonstration of simulation demonstration objects, which greatly improves the intelligence level of the system; introduces a standard semantic set, and quickly determines the applicable object determination rules, simulation demonstration expectations and simulation demonstration constraints based on the maximum matching degree and matching degree threshold between the standard semantic set and the semantic set, and determines the candidate experts, sets the target personnel conditions and determines the simulation demonstration stage in turn based on these three, which greatly improves the accuracy and efficiency of real-time attempts to determine multiple simulation demonstration objects among each expert and the simulation demonstration control timeline, and greatly improves the applicability of the system; sets the target personnel conditions to ensure the suitability of the simulation demonstration objects selected from multiple candidate experts, avoids targeted demonstrations to non-suitable experts and reduces the efficiency of optimizing control scheme decisions, and greatly improves the applicability of the system; secondly, introduces the virtual camera shooting trajectory, so that the simulation demonstration object can comprehensively and timely view the operation process of the running simulation model, which greatly improves the humanization level.

[0148] In one embodiment, the step S3509, generating a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage, includes:

[0149] S35091, traversing each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage;

[0150] S35092. During each traversal, determine a plurality of reaction areas after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured and a plurality of reaction contents of each reaction area;

[0151] In S35092, the simulation subject refers to the subject that generates the simulation reaction in the running simulation model, such as: the three-dimensional model of the permanent magnet synchronous motor; after the running simulation model is configured based on the simulation configuration parameters, the simulation subject will generate a simulation reaction, that is, generate multiple reaction areas and multiple reaction contents of each reaction area, such as: the simulation configuration parameters are parameters for simulating and demonstrating the operation of the motor under loads of different abnormalities, then the reaction areas are the motor running temperature rising area, the motor running efficiency decreasing area, the motor running electromagnetic interference area, etc., and the corresponding reaction content can be the motor running temperature rising curve, the motor running efficiency decreasing curve, etc.;

[0152] S35093. Planning a shooting position of a virtual camera in the running simulation model; wherein when the virtual camera is located at the shooting position and shoots the simulation subject, the entire reaction area can be clearly captured;

[0153] In S35093, clearly captured means that when the virtual camera captures the entire reaction area, all reaction contents are clearly presented;

[0154] S35094, generating shooting constraints of the shooting position;

[0155] In S35094, the shooting constraint is used to constrain how to shoot when the virtual camera is in the shooting position;

[0156] S35095, assigning shooting constraints to the shooting position to obtain the position to be put into orbit;

[0157] In S35095, after the shooting constraint is assigned to the shooting position, it is used as the waiting position to enter the orbit, waiting to enter the shooting trajectory of the virtual camera;

[0158] S35096, after each simulation demonstration stage is completed, the positions to be put into orbit obtained by each traversal are sequentially connected in the order of the traversal to obtain the shooting trajectory of the virtual camera;

[0159] In S35096, the positions to be placed on the orbit obtained in each traversal are connected in sequence according to the order of the traversal, and a straight line is used for connection;

[0160] The shooting constraints include:

[0161] Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area;

[0162] The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area;

[0163] The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set;

[0164] The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

[0165] In the shooting constraint, the virtual camera has a focus area when shooting, and the content in the focus area is displayed clearly in the shooting picture of the virtual camera, while the rest of the area is displayed blurred in the shooting picture of the virtual camera; first, the virtual camera is controlled to take the entire reflection area as the first focus area for the first shooting at the shooting position, so that the simulation demonstration object can globally understand the current simulation situation of the running simulation model. Each reaction content has a minimum reasonable reaction time, which is the minimum time required for the simulation demonstration object to basically understand the situation of the reaction content. For example, if the reaction content is the rising curve of the motor running temperature, the simulation demonstration object needs at least 5 minutes to observe the obvious rising trend of the curve, that is, the minimum reasonable reaction time is 5 minutes; the total number of each reflection area corresponds to a division coefficient, the value of the division coefficient is greater than 0 and less than 1, the simulation demonstration time is multiplied by the division coefficient to obtain the product and then rounded down to obtain the second target value; the time threshold takes the smaller value of the first target value and the second target value, so that the time threshold is set appropriately. At least two reaction contents are combined into a content set. If there is a corresponding time of the combined content set in the shooting time library of the traversed simulation demonstration stage, it is used as the target shooting time; the shooting time library contains the time of the reflection content in different content sets that the simulation demonstration object needs to focus on in the simulation demonstration stage, such as: the simulation demonstration stage is to simulate the overload operation of the motor, and the reflection content in the content set with the corresponding time is the motor operation temperature rise curve and the motor operation efficiency decrease curve; therefore, every time the target shooting time is entered, the virtual camera is controlled to take the reflection area where each reaction content in the content set corresponding to the target shooting time is located as the second focus area for the second shooting. The proportion threshold can be 50%; if the focus area changes too much, it may cause confusion or discomfort to the user, and frequent large changes or content jumps should be avoided. Therefore, the area proportion of the second focus area to the first focus area is always kept above the area proportion threshold.

[0166] When generating the shooting trajectory of the virtual camera in each simulation demonstration stage, the embodiment of the present invention first plans the shooting position of the virtual camera in the running simulation model, then generates the shooting constraints of the shooting position, and assigns the shooting constraints to the shooting position, which are sequentially connected as the positions to be put into orbit to obtain the shooting trajectory of the virtual camera, thereby greatly improving the generation efficiency of the shooting trajectory of the virtual camera and improving the subsequent level of the system; secondly, the shooting constraints can be used to appropriately control the virtual camera to switch different intersection areas at the shooting position, so as to continuously guide the simulation demonstration object to view the appropriate content at the appropriate time, thereby greatly improving the humanization level and the efficiency of each expert in making decisions on the optimization control scheme.

[0167] In one embodiment, after S37, based on the simulation demonstration control timeline, starting to perform corresponding simulation demonstration control on the running simulation model in the second visualization interface, the method further includes:

[0168] Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface;

[0169] Based on the interaction records, try to determine auxiliary knowledge in real time;

[0170] Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

[0171] The interaction record can be the operation type, operation timing, operation content, interface response, etc. of the running simulation model of the simulation demonstration in the second visual interface of the simulation demonstration object; the interaction record may reflect what kind of further assistance the simulation demonstration object needs, such as: when the user pauses for a long time at a certain step or repeatedly tries the same operation, the system can judge that the user may be confused about the operation or needs more guidance; therefore, based on its determination of auxiliary knowledge, the demonstration auxiliary knowledge can further assist the simulation demonstration object.

[0172] The embodiment of the present invention provides a visual optimization control management system for a permanent magnet synchronous motor. Figure 2 As shown, including:

[0173] A determination module 1 is used to determine a target operating condition to be optimized and controlled based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles;

[0174] A generation module 2, used to generate an operation simulation model of a target operation situation;

[0175] Auxiliary module 3, used to assist the expert group in making an optimal control plan for the target operation situation based on the operation simulation model visualization decision;

[0176] The upgrade module 4 is used to perform OTA upgrade on the permanent magnet synchronous motor based on an optimized control scheme.

[0177] The auxiliary module assists the expert group in optimizing the control scheme of the target operation situation based on the operation simulation model visualization decision, including:

[0178] Activate a first visualization interface for all experts in the expert group to jointly view the running simulation model;

[0179] When at least one expert starts to perform simulation demonstration control on the running simulation model in the first visual interface, continuously obtain the communication records between the experts within the most recent preset time;

[0180] Extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods;

[0181] Based on the trigger degree table, the trigger degree is determined according to the characteristic value set;

[0182] When the trigger degree exceeds the trigger degree threshold, based on the communication record, a plurality of simulation demonstration objects and a simulation demonstration control timeline among the experts are attempted to be determined in real time;

[0183] Whenever the attempt is determined to be successful, a second visualization interface is activated for each simulation demonstration object to view the running simulation model together;

[0184] Based on the simulation demonstration control timeline, start to perform corresponding simulation demonstration control on the running simulation model in the second visual interface;

[0185] Receive the optimal control plan based on the final decision of each expert.

[0186] The auxiliary module attempts to determine multiple simulation demonstration objects and simulation demonstration control timelines among the experts in real time based on the communication records, including:

[0187] Extract semantics from communication records to obtain semantic sets;

[0188] Match the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree;

[0189] When the maximum matching degree exceeds the matching degree threshold, the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set are obtained;

[0190] Based on the object determination rule, multiple candidate experts are determined from among the experts according to their expert portraits;

[0191] When multiple candidate experts meet the target personnel conditions, an attempt is made to determine success, and each candidate expert meeting the target personnel conditions is used as a plurality of simulation demonstration objects; wherein the target personnel conditions include: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer;

[0192] Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters;

[0193] Based on the sequence of each simulation demonstration stage and the duration of each simulation demonstration, the time interval of each simulation demonstration stage is divided on the initial time axis;

[0194] Assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0195] Based on the simulation configuration parameters corresponding to each simulation demonstration stage, a virtual camera shooting trajectory of each simulation demonstration stage is generated;

[0196] Assigning the shooting trajectory of the virtual camera in each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage;

[0197] Different time intervals are assigned different simulation configuration parameters and the initial timeline of the virtual camera shooting trajectory is used as the simulation demonstration control timeline.

[0198] The auxiliary module generates a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage, including:

[0199] Traverse each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage;

[0200] During each traversal, a plurality of reaction areas and a plurality of reaction contents of each reaction area after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured are determined;

[0201] Planning the shooting position of the virtual camera in the running simulation model; wherein, when the virtual camera is located at the shooting position to shoot the simulation subject, the entire reaction area can be clearly captured;

[0202] Generate shooting constraints for shooting positions;

[0203] Assign shooting constraints to the shooting position to obtain the position to be put into orbit;

[0204] After each simulation demonstration phase is completed, the positions to be put into orbit obtained by each traversal are connected in sequence according to the order of traversal to obtain the shooting trajectory of the virtual camera;

[0205] The shooting constraints include:

[0206] Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area;

[0207] The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area;

[0208] The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set;

[0209] The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

[0210] After the auxiliary module starts to perform corresponding simulation demonstration control on the running simulation model in the second visual interface based on the simulation demonstration control timeline, it also performs the following operations:

[0211] Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface;

[0212] Based on the interaction records, try to determine auxiliary knowledge in real time;

[0213] Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

[0214] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A visual optimization control management method for a permanent magnet synchronous motor, characterized in that: include: Based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles, determine the target operating conditions to be optimized and controlled; Generate an operational simulation model of the target operational scenario; Assist the expert group to visualize the decision-making target operation situation based on the operation simulation model to optimize the control plan; Based on the optimized control scheme, OTA upgrade of permanent magnet synchronous motor is carried out; The auxiliary expert group makes an optimal control plan for the target operation situation based on the operation simulation model visualization decision, including: Activate a first visualization interface for all experts in the expert group to jointly view the running simulation model; When at least one expert starts to perform simulation demonstration control on the running simulation model in the first visual interface, continuously obtain the communication records between the experts within the most recent preset time; Extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods; Based on the trigger degree table, the trigger degree is determined according to the characteristic value set; When the trigger degree exceeds the trigger degree threshold, based on the communication record, a plurality of simulation demonstration objects and a simulation demonstration control timeline among the experts are attempted to be determined in real time; Whenever the attempt is determined to be successful, a second visualization interface is activated for each simulation demonstration object to view the running simulation model together; Based on the simulation demonstration control timeline, start to perform corresponding simulation demonstration control on the running simulation model in the second visual interface; Receive the optimal control plan based on the final decision of each expert.

2. The visual optimization control management method of a permanent magnet synchronous motor according to claim 1, characterized in that: The method of trying to determine multiple simulation demonstration objects and simulation demonstration control timelines among various experts in real time based on the communication records includes: Extract semantics from communication records to obtain semantic sets; Match the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree; When the maximum matching degree exceeds the matching degree threshold, the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set are obtained; Based on the object determination rule, multiple candidate experts are determined from among the experts according to their expert portraits; When multiple candidate experts meet the target personnel conditions, an attempt is made to determine success, and each candidate expert meeting the target personnel conditions is used as a plurality of simulation demonstration objects; wherein the target personnel conditions include: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer; Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters; Based on the sequence of each simulation demonstration stage and the duration of each simulation demonstration, the time interval of each simulation demonstration stage is divided on the initial time axis; Assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage; Based on the simulation configuration parameters corresponding to each simulation demonstration stage, a virtual camera shooting trajectory of each simulation demonstration stage is generated; Assigning the shooting trajectory of the virtual camera in each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage; Different time intervals are assigned different simulation configuration parameters and the initial timeline of the virtual camera shooting trajectory is used as the simulation demonstration control timeline.

3. The visual optimization control management method of a permanent magnet synchronous motor according to claim 2, characterized in that: The generating of the virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage includes: Traverse each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage; During each traversal, a plurality of reaction areas and a plurality of reaction contents of each reaction area after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured are determined; Planning the shooting position of the virtual camera in the running simulation model; wherein, when the virtual camera is located at the shooting position to shoot the simulation subject, the entire reaction area can be clearly captured; Generate shooting constraints for shooting positions; Assign shooting constraints to the shooting position to obtain the position to be put into orbit; After each simulation demonstration phase is completed, the positions to be put into orbit obtained by each traversal are connected in sequence according to the order of traversal to obtain the shooting trajectory of the virtual camera; The shooting constraints include: Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area; The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area; The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set; The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

4. The visual optimization control management method of a permanent magnet synchronous motor according to claim 1, characterized in that: After starting to perform corresponding simulation demonstration control on the running simulation model in the second visualization interface based on the simulation demonstration control timeline, the method further includes: Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface; Based on the interaction records, try to determine auxiliary knowledge in real time; Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

5. A visual optimization control management system for a permanent magnet synchronous motor, characterized in that: include: A determination module is used to determine a target operating condition to be optimized based on a large amount of operating big data of permanent magnet synchronous motors of new energy vehicles; A generation module, used for generating an operation simulation model of a target operation situation; Auxiliary module, used to assist the expert group in making optimal control plans for target operation situations based on the operation simulation model visualization decision; Upgrade module, used to perform OTA upgrade of permanent magnet synchronous motor based on optimized control scheme; The auxiliary module assists the expert group in optimizing the control scheme of the target operation situation based on the operation simulation model visualization decision, including: Activate a first visualization interface for all experts in the expert group to jointly view the running simulation model; When at least one expert starts to perform simulation demonstration control on the running simulation model in the first visual interface, continuously obtain the communication records between the experts within the most recent preset time; Extracting feature values ​​from the communication records to obtain a feature value set; wherein the feature value set includes: the number of conversations in the communication records, the number of people in the conversations, and the overlapping duration of the conversation time periods; Based on the trigger degree table, the trigger degree is determined according to the characteristic value set; When the trigger degree exceeds the trigger degree threshold, based on the communication record, a plurality of simulation demonstration objects and a simulation demonstration control timeline among the experts are attempted to be determined in real time; Whenever the attempt is determined to be successful, a second visualization interface is activated for each simulation demonstration object to view the running simulation model together; Based on the simulation demonstration control timeline, start to perform corresponding simulation demonstration control on the running simulation model in the second visual interface; Receive the optimal control plan based on the final decision of each expert.

6. The visual optimization control management system for a permanent magnet synchronous motor according to claim 5, characterized in that: The auxiliary module attempts to determine multiple simulation demonstration objects and simulation demonstration control timelines among the experts in real time based on the communication records, including: Extract semantics from communication records to obtain semantic sets; Match the semantic set with multiple standard semantic sets in the standard semantic set library respectively to obtain the maximum matching degree; When the maximum matching degree exceeds the matching degree threshold, the object determination rule, simulation demonstration expectation and simulation demonstration constraint of the standard semantic set with the maximum matching degree between the semantic set are obtained; Based on the object determination rule, multiple candidate experts are determined from among the experts according to their expert portraits; When multiple candidate experts meet the target personnel conditions, an attempt is made to determine success, and each candidate expert meeting the target personnel conditions is used as a plurality of simulation demonstration objects; wherein the target personnel conditions include: the demonstration expectation and the candidate expert's most recent N historical simulation demonstration expectations each have at least one expected correlation relationship; N is a positive integer; Based on the simulation demonstration constraints, determine multiple groups of one-to-one corresponding simulation demonstration stages, simulation demonstration durations, and simulation configuration parameters; Based on the sequence of each simulation demonstration stage and the duration of each simulation demonstration, the time interval of each simulation demonstration stage is divided on the initial time axis; Assigning the simulation configuration parameters corresponding to each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage; Based on the simulation configuration parameters corresponding to each simulation demonstration stage, a virtual camera shooting trajectory of each simulation demonstration stage is generated; Assigning the shooting trajectory of the virtual camera in each simulation demonstration stage to the time interval corresponding to each simulation demonstration stage; Different time intervals are assigned different simulation configuration parameters and the initial timeline of the virtual camera shooting trajectory is used as the simulation demonstration control timeline.

7. The visual optimization control management system for a permanent magnet synchronous motor according to claim 6, characterized in that: The auxiliary module generates a virtual camera shooting trajectory of each simulation demonstration stage based on the simulation configuration parameters corresponding to each simulation demonstration stage, including: Traverse each simulation demonstration stage in sequence according to the stage sequence of each simulation demonstration stage; During each traversal, a plurality of reaction areas and a plurality of reaction contents of each reaction area after the simulation configuration parameters corresponding to the simulation demonstration stage traversed by the simulation subject in the running simulation model are configured are determined; Planning the shooting position of the virtual camera in the running simulation model; wherein, when the virtual camera is located at the shooting position to shoot the simulation subject, the entire reaction area can be clearly captured; Generate shooting constraints for shooting positions; Assign shooting constraints to the shooting position to obtain the position to be put into orbit; After each simulation demonstration phase is completed, the positions to be put into orbit obtained by each traversal are connected in sequence according to the order of traversal to obtain the shooting trajectory of the virtual camera; The shooting constraints include: Controlling the virtual camera to perform a first shooting at a shooting position with the entire reflection area as a first focus area, and when the duration of the first shooting exceeds a duration threshold, whenever a target shooting time is reached, controlling the virtual camera to perform a second shooting with the reflection area where each reaction content in the content set corresponding to the target shooting time is located as a second focus area; The duration threshold is the smaller value between the first target value and the second target value; the first target value is the minimum required duration of each reaction content; the second target value is the rounded-down value of the simulation demonstration duration corresponding to the traversed simulation demonstration stage multiplied by the division coefficient corresponding to the total number of each reaction area; The content set includes: at least two reaction contents; the target shooting timing is the corresponding timing in the shooting timing library of the simulated demonstration stage traversed by the content set; The area ratio of the second focus area to the first focus area exceeds the area ratio threshold.

8. The visual optimization control management system for a permanent magnet synchronous motor according to claim 5, characterized in that: After the auxiliary module starts to perform corresponding simulation demonstration control on the running simulation model in the second visual interface based on the simulation demonstration control timeline, it also performs the following operations: Continuously obtaining the interaction record between each simulation demonstration object and the running simulation model of the simulation demonstration in the second visualization interface; Based on the interaction records, try to determine auxiliary knowledge in real time; Whenever the attempt is determined to be successful, the second visual interface is controlled to start demonstrating auxiliary knowledge.

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