CN118769935B - An intelligent anti-interference wireless charging school bus control system and method based on AI large model analysis - Google Patents
An intelligent anti-interference wireless charging school bus control system and method based on AI large model analysis Download PDFInfo
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Abstract
本发明提出了一种基于AI大模型分析的智能抗干扰无线充电校车控制系统及方法，属于无线充电控制领域，包括：无线充电控制单元，其配置为采用恒压滤波级联自抗扰控制策略对校车进行无线充电；数据采集与传输单元，其配置为实时收集校车运行数据，并将校车运行数据传输至中央数据处理平台进行数据处理；人工智能分析单元，其配置为基于AI大模型对数据处理后的校车运行数据进行多维度分析，并生成智能调度策略；云端应用接口，其配置为将智能调度策略和数据处理后的校车运行数据传输至移动终端，操作人员通过移动终端进行实时查询和使用；智能调度执行单元，其配置为将智能调度策略传输给校车驾驶员，校车驾驶员根据智能调度策略进行资源分配。本申请有效抑制充电过程中的干扰和波动，并对校车运行数据进行智能化分析，实现实时动态调度，提高了校车运营效率，优化资源分配。
The present invention proposes an intelligent anti-interference wireless charging school bus control system and method based on AI large model analysis, which belongs to the field of wireless charging control, including: a wireless charging control unit, which is configured to use a constant voltage filter cascade self-anti-interference control strategy to wirelessly charge the school bus; a data acquisition and transmission unit, which is configured to collect school bus operation data in real time, and transmit the school bus operation data to a central data processing platform for data processing; an artificial intelligence analysis unit, which is configured to perform multi-dimensional analysis on the school bus operation data after data processing based on the AI large model, and generate an intelligent scheduling strategy; a cloud application interface, which is configured to transmit the intelligent scheduling strategy and the school bus operation data after data processing to a mobile terminal, and the operator performs real-time query and use through the mobile terminal; an intelligent scheduling execution unit, which is configured to transmit the intelligent scheduling strategy to the school bus driver, and the school bus driver allocates resources according to the intelligent scheduling strategy. This application effectively suppresses interference and fluctuations during the charging process, and performs intelligent analysis on the school bus operation data, realizes real-time dynamic scheduling, improves the school bus operation efficiency, and optimizes resource allocation.
Description
Technical Field
The invention relates to the technical field of wireless charging control, in particular to an intelligent anti-interference wireless charging school bus control system and method based on AI large model analysis.
Background
Along with the development and application of science and technology and the continuous expansion of the area of university campuses in recent years, in order to improve the travel convenience of university campuses, it is necessary to put in the school bus at universities. However, for the existing school buses, the phenomenon that the school buses in the campus cannot be allocated in time in part of the peak period to cause the congestion of the campus part occurs, so that reasonable and efficient resource allocation is necessary.
However, in the prior art, the existing wireless charging system is easy to receive external electromagnetic interference in the charging process, the charging efficiency and the charging stability are affected, because a large amount of electronic equipment and wireless signals exist in a campus, the influence on the school bus is particularly obvious, and the school bus scheduling system often operates in a fixed route and schedule mode, is inflexible when dealing with the sudden demand in the peak period, and easily causes that the school bus in some areas is not supplied and is not required, and the school bus in other areas is idle, so that the resource waste and the traffic jam are caused.
Therefore, finding a method which can not only wirelessly charge a school bus and improve the anti-interference capability in the charging process, but also scientifically and efficiently allocate the school bus is a technical problem to be solved by the person skilled in the art.
Disclosure of Invention
In view of the above, the invention provides an intelligent anti-interference wireless charging school bus control system and method based on AI large model analysis, which can effectively inhibit interference and fluctuation in the charging process, and conduct intelligent analysis on school bus operation data, so as to realize real-time dynamic scheduling, improve school bus operation efficiency, optimize resource allocation and improve service quality.
The technical scheme of the invention is realized as follows:
In a first aspect, the invention provides an intelligent anti-interference wireless charging school bus control system based on AI large model analysis, comprising:
The wireless charging control unit is configured to comprise a primary side circuit, a secondary side circuit and a constant voltage filtering cascade active disturbance rejection control strategy, and is used for wirelessly charging the school bus, wherein the constant voltage filtering cascade active disturbance rejection control strategy comprises a first-stage active disturbance rejection controller, a second-stage active disturbance rejection controller and a Butterworth filter;
The data acquisition and transmission unit is configured to collect the school bus operation data in real time and transmit the school bus operation data to the central data processing platform for data processing;
the artificial intelligent analysis unit is configured to carry out multidimensional analysis on the school bus operation data after data processing based on the AI large model and generate an intelligent scheduling strategy;
the cloud application interface is configured to transmit the intelligent scheduling strategy and the school bus operation data after data processing to the mobile terminal, and operators inquire and use the school bus operation data in real time through the mobile terminal;
And the intelligent dispatching execution unit is configured to transmit the intelligent dispatching strategy to a school bus driver, and the school bus driver performs resource allocation according to the intelligent dispatching strategy.
On the basis of the above technical solution, preferably, the constant voltage filtering cascade active disturbance rejection control strategy specifically includes:
The primary active disturbance rejection controller processes the output voltage of a DC-DC circuit in a secondary side circuit after the DC-DC circuit passes through a Butterworth filter, wherein the secondary side circuit comprises a rectification output circuit and a DC-DC circuit;
the second-stage active disturbance rejection controller processes the output voltage of the secondary side DC-DC circuit;
And combining the Butterworth filter, the first-stage active disturbance rejection controller, the second-stage active disturbance rejection controller and the secondary DC-DC circuit into a new composite cascade system to obtain a constant-voltage filtering cascade active disturbance rejection control strategy.
On the basis of the technical proposal, preferably, the first-stage active disturbance rejection controller comprises a first-stage linear expansion state observer, a first state feedback controller, a first disturbance compensator and a first control rate generator, wherein,
The two ends of the first-stage linear expansion state observer are respectively connected with the Butterworth filter and the first state feedback controller, the other end of the first state feedback controller is connected with the first end of the first control rate generator, the second end of the first control rate generator is connected with the first disturbance compensator, the first disturbance compensator is also connected with the second disturbance compensator, and the calculation formula of the first-stage active disturbance rejection controller is as follows:
Wherein, Representing the change in state variable in the first stage linear extended state observer, a represents the state matrix,B represents an input matrix, b= [ 0B 0 0]T,b0 ] represents the gain of the second stage active-disturbance-rejection controller, L represents a bandwidth parameter, y q represents the input of the butterworth filter,Representing observations of the first stage active disturbance rejection controller, C 1 representing the mapping of z 1 to the output of the secondary side circuit, z 1 representing the state vector of the first stage linear extended state observer,Represents the acceleration of the output of the butterworth filter, d q represents the total disturbance of the butterworth filter, b 1 represents the control gain of the wireless charging unit,And represents the output of the first control rate generator, n being the noise disturbance.
On the basis of the technical scheme, preferably, the second-stage active disturbance rejection controller comprises a second-stage linear expansion state observer, a second state feedback controller, a second disturbance compensator and a second control rate generator, wherein,
The two ends of the second-stage linear expansion state observer are respectively connected with a DC-DC circuit of the secondary side circuit and a second state feedback controller, the other end of the second state feedback controller is connected with the first end of a second control rate generator, the second end of the second control rate generator is connected with a second disturbance compensator, the second disturbance compensator is connected with the secondary side circuit through PWM, and the calculation formula of the second-stage active disturbance rejection controller is as follows:
Wherein, Representing the change in state variable in the second stage linear extended state observer, z 2 represents the state vector of the second stage linear extended state observer, p f represents the output noise of the secondary side circuit,Representing observations of the second stage active-disturbance-rejection controller,Representing the output of the second control rate generator, C 2 representing the output mapping z 2 to the secondary circuit, and y 2 representing the actual output of the second stage active-disturbance-rejection controller.
On the basis of the above technical solution, preferably, the calculation formula of the constant voltage filtering cascade active disturbance rejection control strategy is:
Wherein, Representing the rate of change of z, z representing the state vector of the constant voltage filter cascade active disturbance rejection control strategy, u representing the input of the constant voltage filter cascade active disturbance rejection control strategy, y representing the actual output of the constant voltage filter cascade active disturbance rejection control strategy,Represents the estimated output of the constant voltage filter cascade active disturbance rejection control strategy, k p represents the proportional gain parameter of the first stage active disturbance rejection controller,Representing the state variable of z 1 through the Butterworth filter, z '1、z'2 and z' 3 representing three components of z, respectively, k 2 representing the differential gain parameter of the first stage self-antiwind controller, k 3 representing the disturbance compensation gain parameter of the first stage self-antiwind controller,Representing the time derivative of z q, a q represents the state matrix of the cascade system, wherein the cascade system comprises a first stage active-disturbance-rejection controller and a second stage active-disturbance-rejection controller, B q represents the input matrix of the cascade system, u q represents the control input of the cascade system, L 1 represents the observer gain matrix of the cascade system,Representing the estimated output of the cascade system, y q representing the actual output of the cascade system, z q representing the state vector of the cascade system, b 1 representing the control gain of the cascade system,Representing the proportional gain parameter of the cascade system, v r represents the reference input,AndThree components of z q are represented, k 4 represents a differential gain parameter of the cascade system, and k 5 represents a disturbance compensation gain parameter of the cascade system
Still further preferably, the school bus operation data includes card swiping data and vehicle data, wherein the card swiping data includes card swiping time, card swiping place and card swiping type, and the vehicle data includes the number of persons in the bus, the distance between front and rear school buses, the number of persons in front and rear school buses, the number of persons on average on-board at a lower station in a near term and the number of persons on board at a lower station at a front school.
On the basis of the above technical solution, preferably, the multidimensional analysis includes:
transferring the processed school bus operation data to a high-dimensional feature space through mapping, and extracting key features of the data;
setting analysis dimensions, and creating a dimension prompt for each analysis dimension;
And carrying out deep analysis on the key features and the dimension prompts of the data by using the AI large model, and summarizing the analysis results of each dimension to obtain the current school bus operation analysis result.
In a second aspect, the invention provides an intelligent anti-interference control wireless charging school bus method based on AI large model analysis, which is applied to the intelligent anti-interference wireless charging school bus control system, and comprises the following steps:
s1, taking output voltage in a charging process as a control variable, and setting the voltage as an input variable;
S2, designing a first-stage active disturbance rejection controller and a second-stage active disturbance rejection controller, and combining a first-stage Butterworth filter, a constant-voltage filtering cascade active disturbance rejection controller and a secondary DC-DC circuit of a wireless charging unit into a constant-voltage filtering cascade active disturbance rejection control strategy;
s3, wirelessly charging the school bus by using a constant-voltage filtering cascade active disturbance rejection control strategy;
s4, collecting school bus operation data in real time, and transmitting the school bus operation data to a central data processing platform for data processing;
S5, carrying out multidimensional analysis on the school bus operation data after data processing based on the AI large model, and generating an intelligent scheduling strategy;
s6, transmitting the intelligent scheduling strategy and the school bus operation data after data processing to the mobile terminal, and inquiring and using an operator in real time through the mobile terminal;
And S7, transmitting the intelligent scheduling strategy to a school bus driver, and performing resource allocation by the school bus driver according to the intelligent scheduling strategy.
In a third aspect, the invention provides an electronic device comprising at least one processor, at least one memory, a communication interface, and a bus, wherein,
The processor, the memory and the communication interface complete the communication with each other through the bus;
the memory stores program instructions executable by the processor, and the processor invokes the program instructions to implement the intelligent anti-interference wireless charging school bus control system.
In a fourth aspect, the present invention provides a computer readable storage medium storing computer instructions that cause the computer to implement the intelligent anti-interference wireless charging school bus control system as described above.
Compared with the prior art, the intelligent anti-interference wireless charging school bus control system has the following beneficial effects:
(1) The interference and fluctuation in the charging process are effectively restrained through a constant-voltage filtering cascade active disturbance rejection control strategy, the robustness of wireless charging is improved by using a first-stage active disturbance rejection controller and a second-stage active disturbance rejection controller, the charging efficiency is improved, intelligent analysis is carried out on the operation data of the school bus, real-time dynamic scheduling is realized, the operation efficiency of the school bus is improved, the resource allocation is optimized, and the service quality is improved;
(2) The constant voltage filtering cascade active disturbance rejection control strategy is utilized to monitor parameters such as input voltage, output voltage, charging current and the like in real time, stability of the output voltage is ensured, constant and reliable charging voltage is provided for a school bus, the Butterworth filter is utilized to effectively filter high-frequency noise, anti-disturbance capacity of a wireless charging unit is improved, and interruption or efficiency reduction of a charging process is reduced.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an intelligent anti-jamming wireless charging school bus control system of the present invention;
FIG. 2 is a block diagram of a first level active disturbance rejection controller of the intelligent anti-disturbance wireless charging school bus control system of the present invention;
FIG. 3 is a schematic diagram of a school bus flow for the intelligent anti-interference wireless charging school bus control method of the invention;
FIG. 4 is a flow chart of the intelligent anti-interference wireless charging school bus control method of the invention;
FIG. 5 is a flow chart diagram of an intelligent anti-interference wireless charging school bus control method of the invention;
Fig. 6 is a comparative simulation output diagram of the intelligent anti-interference wireless charging school bus control method of the invention.
Detailed Description
The following description of the embodiments of the present invention will clearly and fully describe the technical aspects of the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
As shown in fig. 1, the invention provides an intelligent anti-interference wireless charging school bus control system based on AI large model analysis, comprising:
The wireless charging control unit is configured to comprise a primary side circuit, a secondary side circuit and a constant voltage filtering cascade active disturbance rejection control strategy, and is used for wirelessly charging the school bus by adopting the constant voltage filtering cascade active disturbance rejection control (FCLADRC) strategy, wherein the constant voltage filtering cascade active disturbance rejection control (FCLADRC) strategy comprises a first-stage active disturbance rejection controller, a second-stage active disturbance rejection controller and a Butterworth filter.
The primary side circuit receives an alternating current power supply and converts the alternating current power supply into a high-frequency alternating current, the high-frequency alternating current generates an alternating magnetic field through a primary side coil, the secondary side circuit converts the induced alternating current into a direct current through a rectifying circuit after receiving the induced alternating current, the direct current subjected to rectification filtering is subjected to voltage regulation to a level required by a school bus through a DC-DC conversion circuit, and the regulated direct current is used for supplying power to a school bus battery or a motor system through a constant voltage filtering cascade active disturbance rejection control strategy.
The cascade active disturbance rejection control system based on the constant voltage filtering can not only improve the charging response time of the system, but also well inhibit external disturbance, when the rated voltage is changed, the set voltage can be recovered more quickly, the school bus can be charged wirelessly when reaching the designated position, the operation of the school bus is satisfied by the wireless charging, and meanwhile, the electric energy received by the wireless charging can also be supplied to the operation of the school bus card swiping system.
In an embodiment of the present application, the constant voltage filtering cascade active disturbance rejection control strategy specifically includes:
The primary active disturbance rejection controller processes the output voltage of a DC-DC circuit in a secondary side circuit after the DC-DC circuit passes through a Butterworth filter, wherein the secondary side circuit comprises a rectification output circuit and a DC-DC circuit;
the second-stage active disturbance rejection controller processes the output voltage of the secondary side DC-DC circuit;
And combining the Butterworth filter, the first-stage active disturbance rejection controller, the second-stage active disturbance rejection controller and the secondary DC-DC circuit into a new composite cascade system to obtain a constant-voltage filtering cascade active disturbance rejection control strategy.
The first-stage active disturbance rejection controller receives the secondary side output voltage processed by the Butterworth filter and generates a control signal to adjust primary side circuit parameters, the second-stage active disturbance rejection controller receives the output voltage of the DC-DC circuit and generates a control signal to adjust DC-DC circuit parameters, and the Butterworth filter is used for filtering high-frequency noise of the secondary side circuit to enhance the anti-disturbance capability.
It can be understood that the constant voltage filtering cascade active disturbance rejection control based on the application solves the problem of amplitude and phase loss caused by using a filter while filtering the system output ripple, and effectively improves the performance of each aspect of the control system.
The parameters of the primary side circuit and the secondary side circuit are dynamically adjusted according to monitoring results by utilizing a constant-voltage filtering cascade active disturbance rejection control strategy to monitor parameters such as input voltage, output voltage and charging current in real time, stability of the output voltage is ensured, constant and reliable charging voltage is provided for a school bus, high-frequency noise is effectively filtered by utilizing a Butterworth filter, anti-disturbance capability of a wireless charging unit is improved, and interruption or efficiency reduction of the charging process is reduced.
Further, the first-stage active disturbance rejection controller comprises a first-stage linear extended state observer, a first state feedback controller, a first disturbance compensator and a first control rate generator, wherein,
The two ends of the first-stage linear expansion state observer are respectively connected with the Butterworth filter and the first state feedback controller, the other end of the first state feedback controller is connected with the first end of the first control rate generator, the second end of the first control rate generator is connected with the first disturbance compensator, the first disturbance compensator is also connected with the second disturbance compensator, and the calculation formula of the first-stage active disturbance rejection controller is as follows:
Wherein, Representing the change in state variable in the first stage linear extended state observer, a represents the state matrix,B represents an input matrix, b= [ 0B 0 0]T,b0 ] represents the gain of the second stage active-disturbance-rejection controller, L represents a bandwidth parameter, y q represents the input of the butterworth filter,Representing observations of the first stage active disturbance rejection controller, C 1 representing the mapping of z 1 to the output of the secondary side circuit, z 1 representing the state vector of the first stage linear extended state observer,Represents the acceleration of the output of the butterworth filter, d q represents the total disturbance of the butterworth filter, b 1 represents the control gain of the wireless charging unit,And represents the output of the first control rate generator, n being the noise disturbance.
Further, the second-stage active disturbance rejection controller comprises a second-stage linear extended state observer, a second state feedback controller, a second disturbance compensator and a second control rate generator, wherein,
The two ends of the second-stage linear expansion state observer are respectively connected with a DC-DC circuit of the secondary side circuit and a second state feedback controller, the other end of the second state feedback controller is connected with the first end of a second control rate generator, the second end of the second control rate generator is connected with a second disturbance compensator, the second disturbance compensator is connected with the secondary side circuit through PWM, and the calculation formula of the second-stage active disturbance rejection controller is as follows:
Wherein, Representing the change in state variable in the second stage linear extended state observer, z 2 represents the state vector of the second stage linear extended state observer, p f represents the output noise of the secondary side circuit,Representing observations of the second stage active-disturbance-rejection controller,Representing the output of the second control rate generator, C 2 representing the output mapping z 2 to the secondary circuit, and y 2 representing the actual output of the second stage active-disturbance-rejection controller.
As shown in fig. 2, fig. 2 is a block diagram of a first stage active-disturbance-rejection controller. The first-stage active-disturbance-rejection controller also comprises a Linear Tracking Differentiator (LTD) and a Linear State Error Feedback (LSEF), a smooth reference signal is generated by using the LTD, the control law is calculated by using the output of the LESO LSEF, the control signal acts on a controlled object after being normalized by 1/b_0, and meanwhile, external disturbance acts on the controlled object, so that the first-stage active-disturbance-rejection controller estimates and compensates disturbance in real time, and the anti-disturbance capability and control precision of the system are improved.
In an embodiment of the present application, the structural block diagram of the first-stage active-disturbance-rejection controller is the same as the structural block diagram of the second-stage active-disturbance-rejection controller.
In an embodiment of the present application, a calculation formula of the first control rate generator is:
u0＝kp(vr-z1)-kdz2
Where u 0 denotes an output signal of the first control rate generator, k p denotes a proportional gain parameter of the first control rate generator, v r denotes a reference value, and k d denotes a differential gain coefficient of the first control rate generator.
It is understood that the second control rate generator is the same as the first control rate generator, and thus will not be described in detail.
In an embodiment of the present application, an output variable of the butterworth filter is defined as x q＝yq, and the butterworth filter and the secondary circuit form a first composite cascade system, and a calculation formula of the first composite cascade system is as follows:
yq＝xq
Where x q denotes the output of the butterworth filter, f q denotes a nonlinear function, The acceleration of x q is indicated,Representing the speed of x q, y representing the output number of the first composite cascade system,Representing the total disturbance of the first composite cascode system, u representing the input of the first composite cascode system,Representing observations of the butterworth filter, y q representing the output of the first complex cascade system after filtering.
Order theThe expanded state space equation for the first composite cascade system is:
y=Cx+n
yq＝Cxq
Wherein A q represents a state matrix of a cascade system, wherein the cascade system comprises a first-stage active-disturbance-rejection controller and a second-stage active-disturbance-rejection controller, B q represents an input matrix of the cascade system, S q represents a disturbance input matrix of the cascade system, H represents a disturbance of a Butterworth filter, The rate of change of the secondary circuit state variable is represented by P, the disturbance of the secondary circuit is represented by S, and the effect of the disturbance on the secondary circuit is represented by S.
Furthermore, the calculation formula of the constant voltage filtering cascade active disturbance rejection control strategy is as follows:
Wherein, Representing the rate of change of z, z representing the state vector of the constant voltage filter cascade active disturbance rejection control strategy, u representing the input of the constant voltage filter cascade active disturbance rejection control strategy, y representing the actual output of the constant voltage filter cascade active disturbance rejection control strategy,Represents the estimated output of the constant voltage filter cascade active disturbance rejection control strategy, k p represents the proportional gain parameter of the first stage active disturbance rejection controller,Representing the state variable of z 1 through the Butterworth filter, z '1、z'2 and z' 3 representing three components of z, respectively, k 2 representing the differential gain parameter of the first stage self-antiwind controller, k 3 representing the disturbance compensation gain parameter of the first stage self-antiwind controller,Representing the time derivative of z q, a q represents the state matrix of the cascade system, wherein the cascade system comprises a first stage active-disturbance-rejection controller and a second stage active-disturbance-rejection controller, B q represents the input matrix of the cascade system, u q represents the control input of the cascade system, L 1 represents the observer gain matrix of the cascade system,Representing the estimated output of the cascade system, y q representing the actual output of the cascade system, z q representing the state vector of the cascade system, b 1 representing the control gain of the cascade system,Representing the proportional gain parameter of the cascade system, v r represents the reference input,AndThree components of z q are represented, k 4 represents a differential gain parameter of the cascade system, and k 5 represents a disturbance compensation gain parameter of the cascade system.
The system comprises a data acquisition and transmission unit, a central data processing platform and a data processing unit, wherein the data acquisition and transmission unit is configured to collect school bus operation data in real time and transmit the school bus operation data to the central data processing platform for data processing, the school bus operation data comprise card swiping data and vehicle data, the card swiping data comprise card swiping time, card swiping places and card swiping types, and the vehicle data comprise the number of people in a bus, the distance between front and rear school buses, the number of people in front and rear school buses, the number of people on a lower station in the near term average in a time interval and the number of people on a lower station in the front school.
And the artificial intelligent analysis unit is configured to carry out multidimensional analysis on the school bus operation data after the data processing based on the AI large model and generate an intelligent scheduling strategy.
Specifically, the multi-dimensional analysis includes:
transferring the processed school bus operation data to a high-dimensional feature space through mapping, and extracting key features of the data;
setting analysis dimensions, and creating a dimension prompt for each analysis dimension;
And carrying out deep analysis on the key features and the dimension prompts of the data by using the AI large model, and summarizing the analysis results of each dimension to obtain the current school bus operation analysis result.
As shown in FIG. 3, the artificial intelligence analysis unit is further described in one embodiment:
Designing special dimension prompts such as departure and dispatch based on different scenes;
Generating training data by using the quantization index and the professional labeling mode, wherein the training data comprises actual situation description and decision suggestion;
Mapping school bus operation data to a high-dimensional feature space, and extracting key features such as vehicle spacing, passenger number, station requirements and the like;
setting analysis dimensions such as departure decision dimension, vehicle scheduling dimension, passenger demand prediction dimension and operation efficiency optimization dimension;
For each dimension, analysis is performed using trained AI models, such as for departure decisions:
the input is { "distance before car": 3, "number of running vehicles": 2, "number of people in car average": 10, "number of stations with high demand": 4, "number of people on car average": 5};
The output is that the departure is recommended, the reason is that stations with high demands are more, and the distance between the vehicles ahead is longer;
and (3) synthesizing analysis results of all dimensions to generate a scheduling strategy, such as { "departure decision": "immediate departure", "route suggestion": "focus on station 3 and station 5", "vehicle speed suggestion": "keep normal speed" }.
In an embodiment of the application, the language understanding capability of the AI large model in the nlp field is reserved by using the Lora fine tuning mode when the AI large model is trained, and the decision capability of the AI large model in the vertical field of school bus scheduling planning is enhanced. And determining a super-parameter initial value of AI large model fine tuning, wherein the default parameters are training round number=2, gradient accumulated step number=1, learning rate=0.00001, batch=8, withdrawal length=2048 and verification set proportion=0.1.
The cloud application interface is configured to transmit the intelligent scheduling strategy and the school bus operation data after data processing to the mobile terminal, and operators inquire and use the school bus operation data in real time through the mobile terminal;
And the intelligent dispatching execution unit is configured to transmit the intelligent dispatching strategy to a school bus driver, and the school bus driver performs resource allocation according to the intelligent dispatching strategy.
In an embodiment of the application, when each station stops in the running process of the school bus, the current data are synchronized, and the intelligent scheduling strategy is returned to the school bus driver in the form of voice report or message.
According to the application, interference and fluctuation in the charging process are effectively inhibited through the constant-voltage filtering cascade active disturbance rejection control strategy, the robustness of wireless charging is improved by using the first-stage active disturbance rejection controller and the second-stage active disturbance rejection controller, the charging efficiency is improved, intelligent analysis is carried out on the operation data of the school bus, real-time dynamic scheduling is realized, the operation efficiency of the school bus is improved, the resource allocation is optimized, and the service quality is improved.
As shown in fig. 4 and 5, the invention provides an intelligent anti-interference control wireless charging school bus method based on AI large model analysis, which is applied to the intelligent anti-interference wireless charging school bus control system, and comprises the following steps:
s1, taking output voltage in a charging process as a control variable, and setting the voltage as an input variable;
S2, designing a first-stage active disturbance rejection controller and a second-stage active disturbance rejection controller, and combining a first-stage Butterworth filter, a constant-voltage filtering cascade active disturbance rejection controller and a secondary DC-DC circuit of a wireless charging unit into a constant-voltage filtering cascade active disturbance rejection control strategy;
s3, wirelessly charging the school bus by using a constant-voltage filtering cascade active disturbance rejection control strategy;
s4, collecting school bus operation data in real time, and transmitting the school bus operation data to a central data processing platform for data processing;
S5, carrying out multidimensional analysis on the school bus operation data after data processing based on the AI large model, and generating an intelligent scheduling strategy;
s6, transmitting the intelligent scheduling strategy and the school bus operation data after data processing to the mobile terminal, and inquiring and using an operator in real time through the mobile terminal;
And S7, transmitting the intelligent scheduling strategy to a school bus driver, and performing resource allocation by the school bus driver according to the intelligent scheduling strategy.
It can be understood that the user layer collects the operation data of the school bus in the school bus card swiping system, sends the operation data to the data center for data processing, the data center receives the timing task sent by the timing task layer, inputs the processed data to the AI big model for training, and obtains the trained AI big model and data analysis result, the user performs data access processing through the small program, accesses the data analysis result of the data center, and determines the use condition of the school bus according to the data analysis result.
As shown in fig. 6, in one embodiment of the present application, four control methods are provided, namely, a first order filtered lacc control (F1-lacc), a second order filtered lacc control (F2-lacc), a first order FCLADRC control (F1-CLADRC), a second order FCLADRC control (F2-CLADRC), respectively:
The four time-consuming control strategies for the starting process to reach the set value are F2-LADRC control, F1-LADRC control, F2-CLADRC control and F1-CLADRC control in sequence from high to low, wherein the time is 11.35ms, 10.24ms, 8.9ms and 7.5ms respectively. The constant voltage filtering cascade active disturbance rejection control provided by the application can effectively improve the response speed, but the effect of a second-order controller is inferior to that of a first-order controller due to the improvement of the filtering order;
In the face of abrupt change of the set input voltage, four time consuming control strategies for the system to recover the steady state are F2-LADRC control, F1-LADRC control, F2-CLADRC control and F1-CLADRC control in sequence from high to low. The constant-voltage filtering cascade active disturbance rejection control can well solve the problem of input mutation, reduces the time consumption for recovering the steady state of the system, but also has poor effect due to more complicated system regulation and control due to the increase of the order;
The face load abrupt change is from 20 to 10. For the system recovery steady state time, four control strategies are F1-LADRC control, F2-LADRC control, F1-CLADRC control and F2-CLADRC control in sequence from high to low. For the system overshoot, four control strategies, F1-LADRC control, F2-LADRC control, F1-CLADRC control and F2-CLADRC control, are sequentially carried out from large to small. The constant voltage filtering cascade active disturbance rejection control can well solve the problem of load mutation, wherein the mutation resistance with higher order is higher, and the mutation resistance with lower order is stronger;
When the system is facing an external step disturbance. For the time consuming system recovery to steady state, four control strategies are F2-LADRC control, F1-LADRC control, F2-CLADRC control and F1-CLADRC control in sequence from high to low. For the system overshoot, four control strategies, F1-LADRC control, F2-LADRC control, F1-CLADRC control and F2-CLADRC control, are sequentially carried out from large to small. Therefore, the constant-voltage filtering cascade active disturbance rejection control can well solve the problem of external disturbance, and the effectiveness of the proposed strategy is verified, wherein the overshoot with higher order is smaller than the overshoot with lower order, and the time for recovering the steady state with lower order is shorter than the time for recovering the steady state with higher order.
The invention provides electronic equipment which comprises at least one processor, at least one memory, a communication interface and a bus, wherein the processor, the memory and the communication interface are communicated with each other through the bus, the memory stores program instructions which can be executed by the processor, and the processor calls the program instructions to realize the intelligent anti-interference wireless charging school bus control system.
The invention provides a computer readable storage medium which stores computer instructions which enable the computer to realize the intelligent anti-interference wireless charging school bus control system.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
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