A method for controlling an auxiliary power supply for highway mobile charging

Abstract

This application discloses an auxiliary power supply control method for highway mobile charging, comprising: setting a first control strategy for the auxiliary power supply system according to the type and demand of the highway vehicle; collecting feature data in real time; generating feature data difference for each feature data; adjusting the first control strategy according to the feature data difference to obtain multiple second control strategies; comparing the simulation feature data of each second control strategy in the auxiliary power supply control simulation model with preset standard feature data to generate an operation evaluation value; generating a similarity degree based on the actual operation and the simulation operation of the auxiliary power supply control simulation model; and selecting a preferred control strategy based on the operation evaluation value and the similarity degree, thereby improving the performance and stability of the auxiliary power supply system.

Description

Technical Field

[0001] This application relates to the field of mobile charging intelligent rail transit technology, and in particular to an auxiliary power control method for mobile charging on highways. Background Technology

[0002] Transportation is a crucial sector for energy consumption, significantly influencing and driving adjustments to the social energy structure and promoting energy conservation and emission reduction. In land transportation, the electrification of rail transit is a relatively clear development direction. A mobile charging intelligent rail system is proposed for highway freight transport. The main component of this system is an auxiliary power supply system, which provides electrical energy to all load equipment on highway vehicles that require electricity, excluding the traction power system.

[0003] In existing technologies, auxiliary power supply systems are controlled by adjusting current or voltage. However, there are many uncontrollable factors during the operation of auxiliary power supply systems, and a single control strategy cannot guarantee the stable operation of the auxiliary power supply system. Therefore, there is an urgent need for an auxiliary power supply control method to ensure the performance and stability of the auxiliary power supply system. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides an auxiliary power supply control method for highway mobile charging. The method determines a first control strategy based on the type and needs of the highway vehicle. The first control strategy is then adjusted multiple times based on the differences in characteristic data of the first control strategy to obtain multiple second control strategies. These second control strategies are then simulated and their operation is precisely evaluated to obtain an optimal control strategy, thereby improving the performance and stability of the auxiliary power supply system.

[0005] In some embodiments of this application, an auxiliary power control method for highway mobile charging is provided, including:

[0006] Read the types and requirements of the highway vehicles that need to be connected, and set the first control strategy for the auxiliary power system.

[0007] The auxiliary power system is driven to charge the highway vehicle according to the first control strategy, and the characteristic data of the auxiliary power system is collected in real time. Based on the preset standard characteristic data, the characteristic data difference of each characteristic data is generated.

[0008] The first control strategy is adjusted based on the difference in characteristic data to obtain multiple second control strategies, and the multiple second control strategies are simulated based on the auxiliary power supply control simulation model.

[0009] The simulation feature data of each second control strategy in the auxiliary power supply control simulation model is compared with the preset standard feature data, and the operation evaluation value of the corresponding second control strategy is generated based on the comparison results.

[0010] The auxiliary power system is controlled by the corresponding second control strategy according to the order of the operation evaluation values. The similarity between the actual operation and the simulation operation of the auxiliary power control simulation model is generated, and the preferred control strategy is selected based on the operation evaluation values ​​and the similarity.

[0011] In some embodiments of this application, a first control strategy for the auxiliary power system is defined, including:

[0012] Based on the type of highway vehicle, multiple preset control strategies are determined from the type-control strategy database, and the power supply threshold for each preset control strategy is obtained.

[0013] The demand of highway vehicles is compared with the power supply threshold, and a preset control strategy that meets the current demand is selected. The state parameters and performance parameters corresponding to the selected preset control strategy are obtained.

[0014] The state parameters and performance parameters are compared with the preset optimal state parameters and preset optimal performance parameters, respectively, and the first deviation degree and the second deviation degree are generated based on the comparison results.

[0015] The first and second deviation degrees of the same preset control strategy are calculated, and a comprehensive deviation degree is generated. The preset control strategy with the smallest comprehensive deviation degree is set as the first control strategy.

[0016] In some embodiments of this application, generating the feature data difference for each feature data includes:

[0017] A time reference line is established for the first control strategy, and the corresponding acquisition time node is set based on the preset time interval;

[0018] According to each acquisition time node of the corresponding time reference line, the characteristic parameters of the auxiliary power system are acquired, and the characteristic data of the same acquisition time node are analyzed with the preset standard characteristic data to generate the characteristic data difference.

[0019] A comprehensive analysis of the feature data differences at the same acquisition time node is performed to obtain the comprehensive feature data differences of the corresponding acquisition node, and a feature data difference matrix J, J(J1, J2, ..., Jn) is constructed, where Ji is the comprehensive feature data difference at the i-th acquisition time node, and n is the number of acquisition time nodes.

[0020] In this embodiment, feature data refers to data that may affect the state of the auxiliary power supply system, including input voltage, output voltage, input current, output current, voltage waveform, and current waveform, etc. The state, response time, and quality of the auxiliary power supply system are analyzed through feature data.

[0021] In some embodiments of this application, the first control strategy is adjusted based on the difference in feature data to obtain multiple second control strategies, including:

[0022] Based on the relationship between each comprehensive feature data difference in the feature data difference matrix J and the preset difference range, the operating status coefficient of the auxiliary power supply system at each acquisition time node is determined.

[0023] Based on the preset control and adjustment model, multiple adjustment strategies of the operating status system at each acquisition time node are obtained, and multiple adjustment strategies are combined according to the corresponding time nodes and combination methods to form multiple second control strategies.

[0024] In some embodiments of this application, determining the operating state coefficient of the auxiliary power system at each data acquisition time node includes:

[0025] The first preset difference range, the second preset difference range, the third preset difference range and the fourth preset difference range are preset.

[0026] When the difference in comprehensive feature data is within the first preset difference range, the operating state coefficient of the auxiliary power supply system is set to the fourth preset operating state coefficient.

[0027] When the difference in comprehensive characteristic data is within the second preset difference range, the operating state coefficient of the auxiliary power supply system is set to the third preset operating state coefficient.

[0028] When the difference in comprehensive feature data is within the third preset difference range, the operating state coefficient of the auxiliary power supply system is set to the second preset operating state coefficient.

[0029] When the difference in comprehensive characteristic data is within the fourth preset difference range, the operating state coefficient of the auxiliary power supply system is set to the first preset operating state coefficient.

[0030] In some embodiments of this application, multiple second control strategies are simulated based on an auxiliary power supply control simulation model, including:

[0031] To determine the importance and impact of each feature data point during the historical operation of the auxiliary power system;

[0032] Based on the association and dependency relationship between each feature data and other feature data, a feature structure relationship graph is constructed. In the feature structure relationship graph, each feature data is set as a node, and the association and dependency relationship between each node and its related feature data is set as an edge. The influence weight of the corresponding node is set according to the importance and influence degree of each feature data.

[0033] Each historical control strategy is divided into multiple control sub-processes. The influence nodes and influence edges in the feature structure relationship graph under each control sub-process are determined, and influence factors are generated based on the influence nodes and influence edges.

[0034] According to the time sequence of the control sub-processes of the same historical control strategy, the influencing factors and the corresponding historical state factors are simulated to generate the simulation model of the corresponding historical control strategy.

[0035] The simulation models of multiple historical control strategies are merged to generate an auxiliary power supply control simulation model.

[0036] Based on the auxiliary power supply control simulation model, multiple second control strategies were simulated to obtain simulation characteristic data for each second control strategy.

[0037] In some embodiments of this application, generating an operational evaluation value corresponding to the second control strategy based on the comparison results includes:

[0038] A time reference line is established for the simulation running time of each second control strategy, and the preset acquisition time node for the corresponding second control strategy is set according to the preset time interval.

[0039] According to the corresponding preset acquisition time nodes, the simulation feature data of each second control strategy is acquired and compared with the preset standard feature data. The comparison results of each second control strategy at the same preset acquisition time node are comprehensively analyzed to generate the simulation feature data difference matrix Rf, R(Rf1, Rf2, ..., Rfg) of each second control strategy, where Rf1 is the comprehensive simulation feature data difference of the f-th second control strategy at the i-th preset acquisition time node, f = 1, 2, ..., h, h is the number of second control strategies, i = 1, 2, ..., g, g is the number of preset acquisition time nodes;

[0040] The operational evaluation value Df of each second control strategy is generated based on the difference matrix Rf of the simulation characteristic data of each second control strategy.

[0041]

[0042] Where Df is the operational evaluation value of the f-th second control strategy, and w is the conversion coefficient.

[0043] In this embodiment, a preset time interval is set according to the detection accuracy and the simulation running time, and multiple preset acquisition time nodes are set on the time reference line according to the preset time interval.

[0044] In some embodiments of this application, a similarity level is generated based on the actual operating conditions and the simulated operating conditions of the auxiliary power supply control simulation model, including:

[0045] The second control strategy is set according to the order of the operation evaluation values. The auxiliary power system is controlled according to the second control strategy of the first position. Actual characteristic data is acquired according to the preset acquisition time node of the current second control strategy. The actual operating state coefficient is determined according to the comparison result of the actual characteristic data and the preset standard characteristic data, and the actual operating state coefficient matrix T0, T0(T01, T02, ..., T0g) is generated, where T0i is the actual operating state coefficient of the i-th preset acquisition time node.

[0046] Based on the relationship between each comprehensive simulation feature data difference and the preset difference interval in the simulation feature data difference matrix Rf corresponding to the second control strategy, the simulation operation state coefficient of the current second control strategy at the preset acquisition time node is determined. Based on multiple simulation operation state coefficients, the simulation operation state coefficient matrix T of the current second control strategy is generated (T1, T2, ..., Tg), where Ti is the simulation operation state coefficient of the i-th preset acquisition time node.

[0047] The actual operating conditions are determined based on the actual operating state coefficient matrix, the simulated operating conditions are determined based on the simulated operating state coefficients, and the similarity between the actual operating conditions and the simulated operating conditions is calculated.

[0048]

[0049] Where Bf represents the similarity between the simulated and actual operation of the f-th second control strategy, u represents the similarity conversion coefficient, and si represents the weight coefficient of the i-th preset acquisition time node.

[0050] In some embodiments of this application, a preferred control strategy is selected based on operational evaluation values ​​and similarity, including:

[0051] A comprehensive evaluation value is generated based on the operational evaluation values ​​of the same second control strategy and the degree of similarity.

[0052] Pf = Bf × a1 + Df × a2;

[0053] Where Pf is the comprehensive evaluation value of the f-th second control strategy, a1 is the first weight coefficient, a2 is the second weight coefficient, and a1+a2=1;

[0054] The comprehensive evaluation values ​​of multiple second control strategies are ranked, and the second control strategy ranked first is set as the preferred control strategy.

[0055] In some embodiments of this application, the method further includes updating the preferred control strategy and the currently corresponding highway vehicle type to the type-control strategy database.

[0056] The auxiliary power control method for mobile charging on highways according to an embodiment of this application has the following advantages compared with the prior art:

[0057] The first control strategy is determined by the type and demand of highway vehicles. The first control strategy is then adjusted multiple times based on the differences in characteristic data of the first control strategy to obtain multiple second control strategies. The multiple second control strategies are simulated and the operation process is accurately evaluated to obtain the optimal control strategy, thereby improving the performance and stability of the auxiliary power supply system. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating an auxiliary power control method for highway mobile charging in a preferred embodiment of this application. Detailed Implementation

[0059] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0060] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0061] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0062] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0063] like Figure 1As shown in the preferred embodiment of this application, an auxiliary power supply control method for mobile charging on highways includes:

[0064] Step S101: Read the type and requirements of the highway vehicles that need to be connected, and set the first control strategy of the auxiliary power system;

[0065] Step S102: Drive the auxiliary power system to charge the highway vehicle according to the first control strategy, collect the characteristic data of the auxiliary power system in real time, and generate the characteristic data difference of each characteristic data based on the preset standard characteristic data.

[0066] Step S103: Adjust the first control strategy according to the difference in feature data to obtain multiple second control strategies, and simulate the multiple second control strategies based on the auxiliary power supply control simulation model;

[0067] Step S104: Compare the simulation feature data of each second control strategy in the auxiliary power supply control simulation model with the preset standard feature data, and generate the corresponding operation evaluation value of the second control strategy based on the comparison results;

[0068] Step S105: Drive the corresponding second control strategy to control the auxiliary power system according to the order of the operation evaluation values, and generate the similarity between the actual operation and the simulation operation of the auxiliary power control simulation model. Select the preferred control strategy based on the operation evaluation values ​​and the similarity.

[0069] In this embodiment, the auxiliary power system works together with the charging rectifier and the overhead contact line erected along the highway to charge vehicles traveling on the highway. The charging rectifier steps down the high-voltage DC or AC power from the high-voltage transmission line and supplies it to the contact line. The pantograph contacts the contact line to supply the DC or AC power from the contact line to the contact line DC-DC or AC-DC converter. The contact line DC-DC or AC-DC converter steps down or rectifies the DC or AC power from the contact line back to DC power and supplies it to the traction inverter. The traction inverter then steps down the DC power again and converts it back to AC power to supply the permanent magnet synchronous AC motor and the power battery. The permanent magnet synchronous AC motor drives the vehicle forward.

[0070] In this embodiment, the first control strategy includes voltage regulation, current regulation, and auxiliary converter control. The highway vehicle is charged according to the first control strategy, and the characteristic data difference is obtained. The first control strategy is modified multiple times based on the characteristic data difference to obtain multiple second control strategies. An auxiliary power supply control simulation model is obtained based on the simulation of multiple second control strategies. The optimal control strategy is determined based on the operation evaluation value of each second control strategy and the similarity of real-time feedback, thereby achieving the best control effect of the auxiliary power supply system and improving the performance and stability of the auxiliary power supply system while ensuring the charging needs of the highway vehicle.

[0071] In some embodiments of this application, a first control strategy for the auxiliary power system is defined, including:

[0072] Based on the type of highway vehicle, multiple preset control strategies are determined from the type-control strategy database, and the power supply threshold for each preset control strategy is obtained.

[0073] The demand of highway vehicles is compared with the power supply threshold, and a preset control strategy that meets the current demand is selected. The state parameters and performance parameters corresponding to the selected preset control strategy are obtained.

[0074] The state parameters and performance parameters are compared with the preset optimal state parameters and preset optimal performance parameters, respectively, and the first deviation degree and the second deviation degree are generated based on the comparison results.

[0075] The first and second deviation degrees of the same preset control strategy are calculated, and a comprehensive deviation degree is generated. The preset control strategy with the smallest comprehensive deviation degree is set as the first control strategy.

[0076] In this embodiment, the types of highway vehicles include highway transport types and vehicle types, with highway transport types including but not limited to long-distance transport and short-distance transport.

[0077] In this embodiment, the demand of highway vehicles refers to charging demand. The state parameters refer to the operating data of the auxiliary energy system corresponding to the preset control strategy and the charging data of the highway vehicles. The operating status of the auxiliary energy system and the charging status of the highway vehicles are determined based on the operating data and charging data. The performance parameters refer to the stability parameters and cost parameters of the auxiliary energy system corresponding to the preset control strategy. The performance parameters are composed of the stability parameters and cost parameters. The state parameters and performance parameters of each preset control strategy are compared with the preset optimal state parameters and the preset optimal performance parameters. The first deviation degree is determined based on the deviation value between the state parameters and the preset optimal state parameters. The second deviation degree is determined based on the deviation value between the performance parameters and the preset optimal performance parameters. Thus, the comprehensive deviation degree and the first control strategy are determined.

[0078] In some embodiments of this application, generating the feature data difference for each feature data includes:

[0079] A time reference line is established for the first control strategy, and the corresponding acquisition time node is set based on the preset time interval;

[0080] According to each acquisition time node of the corresponding time reference line, the characteristic parameters of the auxiliary power system are acquired, and the characteristic data of the same acquisition time node are analyzed with the preset standard characteristic data to generate the characteristic data difference.

[0081] A comprehensive analysis of the feature data differences at the same acquisition time node is performed to obtain the comprehensive feature data differences of the corresponding acquisition node, and a feature data difference matrix J, J(J1, J2, ..., Jn) is constructed, where Ji is the comprehensive feature data difference at the i-th acquisition time node, and n is the number of acquisition time nodes.

[0082] In this embodiment, feature data refers to data that may affect the state of the auxiliary power supply system, including input voltage, output voltage, input current, output current, voltage waveform, and current waveform, etc. The state, response time, and quality of the auxiliary power supply system are analyzed through feature data.

[0083] In this embodiment, the preset standard feature data refers to the set of feature data corresponding to the first control strategy under normal operation. By comparing the feature data with the preset standard feature data, it can be determined whether the corresponding feature data is within the standard range, thereby obtaining the operating status of the auxiliary power system. This lays the data foundation for subsequent correction of the first control strategy. By continuously correcting the control strategy, the performance and stability of the auxiliary power system can be improved.

[0084] In some embodiments of this application, the first control strategy is adjusted based on the difference in feature data to obtain multiple second control strategies, including:

[0085] Based on the relationship between each comprehensive feature data difference in the feature data difference matrix J and the preset difference range, the operating status coefficient of the auxiliary power supply system at each acquisition time node is determined.

[0086] Based on the preset control and adjustment model, multiple adjustment strategies of the operating status system at each acquisition time node are obtained, and multiple adjustment strategies are combined according to the corresponding time nodes and combination methods to form multiple second control strategies.

[0087] In this embodiment, the preset control adjustment model is constructed based on the historical operating state coefficients and historical adjustment strategies at the corresponding acquisition time nodes. The first control strategy is adjusted in different combinations of multiple adjustment strategies at the corresponding acquisition time nodes to form multiple second control strategies.

[0088] In this embodiment, the first control strategy is continuously adjusted and real-time feedback is provided to form multiple second control strategies. By subsequently calculating the operation evaluation value and similarity of the second control strategies, a preferred control strategy is obtained, thereby improving the performance and stability of the auxiliary power supply system.

[0089] In some embodiments of this application, determining the operating state coefficient of the auxiliary power system at each data acquisition time node includes:

[0090] The first preset difference range, the second preset difference range, the third preset difference range and the fourth preset difference range are preset.

[0091] When the difference in comprehensive feature data is within the first preset difference range, the operating state coefficient of the auxiliary power supply system is set to the fourth preset operating state coefficient.

[0092] When the difference in comprehensive characteristic data is within the second preset difference range, the operating state coefficient of the auxiliary power supply system is set to the third preset operating state coefficient.

[0093] When the difference in comprehensive feature data is within the third preset difference range, the operating state coefficient of the auxiliary power supply system is set to the second preset operating state coefficient.

[0094] When the difference in comprehensive characteristic data is within the fourth preset difference range, the operating state coefficient of the auxiliary power supply system is set to the first preset operating state coefficient.

[0095] In this embodiment, the first preset operating state coefficient < the second preset operating state coefficient < the third preset operating state coefficient < the fourth preset operating state coefficient < 1, and the first preset difference range < the second preset difference range < the third preset difference range < the fourth preset difference range.

[0096] In this embodiment, the larger the preset difference range of the comprehensive feature data difference, the worse the operating state of the auxiliary power system, that is, the smaller the operating state coefficient. The operating state coefficient is input into the preset control adjustment model, and multiple adjustment strategies of the first control strategy at the corresponding acquisition time node are output, thereby obtaining multiple second control strategies.

[0097] In some embodiments of this application, multiple second control strategies are simulated based on an auxiliary power supply control simulation model, including:

[0098] To determine the importance and impact of each feature data point during the historical operation of the auxiliary power system;

[0099] Based on the association and dependency relationship between each feature data and other feature data, a feature structure relationship graph is constructed. In the feature structure relationship graph, each feature data is set as a node, and the association and dependency relationship between each node and its related feature data is set as an edge. The influence weight of the corresponding node is set according to the importance and influence degree of each feature data.

[0100] Each historical control strategy is divided into multiple control sub-processes. The influence nodes and influence edges in the feature structure relationship graph under each control sub-process are determined, and influence factors are generated based on the influence nodes and influence edges.

[0101] According to the time sequence of the control sub-processes of the same historical control strategy, the influencing factors and the corresponding historical state factors are simulated to generate the simulation model of the corresponding historical control strategy.

[0102] The simulation models of multiple historical control strategies are merged to generate an auxiliary power supply control simulation model.

[0103] Based on the auxiliary power supply control simulation model, multiple second control strategies were simulated to obtain simulation characteristic data for each second control strategy.

[0104] In this embodiment, the degree of influence refers to the degree of influence of feature data on the state, response time or quality of the auxiliary power system, the correlation refers to the mutual influence relationship between feature data, and the dependency relationship refers to the degree to which changes in feature data cause changes in other feature data. When a change in feature data A causes a change in feature data B and exceeds a preset change threshold, then feature data B depends on feature data A.

[0105] In this embodiment, an influencing node refers to a node whose characteristic data changes after each control sub-process runs, thereby affecting the operating state or response time of the auxiliary power system. An influencing edge refers to the boundary where the characteristic data and related characteristic data of each control sub-process run affect the operating state or response time of the auxiliary power system. The historical state factor refers to the historical operating state changes and historical operating state coefficients corresponding to the influencing factor. Generating the influencing factor can better understand the changes and degree of influence of the characteristic data and related characteristic data after each control sub-process, thereby obtaining the state coefficient of the auxiliary power system, so as to simulate, analyze and adjust the second control strategy in the future.

[0106] In this embodiment, the influence of changes in various feature data on the auxiliary power system can be clearly understood based on the feature structure relationship diagram. By simulating the influence factors and corresponding historical state factors according to the time sequence of each control sub-process of the historical control strategy, the simulation model of the corresponding historical control strategy is obtained. Multiple simulation models are merged to form an auxiliary energy control simulation model, which improves the accuracy of the auxiliary power control simulation model and lays the foundation for subsequent operational evaluation of the second control strategy.

[0107] In some embodiments of this application, generating an operational evaluation value corresponding to the second control strategy based on the comparison results includes:

[0108] A time reference line is established for the simulation running time of each second control strategy, and the preset acquisition time node for the corresponding second control strategy is set according to the preset time interval.

[0109] According to the corresponding preset acquisition time nodes, the simulation feature data of each second control strategy is acquired and compared with the preset standard feature data. The comparison results of each second control strategy at the same preset acquisition time node are comprehensively analyzed to generate the simulation feature data difference matrix Rf, R(Rf1, Rf2, ..., Rfg) of each second control strategy, where Rf1 is the comprehensive simulation feature data difference of the f-th second control strategy at the i-th preset acquisition time node, f = 1, 2, ..., h, h is the number of second control strategies, i = 1, 2, ..., g, g is the number of preset acquisition time nodes;

[0110] The operational evaluation value Df of each second control strategy is generated based on the difference matrix Rf of the simulation characteristic data of each second control strategy.

[0111]

[0112] Where Df is the operational evaluation value of the f-th second control strategy, and w is the conversion coefficient.

[0113] In this embodiment, a preset time interval is set according to the detection accuracy and the simulation running time, and multiple preset acquisition time nodes are set on the time reference line according to the preset time interval.

[0114] In this embodiment, the comprehensive simulation feature data difference at each preset acquisition time node is obtained based on the simulation feature data difference matrix of each second control strategy, and the corresponding operation evaluation value is generated to achieve accurate evaluation of the second control strategy. When the operation evaluation value is larger, it indicates that the stability and performance of the corresponding second control strategy are better. The operation order of the second control strategies is arranged according to the size of the operation evaluation value, and the preferred control strategy is selected according to the degree of similarity to improve the performance and stability of the auxiliary power supply system.

[0115] In some embodiments of this application, a similarity level is generated based on the actual operating conditions and the simulated operating conditions of the auxiliary power supply control simulation model, including:

[0116] The second control strategy is set according to the order of the operation evaluation values. The auxiliary power system is controlled according to the second control strategy of the first position. Actual characteristic data is acquired according to the preset acquisition time node of the current second control strategy. The actual operating state coefficient is determined according to the comparison result of the actual characteristic data and the preset standard characteristic data, and the actual operating state coefficient matrix T0, T0(T01, T02, ..., T0g) is generated, where T0i is the actual operating state coefficient of the i-th preset acquisition time node.

[0117] Based on the relationship between each comprehensive simulation feature data difference and the preset difference interval in the simulation feature data difference matrix Rf corresponding to the second control strategy, the simulation operation state coefficient of the current second control strategy at the preset acquisition time node is determined. Based on multiple simulation operation state coefficients, the simulation operation state coefficient matrix T of the current second control strategy is generated (T1, T2, ..., Tg), where Ti is the simulation operation state coefficient of the i-th preset acquisition time node.

[0118] The actual operating conditions are determined based on the actual operating state coefficient matrix, the simulated operating conditions are determined based on the simulated operating state coefficients, and the similarity between the actual operating conditions and the simulated operating conditions is calculated.

[0119]

[0120] Where Bf represents the similarity between the simulated and actual operation of the f-th second control strategy, u represents the similarity conversion coefficient, and si represents the weight coefficient of the i-th preset acquisition time node.

[0121] In this embodiment, the similarity between the actual operating state coefficient matrix and the simulated operating state coefficient matrix is ​​determined respectively. The higher the similarity, the higher the credibility of the operating evaluation value of the second control strategy. Therefore, the preferred control strategy is selected to improve the performance and stability of the auxiliary power supply system.

[0122] In some embodiments of this application, a preferred control strategy is selected based on operational evaluation values ​​and similarity, including:

[0123] A comprehensive evaluation value is generated based on the operational evaluation values ​​of the same second control strategy and the degree of similarity.

[0124] Pf = Bf × a1 + Df × a2;

[0125] Where Pf is the comprehensive evaluation value of the f-th second control strategy, a1 is the first weight coefficient, a2 is the second weight coefficient, and a1+a2=1;

[0126] The comprehensive evaluation values ​​of multiple second control strategies are ranked, and the second control strategy ranked first is set as the preferred control strategy.

[0127] In some embodiments of this application, the method further includes updating the preferred control strategy and the currently corresponding highway vehicle type to the type-control strategy database.

[0128] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. An auxiliary power supply control method for mobile charging on highways, characterized in that, include: Read the types and requirements of the highway vehicles that need to be connected, and set the first control strategy for the auxiliary power system. The auxiliary power system is driven to charge the highway vehicle according to the first control strategy, and the characteristic data of the auxiliary power system is collected in real time. Based on the preset standard characteristic data, the characteristic data difference of each characteristic data is generated. The first control strategy is adjusted based on the difference in characteristic data to obtain multiple second control strategies, and the multiple second control strategies are simulated based on the auxiliary power supply control simulation model. The simulation feature data of each second control strategy in the auxiliary power supply control simulation model is compared with the preset standard feature data, and the operation evaluation value of the corresponding second control strategy is generated based on the comparison results. The auxiliary power system is controlled by driving the corresponding second control strategy according to the order of the operation evaluation values. The similarity between the actual operation and the simulation operation of the auxiliary power control simulation model is generated, and the preferred control strategy is selected based on the operation evaluation values ​​and the similarity. The first control strategy for the auxiliary power system is defined, including: Based on the type of highway vehicle, multiple preset control strategies are determined from the type-control strategy database, and the power supply threshold for each preset control strategy is obtained. The demand of highway vehicles is compared with the power supply threshold, and a preset control strategy that meets the current demand is selected. The state parameters and performance parameters corresponding to the selected preset control strategy are obtained. The state parameters and performance parameters are compared with the preset optimal state parameters and preset optimal performance parameters, respectively, and the first deviation degree and the second deviation degree are generated based on the comparison results. The first and second deviation degrees of the same preset control strategy are calculated and a comprehensive deviation degree is generated. The preset control strategy with the smallest comprehensive deviation degree is set as the first control strategy. The feature data variance for each feature data point is generated, including: A time reference line is established for the first control strategy, and the corresponding acquisition time node is set based on the preset time interval; According to each acquisition time node of the corresponding time reference line, the characteristic data of the auxiliary power system is acquired, and the characteristic data of the same acquisition time node is analyzed with the preset standard characteristic data to generate the characteristic data difference quantity. A comprehensive analysis of the feature data differences at the same acquisition time node is performed to obtain the comprehensive feature data differences of the corresponding acquisition node, and a feature data difference matrix J, J(J1, J2, ..., Jn) is constructed, where Ji is the comprehensive feature data difference at the i-th acquisition time node, and n is the number of acquisition time nodes.

2. The auxiliary power supply control method for highway mobile charging as described in claim 1, characterized in that, The first control strategy is adjusted based on the difference in feature data to obtain multiple second control strategies, including: Based on the relationship between each comprehensive feature data difference in the feature data difference matrix J and the preset difference range, the operating status coefficient of the auxiliary power supply system at each acquisition time node is determined. Based on the preset control and adjustment model, multiple adjustment strategies of the operating status system at each acquisition time node are obtained, and multiple adjustment strategies are combined according to the corresponding time nodes and combination methods to form multiple second control strategies.

3. The auxiliary power supply control method for highway mobile charging as described in claim 2, characterized in that, Determine the operating state coefficients of the auxiliary power system at each data acquisition time point, including: The first preset difference range, the second preset difference range, the third preset difference range and the fourth preset difference range are preset. When the difference in comprehensive feature data is within the first preset difference range, the operating state coefficient of the auxiliary power supply system is set to the fourth preset operating state coefficient. When the difference in comprehensive characteristic data is within the second preset difference range, the operating state coefficient of the auxiliary power supply system is set to the third preset operating state coefficient. When the difference in comprehensive feature data is within the third preset difference range, the operating state coefficient of the auxiliary power supply system is set to the second preset operating state coefficient. When the difference in comprehensive characteristic data is within the fourth preset difference range, the operating state coefficient of the auxiliary power supply system is set to the first preset operating state coefficient.

4. The auxiliary power supply control method for mobile charging on highways as described in claim 3, characterized in that, Simulations were performed on several secondary control strategies based on the auxiliary power supply control simulation model, including: To determine the importance and impact of each feature data point during the historical operation of the auxiliary power system; Based on the association and dependency relationship between each feature data and other feature data, a feature structure relationship graph is constructed. In the feature structure relationship graph, each feature data is set as a node, and the association and dependency relationship between each node and its related feature data is set as an edge. The influence weight of the corresponding node is set according to the importance and influence degree of each feature data. Each historical control strategy is divided into multiple control sub-processes. The influence nodes and influence edges in the feature structure relationship graph under each control sub-process are determined, and influence factors are generated based on the influence nodes and influence edges. According to the time sequence of the control sub-processes of the same historical control strategy, the influencing factors and the corresponding historical state factors are simulated to generate the simulation model of the corresponding historical control strategy. The simulation models of multiple historical control strategies are merged to generate an auxiliary power supply control simulation model. Based on the auxiliary power supply control simulation model, multiple second control strategies were simulated to obtain simulation characteristic data for each second control strategy.

5. The auxiliary power supply control method for highway mobile charging as described in claim 4, characterized in that, Based on the comparison results, the corresponding operational evaluation value for the second control strategy is generated, including: A time reference line is established for the simulation running time of each second control strategy, and the preset acquisition time node for the corresponding second control strategy is set according to the preset time interval. According to the corresponding preset acquisition time nodes, the simulation feature data of each second control strategy is acquired and compared with the preset standard feature data. The comparison results of each second control strategy at the same preset acquisition time node are comprehensively analyzed to generate the simulation feature data difference matrix Rf, R(Rf1, Rf2, ..., Rfg) of each second control strategy, where Rf1 is the comprehensive simulation feature data difference of the f-th second control strategy at the i-th preset acquisition time node, f=1,2,...,h, h is the number of second control strategies, i=1,2,...,g, g is the number of preset acquisition time nodes; The operational evaluation value Df of each second control strategy is generated based on the difference matrix Rf of the simulation characteristic data of each second control strategy. w； Where Df is the operational evaluation value of the f-th second control strategy, and w is the conversion coefficient; Among them, a preset time interval is set according to the detection accuracy and the simulation running time, and multiple preset acquisition time nodes are set on the time reference line according to the preset time interval.

6. The auxiliary power supply control method for highway mobile charging as described in claim 5, characterized in that, The similarity score is generated based on the actual operating conditions and the simulation results of the auxiliary power supply control simulation model, including: The second control strategy is set according to the order of the operation evaluation values. The auxiliary power system is controlled according to the second control strategy of the first position. Actual characteristic data is acquired according to the preset acquisition time node of the current second control strategy. The actual operating state coefficient is determined according to the comparison result of the actual characteristic data and the preset standard characteristic data, and the actual operating state coefficient matrix T0, T0(T01, T02, ..., T0g) is generated, where T0i is the actual operating state coefficient of the i-th preset acquisition time node. Based on the relationship between each comprehensive simulation feature data difference and the preset difference interval in the simulation feature data difference matrix Rf corresponding to the second control strategy, the simulation operation state coefficient of the current second control strategy at the preset acquisition time node is determined. Based on multiple simulation operation state coefficients, the simulation operation state coefficient matrix T of the current second control strategy is generated (T1, T2, ..., Tg), where Ti is the simulation operation state coefficient of the i-th preset acquisition time node. The actual operating conditions are determined based on the actual operating state coefficient matrix, the simulated operating conditions are determined based on the simulated operating state coefficients, and the similarity between the actual operating conditions and the simulated operating conditions is calculated. ； Where Bf represents the similarity between the simulated and actual operation of the f-th second control strategy, u represents the similarity conversion coefficient, and si represents the weight coefficient of the i-th preset acquisition time node.

7. The auxiliary power supply control method for highway mobile charging as described in claim 6, characterized in that, The preferred control strategy is selected based on the operational evaluation value and the degree of similarity, including: A comprehensive evaluation value is generated based on the operational evaluation values ​​of the same second control strategy and the degree of similarity. ； Where Pf is the comprehensive evaluation value of the f-th second control strategy, a1 is the first weight coefficient, a2 is the second weight coefficient, and a1+a2=1; The comprehensive evaluation values ​​of multiple second control strategies are ranked, and the second control strategy ranked first is set as the preferred control strategy.

8. The auxiliary power supply control method for highway mobile charging as described in claim 1, characterized in that, Also includes: Update the preferred control strategy and the corresponding highway vehicle type to the type-control strategy database.

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