A charging management method and system based on Internet of Things

Abstract

The present application relates to the field of charging management technology, and in particular to a charging management method and system based on the Internet of Things. The method includes: obtaining the initial state information of a number of charging vehicles, and determining the initial power of a number of operating charging piles accordingly; obtaining the external influencing factors of each operating charging pile and the real-time power of the corresponding vehicle, and dynamically adjusting the real-time output power of each operating charging pile accordingly; based on the real-time output power, obtaining the current change data and voltage change data of each operating charging pile, and determining the nonlinear load change information accordingly; analyzing the nonlinear load change information, and determining the system resonance risk according to the analysis results; adjusting the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk. The present application determines and adjusts the optimal output power of each charging pile while reducing the nonlinear load and system resonance risks, so as to achieve a balance between the safety risk of the charging system and the charging efficiency.

Description

Technical Field

[0001] The present application relates to the field of charging management technology, and in particular to a charging management method and system based on the Internet of Things. Background Art

[0002] With the rapid development of the electric vehicle market, the demand for charging facilities is also increasing. The construction of charging piles has become a key link in energy transformation. The widespread popularization of charging piles is conducive to improving user convenience and experience, while reducing the operating costs of electric vehicles.

[0003] Since charging piles have high output power during the charging process of electric vehicles and are prone to safety accidents, safety monitoring of charging piles is very critical. However, the existing charging pile safety monitoring technology does not fully consider the impact of different factors on charging piles, and does not effectively monitor and solve the negative impact of different factors on charging piles, resulting in safety risks in the electric vehicle charging process and a decrease in the stability and reliability of charging piles. Summary of the invention

[0004] The present application provides a charging management method and system based on the Internet of Things to solve the above technical problems.

[0005] In a first aspect, the present application provides a charging management method based on the Internet of Things, the method comprising:

[0006] Acquire initial state information of a plurality of charging vehicles, and determine initial powers of a plurality of operating charging piles respectively according to the initial state information;

[0007] Obtaining the external influence factor of each running charging pile and the real-time power of the corresponding vehicle, and dynamically adjusting the real-time output power of each running charging pile according to the external influence factor and the real-time power of the corresponding vehicle;

[0008] Based on the real-time output power, current change data and voltage change data of each running charging pile are obtained, and nonlinear load change information is determined according to the current change data and voltage change data;

[0009] Analyzing the nonlinear load change information, and determining the system resonance risk according to the analysis result;

[0010] According to the nonlinear load change information and the system resonance risk, the optimal output power of each operating charging pile is adjusted.

[0011] The method of the present application first determines the initial power of the operating charging pile through the initial state information of the charging vehicle, and then, on the basis of the initial power, considers the impact of external influencing factors and the real-time power of the vehicle on the output power of the charging pile, and realizes dynamic adjustment of the real-time output power of the operating charging pile, while protecting the battery life of the vehicle, ensuring the safety of the charging process, and further, considering the nonlinear load of the charging system caused by the above-mentioned real-time output power adjustment and the change of the system resonance risk under the nonlinear load, the power of the operating charging pile is adjusted, and the optimal output power of each operating charging pile is obtained while reducing the nonlinear load and the system resonance risk, so as to achieve a balance between the safety risk of the charging system and the charging efficiency.

[0012] Optionally, the acquiring initial state information of a plurality of charging vehicles and determining initial powers of a plurality of operating charging piles respectively according to the initial state information includes:

[0013] Acquire the current power, basic charging power and maximum capacity of the charging vehicle, and determine the current power, basic charging power and maximum capacity as the initial state information;

[0014] According to the initial state information, the initial powers of several running charging piles are determined respectively, referring to the following formula:

[0015] ;

[0016] in, is the initial power of the running charging pile, is the basic charging power, is the current power, is the maximum capacity, is the benchmark parameter, To adjust the parameters.

[0017] The above technical solution calculates the accurate initial charging power data required for the current charging vehicle through the current power of the charging vehicle, the basic charging power and the maximum capacity, and provides accurate data basis for the subsequent dynamic adjustment of the output power of the charging pile, so as to ensure that the output power of the charging pile after the subsequent dynamic adjustment can ensure the charging efficiency of different charging vehicles.

[0018] Optionally, the external influencing factors include but are not limited to temperature values, humidity values ​​and battery temperature. According to the external influencing factors and the real-time power of the corresponding vehicle, the real-time output power of each running charging pile is dynamically adjusted, including:

[0019] According to the battery temperature, the basic charging power, the temperature value, the humidity value, the corresponding vehicle real-time power and the maximum capacity, the real-time power value of each running charging pile is determined by the following formula:

[0020] ;

[0021] in, is the real-time power value, is the basic charging power, is the humidity value, is the temperature value, is the battery temperature, is the real-time power of the vehicle, is the maximum capacity, is the benchmark parameter, To adjust the parameters;

[0022] According to the real-time power value of each running charging pile, the real-time output power of each running charging pile is adjusted in real time.

[0023] The above technical scheme, on the basis of considering the basic charging power and the maximum capacity to ensure the charging efficiency in the aforementioned embodiment, further considers the influence of external temperature, external humidity and vehicle battery temperature on the output power of the operating charging pile, accurately calculates the optimal output power value required for the current operating charging pile to ensure the charging efficiency of the charging vehicle at the current temperature, humidity and battery temperature, and adjusts the real-time output power of the operating charging pile according to the optimal output power value. While ensuring the charging efficiency of the vehicle, it avoids safety accidents caused by the influence of external temperature, external humidity and battery temperature, thereby further improving the safety of the charging process.

[0024] Optionally, determining the nonlinear load change information according to the current change data and the voltage change data includes:

[0025] Analyze the current change data and the voltage change data to determine useful power change data of each operating charging pile;

[0026] Determining power factor change data according to the current change data, the voltage change data and the useful power change data;

[0027] The power factor change data is analyzed to determine the nonlinear load change information.

[0028] The above technical scheme obtains useful power change data based on current change data and voltage change data, and then combines the current change data, voltage conversion data and useful power change data to determine the power factor change data that can accurately reflect the nonlinear load, and then determines the nonlinear load change information based on the power factor change data, thereby providing accurate nonlinear load change information for the subsequent adjustment of the optimal output power of the charging pile for the nonlinear load.

[0029] Optionally, analyzing the current change data and the voltage change data to determine the useful power change data of each operating charging pile includes:

[0030] Determining phase angle change data according to the current change data and the voltage change data;

[0031] According to the current change data, the voltage change data and the phase angle change data, the useful power value of each running charging pile at different time points is calculated by the following formula:

[0032] ;

[0033] in, For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at For the The charging piles are in operation at time point Phase angle data of current and voltage at the time;

[0034] According to the useful power value of each operating charging pile at different time points, the useful power change data of each operating charging pile during the charging period is determined.

[0035] The above technical solution is based on the current change data, voltage change data and phase angle change data of each operating charging pile during the charging period, and accurately calculates the useful power change data of each operating charging pile during the charging period according to the current value, voltage value and phase angle data of each operating charging pile at different time points, which provides an important and accurate data basis for the subsequent use of the useful power change data to obtain the power factor change data that can reflect the nonlinear load condition of the charging system.

[0036] Optionally, determining the power factor change data according to the current change data, the voltage change data and the useful power change data includes:

[0037] According to the current change data, the voltage change data and the useful power change data, the power factor at different time points is calculated respectively by the following formula:

[0038] ;

[0039] in, For time point The power factor at For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at

[0040] Power factor variation data is determined according to the power factors at different time points.

[0041] The above technical solution comprehensively analyzes the ratio of the useful power to the total power of each operating charging pile in the charging system, and obtains the power factor change at different time points, thereby determining the power factor change data, which provides an accurate and comprehensive data basis for the subsequent determination of nonlinear load change information based on the power factor change data.

[0042] Optionally, analyzing the power factor change data to determine the nonlinear load change information includes:

[0043] Generating a power factor change curve according to the power factor change data;

[0044] Analyze the power factor change curve, compare the power factor values ​​in the power factor change curve with the preset rated power factor values ​​respectively, and if there is a situation in the power factor change curve where the current power factor value is less than the preset rated power factor value, determine the current power factor value as a suspicious power factor value;

[0045] Comparing the difference ratio between the suspicious power factor value and the preset rated power factor value with a preset power factor difference threshold, and if the difference ratio is greater than the preset power factor difference threshold, determining the suspicious power factor value as an abnormal power factor value;

[0046] The time point corresponding to the abnormal power factor value in the power factor change curve is taken as the abnormal starting point, the time point corresponding to the most recent normal power factor value in the power factor change curve is taken as the abnormal end point, and the time length and curve waveform between the abnormal starting point and the abnormal end point are recorded;

[0047] The nonlinear load change information is determined according to the time length and the curve waveform.

[0048] The above technical scheme obtains a power factor change curve based on the power factor change data, determines the abnormal power factor value that can reflect the nonlinear load in the power factor curve, and then records the time length and curve waveform between the abnormal power factor value and the most recent normal power factor value, and determines the nonlinear load change information by statistically analyzing the time length and the curve waveform, thereby improving the sensitivity of the nonlinear load change information, so that the nonlinear load change information can accurately and intuitively reflect the nonlinear load state, thereby making the subsequent system resonance risk determined based on the nonlinear load change information more accurate.

[0049] Optionally, analyzing the nonlinear load change information and determining the system resonance risk according to the analysis result includes:

[0050] Determining an abnormal power factor fluctuation frequency curve according to the time length and the fluctuation information;

[0051] Obtaining a system natural frequency curve, analyzing the fluctuation frequency curve and the system natural frequency curve, and determining a curve correlation coefficient;

[0052] The system resonance risk is determined according to the curve correlation coefficient.

[0053] The above technical solution obtains the fluctuation frequency curve of the abnormal power factor value by analyzing the time length and the curve waveform, and then evaluates the system resonance risk through the correlation coefficient between the fluctuation frequency curve and the system inherent frequency curve, so that the final system resonance risk can accurately reflect whether the fluctuation of the abnormal power factor under the influence of nonlinear load will cause system resonance, thereby providing accurate quantitative data for avoiding system resonance.

[0054] Optionally, adjusting the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk includes:

[0055] Comparing the curve correlation coefficient with a preset curve correlation coefficient threshold;

[0056] If the curve correlation coefficient is greater than a preset curve correlation coefficient threshold, analyzing the nonlinear load change information to determine a power factor adjustment value;

[0057] Determine the current total power value according to the real-time output power of each operating charging pile, and determine the required adjustment power value of each operating charging pile according to the power factor adjustment value, the current total power value and the real-time output power of each operating charging pile;

[0058] According to the required adjusted power value, the optimal output power of each operating charging pile is adjusted.

[0059] The above technical scheme, in the case of possible system resonance, obtains the power factor adjustment value required to adjust the current power factor value in order to avoid system resonance and reduce nonlinear load by analyzing the nonlinear load change information. Based on the power factor adjustment value, combined with the current total power value and the real-time output power of each operating charging pile, the required adjustment power value of each operating charging pile is determined respectively, and then the optimal output power of each operating charging pile is adjusted according to the required adjustment power value of each operating charging pile, which effectively avoids the occurrence of system resonance, reduces the failure rate of charging piles, and reduces nonlinear loads at the same time, improves the stability of charging piles, and further ensures the safety of the charging process.

[0060] In a second aspect, the present application provides a charging management system based on the Internet of Things, the system comprising:

[0061] An initial power determination module is used to obtain initial state information of a plurality of charging vehicles and determine the initial powers of a plurality of operating charging piles according to the initial state information;

[0062] A real-time adjustment module is used to obtain the external influence factor of each running charging pile and the real-time power of the corresponding vehicle, and dynamically adjust the real-time output power of each running charging pile according to the external influence factor and the real-time power of the corresponding vehicle;

[0063] A load monitoring module, configured to obtain current change data and voltage change data of each running charging pile based on the real-time output power, and determine nonlinear load change information according to the current change data and voltage change data;

[0064] A resonance analysis module, used to analyze the nonlinear load change information and determine the system resonance risk according to the analysis result;

[0065] The power adjustment module is used to adjust the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk.

[0066] Optionally, the initial power determination module is specifically used to:

[0067] Acquire the current power, basic charging power and maximum capacity of the charging vehicle, and determine the current power, basic charging power and maximum capacity as the initial state information;

[0068] According to the initial state information, the initial powers of several running charging piles are determined respectively, referring to the following formula:

[0069] ;

[0070] in, is the initial power of the running charging pile, is the basic charging power, is the current power, is the maximum capacity, is the benchmark parameter, To adjust the parameters.

[0071] Optionally, the real-time adjustment module is specifically used to:

[0072] According to the battery temperature, the basic charging power, the temperature value, the humidity value, the corresponding vehicle real-time power and the maximum capacity, the real-time power value of each running charging pile is determined by the following formula:

[0073] ;

[0074] in, is the real-time power value, is the basic charging power, is the humidity value, is the temperature value, is the battery temperature, is the real-time power of the vehicle, is the maximum capacity, is the benchmark parameter, To adjust the parameters;

[0075] According to the real-time power value of each running charging pile, the real-time output power of each running charging pile is adjusted in real time.

[0076] Optionally, the load monitoring module is specifically used to:

[0077] Analyze the current change data and the voltage change data to determine useful power change data of each operating charging pile;

[0078] Determining power factor change data according to the current change data, the voltage change data and the useful power change data;

[0079] The power factor change data is analyzed to determine the nonlinear load change information.

[0080] Optionally, the load monitoring module is specifically used to:

[0081] Determining phase angle change data according to the current change data and the voltage change data;

[0082] According to the current change data, the voltage change data and the phase angle change data, the useful power value of each running charging pile at different time points is calculated by the following formula:

[0083] ;

[0084] in, For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at For the The charging piles are in operation at time point Phase angle data of current and voltage at the time;

[0085] According to the useful power value of each operating charging pile at different time points, the useful power change data of each operating charging pile during the charging period is determined.

[0086] Optionally, the load monitoring module is specifically used to:

[0087] According to the current change data, the voltage change data and the useful power change data, the power factor at different time points is calculated respectively by the following formula:

[0088] ;

[0089] in, For time point The power factor at For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at

[0090] Power factor variation data is determined according to the power factors at different time points.

[0091] Optionally, the load monitoring module is specifically used to:

[0092] Generating a power factor change curve according to the power factor change data;

[0093] Analyze the power factor change curve, compare the power factor values ​​in the power factor change curve with the preset rated power factor values ​​respectively, and if there is a situation in the power factor change curve where the current power factor value is less than the preset rated power factor value, determine the current power factor value as a suspicious power factor value;

[0094] Comparing the difference ratio between the suspicious power factor value and the preset rated power factor value with a preset power factor difference threshold, and if the difference ratio is greater than the preset power factor difference threshold, determining the suspicious power factor value as an abnormal power factor value;

[0095] The time point corresponding to the abnormal power factor value in the power factor change curve is taken as the abnormal starting point, the time point corresponding to the most recent normal power factor value in the power factor change curve is taken as the abnormal end point, and the time length and curve waveform between the abnormal starting point and the abnormal end point are recorded;

[0096] The nonlinear load change information is determined according to the time length and the curve waveform.

[0097] Optionally, the resonance analysis module is specifically used for:

[0098] Determining an abnormal power factor fluctuation frequency curve according to the time length and the fluctuation information;

[0099] Obtaining a system natural frequency curve, analyzing the fluctuation frequency curve and the system natural frequency curve, and determining a curve correlation coefficient;

[0100] The system resonance risk is determined according to the curve correlation coefficient.

[0101] Optionally, the power adjustment module is specifically used to:

[0102] Comparing the curve correlation coefficient with a preset curve correlation coefficient threshold;

[0103] If the curve correlation coefficient is greater than a preset curve correlation coefficient threshold, analyzing the nonlinear load change information to determine a power factor adjustment value;

[0104] Determine the current total power value according to the real-time output power of each operating charging pile, and determine the required adjustment power value of each operating charging pile according to the power factor adjustment value, the current total power value and the real-time output power of each operating charging pile;

[0105] According to the required adjusted power value, the optimal output power of each operating charging pile is adjusted. BRIEF DESCRIPTION OF THE DRAWINGS

[0106] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0107] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0108] Figure 2 A flowchart of a charging management method based on the Internet of Things provided in one embodiment of the present application;

[0109] Figure 3 A schematic diagram of the structure of a charging management system based on the Internet of Things is provided in one embodiment of the present application. DETAILED DESCRIPTION

[0110] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0111] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0112] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0113] Since charging piles have high output power during the charging process of electric vehicles and are prone to safety accidents, safety monitoring of charging piles is very critical. However, the existing charging pile safety monitoring technology does not fully consider the impact of different factors on charging piles, and does not effectively monitor and solve the negative impact of different factors on charging piles, resulting in safety risks in the electric vehicle charging process and a decrease in the stability and reliability of charging piles.

[0114] Based on this, the present application provides a charging management method and system based on the Internet of Things. The initial power of the operating charging pile is determined through the initial state information of the charging vehicle, and then, on the basis of the initial power, the influence of external influencing factors and the real-time power of the vehicle on the output power of the charging pile is considered to realize dynamic adjustment of the real-time output power of the operating charging pile, while protecting the battery life of the vehicle, ensuring the safety of the charging process, and further, considering the nonlinear load of the charging system caused by the above-mentioned real-time output power adjustment and the change of the system resonance risk under the nonlinear load, the power of the operating charging pile is adjusted to obtain the optimal output power of each operating charging pile while reducing the nonlinear load and the system resonance risk, so as to achieve a balance between the safety risk of the charging system and the charging efficiency.

[0115] Figure 1 A schematic diagram of an application scenario provided for the present application, in the process of a charging pile charging a charging vehicle, the method provided by the present application is applied to monitor the charging process and dynamically adjust the power of the charging pile in real time to ensure the charging efficiency and safety of the charging process.

[0116] The method of the present application is installed in any server, and the server communicates with a plurality of operating charging piles, and the plurality of operating charging piles communicate with corresponding charging vehicles respectively.

[0117] Specifically, the operating charging pile communicates with the charging vehicle, and the initial state information of the charging vehicle is transmitted to the server. The initial state information is analyzed by the server to determine the initial power of the operating charging pile. At the same time, the impact of external influencing factors and the real-time power of the vehicle on the output power of the charging pile is considered to achieve dynamic adjustment of the real-time output power of the operating charging pile. Then, by analyzing the current change information and the voltage change information, the nonlinear load change information and the system resonance risk are determined, and the optimal output power of each operating charging pile is obtained while reducing the nonlinear load and system resonance risks, so as to achieve a balance between the safety risk of the charging system and the charging efficiency.

[0118] For specific implementation methods, please refer to the following embodiments.

[0119] Figure 2This is a flow chart of a charging management method based on the Internet of Things provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes:

[0120] S201. Acquire initial state information of a plurality of charging vehicles, and determine initial powers of a plurality of operating charging piles respectively according to the initial state information.

[0121] The charging vehicle may be a vehicle that has been connected to a charging pile and is in a charging state.

[0122] The initial status information may be a series of status information at the beginning stage of charging of the charging vehicle, such as the current power level of the charging vehicle.

[0123] The operating charging pile may be a charging pile in an output operating state.

[0124] The initial power may be the initial output power of the charging pile to the charging vehicle at the beginning of charging.

[0125] Specifically, due to different operating states of vehicles of different models or the same model, the required initial charging power is different. In order to improve the charging efficiency of different charging vehicles and protect the battery life of different charging vehicles, it is necessary to determine the initial power output of different operating charging piles based on the initial state information of the vehicle. While ensuring the charging efficiency and safety of the vehicle in the initial charging state, it provides basic data basis for the subsequent dynamic adjustment of the output power of the operating charging pile.

[0126] S202: Obtain an external influence factor of each operating charging pile and a real-time power of the corresponding vehicle, and dynamically adjust the real-time output power of each operating charging pile according to the external influence factor and the real-time power of the corresponding vehicle.

[0127] The external influencing factors may be a series of external influencing factors that affect the output power of the operating charging pile, such as temperature and humidity.

[0128] The real-time power level of the corresponding vehicle may be the real-time power level of the battery of the corresponding vehicle during the process of each operating charging pile charging the vehicle.

[0129] The real-time output power may be the charging power value output in real time when the charging pile is charging the vehicle.

[0130] Specifically, in the process of charging a vehicle with a charging pile, the output power of the charging pile is affected by a series of external factors, and is also affected by the constantly changing battery power of the vehicle during the charging process. Therefore, in order to ensure the safety of the charging process and protect the life of the vehicle battery, it is necessary to dynamically adjust the output power of the charging pile according to the external factors around the charging pile and the real-time power of the vehicle.

[0131] S203. Based on the real-time output power, obtain the current change data and the voltage change data of each operating charging pile, and determine the nonlinear load change information according to the current change data and the voltage change data.

[0132] The current change data may be the current size change data of the running charging pile during the charging period, and the current change data may be obtained through a current sensor built into the charging pile.

[0133] The voltage change data may be the voltage change data of the operating charging pile during the charging period, and the voltage change data may be obtained through a voltage sensor built into the charging pile.

[0134] The nonlinear load change information may be change data of the nonlinear relationship between the voltage and current in a charging system composed of a number of control devices, a number of cables, and a number of charging piles during the charging process.

[0135] Specifically, in the process of charging vehicles through charging piles, since there are several operating charging piles in the same charging system that charge several corresponding vehicles at the same time, and the output power of each operating charging pile is adjusted accordingly during the charging period as external influencing factors and vehicle status information change, the output power of each operating charging pile in the same period fluctuates frequently.

[0136] The above-mentioned frequent output power fluctuations may easily cause the relationship between the voltage and current in the charging system to no longer follow a simple linear relationship, thereby causing a nonlinear load in the charging system. The nonlinear load in the charging system will lead to decreased stability of the charging system, increased equipment losses and reduced energy efficiency. Therefore, it is necessary to monitor the nonlinear load change information in the charging system to provide an important data basis for making corresponding adjustments based on the nonlinear load change information.

[0137] S204: Analyze nonlinear load change information, and determine system resonance risk based on the analysis results.

[0138] The system resonance risk may be a risk level of resonance phenomenon currently occurring in the charging system.

[0139] Specifically, due to the nonlinear load in the charging system, the voltage and current in the charging line system no longer follow a simple linear relationship, but present a more complex nonlinear relationship, which makes the frequency characteristics of the charging system more complex. Moreover, since the resonance phenomenon of the charging system is due to the existence of a certain frequency in the charging system that matches the inherent frequency of the charging system, it can be inferred that the frequency characteristics caused by the nonlinear load in the charging system tend to be complex, which will increase the risk of system resonance. By analyzing the nonlinear load change information, the frequency of abnormal power factor fluctuations caused by the nonlinear load in the charging system is determined, thereby determining the resonance risk of the charging system to avoid the continuous accumulation of nonlinear loads and causing resonance of the charging system.

[0140] S205: Adjust the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk.

[0141] The optimal output power may be the real-time output power during the process of operating the charging pile to charge the vehicle.

[0142] Specifically, after the aforementioned technical scheme dynamically adjusts the real-time output power of the operating charging piles according to external influencing factors and vehicle status information, the power fluctuations of several operating charging piles will be frequent, and nonlinear loads will be generated in the charging system, thereby increasing the risk of system resonance. At this time, it is necessary to analyze the nonlinear load change information and system resonance risks in the charging system to obtain the optimal output power of each operating charging pile while reducing the nonlinear load and system resonance risks, so as to achieve a balance between the safety risks of the charging system and the charging efficiency.

[0143] The method of the present application first determines the initial power of the operating charging pile through the initial state information of the charging vehicle, and then, on the basis of the initial power, considers the influence of external influencing factors and the real-time power of the vehicle on the output power of the charging pile, and realizes dynamic adjustment of the real-time output power of the operating charging pile, while protecting the battery life of the vehicle, ensuring the safety of the charging process, and further, considering the nonlinear load of the charging system caused by the above-mentioned real-time output power adjustment and the change of the system resonance risk under the nonlinear load, the power of the operating charging pile is adjusted, and the optimal output power of each operating charging pile is obtained while reducing the nonlinear load and the system resonance risk, so as to achieve a balance between the safety risk of the charging system and the charging efficiency.

[0144] In some embodiments, the current power, basic charging power and maximum capacity of the charging vehicle are obtained, and the current power, basic charging power and maximum capacity are determined as initial state information; according to the initial state information, the initial powers of several operating charging piles are determined respectively, referring to formula (1):

[0145] (1)

[0146] in, is the initial power of the charging pile. is the basic charging power, is the current power, To accommodate the maximum power, is the benchmark parameter, To adjust the parameters.

[0147] The current power of the charging vehicle may be the real-time battery power of the charging vehicle during the charging process, and the current power of the charging vehicle may be obtained through a charging pile that supports OBD interface communication or an on-board communication protocol.

[0148] The basic charging power can be the required charging power obtained by the electric vehicle during factory testing. The basic charging power is a factory parameter of the electric vehicle. The specific value can be obtained through communication between the charging pile and the charging vehicle that supports OBD interface communication or vehicle communication protocol.

[0149] The maximum capacity may be the maximum amount of electrical energy that an electric vehicle battery can hold. The maximum capacity is a standard parameter for electric vehicles, and the specific value may be obtained through communication between a charging pile that supports OBD interface communication or vehicle communication protocol and the charging vehicle.

[0150] The benchmark parameter can be the maximum value of the initial power of the charging pile. When it approaches infinity, formula (1) approaches the value of . The benchmark parameters can be obtained based on a large amount of charging data and tested according to formula (1).

[0151] The adjustment parameter may be a parameter used to adjust the strength of the parameter in the exponential function in formula (1). The adjustment parameter may be obtained based on a large amount of charging data and tested according to formula (1).

[0152] Specifically, due to different models of vehicles and different operating states of the same model of vehicles, the required initial charging power is different, and the required initial charging power of the vehicle is correlated with the current power, basic charging power and maximum capacity of the charging vehicle. Therefore, by obtaining the current power, basic charging power and maximum capacity of the charging vehicle, the accurate initial charging power data required by the current charging vehicle can be calculated according to formula (1), providing accurate data basis for the subsequent dynamic adjustment of the output power of the charging pile.

[0153] In the method of this embodiment, by obtaining the current power, basic charging power and maximum capacity of the charging vehicle, the accurate initial charging power data required by the current charging vehicle is calculated according to formula (1), so as to provide an accurate data basis for the subsequent dynamic adjustment of the output power of the charging pile, so as to ensure that the output power of the charging pile after the subsequent dynamic adjustment can ensure the charging efficiency of different charging vehicles.

[0154] In some embodiments, the real-time power value of each running charging pile is determined by formula (2) according to the battery temperature, basic charging power, temperature value, humidity value, corresponding vehicle real-time power and maximum capacity:

[0155] (2)

[0156] in, is the real-time power value, is the basic charging power, is the humidity value, is the temperature value, is the battery temperature, The real-time power of the vehicle. To accommodate the maximum power, is the benchmark parameter, To adjust the parameters; according to the real-time power value of each running charging pile, the real-time output power of each running charging pile is adjusted in real time.

[0157] The battery temperature may be the real-time temperature of the battery inside the currently charged vehicle, and the battery temperature may be obtained through communication between a charging pile supporting an on-board communication protocol and the charging vehicle.

[0158] The temperature value may be an ambient temperature value around the running charging pile, and the temperature value may be obtained by a temperature sensor disposed on the running charging pile.

[0159] The humidity value may be a humidity value of the environment around the running charging pile, and the humidity value may be obtained by a humidity sensor disposed on the running charging pile.

[0160] Specifically, during the process of charging the vehicle with the charging pile, the real-time power of the charging pile is affected by external factors, such as ambient temperature and humidity. When the external temperature is too high, such as in the summer, the output power of the charging pile should be adjusted to prevent the temperature of the charging pile from overloading. When the external humidity is too high, such as in rainy days, the output power of the charging pile should be adjusted to prevent leakage during the charging process. At the same time, the battery temperature of the vehicle will also change dynamically during the charging process. To prevent the battery from overheating, the output power of the charging pile also needs to be adjusted. Therefore, by obtaining the temperature value, humidity value and the real-time power of the corresponding vehicle, and comprehensively considering the basic charging power and the maximum capacity, the optimal output power value required for the current charging pile to ensure the charging efficiency of the charging vehicle under the current temperature, humidity and battery temperature is calculated according to formula (2), and the real-time output power of the charging pile is adjusted according to the optimal output power value.

[0161] In the method of this embodiment, on the basis of considering the basic charging power and the maximum capacity to ensure the charging efficiency in the previous embodiment, the influence of the external temperature, external humidity and the vehicle battery temperature on the output power of the running charging pile is further considered. The design formula (2) accurately calculates the optimal output power value required for the current running charging pile to ensure the charging efficiency of the charging vehicle under the current temperature, humidity and battery temperature, and adjusts the real-time output power of the running charging pile according to the optimal output power value. Under the condition of ensuring the charging efficiency of the vehicle, safety accidents caused by the influence of external temperature, external humidity and battery temperature are avoided, thereby further improving the safety of the charging process.

[0162] In some embodiments, the current change data and the voltage change data are analyzed to determine the useful power change data of each operating charging pile; the power factor change data is determined based on the current change data, the voltage change data and the useful power change data; the power factor change data is analyzed to determine the nonlinear load change information.

[0163] The useful power change data may be the change data of the conversion of electrical energy into useful power during the charging process of the charging pile, and the useful power change data may reflect the performance of the charging pile.

[0164] The power factor change data may be the power factor change data of the charging system during the charging process, and the power factor change data may reflect the load state change of the charging system.

[0165] Specifically, when a nonlinear load is generated in the charging system, it will directly affect the change of the power factor in the charging system. The change of the power factor is closely related to the current change, voltage change and useful power change in the charging system. Therefore, the useful power change data of the charging system during the charging period is determined based on the current change data and the voltage change data. Then, the power factor change data of the charging system during the charging period can be obtained by combining the current change data, the voltage change data and the useful power change data. By analyzing the power factor change data, the nonlinear load change information of the charging system during the charging period can be obtained.

[0166] The method of this embodiment obtains useful power change data based on current change data and voltage change data, and then determines power factor change data that can accurately reflect the nonlinear load by combining the current change data, voltage conversion data and useful power change data, and then determines nonlinear load change information based on the power factor change data, thereby providing accurate nonlinear load change information for subsequent adjustment of the optimal output power of the charging pile for the nonlinear load.

[0167] In some embodiments, the phase angle change data is determined according to the current change data and the voltage change data; and the useful power value of each running charging pile at different time points is calculated respectively according to the current change data, the voltage change data and the phase angle change data by the following formula:

[0168] (3)

[0169] in, For the Charging piles in operation at time point The useful power value at For the Charging piles in operation at time point The voltage value at For the Charging piles in operation at time point The current value at For the Charging piles in operation at time point The phase angle data of the current and voltage at different time points is used to determine the useful power change data of each running charging pile during the charging period.

[0170] The phase angle change data may be the change data of the phase angle corresponding to the current and voltage changes in the running charging pile. The phase angle change data may be detected by a phase sensor in the charging pile based on the current change data and the voltage change data.

[0171] Specifically, the useful power value is related to the current, voltage and the phase angle between the current and voltage. To determine the useful power change data of the operating charging pile during the charging period, it is necessary to comprehensively consider the current change, voltage change and phase angle change caused by the current and voltage changes of the operating charging pile during the charging period. Therefore, based on the current change data, voltage change data and phase angle change data, formula (3) is designed to calculate the useful power value of each operating charging pile during the charging period at different time points. Then, after comprehensively calculating the useful power values ​​of each operating charging pile during the charging period at different time points, the useful power change data of each operating charging pile during the charging period is determined.

[0172] The method of this embodiment is based on the current change data, voltage change data and phase angle change data of each operating charging pile during the charging period, and according to the current value, voltage value and phase angle data of each operating charging pile at different time points, the useful power change data of each operating charging pile during the charging period is accurately calculated by formula (3), which provides an important and accurate data basis for the subsequent use of the useful power change data to obtain the power factor change data that can reflect the nonlinear load condition of the charging system.

[0173] In some embodiments, the power factor at different time points is calculated according to the current change data, the voltage change data and the useful power change data by using formula (4):

[0174] (4)

[0175] in, For time point The power factor at For the Charging piles in operation at time point The useful power value at For the Charging piles in operation at time point The voltage value at For the Charging piles in operation at time point The current value at that time; according to the power factor at different time points, the power factor change data is determined.

[0176] It should be noted that the power factor calculated by formula (4) is the power factor of the entire charging system at different time points.

[0177] Specifically, analyzing the change of the overall power factor of the charging system can reflect the nonlinear load state of the entire charging system. The change of the overall power factor of the charging system requires a comprehensive analysis of the ratio of the useful power of each operating charging pile in the charging system to the total power. Therefore, based on the useful power change data of each operating charging pile, combined with the current change data and voltage change data of each operating charging pile, the power factor of the entire charging system at different time points is calculated by formula (4). By comprehensively counting the power factors at different time points, the power factor change data of the entire charging system can be determined.

[0178] In the method of this embodiment, the ratio of the useful power to the total power of each operating charging pile in the charging system is comprehensively analyzed by formula (4), and the power factor change at different time points is obtained, so as to determine the power factor change data, which provides an accurate comprehensive data basis for determining the nonlinear load change information based on the power factor change data.

[0179] In some embodiments, a power factor change curve is generated based on power factor change data; the power factor change curve is analyzed, and the power factor values ​​in the power factor change curve are compared with preset rated power factor values ​​respectively. If there is a situation in the power factor change curve where the current power factor value is less than the preset rated power factor value, the current power factor value is determined as a suspicious power factor value; the difference ratio between the suspicious power factor value and the preset rated power factor value is compared with a preset power factor difference ratio threshold value. If the difference ratio is greater than the preset power factor difference ratio threshold value, the suspicious power factor value is determined as an abnormal power factor value; the corresponding time point of the abnormal power factor value in the power factor change curve is taken as the abnormal starting point, and the corresponding time point of the most recent normal power factor value in the power factor change curve is taken as the abnormal end point, and the time length and curve waveform between the abnormal starting point and the abnormal end point are recorded; based on the time length and the curve waveform, nonlinear load change information is determined.

[0180] The power factor variation curve may be a curve reflecting the variation of the overall power factor value in the charging system over time, and the power factor variation curve may be obtained based on the power factor variation data.

[0181] The preset rated power factor value may be a power factor value of the charging system under rated operating conditions. The preset rated power factor value may be obtained through simulation testing of the charging system during the design phase of the charging system, and may be set between 0.9 and 1.0. This application does not make any specific limitation.

[0182] The preset power factor difference ratio threshold may be the maximum difference ratio allowed between the current power factor and the preset rated power factor value. The preset power factor difference ratio threshold may be set according to the actual situation of the charging system and may be set to 10%. This application does not make any specific limitation.

[0183] The most recent normal power factor value may be a normal power factor value that is closest to the current abnormal power factor value in the time variation direction in the power factor variation curve.

[0184] The time length may be a time length value between an abnormal starting point and an abnormal end point in the time variation direction of the power factor variation curve, reflecting the time span between the two.

[0185] The curve waveform may be a curve segment waveform between an abnormal starting point and an abnormal end point in the power factor variation curve.

[0186] The difference ratio between the suspected power factor value and the preset rated power factor value can be calculated by referring to formula (5):

[0187] (5)

[0188] in, is the difference ratio, is the questionable power factor value, is the preset rated power factor value.

[0189] Specifically, when a nonlinear load appears in the charging system, the useless power in the charging system increases, causing the ratio between useful power and total power to decrease, so that the power factor value in the charging system shows a downward trend based on the preset rated power factor value. Therefore, the corresponding power factor value whose power factor change curve is less than the preset rated power factor value can be determined as a suspicious power factor value. When the power factor value is significantly lower than the preset rated power factor value, it can be determined that there is a nonlinear load in the charging system. Therefore, by comparing the difference ratio between the suspicious power factor value and the preset rated power factor value with the preset power factor difference ratio threshold, it is determined whether the suspicious power factor value reflects the charging system. There is an abnormal power factor value of a nonlinear load in the electrical system. After determining the abnormal power factor value, since the nonlinear load does not appear in the charging system at a single time point, it is necessary to record the time length between the abnormal starting point and the abnormal end point as the time span of the nonlinear load in the charging system. At the same time, since the frequent fluctuations in the power factor caused by the nonlinear load may cause resonance in the charging system, it is necessary to record the curve waveform between the abnormal starting point and the abnormal end point, so as to determine the system resonance risk by analyzing the curve waveform later, and then comprehensively count the time length and the curve waveform to obtain the fluctuation curve of the abnormal power factor value, and use the fluctuation curve of the primary power factor value as the nonlinear load information.

[0190] In the method of this embodiment, a power factor change curve is obtained based on the power factor change data, and the abnormal power factor value that can reflect the nonlinear load in the power factor curve is determined, and then the time length and curve waveform between the abnormal power factor value and the most recent normal power factor value are recorded, and the nonlinear load change information is determined by statistically analyzing the time length and the curve waveform, thereby improving the sensitivity of the nonlinear load change information, so that the nonlinear load change information can accurately and intuitively reflect the nonlinear load state, thereby making the subsequent system resonance risk determined based on the nonlinear load change information more accurate.

[0191] In some embodiments, the fluctuation frequency curve of the abnormal power factor is determined based on the time length and the curve waveform; the system inherent frequency curve is obtained, the fluctuation frequency curve and the system inherent frequency curve are analyzed, and the curve correlation coefficient is determined; based on the curve correlation coefficient, the system resonance risk is determined.

[0192] The abnormal power factor fluctuation frequency curve may be a frequency curve in which the abnormal power factor value fluctuates over time.

[0193] The frequency curve corresponding to each curve waveform and time length can be obtained through the following Fourier transform formula:

[0194] ;

[0195] in, is the frequency curve corresponding to the curve waveform and time length, is the length of time, For time point The abnormal power factor value at is an imaginary unit, It is the abnormal power factor value fluctuation frequency under the current curve waveform.

[0196] It should be noted that the abnormal power factor value fluctuation frequency under the current curve waveform can be obtained by analyzing and calculating the curve waveform through an existing fast Fourier transform algorithm, such as the Cooley-Tukey algorithm.

[0197] Then, according to the frequency curve corresponding to each curve waveform and time length, the fluctuation frequency curve of the abnormal power factor is expressed by formula (5):

[0198] (5)

[0199] in, is the abnormal power factor fluctuation frequency curve, For the The weight of the curve waveform, For the The frequency curve corresponding to the waveform.

[0200] It should be noted that the division of the weights of the curve waveforms can be set according to the ratio of the length of the curve waveform to the length of the entire power factor change curve, and this application does not make any specific limitation.

[0201] The curve correlation coefficient can be a coefficient value used to express the similarity between the fluctuation frequency curve and the system natural frequency curve. The curve correlation coefficient can be calculated by substituting the fluctuation frequency curve and the system natural frequency curve into the existing curve correlation coefficient calculation formula, such as the Pearson correlation coefficient formula and the Spearman formula, to obtain the correlation coefficient value. The closer the correlation coefficient is to 1, the higher the similarity between the fluctuation frequency curve and the system natural frequency curve, and the greater the system resonance risk. Conversely, the closer the correlation coefficient is to 0, the lower the similarity between the fluctuation frequency curve and the system natural frequency curve, and the smaller the system resonance risk.

[0202] The method of this embodiment is to obtain the fluctuation frequency curve of the abnormal power factor value by analyzing the time length and the curve waveform, and then evaluate the system resonance risk through the correlation coefficient between the fluctuation frequency curve and the system natural frequency curve, so that the final system resonance risk can accurately reflect whether the fluctuation of the abnormal power factor under the influence of nonlinear load will cause system resonance, thereby providing accurate quantitative data for avoiding system resonance.

[0203] In some embodiments, the curve correlation coefficient is compared with a preset curve correlation coefficient threshold; if the curve correlation coefficient is greater than the preset curve correlation coefficient threshold, the nonlinear load change information is analyzed to determine the power factor adjustment value; based on the real-time output power of each operating charging pile, the current total power value is determined, and based on the power factor adjustment value, the current total power value and the real-time output power of each operating charging pile, the required adjustment power value of each operating charging pile is determined; based on the required adjustment power value, the optimal output power of each operating charging pile is adjusted.

[0204] The preset curve correlation coefficient threshold may be the maximum value that the curve correlation coefficient can reach when no system resonance occurs. If the curve correlation coefficient exceeds the preset curve correlation coefficient threshold, it indicates that there is a high probability that the current charging system will experience system resonance. The preset curve correlation coefficient may be set to 0.7, or may be adjusted according to the actual situation of the charging system. This application does not make any specific limitation.

[0205] The current total power value is the overall output power in the current charging system. The current total power value may be the sum of the real-time output power of each operating charging pile.

[0206] The power factor adjustment value may be a value that needs to be adjusted for the current power factor value in order to avoid system resonance of the current charging system and reduce nonlinear loads by adjusting the current power factor value.

[0207] Specifically, when the nonlinear load level in the charging system is high, it will cause a decrease in power factor and frequent fluctuations, which will make the frequency information in the charging system complicated, and ultimately lead to an increasing risk of system resonance. When the curve correlation coefficient exceeds the preset curve correlation coefficient threshold, it means that if the current charging system still works according to the current power output strategy, then the charging system will resonate. At this time, by analyzing the nonlinear load change information, the average value of the abnormal power factor in the current abnormal power factor change curve is determined, and then the difference between the abnormal power factor average value and the rated power factor value is determined as the power factor adjustment value.

[0208] According to the power factor adjustment value, the current total power value and the real-time output power of each running charging pile, the required adjustment power value of each running charging pile is determined, referring to formula (6):

[0209] (6)

[0210] in, For the The required adjustment power value of a running charging pile, is the power factor adjustment value, is the current total power value, For the The real-time output power of a running charging pile.

[0211] Finally, the optimal output power of each operating charging pile is adjusted according to the required adjustment power value of each operating charging pile.

[0212] According to the method of this embodiment, in the case of possible system resonance, the power factor adjustment value required for adjusting the current power factor value in order to avoid system resonance and reduce nonlinear load is obtained by analyzing the nonlinear load change information. Based on the power factor adjustment value, combined with the current total power value and the real-time output power of each operating charging pile, the required adjustment power value of each operating charging pile is determined respectively, and then the optimal output power of each operating charging pile is adjusted according to the required adjustment power value of each operating charging pile, which effectively avoids the occurrence of system resonance, reduces the failure rate of charging piles, reduces nonlinear loads, improves the stability of charging piles, and further ensures the safety of the charging process.

[0213] Figure 3 A schematic diagram of a charging management system based on the Internet of Things provided in one embodiment of the present application is shown in FIG. Figure 3As shown, the IoT-based charging management system 300 of this embodiment includes: an initial power determination module 301 , a real-time adjustment module 302 , a load monitoring module 303 , a resonance analysis module 304 and a power adjustment module 305 .

[0214] The initial power determination module 301 is used to obtain initial state information of a plurality of charging vehicles and determine the initial powers of a plurality of operating charging piles according to the initial state information;

[0215] A real-time adjustment module 302 is used to obtain the external influence factor of each running charging pile and the real-time power of the corresponding vehicle, and dynamically adjust the real-time output power of each running charging pile according to the external influence factor and the real-time power of the corresponding vehicle;

[0216] A load monitoring module 303 is used to obtain current change data and voltage change data of each running charging pile based on the real-time output power, and determine nonlinear load change information according to the current change data and voltage change data;

[0217] A resonance analysis module 304 is used to analyze the nonlinear load change information and determine the system resonance risk according to the analysis result;

[0218] The power adjustment module 305 is used to adjust the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk.

[0219] Optionally, the initial power determination module 301 is specifically configured to:

[0220] Acquire the current power, basic charging power and maximum capacity of the charging vehicle, and determine the current power, basic charging power and maximum capacity as the initial state information;

[0221] According to the initial state information, the initial powers of several running charging piles are determined respectively, referring to the following formula:

[0222] ;

[0223] in, is the initial power of the running charging pile, is the basic charging power, is the current power, is the maximum capacity capacity, is the benchmark parameter, To adjust the parameters.

[0224] Optionally, the real-time adjustment module 302 is specifically configured to:

[0225] According to the battery temperature, the basic charging power, the temperature value, the humidity value, the corresponding vehicle real-time power and the maximum capacity, the real-time power value of each running charging pile is determined by the following formula:

[0226] ;

[0227] in, is the real-time power value, is the basic charging power, is the humidity value, is the temperature value, is the battery temperature, is the real-time power of the vehicle, is the maximum capacity capacity, is the benchmark parameter, To adjust the parameters;

[0228] According to the real-time power value of each running charging pile, the real-time output power of each running charging pile is adjusted in real time.

[0229] Optionally, the load monitoring module 303 is specifically used to:

[0230] Analyze the current change data and the voltage change data to determine useful power change data of each operating charging pile;

[0231] Determining power factor change data according to the current change data, the voltage change data and the useful power change data;

[0232] The power factor change data is analyzed to determine the nonlinear load change information.

[0233] Optionally, the load monitoring module 303 is specifically used to:

[0234] Determining phase angle change data according to the current change data and the voltage change data;

[0235] According to the current change data, the voltage change data and the phase angle change data, the useful power value of each running charging pile at different time points is calculated by the following formula:

[0236] ;

[0237] in, For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at For the The charging piles are in operation at time point Phase angle data of current and voltage at the time;

[0238] According to the useful power value of each operating charging pile at different time points, the useful power change data of each operating charging pile during the charging period is determined.

[0239] Optionally, the load monitoring module 303 is specifically used to:

[0240] According to the current change data, the voltage change data and the useful power change data, the power factor at different time points is calculated respectively by the following formula:

[0241] ;

[0242] in, For time point The power factor at For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at

[0243] Power factor variation data is determined according to the power factors at different time points.

[0244] Optionally, the load monitoring module 303 is specifically used to:

[0245] Generating a power factor change curve according to the power factor change data;

[0246] Analyze the power factor change curve, compare the power factor values ​​in the power factor change curve with the preset rated power factor values ​​respectively, and if there is a situation in the power factor change curve where the current power factor value is less than the preset rated power factor value, determine the current power factor value as a suspicious power factor value;

[0247] Comparing the difference ratio between the suspicious power factor value and the preset rated power factor value with a preset power factor difference threshold, and if the difference ratio is greater than the preset power factor difference threshold, determining the suspicious power factor value as an abnormal power factor value;

[0248] The time point corresponding to the abnormal power factor value in the power factor change curve is taken as the abnormal starting point, the time point corresponding to the most recent normal power factor value in the power factor change curve is taken as the abnormal end point, and the time length and curve waveform between the abnormal starting point and the abnormal end point are recorded;

[0249] The nonlinear load change information is determined according to the time length and the curve waveform.

[0250] Optionally, the resonance analysis module 304 is specifically used to:

[0251] Determining an abnormal power factor fluctuation frequency curve according to the time length and the fluctuation information;

[0252] Obtaining a system natural frequency curve, analyzing the fluctuation frequency curve and the system natural frequency curve, and determining a curve correlation coefficient;

[0253] The system resonance risk is determined according to the curve correlation coefficient.

[0254] Optionally, the power adjustment module 305 is specifically used to:

[0255] Comparing the curve correlation coefficient with a preset curve correlation coefficient threshold;

[0256] If the curve correlation coefficient is greater than a preset curve correlation coefficient threshold, analyzing the nonlinear load change information to determine a power factor adjustment value;

[0257] Determine the current total power value according to the real-time output power of each operating charging pile, and determine the required adjustment power value of each operating charging pile according to the power factor adjustment value, the current total power value and the real-time output power of each operating charging pile;

[0258] According to the required adjusted power value, the optimal output power of each operating charging pile is adjusted.

[0259] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A charging management method based on the Internet of Things, characterized in that: include: Acquire initial state information of a plurality of charging vehicles, and determine initial powers of a plurality of operating charging piles respectively according to the initial state information; Obtaining the external influence factor of each running charging pile and the real-time power of the corresponding vehicle, and dynamically adjusting the real-time output power of each running charging pile according to the external influence factor and the real-time power of the corresponding vehicle; Based on the real-time output power, current change data and voltage change data of each running charging pile are obtained, and nonlinear load change information is determined according to the current change data and voltage change data; Analyzing the nonlinear load change information, and determining the system resonance risk according to the analysis result; According to the nonlinear load change information and the system resonance risk, adjusting the optimal output power of each operating charging pile; The external influencing factors include temperature value, humidity value and battery temperature. According to the external influencing factors and the real-time power of the corresponding vehicle, the real-time output power of each running charging pile is dynamically adjusted, including: Obtaining the current power, basic charging power and maximum capacity of the charging vehicle; According to the battery temperature, the basic charging power, the temperature value, the humidity value, the corresponding vehicle real-time power and the maximum capacity, the real-time power value of each running charging pile is determined by the following formula: ； in, is the real-time power value, is the basic charging power, is the humidity value, is the temperature value, is the battery temperature, is the real-time power of the vehicle, is the maximum capacity, is the benchmark parameter, To adjust the parameters; According to the real-time power value of each running charging pile, adjusting the real-time output power of each running charging pile in real time; The determining of nonlinear load change information according to the current change data and the voltage change data includes: Analyze the current change data and the voltage change data to determine useful power change data of each operating charging pile; Determining power factor change data according to the current change data, the voltage change data and the useful power change data; Analyzing the power factor change data to determine the nonlinear load change information; The analyzing the power factor change data to determine the nonlinear load change information includes: Generating a power factor change curve according to the power factor change data; Analyze the power factor change curve, compare the power factor values ​​in the power factor change curve with the preset rated power factor values ​​respectively, and if there is a situation in the power factor change curve where the current power factor value is less than the preset rated power factor value, determine the current power factor value as a suspicious power factor value; Comparing the difference ratio between the suspicious power factor value and the preset rated power factor value with a preset power factor difference threshold, and if the difference ratio is greater than the preset power factor difference threshold, determining the suspicious power factor value as an abnormal power factor value; The time point corresponding to the abnormal power factor value in the power factor change curve is taken as the abnormal starting point, the time point corresponding to the most recent normal power factor value in the power factor change curve is taken as the abnormal end point, and the time length and curve waveform between the abnormal starting point and the abnormal end point are recorded; Determining the nonlinear load change information according to the time length and the curve waveform; The analyzing the nonlinear load change information and determining the system resonance risk according to the analysis result includes: Determining an abnormal power factor fluctuation frequency curve according to the time length and the curve waveform; Obtaining a system natural frequency curve, analyzing the fluctuation frequency curve and the system natural frequency curve, and determining a curve correlation coefficient; Determining the system resonance risk according to the curve correlation coefficient; The adjusting the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk includes: Comparing the curve correlation coefficient with a preset curve correlation coefficient threshold; If the curve correlation coefficient is greater than a preset curve correlation coefficient threshold, analyzing the nonlinear load change information to determine a power factor adjustment value; Determine the current total power value according to the real-time output power of each operating charging pile, and determine the required adjustment power value of each operating charging pile according to the power factor adjustment value, the current total power value and the real-time output power of each operating charging pile; According to the required adjusted power value, the optimal output power of each operating charging pile is adjusted.

2. The method according to claim 1, characterized in that The obtaining of initial state information of a plurality of charging vehicles and determining initial powers of a plurality of operating charging piles respectively according to the initial state information include: Determine the current power, the basic charging power and the maximum capacity as the initial state information; According to the initial state information, the initial powers of several running charging piles are determined respectively, referring to the following formula: ； in, is the initial power of the running charging pile, is the basic charging power, is the current power, is the maximum capacity, is the benchmark parameter, To adjust the parameters.

3. The method according to claim 1, characterized in that: The analyzing the current change data and the voltage change data to determine the useful power change data of each operating charging pile includes: Determining phase angle change data according to the current change data and the voltage change data; According to the current change data, the voltage change data and the phase angle change data, the useful power value of each running charging pile at different time points is calculated by the following formula: ; in, For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at For the The charging piles are in operation at time point Phase angle data of current and voltage at the time; According to the useful power value of each operating charging pile at different time points, the useful power change data of each operating charging pile during the charging period is determined.

4. The method according to claim 2, characterized in that: Determining the power factor change data according to the current change data, the voltage change data and the useful power change data includes: According to the current change data, the voltage change data and the useful power change data, the power factor at different time points is calculated respectively by the following formula: ； in, For time point The power factor at For the The charging piles are in operation at time point The useful power value at For the The charging piles are in operation at time point The voltage value at For the The charging piles are in operation at time point The current value at Power factor variation data is determined according to the power factors at different time points.

5. A charging management system based on the Internet of Things, characterized in that: The method as claimed in any one of claims 1 to 4 comprises: An initial power determination module is used to obtain initial state information of a plurality of charging vehicles and determine the initial powers of a plurality of operating charging piles according to the initial state information; A real-time adjustment module is used to obtain the external influence factor of each running charging pile and the real-time power of the corresponding vehicle, and dynamically adjust the real-time output power of each running charging pile according to the external influence factor and the real-time power of the corresponding vehicle; A load monitoring module, configured to obtain current change data and voltage change data of each running charging pile based on the real-time output power, and determine nonlinear load change information according to the current change data and voltage change data; A resonance analysis module, used to analyze the nonlinear load change information and determine the system resonance risk according to the analysis result; The power adjustment module is used to adjust the optimal output power of each operating charging pile according to the nonlinear load change information and the system resonance risk.

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