A vehicle charger analysis system and method based on weighted algorithm

Abstract

The present invention discloses a vehicle charger analysis system and method based on a weighted algorithm, which relates to the field of analysis systems. The system includes: an input interface for receiving real-time power from a vehicle power supply; an output interface connected to a charged device; a control unit including a microprocessor with processing capabilities and running a weighted algorithm to evaluate and adjust charging parameters; a memory for storing preset weighted parameters and historical charging data; a current and voltage sensor for real-time monitoring of current and voltage changes during charging; and a communication module for realizing interaction between the current and voltage sensor, the control unit, and the vehicle. The present invention optimizes charging efficiency and safety by processing the data obtained by the charging current and voltage sensors and adjusting the charging parameters accordingly.

Description

Technical Field

[0001] The present invention belongs to the field of analysis systems, and more specifically, it particularly relates to an on-board charger analysis system based on a weighted algorithm. Meanwhile, the present invention also relates to an on-board charger analysis method based on a weighted algorithm. Background Art

[0002] The composition of new energy electric vehicles includes electric drive and control system, driving force transmission mechanical system, and working devices to complete the given tasks. The electric drive and control system is the core of electric vehicles and the biggest difference from internal combustion engine vehicles. The on-board charger of new energy electric vehicles is very important and requires strict quality control.

[0003] In the prior art, when charging new energy electric vehicles through an on-board charger, the on-board charger cannot analyze the status of the charged vehicle and the voltage and current data of the charging power supply, resulting in the use of a uniform voltage and current value for charging, and the charging efficiency and charging safety cannot be guaranteed. Therefore, we propose an on-board charger analysis system and method based on a weighted algorithm. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and propose a vehicle charger analysis system and method based on a weighted algorithm to process the data obtained by the charging current and voltage sensors, and adjust the charging parameters accordingly to optimize the charging efficiency and safety.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A vehicle charger analysis system based on a weighted algorithm, comprising:

[0007] An input interface for receiving real-time power from a vehicle power source;

[0008] Output interface, connected to the charged device;

[0009] a control unit including a microprocessor having processing power and running a weighted algorithm to evaluate and adjust charging parameters;

[0010] A memory, used to store preset weighted parameters and historical charging data;

[0011] Current and voltage sensors monitor the current and voltage changes during charging in real time;

[0012] A communication module for realizing the interaction between the current and voltage sensors, the control unit and the vehicle;

[0013] The control unit processes the data obtained by the charging current and voltage sensors according to a weighted algorithm, and adjusts the charging parameters accordingly to optimize the charging efficiency and safety.

[0014] Preferably, in the weighted algorithm, the factors considered include:

[0015] The magnitude of the charging current and its rate of change;

[0016] Stability of charging voltage;

[0017] Charging status and historical data of the charged device;

[0018] Ambient temperature.

[0019] A vehicle charger analysis method based on a weighted algorithm comprises the following steps:

[0020] S1. The control unit receives real-time power from the vehicle power supply through the input interface and ensures that the output interface is connected to the charged device;

[0021] S2, the user or the automatic program interacts with the control unit through the communication module to set initial charging parameters, including current and voltage, and store them in the memory;

[0022] S3, turn on the current and voltage sensors to monitor the current size, its change rate, and voltage stability data during the charging process in real time;

[0023] S4, the microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to the preset weighted parameters;

[0024] S5. The control unit dynamically adjusts the charging parameters output to the charged device according to the weighted score;

[0025] S6. Storing the real-time monitoring data and the adjusted charging parameters in a memory as historical charging data for subsequent analysis and optimization;

[0026] S7. During the charging process, continuously monitor safety indicators and notify the user through the communication module when the threshold is reached, and interrupt charging to protect the device when necessary;

[0027] S8. After completing the charging cycle, the control unit provides a complete charging report through the communication module, including efficiency evaluation, problem records and optimization suggestions.

[0028] Preferably, the microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to preset weighted parameters, specifically:

[0029] S41. Set a weight for each influencing factor;

[0030] Among them, the weight of the charging current (I) is: ωI;

[0031] Weight of the rate of change of charging current (ΔI): ωΔI;

[0032] Weight of charging voltage stability (V): ωV;

[0033] The weight of the charging state (S) of the charged device: ωS;

[0034] Weight of ambient temperature (T): ωT;

[0035] S42. Standardize all measurement parameters to the same range to facilitate comparison;

[0036] S43. For each factor, multiply its standardized value by the corresponding weight to obtain a weighted input value, and the calculation formula is:

[0037] X 加权输入 =ωX×X 标准化参数 ;

[0038] In the formula, X 加权输入 is the ideal value of a factor after weighted calculation, ωX is the weight value of the factor, X 标准化参数 is the standardized value of the factor;

[0039] S44. All weighted input values ​​are added together to obtain a total weighted score; the calculation formula is:

[0040] Text 加权得分 =∑ i X 加权输入 ;

[0041] S45. Adjust charging parameters based on the total weighted score and with reference to a preset mapping table.

[0042] Preferably, step S42 standardizes all measurement parameters to the same range for comparison, and the standardization calculation formula is:

[0043]

[0044] In the formula, X 实际值 is the actual measured value of a factor, I 最大值 is the theoretical maximum value of the measured parameter of this factor, I 最小值 It is the theoretical minimum value of the measured parameter of this factor.

[0045] Preferably, the mapping table preset in step S45 is established by the following steps:

[0046] Collect charging efficiency and safety data under different charging parameters, covering all key influencing factors, including current size, current change rate, voltage stability, charging status of the charged device and ambient temperature;

[0047] Set weights for each factor based on its impact on charging efficiency and safety;

[0048] Using known data and weights, a model is established through mathematical modeling to map weighted scores to charging parameter adjustment strategies;

[0049] Verify the accuracy and effectiveness of the mapping relationship or function through actual analysis.

[0050] Preferably, the initial preset of the mapping table is specifically:

[0051] 0.8<Text 加权得分 ≤1.0, output decreases by 10%;

[0052] 0.6<Text 加权得分 ≤0.8, the output remains unchanged;

[0053] 0.4<Text 加权得分 ≤0.6, output increased by 10%;

[0054] 0.2<Text 加权得分 ≤0.4, output increased by 20%;

[0055] 0.0<Text 加权得分 ≤0.2, output increased by 30%;

[0056] The mapping table is updated as time goes by and data accumulates, and the update is iteratively updated by mapping the weighted scores to a model of the charging parameter adjustment strategy.

[0057] Preferably, the step of establishing a model that maps weighted scores to charging parameter adjustment strategies through mathematical modeling specifically includes:

[0058] Collect historical charging data and pre-process the data;

[0059] Calculate the weighted score; use the determined weight ωX and the normalized measurement parameter X 标准化参数 , calculate the weighted score W according to the following formula:

[0060]

[0061] In the formula, ωX is the weight determined by a certain factor, X 标准化参数 is the standardized measurement parameter of the factor, where n is the number of influencing factors and cdot indicates that the calculation formula is a vector function;

[0062] Establish a mapping model and use the collected historical data as a training set to train the model by minimizing the difference between actual and predicted charging parameter adjustment values;

[0063] Deploy the trained model to the charger's control system and adjust the charging parameters in real time during the actual charging process;

[0064] The model is continuously retrained and optimized based on new charging data to adapt to changes in charging behavior.

[0065] Preferably, the establishment of the mapping model is expressed as:

[0066] The mapping model is established as follows:

[0067] y=mW x +b

[0068] Where y is the predicted charging parameter adjustment, including current and voltage parameter adjustments, m is the slope, b is the intercept, and W x Represents the weighted scores of current and voltage respectively.

[0069] Technical effects and advantages of the present invention: The present invention provides a vehicle charger analysis system and method based on a weighted algorithm. Compared with the conventional technology, the present invention processes the data obtained by the charging current and voltage sensors and adjusts the charging parameters accordingly to optimize the charging efficiency and safety.

[0070] Secondly, by adopting weighted calculation, different weights can be assigned according to the importance or influence of the data, making the calculation results more in line with the actual situation. At the same time, through weighted calculation, it can more accurately reflect the role of different data in the whole, thereby obtaining more accurate results. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a diagram of the architecture of the on-board charger analysis system based on the weighted algorithm of the present invention;

[0072] Figure 2 The flowchart of the vehicle charger analysis method based on the weighted algorithm of the present invention;

[0073] Figure 3 This is a flow chart for calculating the weighted score of data obtained by the charging current and voltage sensors in an embodiment of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0075] The present invention provides a vehicle charger analysis system based on a weighted algorithm, such as Figure 1 As shown, including:

[0076] An input interface for receiving real-time power from a vehicle power source;

[0077] Output interface, connected to the charged device;

[0078] A control unit includes a microprocessor with processing power and runs a weighted algorithm to evaluate and adjust charging parameters; wherein the weighted algorithm considers factors including: the magnitude of the charging current and its rate of change; the stability of the charging voltage; the charging status and historical data of the charged device; and the ambient temperature;

[0079] A memory, used to store preset weighted parameters and historical charging data;

[0080] Current and voltage sensors monitor the current and voltage changes during charging in real time;

[0081] A communication module for realizing the interaction between the current and voltage sensors, the control unit and the vehicle;

[0082] The control unit processes the data obtained by the charging current and voltage sensors according to a weighted algorithm, and adjusts the charging parameters accordingly to optimize the charging efficiency and safety.

[0083] As described above, the control unit processes the data obtained from the charging current and voltage sensors, and adjusts the charging parameters accordingly to optimize the charging efficiency and safety.

[0084] This embodiment also provides a vehicle charger analysis method based on a weighted algorithm. Figure 2 As shown, the method adopts the above system for analysis, and includes the following steps:

[0085] S1. The control unit receives real-time power from the vehicle power supply through the input interface and ensures that the output interface is connected to the charged device;

[0086] S2, the user or the automatic program interacts with the control unit through the communication module to set initial charging parameters, including current and voltage, and store them in the memory;

[0087] S3, turn on the current and voltage sensors to monitor the current size, its change rate, and voltage stability data during the charging process in real time;

[0088] S4, the microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to the preset weighted parameters;

[0089] S5. The control unit dynamically adjusts the charging parameters output to the charged device according to the weighted score;

[0090] S6. Storing the real-time monitoring data and the adjusted charging parameters in a memory as historical charging data for subsequent analysis and optimization;

[0091] S7. During the charging process, continuously monitor safety indicators and notify the user through the communication module when the threshold is reached, and interrupt charging to protect the device when necessary;

[0092] S8. After completing the charging cycle, the control unit provides a complete charging report through the communication module, including efficiency evaluation, problem records and optimization suggestions.

[0093] Further, such as Figure 3 As shown, the microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to the preset weighted parameters, specifically:

[0094] S41. Set a weight for each influencing factor;

[0095] Among them, the weight of the charging current (I) is: ωI;

[0096] Weight of the rate of change of charging current (ΔI): ωΔI;

[0097] Weight of charging voltage stability (V): ωV;

[0098] The weight of the charging state (S) of the charged device: ωS;

[0099] Weight of ambient temperature (T): ωT;

[0100] S42, standardize all measurement parameters to the same range for comparison; Step S42 standardizes all measurement parameters to the same range for comparison, and the standardization calculation formula is:

[0101]

[0102] In the formula, X 实际值 is the actual measured value of a factor, I 最大值 is the theoretical maximum value of the measured parameter of this factor, I 最小值It is the theoretical minimum value of the measured parameter of this factor.

[0103] S43. For each factor, multiply its standardized value by the corresponding weight to obtain a weighted input value, and the calculation formula is:

[0104] X 加权输入 =ωX×X 标准化参数 ;

[0105] In the formula, X 加权输入 is the ideal value of a factor after weighted calculation, ωX is the weight value of the factor, X 标准化参数 is the standardized value of the factor;

[0106] S44. All weighted input values ​​are added together to obtain a total weighted score; the calculation formula is:

[0107] Text 加权得分 =∑ i X 加权输入 ;

[0108] S45, adjusting charging parameters based on the total weighted score and referring to a preset mapping table;

[0109] The mapping table preset in step S45 is established by the following steps:

[0110] Collect charging efficiency and safety data under different charging parameters, covering all key influencing factors, including current size, current change rate, voltage stability, charging status of the charged device and ambient temperature;

[0111] Set weights for each factor based on its impact on charging efficiency and safety;

[0112] Using known data and weights, a model is established through mathematical modeling to map weighted scores to charging parameter adjustment strategies;

[0113] The initial preset of the mapping table is as follows:

[0114] 0.8<Text 加权得分 ≤1.0, output decreases by 10%;

[0115] 0.6<Text 加权得分 ≤0.8, the output remains unchanged;

[0116] 0.4<Text 加权得分 ≤0.6, output increased by 10%;

[0117] 0.2<Text 加权得分 ≤0.4, output increased by 20%;

[0118] 0.0<Text 加权得分 ≤0.2, output increased by 30%;

[0119] The mapping table is updated as time goes by and data accumulates, and the update is iteratively updated by mapping the weighted scores to a model of the charging parameter adjustment strategy.

[0120] Exemplarily, a weight is set for each influencing factor;

[0121] Among them, the weight of the charging current (I) is 0.3;

[0122] Weight of the rate of change of charging current (ΔI): 0.2;

[0123] Weight of charging voltage stability (V): 0.3;

[0124] Weight of the charging state (S) of the charged device: 0.1;

[0125] Weight of ambient temperature (T): 0.1;

[0126] Standardize all measured parameters to the same range to facilitate comparison;

[0127] The original values ​​of the measured parameters are: Charging current (I): 10A;

[0128] Charging current change rate (ΔI): 0.5A / s;

[0129] Charging voltage stability (V): 5V;

[0130] Charging state of the charged device (S): 80%;

[0131] Ambient temperature (T): 25℃.

[0132] First, these parameters are normalized to the same range of 0-1, and the calculation formula is:

[0133]

[0134] For each factor, multiply its standardized value by the corresponding weight to get the weighted input value, calculated as: 加权输入 =ωX×X 标准化参数 ;

[0135] Based on the above normalized values ​​and weights, the following weighted input values ​​are obtained:

[0136] Weighted input of the charging current (I): (10-0) / (20-0)×0.3=0.3;

[0137] Weighted input of the rate of change of charging current (ΔI): (0.5-0) / (1-0)×0.2=0.1;

[0138] Weighted input of charging voltage stability (V): (5-0) / (10-0)×0.3=0.15;

[0139] Weighted input of the charging state (S) of the charged device: (80-0) / (100-0)×0.1=0.08;

[0140] Weighted input of ambient temperature (T): (25-0) / (50-0)×0.1=0.1.

[0141] All weighted input values ​​are added together to get the total weighted score; the calculation formula is:

[0142] Text 加权得分 =∑ i X 加权输入 =0.3+0.1+0.15+0.08+0.1=0.76, which is the weighted score.

[0143] In addition, it should be noted that establishing a model that maps weighted scores to charging parameter adjustment strategies through mathematical modeling specifically includes:

[0144] Collect historical charging data and pre-process the data;

[0145] Calculate the weighted score; use the determined weight ωX and the normalized measurement parameter X 标准化参数 , calculate the weighted score W according to the following formula:

[0146]

[0147] In the formula, ωX is the weight determined by a certain factor, X 标准化参数 is the standardized measurement parameter of the factor, where n is the number of influencing factors and cdot indicates that the calculation formula is a vector function;

[0148] A mapping model is established, and the collected historical data is used as a training set to train the model by minimizing the difference between the actual and predicted charging parameter adjustment values; a mapping model is established, which is expressed as:

[0149] Establish a mapping model, expressed as:

[0150] y=mW x +b

[0151] Where y is the predicted charging parameter adjustment, including current and voltage parameter adjustments, m is the slope, b is the intercept, and W x represents the weighted scores of current and voltage respectively;

[0152] The trained model is deployed to the charger’s control system, and the charging parameters are adjusted in real time during the actual charging process.

[0153] In summary, this method can assign different weights according to the importance or influence of the data by adopting weighted calculation, so that the calculation results are more in line with the actual situation. At the same time, through weighted calculation, it can more accurately reflect the role of different data in the whole, thereby obtaining more accurate results.

[0154] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle charger analysis method based on a weighted algorithm, characterized in that: The steps include: S1. The control unit receives real-time power from the vehicle power supply through the input interface and ensures that the output interface is connected to the charged device; S2, the user or the automatic program interacts with the control unit through the communication module to set initial charging parameters, including current and voltage, and store them in the memory; S3, turn on the current and voltage sensors to monitor the current size, its change rate, and voltage stability data during the charging process in real time; S4. The microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to the preset weighted parameters; The microprocessor in the control unit calculates the weighted scores of the data obtained by the charging current and voltage sensors in real time according to the preset weighted parameters, specifically: S41. Set a weight for each influencing factor; S42, standardize all measurement parameters to the same range for comparison; Step S42 standardizes all measurement parameters to the same range for comparison, and the standardization calculation formula is: In the formula, X 实际值 is the actual measured value of a factor, I 最大值 is the theoretical maximum value of the measured parameter of this factor, I 最小值 is the theoretical minimum value of the measured parameter of this factor; S43. For each factor, multiply its standardized value by the corresponding weight to obtain a weighted input value, and the calculation formula is: X 加权输入 =ωX×X 标准化参数 ; In the formula, X 加权输入 is the ideal value of a factor after weighted calculation, ωX is the weight value of the factor, X 标准化参数 is the standardized value of the factor; S44. All weighted input values ​​are added together to obtain a total weighted score; the calculation formula is: Text 加权得分 =∑ i X 加权输入 ; S45, based on the total weighted score, adjusting the charging parameters with reference to a preset mapping table; the preset mapping table in step S45 is established by the following steps: Collect charging efficiency and safety data under different charging parameters, covering all key influencing factors, including current size, current change rate, voltage stability, charging status of the charged device and ambient temperature; Set weights for each factor based on its impact on charging efficiency and safety; Using known data and weights, a model is established through mathematical modeling to map weighted scores to charging parameter adjustment strategies; Verify the accuracy and effectiveness of mapping relationships or functions through actual analysis; The initial preset of the mapping table is specifically: 0.8<Text 加权得分 ≤1.0, output decreases by 10%; 0.6<Text 加权得分 ≤0.8, the output remains unchanged; 0.4<Text 加权得分 ≤0.6, output increased by 10%; 0.2<Text 加权得分 ≤0.4, output increased by 20%; 0.0<Text 加权得分 ≤0.2, output increased by 30%; The mapping table is updated as time goes by and data accumulates, and the update is iteratively updated by mapping the weighted scores to the model of the charging parameter adjustment strategy; The method of establishing a model that maps weighted scores to charging parameter adjustment strategies through mathematical modeling specifically includes: Collect historical charging data and pre-process the data; Calculate the weighted score; use the determined weight ωX and the normalized measurement parameter X 标准化参数 , calculate the weighted score W according to the following formula: In the formula, ωX is the weight determined by a certain factor, X 标准化参数 is the standardized measurement parameter of the factor, where n is the number of influencing factors and cdot indicates that the calculation formula is a vector function; Establish a mapping model and use the collected historical data as a training set to train the model by minimizing the difference between actual and predicted charging parameter adjustment values; Deploy the trained model to the charger's control system and adjust the charging parameters in real time during the actual charging process; Continuously retrain and optimize the model based on new charging data to adapt to changes in charging behavior; The mapping model is established as follows: y=mW x +b Where y is the predicted charging parameter adjustment, including current and voltage parameter adjustments, m is the slope, b is the intercept, and W x represents the weighted scores of current and voltage respectively; S5. The control unit dynamically adjusts the charging parameters output to the charged device according to the weighted score; S6. Storing the real-time monitoring data and the adjusted charging parameters in a memory as historical charging data for subsequent analysis and optimization; S7. During the charging process, continuously monitor safety indicators and notify the user through the communication module when the threshold is reached, and interrupt charging to protect the device when necessary; S8. After completing the charging cycle, the control unit provides a complete charging report through the communication module, including efficiency evaluation, problem records and optimization suggestions.

2. A vehicle charger analysis method based on a weighted algorithm according to claim 1, characterized in that: The method is implemented based on the following system, which includes: An input interface for receiving real-time power from a vehicle power source; Output interface, connected to the charged device; a control unit including a microprocessor having processing power and running a weighted algorithm to evaluate and adjust charging parameters; A memory, used to store preset weighted parameters and historical charging data; Current and voltage sensors monitor the current and voltage changes during charging in real time; A communication module for realizing the interaction between the current and voltage sensors, the control unit and the vehicle; The control unit processes the data obtained by the charging current and voltage sensors according to a weighted algorithm, and adjusts the charging parameters accordingly to optimize the charging efficiency and safety.

3. The vehicle charger analysis method based on weighted algorithm according to claim 2 is characterized in that: In the weighted algorithm, the factors considered include: The magnitude of the charging current and its rate of change; Stability of charging voltage; Charging status and historical data of the charged device; Ambient temperature.

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