Method, device and computer program product for determining vehicle electrical load power supply requirements

Abstract

This invention provides a method, device, and computer program product for determining the power supply requirements of vehicle electrical loads, relating to the power supply field of vehicle auxiliary equipment. The method includes: determining a first weight to be used based on electrical load data from multiple scenarios in a first set; determining a second weight to be used based on vehicle driving test results data from multiple scenarios in a second set of electrical loads; determining a third weight to be used based on development process allocation results data from multiple scenarios in a third set of electrical loads; determining a combination of weights to be used based on the set to which the electrical loads belong; calculating a comprehensive load scenario weight value based on the combination of weights and weight allocation percentages; weighting and summing the rated power using the comprehensive load scenario weight value to obtain the power demand value for each scenario; and determining the total power demand value based on the power demand values ​​for multiple scenarios. This invention improves the accuracy of power demand determination.

Description

Technical Field

[0001] This invention relates to the field of power supply technology for vehicle auxiliary equipment, specifically to a method, device, and computer program product for determining the power supply requirements of vehicle electrical loads. Background Technology

[0002] Currently, low-voltage power consumption is a key factor affecting the driving range of pure electric vehicles. More accurate calculation of low-voltage power consumption allows for the selection of more practical and cost-effective key components of the low-voltage system, such as DC / DC converters and 12V batteries. Therefore, obtaining more accurate preliminary data to calculate, for example, the power requirements of the DC / DC converter becomes crucial.

[0003] In existing technologies, low-voltage power requirements are usually determined based on experience, which can lead to inaccurate power demand. In some scenarios, the load may not receive enough power and may not be able to start. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, in a first aspect, embodiments of the present invention provide a method for determining the power supply requirements of vehicle electrical loads. The method includes: determining multiple first usage weights for the multiple scenarios based on usage time and frequency data of electrical loads in a first electrical load set within electrical load embedding data in multiple scenarios; determining multiple second usage weights for the multiple scenarios based on electrical load usage time and test time data of electrical loads in a second electrical load set within vehicle driving test results data in the multiple scenarios; and determining multiple third usage weights for the multiple scenarios based on development process allocation result data of electrical loads in a third electrical load set within the multiple scenarios. Based on one or more sets of electrical loads, determine a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight; for each of the multiple scenarios, calculate the comprehensive load scenario weight value of the electrical loads based on the combination of used weights of the electrical loads and a predefined weight allocation percentage for each combination of used weights; for each of the multiple scenarios, use the comprehensive load scenario weight value of the electrical loads to weight and sum the rated power of the electrical loads in that scenario to obtain the power demand value of the total electrical load of the vehicle in that scenario; based on the multiple power demand values ​​for the multiple scenarios, determine the total power demand value.

[0005] In some implementations, the classification of the multiple scenarios includes one or more of road condition scenario classification, time scenario classification, and vehicle type scenario classification. Specifically, the road condition scenario classification includes one or more of urban commuting road conditions, highway road conditions, and off-road driving conditions; the time scenario classification includes one or more of ordinary daytime, summer rainy night, and winter snowy night.

[0006] In some implementations, the development process allocation result data includes usage frequency data of visible electrical loads input by the driver and / or usage frequency data of invisible electrical loads input by the load component engineer.

[0007] In some implementations, determining the total power demand value based on the power demand values ​​for multiple power scenarios for the multiple scenarios includes taking the maximum value among the power demand values ​​for multiple power scenarios as the total power demand value.

[0008] In some implementations, determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets of electrical loads, includes: for electrical loads located at the intersection of the first set of electrical loads, the second set of electrical loads, and the third set of electrical loads, the combination of used weights includes the first used weight, the second used weight, and the third used weight. Furthermore, in the weight allocation percentage for this combination of used weights, the weight allocation percentage of the first used weight is greater than the weight allocation percentage of the second used weight, and the weight allocation percentage of the second used weight is greater than the weight allocation percentage of the third used weight.

[0009] In some implementations, determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets of electrical loads, includes: for electrical loads that are in the intersection of the second and third electrical load sets but not in the first electrical load set, the combination of used weights includes both the second and third used weights. Furthermore, in the weight allocation percentage for this combination of used weights, the weight allocation percentage of the second used weight is greater than the weight allocation percentage of the third used weight.

[0010] In some implementations, determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets of electrical loads, includes: for electrical loads that are in the intersection of a first set of electrical loads and a third set of electrical loads but are not in a second set of electrical loads, the combination of used weights includes both the first used weight and the third used weight. Furthermore, in the weight allocation percentage for this combination of used weights, the weight allocation percentage of the first used weight is greater than the weight allocation percentage of the third used weight.

[0011] In some implementations, determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets of electrical loads, includes: for electrical loads that are in a third set of electrical loads but not in the first or second sets of electrical loads, the combination of used weights includes the third used weight. Furthermore, in the weight allocation percentage for this combination of used weights, the weight allocation percentage for the third used weight is 100%.

[0012] In a second aspect, embodiments of the present invention provide a vehicle electrical load power demand determination device, the device including a memory and a processor, the memory storing a computer program that, when executed by the processor, implements the vehicle electrical load power demand determination method described in any of the above embodiments.

[0013] In a third aspect, embodiments of the present invention provide a computer program product including computer-readable instructions that, when executed by a processor, perform the steps of the vehicle electrical load power demand determination method described in any of the above embodiments.

[0014] The embodiments of this invention propose a method for determining the power demand of vehicle electrical loads, realizing a power demand calculation method based on driving conditions, including workload weight allocation and driving condition calculation. Workload weight allocation is obtained by comprehensively considering three aspects: vehicle electrical load data embedding, vehicle driving tests, and allocation during the development process. Driving condition calculation employs a weighted power calculation method, combining workload weights and rated power to calculate power demand.

[0015] The availability and accessibility of data for different electrical loads in a vehicle vary. For loads that are easily accessible, such as those that can be directly measured or have their data directly obtained from the cloud, the proportion of real data is amplified. For loads that are not easily accessible, the current data is analyzed comprehensively. Assigning values ​​and calculating from multiple perspectives ensures the accuracy and reliability of the data and improves the accuracy of power demand determination. Attached Figure Description

[0016] The above and other objects, features, and advantages of embodiments of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the invention are illustrated in the drawings by way of example and not limitation, wherein:

[0017] Figure 1 A flowchart of a method for determining the power supply requirements of a vehicle electrical load according to an embodiment of the present invention is shown.

[0018] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0019] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way.

[0020] In one aspect, embodiments of the present invention provide a method for determining the power demand of a vehicle's electrical load. This method is a power demand calculation method based on driving conditions, mainly including workload weight allocation and driving condition calculation. (Reference) Figure 1 This illustrates a flowchart of a method for determining the power supply requirements of a vehicle's electrical load according to an embodiment of the present invention. Figure 1 As shown, the method includes steps S101-S107. Among them, the work weight allocation is realized through steps S101-S105, and the driving condition calculation is realized through steps S106-S107.

[0021] The work weight allocation in this invention refers to the calculation of work weight values ​​for all low-voltage electrical loads of the vehicle. For example, the weight value is between 0 and 1.

[0022] The allocation of workload weights depends on the scenario; for example, the weight allocation differs depending on different road conditions and driving environments. As one embodiment of the invention, scenario classification includes one or more of road condition scenario classification, time scenario classification, and vehicle model scenario classification. Specifically, road condition scenario classification includes one or more of urban commuting road conditions, highway road conditions, and off-road recreational road conditions. Time scenario classification includes one or more of ordinary daytime, summer rainy night, and winter snowy night. In vehicle model scenario classification, a single vehicle model can be considered as a scenario, or a class of vehicle models or a predefined group of vehicle models can be considered as a scenario.

[0023] In practical applications, one or more scene categories can be selected as needed. When multiple scene categories are selected, the scenes within each category are combined to form the final scene. For example, if only the road condition scene category is selected, the total number of scenes could include: city commuting road conditions, highway road conditions, and off-road recreational road conditions. If both a road condition scene category and a time scene category are selected, and the road condition scene category includes three types: city commuting road conditions, highway road conditions, and off-road recreational road conditions, and the time scene category includes three types: normal daytime, summer rainy night, and winter snowy night, then based on the combination of specific scenes from the two scene categories, the total number of scenes would be 3*3, namely: normal daytime city commuting road conditions, normal daytime highway road conditions, normal daytime off-road recreational road conditions, summer rainy night city commuting road conditions, summer rainy night highway road conditions, summer rainy night off-road recreational road conditions, winter snowy night city commuting road conditions, winter snowy night highway road conditions, and winter snowy night off-road recreational road conditions. The same logic applies if only three scene categories are selected, and will not be listed here.

[0024] In step S101, based on the usage time and frequency data of the electrical loads in the first electrical load set in the electrical load embedding data of multiple scenarios, multiple first usage weights W1 for multiple scenarios are determined.

[0025] The data obtained from tracking the electrical loads of a vehicle is acquired by tracking specific electrical loads within the vehicle. For example, the usage time and frequency of electrical loads can be periodically uploaded to the cloud. Subsequently, the cloud is used to retrieve the vehicle's electrical load usage time and frequency data, thereby determining the first usage weight value W1 for the tracked loads. As an example, the total usage time of the electrical loads can be divided by the overall vehicle usage time to calculate the first usage weight value. Typically, not all vehicle electrical loads are tracked and data is retrieved from the cloud; the focus is more on specific controllers and high-power devices, such as in-vehicle 4G / 5G modules, in-vehicle infotainment screens, and door / window motors.

[0026] The electrical load tracking data varies depending on the scenario. For example, in a typical daytime scenario, the electrical load tracking data is obtained from controller data collected during the vehicle's daily driving. Based on this data, the first used weight value W1 for the typical daytime scenario can be calculated. Similarly, in an urban commuting scenario, the electrical load tracking data is obtained from controller data collected during the vehicle's urban commuting. Based on this data, the first used weight value W1 for the urban commuting scenario can be calculated.

[0027] In step S102, based on the electrical load usage time and test time in the vehicle driving test result data of the electrical loads in the second electrical load set in multiple scenarios, multiple second usage weights W2 are determined for multiple scenarios.

[0028] The vehicle driving test result refers to the test conducted by the experimenter driving the vehicle under a set scenario, measuring the usage time of the vehicle's electrical loads. The ratio of the usage time Tuse to the test time T (i.e., the time the experimenter drives the vehicle) is the second used weight W2. Typically, due to reasons such as the installation and assembly of the vehicle's electrical loads, only a portion of the loads can be directly tested.

[0029] Vehicle driving test results in different scenarios are obtained through actual testing in those scenarios. Therefore, the weight of the second usage will differ in different scenarios. For example, the vehicle driving test results in a normal daytime scenario are obtained during driving tests conducted on the vehicle during normal daytime driving. Based on this data, the weight value W1 of the second usage in a normal daytime scenario can be calculated.

[0030] In step S103, multiple third-level weights W3 are determined for multiple scenarios based on the development process allocation result data of electrical loads in the third electrical load set in multiple scenarios.

[0031] As one embodiment of the present invention, the development process allocation result data includes usage frequency data of visible electrical loads input by the driver and / or usage frequency data of invisible electrical loads input by the load component engineer.

[0032] The development process allocation result refers to the weighting of all vehicle loads by summarizing driving experience, obtaining a third-party weight value of W3. Since this scheme is unaffected by installation or data entry points, all vehicle loads can be weighted. For example, setting a commuting route with a driving time of 30 minutes, several drivers or operators input the usage frequency of visible electrical loads (e.g., headlights, air conditioning, seat heating, etc.) based on their usage habits; load component engineers can input the driving usage frequency based on data and experience. Invisible electrical loads, such as battery and motor cooling, depend on ambient temperature and driving conditions and do not require active driver control. Optionally, if there are duplicate component entries, the average value is taken to obtain the weighting result of the development process allocation.

[0033] The allocation results of the development process in different scenarios depend on the scenario. For example, the usage frequency data of visible electrical loads is input by the driver considering different scenarios. For example, in the summer rainy night scenario, the usage time of vehicle lights will be significantly higher than that in the normal daytime scenario. Therefore, the usage weight of vehicle lights in the summer rainy night scenario will be higher than that of vehicle lights in the normal daytime scenario.

[0034] As can be seen, in the embodiments of the present invention, there are three methods for determining the weights to be used in the work weight allocation, which are based on the vehicle electrical load data embedding data, the vehicle driving test result data, and the development process allocation result data, respectively. These data will be different in different scenarios. Therefore, the first, second, and third weights to be used determined based on these data will also change in different scenarios.

[0035] In step S104, a combination of used weights, including one or more of the first used weight, the second used weight, and the third used weight, is determined based on one or more sets where the electrical loads are located.

[0036] Combining the above three methods of obtaining the weights used, the partial electrical load Load1 has three weights: vehicle electrical load data embedding results, vehicle driving test results, and development process allocation results. That is, the electrical load is located at the intersection of the first, second, and third electrical load sets, so the combined weights used include the first used weight, the second used weight, and the third used weight. The partial electrical load Load2 has two weights: vehicle driving test results and development process allocation results. That is, the electrical load is located at the intersection of the second and third electrical load sets and is not in the first electrical load set. In the case of partial electrical load Load3, the weight combination used includes the second weight and the third weight used; partial electrical load Load3 has two weights: the data embedding result of the whole vehicle electrical load and the allocation result of the development process. That is, the electrical load is in the intersection of the first electrical load set and the third electrical load set and is not in the second electrical load set. Therefore, the weight combination used includes the first weight and the third weight used; partial electrical load Load4 only has the allocation result of the development process. That is, the electrical load is in the third electrical load set and is not in the first electrical load set or the second electrical load set. Therefore, the weight combination used only includes the third weight used.

[0037] In step S105, for each of the multiple scenarios, the comprehensive load scenario weight value of the electrical load is calculated based on the combination of used weights of the electrical load and the predefined weight allocation percentage for each combination of used weights.

[0038] As an embodiment of the present invention, when the weighted combination includes a first weighted weight, a second weighted weight, and a third weighted weight, that is, for the electrical load Load1, in the weight allocation percentage for the weighted combination, the weight allocation percentage of the first weighted weight is greater than the weight allocation percentage of the second weighted weight, and the weight allocation percentage of the second weighted weight is greater than the weight allocation percentage of the third weighted weight.

[0039] As an embodiment of the present invention, when the weighted combination includes a second weighted weight and a third weighted weight, that is, for electrical load Load2, in the weight allocation percentage for the weighted combination, the weight allocation percentage of the second weighted weight is greater than the weight allocation percentage of the third weighted weight.

[0040] As an embodiment of the present invention, when the weighted combination includes a first weighted weight and a third weighted weight, that is, for electrical load Load3, in the weight allocation percentage for the weighted combination, the weight allocation percentage of the first weighted weight is greater than the weight allocation percentage of the third weighted weight.

[0041] As an embodiment of the present invention, when the weighted combination includes a third weighted weight, that is, for electrical load Load4, the weighted percentage of the third weighted weight is 100% in the weighted percentage of the weighted combination.

[0042] For example only, the load in Load1 scenario has a total load weight value of W. load1,controller =60%W1 + 30%W2 + 10%W3; This belongs to Load2, and the overall load weight value is: W load2,controller =70%W2 + 30%W3; This belongs to Load3, and the overall load weight value is: W load3,controller =80%W1 + 20%W3; This belongs to Load4, and the overall load weight value is: W load4,controller =100%W3.

[0043] Among them, W load1,controller W load2,controller W load3,controller W load4,controller These are the combined load scenario weight values ​​for electrical loads Load1, Load2, Load3, and Load4. W1, W2, and W3 are the first, second, and third used weights of the electrical loads, respectively.

[0044] The availability and accessibility of data for different electrical loads in a vehicle vary. Data from embedded electrical load data points is real and highly accurate, thus its importance is ranked highest. Vehicle driving test results data are real data obtained from a limited number of tests, and are of secondary importance. Development process allocation results data are input by drivers or engineers based on experience and certain specific data. While this compensates for the lack of data for electrical loads where the first two types of data are unavailable, manual judgment has limitations, therefore its importance is the lowest. In the above embodiments and examples of this invention, generally speaking, the percentage of W1 is higher than that of W2, and the percentage of W2 is higher than that of W3. This amplifies the proportion of real data for electrical loads where real data can be obtained, ensuring the accuracy and reliability of the data.

[0045] In step S106, for each of the multiple scenarios, the rated power of the electrical load in that scenario is weighted and summed using the comprehensive load scenario weight value of the electrical load to obtain the power demand value of the overall electrical load of the vehicle in that scenario.

[0046] As an example, considering typical daytime scenarios, the power requirement can be calculated using the following formula:

[0047] Pb=P b,controller,1 * W load1,controller,1 + P b,controller,2 * W load1,controller,2 +……+P b,controller,k * W load1,controller,k + P b,controller,k+1 * W load2,controller,k+1 + P b,controller,k+2 *W load1,controller,k+2 +……+ P b,controller k+n * W load1,controller k+n + P b,controller,k+n+1 *W load3,controller,k+n+1 + P b,controller,k+n+2 * W load3,controller k+n+2 +……+ P b,controller k+n+l *W load3,controller ,k+n+l + P b,controller,k+n+1+1 * W load4,controller,k+n+1+1 + P b,controller,k+n+l+2 *W load4,controller k+n+l+2 +……+ P b,controller k+n+l+s * W load4,controller ,k+n+l+s

[0048] Where Pb is the power requirement value for a typical daytime power supply scenario, P b,controller,1This represents the rated power of controller1 under normal daytime conditions; k is the number of Load1 type loads that can be used for vehicle electrical load data collection, vehicle driving tests, and development process allocation; n is the number of Load2 type loads that can be used for vehicle driving tests and development process allocation; l is the number of Load3 type loads that can be used for vehicle electrical load data collection and development process allocation; and s is the number of Load4 type loads that can only be used for development process allocation. W load1,controller,i W load2,controller,i W load3,controller,i W load3,controller,i These are the combined load scenario weight values ​​for four different types of electrical loads: Load1, Load2, Load3, and Load4.

[0049] The calculation method for other scenarios is the same as the example above, using a weighted summation based on the rated power and the overall load scenario weight value for different scenarios. For example, the load weighted power (power demand value for the power supply scenario) for a summer rainy night is calculated as Ps, and the load weighted power (power demand value for the power supply scenario) for a winter snowy night is calculated as Pw.

[0050] In step S107, the total power demand value is determined based on the power demand values ​​for multiple power scenarios across multiple scenarios. As one embodiment of the invention, the maximum value among the power demand values ​​for multiple power scenarios is taken as the total power demand value. Referring to the above example, the total power demand value can be determined as Pmax = max(Pb, Ps, Pw), where Pmax is the total power demand value, and Pb, Ps, and Pw are the power demand values ​​for normal daytime, summer rainy night, and winter snowy night scenarios, respectively.

[0051] As another embodiment of the present invention, the average value of the power demand values ​​of multiple power scenarios for multiple scenarios can be taken as the total power demand value.

[0052] As another embodiment of the present invention, the total power demand value can be obtained by weighting the power demand values ​​of multiple power scenarios for multiple scenarios according to actual application requirements, such as the scenario in which the vehicle is more likely to actually drive or the current season.

[0053] The embodiments of this invention propose a method for determining the power demand of vehicle electrical loads, realizing a power demand calculation method based on driving conditions, including workload weight allocation and driving condition calculation. Workload weight allocation is obtained by comprehensively considering three aspects: vehicle electrical load data embedding, vehicle driving tests, and allocation during the development process. The calculation allocation methods for different vehicle loads are divided into four categories (Load1, 2, 3, and 4). Driving condition calculation uses a weighted power calculation method, combining workload weights and rated power to calculate power demand.

[0054] The availability and accessibility of data for different electrical loads in a vehicle vary. For loads that are easily accessible, such as those that can be directly measured or have their data directly obtained from the cloud, the proportion of real data is amplified. For loads that are not easily accessible, the current data is analyzed comprehensively. Assigning values ​​and calculating from multiple perspectives ensures the accuracy and reliability of the data and improves the accuracy of power demand determination.

[0055] On the other hand, embodiments of the present invention provide a vehicle electrical load power demand determination device, the device including a memory and a processor, the memory storing a computer program, which, when executed by the processor, implements the vehicle electrical load power demand determination method described in any of the foregoing embodiments.

[0056] In another aspect, embodiments of the present invention provide a computer program product including computer-readable instructions that, when executed by a processor, perform the steps of the vehicle electrical load power demand determination method described in any of the foregoing embodiments.

[0057] The foregoing description of embodiments of the invention has been given for illustrative purposes and is not exhaustive, nor is it intended to limit the invention to the exact forms disclosed. Those skilled in the art will understand that various changes can be made without departing from the scope of the invention, and elements therein can be substituted with equivalents. Furthermore, many modifications can be made to adapt particular situations or materials to the teachings of the invention without departing from the basic scope of the invention. Therefore, the invention is not intended to be limited to the specific embodiments disclosed as the best mode contemplated for carrying out the invention; the invention will include all embodiments falling within the scope of the appended claims.

Claims

1. A method for determining the power supply requirements of a vehicle's electrical load, characterized in that, The method includes: Based on the usage time and frequency data of electrical loads in the first electrical load set in the electrical load embedding data of multiple scenarios, determine multiple first usage weights for the multiple scenarios; Based on the electrical load usage time and test time of the electrical loads in the second electrical load set in the vehicle driving test result data of the multiple scenarios, determine multiple second usage weights for the multiple scenarios; Based on the development process allocation results data of the electrical loads in the third electrical load set in the multiple scenarios, multiple third used weights are determined for the multiple scenarios; Based on one or more sets of electrical loads, determine a combination of used weights including one or more of a first used weight, a second used weight, and a third used weight; For each of the multiple scenarios, the comprehensive load scenario weight value of the electrical load is calculated based on the combination of used weights of the electrical load and the predefined weight allocation percentage for each combination of used weights. For each of the multiple scenarios, the rated power of the electrical load in that scenario is weighted and summed using the comprehensive load scenario weight value of the electrical load to obtain the power demand value of the overall electrical load of the vehicle in that scenario. The total power demand value is determined based on the power demand values ​​for multiple power scenarios in the aforementioned scenarios.

2. The method for determining the power supply requirements of vehicle electrical loads according to claim 1, characterized in that, The classification of these multiple scenarios includes one or more of the following: road condition scenario classification, time scenario classification, and vehicle model scenario classification. The road condition scenario classification includes one or more of the following: urban commuting road conditions, highway road conditions, and off-road recreational road conditions. The time scene classification includes one or more of the following: ordinary daytime, summer rainy night, and winter snowy night.

3. The method for determining the power supply requirements of vehicle electrical loads according to claim 1, characterized in that, The development process allocation results data include usage frequency data of visible electrical loads input by the driver and / or usage frequency data of invisible electrical loads input by the load component engineer.

4. The method for determining the power supply requirements of vehicle electrical loads according to claim 1, characterized in that, Based on the power demand values ​​for multiple power scenarios in the aforementioned scenarios, the total power demand value is determined, including: The maximum value among the power demand values ​​for multiple power scenarios is taken as the total power demand value.

5. The method for determining the power supply requirements of vehicle electrical loads according to any one of claims 1-4, characterized in that, Determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets to which the electrical loads belong, includes: For electrical loads in the intersection of the first set of electrical loads, the second set of electrical loads, and the third set of electrical loads, the used weight combination includes a first used weight, a second used weight, and a third used weight, and, In the weight allocation percentages for the weight combination used, the weight allocation percentage of the first used weight is greater than that of the second used weight, and the weight allocation percentage of the second used weight is greater than that of the third used weight.

6. The method for determining the power supply requirements of vehicle electrical loads according to any one of claims 1-4, characterized in that, Determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets to which the electrical loads belong, includes: For electrical loads that are in the intersection of the second and third electrical load sets but not in the first electrical load set, the weighted combination used includes the second used weight and the third used weight, and, In the weight allocation percentage for the weight combination used, the weight allocation percentage of the second used weight is greater than the weight allocation percentage of the third used weight.

7. The method for determining the power supply requirements of vehicle electrical loads according to any one of claims 1-4, characterized in that, Determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets to which the electrical loads belong, includes: For electrical loads that are in the intersection of the first and third electrical load sets but not in the second electrical load set, the weighted combination used includes the first used weight and the third used weight, and, In the weight allocation percentage for the weight combination used, the weight allocation percentage of the first used weight is greater than the weight allocation percentage of the third used weight.

8. The method for determining the power supply requirements of vehicle electrical loads according to any one of claims 1-4, characterized in that, Determining a combination of used weights, including one or more of a first used weight, a second used weight, and a third used weight, based on one or more sets to which the electrical loads belong, includes: For electrical loads that are in the third set of electrical loads but not in the first or second set of electrical loads, the weighted combination used includes the third weighted combination, and... In the weight allocation percentage for this weight combination, the weight allocation percentage for the third weight is 100%.

9. A device for determining the power supply requirements of a vehicle's electrical load, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method for determining the power supply requirements of the vehicle electrical load as described in any one of claims 1-8.

10. A computer program product comprising computer-readable instructions, characterized in that, When the instruction is executed by the processor, it performs the steps of the method for determining the power supply requirements of the vehicle electrical load according to any one of claims 1-8.

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