Energy consumption calculation method and device of electric vehicle and computer storage medium

Abstract

The invention relates to the technical field of new energy, and discloses an energy consumption calculation method and device of an electric automobile and a computer storage medium, the method comprises the steps that sampling intervals of state parameters of the electric automobile are determined, and the state parameters are different under different sampling intervals; matching a corresponding energy consumption calculation algorithm according to the state parameters and the sampling intervals; and calculating a target energy consumption parameter of the electric vehicle according to an energy consumption calculation algorithm and the state parameters under the sampling interval. Therefore, by implementing the method, the corresponding energy consumption calculation algorithm can be matched based on the determined state parameters under the different sampling intervals of the electric vehicle, and then the target energy consumption parameter of the electric vehicle is calculated based on the energy consumption calculation algorithm and the state parameters under the sampling intervals; therefore, on the basis of reducing the dependence on the specific driving data of the main engine plant, the energy consumption calculation accuracy and flexibility of the electric vehicle are improved, and the energy consumption calculation efficiency of the electric vehicle is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy, and particularly to an energy consumption calculation method, device and computer storage medium for an electric vehicle. Background Art

[0002] With the rapid development of the electric vehicle industry, accurate energy consumption estimation and driving range prediction technologies have become the key to improving user experience and optimizing the performance of battery systems.

[0003] Currently, the energy consumption calculation methods for electric vehicles proposed by the existing technologies generally rely too much on the specific driving data of the vehicle manufacturers. For suppliers who are not vehicle manufacturers, they usually can only obtain battery state data based on the GB / T 32960.3 communication protocol. The channels for obtaining battery state data are relatively single and the types of data obtained are relatively monotonous. Therefore, it is particularly important to improve the accuracy and flexibility of the energy consumption calculation of electric vehicles on the basis of reducing the dependence on the specific driving data of vehicle manufacturers. Summary of the Invention

[0004] The present invention provides an energy consumption calculation method, device and computer storage medium for an electric vehicle, which can improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle manufacturer.

[0005] To solve the above technical problems, in a first aspect of the present invention, an energy consumption calculation method for an electric vehicle is disclosed, and the method includes:

[0006] Determine the sampling interval of the state parameters of the electric vehicle, and the state parameters are different under different sampling intervals;

[0007] Match a corresponding energy consumption calculation algorithm according to the state parameters and the sampling interval;

[0008] Calculate the target energy consumption parameter of the electric vehicle according to the energy consumption calculation algorithm and the state parameters under the sampling interval.

[0009] As an optional implementation manner, in the first aspect of the present invention, the matching a corresponding energy consumption calculation algorithm according to the state parameters and the sampling interval includes:

[0010] Judge whether the sampling interval exceeds a preset sampling interval threshold range;

[0011] When it is judged that the sampling interval exceeds the preset sampling interval threshold range, identify the constant current charging segment in the sampling interval according to the state parameters under the sampling interval;

[0012] Calculate the charging power target value of the constant current charging segment and the frequency distribution parameter of the charging power target value, where the charging power target value is used to indicate the concentrated distribution of the charging power of the constant current charging segment, and the frequency distribution parameter is used to represent the occurrence frequency of the charging power target value in the constant current charging segment;

[0013] Match a corresponding energy consumption calculation algorithm according to the charging power target value, the frequency distribution parameter, and the state parameter of the constant current charging segment;

[0014] When it is determined that the sampling interval does not exceed the preset sampling interval threshold range, match a corresponding energy consumption calculation algorithm according to the state parameter at the sampling interval.

[0015] As an optional implementation manner, in the first aspect of the present invention, the identifying the constant current charging segment in the sampling interval according to the state parameter at the sampling interval includes:

[0016] Determine the charging state identifier in the state parameter;

[0017] Identify the charging segment in the sampling interval according to the charging state identifier;

[0018] Calculate the power characteristic distribution parameter of the charging segment according to the state parameter in the charging segment, where the power characteristic distribution parameter is used to represent the charging power distribution of the charging segment;

[0019] Identify the constant current charging segment in the charging segment according to the power characteristic distribution parameter and the preset constant current power range threshold, where the charging power of the constant current charging segment is within the preset constant current power range threshold.

[0020] As an optional implementation manner, in the first aspect of the present invention, when it is determined that the sampling interval does not exceed the preset sampling interval threshold range, the calculating the target energy consumption parameter of the electric vehicle according to the energy consumption calculation algorithm and the state parameter at the sampling interval includes:

[0021] Determine the battery type parameter corresponding to the electric vehicle and at least one driving segment at the sampling interval according to the state parameter;

[0022] Match the power consumption algorithm of the electric vehicle under each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle under each driving segment;

[0023] Calculate the total power consumption of the electric vehicle according to the power consumption of the electric vehicle under all driving segments;

[0024] Calculate the target energy consumption parameter of the electric vehicle according to the total power consumption, the effective driving mileage under all the driving segments, and a preset first weight value.

[0025] As an alternative implementation, in the first aspect of the present invention, the state parameters include the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value, the discharge start SOC, the discharge end SOC, and the first rated power of the electric vehicle under each driving segment; the driving segments are determined based on the state parameters;

[0026] The step of matching the power consumption algorithm of the electric vehicle under each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle under each driving segment includes:

[0027] Judge whether the battery type parameter matches a preset battery type parameter. When it is judged that the battery type parameter matches the preset battery type parameter, for each driving segment, calculate the power consumption of the electric vehicle under this driving segment according to the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value, and a preset second weight value under this driving segment;

[0028] When it is judged that the battery type parameter does not match the preset battery type parameter, for each driving segment, calculate the power consumption of the electric vehicle under this driving segment according to the discharge start SOC, the discharge end SOC, the first rated power, and the first battery health value under this driving segment.

[0029] As an alternative implementation, in the first aspect of the present invention, the state parameters include the charging start SOC, the second rated power, and the second battery health value of the electric vehicle under the constant current charging segment. When it is judged that the sampling interval exceeds the preset sampling interval threshold range, the step of calculating the target energy consumption parameter of the electric vehicle according to the energy consumption calculation algorithm and the state parameters under the sampling interval includes:

[0030] Match the charging process power algorithm of the electric vehicle according to the frequency distribution parameter to calculate the charging process power of the electric vehicle under the constant current charging segment;

[0031] Calculate the total charging end power of the electric vehicle under the constant current charging segment according to the charging process power, the charging start SOC, the second rated power, and the second battery health value;

[0032] Calculating a preset subsequent adjacent charging start power of the constant current charging segment according to the preset subsequent adjacent charging start SOC of the constant current charging segment, the second rated power, and the second battery health value;

[0033] Calculating the actual power consumption of the electric vehicle according to the total power consumption at the end of charging and the preset subsequent adjacent charging start power consumption;

[0034] The target energy consumption parameter of the electric vehicle is calculated according to the actual power consumption, the effective driving mileage of the electric vehicle and a preset third weight.

[0035] As an optional implementation, in the first aspect of the present invention, the state parameter also includes the charging time of the electric vehicle in the constant current charging segment, the second voltage parameter, the second current parameter, and the second inter-frame time difference, and the matching of the charging process power algorithm of the electric vehicle according to the frequency distribution parameter to calculate the charging process power of the electric vehicle in the constant current charging segment includes:

[0036] Determining whether the frequency distribution parameter is greater than or equal to a preset frequency distribution parameter threshold, and when it is determined that the frequency distribution parameter is greater than or equal to the preset frequency distribution parameter threshold, calculating the amount of electricity in the charging process of the electric vehicle according to the charging duration, the charging power target value and a preset fourth weight;

[0037] When it is determined that the frequency distribution parameter is less than the preset frequency distribution parameter threshold, the charging process power of the electric vehicle is calculated based on the second voltage parameter, the second current parameter, the second frame time difference, the second battery health value and the preset fifth weight under the constant current charging segment.

[0038] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0039] Determine a parameter dimension representation value of the state parameter, wherein the parameter dimension representation value is used to represent the dimensional richness of the state parameter and the vehicle state value under each dimension;

[0040] Generate a working condition matrix of the electric vehicle according to the parameter dimension representation value, wherein the working condition matrix is ​​used to represent the working condition status of the electric vehicle;

[0041] According to the target energy consumption parameter and the operating condition matrix, analyzing the linkage influence factor between the target energy consumption parameter and the operating condition matrix, the linkage influence factor is used to indicate the factor that the operating condition matrix causes the target energy consumption parameter to change;

[0042] Generate an energy consumption optimization plan for the electric vehicle and a charging and discharging strategy optimization plan for the electric vehicle according to the linkage influence factor.

[0043] The second aspect of the present invention discloses an energy consumption calculation device for an electric vehicle, and the device includes:

[0044] A memory storing executable program code;

[0045] A processor coupled to the memory;

[0046] The processor calls the executable program code stored in the memory and executes the energy consumption calculation method for the electric vehicle disclosed in the first aspect of the present invention.

[0047] The third aspect of the present invention discloses a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute the energy consumption calculation method for the electric vehicle disclosed in the first aspect of the present invention when called.

[0048] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0049] In the embodiments of the present invention, the sampling interval of the state parameters of the electric vehicle is determined, and the state parameters are different under different sampling intervals; according to the state parameters and the sampling interval, the corresponding energy consumption calculation algorithm is matched; according to the energy consumption calculation algorithm and the state parameters at the sampling interval, the target energy consumption parameters of the electric vehicle are calculated. It can be seen that implementing the present invention can match the corresponding energy consumption calculation algorithm based on the determined state parameters of the electric vehicle under different sampling intervals, and then calculate the target energy consumption parameters of the electric vehicle based on the energy consumption calculation algorithm and the state parameters at the sampling interval, so as to improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle factory, which is beneficial to improving the energy consumption calculation efficiency of the electric vehicle. Description of the Drawings

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0051] Figure 1 It is a schematic flowchart of an energy consumption calculation method for an electric vehicle disclosed in an embodiment of the present invention;

[0052] Figure 2 It is a schematic flowchart of another energy consumption calculation method for an electric vehicle disclosed in an embodiment of the present invention;

[0053] Figure 3 It is a schematic structural diagram of an energy consumption calculation device for an electric vehicle disclosed in an embodiment of the present invention. Detailed implementation manners

[0054] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0055] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or terminals.

[0056] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0057] The present invention discloses an energy consumption calculation method, device and computer storage medium for an electric vehicle, which can match corresponding energy consumption calculation algorithms based on the determined state parameters of the electric vehicle at different sampling intervals, and then calculate the target energy consumption parameters of the electric vehicle based on the energy consumption calculation algorithms and the state parameters at the sampling intervals, so as to improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle factory, which is beneficial to improving the energy consumption calculation efficiency of the electric vehicle. The following will be described in detail respectively.

[0058] Embodiment 1

[0059] Please refer to Figure 1 , Figure 1 It is a schematic flowchart of an energy consumption calculation method for an electric vehicle disclosed in an embodiment of the present invention. Among them, Figure 1The described energy consumption calculation method for electric vehicles can be applied to electric vehicles, battery management systems / devices, and intelligent devices related to the above-mentioned electric vehicles and battery management systems / devices. The intelligent devices include, but are not limited to, one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, urban management devices, and intelligent connected devices. The embodiments of the present invention do not make limitations. As Figure 1 shown, the energy consumption calculation method for the electric vehicle may include the following operations:

[0060] 101. Determine the sampling interval of the state parameters of the electric vehicle. The state parameters are different under different sampling intervals;

[0061] In the embodiments of the present invention, optionally, the above sampling interval may be 1 s, 10 s, etc. Further, regardless of the sampling interval, it can be sampling for the discharging or charging process of the electric vehicle, and then calculating its energy consumption situation;

[0062] It should be noted that generally, for a 1 s sampling interval, it is for sampling the discharging process of the electric vehicle, and for a 10 s sampling interval, it is for sampling the charging process of the electric vehicle. Specifically, it is subject to the actual application. The embodiments of the present invention do not make specific limitations on this;

[0063] Further optionally, during the above sampling process, it is also possible to further determine the working condition of the electric vehicle based on the sampled state parameters of the electric vehicle, so as to further analyze the influence of stable working conditions and dynamic working conditions on energy consumption, the influence of SOH on the rated power, etc., providing a basis for the study of energy consumption characteristics under different working conditions. For the specific process, see Embodiment 2 below;

[0064] Further optionally, the above state parameters include, but are not limited to, multi-dimensional parameters such as vehicle temperature, battery temperature, mechanical component temperature, vehicle SOC, vehicle speed, and vehicle load. That is, the embodiments of the present invention can fully consider the influence of multi-dimensional state factors of electric vehicles on energy consumption, not limited to batteries, etc., making the calculation result closer to the actual use scenario. On the basis of reducing the dependence on specific driving data of the vehicle factory, it improves the accuracy and flexibility of the energy consumption calculation of electric vehicles, which is beneficial to improving the energy consumption calculation efficiency of electric vehicles;

[0065] 102. Match the corresponding energy consumption calculation algorithm according to the state parameters and the sampling interval;

[0066] In the embodiments of the present invention, as an optional implementation manner, the above matching of the corresponding energy consumption calculation algorithm according to the state parameters and the sampling interval includes:

[0067] Judge whether the sampling interval exceeds the preset sampling interval threshold range;

[0068] When it is determined that the sampling interval exceeds the preset sampling interval threshold range, the constant current charging segments in the sampling interval are identified according to the state parameters at the sampling interval;

[0069] Calculate the charging power target value of the constant current charging segment and the frequency distribution parameter of the charging power target value. The charging power target value is used to indicate the concentrated distribution of the charging power in the constant current charging segment, and the frequency distribution parameter is used to represent the occurrence frequency of the charging power target value in the constant current charging segment;

[0070] Match the corresponding energy consumption calculation algorithm according to the charging power target value, the frequency distribution parameter, and the state parameters of the constant current charging segment;

[0071] When it is determined that the sampling interval does not exceed the preset sampling interval threshold range, the corresponding energy consumption calculation algorithm is matched according to the state parameters at the sampling interval.

[0072] In an embodiment of the present invention, optionally, the above charging power target value may be one of a mode value, an average value, a variance value, etc.;

[0073] It can be seen that implementing this optional embodiment can, in the process of matching the corresponding energy consumption calculation algorithm according to the collected state parameters and the sampling interval. Specifically, when it is determined that the sampling interval exceeds the preset sampling interval threshold range, the constant current charging segments in the sampling interval are identified according to the state parameters at the sampling interval, so as to calculate the electric quantity based on the constant current charging segments, improve the accuracy of the energy consumption calculation of the electric vehicle, calculate the charging power target value of the constant current charging segment for indicating the concentrated distribution of the charging power in the constant current charging segment and the frequency distribution parameter of the charging power target value for representing the occurrence frequency of the charging power target value in the constant current charging segment, and match the corresponding energy consumption calculation algorithm according to the charging power target value, the frequency distribution parameter, and the state parameters of the constant current charging segment, improve the matching accuracy of the energy consumption calculation algorithm for different state parameters under different sampling intervals, which is beneficial to improving the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle factory, and is beneficial to improving the energy consumption calculation efficiency of the electric vehicle.

[0074] In this optional embodiment, as an optional implementation manner, the above identifying the constant current charging segments in the sampling interval according to the state parameters at the sampling interval includes:

[0075] Determine the charging status identifier in the state parameters;

[0076] Identify the charging segments in the sampling interval according to the charging status identifier;

[0077] Calculate the power characteristic distribution parameters of the charging segment according to the state parameters in the charging segment, where the power characteristic distribution parameters are used to represent the charging power distribution of the charging segment;

[0078] Identify the constant current charging segments in the charging segment according to the power characteristic distribution parameters and the preset constant current power range threshold, where the charging power of the constant current charging segments is within the preset constant current power range threshold.

[0079] It can be seen that implementing this optional embodiment can, in the process of identifying the constant current charging segments in the sampling interval according to the state parameters under the sampling interval. Specifically, based on the charging state identifier in the determined state parameters, identify the charging segments in the sampling interval, calculate the power characteristic distribution parameters of the charging segments according to the state parameters in the charging segments, and identify the constant current charging segments with the charging power within the preset constant current power range threshold in the charging segments according to the power characteristic distribution parameters and the preset constant current power range threshold, improving the accuracy of power consumption calculation and reducing the error caused by the part with large power mutation and large fluctuation participating in the power consumption calculation.

[0080] 103. Calculate the target energy consumption parameter of the electric vehicle according to the energy consumption calculation algorithm and the state parameters under the sampling interval.

[0081] In this optional embodiment, as another optional implementation manner, when it is determined that the sampling interval does not exceed the preset sampling interval threshold range, calculating the target energy consumption parameter of the electric vehicle according to the energy consumption calculation algorithm and the state parameters under the sampling interval includes:

[0082] Determine the battery type parameter corresponding to the electric vehicle and at least one driving segment under the sampling interval according to the state parameters;

[0083] Match the power consumption algorithm of the electric vehicle under each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle under each driving segment;

[0084] Calculate the total power consumption of the electric vehicle according to the power consumption of the electric vehicle under all driving segments;

[0085] Calculate the target energy consumption parameter of the electric vehicle according to the total power consumption, the effective driving mileage under all driving segments, and the preset first weight.

[0086] In this optional embodiment, optionally, the above formula for calculating the target energy consumption parameter is specifically

[0087]

[0088] Among them, C is used to represent the energy consumption per 100 kilometers (kWh / 100km), that is, the target energy consumption parameter, P is used to represent the total power consumption (kWh), Si is used to represent the effective driving mileage (km) of the i-th driving segment, and N is used to represent the preset first weight;

[0089] It can be seen that when it is determined that the sampling interval does not exceed the preset sampling interval threshold range, the optional embodiment can, according to the state parameters, determine the battery type parameter corresponding to the electric vehicle and at least one driving segment at the sampling interval, match the power consumption algorithm of the electric vehicle under each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle under each driving segment, calculate the total power consumption of the electric vehicle according to the power consumption of the electric vehicle under all driving segments, and calculate the target energy consumption parameter of the electric vehicle according to the total power consumption, the effective driving mileage under all driving segments and the preset first weight, so as to improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle factory, which is beneficial to improving the energy consumption calculation efficiency of the electric vehicle.

[0090] In this optional embodiment, as an optional implementation manner, the above state parameters include the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value, the discharge start SOC, the discharge end SOC and the first rated power under each driving segment of the electric vehicle; the driving segment is determined based on the state parameters;

[0091] Matching the power consumption algorithm of the electric vehicle under each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle under each driving segment includes:

[0092] Judging whether the battery type parameter matches the preset battery type parameter. When it is determined that the battery type parameter matches the preset battery type parameter, for each driving segment, calculate the power consumption of the electric vehicle under the driving segment according to the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value and the preset second weight under the driving segment;

[0093] When it is determined that the battery type parameter does not match the preset battery type parameter, for each driving segment, calculate the power consumption of the electric vehicle under the driving segment according to the discharge start SOC, the discharge end SOC, the first rated power and the first battery health value under the driving segment.

[0094] In this optional embodiment, optionally, when it is determined that the battery type parameter matches the preset battery type parameter, the calculation formula for the total power consumption of the above electric vehicle is:

[0095]

[0096] Wherein, P is used to represent the total power consumption of the electric vehicle, and U i is used to represent the first voltage parameter of the i-th driving segment, and I i is used to represent the first current parameter of the i-th driving segment, and Δ t (h) is used to represent the first inter-frame time difference. Specifically, it can be the time difference between the upper and lower frames in hours. SOH1 is used to represent the first battery health, and A is used to represent the preset second weight;

[0097] Further, optionally, when it is determined that the battery type parameter does not match the preset battery type parameter, the calculation formula for the total power consumption of the above-mentioned electric vehicle is:

[0098]

[0099] Wherein, SOC i,star and SOC i,end are respectively used to represent the starting SOC of discharge in the i-th driving segment and the ending SOC of discharge in the i-th driving segment, and E is used to represent the first rated power;

[0100] It can be seen that implementing this optional embodiment can match the power consumption algorithm of the electric vehicle in each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle in each driving segment. Specifically, when it is determined that the battery type parameter matches the preset battery type parameter, for each driving segment, according to the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value and the preset second weight in this driving segment, calculate the power consumption of the electric vehicle in this driving segment; while when it is determined that the battery type parameter does not match the preset battery type parameter, for each driving segment, according to the starting SOC of discharge, the ending SOC of discharge, the first rated power and the first battery health value in this driving segment, calculate the power consumption of the electric vehicle in this driving segment, which can further improve the flexibility, accuracy and feasibility of calculating the power consumption of the electric vehicle in a certain driving segment, and further improve the flexibility and accuracy of the energy consumption calculation of the electric vehicle.

[0101] In an optional embodiment, the above state parameters include the starting SOC of charging, the second rated power and the second battery health value of the electric vehicle in the constant current charging segment. When it is determined that the sampling interval exceeds the preset sampling interval threshold range, according to the energy consumption calculation algorithm and the state parameters at the sampling interval, calculate the target energy consumption parameter of the electric vehicle, including:

[0102] Match the charging process power algorithm of the electric vehicle according to the frequency distribution parameter to calculate the charging process power of the electric vehicle in the constant current charging segment;

[0103] Calculate the total charge at the end of the constant current charging segment of the electric vehicle based on the charge during the charging process, the initial SOC of charging, the second rated charge, and the second battery health value;

[0104] Calculate the preset subsequent adjacent starting charge of the constant current charging segment according to the preset subsequent adjacent starting SOC, the second rated charge, and the second battery health value of the constant current charging segment;

[0105] Calculate the actual power consumption of the electric vehicle based on the total charge at the end of charging and the preset subsequent adjacent starting charge;

[0106] Calculate the target energy consumption parameter of the electric vehicle based on the actual power consumption, the effective driving range of the electric vehicle, and the preset third weight value.

[0107] In this alternative embodiment, optionally, the specific calculation method of the above target energy consumption parameter is as follows:

[0108]

[0109] Among them, C is used to represent the energy consumption per 100 kilometers (kWh / 100km), that is, the target energy consumption parameter, and S is used to represent the preset third weight value.

[0110] It can be seen that implementing this alternative embodiment can, when it is determined that the sampling interval exceeds the preset sampling interval threshold range, specifically, match the charging process power algorithm of the electric vehicle based on the frequency distribution parameter to calculate the charging process power of the electric vehicle in the constant current charging segment, improve the calculation accuracy and adaptability of the charging process power, improve the energy consumption calculation granularity of the electric vehicle, calculate the total charge at the end of the constant current charging segment of the electric vehicle based on the charge during the charging process, the initial SOC of charging, the second rated charge, and the second battery health value; calculate the preset subsequent adjacent starting charge of the constant current charging segment according to the preset subsequent adjacent starting SOC, the second rated charge, and the second battery health value of the constant current charging segment; calculate the actual power consumption of the electric vehicle based on the total charge at the end of charging and the preset subsequent adjacent starting charge; calculate the target energy consumption parameter of the electric vehicle based on the actual power consumption, the effective driving range of the electric vehicle, and the preset third weight value, so as to further improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle manufacturer, which is beneficial to improving the energy consumption calculation efficiency of the electric vehicle.

[0111] In this alternative embodiment, as an alternative implementation manner, the above state parameters further include the charging duration, the second voltage parameter, the second current parameter, and the second inter-frame time difference of the electric vehicle in the constant current charging segment. Matching the charging process power algorithm of the electric vehicle according to the frequency distribution parameter to calculate the charging process power of the electric vehicle in the constant current charging segment includes:

[0112] Determine whether the frequency distribution parameter is greater than or equal to a preset frequency distribution parameter threshold. When it is determined that the frequency distribution parameter is greater than or equal to the preset frequency distribution parameter threshold, calculate the charging process power of the electric vehicle according to the charging duration, the target charging power value, and a preset fourth weight value;

[0113] When it is determined that the frequency distribution parameter is less than the preset frequency distribution parameter threshold, calculate the charging process power of the electric vehicle according to the second voltage parameter, the second current parameter, the second inter-frame time difference, the second battery health value, and a preset fifth weight value under the constant current charging segment.

[0114] In this optional embodiment, optionally, when it is determined that the frequency distribution parameter is greater than or equal to the preset frequency distribution parameter threshold, the specific calculation method of the above charging process power is as follows:

[0115] Charging process power = charging duration × charging power mode ÷ D;

[0116] where D is the preset fourth weight value;

[0117] Furthermore, optionally, when it is determined that the frequency distribution parameter is less than the preset frequency distribution parameter threshold, the specific calculation method of the above charging process power is as follows:

[0118]

[0119] where P1 is used to represent the total power consumption of the electric vehicle, U1 i is used to represent the second voltage parameter under the i-th constant current charging segment, I1 i is used to represent the second current parameter under the i-th constant current charging segment, Δ t (h1) is used to represent the second inter-frame time difference, specifically, it can be the time difference between the upper and lower frames in hours, SOH2 is used to represent the second battery health, and A is used to represent the preset fifth weight value;

[0120] It can be seen that implementing this optional embodiment can calculate the charging process power of the electric vehicle respectively based on different judgment results of whether the frequency distribution parameter is greater than or equal to the preset frequency distribution parameter threshold, and can improve the flexibility and accuracy of the charging process power calculation, and improve the flexibility and accuracy of the energy consumption calculation of the electric vehicle.

[0121] It can be seen that implementing the embodiment of the present invention can match the corresponding energy consumption calculation algorithm based on the determined state parameters of the electric vehicle under different sampling intervals, and then calculate the target energy consumption parameter of the electric vehicle based on the energy consumption calculation algorithm and the state parameters under the sampling interval, so as to improve the accuracy and flexibility of the energy consumption calculation of the electric vehicle on the basis of reducing the dependence on the specific driving data of the vehicle factory, which is beneficial to improving the energy consumption calculation efficiency of the electric vehicle.

[0122] Example 2

[0123] Please refer to Figure 2 , Figure 2 , which is a schematic flowchart of another method for calculating the energy consumption of an electric vehicle disclosed in an embodiment of the present invention. Among them, Figure 2 The described method for calculating the energy consumption of an electric vehicle can be applied to electric vehicles, and can also be applied to battery management systems / devices, and can also be applied to intelligent devices related to the above-mentioned electric vehicles and battery management systems / devices. The intelligent devices include, but are not limited to, one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, urban management devices, and intelligent networked devices. The embodiments of the present invention do not make limitations. As Figure 2 shown, the method for calculating the energy consumption of the electric vehicle may include the following operations:

[0124] 201. Determine the sampling interval of the state parameters of the electric vehicle. The state parameters are different under different sampling intervals;

[0125] 202. Match the corresponding energy consumption calculation algorithm according to the state parameters and the sampling interval;

[0126] 203. Calculate the target energy consumption parameters of the electric vehicle according to the energy consumption calculation algorithm and the state parameters under the sampling interval;

[0127] In the embodiments of the present invention, for the supplementary description of steps 201-step 203, please refer to the supplementary description of steps 101-step 103 in Example 1, and the embodiments of the present invention will not elaborate on this.

[0128] 204. Determine the parameter dimension representation value of the state parameter. The parameter dimension representation value is used to represent the dimension richness of the state parameter and the vehicle state values under each dimension;

[0129] 205. Generate a working condition matrix of the electric vehicle according to the parameter dimension representation value. The working condition matrix is used to represent the working condition state of the electric vehicle;

[0130] 206. Analyze the linkage influence factor between the target energy consumption parameter and the working condition matrix according to the target energy consumption parameter and the working condition matrix. The linkage influence factor is used to represent the factor that causes the target energy consumption parameter to change due to the working condition matrix;

[0131] 207. Generate an energy consumption optimization plan for the electric vehicle and a charging and discharging strategy optimization plan for the electric vehicle according to the linkage influence factor.

[0132] In the embodiments of the present invention, optionally, a typical working condition matrix is constructed: a multi-dimensional working condition matrix including the SOC range, temperature range, and speed characteristics is established:

[0133] Operating condition W1: Low-temperature and low-battery condition (SOC < 40%, temperature < 15°C, steady / dynamic)

[0134] Operating condition W2: Low-temperature and high-battery condition (SOC > 90%, temperature < 15°C, steady / dynamic)

[0135] Operating condition W3: Normal condition (SOC: 40 - 90%, temperature 15 - 30°C, steady / dynamic)

[0136] Operating condition W4: High-temperature and high-battery condition (SOC > 90%, temperature > 30°C, steady / dynamic)

[0137] Operating condition W5: High-temperature and low-battery condition (SOC < 40%, temperature > 30°C, steady / dynamic)

[0138] Among them, the SOC range refers to the starting SOC of discharge, and the temperature range refers to the highest temperature of the single battery at the start of discharge (°C);

[0139] And the criteria for determining steady / dynamic operating conditions can be:

[0140] Determination of steady operating condition (needs to be satisfied simultaneously):

[0141] Standard deviation of vehicle speed < 8 km / h

[0142] Range of vehicle speed < 25 km / h

[0143] 90th percentile of acceleration < 0.5 m / s 2

[0144] Determination of dynamic operating condition (meeting any one condition):

[0145] Standard deviation of vehicle speed ≥ 8 km / h

[0146] Range of vehicle speed ≥ 25 km / h

[0147] 90th percentile of acceleration ≥ 0.5 m / s 2

[0148] It can be seen that implementing the embodiments of the present invention can reduce the dependence on specific driving data of the vehicle factory, improve the accuracy and flexibility of the energy consumption calculation of electric vehicles, and is conducive to improving the energy consumption calculation efficiency of electric vehicles. Further, by determining the parameter dimension representation values that represent the richness of the dimensions of the state parameters and the vehicle state values under each dimension, according to the parameter dimension representation values, a working condition matrix for representing the working condition state of the electric vehicle is generated. According to the target energy consumption parameters and the working condition matrix, the linkage influence factor representing the factors that cause the target energy consumption parameters to change due to the working condition matrix is analyzed. According to the linkage influence factor, an energy consumption optimization plan for the electric vehicle and a charging and discharging strategy optimization plan for the electric vehicle are generated. Thus, it is possible to further determine the working conditions of the electric vehicle based on the sampled state parameters of the electric vehicle, so as to further analyze the influence of stable working conditions and dynamic working conditions on energy consumption, the influence of SOH on the rated power, etc., provide a basis for the research of energy consumption characteristics under different working conditions, improve the sustainability and stability of the energy consumption analysis of electric vehicles, and is conducive to further improving the accuracy of the energy consumption analysis of electric vehicles.

[0149] Embodiment III

[0150] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an energy consumption calculation device for an electric vehicle disclosed in the embodiments of the present invention. Among them, the energy consumption calculation device for the electric vehicle can be applied to an electric vehicle, can also be applied to a battery management system / device, and can also be applied to an intelligent device related to the above-mentioned electric vehicle and battery management system / device. The intelligent device includes, but is not limited to, one or more of a battery device, a cloud device, an edge computing device, a relay device, a base station device, a city management device, and an intelligent network connection device, which are not limited in the embodiments of the present invention. As Figure 3 shown, the energy consumption calculation device for the electric vehicle may include:

[0151] A memory 301 storing executable program code.

[0152] A processor 302 coupled to the memory 301.

[0153] The processor 302 calls the executable program code stored in the memory 301 and executes the steps in the energy consumption calculation method for the electric vehicle described in Embodiment I or Embodiment II of the present invention.

[0154] Embodiment IV

[0155] The embodiments of the present invention disclose a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps in the energy consumption calculation method for the electric vehicle described in Embodiment I or Embodiment II of the present invention.

[0156] Example 5

[0157] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the energy consumption calculation method of the electric vehicle described in Embodiment 1 or Embodiment 2.

[0158] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0159] Through the above specific descriptions of the embodiments, those skilled in the art can clearly understand that each implementation manner can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically-erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc memories, a magnetic disk memory, a tape memory, or any other computer-readable medium capable of carrying or storing data.

[0160] Finally, it should be noted that: What is disclosed by a method, device, and computer storage medium for calculating energy consumption of an electric vehicle according to the embodiments of the present invention is only the preferred embodiments of the present invention, and is only used to illustrate the technical solutions of the present invention, rather than limiting it; Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating energy consumption of an electric vehicle, characterized in that: The method comprises: Determine a sampling interval of a state parameter of the electric vehicle, wherein the state parameter at different sampling intervals is different; According to the state parameter and the sampling interval, matching a corresponding energy consumption calculation algorithm; According to the energy consumption calculation algorithm and the state parameters at the sampling interval, the target energy consumption parameters of the electric vehicle are calculated.

2. The method for calculating the energy consumption of an electric vehicle according to claim 1, characterized in that: The matching of the corresponding energy consumption calculation algorithm according to the state parameter and the sampling interval includes: Determining whether the sampling interval exceeds a preset sampling interval threshold interval; When it is determined that the sampling interval exceeds the preset sampling interval threshold interval, a constant current charging segment in the sampling interval is identified according to the state parameter in the sampling interval; Calculating a charging power target value of the constant current charging segment and a frequency distribution parameter of the charging power target value, wherein the charging power target value is used to indicate a concentrated distribution of the charging power of the constant current charging segment, and the frequency distribution parameter is used to indicate an occurrence frequency of the charging power target value in the constant current charging segment; Matching a corresponding energy consumption calculation algorithm according to the charging power target value, the frequency distribution parameter and the state parameter of the constant current charging segment; When it is determined that the sampling interval does not exceed the preset sampling interval threshold range, a corresponding energy consumption calculation algorithm is matched according to the state parameter under the sampling interval.

3. The method for calculating the energy consumption of an electric vehicle according to claim 2, characterized in that: The step of identifying the constant current charging segment in the sampling interval according to the state parameter in the sampling interval includes: Determining a charging status indicator in the status parameter; According to the charging state identifier, identifying a charging segment in the sampling interval; Calculating a power characteristic distribution parameter of the charging segment according to the state parameter in the charging segment, wherein the power characteristic distribution parameter is used to represent a charging power distribution condition of the charging segment; According to the power characteristic distribution parameter and the preset constant current power range threshold, a constant current charging segment in the charging segments is identified, and the charging power of the constant current charging segment is within the preset constant current power range threshold.

4. The method for calculating the energy consumption of an electric vehicle according to claim 2, characterized in that: When it is determined that the sampling interval does not exceed the preset sampling interval threshold range, the target energy consumption parameter of the electric vehicle is calculated according to the energy consumption calculation algorithm and the state parameter under the sampling interval, including: Determine, according to the state parameter, a battery type parameter corresponding to the electric vehicle and at least one driving segment in the sampling interval; According to the battery type parameter, matching the power consumption algorithm of the electric vehicle in each driving segment to calculate the power consumption of the electric vehicle in each driving segment; Calculating the total power consumption of the electric vehicle according to the power consumption of the electric vehicle in all the driving segments; The target energy consumption parameter of the electric vehicle is calculated according to the total power consumption, the effective driving mileage in all the driving segments and a preset first weight.

5. The method for calculating the energy consumption of an electric vehicle according to claim 4, characterized in that: The state parameters include a first voltage parameter, a first current parameter, a first inter-frame time difference, a first battery health value, a discharge start SOC, a discharge end SOC and a first rated power in each driving segment of the electric vehicle; The driving segment is determined based on the state parameter; The step of matching the power consumption algorithm of the electric vehicle in each driving segment according to the battery type parameter to calculate the power consumption of the electric vehicle in each driving segment includes: Determine whether the battery type parameter matches the preset battery type parameter. When it is determined that the battery type parameter matches the preset battery type parameter, for each driving segment, calculate the power consumption of the electric vehicle in the driving segment according to the first voltage parameter, the first current parameter, the first inter-frame time difference, the first battery health value and the preset second weight in the driving segment; When it is determined that the battery type parameter does not match the preset battery type parameter, for each driving segment, the power consumption of the electric vehicle in the driving segment is calculated according to the discharge start SOC, the discharge end SOC, the first rated power and the first battery health value in the driving segment.

6. The method for calculating the energy consumption of an electric vehicle according to claim 2, characterized in that: The state parameters include the charging start SOC, the second rated power, and the second battery health value of the electric vehicle in the constant current charging segment. When it is determined that the sampling interval exceeds the preset sampling interval threshold interval, the target energy consumption parameters of the electric vehicle are calculated according to the energy consumption calculation algorithm and the state parameters in the sampling interval, including: According to the frequency distribution parameters, matching the charging process power algorithm of the electric vehicle to calculate the charging process power of the electric vehicle in the constant current charging segment; Calculating the total charge of the electric vehicle at the end of charging in the constant current charging segment according to the charge during the charging process, the charging start SOC, the second rated charge and the second battery health value; Calculating a preset subsequent adjacent charging start power of the constant current charging segment according to the preset subsequent adjacent charging start SOC of the constant current charging segment, the second rated power, and the second battery health value; Calculating the actual power consumption of the electric vehicle according to the total power consumption at the end of charging and the preset subsequent adjacent charging start power consumption; The target energy consumption parameter of the electric vehicle is calculated according to the actual power consumption, the effective driving mileage of the electric vehicle and a preset third weight.

7. The method for calculating the energy consumption of an electric vehicle according to claim 6, characterized in that: The state parameters also include the charging time of the electric vehicle in the constant current charging segment, the second voltage parameter, the second current parameter, and the second inter-frame time difference. The matching of the charging process power algorithm of the electric vehicle according to the frequency distribution parameters to calculate the charging process power of the electric vehicle in the constant current charging segment includes: Determining whether the frequency distribution parameter is greater than or equal to a preset frequency distribution parameter threshold, and when it is determined that the frequency distribution parameter is greater than or equal to the preset frequency distribution parameter threshold, calculating the amount of electricity in the charging process of the electric vehicle according to the charging duration, the charging power target value and a preset fourth weight; When it is determined that the frequency distribution parameter is less than the preset frequency distribution parameter threshold, the charging process power of the electric vehicle is calculated based on the second voltage parameter, the second current parameter, the second frame time difference, the second battery health value and the preset fifth weight under the constant current charging segment.

8. The method for calculating the energy consumption of an electric vehicle according to any one of claims 1 to 7, characterized in that: The method further comprises: Determine a parameter dimension representation value of the state parameter, wherein the parameter dimension representation value is used to represent the dimensional richness of the state parameter and the vehicle state value under each dimension; Generate a working condition matrix of the electric vehicle according to the parameter dimension representation value, wherein the working condition matrix is ​​used to represent the working condition status of the electric vehicle; According to the target energy consumption parameter and the operating condition matrix, analyzing the linkage influence factor between the target energy consumption parameter and the operating condition matrix, the linkage influence factor is used to indicate the factor that the operating condition matrix causes the target energy consumption parameter to change; According to the linkage influencing factors, an energy consumption optimization plan of the electric vehicle and a charging and discharging strategy optimization plan of the electric vehicle are generated.

9. An energy consumption calculation device for an electric vehicle, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the energy consumption calculation method for an electric vehicle as described in any one of claims 1-8.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the energy consumption calculation method for an electric vehicle as described in any one of claims 1-8.

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