A method and system for determining the cruising range reliability of a pure electric vehicle

Abstract

The present application discloses a method and system for determining the cruising reliability of pure electric vehicles, which relates to the field of new energy vehicle cruising evaluation. The method includes: respectively conducting multiple cruising range tests on each target vehicle, and calculating the experimental energy consumption of each target vehicle under each cruising range test; determining a first matrix based on the actual annual comprehensive energy consumption of all target vehicles, and determining a second matrix based on the experimental energy consumption of all target vehicles under different cruising range tests; determining the N cruising range tests with the highest correlation with the first matrix as N test indicators; performing the weighted product summation on the cruising range feedback of each target vehicle under the N test indicators to obtain the cruising range evaluation value of each target vehicle; the calibrated cruising range of the target vehicle with the cruising range evaluation value greater than the set threshold is truly reliable. The present application can determine the reliability of the calibrated cruising range of pure electric vehicles, and at the same time provides an objective basis for consumers to select target vehicles.

Description

Technical Field

[0001] This application relates to the technical field of new energy vehicle endurance evaluation, and particularly to a method and system for determining the endurance reliability of pure electric vehicles. Background Art

[0002] Pure electric vehicles have been favored by consumers due to their advantages such as pollution-free, low noise, high energy efficiency, and low maintenance and usage costs. With the continuous popularization of new energy vehicles, the market penetration rate and the number of owned pure electric vehicles have been continuously increasing. Although the number of owned fuel vehicles still far exceeds that of pure electric vehicles, the proportion of new models and the sales proportion of pure electric vehicles have exceeded those of fuel vehicles.

[0003] As one of the iconic performance indicators of pure electric vehicles, endurance has always been highly concerned by manufacturers and consumers. Currently, most enterprises will give the normal temperature values of the China Light Vehicle Test Cycle (CLTC) of the vehicle during the publicity process, and some models will also give the normal temperature values of the World Light Vehicle Test Cycle (WLTC). However, the usage scenarios of consumers vary greatly, and there are also large temperature differences between the north and the south. Therefore, in the actual usage process, most consumers often question the problem of overstated endurance of pure electric vehicles, and at the same time, they cannot determine whether its calibrated endurance is true and reliable based on objective evidence. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for determining the endurance reliability of pure electric vehicles, which can determine the reliability of the calibrated endurance of pure electric vehicles and at the same time provide an objective basis for consumers to select target vehicles.

[0005] To achieve the above purpose, this application provides the following solutions.

[0006] In the first aspect, this application provides a method for determining the endurance reliability of pure electric vehicles, and the method for determining the endurance reliability of pure electric vehicles is as follows.

[0007] Determine multiple target vehicles, and calculate the actual annual comprehensive energy consumption of each target vehicle; the multiple target vehicles include pure electric vehicles of different models and different urban users.

[0008] Conduct multiple driving range tests on each target vehicle respectively, and calculate the experimental energy consumption of each target vehicle under each driving range test.

[0009] Determine the first matrix based on the actual annual comprehensive energy consumption of all target vehicles, and determine the second matrix based on the experimental energy consumption of all target vehicles under different driving range tests.

[0010] Calculate the correlation coefficient of the first matrix and the second matrix, select the N kinds of driving range tests with the highest correlation with the first matrix as N test indicators according to the correlation coefficient, and determine the weights of each test indicator.

[0011] Calculate the driving range feedback of each target vehicle under each test indicator; the driving range feedback includes the driving range decline rate and the driving range accuracy coefficient.

[0012] Perform the weighted product summation on the driving range feedback of each target vehicle under N test indicators to obtain the driving range evaluation value of each target vehicle.

[0013] Compare the driving range evaluation values of all target vehicles, and prompt consumers to select the target vehicles whose driving range evaluation values are greater than the set threshold; the calibrated cruising range of the target vehicles whose driving range evaluation values are greater than the set threshold is true and reliable.

[0014] In a second aspect, the present application also provides a computer system, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the method for determining the cruising reliability of a pure electric vehicle described in the first aspect.

[0015] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application.

[0016] This application selects pure electric vehicles of different models and users in different cities as multiple target vehicles, fully considering key factors affecting the endurance of pure electric vehicles, such as temperature, road conditions, and user driving habits. At the same time, in order to further enhance the impact of these key factors on the endurance of pure electric vehicles, this application also conducts various endurance tests on each target vehicle respectively. These endurance tests can comprehensively reflect the above key factors. Secondly, this application also determines a first matrix based on the actual annual comprehensive energy consumption of all target vehicles, and determines a second matrix based on the experimental energy consumption of all target vehicles under different endurance tests. By calculating and comparing the correlation coefficients of the two matrices, N endurance tests with the highest correlation with the first matrix are selected from various endurance tests as N test indicators. These test indicators are the factors that ultimately have the greatest impact on the endurance of pure electric vehicles determined by this application. In addition, for each test indicator, this application also proposes the calculation of the endurance mileage decline rate and the endurance mileage accuracy coefficient, and through the weighted summation between different test indicators and between the endurance mileage decline rate and the endurance mileage accuracy coefficient under each test indicator, the endurance mileage evaluation value of each target vehicle is obtained. This endurance mileage evaluation value is determined based on the test indicators after the above complex screening, fully considering and integrating important factors affecting the endurance of pure electric vehicles. Therefore, ultimately, consumers only need to select a target vehicle whose endurance mileage evaluation value is greater than the set threshold, and the calibrated endurance of this target vehicle is true and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of the method for determining the endurance reliability of pure electric vehicles in the embodiments of the present application.

[0019] Figure 2 It is the internal structure diagram of the computer system in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0021] The purpose of this application is to provide a method and system for determining the endurance reliability of a pure electric vehicle, which can determine the reliability of the calibrated endurance of a pure electric vehicle and also provide an objective basis for consumers to select a target vehicle.

[0022] To make the above objects, features, and advantages of this application more obvious and understandable, the following further detailed description of this application will be given in conjunction with the accompanying drawings and specific embodiments.

[0023] In an exemplary embodiment, as Figure 1 shown, a method for determining the endurance reliability of a pure electric vehicle is provided, and the method for determining the endurance reliability of a pure electric vehicle is specifically as follows.

[0024] Step S1: Determine multiple target vehicles and calculate the actual annual comprehensive energy consumption of each target vehicle; the multiple target vehicles include pure electric vehicles of different models and different urban users.

[0025] In this embodiment, the actual road energy consumption data of the target vehicles is collected in six major regions and ten typical cities in China, that is, the annual cumulative power grid power consumption and the annual driving mileage of each vehicle owner are statistically counted, and then based on the annual cumulative power grid power consumption and the annual driving mileage, the actual annual comprehensive energy consumption of each target vehicle is calculated. Among them, the calculation formula of the actual annual comprehensive energy consumption is as follows.

[0026] 。

[0027] In the formula, is the actual annual comprehensive energy consumption (kw·h / 100km) of the i th target vehicle, is the annual cumulative power grid power consumption (kw·h) of the i th target vehicle, is the annual driving mileage (km) of the i th target vehicle.

[0028] Step S2: Conduct multiple endurance mileage tests on each target vehicle respectively, and calculate the experimental energy consumption of each target vehicle under each endurance mileage test.

[0029] In this embodiment, different driving range tests are carried out on each target vehicle selected in step S1 in the laboratory environmental chamber. The driving range test items are successively the normal temperature driving range test of China Light-duty Vehicle Test Cycle-Passenger (CLTC-P), the low temperature driving range test of CLTC-P, the high temperature driving range test of CLTC-P, the normal temperature constant speed 120 km / h driving range test, the low temperature constant speed 120 km / h driving range test, and the high temperature constant speed 120 km / h driving range test. Among them, the low temperature in the above driving range test is -10°C (the low temperature test temperature range specified by the national standard is -4°C to -10°C (-7°C ± 3°C), and -10°C is within the low temperature test temperature range specified by the national standard, and only the upper limit is taken here), and the air conditioner settings are the same as those in the national standard low temperature test; the high temperature is 35°C, and the air conditioner settings are the same as those in the national standard high temperature test. In addition, during the above driving range test, the battery pack current and voltage of the target vehicle need to be recorded through a current clamp or a data acquisition device (the sampling frequency is 1 Hz), and the experimental energy consumption is calculated by the following formula.

[0030] 。

[0031] 。

[0032] 。

[0033] In the formula, is the experimental energy consumption of the i th target vehicle under the k th driving range test, is the power consumption (kw) of the i th target vehicle under the k th driving range test, is the start time of the k th driving range test, is the end time of the k th driving range test, is the battery pack current (A) of the t th target vehicle at i moment, is the battery pack voltage (V) of the t th target vehicle at i moment, is the driving range (km) of the i th target vehicle under the k th driving range test, is the vehicle speed (km / h) of the t th target vehicle at i moment.

[0034] Step S3: Determine the first matrix based on the actual annual comprehensive energy consumption of all target vehicles, and determine the second matrix based on the experimental energy consumption of all target vehicles under different cruising range tests.

[0035] In this embodiment, the form of the first matrix is as follows.

[0036] .

[0037] In the formula, A is the first matrix, is the actual annual comprehensive energy consumption of the 1st target vehicle, is the actual annual comprehensive energy consumption of the 2nd target vehicle, and the total number of rows of the first matrix A is the same as the total number of target vehicles.

[0038] The form of the second matrix is as follows.

[0039] .

[0040] In the formula, B is the second matrix, is the experimental energy consumption of the 1st target vehicle under the CLTC-P normal temperature cruising range test, is the experimental energy consumption of the 1st target vehicle under the CLTC-P low temperature cruising range test, is the experimental energy consumption of the 1st target vehicle under the CLTC-P high temperature cruising range test, is the experimental energy consumption of the 1st target vehicle under the normal temperature constant speed 120 km / h cruising range test, is the experimental energy consumption of the 1st target vehicle under the low temperature constant speed 120 km / h cruising range test, is the experimental energy consumption of the 1st target vehicle under the high temperature constant speed 120 km / h cruising range test, is the i experimental energy consumption of the th target vehicle under the CLTC-P normal temperature cruising range test, i is the experimental energy consumption of the i th target vehicle under the CLTC-P low temperature cruising range test, is the i experimental energy consumption of the th target vehicle under the normal temperature constant speed 120 km / h cruising range test, i is the experimental energy consumption of the th target vehicle under the low temperature constant speed 120 km / h cruising range test,i The experimental energy consumption of a target vehicle under the high-temperature constant-speed 120 km / h endurance mileage test, the second matrix B The total number of rows of is the same as the total number of target vehicles, the second matrix B The total number of columns of is the same as the total number of endurance mileage test categories.

[0041] Step S4: Calculate the correlation coefficient between the first matrix and the second matrix, select the N endurance mileage tests with the highest correlation with the first matrix as N test indicators according to the correlation coefficient, and determine the weights of each test indicator; N is an integer greater than 3 and less than 6 (N is 4 in this embodiment).

[0042] In this embodiment, it is necessary to calculate the Pearson correlation coefficient between the first matrix and the second matrix. This coefficient is a quantity that studies the degree of linear correlation between variables, generally represented by the letter Corr( A , B ) to represent, and is used to measure the linear relationship between the first matrix A and the second matrix B . After calculating the Pearson correlation coefficient, by comparing the magnitude relationship between them, select the endurance mileage tests corresponding to the top four Pearson correlation coefficients, and use these four selected endurance mileage tests as four test indicators for subsequent evaluation. In addition, it is also necessary to determine the weights of each test indicator when calculating the final endurance mileage evaluation value according to the proportion of the driving mileage (urban driving mileage and highway driving mileage) of the user in different scenarios (spring, summer, autumn, winter). For example: the user's urban driving mileage at normal temperature = 5000 km, the urban driving mileage at low temperature = 2000 km, the urban driving mileage at high temperature = 2000 km, the highway driving mileage = 1000 km, then the total driving mileage = urban driving mileage at normal temperature + urban driving mileage at low temperature + urban driving mileage at high temperature + highway driving mileage = 10000 km, the weight of urban driving at normal temperature = urban driving mileage at normal temperature / total driving mileage, the weight of urban driving at low temperature = urban driving mileage at low temperature / total driving mileage, the high temperature urban driving = urban driving mileage at high temperature / total driving mileage, the highway driving weight = highway driving mileage / total driving mileage.

[0043] Step S5: Calculate the endurance mileage feedback of each target vehicle under each test indicator; the endurance mileage feedback includes the endurance mileage decline rate and the endurance mileage accuracy coefficient.

[0044] In this embodiment, each test indicator is considered from the following two dimensions. The first is the endurance mileage decline rate, and the second is the endurance mileage accuracy coefficient. The weights of the two in the final calculation of the endurance mileage evaluation value are 80% and 20% respectively. The calculation formula of the endurance mileage decline rate is as follows.

[0045] .

[0046] In the formula, is the decline rate of the cruising range of the i th target vehicle under the j th test index, is the cruising range (km) of the i th target vehicle in the CLTC-P normal temperature cruising range test, is the cruising range (km) of the i th target vehicle under the j th test index.

[0047] The calculation formula of the cruising range accuracy coefficient is as follows.

[0048] .

[0049] In the formula, is the cruising range accuracy coefficient (retaining two significant figures) of the i th target vehicle under the j th test index, is the actual remaining range of the i th target vehicle at the j th sampling point under the m th test index, is the indicated remaining range of the i th target vehicle at the j th sampling point under the m th test index, is the average value of the indicated remaining ranges of all sampling points (retaining one significant figure) of the i th target vehicle under the j th test index. Each cruising range test is regarded as a sampling point.

[0050] As a preferred implementation manner, when the test index determined in step S4 includes the CLTC-P normal temperature cruising range test, the score of this item is calculated through Table 1 below.

[0051] Table 1 CLTC-P Normal Temperature Score Table

[0052]

[0053] When the CLTC-P normal temperature power consumption of the target vehicle is ≤Y and ≥0.85Y, the score is between 0 and 60 points, and it is calculated by the method of linear interpolation within the interval. For example: the CLTC-P normal temperature power consumption a1 of vehicle 1 = 13.2, Y = 18.39, 0.6 < a1 / Y = 0.7177 < 0.85, and the final score is calculated by the difference (100 - final score) / (100 - 60) = (0.7177 - 0.6) / (0.85 - 0.6); when the CLTC-P normal temperature power consumption of the target vehicle is <0.85Y and ≥0.6Y, the score is between 60 and 100 points, and it is calculated by the above method of linear interpolation within the interval. In addition, the Y value is mainly calculated by the following formula.

[0054] Y = 0.006×M + 8.

[0055] In the formula, M is the curb weight of the target vehicle (kg, reserved to two significant figures), and this formula is obtained by linear fitting based on the data provided by the enterprise, historical test results and empirical values.

[0056] Score for the decline rate of cruising range: When the test indicators include CLTC-P low temperature cruising range test, CLTC-P high temperature cruising range test, normal temperature constant speed 120km / h cruising range test, low temperature constant speed 120km / h cruising range test or high temperature constant speed 120km / h cruising range test, the item score is calculated by Table 2 below.

[0057] Table 2 Score Table for the Decline Rate of Cruising Range

[0058]

[0059] When the decline rate of cruising range is ≤60% and ≥40%, the score is between 0 and 80 points, and it is calculated by the method of linear interpolation within the interval; when the decline rate of cruising range is ≤40% and ≥30%, the score is between 80 and 100 points, and it is calculated by the method of linear interpolation within the interval.

[0060] Score for the accuracy coefficient of cruising range: When the test indicators include CLTC-P low temperature cruising range test, CLTC-P high temperature cruising range test, normal temperature constant speed 120km / h cruising range test, low temperature constant speed 120km / h cruising range test or high temperature constant speed 120km / h cruising range test, the item score is calculated by Table 3 below.

[0061] Table 3 Score Table for the Accuracy Coefficient of Cruising Range

[0062]

[0063] When the cruising range accuracy coefficient is ≥ 0.40 and ≤ 0.99, the score is between 0 and 100 points, and the value within the range is calculated by the method of linear interpolation.

[0064] Step S6: Multiply and sum the weights of the cruising range feedback of each target vehicle under N test indicators to obtain the cruising range evaluation value of each target vehicle.

[0065] In this embodiment, the cruising range evaluation value is obtained by combining the results of the 4 test indicators determined in step S4, the scoring method given in step S5, and the corresponding weight product.

[0066] Step S7: Compare the cruising range evaluation values of all target vehicles, and prompt consumers to select the target vehicles whose cruising range evaluation values are greater than the set threshold; the calibrated cruising range of the target vehicles with cruising range evaluation values greater than the set threshold is true and reliable.

[0067] In this embodiment, the set threshold is 90.

[0068] In another exemplary embodiment, in order to verify the effectiveness of the above method for determining the cruising reliability of pure electric vehicles, this embodiment provides a practical application scenario of the method for determining the cruising reliability of pure electric vehicles, which is as follows.

[0069] First step, according to the regional characteristics of our country, in ten cities including Changchun, Hangzhou, Shanghai, Xiamen, Shenzhen, Sanya, Chongqing, Kunming, Wuhan, and Tianjin, 3 pure electric SUVs (models 1 - 3, 10 vehicles of each model are selected in each city) and 3 pure electric sedans (models 4 - 5, 10 vehicles of each model are selected in each city) are selected as test objects. The actual annual comprehensive energy consumption of each user is collected, the annual cumulative grid-end power consumption and the annual driving mileage of each user are statistically calculated, and the actual annual comprehensive power consumption of the corresponding models is calculated. The annual comprehensive power consumption of the 6 vehicles is as shown in Table 4 below.

[0070] Table 4 Summary Table of Annual Comprehensive Power Consumption

[0071]

[0072] Second step, in the laboratory, conduct CLTC-P normal temperature cruising range test, CLTC-P low temperature cruising range test, CLTC-P high temperature cruising range test, normal temperature constant speed 120km / h cruising range test, low temperature constant speed 120km / h cruising range test, and high temperature constant speed 120km / h cruising range test on the six vehicles respectively, and calculate the experimental energy consumption of each vehicle under each cruising range test.

[0073] Third step, record the annual comprehensive power consumption of the 6 vehicles as the first matrix A, record the experimental energy consumption of 6 vehicles under each cruising range test as the second matrix B , the second matrix B The first column in it represents the experimental energy consumption of 6 vehicles under the CLTC-P normal temperature cruising range test, the second column represents the experimental energy consumption of 6 vehicles under the CLTC-P low temperature cruising range test, the third column represents the experimental energy consumption of 6 vehicles under the CLTC-P high temperature cruising range test, the fourth column represents the experimental energy consumption of 6 vehicles under the normal temperature constant speed 120km / h cruising range test, the fifth column represents the experimental energy consumption of 6 vehicles under the low temperature constant speed 120km / h cruising range test, and the sixth column represents the experimental energy consumption of 6 vehicles under the high temperature constant speed 120km / h cruising range test.

[0074] .

[0075] .

[0076] Fourth step, calculate the Pearson correlation coefficients p=(0.96, 0.91, 0.69, 0.83, 0.76, 0.79) between the first matrix A and the second matrix B . Compare the magnitude relationships of the coefficients, select the 4 cruising range test items corresponding to the 4 highest coefficient values (which are the CLTC-P normal temperature cruising range test, the CLTC-P low temperature cruising range test, the CLTC-P high temperature cruising range test, and the normal temperature constant speed 120km / h cruising range test), use the above 4 cruising range tests as the 4 test indicators for calculating the subsequent cruising range evaluation value, and then determine the weight coefficients of the 4 test indicators to be 0.5, 0.2, 0.2, and 0.1 according to the proportion of the driving mileage (urban driving mileage and highway driving mileage) of vehicle users in different scenarios (spring, summer, autumn, winter).

[0077] Fifth step, conduct the CLTC-P normal temperature cruising range test, the CLTC-P low temperature cruising range test, the CLTC-P high temperature cruising range test, and the normal temperature constant speed 120km / h cruising range test on two models with relatively high sales volume on the laboratory drum respectively. The cruising range and energy consumption of the two models under different test indicators are shown in Tables 5 and 6 below.

[0078] Table 5 Data table of Model 1 under different test indicators

[0079]

[0080] Table 6 Data table of Model 2 under different test indicators

[0081]

[0082] Substitute the curb weight of vehicle model 1, 1732 kg, and the curb weight of vehicle model 2, 1870 kg, into the formula Y = 0.006×M + 8, and we get Y1 = 18.39 and Y2 = 19.22.

[0083] In addition, according to the scoring rules in step 5 above, determine the scores of the two vehicle models under different test indicators. The specific scores are shown in Tables 7 and 8 below.

[0084] Table 7 Score Table of Vehicle Model 1 under Different Test Indicators

[0085]

[0086] Table 8 Score Table of Vehicle Model 2 under Different Test Indicators

[0087]

[0088] Step 6: According to the above calculation results, determine the CLTC-P normal temperature power consumption with a weight ratio of 0.5; the CLTC-P low temperature cruising range with a weight of 0.2, where the weight of the cruising range decline rate score is 0.8 and the weight of the cruising range accuracy coefficient score is 0.2; for the CLTC-P high temperature cruising range, the weight is 0.2, where the weight of the cruising range decline rate score is 0.8 and the weight of the cruising range accuracy coefficient score is 0.2; the constant speed 120 km / h cruising range with a weight of 0.1, where the weight of the cruising range decline rate score is 0.8 and the weight of the cruising range accuracy coefficient score is 0.2. Finally, the calculated cruising range evaluation values S1 of vehicle model 1 and S2 of vehicle model 2 are as follows.

[0089] S1 = 81.7×0.5 + (71.56×0.8 + 55.93×0.2)×0.2 + (100×0.8 + 83.05×0.2)×0.2 + (22.67×0.8 + 72.8×0.2)×0.1 = 77.45.

[0090] S2 = 99.4×0.5 + (81.65×0.8 + 35.59×0.2)×0.2 + (100×0.8 + 86.44×0.2)×0.2 + (62.8×0.8 + 79.66×0.2)×0.1 = 90.26.

[0091] It can be seen that for consumers, in terms of the performance of battery life, they can make a judgment based on the driving range evaluation value of this application. The overall performance of Model 2 in terms of battery life is better than that of Model 1. Consumers who care about battery life performance can choose Model 2. In addition, if consumers have some specific driving scenarios and driving preferences, they can also make a judgment based on this application. For example, if consumers live in the north and are more sensitive to low-temperature battery life, then special attention should be paid to the score of low-temperature driving range; some consumers have more high-speed driving conditions in actual use scenarios, then special attention should be paid to the score of high-speed driving range. In addition, the vehicle manufacturer can evaluate the overall battery life performance of the vehicle according to this application, find the key points that cause consumers' dissatisfaction in terms of battery life, and improve the driving range evaluation value of the vehicle by optimizing the energy flow distribution, improving air conditioning technology and battery thermal management system, so as to obtain better market evaluation and increase sales volume.

[0092] In another exemplary embodiment, a computer system is provided. The computer system can be a server or a terminal, and its internal structure diagram can be as Figure 2 shown. The computer system includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer system is used to provide computing and control capabilities. The memory of the computer system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer system is used to exchange information between the processor and external devices. The communication interface of the computer system is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it is used to implement the method for determining the reliability of the battery life of a pure electric vehicle as described above.

[0093] Those skilled in the art can understand that Figure 2 the structure shown in

[0094] is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer system to which the solution of this application is applied. The specific computer system may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0095] In a scientific way, this application selects multiple pure electric vehicles of different types (sedans, SUVs) with the highest sales volume on the market as test objects, conducts a driving range test by designing composite test conditions with different temperatures and different working conditions, and combines the actual annual comprehensive energy consumption of users of the corresponding models to determine the four factors that have the greatest impact on the driving range as the test indicators for vehicle energy consumption and driving range and the weights between the indicators. Finally, according to the scores of the vehicle under each indicator, the weighted driving range evaluation value of the model is obtained, providing a scientific and objective basis for consumers to compare different models when choosing a car.

[0096] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the users or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0097] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0098] In each of the embodiments provided in the present application, the database involved may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a distributed database based on a blockchain, etc. In each of the embodiments provided in the present application, the processor may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., not limited thereto.

[0099] In this application, all actions of obtaining signals, information, or data are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where it is located and with the authorization given by the owner of the corresponding device.

[0100] The various embodiments in this specification are described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same or similar parts among the various embodiments, reference can be made to each other.

[0101] [[ID=⑨]]Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, based on the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation on the present application.

Claims

1. A method for determining the endurance reliability of a pure electric vehicle, characterized in that, The method for determining the cruising range reliability of a pure electric vehicle includes: Determine multiple target vehicles and calculate the actual annual comprehensive energy consumption of each target vehicle; the multiple target vehicles include pure electric vehicles of different models and different urban users; Conduct multiple cruising range tests on each target vehicle respectively and calculate the experimental energy consumption of each target vehicle under each cruising range test; Determine a first matrix based on the actual annual comprehensive energy consumption of all target vehicles, and determine a second matrix based on the experimental energy consumption of all target vehicles under different cruising range tests; Calculate the correlation coefficient between the first matrix and the second matrix, select the N cruising range tests with the highest correlation with the first matrix as N test indicators according to the correlation coefficient, and determine the weights of each test indicator; Calculate the cruising range feedback of each target vehicle under each test indicator; the cruising range feedback includes the cruising range decline rate and the cruising range accuracy coefficient; Perform the weighted product summation on the cruising range feedback of each target vehicle under N test indicators to obtain the cruising range evaluation value of each target vehicle; Compare the cruising range evaluation values of all target vehicles and prompt consumers to select the target vehicles whose cruising range evaluation values are greater than the set threshold; the calibrated cruising range of the target vehicles whose cruising range evaluation values are greater than the set threshold is truly reliable.

2. The method for determining the endurance reliability of a pure electric vehicle according to claim 1, wherein Calculate the actual annual comprehensive energy consumption of each target vehicle, specifically including: Obtain the actual road energy consumption data of each target vehicle; the actual road energy consumption data includes the annual cumulative power consumption at the grid end and the annual driving mileage; Based on the annual cumulative power consumption at the grid end and the annual driving mileage, calculate the actual annual comprehensive energy consumption of each target vehicle.

3. The method for determining the endurance reliability of a pure electric vehicle according to claim 2, wherein The calculation formula for the actual annual comprehensive energy consumption is: ； Wherein, is the actual annual comprehensive energy consumption of the i th target vehicle, is the annual cumulative power consumption of the i th target vehicle from the power grid, is the annual driving mileage of the i th target vehicle.

4. The method for determining the cruising reliability of a pure electric vehicle according to claim 1, wherein, The multiple cruising range tests include: CLTC-P normal temperature cruising range test, CLTC-P low temperature cruising range test, CLTC-P high temperature cruising range test, normal temperature constant speed 120km / h cruising range test, low temperature constant speed 120km / h cruising range test, and high temperature constant speed ១២០km / h cruising range test.

5. The method for determining the cruising reliability of a pure electric vehicle according to claim 1, wherein The calculation formula for the experimental energy consumption is: ； ； ； Wherein, is the experimental energy consumption of the i th target vehicle under the k th cruising range test, is the power consumption of the i th target vehicle under the k th cruising range test, is the start time of the k th cruising range test, is the end time of the k th cruising range test, is the battery pack current of the t th target vehicle at i time, is the battery pack voltage of the t th target vehicle at i time, is the cruising range of the i th target vehicle under the k th cruising range test, is the vehicle speed of the t th target vehicle at i time.

6. The method for determining the endurance reliability of a pure electric vehicle according to claim 1, characterized in that, The first matrix is: ； In the formula, A is the first matrix, is the i actual annual comprehensive energy consumption of the -th target vehicle.

7. The method for determining the endurance reliability of a pure electric vehicle according to claim 4, wherein The second matrix is: ； In the formula, B is the second matrix, is the i experimental energy consumption of the th target vehicle under the CLTC-P normal temperature endurance mileage test, i is the th target vehicle's experimental energy consumption under the CLTC-P low temperature endurance mileage test, i is the th target vehicle's experimental energy consumption under the CLTC-P high temperature endurance mileage test, i is the th target vehicle's experimental energy consumption under the normal temperature constant speed 120km / h endurance mileage test, i is the th target vehicle's experimental energy consumption under the low temperature constant speed 120km / h endurance mileage test, i is the th target vehicle's experimental energy consumption under the high temperature constant speed 120km / h endurance mileage test.

8. The method for determining the cruising reliability of a pure electric vehicle according to claim 1, wherein The calculation formula for the cruising range decline rate is: ； In the formula, is the decline rate of the cruising range of the i th target vehicle under the j th test index, is the cruising range of the i th target vehicle under the CLTC-P normal temperature cruising range test, is the cruising range of the i th target vehicle under the j th test index.

9. The method for determining the endurance reliability of a pure electric vehicle according to claim 1, wherein The calculation formula for the cruising range accuracy coefficient is: ； Wherein, is the cruising range accuracy coefficient of the i th target vehicle under the j th test index, is the actual remaining mileage of the i th target vehicle at the j th sampling point under the m th test index, is the indicated remaining mileage of the i th target vehicle at the j th sampling point under the m th test index, is the average value of the indicated remaining mileage of all sampling points of the i th target vehicle under the j th test index.

10. A computer system, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the cruising range reliability of a pure electric vehicle according to any one of claims 1-9.

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