A new energy vehicle endurance mileage management method and system

Abstract

The application relates to the field of new energy vehicles, and provides a new energy vehicle endurance mileage management method and system. A battery attenuation coefficient is obtained based on vehicle driving environment information, energy consumption parameters are obtained based on load, road surface and speed information, initial endurance mileage and initial endurance time are obtained in combination with real-time battery capacity; the attenuation battery capacity and the actual battery capacity are calculated and obtained according to the initial endurance time and the battery attenuation coefficient; the corrected endurance mileage is calculated and obtained according to the actual battery capacity and the driving energy consumption parameters, and the management scheme is obtained according to the charging station position in combination with the corrected endurance mileage. The technical problem that the endurance mileage management scheme of the new energy vehicle in the prior art does not have high consistency with the actual driving condition of the vehicle and the battery use condition, and the endurance management has low adaptability to the new energy vehicle is solved, the endurance management is realized according to the actual driving condition and the driving environment of the new energy vehicle, and the technical effect that the endurance management of the new energy vehicle and the vehicle adaptability are improved is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy vehicles, in particular to a new energy vehicle endurance mileage management method and system. BACKGROUND

[0002] With the continuous development of the new energy vehicle market, the endurance mileage problem has gradually become one of the focuses of consumers. In order to better manage the endurance performance of new energy vehicles, various manufacturers and research institutions are constantly exploring and researching new endurance management methods.

[0003] The most common new energy vehicle endurance management method at present is to dynamically manage the battery charging and discharging, automatically adjust the battery charging and discharging strategy according to the actual situation of the vehicle, and thereby maximize the service life of the battery and the endurance mileage of the vehicle.

[0004] The current new energy vehicle endurance management method tends to focus on multi-dimensional utilization of energy and battery charging and discharging control according to the driving conditions of new energy vehicles. There is currently no scheme for managing the endurance of new energy vehicles in combination with the driving environment of new energy vehicles.

[0005] In summary, the existing technology has the technical problem that the endurance mileage management scheme of new energy vehicles does not match the actual driving conditions and battery usage conditions of the vehicle, resulting in low adaptability of the endurance management strategy to new energy vehicles. SUMMARY

[0006] Therefore, it is necessary to provide a new energy vehicle endurance mileage management method and system that can realize endurance management according to the actual driving conditions and driving environment of new energy vehicles and improve the adaptability of new energy vehicle endurance management to the actual usage conditions of the vehicle.

[0007] A new energy vehicle endurance mileage management method, the method comprising: in response to an endurance mileage management instruction, collecting current real-time load information and travel information of a target vehicle, and current real-time battery capacity of a battery of the target vehicle, the target vehicle being a new energy vehicle; collecting a plurality of environmental information of an environment in which the target vehicle is currently located, obtaining an environmental information set, inputting the environmental information set into a battery attenuation analysis model, and obtaining a battery attenuation coefficient; inputting road surface information and speed information in the travel information into a travel energy consumption analysis model, obtaining travel energy consumption parameters, combining the real-time battery capacity, and calculating an initial endurance mileage and an initial endurance time; according to the initial endurance time and the battery attenuation coefficient, calculating an attenuation battery capacity of the battery within the initial endurance time, and calculating an actual battery capacity; according to the actual battery capacity and the travel energy consumption parameters, calculating a corrected endurance mileage; according to travel route information in the travel information, obtaining a charging station near the travel route information, combining the corrected endurance mileage, analyzing an endurance mileage management scheme, and displaying the endurance mileage management scheme.

[0008] A new energy vehicle endurance mileage management system, the system comprising: a management instruction response module for collecting current real-time load information and travel information of a target vehicle, and current real-time battery capacity of a battery of the target vehicle in response to an endurance mileage management instruction, the target vehicle being a new energy vehicle; an environmental information collection module for collecting a plurality of environmental information of an environment in which the target vehicle is currently located, obtaining an environmental information set, inputting the environmental information set into a battery attenuation analysis model, and obtaining a battery attenuation coefficient; an endurance data calculation module for inputting road surface information and speed information in the travel information into a travel energy consumption analysis model, obtaining travel energy consumption parameters, combining the real-time battery capacity, and calculating an initial endurance mileage and an initial endurance time; a battery capacity calculation module for calculating an attenuation battery capacity of the battery within the initial endurance time according to the initial endurance time and the battery attenuation coefficient, and calculating an actual battery capacity; an endurance mileage correction module for calculating a corrected endurance mileage according to the actual battery capacity and the travel energy consumption parameters; a management scheme generation module for obtaining a charging station near travel route information in the travel information, combining the corrected endurance mileage, analyzing an endurance mileage management scheme, and displaying the endurance mileage management scheme.

[0009] A computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0010] In response to the endurance mileage management instruction, current real-time load information and travel information of the target vehicle are collected, and current real-time battery capacity of the battery of the target vehicle is collected, the target vehicle being a new energy vehicle;

[0011] A plurality of environmental information of an environment in which the target vehicle is currently located is collected to obtain an environmental information set, and the environmental information set is input into a battery attenuation analysis model to obtain a battery attenuation coefficient;

[0012] The load information, road surface information and speed information in the travel information are input into a travel energy consumption analysis model to obtain travel energy consumption parameters, and the initial endurance mileage and the initial endurance time are calculated in combination with the real-time battery capacity;

[0013] The attenuation battery capacity of the battery within the initial endurance time is calculated according to the initial endurance time and the battery attenuation coefficient, and the actual battery capacity is calculated;

[0014] The corrected endurance mileage is calculated according to the actual battery capacity and the travel energy consumption parameters;

[0015] The charging stations near the travel route information are obtained according to the travel route information in the travel information, and the endurance mileage management scheme is analyzed and obtained in combination with the corrected endurance mileage, and is displayed.

[0016] A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the following steps:

[0017] In response to the endurance mileage management instruction, current real-time load information and travel information of the target vehicle are collected, and current real-time battery capacity of the battery of the target vehicle is collected, the target vehicle being a new energy vehicle;

[0018] A plurality of environmental information of an environment in which the target vehicle is currently located is collected to obtain an environmental information set, and the environmental information set is input into a battery attenuation analysis model to obtain a battery attenuation coefficient;

[0019] The load information, road surface information and speed information in the travel information are input into a travel energy consumption analysis model to obtain travel energy consumption parameters, and the initial endurance mileage and the initial endurance time are calculated in combination with the real-time battery capacity;

[0020] The attenuation battery capacity of the battery within the initial endurance time is calculated according to the initial endurance time and the battery attenuation coefficient, and the actual battery capacity is calculated;

[0021] The corrected endurance mileage is calculated according to the actual battery capacity and the travel energy consumption parameters;

[0022] According to the driving route information in the driving information, a charging station near the driving route information is obtained, a range management scheme is analyzed and obtained in combination with the corrected range, and is displayed.

[0023] The new energy vehicle range management method and system solve the technical problem that the range management scheme of the new energy vehicle does not match the actual driving condition and the battery usage condition, resulting in low adaptation of the range management strategy to the new energy vehicle, and achieve the technical effect of range management according to the actual driving condition and the driving environment of the new energy vehicle, and improve the adaptation of the range management of the new energy vehicle to the actual usage condition of the vehicle.

[0024] The above description is only a summary of the technical solutions of the present application, in order to more clearly understand the technical means of the present application, and can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 It is a flowchart of a new energy vehicle range management method in one embodiment;

[0026] Figure 2 It is a flowchart of analyzing and obtaining a range management scheme in a new energy vehicle range management method in one embodiment;

[0027] Figure 3 It is a structural block diagram of a new energy vehicle range management system in one embodiment;

[0028] Figure 4 It is an internal structure diagram of a computer device in one embodiment.

[0029] Explanation of reference signs: management instruction response module 1, environment information acquisition module 2, range data calculation module 3, battery capacity calculation module 4, range correction module 5, management scheme generation module 6. DETAILED DESCRIPTION

[0030] In order to make the purposes, technical solutions and advantages of the present application more clear and obvious, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0031] As shown in Figure 1 The present application provides a new energy vehicle range management method, which comprises:

[0032] S100: collecting real-time load information and real-time driving information of the target vehicle, and collecting real-time battery capacity of the battery of the target vehicle in response to the endurance mileage management instruction, the target vehicle being a new energy vehicle;

[0033] In one embodiment, real-time load information and real-time driving information of the target vehicle are collected in response to the endurance mileage management instruction, and real-time battery capacity of the battery of the target vehicle is collected. The endurance mileage management instruction can be an instruction that is periodically and automatically executed, for example, executed every 10 minutes based on the vehicle control computer, or executed by a user of the target vehicle by triggering the "endurance mileage management" function. The method step S100 provided in the present application further comprises:

[0034] S110: collecting real-time load information of the target vehicle, and calculating the load information in combination with full load information of the target vehicle;

[0035] S120: collecting road surface information of a current driving road of the target vehicle;

[0036] S130: collecting driving route information and speed information of the target vehicle, and obtaining the driving information in combination with the road surface information;

[0037] S140: collecting real-time battery capacity of the battery of the target vehicle.

[0038] Specifically, in the present embodiment, the target vehicle is a new energy vehicle. The load information is real-time load of the target vehicle, and the driving information specifically includes speed information of real-time speed data of the target vehicle and road surface information representing road slope and road friction of the target vehicle. The real-time battery capacity is the remaining battery capacity of the target vehicle, for example, 75% battery capacity.

[0039] It should be understood that the power system of the new energy vehicle is powered by the battery, and the energy reserve of the battery is limited. Therefore, the energy consumption of the new energy vehicle is related to the load of the vehicle, and the endurance mileage of the new energy vehicle is affected by the load of the vehicle. The greater the load of the vehicle, the more energy is consumed to drive the vehicle, resulting in a decrease in the endurance mileage of the vehicle. When the new energy vehicle climbs or descends, more energy is consumed to maintain stable driving on a road section with small road friction (such as muddy road surface, slippery road surface, etc.), which will result in a decrease in the endurance mileage.

[0040] Thus, the embodiment generates the endurance mileage management instruction, sends the endurance mileage management instruction to an ECU (engine control unit) to obtain the current real-time battery capacity of the battery of the target vehicle, vehicle speed information, and the current real-time load information of the target vehicle, calls the full load load information of the target vehicle, the full load load information is the upper limit of the load for safe driving of the target vehicle, calculates the ratio based on the full load load information and the real-time load information to obtain the load information.

[0041] The endurance mileage management instruction is sent to a vehicle-mounted camera management system or through a level system to obtain the road slope and road friction information of the target vehicle. The vehicle driving road slope, road friction information and vehicle speed information are integrated to generate the driving information of the target vehicle.

[0042] S200: Collecting a plurality of environmental information of the target vehicle in the current environment, obtaining an environmental information set, inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient;

[0043] In one embodiment, a plurality of environmental information of the target vehicle in the current environment is collected, an environmental information set is obtained, the environmental information set is input into a battery attenuation analysis model to obtain a battery attenuation coefficient, and the method provided in the application further includes:

[0044] S210: Collecting temperature information and temperature information of the target vehicle in the current environment to obtain the environmental information set;

[0045] S210: Obtaining a sample temperature information set and a sample humidity information set, and combining to obtain a plurality of sample environmental information sets;

[0046] S220: Under the plurality of sample environmental information sets, performing battery attenuation coefficient test on the battery of the target vehicle to obtain a sample battery attenuation coefficient set;

[0047] S230: Using the plurality of sample environmental information sets and the sample battery attenuation coefficient set to construct the battery attenuation analysis model, the battery attenuation analysis model includes an analysis coordinate system and a plurality of sample coordinate points, each sample coordinate point is marked by a corresponding sample battery attenuation coefficient;

[0048] S240: Inputting the environmental information set into the battery attenuation analysis model to obtain a real-time coordinate point, obtaining K sample coordinate points closest to the real-time coordinate point, K being an odd number greater than or equal to 3;

[0049] S250: Obtaining K sample battery attenuation coefficients marked by the K sample coordinate points, and taking the sample battery attenuation coefficient with the highest frequency as the battery attenuation coefficient.

[0050] In one embodiment, the battery attenuation analysis model is constructed by using the plurality of sample environment information sets and the sample battery attenuation coefficient set, and the method provided in the present application further includes the following steps S230:

[0051] S231: Based on the ambient temperature and the ambient humidity, a horizontal coordinate axis and a vertical coordinate axis perpendicular to each other in the analysis coordinate system are constructed.

[0052] S232: The plurality of sample environment information sets are input into the analysis coordinate system to obtain a plurality of sample coordinate points.

[0053] S233: A plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set are used as a plurality of markers to mark the plurality of sample coordinate points to obtain the battery attenuation analysis model.

[0054] Specifically, it should be understood that high temperature can accelerate the speed of chemical reactions in the battery, cause corrosion and damage to the electrolyte and electrode materials inside the battery, and thus affect the performance and service life of the battery, and low temperature can reduce the discharge capacity of the battery, thereby reducing the cruising range of the battery. The electrolyte and electrode materials inside the battery are prone to moisture damage in a humid environment, thereby affecting the performance and service life of the battery and reducing the cruising range of the battery.

[0055] Therefore, the battery attenuation coefficient is obtained based on the analysis of the ambient temperature and humidity of the target vehicle, and the battery attenuation coefficient reflects the percentage of the battery capacity in the unit time that is affected by the environment and is not converted into kinetic energy of the vehicle to offset the impact of high temperature and high humidity on the battery. For example, the battery attenuation coefficient of 2.7% represents that 2.7% of the total battery capacity is lost to offset the impact of ambient temperature and humidity.

[0056] Since the ambient temperature and humidity of the target vehicle change little, the temperature information and the temperature information of the current environment of the target vehicle are collected to obtain the environment information set, which represents the ambient temperature and humidity of the target vehicle.

[0057] Based on the analysis of the ambient temperature and humidity information, the battery attenuation coefficient of the battery of the target vehicle is determined. To ensure the accuracy of the obtained battery attenuation coefficient, the battery attenuation analysis model is constructed, and the data analysis of the environment information set is performed based on the battery attenuation analysis model instead of manual experience, so as to improve the accuracy of the obtained battery attenuation coefficient.

[0058] The method for constructing the battery attenuation analysis model is as follows:

[0059] A plurality of sample batteries of the same model as the target automobile battery are obtained, sample temperature information and sample humidity information of the plurality of sample batteries are set, the sample temperature information of the plurality of sample batteries is integrated to obtain a sample temperature information set, the sample humidity information of the plurality of sample batteries is integrated to obtain a sample humidity information set, and the sample humidity information set and the sample temperature information set are combined to obtain a plurality of sample environment information sets.

[0060] While controlling other variables to be constant, the environmental temperature and the environmental humidity are changed singly to implement charging and discharging control of the plurality of sample batteries under the environmental temperature-environmental humidity combinations of the plurality of sample environment information sets, the plurality of sample batteries of the target automobile are subjected to attenuation coefficient testing, a sample battery attenuation coefficient set corresponding to the plurality of sample batteries is obtained, and each sample battery attenuation coefficient corresponds to a set of sample humidity information-sample temperature information.

[0061] Based on the environmental temperature and the environmental humidity, the analysis coordinate system is constructed, the analysis coordinate system is a two-dimensional analysis coordinate system, the horizontal coordinate axis X in the analysis coordinate system is the environmental temperature, and the vertical coordinate axis Y is the environmental humidity.

[0062] The set of sample humidity information-sample temperature information corresponding to the first sample battery attenuation coefficient is filled into the constructed two-dimensional analysis coordinate system, the intersection of the set of sample humidity information-sample temperature information in the two-dimensional analysis coordinate system is taken as a sample coordinate point of the set of data, and the first sample battery attenuation coefficient is marked.

[0063] The first sample battery attenuation coefficient and the set of sample humidity information-sample temperature information corresponding thereto are filled in the analysis coordinate system by using the same filling method, a plurality of sample coordinate points are constructed based on the plurality of sample environment information sets and the sample battery attenuation coefficient set, each sample coordinate point is marked by a corresponding sample battery attenuation coefficient, and the construction of the battery attenuation analysis model is completed.

[0064] The environmental information set is input into the battery attenuation analysis model to obtain a real-time coordinate point, the real-time coordinate point is a coordinate point obtained by intersecting the temperature information and the temperature information data of the current environment of the target automobile in the analysis coordinate system of the battery attenuation analysis model.

[0065] Based on the real-time coordinate point, K sample coordinate points closest to the real-time coordinate point are obtained, K is an odd number greater than or equal to 3, K sample battery attenuation coefficients marked by the K sample coordinate points are obtained, the K sample battery attenuation coefficients are subjected to frequency statistics, and the sample battery attenuation coefficient with the highest frequency is taken as the battery attenuation coefficient.

[0066] The embodiment realizes obtaining the battery attenuation coefficient which scientifically and accurately reflects the maximum capacity attenuation of the target automobile battery by constructing a battery attenuation analysis model and obtaining the temperature information of the current environment of the target automobile battery, thereby providing a technical effect of providing update data reference for subsequent updating of the capacity of the target automobile battery.

[0067] S300: inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, combining the real-time battery capacity to calculate and obtain initial cruising range and initial cruising time;

[0068] In one embodiment, the load information, the road surface information and the speed information in the driving information are input into a driving energy consumption analysis model to obtain driving energy consumption parameters, and the real-time battery capacity is combined to calculate and obtain initial cruising range and initial cruising time. The method provided in the application further comprises the following steps:

[0069] S310: obtaining a sample load information set, a sample road surface information set and a sample speed information set of the target automobile;

[0070] S320: combining data in the sample load information set, the sample road surface information set and the sample speed information set, and performing driving energy consumption test detection on the target automobile to obtain a sample driving energy consumption parameter set;

[0071] S330: randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample driving energy consumption parameter set with replacement to obtain a first construction data set, M being an integer greater than 1 and less than the number of the sample load information set;

[0072] S340: constructing a first driving energy consumption analysis unit in the driving energy consumption analysis model based on a BP neural network using the first construction data set;

[0073] S350: again randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample driving energy consumption parameter set with replacement to obtain a second construction data set,

[0074] S360: constructing a second driving energy consumption analysis unit in the driving energy consumption analysis model based on a BP neural network using the second construction data set;

[0075] S370: continuing to construct N-2 driving energy consumption analysis units in the driving energy consumption analysis model, N being an integer greater than 3, and obtaining the driving energy consumption analysis model according to the N driving energy consumption analysis units;

[0076] S380: input the load information and the driving information into the N driving energy consumption analysis units, obtain N output results, and take the one with the highest frequency in the N output results as the driving energy consumption parameter.

[0077] Specifically, in the embodiment, the load range of the target vehicle is obtained, the speed range is obtained, T sample load information is set based on the load range, the sample load information set is formed, K sample speed information is set based on the speed range, the sample speed information set is formed, and W sets of road slope and road friction data are set, and the sample road information set is formed. T, K, and W are positive integers greater than 100.

[0078] The data in the sample load information set, the sample road information set, and the sample speed information set are randomly arranged and combined without repetition to obtain a plurality of sets of sample speed, sample load, sample road slope, and sample road friction data.

[0079] The variables such as temperature and humidity are controlled to be fixed, the initial performance state of the target vehicle is controlled to be consistent, the driving distance of the target vehicle is controlled to be consistent, and a plurality of target sample vehicles with consistent initial performance states are subjected to driving energy consumption test detection based on a plurality of sets of sample speed, sample load, sample road slope, and sample road friction data. A sample driving energy consumption parameter set is obtained, the sample driving energy consumption parameter set includes a plurality of sample driving energy consumption data mapped from a plurality of sets of sample speed, sample load, sample road slope, and sample road friction data, and the driving energy consumption data is the battery power consumption of the target vehicle per unit distance under the condition of a certain speed, load, road slope, and road friction.

[0080] M sets of data are randomly selected from the sample load information set, the sample road information set, the sample speed information set, and the sample driving energy consumption parameter set with replacement, and M sample driving energy consumptions corresponding to the M sets of data are obtained in the sample driving energy consumption set. The M sample driving energy consumptions of the M sets of data are taken as the first constructed data set, and M is an integer greater than 1 and less than the number of the sample load information set.

[0081] In the embodiment, the driving energy consumption analysis model includes an input layer, a data analysis layer, and an output layer. The data analysis layer is N driving energy consumption analysis units that run in parallel and do not interfere with each other. The embodiment takes constructing and training the first driving energy consumption analysis unit as an example to describe the construction and training method of N driving energy consumption analysis units that run in parallel and do not interfere with each other.

[0082] Based on the BP neural network, a first driving energy consumption analysis unit in the driving energy consumption analysis model is constructed, the input data of the first driving energy consumption analysis unit is the vehicle speed, load, driving road slope and road friction data, and the output result is the driving energy consumption data.

[0083] The first construction data set identification is divided into a training set, a test set and a validation set, the training of the first driving energy consumption analysis unit is carried out based on the training set and the test set, the validation of the output result accuracy of the first driving energy consumption analysis unit is carried out based on the validation set, and when the output accuracy of the first driving energy consumption analysis unit is higher than 97%, the training of the first driving energy consumption analysis unit is stopped.

[0084] Again, M groups of data are randomly selected from the sample load information set, the sample road information set, the sample speed information set and the sample driving energy consumption parameter set, respectively, to obtain a second construction data set, the second construction data set is divided into data set identification by using the same processing method as the first construction data set, and the second driving energy consumption analysis unit is constructed and trained by using the first driving energy consumption analysis unit construction and training method.

[0085] The same construction and training method of the first driving energy consumption analysis unit and the second driving energy consumption analysis unit is used to construct N-2 driving energy consumption analysis units in the driving energy consumption analysis model, N is an integer greater than 3, and the data analysis layer of the driving energy consumption analysis model is generated based on the parallel arrangement of N driving energy consumption analysis units, the input layer and the output layer are set, and the construction of the driving energy consumption analysis model is completed.

[0086] The load information and the driving information are input into the N driving energy consumption analysis units through the input layer of the driving energy consumption analysis model, the load information and the driving information are analyzed and processed based on the N driving energy consumption analysis units, N output results are obtained, the N output results are N driving energy consumption data, and the driving energy consumption parameter with the highest frequency in the N output results is taken as the driving energy consumption parameter, which is the battery power consumption of the target vehicle per unit distance under the conditions of the target vehicle speed, load, road slope and road friction corresponding to the load information and the driving information.

[0087] Further, the real-time battery capacity of the target vehicle is obtained based on the ECU (engine control unit), the driving distance of the target vehicle under the real-time battery capacity is calculated based on the real-time battery capacity and the driving energy consumption parameter, which represents the target vehicle speed, load, road slope and road friction corresponding to the load information and the driving information, and the initial cruising range is generated, and the initial cruising time is calculated based on the initial cruising range and the vehicle speed.

[0088] This embodiment constructs a driving energy consumption analysis model with multiple driving energy consumption analysis units. Based on the target vehicle's load information and driving information, it performs data analysis to obtain highly accurate and reliable driving energy consumption parameters of the target vehicle, as well as the technical effect of reflecting the target vehicle's initial driving range and initial driving time under real-time battery capacity.

[0089] S400: Based on the initial driving time and the battery degradation coefficient, calculate the battery capacity degradation during the initial driving time, and calculate the actual battery capacity.

[0090] S500: Calculate the corrected driving range based on the actual battery capacity and the driving energy consumption parameters;

[0091] Specifically, in this embodiment, the battery degradation coefficient, the initial driving time, and the real-time battery capacity are multiplied to obtain the degradation battery capacity of the target vehicle. The degradation battery capacity is the amount of charge lost by the target vehicle's battery during the initial driving time to offset the effects of ambient temperature and humidity.

[0092] The difference between the degraded battery capacity and the real-time battery capacity is calculated to obtain the actual battery capacity, which reflects the current battery capacity of the target vehicle and is applicable to powering the vehicle's operation. Based on the actual battery capacity and the driving energy consumption parameters, a corrected driving range is calculated, which is the distance the target vehicle can travel supported by its current battery capacity.

[0093] S600: Based on the driving route information in the driving information, obtain the charging stations near the driving route information, combine the corrected driving range, analyze and obtain the driving range management scheme, and display it.

[0094] In one embodiment, such as Figure 2 As shown, based on the driving route information in the driving information, charging stations near the driving route information are obtained. Combined with the corrected driving range, a driving range management scheme is obtained and displayed. The method step S600 of this application also includes:

[0095] S610: Obtain the critical driving range, and combine the driving route information and the corrected driving range to obtain the critical position;

[0096] S620: Obtain multiple charging stations within a preset range of the critical position, and multiple distance information between the multiple charging stations and the critical position;

[0097] S630: Based on the multiple distance information, formulate multiple display schemes;

[0098] S640: display the plurality of charging stations and the plurality of distance information by using the plurality of display schemes, and display the corrected range.

[0099] In one embodiment, according to the plurality of distance information, a plurality of display schemes are formulated, and the method provided in the present application further includes the following steps:

[0100] S631: obtain a plurality of order information sorted in ascending order of distance information;

[0101] S632: according to the plurality of order information, construct a plurality of sample display schemes;

[0102] S633: sort the plurality of distance information in ascending order to obtain a plurality of real-time order information, and obtain a plurality of sample display schemes as the plurality of display schemes.

[0103] Specifically, in the present embodiment, the critical range is the distance that the vehicle can travel from the critical power level to the depletion of the target power level. The critical range can be set according to the density of new energy vehicle charging stations in the city, and the numerical value of the critical range is not limited in the present embodiment, which can be set according to the actual city charging station infrastructure.

[0104] In the present embodiment, the critical range is obtained, and the critical position is obtained in combination with the driving route information and the corrected range. The critical position is the specific position of the target vehicle on the driving route when driving to the critical range on the driving route.

[0105] The preset range is a circle with the critical position as the center and the range difference between the critical range and the corrected range as the radius. A plurality of charging stations within the preset range of the critical position and a plurality of distance information between the plurality of charging stations and the critical position are obtained, and a plurality of display schemes are formulated according to the plurality of distance information.

[0106] In the present embodiment, the scheme generation method of the plurality of display schemes is as follows:

[0107] A plurality of sample display schemes are constructed, each sample display scheme including a charging station and distance information between the charging station and the critical position. The sorting rule of the plurality of distance information of the plurality of charging stations is to sort in ascending order of distance information.

[0108] In the embodiment, the plurality of distance information is sorted in ascending order of distance, and a plurality of order information corresponding to the plurality of distance information is generated. In the plurality of order information, the earlier the ranking is, the smaller the distance data is, that is, the closer the charging station and the critical position are.

[0109] In ascending order, the plurality of distance information is sorted to obtain a plurality of real-time order information, which is the sorting order of the plurality of distances, that is, the priority of the plurality of charging stations. Based on the plurality of real-time order information, a plurality of distance information corresponding to the plurality of distance information and a plurality of sample display schemes corresponding to the plurality of distance information are obtained as the plurality of display schemes.

[0110] Based on the plurality of display schemes, the target automobile driver can intuitively know that the target automobile needs to be charged when reaching the critical position, and the priority of the plurality of charging stations available at the critical position.

[0111] The embodiment realizes the management of the cruising range of the new energy automobile according to the actual driving condition and the driving environment of the new energy automobile, improves the adaptation of the cruising range management of the new energy automobile and the actual use condition of the vehicle, and facilitates the target automobile driver to select the charging station for power supply.

[0112] In one embodiment, as shown in Figure 3 A new energy automobile cruising range management system is provided, which comprises a management instruction response module 1, an environment information acquisition module 2, a cruising data calculation module 3, a battery capacity calculation module 4, a cruising range correction module 5, and a management scheme generation module 6, wherein:

[0113] The management instruction response module 1 is used to respond to the cruising range management instruction, acquire the current real-time load information and driving information of the target automobile, and acquire the current real-time battery capacity of the battery of the target automobile, wherein the target automobile is a new energy automobile;

[0114] The environment information acquisition module 2 is used to acquire a plurality of environment information of the environment in which the target automobile is currently located, obtain an environment information set, input the environment information set into a battery attenuation analysis model, and obtain a battery attenuation coefficient;

[0115] The cruising data calculation module 3 is used to input the load information, road surface information and speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and combine the real-time battery capacity to calculate an initial cruising range and an initial cruising time;

[0116] The battery capacity calculation module 4 is used to calculate the attenuation battery capacity of the battery within the initial cruising time according to the initial cruising time and the battery attenuation coefficient, and calculate the actual battery capacity.

[0117] a cruising range correction module 5, configured to calculate a corrected cruising range according to the actual battery capacity and the energy consumption parameter of driving;

[0118] a management scheme generation module 6, configured to obtain charging stations near the driving route information in the driving information according to the driving route information, analyze a cruising range management scheme in combination with the corrected cruising range, and display the cruising range management scheme.

[0119] In an embodiment, the system further comprises:

[0120] a load information calculation unit, configured to collect real-time load information of the target vehicle, and calculate the load information in combination with full load information of the target vehicle;

[0121] a road surface information collection unit, configured to collect road surface information of a current driving road of the target vehicle;

[0122] a driving information obtaining unit, configured to collect driving route information and speed information of a current driving road of the target vehicle, and obtain the driving information in combination with the road surface information;

[0123] a battery capacity collection unit, configured to collect real-time battery capacity of a battery of the target vehicle.

[0124] In an embodiment, the system further comprises:

[0125] an environment information collection unit, configured to collect temperature information and humidity information of an environment in which the target vehicle is currently located, and obtain the environment information set;

[0126] a sample data obtaining unit, configured to obtain a sample temperature information set and a sample humidity information set, and combine to obtain a plurality of sample environment information sets;

[0127] a decay coefficient obtaining unit, configured to perform decay coefficient testing on the battery of the target vehicle under the plurality of sample environment information sets, and obtain a sample battery decay coefficient set;

[0128] a model construction execution unit, configured to construct the battery decay analysis model by using the plurality of sample environment information sets and the sample battery decay coefficient set, the battery decay analysis model comprising an analysis coordinate system and a plurality of sample coordinate points, each sample coordinate point being marked by a corresponding sample battery decay coefficient;

[0129] a model analysis execution unit, configured to input the environment information set into the battery decay analysis model, obtain a real-time coordinate point, and obtain K sample coordinate points nearest to the real-time coordinate point, K being an odd number greater than or equal to 3;

[0130] The attenuation coefficient generation unit is configured to obtain K sample battery attenuation coefficients marked by the K sample coordinate points, and take a sample battery attenuation coefficient with the highest frequency of occurrence as the battery attenuation coefficient.

[0131] In one embodiment, the system further comprises:

[0132] The coordinate assignment execution unit is configured to construct a horizontal coordinate axis and a vertical coordinate axis perpendicular to each other in the analysis coordinate system based on the ambient temperature and the ambient humidity.

[0133] The coordinate site generation unit is configured to input the plurality of sample ambient information sets into the analysis coordinate system to obtain the plurality of sample coordinate points.

[0134] The coordinate site marking unit is configured to mark the plurality of sample coordinate points with a plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set as a plurality of markers to obtain the battery attenuation analysis model.

[0135] In one embodiment, the system further comprises:

[0136] The sample information acquisition unit is configured to obtain a sample load information set, a sample road surface information set, and a sample speed information set of the target vehicle.

[0137] The test detection execution unit is configured to combine data in the sample load information set, the sample road surface information set, and the sample speed information set, and perform a driving energy consumption test detection on the target vehicle to obtain a sample driving energy consumption parameter set.

[0138] The data set construction unit is configured to randomly select M groups of data from the sample load information set, the sample road surface information set, the sample speed information set, and the sample driving energy consumption parameter set with replacement to obtain a first construction data set, M being an integer greater than 1 and less than the number of the sample load information set.

[0139] The analysis unit construction unit is configured to use the first construction data set to construct a first driving energy consumption analysis unit in the driving energy consumption analysis model based on a BP neural network.

[0140] The data set construction generation unit is configured to randomly select M groups of data from the sample load information set, the sample road surface information set, the sample speed information set, and the sample driving energy consumption parameter set with replacement again to obtain a second construction data set.

[0141] The analysis unit generation unit is configured to use the second construction data set to construct a second driving energy consumption analysis unit in the driving energy consumption analysis model.

[0142] The analysis model generating unit is configured to continue to construct N-2 driving energy consumption analysis units in the driving energy consumption analysis model, N being an integer greater than 3, and obtain the driving energy consumption analysis model according to the N driving energy consumption analysis units.

[0143] The energy consumption parameter obtaining unit is configured to input the load information and the driving information into the N driving energy consumption analysis units, obtain N output results, and take the one with the highest frequency as the driving energy consumption parameter.

[0144] In an embodiment, the system further comprises:

[0145] The critical position obtaining unit is configured to obtain a critical cruising range, and obtain a critical position in combination with the driving route information and the corrected cruising range.

[0146] The distance information obtaining unit is configured to obtain a plurality of charging stations within a preset range of the critical position, and a plurality of distance information between the plurality of charging stations and the critical position.

[0147] The display scheme customizing unit is configured to customize a plurality of display schemes according to the plurality of distance information.

[0148] The information display executing unit is configured to display the plurality of charging stations and the plurality of distance information by using the plurality of display schemes, and display the corrected cruising range.

[0149] In an embodiment, the system further comprises:

[0150] The order information generating unit is configured to obtain a plurality of order information sorted in ascending order of distance information.

[0151] The display scheme constructing unit is configured to construct a plurality of sample display schemes according to the plurality of order information.

[0152] The display scheme obtaining unit is configured to sort the plurality of distance information in ascending order, obtain a plurality of real-time order information, and obtain a plurality of sample display schemes as the plurality of display schemes.

[0153] For specific embodiments of the new energy vehicle cruising range management system, reference can be made to the embodiments of the new energy vehicle cruising range management method described above, which will not be repeated here. Each module in the new energy vehicle cruising range management system described above can be realized by software, hardware, or a combination thereof, in whole or in part. Each module described above can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0154] In one embodiment, a computer device, which can be a server, has an internal structure diagram as shown in Figure 4 The computer device includes a processor, a memory and a network interface connected by a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device 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 running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store news data and time decay factors and the like. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement a new energy vehicle range management method.

[0155] Those skilled in the art can understand that Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0156] In one embodiment, a computer readable storage medium is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps: in response to a range management instruction, collecting current real-time load information and driving information of a target vehicle, and current real-time battery capacity of a battery of the target vehicle, the target vehicle being a new energy vehicle; collecting a plurality of environmental information of an environment in which the target vehicle is currently located, obtaining an environmental information set, inputting the environmental information set into a battery decay analysis model, and obtaining a battery decay coefficient; inputting the load information, road surface information and speed information in the driving information into a driving energy consumption analysis model, obtaining driving energy consumption parameters, combining the real-time battery capacity, and calculating an initial range and an initial range time; according to the initial range time and the battery decay coefficient, calculating the decay battery capacity of the battery within the initial range time, and calculating the actual battery capacity; according to the actual battery capacity and the driving energy consumption parameters, calculating a corrected range; according to the driving route information in the driving information, obtaining a charging station near the driving route information, combining the corrected range, analyzing a range management scheme, and displaying the range management scheme.

[0157] Any combination of the technical features in the above embodiments can be made, and for the sake of brevity, not all possible combinations are described above, however, as long as the combination of the technical features does not exist in contradiction, it shall be considered within the scope of the present disclosure.

[0158] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it shall not be understood as a limitation on the patent scope of the present application. It shall be pointed out that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, and these shall be within the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A new energy vehicle endurance distance management method, characterized in that, The method comprises: In response to the endurance mileage management instruction, collecting current real-time load information and travel information of the target automobile, and current real-time battery capacity of the battery of the target automobile, the target automobile being a new energy automobile; Collecting a plurality of environmental information of the environment in which the target automobile is currently located to obtain an environmental information set, and inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient, comprising: Collecting temperature information of the environment in which the target automobile is currently located to obtain the environmental information set; Obtaining a sample temperature information set and a sample humidity information set, and combining to obtain a plurality of sample environmental information sets; Under the plurality of sample environmental information sets, testing the battery of the target automobile for a battery attenuation coefficient to obtain a sample battery attenuation coefficient set; Using the plurality of sample environmental information sets and the sample battery attenuation coefficient set, constructing the battery attenuation analysis model, the battery attenuation analysis model comprising an analysis coordinate system and a plurality of sample coordinate points, each sample coordinate point being marked by a corresponding sample battery attenuation coefficient; Inputting the environmental information set into the battery attenuation analysis model to obtain a real-time coordinate point, obtaining K sample coordinate points nearest to the real-time coordinate point, K being an odd number greater than or equal to 3; Obtaining K sample battery attenuation coefficients marked by the K sample coordinate points, and taking the sample battery attenuation coefficient with the highest frequency of occurrence as the battery attenuation coefficient; Inputting the load information, road surface information and speed information in the travel information into a travel energy consumption analysis model to obtain a travel energy consumption parameter, combining the real-time battery capacity to calculate an initial endurance mileage and an initial endurance time, wherein obtaining the travel energy consumption parameter comprises: Obtaining a sample load information set, a sample road surface information set and a sample speed information set of the target automobile; Combining data in the sample load information set, the sample road surface information set and the sample speed information set, and performing a travel energy consumption test on the target automobile to obtain a sample travel energy consumption parameter set; Randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample travel energy consumption parameter set with replacement to obtain a first construction data set, M being an integer greater than 1 and less than the number of the sample load information set; Using the first construction data set, constructing a first travel energy consumption analysis unit in the travel energy consumption analysis model based on a BP neural network; Randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample travel energy consumption parameter set with replacement again to obtain a second construction data set, Using the second construction data set, constructing a second travel energy consumption analysis unit in the travel energy consumption analysis model; Continuing to construct N-2 travel energy consumption analysis units in the travel energy consumption analysis model, N being an integer greater than 3, and obtaining the travel energy consumption analysis model according to the N travel energy consumption analysis units; Input the load information and the travel information into the N travel energy consumption analysis units to obtain N output results, and take the output result with the highest frequency as the travel energy consumption parameter; According to the initial endurance time and the battery attenuation coefficient, the decay battery capacity of the battery within the initial endurance time is calculated and obtained, and the actual battery capacity is calculated and obtained; According to the actual battery capacity and the travel energy consumption parameter, the corrected endurance mileage is calculated and obtained; According to the travel route information in the travel information, the charging stations near the travel route information are obtained, and the corrected endurance mileage is combined to analyze and obtain the endurance mileage management scheme for display.

2. The method of claim 1, wherein, In response to the endurance mileage management instruction, the current real-time load information and travel information of the target vehicle, and the current real-time battery capacity of the battery of the target vehicle are collected, including: The current real-time load information of the target vehicle is collected, and the load information is calculated and obtained in combination with the full load information of the target vehicle; The road surface information of the current travel road of the target vehicle is collected; The travel route information and speed information of the current travel of the target vehicle are collected, and the travel information is obtained in combination with the road surface information; The current real-time battery capacity of the battery of the target vehicle is collected.

3. The method of claim 1, wherein, The battery attenuation analysis model is constructed by using the plurality of sample environment information sets and the sample battery attenuation coefficient set, including: Based on the environmental temperature and the environmental humidity, the horizontal coordinate axis and the vertical coordinate axis perpendicular to each other in the analysis coordinate system are constructed; The plurality of sample environment information sets are input into the analysis coordinate system to obtain the plurality of sample coordinate points; A plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set are used as a plurality of markers to mark the plurality of sample coordinate points to obtain the battery attenuation analysis model.

4. The method of claim 1, wherein, According to the travel route information in the travel information, a plurality of position information of a plurality of charging stations within a predetermined range of the travel route information is obtained, and the corrected endurance mileage is combined to analyze and obtain the endurance mileage management scheme, including: A critical endurance mileage is obtained, and the critical position is obtained in combination with the travel route information and the corrected endurance mileage; A plurality of charging stations within a predetermined range of the critical position and a plurality of distance information of the plurality of charging stations from the critical position are obtained; According to the plurality of distance information, a plurality of display schemes are developed; The plurality of charging stations and the plurality of distance information are displayed by using the plurality of display schemes, and the corrected endurance mileage is displayed.

5. The method of claim 4, wherein, According to the plurality of distance information, a plurality of display schemes are developed, including: A plurality of order information sorted in ascending order of distance information is obtained; According to the plurality of order information, a plurality of corresponding sample display schemes are constructed; The plurality of distance information is sorted in ascending order to obtain a plurality of real-time order information, and a plurality of corresponding sample display schemes are obtained as the plurality of display schemes.

6. A new energy vehicle endurance mileage management system, characterized in that, The system comprises: The management instruction response module is configured to collect current real-time load information and travel information of the target vehicle and current real-time battery capacity of the battery of the target vehicle in response to the endurance mileage management instruction, and the target vehicle is a new energy vehicle; The environmental information collection module is configured to collect various environmental information of an environment in which the target vehicle is currently located, obtain an environmental information set, and input the environmental information set into the battery attenuation analysis model to obtain a battery attenuation coefficient; The environmental information collection module further includes: An environmental information collection unit is configured to collect temperature information and temperature information of an environment in which the target vehicle is currently located, and obtain the environmental information set; A sample data acquisition unit is configured to acquire a sample temperature information set and a sample humidity information set, and combine to obtain a plurality of sample environmental information sets; An attenuation coefficient acquisition unit is configured to test the battery attenuation coefficient of the battery of the target vehicle under the plurality of sample environmental information sets to obtain a sample battery attenuation coefficient set; A model construction execution unit is configured to construct the battery attenuation analysis model using the plurality of sample environmental information sets and the sample battery attenuation coefficient set, and the battery attenuation analysis model includes an analysis coordinate system and a plurality of sample coordinate points, and each sample coordinate point is marked by a corresponding sample battery attenuation coefficient; A model analysis execution unit is configured to input the environmental information set into the battery attenuation analysis model to obtain a real-time coordinate point, acquire K sample coordinate points closest to the real-time coordinate point, and K is an odd number greater than or equal to 3; An attenuation coefficient generation unit is configured to acquire K sample battery attenuation coefficients marked by the K sample coordinate points, and take a sample battery attenuation coefficient with the highest frequency as the battery attenuation coefficient; The endurance data calculation module is configured to input the load information, road surface information and speed information in the travel information into a travel energy consumption analysis model to obtain a travel energy consumption parameter, and calculate an initial endurance mileage and an initial endurance time in combination with the real-time battery capacity; The endurance data calculation module further includes: A sample information acquisition unit is configured to acquire a sample load information set, a sample road surface information set and a sample speed information set of the target vehicle; A test detection execution unit is configured to combine data in the sample load information set, the sample road surface information set and the sample speed information set, and perform a travel energy consumption test detection on the target vehicle to acquire a sample travel energy consumption parameter set; A data set construction unit is configured to randomly select M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample travel energy consumption parameter set with replacement to obtain a first construction data set, and M is an integer greater than 1 and less than a number in the sample load information set; An analysis unit construction unit is configured to construct a first travel energy consumption analysis unit in the travel energy consumption analysis model based on a BP neural network using the first construction data set. The data set construction generation unit is configured to randomly select M groups of data from the sample load information set, the sample road surface information set, the sample speed information set, and the sample driving energy consumption parameter set again respectively with replacement, and obtain a second construction data set. The analysis unit generation unit is configured to use the second construction data set to construct a second driving energy consumption analysis unit in the driving energy consumption analysis model. The analysis model generation unit is configured to continue to construct N-2 driving energy consumption analysis units in the driving energy consumption analysis model, N being an integer greater than 3, and obtain the driving energy consumption analysis model according to the N driving energy consumption analysis units. The energy consumption parameter obtaining unit is configured to input the load information and the driving information into the N driving energy consumption analysis units, obtain N output results, and take the output result with the highest frequency as the driving energy consumption parameter. The battery capacity calculation module is configured to calculate the decay battery capacity of the battery within the initial endurance time according to the initial endurance time and the battery decay coefficient, and calculate the actual battery capacity. The endurance distance correction module is configured to calculate the corrected endurance distance according to the actual battery capacity and the driving energy consumption parameter. The management scheme generation module is configured to obtain a charging station near the driving route information according to the driving route information in the driving information, analyze the endurance distance management scheme in combination with the corrected endurance distance, and display the endurance distance management scheme. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the method in any one of claims 1 to 5.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 5.

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