Comprehensive decision-making method and system for charging navigation

Abstract

The invention relates to a comprehensive decision-making method and a comprehensive decision-making system for charging navigation. Dynamic power consumption, a current position, a current residual electric quantity, a current navigation path and front road surface event information of a vehicle in a driving process are acquired in real time; if the abnormal event exists in front, the power consumption of the road section corresponding to the abnormal event can be proportionally corrected based on the pre-constructed energy consumption influence model, so that the electric quantity prediction result is more accurate, and the situation that power is not available when an energy supplementing point cannot be reached is avoided. In addition, a comprehensive decision is made based on the remaining electric quantity reaching each energy complementing point, and the situation that the energy complementing point cannot be reached is avoided. Real-time dynamic charging navigation is adopted, the charging decision can be automatically provided for the driver on the premise that it is guaranteed that the vehicle arrives at the energy supplementing point, a user does not need to plan in advance, and high practicability is achieved.

Description

Technical Field

[0001] The present invention relates to the field of charging navigation, and in particular to a comprehensive decision-making method and system for charging navigation. Background Art

[0002] Charging navigation refers to a service designed specifically for electric vehicle users that helps drivers find the nearest available charging stations and plan the best routes to these charging stations.

[0003] In the prior art, the typical application scenario of charging navigation is that when the vehicle battery SOC reaches the threshold, navigation begins to navigate the electric vehicle to the nearest charging station. However, this method cannot solve the problem of providing charging decisions and route planning for drivers in real time during long-distance driving. This requires the driver to make route rules at the starting point and determine which service area to recharge. However, the situation on the road during long-distance driving is complicated. For example, traffic jams, sudden rain, long uphill sections, etc. will cause changes in power consumption, which in turn causes changes in the planning made in advance, resulting in the possibility that the vehicle cannot reach the predetermined recharging point. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a comprehensive decision-making method and system for charging navigation to solve the problem of user demand for information content in power marketing in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A comprehensive decision-making method for charging navigation of the present invention comprises the following steps:

[0007] Obtaining the vehicle's dynamic power consumption, current location, current remaining power, current navigation path, and road event information ahead, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs;

[0008] Determining from the map information a currently available refueling point for the vehicle, a next refueling point for each currently available refueling point, and a priority for each refueling point based on the current position and the current navigation path;

[0009] Determine the power consumption impact ratio of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and the pre-built power consumption impact model, and determine the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio, the dynamic power consumption and the current remaining power;

[0010] The usage of the charging piles at the current charging point and the next charging point is obtained, and a charging decision analysis is performed on the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles at the current charging point and the next charging point, and the priority of the currently available charging points.

[0011] In an embodiment of the present application, determining the currently available charging point of the vehicle, the next charging point of each currently available charging point, and the priority of each charging point from the map information based on the current position and the current navigation path includes:

[0012] Call the navigation service API to find the first charging point that is closest to the current location and in the direction of the vehicle as the current charging point

[0013] At the current energy point As the starting point, find the current energy replenishment point Next energy point

[0014] Starting from the current location and passing through the current energy replenishment point Or the next energy replenishment point Execute path planning with the end point of the current navigation path as the end point to obtain multiple planned routes, and determine the priority of each charging point based on the mileage of the multiple planned routes, wherein the priority is inversely proportional to the mileage of the planned routes.

[0015] In one embodiment of the present application, the process of constructing the power consumption impact model includes:

[0016] Acquire event energy consumption history data and standard energy consumption data of multiple vehicle models in multiple driving records, wherein the event energy consumption history data includes energy consumption data of the vehicle when driving in an abnormal event, and the abnormal event is one of a traffic jam, a long uphill driving, a long downhill driving, and raining, and the event energy consumption history data and the standard energy consumption data are data at the same temperature level and speed level;

[0017] Determine the abnormal event level in the event energy consumption history data, and divide the event energy consumption history data in multiple driving records based on the vehicle type and the abnormal event level to obtain multiple data units, wherein one data unit includes multiple dynamic energy consumption data of one vehicle type in an abnormal event of one abnormal event level;

[0018] Calculate the average energy consumption value of multiple dynamic energy consumption data in each data unit And the energy consumption variance Based on the average energy consumption and the energy consumption variance Construct energy consumption reference range for each data unit Where n is the range adjustment parameter;

[0019] Energy consumption reference range based on multiple data units And the standard energy consumption data E of the corresponding vehicle model to build the energy consumption ratio reference range (Pr min ,Pr max );

[0020]

[0021] An electricity consumption impact model is constructed based on abnormal events, abnormal event levels and energy consumption ratio reference ranges of multiple data units.

[0022] In one embodiment of the present application, determining the power consumption impact ratio value of vehicles on the road section corresponding to the abnormal event according to the road event information ahead and the pre-built power consumption impact model includes:

[0023] Determine all abnormal events and abnormal event levels included in the front road event information, wherein if the abnormal event is a long uphill slope or a long downhill slope, the abnormal event level is determined based on the altitude change value and the mileage;

[0024] Based on the abnormal event and the abnormal event level, a reference range of energy consumption ratio of vehicles on the road section corresponding to the abnormal event is determined.

[0025] In one embodiment of the present application, determining the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power includes:

[0026] Determine the vehicle from the current position P N Arrived at the currently available energy point Mileage The vehicle moves from its current position P N Arrive at the next energy point Mileage And the abnormal event mileage S(abn k ), k is the abnormal event number;

[0027] Estimate the vehicle from the current position P N Arrived at the currently available energy point Minimum remaining power The vehicle moves from its current position P N Arrive at the next energy point Minimum remaining power

[0028]

[0029] In the formula, SOC N The current remaining power, EC N is the dynamic power consumption, is the maximum proportional parameter corresponding to abnormal event k, and BAT is the total capacity of the vehicle battery.

[0030] In an embodiment of the present application, obtaining the usage of the charging piles of the current charging point and the next charging point includes:

[0031] Request the charging pile usage status from the charging pile cloud server;

[0032] When a response is received from the charging pile cloud server, the charging pile occupancy rates of the current charging point and the next charging point are obtained.

[0033] In one embodiment of the present application, a charging decision analysis is performed on the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles at the current charging point and the next charging point, and the priority of the currently available charging points, including:

[0034] When the remaining power of the vehicle at the current charging point with the highest priority is less than or equal to 0, the vehicle will prioritize charging and plan a route based on the distance to the current charging point. The shortest planned route will be selected and sent to the driver.

[0035] When the remaining power of the vehicle at the current charging point with the highest priority is greater than or equal to the preset first power threshold, and the remaining power at the next charging point with the highest priority is less than or equal to 0, the vehicle plans a route based on the occupancy rate of the current charging point and the detour distance with the goal of charging priority and shortest detour, and sends the planned route to the driver;

[0036] When the remaining power of the vehicle at the next charging point with the highest priority is greater than or equal to a preset first power threshold, the vehicle continues to travel based on the current navigation route without performing route planning.

[0037] In one embodiment of the present application, path planning is performed based on the occupancy rate of the current charging point and the detour distance, including:

[0038] Based on the mileage of the planned path of the current charging point with the highest priority, calculate the detour distance of the mileage of the planned paths of other current charging points;

[0039] The occupancy rate and detour distance of all current charging points are weighted and summed to obtain a comprehensive evaluation score;

[0040] The current charging point with the highest comprehensive evaluation score is used as the target charging point, and a path planning is performed based on the target charging point to obtain a planned path from the current position to the target charging point.

[0041] In one embodiment of the present application, it also includes:

[0042] When the vehicle leaves the current charging point, the next charging point is used as the current charging point, and the vehicle returns to obtain dynamic power consumption, current position, current remaining power, current navigation path, and road event information ahead.

[0043] The present application also provides a comprehensive decision-making system for charging navigation, including:

[0044] An acquisition module, used to acquire the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs;

[0045] A charging point query module, used to determine the vehicle's currently available charging points, the priority of the currently available charging points, and the next charging point of each currently available charging point from the map information based on the current position and the current navigation path;

[0046] A power calculation module, used to determine the power consumption impact ratio value of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and a pre-built power consumption impact model, and determine the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power;

[0047] a decision-making module, for obtaining the usage of the charging piles of the current charging point and the next charging point, and performing charging decision analysis for the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles of the current charging point and the next charging point, and the priority of the currently available charging points.

[0048] The beneficial effects of the present invention are as follows: a comprehensive decision-making method and system for charging navigation of the present invention obtains the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle in real time during driving. If there is an abnormal event ahead, the power consumption of the road section corresponding to the abnormal event can be proportionally corrected based on the pre-built energy consumption impact model, so that the power prediction result is more accurate and the situation where the battery is out of power before reaching the charging point is avoided. In addition, the present application makes a comprehensive decision based on the remaining power at each charging point to avoid the situation where the charging point cannot be reached. The present application adopts real-time dynamic charging navigation, which can automatically provide charging decisions for the driver on the premise of ensuring that the vehicle reaches the charging point. The user does not need to plan in advance, and it has strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0050] Figure 1 is a flow chart of a comprehensive decision-making method for charging navigation shown in an embodiment of the present application;

[0051] Figure 2 This is a schematic diagram of the marketing copy promotion process in one embodiment of the present application;

[0052] Figure 3 is a structural diagram of a comprehensive decision-making system for charging navigation shown in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0055] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show the layers related to the present invention rather than being drawn according to the number, shape and size of the layers in actual implementation. In actual implementation, the type, quantity and proportion of each layer may be changed arbitrarily, and the layer layout may also be more complicated.

[0056] The comprehensive decision-making method and system for charging navigation in the present application can be operated by a vehicle computer, or a cloud server or terminal connected to the vehicle computer.

[0057] Figure 1 This is an application scenario diagram of a comprehensive decision-making method for charging navigation in one embodiment of the present application, such as Figure 1 As shown, the present application is executed by the vehicle computer 110, which connects to the navigation server 120 by calling the API service interface to obtain real-time traffic information, map updates, route planning and other services. In addition, the real-time energy consumption information and battery SOC counted and monitored by the battery management system 130 (Battery Management System, BMS) are also transmitted to the vehicle computer 110. The vehicle computer 110 performs decision analysis on the above information and puts it into the multimedia audio-visual unit to interact with the driver.

[0058] Figure 2 is a flow chart of a comprehensive decision-making method for charging navigation shown in an embodiment of the present application, such as Figure 2 As shown: A comprehensive decision-making method for charging navigation in this embodiment may include steps S210 to S240:

[0059] S210, obtaining dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs;

[0060] The current navigation route is the route determined by the driver through the navigation service when setting out.

[0061] The road event information ahead is learned through the navigation server. First, the navigation server needs to collect information about road conditions from various sources. This information may come from: traffic cameras, other vehicles (through vehicle networking technology), real-time data provided by traffic management departments, user reports, and weather data from weather stations. The collected data will be sent to the data center of the navigation service provider, where it will be analyzed and processed. In this step, complex algorithms are used to identify and classify different road conditions, such as traffic accidents, construction areas, congestion, etc. Finally, the navigation server pushes the road event information ahead to the vehicle based on the real-time location of the vehicle. The received information will be displayed on the car screen in the form of a graphical interface, such as marking the accident site, construction area, etc. on the map, and providing voice prompts or visual warnings to help the driver respond in time. In this application, the pushed information is not only displayed in the form of a graphical interface on the car screen, but also used as power consumption impact data in the background to compensate for power consumption.

[0062] S220, determining, from the map information, currently available refueling points of the vehicle, the next refueling point of each currently available refueling point, and the priority of each refueling point based on the current position and the current navigation path;

[0063] In this application, charging navigation is performed by real-time path planning based on navigation information to help users plan the charging process.

[0064] Figure 3 Schematic diagram of the topological structure of the energy replenishment point in one embodiment of the present application. Figure 3 As shown, in this application, the API interface of the navigation service is first called to find the first charging point closest to the current position and in line with the vehicle's forward direction as the current charging point i is the serial number of the current charging point. This application uses the current position of the vehicle as the starting point, searches for all feasible routes to the current position in the map, and finds the first charging point in the feasible routes to obtain the current charging point;

[0065] Then, the current energy replenishment point As the starting point, find the current energy replenishment point Next energy point Since this application uses the route as the basis to find the current refueling point, you can find the next refueling point by following the route. like Figure 3 As shown, since the roads exist in the form of a road network, different energy replenishment points may be interconnected.

[0066] Finally, starting from the current location, passing through the current energy replenishment point Or the next energy replenishment point Execute the path planning with the end point of the current navigation path as the end point, obtain multiple planned routes, and determine the priority of each charging point based on the mileage of the multiple planned routes, wherein the priority is inversely proportional to the mileage of the planned route. All possible routes can be obtained by planning the route passing through each charging point to the end point, and the route with the shortest distance is regarded as the route with the highest priority, and the corresponding charging point has a higher priority.

[0067] S230, determining the power consumption impact ratio value of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and the pre-built power consumption impact model, and determining the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power;

[0068] In this application, if the road event information ahead is empty, no energy consumption compensation is performed, and the remaining power is predicted and estimated directly based on the current dynamic energy consumption.

[0069] If there are abnormal events on the road ahead, such as rain, long uphill, congestion, etc., the corresponding energy consumption compensation process will be triggered. Since there are many factors that affect energy consumption, such as temperature, driving habits, speed, vehicle type, etc. Therefore, the power consumption impact model in this application mainly determines the proportion of energy consumption impact under various events by controlling variables.

[0070] The construction method of the power consumption impact model in this application is as follows:

[0071] (1) obtaining event energy consumption history data and standard energy consumption data of multiple vehicle models in multiple driving records, wherein the event energy consumption history data includes energy consumption data of the vehicle when driving in an abnormal event, and the abnormal event is one of a traffic jam, a long uphill driving, a long downhill driving, and raining, and the event energy consumption history data and the standard energy consumption data are data at the same temperature level and speed level;

[0072] This application uses a test vehicle, or collects test vehicles online, to conduct actual energy consumption measurements in a variety of single-factor event scenarios, thereby obtaining event energy consumption historical data and corresponding standard energy consumption data.

[0073] For example, in a traffic jam, the motor keeps starting and stopping, which leads to increased energy consumption. In a sample data, the vehicle energy consumption is 15.3Kwh / 100km when driving normally on urban roads, and it rises to 16.4Kwh / 100km in a traffic jam. 15.3Kwh / 100km is the standard energy consumption data, and 16.4Kwh / 100km is the event energy consumption historical data.

[0074] (2) determining the abnormal event level in the event energy consumption history data, and dividing the event energy consumption history data in multiple driving records based on the vehicle type and the abnormal event level to obtain multiple data units, wherein one data unit includes multiple dynamic energy consumption data of one vehicle type in an abnormal event of one abnormal event level;

[0075] In addition, different abnormal event levels will also affect the ratio value. In this application, the abnormal event level is divided based on the information in the sample data. Among them, the navigation system will automatically prompt the level in rainy and congested conditions. For long uphill and downhill slopes, the following formula is used to determine the level:

[0076]

[0077] Here, Range(x) represents the pre-defined range of values ​​corresponding to level x.

[0078] (3) Calculate the average energy consumption value of multiple dynamic energy consumption data in each data unit And the energy consumption variance Based on the average energy consumption and the energy consumption variance Construct energy consumption reference range for each data unit Where n is the range adjustment parameter;

[0079] In this application, big data is used to evaluate energy consumption data, so directly summarizing with a typical value is actually unable to reflect the value pattern. A better way is to calculate the mean and standard deviation to construct a range that can represent the value.

[0080] (4) Energy consumption reference range based on multiple data units And the standard energy consumption data E of the corresponding vehicle model to build the energy consumption ratio reference range (Pr min ,Pr max );

[0081]

[0082] (5) Construct an electricity consumption impact model based on abnormal events, abnormal event levels and energy consumption ratio reference ranges of multiple data units.

[0083] Finally, the ratio value is calculated and used to summarize the ratio range of energy consumption changes caused by different events. This ratio range can better summarize the ratio of energy consumption changes caused by abnormal events in various vehicle models and under different driving conditions.

[0084] Due to the pre-built power consumption impact model, when returning to the power consumption replenishment process, the process of using the power consumption impact model to compensate for the current energy consumption includes:

[0085] S231, determining all abnormal events and abnormal event levels included in the front road event information, wherein if the abnormal event is a long uphill slope or a long downhill slope, the abnormal event level is determined based on the altitude change value and the mileage;

[0086] Among them, the principle of determining the abnormal event level of the abnormal event in the front road event information is consistent with the above, and will not be repeated here.

[0087] S232, determining a reference range of energy consumption ratio of vehicles on the road section corresponding to the abnormal event based on the abnormal event and the abnormal event level;

[0088] S233, determine the vehicle from the current position P N Arrived at the currently available energy point Mileage The vehicle moves from its current position P N Arrive at the next energy point Mileage And the abnormal event mileage S(abn k ), k is the abnormal event number;

[0089] S234, estimating the vehicle's position from the current position P N Arrived at the currently available energy point Minimum remaining power The vehicle moves from its current position P N Arrive at the next energy point Minimum remaining power

[0090]

[0091] In the formula, SOC N The current remaining power, EC N is the dynamic power consumption, is the maximum proportional parameter corresponding to abnormal event k, and BAT is the total capacity of the vehicle battery.

[0092] In this embodiment, there may be multiple abnormal events on the road ahead, such as heavy rain + long uphill, moderate rain + traffic jam. Since the single factor impact model is constructed in the previous text, the total mileage is calculated first. or The energy consumption caused by various abnormal events is calculated, and then the energy consumption increase or decrease corresponding to the abnormal events is calculated. Finally, divide it by the total battery capacity to get the consumed SOC value. Current SOC N Subtracting the consumed SOC value can give the estimated remaining SOC amount compensated for abnormal events.

[0093] S240, obtaining the usage status of the charging piles of the current charging point and the next charging point, and performing a charging decision analysis for the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage status of the charging piles of the current charging point and the next charging point, and the priority of the currently available charging points.

[0094] By analyzing the remaining power of the vehicle at the current charging point and the next charging point, the necessity of charging the vehicle at present can be analyzed. For vehicle charging, if there are multiple charging points, it is necessary to consider the usage of the charging points to find the best charging point. Therefore, before making a decision, it is also necessary to access the charging pile server through the Internet to obtain the occupancy rate of the charging pile. By requesting the charging pile usage from the charging pile cloud server; when receiving a response from the charging pile cloud server, the charging pile occupancy rate of the current charging point and the next charging point is obtained.

[0095] The logic of decision analysis is as follows:

[0096] (1) When the remaining power of the vehicle at the current charging point with the highest priority is less than or equal to 0, the vehicle will prioritize charging and plan a route based on the distance to the current charging point. The shortest planned route will be selected and sent to the driver.

[0097] Since the initial navigation route is generally planned with the shortest distance as the goal, if the remaining power of the vehicle when it reaches the current charging point with the highest priority is less than or equal to 0, it means that it is currently impossible to drive along the established route. In this case, it is necessary to find a charging point as soon as possible to recharge. The goal in this scenario is to give priority to charging. At this time, starting from the current location, a route to the nearest charging point is planned, and then voice prompts and screen displays are used to prompt the driver to drive along the shortest route to reach the charging point.

[0098] (2) When the remaining power of the vehicle at the current charging point with the highest priority is greater than or equal to a preset first power threshold, and the remaining power at the next charging point with the highest priority is less than or equal to 0, a route is planned based on the occupancy rate of the current charging point and the detour distance with the goal of charging priority and shortest detour, and the planned route is sent to the driver;

[0099] If the remaining power of the vehicle when it reaches the current charging point with the highest priority is greater than or equal to the preset first power threshold (such as 20%), and the remaining power when it reaches the next charging point with the highest priority is less than or equal to 0, in this case, the vehicle has the necessity to recharge at the current charging point. At this time, the path planning is carried out with charging priority and the shortest detour as the goal. Charging priority needs to take into account the queuing time for charging. Therefore, this application uses the mileage of the planned path of the current charging point with the highest priority as the benchmark, and calculates the detour distance of the mileage of the planned paths of other current charging points; the occupancy rate and detour distance of all current charging points are weighted and summed to obtain a comprehensive evaluation score; finally, the current charging point with the highest comprehensive evaluation score is used as the target charging point, and path planning is performed based on the target charging point to obtain the planned path from the current position to the target charging point. The above process combines the detour distance and possible queuing time to decide the best charging point for the driver.

[0100] As can be seen from scenario (2), this application will make a recharging decision when the vehicle cannot reach the next recharging point. Therefore, scenario (1) mostly occurs when the driver does not drive according to the decision or misses the intersection. It is an auxiliary scenario for scenario (2).

[0101] (3) When the remaining power of the vehicle at the next charging point with the highest priority is greater than or equal to a preset first power threshold, the vehicle continues to travel based on the current navigation route without performing route planning.

[0102] In most cases, the battery does not need to be recharged. In this case, the decision is made in the same way as in scenario (3), without any prompt or decision suggestion. A voice prompt may also be given, for example, "The current battery level is sufficient to drive to the next recharging point, please drive without worry."

[0103] S250, when the vehicle leaves the current charging point, the next charging point is used as the current charging point, and the process returns to step S210.

[0104] This application helps drivers make energy replenishment calculations during long-distance driving by making real-time cyclic decisions, greatly improving the driving experience of pure electric vehicles during long-distance driving.

[0105] A comprehensive decision-making method for charging navigation of the present invention obtains the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle in real time during driving. If there is an abnormal event ahead, the power consumption of the road section corresponding to the abnormal event can be proportionally corrected based on the pre-built energy consumption impact model, so that the power prediction result is more accurate and the situation where the battery is out of power before reaching the charging point is avoided. In addition, the present application makes a comprehensive decision based on the remaining power at each charging point to avoid the situation where the charging point cannot be reached. The present application adopts real-time dynamic charging navigation, which can automatically provide charging decisions for the driver on the premise of ensuring that the vehicle reaches the charging point, without the need for users to plan in advance, and has strong practicality.

[0106] like Figure 4 As shown, the present application also provides a comprehensive decision-making system for charging navigation, including:

[0107] An acquisition module, used to acquire the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs;

[0108] A charging point query module, used to determine the vehicle's currently available charging points, the priority of the currently available charging points, and the next charging point of each currently available charging point from the map information based on the current position and the current navigation path;

[0109] A power calculation module, used to determine the power consumption impact ratio value of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and a pre-built power consumption impact model, and determine the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power;

[0110] a decision-making module, for obtaining the usage of the charging piles of the current charging point and the next charging point, and performing charging decision analysis for the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles of the current charging point and the next charging point, and the priority of the currently available charging points.

[0111] The beneficial effects of the present invention are as follows: a comprehensive decision-making method and system for charging navigation of the present invention obtains the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle in real time during driving. If there is an abnormal event ahead, the power consumption of the road section corresponding to the abnormal event can be proportionally corrected based on the pre-built energy consumption impact model, so that the power prediction result is more accurate and the situation where the battery is out of power before reaching the charging point is avoided. In addition, the present application makes a comprehensive decision based on the remaining power at each charging point to avoid the situation where the charging point cannot be reached. The present application adopts real-time dynamic charging navigation, which can automatically provide charging decisions for the driver on the premise of ensuring that the vehicle reaches the charging point. The user does not need to plan in advance, and it has strong practicality.

[0112] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any one of the methods in this embodiment is implemented, wherein the method is the execution logic of this system.

[0113] This embodiment also provides an electronic terminal, including: a processor and a memory;

[0114] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any one of the methods in this embodiment.

[0115] The computer-readable storage medium in this embodiment can be understood by ordinary technicians in this field: all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0116] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run computer programs so that the electronic terminal executes each step of the above method.

[0117] In this embodiment, the memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0118] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0119] In the above-mentioned embodiments, although the present invention has been described in conjunction with the specific embodiments of the present invention, many replacements, modifications and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. The embodiments of the present invention are intended to cover all such replacements, modifications and variations falling within the broad scope of the appended claims.

[0120] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A comprehensive decision-making method for charging navigation, characterized in that: Includes steps: Obtaining the vehicle's dynamic power consumption, current location, current remaining power, current navigation path, and road event information ahead, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs; Determining from the map information a currently available refueling point for the vehicle, a next refueling point for each currently available refueling point, and a priority for each refueling point based on the current position and the current navigation path; Determine the power consumption impact ratio of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and the pre-built power consumption impact model, and determine the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio, the dynamic power consumption and the current remaining power; The usage of the charging piles at the current charging point and the next charging point is obtained, and a charging decision analysis is performed on the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles at the current charging point and the next charging point, and the priority of the currently available charging points.

2. The comprehensive decision-making method for charging navigation according to claim 1, characterized in that: Determining a currently available refueling point of the vehicle, a next refueling point of each currently available refueling point, and a priority of each refueling point from map information based on the current position and the current navigation path, including: Call the navigation service API to find the first charging point closest to the current location and in the direction of the vehicle as the current charging point At the current energy point As the starting point, find the current energy replenishment point Next energy point Starting from the current location and passing through the current energy replenishment point Or the next energy replenishment point Execute path planning with the end point of the current navigation path as the end point to obtain multiple planned routes, and determine the priority of each charging point based on the mileage of the multiple planned routes, wherein the priority is inversely proportional to the mileage of the planned routes.

3. The comprehensive decision-making method for charging navigation according to claim 1, characterized in that: The construction process of the power consumption impact model includes: Acquire event energy consumption history data and standard energy consumption data of multiple vehicle models in multiple driving records, wherein the event energy consumption history data includes energy consumption data of the vehicle when driving in an abnormal event, and the abnormal event is one of a traffic jam, a long uphill driving, a long downhill driving, and raining, and the event energy consumption history data and the standard energy consumption data are data at the same temperature level and speed level; Determine the abnormal event level in the event energy consumption history data, and divide the event energy consumption history data in multiple driving records based on the vehicle type and the abnormal event level to obtain multiple data units, wherein one data unit includes multiple dynamic energy consumption data of one vehicle type in an abnormal event of one abnormal event level; Calculate the average energy consumption value of multiple dynamic energy consumption data in each data unit And the energy consumption variance Based on the average energy consumption and the energy consumption variance Construct energy consumption reference range for each data unit Where n is the range adjustment parameter; Energy consumption reference range based on multiple data units And the standard energy consumption data E of the corresponding vehicle model to build the energy consumption ratio reference range (Pr min ,Pr max ); An electricity consumption impact model is constructed based on abnormal events, abnormal event levels and energy consumption ratio reference ranges of multiple data units.

4. The comprehensive decision-making method for charging navigation according to claim 3, characterized in that: Determining the power consumption impact ratio value of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and the pre-built power consumption impact model includes: Determine all abnormal events and abnormal event levels included in the front road event information, wherein if the abnormal event is a long uphill slope or a long downhill slope, the abnormal event level is determined based on the altitude change value and the mileage; Based on the abnormal event and the abnormal event level, a reference range of energy consumption ratio of vehicles on the road section corresponding to the abnormal event is determined.

5. The comprehensive decision-making method for charging navigation according to claim 4, characterized in that: Determining the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power includes: Determine the vehicle from the current position P N Arrived at the currently available energy point Mileage The vehicle moves from its current position P N Arrive at the next energy point Mileage And the abnormal event mileage S(abn k ), k is the abnormal event number; Estimate the vehicle from the current position P N Arrived at the currently available energy point Minimum remaining power The vehicle moves from its current position P N Arrive at the next energy point Minimum remaining power In the formula, SOC N The current remaining power, EC N is the dynamic power consumption, is the maximum proportional parameter corresponding to abnormal event k, and BAT is the total capacity of the vehicle battery.

6. The comprehensive decision-making method for charging navigation according to claim 1, characterized in that: Obtaining the usage of the charging piles of the current charging point and the next charging point, including: Request the charging pile usage status from the charging pile cloud server; When a response is received from the charging pile cloud server, the charging pile occupancy rates of the current charging point and the next charging point are obtained.

7. The comprehensive decision-making method for charging navigation according to claim 1, characterized in that: The charging decision analysis of the current charging point is performed based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles of the current charging point and the next charging point, and the priority of the currently available charging points, including: When the remaining power of the vehicle at the current charging point with the highest priority is less than or equal to 0, the vehicle will prioritize charging and plan a route based on the distance to the current charging point. The shortest planned route will be selected and sent to the driver. When the remaining power of the vehicle at the current charging point with the highest priority is greater than or equal to the preset first power threshold, and the remaining power at the next charging point with the highest priority is less than or equal to 0, the vehicle plans a route based on the occupancy rate of the current charging point and the detour distance with the goal of charging priority and shortest detour, and sends the planned route to the driver; When the remaining power of the vehicle at the next charging point with the highest priority is greater than or equal to a preset first power threshold, the vehicle continues to travel based on the current navigation route without performing route planning.

8. The comprehensive decision-making method for charging navigation according to claim 7, characterized in that: Path planning is performed based on the current occupancy rate of the charging point and the detour distance, including: Based on the mileage of the planned path of the current charging point with the highest priority, calculate the detour distance of the mileage of the planned paths of other current charging points; The occupancy rate and detour distance of all current charging points are weighted and summed to obtain a comprehensive evaluation score; The current charging point with the highest comprehensive evaluation score is used as the target charging point, and a path planning is performed based on the target charging point to obtain a planned path from the current position to the target charging point.

9. The comprehensive decision-making method for charging navigation according to claim 8, characterized in that: Also includes: When the vehicle leaves the current charging point, the next charging point is used as the current charging point, and the vehicle returns to obtain dynamic power consumption, current position, current remaining power, current navigation path, and road event information ahead.

10. A comprehensive decision-making system for charging navigation, characterized in that: include: An acquisition module, used to acquire the dynamic power consumption, current position, current remaining power, current navigation path and road event information ahead of the vehicle, wherein the road event information ahead includes the type of abnormal event and the length of the road section where the abnormal event occurs; A charging point query module, used to determine the vehicle's currently available charging points, the priority of the currently available charging points, and the next charging point of each currently available charging point from the map information based on the current position and the current navigation path; A power calculation module, used to determine the power consumption impact ratio value of the vehicle on the road section corresponding to the abnormal event according to the road event information ahead and a pre-built power consumption impact model, and determine the remaining power of the vehicle when it reaches the current available charging point and the next charging point based on the power consumption impact ratio value, the dynamic power consumption and the current remaining power; a decision-making module, for obtaining the usage of the charging piles of the current charging point and the next charging point, and performing charging decision analysis for the current charging point based on the remaining power of the vehicle when it reaches the current charging point, the remaining power of the vehicle when it reaches the next charging point, the usage of the charging piles of the current charging point and the next charging point, and the priority of the currently available charging points.

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