Energy integrated management platform based on cloud model

Abstract

The present invention is applicable to the field of energy management technology, and in particular to an integrated energy management platform based on a cloud model, the platform comprising: an information acquisition module for acquiring energy information of battery swapping points and constructing a cloud model; a path analysis module for acquiring vehicle auxiliary information and determining user driving path information; a first-level scheduling module for determining backup battery swapping points based on user driving path information and vehicle auxiliary information, and generating a first-level scheduling plan; a second-level scheduling module for determining the actual battery swapping point of the vehicle based on the cloud model and the real-time location information of the vehicle, and generating a second-level scheduling plan. The present invention collects information from battery swapping car owners, thereby predicting the owner's movement trajectory based on a preset cloud model, and determining an energy allocation plan after analyzing the movement trajectories of all car owners, thereby allocating energy according to the energy allocation plan to meet the needs of car owners, avoid the problem of car owners having to wait for a long time, and improve the user experience.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy management, and in particular relates to an integrated energy management platform based on a cloud model. Background Art

[0002] New energy vehicles refer to vehicles that use unconventional automotive fuels as their power source (or use conventional automotive fuels and adopt new on-board power devices), and integrate advanced technologies in vehicle power control and drive to form vehicles with advanced technical principles, new technologies, and new structures.

[0003] Among the current new energy vehicles, electric vehicles occupy a large part of the market. Electric vehicles are energy-saving, environmentally friendly and quiet, but they also have certain shortcomings. Electric vehicles need to be charged. If the owner charges before reaching the destination, he needs to wait. Since gasoline vehicles are in the form of refueling, it can be completed in a few minutes. In order to solve the problem of electric vehicles needing to be charged and poor convenience, a solution has been proposed in the prior art, that is, to recharge the electric vehicle by replacing the battery. In this way, the electric vehicle does not need to wait for charging, and the battery replacement can be completed in a few minutes, which makes up for the shortcomings.

[0004] Although battery swapping is convenient, since the vehicle's driving trajectory is not fixed, it is easy for the battery to be insufficient at the battery swapping point. This will cause car owners waiting for battery swapping to wait for a long time. In addition, the traffic volume in some areas is small, and there are a large number of fully charged batteries that are not used. In essence, this presents a problem of energy allocation. Summary of the Invention

[0005] The purpose of the embodiments of the present invention is to provide an energy integrated management platform based on a cloud model, aiming to solve the problems raised in the third part of the background technology.

[0006] The embodiment of the present invention is implemented as follows: a cloud-based integrated energy management platform, the platform comprising:

[0007] An information acquisition module, configured to acquire energy information of a battery swap point and construct a cloud model based on the energy information of the battery swap point, wherein the energy information of the battery swap point includes at least location information of the battery swap point and battery remaining charge information, and the cloud model includes road information and the location of the battery swap point corresponding to the location information of the battery swap point;

[0008] A path analysis module is used to obtain vehicle auxiliary information and determine the user's driving path information based on the vehicle auxiliary information, wherein the vehicle auxiliary information includes destination location information, vehicle real-time power information, and vehicle real-time location information;

[0009] The first-level scheduling module is used to determine the backup battery swap point based on the user's driving path information and vehicle auxiliary information, and generate a first-level scheduling plan;

[0010] The secondary scheduling module is used to determine the actual battery swap point of the vehicle based on the cloud model and the real-time location information of the vehicle, and generate a secondary scheduling plan.

[0011] Preferably, the path analysis module includes:

[0012] Auxiliary information acquisition unit, used to obtain the real-time location information and real-time power information of the vehicle;

[0013] A trajectory analysis unit, used to obtain the destination location information and determine the feasible movement trajectory based on the cloud model;

[0014] The path confirmation unit is used to determine the user's driving path information based on the real-time location information.

[0015] Preferably, the first-level scheduling module includes:

[0016] A battery swap point analysis unit, used to determine available battery swap points along the route based on the user's driving route information;

[0017] A battery swap position determination unit is used to determine the battery swap position information when the vehicle battery level is lower than a preset value based on the vehicle's real-time battery level information;

[0018] The first-level scheduling plan generation unit is used to determine the backup battery exchange point based on the battery exchange location information and the user's driving path information, and generate a first-level scheduling plan. The first-level scheduling plan includes a plan to dispatch batteries to the backup battery exchange point with the smallest sum of distances from other battery exchange points.

[0019] Preferably, the secondary scheduling module includes:

[0020] An information push unit is used to determine available backup battery swap points based on the cloud model and the vehicle's real-time location information, and push them to the user for confirmation;

[0021] The actual battery swap point determination unit is used to determine the location of the actual battery swap point based on user feedback information;

[0022] The secondary scheduling plan generation unit is used to query the battery remaining capacity of the battery exchange points within a preset range near the location of the actual battery exchange point, and generate a secondary scheduling plan, which includes a battery allocation plan between the battery exchange points within a preset range near the location of the actual battery exchange point.

[0023] Preferably, the vehicle auxiliary information is transmitted in encrypted form.

[0024] Preferably, when the user feedback information is empty, the nearest battery exchange point when the vehicle power level is lower than the minimum power value is regarded as the actual battery exchange point.

[0025] Preferably, when the first-level scheduling plan is generated, recommended battery swap point information is pushed to the user.

[0026] Preferably, the vehicle auxiliary information is obtained by actively acquiring and / or actively uploading.

[0027] Another object of an embodiment of the present invention is to provide a cloud model-based integrated energy management method, the method comprising:

[0028] Obtaining energy information of the battery swap point and constructing a cloud model based on the energy information of the battery swap point, wherein the energy information of the battery swap point includes at least location information of the battery swap point and battery remaining information, and the cloud model includes road information and the location of the battery swap point corresponding to the location information of the battery swap point;

[0029] Acquire vehicle auxiliary information and determine the user's driving path information based on the vehicle auxiliary information, wherein the vehicle auxiliary information includes destination location information, vehicle real-time power information, and vehicle real-time location information;

[0030] Determine the backup battery swap point based on the user's driving path information and vehicle auxiliary information, and generate a first-level scheduling plan;

[0031] The actual battery swap point of the vehicle is determined based on the cloud model and the vehicle's real-time location information, and a secondary scheduling plan is generated.

[0032] Preferably, the step of obtaining vehicle auxiliary information and determining the user's driving path information based on the vehicle auxiliary information specifically includes:

[0033] Obtain the vehicle's real-time location information and real-time vehicle power information;

[0034] Obtain the destination location information and determine the feasible movement trajectory based on the cloud model;

[0035] Determine the user's driving path information based on real-time location information.

[0036] Preferably, the step of determining the backup battery swap point based on the user's driving path information and the vehicle auxiliary information and generating a first-level scheduling plan specifically includes:

[0037] Determine available battery swap points along the way based on the user's driving route information;

[0038] Determine the battery swap location information when the vehicle's battery level is lower than a preset value based on the vehicle's real-time battery level information;

[0039] The backup battery swap point is determined based on the battery swap location information and the user's driving path information, and a first-level scheduling plan is generated. The first-level scheduling plan includes a plan to dispatch batteries to the backup battery swap point with the smallest sum of distances from other battery swap points.

[0040] Preferably, the step of determining the actual battery swap point of the vehicle based on the cloud model and the real-time location information of the vehicle and generating a secondary scheduling plan specifically includes:

[0041] Determine available backup battery swap points based on the cloud model and the vehicle's real-time location information, and push them to the user for confirmation;

[0042] Determine the location of the actual battery swap point based on user feedback;

[0043] Query the battery remaining capacity of the battery swap points within a preset range near the actual battery swap point, and generate a secondary scheduling plan, which includes a battery allocation plan between the battery swap points within a preset range near the actual battery swap point.

[0044] The cloud-based integrated energy management platform provided by the embodiment of the present invention collects information from battery-swapping vehicle owners, thereby predicting the vehicle owners' movement trajectories based on a preset cloud model. After analyzing the movement trajectories of all vehicle owners, an energy allocation plan is determined, and energy allocation is performed according to the energy allocation plan to meet the needs of vehicle owners, avoid the problem of vehicle owners having to wait for a long time, and improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flowchart of a cloud-based integrated energy management method provided by an embodiment of the present invention;

[0046] Figure 2 A flowchart of the steps of obtaining vehicle auxiliary information and determining user driving path information based on the vehicle auxiliary information provided by an embodiment of the present invention;

[0047] Figure 3 A flowchart of the steps of determining a backup battery swap point based on user driving path information and vehicle auxiliary information and generating a first-level scheduling plan provided in an embodiment of the present invention;

[0048] Figure 4 A flowchart of the steps for determining the actual battery swap point of a vehicle based on a cloud model and the vehicle's real-time location information and generating a secondary scheduling plan, provided in an embodiment of the present invention;

[0049] Figure 5 An architecture diagram of a cloud-based integrated energy management platform provided by an embodiment of the present invention;

[0050] Figure 6 An architectural diagram of a path analysis module provided in an embodiment of the present invention;

[0051] Figure 7 An architectural diagram of a first-level scheduling module provided in an embodiment of the present invention;

[0052] Figure 8 This is an architectural diagram of a two-level scheduling module provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0054] It is understood that the terms "first," "second," etc., used herein may be used to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script without departing from the scope of this application.

[0055] Among the current new energy vehicles, electric vehicles occupy a large part of the market. Electric vehicles are energy-saving, environmentally friendly, and quiet, but they also have certain shortcomings. Electric vehicles need to be charged. If the owner charges before reaching the destination, he needs to wait. Since gasoline vehicles are in the form of refueling, it can be completed in a few minutes. In order to solve the problem of electric vehicles needing to be charged and poor convenience, a solution has been proposed in the prior art, that is, to recharge the electric vehicle by replacing the battery. In this way, the electric vehicle does not need to wait for charging, and the battery replacement can be completed in a few minutes, which makes up for the shortcomings. Although battery replacement is convenient, since the vehicle's driving trajectory is not fixed, it is easy for the battery to be insufficient at the battery replacement point, which will cause the owner waiting for the battery replacement to wait for a long time. In addition, the traffic volume in some areas is small, and there are a large number of fully charged batteries that no one uses, which actually presents the problem of energy allocation.

[0056] The present invention collects information from battery swapping car owners, and predicts the owners' movement trajectories based on a preset cloud model. After analyzing the movement trajectories of all car owners, an energy allocation plan is determined, and energy allocation is carried out according to the energy allocation plan to meet the needs of car owners, avoid the problem of car owners having to wait for a long time, and improve the user experience.

[0057] like Figure 1 FIG. 1 is a flow chart of a cloud-based integrated energy management method according to an embodiment of the present invention, wherein the method includes:

[0058] S100, obtain the energy information of the battery exchange point, and build a cloud model based on the energy information of the battery exchange point, the energy information of the battery exchange point at least includes the battery exchange point location information and battery remaining information, and the cloud model includes road information and the battery exchange point location corresponding to the battery exchange point location information.

[0059] In this step, the energy information of the battery swap points is obtained. For each battery swap point, its location is fixed, and the total storage capacity of its battery is also fixed. What is in a dynamically changing state is the number of available batteries at the battery swap point. Therefore, in order to facilitate unified management and deployment, it is necessary to collect information statistics for all battery swap points. The energy information of the battery swap points obtained by statistics includes at least the location information of the battery swap points and the battery remaining information. Then, a cloud model is constructed. The cloud model is actually a simplified map stored in the cloud. The map marks the road information and the battery swap point location corresponding to the battery swap point location information, and then establishes a corresponding relationship between all battery swap point and battery-related information and the battery swap point; the vehicle auxiliary information is transmitted in encrypted form.

[0060] S200, obtaining vehicle auxiliary information, and determining user driving path information based on the vehicle auxiliary information, wherein the vehicle auxiliary information includes destination location information, vehicle real-time power information, and vehicle real-time location information.

[0061] In this step, vehicle auxiliary information is obtained. During this process, the user is requested to obtain the above information. After the user agrees, the destination location information, the vehicle's real-time power information and the vehicle's real-time location information are obtained. Based on the vehicle's real-time location, the available paths for the user to reach the destination are determined according to the user's destination location information, and the changes in the user's power during this process are determined. Finally, the user's driving path information is determined. The user's driving path information can be multiple; vehicle auxiliary information is obtained by actively acquiring and / or actively uploading.

[0062] S300: Determine the backup battery swap point based on the user's driving path information and vehicle auxiliary information, and generate a first-level scheduling plan.

[0063] In this step, the backup battery swap point is determined based on the user's driving path information and vehicle auxiliary information. By real-time monitoring of the vehicle's condition, based on the user's current power consumption and driving path, it is determined whether the user needs to swap batteries before reaching the destination. If the power is lower than a certain value before reaching the destination, the available battery swap points on the path are determined. The above-mentioned battery swap points are the backup battery swap points, and the backup battery swap points corresponding to all vehicles are counted to determine the number of vehicles corresponding to each battery swap point. When the number of available batteries in the current battery swap point exceeds the number of corresponding vehicles, the excess batteries can be used for long-distance scheduling to generate a first-level scheduling plan.

[0064] S400: Determine the actual battery swapping point of the vehicle based on the cloud model and the real-time location information of the vehicle, and generate a secondary scheduling plan.

[0065] In this step, the actual battery swap point of the vehicle is determined based on the cloud model and the real-time location information of the vehicle. That is, when the battery level of the vehicle is lower than the minimum set value, it is considered that the vehicle is currently looking for a battery swap point. Then, the battery swap points within the vicinity of the vehicle are determined, and the excess batteries are dispatched over short distances from the battery swap points scheduled by the first-level scheduling plan, thus obtaining the second-level scheduling plan.

[0066] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of obtaining vehicle auxiliary information and determining the user's driving path information based on the vehicle auxiliary information specifically includes:

[0067] S201, obtaining the real-time location information and real-time battery information of the vehicle.

[0068] In this step, the real-time location information and real-time power information of the vehicle are obtained. That is, the real-time location of the vehicle can be obtained based on the vehicle's positioning device, or the location uploaded by the user can be used as the real-time location information of the vehicle. The real-time power information of the vehicle records the real-time power of the vehicle.

[0069] S202: Acquire the destination location information and determine a feasible movement trajectory based on the cloud model.

[0070] In this step, the destination location information is obtained. The destination is directly uploaded by the user. During this process, a destination acquisition request can be sent to the user based on the user's power level to obtain the destination location information, thereby generating a feasible movement trajectory in the cloud model based on the user's current location and destination location information.

[0071] S203: Determine the user's driving path information based on the real-time location information.

[0072] In this step, the user's driving path information is determined based on the real-time location information. During the vehicle's movement, the path taken by the user is determined based on the user's real-time location, and thus determined as the user's driving path information. If there are still multiple feasible trajectories, there are multiple user driving path information.

[0073] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of determining the backup battery swap point based on the user's driving path information and the vehicle auxiliary information and generating the first-level scheduling plan specifically includes:

[0074] S301, determine the available battery swapping points along the way based on the user's driving route information.

[0075] S302, determining the battery-swap location information when the vehicle battery level is lower than a preset value based on the vehicle's real-time battery level information.

[0076] In this step, the battery swap points along the way are determined based on the user's current driving route, and the current vehicle power level of the user is analyzed. When it is lower than the preset value, the positions where battery swapping can be performed on the remaining path are determined, and the battery swap location information is generated.

[0077] S303, determine the backup battery swap point based on the battery swap location information and the user's driving path information, and generate a first-level scheduling plan, which includes a plan to dispatch batteries to the backup battery swap point with the smallest sum of distances from other battery swap points.

[0078] In this step, the backup battery swap point is determined based on the battery swap location information and the user's driving path information. Each vehicle will correspond to multiple backup battery swap points. Therefore, all battery swap points are counted to obtain the number of vehicles corresponding to each battery swap point. The larger the number, the more vehicles will swap batteries at the battery swap point. Therefore, it is necessary to schedule them to ensure the number of batteries at the battery swap point. When generating a first-level scheduling plan, there are multiple backup battery swap points. Therefore, based on the number of batteries required for each battery swap point, the cost of scheduling from other battery swap points is calculated to select a plan to schedule batteries to the backup battery swap point with the smallest sum of distances from other battery swap points. For example, there are 10 battery swap points that can be scheduled to backup battery swap point A. Based on the distance between backup battery swap point A and other battery swap points, the cost of all scheduling plans is calculated, and the plan with the lowest cost is selected as the first-level scheduling plan. When the first-level scheduling plan is generated, the recommended battery swap point information is pushed to the user.

[0079] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of determining the actual battery swap point of the vehicle based on the cloud model and the real-time location information of the vehicle and generating a secondary scheduling plan specifically includes:

[0080] S401, determine the available backup battery swap points based on the cloud model and the real-time location information of the vehicle, and push them to the user for confirmation.

[0081] In this step, the available backup battery swap points are determined based on the cloud model and the real-time location information of the vehicle. In order to facilitate the determination of the battery swap demand of each battery swap point, the backup battery swap points can be directly sent for users to choose, so as to alleviate the pressure on each battery swap point and play a role in diversion.

[0082] S402: Determine the actual location of the battery swapping point based on user feedback information.

[0083] S403, query the battery remaining capacity of the battery swap points within a preset range near the actual battery swap point, and generate a secondary scheduling plan, which includes a battery allocation plan between the battery swap points within a preset range near the actual battery swap point.

[0084] In this step, the user feedback information is parsed, which includes the location of the battery swap point selected by the user, so as to determine that the current vehicle will go to the battery swap point for battery swap; then the battery remaining capacity of the battery swap points within the preset range near the actual battery swap point is queried, and the vehicles with battery capacity lower than the minimum preset value and the vehicles whose battery swap points are determined in the user feedback information are counted. With the above-mentioned vehicles as the center, the battery swap points within the preset range are determined, and the number of vehicles corresponding to each battery swap point within the range of these vehicles is determined again, so as to complete the secondary scheduling according to the above-mentioned number of vehicles; when the user feedback information is empty, the nearest battery swap point when the vehicle battery capacity is lower than the minimum battery capacity value is regarded as the actual battery swap point.

[0085] To sum up, the scheduling plan can be understood as: setting two power values, namely the first power value and the second power value, where 0<second power value<first power value<100, and vehicles are divided into three categories according to the power. The power of the first category of vehicles is between the first power value and 100%, so the power is sufficient and there is no need to replace the battery for the time being. The power of the second category of vehicles is between the second power value and the first power value. At this time, the vehicle may replace the battery; the power of the third category of vehicles is less than the second power value. At this time, the power is very low and needs to be replaced immediately; therefore, in the scheduling process, the battery replacement pressure of all battery replacement points is preliminarily evaluated according to the driving path of the second category of vehicles, so as to determine several battery replacement points with peak battery replacement times, and concentrate nearby batteries to them to achieve overall battery scheduling; and then for the third category of vehicles, determine the battery replacement points that are in urgent need of battery supply, and then schedule from nearby battery replacement points where a large number of batteries are concentrated to complete the secondary scheduling.

[0086] like Figure 5 As shown in FIG, an embodiment of the present invention provides an energy integrated management platform based on a cloud model, the platform including:

[0087] The information acquisition module 100 is used to obtain the energy information of the battery exchange point and construct a cloud model based on the energy information of the battery exchange point. The energy information of the battery exchange point includes at least the location information of the battery exchange point and the battery remaining information. The cloud model includes road information and the battery exchange point location corresponding to the battery exchange point location information.

[0088] In this platform, the information acquisition module 100 obtains the energy information of the battery swap point. For each battery swap point, its location is fixed, and the total storage capacity of its battery is also fixed. The number of available batteries at the battery swap point is in a dynamically changing state. Therefore, in order to facilitate unified management and deployment, it is necessary to conduct information statistics on all battery swap points. The energy information of the battery swap points obtained by statistics includes at least the battery swap point location information and battery remaining information, and then a cloud model is constructed. The cloud model is actually a simplified map stored in the cloud. The map marks the road information and the battery swap point location corresponding to the battery swap point location information, and then establishes a correspondence between all battery swap point and battery-related information and the battery swap point; the vehicle auxiliary information is transmitted in encrypted form.

[0089] The path analysis module 200 is used to obtain vehicle auxiliary information and determine the user's driving path information based on the vehicle auxiliary information. The vehicle auxiliary information includes destination location information, vehicle real-time power information and vehicle real-time location information.

[0090] In this platform, the path analysis module 200 obtains vehicle auxiliary information. During this process, it requests the user to obtain the above information. After the user agrees, it obtains the destination location information, the vehicle's real-time power information and the vehicle's real-time location information. Based on the vehicle's real-time location information, it determines the available paths for the user to reach the destination, and then determines the changes in the user's power during this process, and finally determines the user's driving path information. The user's driving path information can be multiple; the vehicle auxiliary information is obtained by actively acquiring and / or actively uploading.

[0091] The first-level scheduling module 300 is used to determine the backup battery swap point based on the user's driving path information and vehicle auxiliary information, and generate a first-level scheduling plan.

[0092] In this platform, the first-level scheduling module 300 determines the backup battery swap point based on the user's driving path information and vehicle auxiliary information. By monitoring the vehicle's condition in real time, it determines whether the user needs to swap batteries before reaching the destination based on the user's current power consumption and driving path. If the power is lower than a certain value before reaching the destination, it starts to determine the available battery swap points on the path. The above-mentioned battery swap points are the backup battery swap points, and the backup battery swap points corresponding to all vehicles are counted to determine the number of vehicles corresponding to each battery swap point. When the number of available batteries in the current battery swap point exceeds the number of corresponding vehicles, the excess batteries can be used for long-distance scheduling to generate a first-level scheduling plan.

[0093] The secondary scheduling module 400 is used to determine the actual battery swap point of the vehicle based on the cloud model and the real-time location information of the vehicle, and generate a secondary scheduling plan.

[0094] In this platform, the secondary scheduling module 400 determines the actual battery swap point of the vehicle based on the cloud model and the real-time location information of the vehicle. That is, when the battery level of the vehicle is lower than the minimum set value, it is considered that the vehicle is currently looking for a battery swap point. Then, the battery swap points within the vicinity of the vehicle are determined, and the excess batteries are dispatched over short distances from the battery swap points scheduled by the primary scheduling plan, thus obtaining the secondary scheduling plan.

[0095] like Figure 6 As shown, as a preferred embodiment of the present invention, the path analysis module 200 includes:

[0096] The auxiliary information acquisition unit 201 is used to acquire the real-time location information and the real-time power information of the vehicle.

[0097] In this module, the auxiliary information acquisition unit 201 acquires the real-time location information and real-time power information of the vehicle. That is, the real-time location of the vehicle can be obtained based on the vehicle's positioning device, or the location uploaded by the user can be used as the real-time location information of the vehicle. The real-time power information of the vehicle records the real-time power of the vehicle.

[0098] The trajectory analysis unit 202 is used to obtain the destination location information and determine the feasible movement trajectory based on the cloud model.

[0099] In this module, the trajectory analysis unit 202 obtains the destination location information, which is directly uploaded by the user. During this process, a destination acquisition request can be sent to the user based on the user's power level to obtain the destination location information, thereby generating a feasible movement trajectory in the cloud model based on the user's current location and the destination location information.

[0100] The path confirmation unit 203 is used to determine the user's driving path information based on the real-time location information.

[0101] In this module, the path confirmation unit 203 determines the user driving path information based on the real-time position information. During the movement of the vehicle, the path taken by the user is determined based on the user's real-time position, and is thus determined as the user driving path information. If there are still multiple feasible trajectories, there are multiple user driving path information.

[0102] like Figure 7 As shown, as a preferred embodiment of the present invention, the first-level scheduling module 300 includes:

[0103] The battery swap point analysis unit 301 is used to determine the available battery swap points along the way based on the user's driving path information.

[0104] The battery swap position determination unit 302 is used to determine the battery swap position information when the vehicle battery level is lower than a preset value based on the vehicle's real-time battery level information.

[0105] In this module, the battery swap points along the way are determined based on the user's current driving route, and the current vehicle power level of the user is analyzed. When it is lower than the preset value, the locations where battery swaps can be performed on the remaining path are determined, and the battery swap location information is generated.

[0106] The first-level scheduling plan generation unit 303 is used to determine the backup battery exchange point based on the battery exchange location information and the user's driving path information, and generate a first-level scheduling plan. The first-level scheduling plan includes a plan to dispatch batteries to the backup battery exchange point with the smallest sum of distances from other battery exchange points.

[0107] In this module, the first-level scheduling plan generation unit 303 determines the backup battery swap point based on the battery swap location information and the user's driving path information. Each vehicle will correspond to multiple backup battery swap points. Therefore, all battery swap points are counted to obtain the number of vehicles corresponding to each battery swap point. The larger the number, the more vehicles will swap batteries at the battery swap point. Therefore, it is necessary to schedule to it to ensure the number of batteries at the battery swap point. When generating the first-level scheduling plan, there are multiple backup battery swap points. Therefore, according to the number of batteries required for each battery swap point, the cost of scheduling from other battery swap points is calculated to select the plan of scheduling batteries to the backup battery swap point with the smallest sum of distances from other battery swap points. For example, there are 10 battery swap points that can be scheduled to backup battery swap point A. According to the distance between backup battery swap point A and other battery swap points, the cost of all scheduling plans is calculated, and the plan with the lowest cost is selected as the first-level scheduling plan; when the first-level scheduling plan is generated, the recommended battery swap point information is pushed to the user.

[0108] like Figure 8 As shown, as a preferred embodiment of the present invention, the secondary scheduling module 400 includes:

[0109] The information push unit 401 is used to determine the available backup battery swap points based on the cloud model and the real-time location information of the vehicle, and push them to the user for confirmation.

[0110] In this module, the information push unit 401 determines the available backup battery exchange points based on the cloud model and the real-time location information of the vehicle. In order to facilitate the determination of the battery exchange needs of each battery exchange point, the backup battery exchange points can be directly sent for users to choose, so as to alleviate the pressure on each battery exchange point and play a role in attracting traffic.

[0111] The actual battery swap point determination unit 402 is used to determine the location of the actual battery swap point based on user feedback information.

[0112] The secondary scheduling plan generation unit 403 is used to query the battery remaining capacity of the battery exchange points within a preset range near the location of the actual battery exchange point, and generate a secondary scheduling plan, which includes a battery allocation plan between the battery exchange points within a preset range near the location of the actual battery exchange point.

[0113] In this module, the user feedback information is parsed, which includes the location of the battery swap point selected by the user, so as to determine that the current vehicle will go to the battery swap point for battery swap; then the battery remaining capacity of the battery swap points within the preset range near the actual battery swap point is queried, and the vehicles with battery capacity lower than the minimum preset value and the vehicles whose battery swap points are determined in the user feedback information are counted. With the above-mentioned vehicles as the center, the battery swap points within the preset range are determined, and the number of vehicles corresponding to each battery swap point within the range of these vehicles is determined again, so as to complete the secondary scheduling according to the above-mentioned number of vehicles; when the user feedback information is empty, the nearest battery swap point when the vehicle battery capacity is lower than the minimum battery capacity value is regarded as the actual battery swap point.

[0114] It should be understood that, although the various steps in the flow chart of each embodiment of the present invention are shown in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0115] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0116] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An energy integrated management platform based on a cloud model, characterized in that: The platform includes: An information acquisition module, configured to acquire energy information of a battery swap point and construct a cloud model based on the energy information of the battery swap point, wherein the energy information of the battery swap point includes at least location information of the battery swap point and battery remaining charge information, and the cloud model includes road information and the location of the battery swap point corresponding to the location information of the battery swap point; A path analysis module is used to obtain vehicle auxiliary information and determine the user's driving path information based on the vehicle auxiliary information, wherein the vehicle auxiliary information includes destination location information, vehicle real-time power information, and vehicle real-time location information; The first-level scheduling module is used to determine the backup battery swap point based on the user's driving path information and vehicle auxiliary information, and generate a first-level scheduling plan; The secondary scheduling module is used to determine the actual battery swap point of the vehicle based on the cloud model and the vehicle's real-time location information, and generate a secondary scheduling plan; The first-level scheduling module includes: A battery swap point analysis unit, used to determine available battery swap points along the route based on the user's driving route information; A battery swap position determination unit is used to determine the battery swap position information when the vehicle battery level is lower than a preset value based on the vehicle's real-time battery level information; A first-level scheduling plan generating unit is used to determine a backup battery swap point based on the battery swap location information and the user's driving path information, and generate a first-level scheduling plan, wherein the first-level scheduling plan includes a plan for dispatching batteries to the backup battery swap point with the smallest sum of distances to other battery swap points; The secondary scheduling module includes: An information push unit is used to determine available backup battery swap points based on the cloud model and the vehicle's real-time location information, and push them to the user for confirmation; The actual battery swap point determination unit is used to determine the location of the actual battery swap point based on user feedback information; The secondary scheduling plan generation unit is used to query the battery remaining capacity of the battery exchange points within a preset range near the location of the actual battery exchange point, and generate a secondary scheduling plan, which includes a battery allocation plan between the battery exchange points within a preset range near the location of the actual battery exchange point.

2. The cloud-based integrated energy management platform according to claim 1, characterized in that: The path analysis module includes: Auxiliary information acquisition unit, used to obtain the real-time location information and real-time power information of the vehicle; A trajectory analysis unit, used to obtain the destination location information and determine the feasible movement trajectory based on the cloud model; The path confirmation unit is used to determine the user's driving path information based on the real-time location information.

3. The cloud-based integrated energy management platform according to claim 1, characterized in that: The vehicle auxiliary information is transmitted in encrypted form.

4. The cloud-based integrated energy management platform according to claim 1, characterized in that: When the user feedback information is empty, the nearest battery swap point when the vehicle's battery level is lower than the minimum battery level will be regarded as the actual battery swap point.

5. The cloud-based integrated energy management platform according to claim 1, characterized in that: When the first-level scheduling plan is generated, recommended battery swap point information is pushed to users.

6. The cloud-based integrated energy management platform according to claim 1, characterized in that: Vehicle auxiliary information is obtained by actively acquiring and / or actively uploading.

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