Battery energy control method and device, electronic equipment and vehicle

Abstract

The invention relates to a battery energy control method and device, electronic equipment and a vehicle, and relates to the technical field of vehicles, and the method comprises the steps: estimating the estimated energy consumption information corresponding to the driving of the vehicle in a target road section based on the road section information of the target road section; and based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road section, the power battery of the vehicle is controlled to release energy, so that the energy of the power battery of the vehicle is released through the estimated energy consumption information of the vehicle, a space is reserved for energy recovery of the vehicle, and the energy recovery efficiency of the vehicle is improved. And the energy recovery efficiency and the driving experience feeling of the vehicle are improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicles, and particularly to a battery energy control method, device, electronic device and vehicle. Background Art

[0002] With the increasing awareness of environmental protection, new energy vehicles have developed rapidly due to their low-emission or zero-emission characteristics. However, in order to save resources, it is necessary to improve the energy utilization rate of new energy vehicles. To improve the energy utilization rate, related technologies disclose constructing a graph structure through the position information and road condition parameters of a vehicle, and then using a target search model to search the graph to determine the driving path of the vehicle. Another related technology discloses receiving terrain information data between nodes, the remaining energy of each node, the data of sharing the remaining energy between each node and other nodes, and calculating the energy consumed by signal transmission between nodes, so as to determine the optimal communication path.

[0003] It can be seen that these two methods only consider determining the driving path of the vehicle based on road conditions to ensure the energy utilization rate of the vehicle, and do not consider the impact of the energy recovery function on the energy utilization rate of the vehicle. The energy recovery function can convert part of the kinetic energy into electrical energy and store it in the battery when the vehicle decelerates or brakes, so as to improve the energy utilization rate. However, in combination with other energy optimization solutions, continuously optimizing the energy utilization rate may cause the energy recovery function to malfunction, thus affecting the driving experience of users. Summary of the Invention

[0004] The purpose of the present invention is to provide a battery energy control method, device, electronic device and vehicle, which are used to improve the driving experience and energy recovery efficiency of users.

[0005] To achieve the above purpose, the technical solutions adopted in the embodiments of the present application are as follows:

[0006] In a first aspect, the embodiments of the present application provide a battery energy control method, which includes: estimating the estimated energy consumption information corresponding to the vehicle driving in the target section based on the section information of the target section; controlling the power battery of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target section.

[0007] According to the above technical means, based on the road segment information of the target road segment, the estimated energy consumption information corresponding to the vehicle driving in the target road segment can be estimated more accurately. The real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment can intuitively display the operation data of the vehicle after driving the target road segment. Furthermore, the power battery of the vehicle is controlled to release energy, while improving the energy utilization rate, reserving space for energy recovery of the vehicle, and avoiding suppressing the energy recovery function to prevent overcharging when the power battery has too much energy. That is to say, the battery energy control method provided by this application can ensure the normal operation of the energy recovery function, thereby improving the braking effect of the vehicle during driving, further reducing the use of mechanical braking, and better improving the driving experience and energy recovery efficiency of users.

[0008] In a possible implementation manner, based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment, controlling the power battery of the vehicle to release energy includes: determining the estimated power information of the power battery when the vehicle is driving based on the real-time operation data and the estimated energy consumption information corresponding to the target road segment; controlling the power battery of the vehicle to release energy when the estimated power information is greater than or equal to a preset power threshold.

[0009] According to the above technical means, the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment can estimate the energy consumption information more accurately. If the estimated power information is greater than or equal to the preset power threshold, that is, the power of the power battery is close to the full charge state, controlling the power battery of the vehicle to release energy, reserving space for energy recovery of the vehicle, and avoiding suppressing the energy recovery function to prevent overcharging when the power battery has too much energy, thereby improving the braking effect of the vehicle during driving, reducing the use of mechanical braking, and better improving the driving experience of the vehicle.

[0010] In a possible implementation manner, the real-time operation data includes: vehicle speed, power, and ambient temperature; determining the estimated power information of the power battery when the vehicle is driving based on the real-time operation data and the estimated energy consumption information corresponding to the target road segment includes: updating the estimated energy consumption information based on the real-time operation data; determining the estimated power information of the power battery when the vehicle is driving based on the updated estimated energy consumption information and the real-time power of the power battery.

[0011] According to the above technical means, by combining multiple factors such as the vehicle speed, power, and ambient temperature of the vehicle, and updating the estimated energy consumption information in real time, the accuracy of the estimated energy consumption information can be effectively improved. Furthermore, based on the updated estimated energy consumption information and the real-time power of the power battery, the estimated power information of the power battery can be determined in real time as the vehicle drives, improving the flexibility and timeliness of the estimated power information.

[0012] In a possible implementation, when there is a navigation route for the vehicle, the target section is determined based on the navigation route; and / or when there is no navigation route for the vehicle, the target section is determined based on the topological road network where the vehicle is located.

[0013] According to the above technical means, when there is a navigation route, the target section is determined based on the navigation route, and when there is no navigation route, the target section is determined based on the topological road network where the vehicle is located. The actual situation during the actual driving process of the vehicle is considered, and the target section is determined in combination with the actual situation, thereby improving the versatility and flexibility of the battery energy control method provided in this application.

[0014] In a possible implementation, the topological road network includes multiple road nodes; when there is no navigation route for the vehicle, the estimated energy consumption information corresponding to the vehicle driving in the target section is estimated based on the section information of the target section, including: determining the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network; the driving section is the section between two road nodes; determining the target section based on the weight corresponding to each driving section, and the vehicle's current node and target node; the target node is a node whose distance from the current node is greater than or equal to a preset distance threshold; determining the estimated energy consumption information corresponding to the target section based on the weight of the target section.

[0015] According to the above technical means, by using the section information in the topological road network, the weight corresponding to each driving section is obtained, and based on the weight, the energy consumption information can be estimated more accurately, and the energy of the battery in the vehicle can be controlled in a timely manner, improving the accuracy of the battery energy control method.

[0016] In a possible implementation, determining the target section based on the weight corresponding to each driving section, and the vehicle's current node and target node includes: determining the section with the lowest weight among the sections from the current node to at least one target node in the topological road network based on the weight corresponding to each driving section, as the target section.

[0017] According to the above technical means, determining the section with the lowest weight among the sections from the current node to at least one target node in the topological road network as the target section. It should be understood that the lowest weight means that the estimated energy consumption information of the vehicle in the target section is the best. When the navigation information of the vehicle cannot be obtained, the battery in the vehicle can also be accurately controlled, improving the accuracy of the battery energy control method.

[0018] In a possible implementation, determining the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network includes: determining the weight corresponding to the driving section based on the section information of the driving section, the vehicle's historical energy consumption data, and the energy recovery efficiency coefficient.

[0019] Based on the above technical means, by combining multiple factors such as the road segment information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient, the weight corresponding to the driving section is determined more comprehensively, improving the accuracy of the battery energy control method.

[0020] In a possible implementation manner, based on the road segment information of the target road segment, the estimated energy consumption information corresponding to the vehicle driving in the target road segment is estimated, including: based on the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle, the estimated energy consumption information corresponding to the vehicle driving in the target road segment is estimated.

[0021] Based on the above technical means, by combining multiple factors such as the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle, the energy consumption information can be estimated more accurately, thereby improving the accuracy of the battery energy control method.

[0022] In a possible implementation manner, the road segment information includes at least one of the following: road segment length, road segment slope, road segment saturation, estimated passing time; and / or, the driving behavior data includes: user driving habits and historical energy consumption data.

[0023] Based on the above technical means, the road segment information includes multiple factors such as road segment length, road segment slope, road segment saturation, and estimated passing time, which can more comprehensively reflect the information in the road segment, thereby improving the accuracy of the battery energy control method.

[0024] In a second aspect, an embodiment of the present application provides a battery energy control device, including: an estimation module and a processing module; the estimation module is used to estimate the estimated energy consumption information corresponding to the vehicle driving in the target road segment based on the road segment information of the target road segment; the processing module is used to control the power battery of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment.

[0025] In a possible implementation manner, the processing module is specifically used to determine the estimated battery power information of the vehicle when driving based on the real-time operation data and the estimated energy consumption information corresponding to the target road segment; in the case where the estimated battery power information is greater than or equal to the preset battery power threshold, control the power battery of the vehicle to release energy.

[0026] In a possible implementation manner, the real-time operation data includes: vehicle speed, battery power, ambient temperature; the processing module is specifically used to update the estimated energy consumption information based on the real-time operation data; and determine the estimated battery power information of the vehicle when driving based on the updated estimated energy consumption information and the real-time battery power of the power battery.

[0027] In a possible implementation, when there is a navigation path for the vehicle, the target section is determined based on the navigation path; and / or, when there is no navigation path for the vehicle, the target section is determined based on the topological road network where the vehicle is located.

[0028] In a possible implementation, the topological road network includes multiple road nodes; the estimation module is specifically configured to determine the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network; the driving section is the section between two road nodes; based on the weight corresponding to each driving section, as well as the current node and the target node where the vehicle is located, determine the target section; the target node is a node whose distance from the current node is greater than or equal to a preset distance threshold; determine the estimated energy consumption information corresponding to the target section based on the weight of the target section.

[0029] In a possible implementation, the estimation module is specifically configured to determine, based on the weight corresponding to each driving section, the section with the lowest weight among the sections from the current node to any target node in the topological road network as the target section.

[0030] In a possible implementation, the estimation module is specifically configured to determine the weight corresponding to each driving section based on the section information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient, based on the weight corresponding to each driving section.

[0031] In a possible implementation, the estimation module is specifically configured to estimate the estimated energy consumption information corresponding to the vehicle's driving in the target section based on the section information of the target section, the driving behavior data, and the real-time operation data of the vehicle.

[0032] In a possible implementation, the section information includes at least one of the following: section length, section slope, section saturation, estimated travel time; and / or, the driving behavior data includes: user driving habits and historical energy consumption data.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, which includes: a processor and a memory; the memory stores instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements the method in the first aspect above.

[0034] In a fourth aspect, an embodiment of the present application provides a vehicle, which includes the electronic device in the third aspect above.

[0035] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the fuel cell temperature control method in any embodiment provided in the first aspect above is implemented.

[0036] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes computer program instructions that, when executed by a processor, implement the fuel cell temperature control method according to any one of the embodiments provided in the first aspect above.

[0037] It should be noted that for the technical effects brought by any implementation manner in the second aspect to the sixth aspect, reference may be made to the technical effects brought by the corresponding implementation manner in the first aspect, which will not be elaborated herein.

[0038] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application, and do not constitute an improper limitation to the present application.

[0040] Figure 1 is a schematic structural diagram of a battery energy control system shown according to an exemplary embodiment;

[0041] Figure 2 is a flowchart of a battery energy control method shown according to an exemplary embodiment;

[0042] Figure 3 is a flowchart of another battery energy control method shown according to an exemplary embodiment;

[0043] Figure 4 is a flowchart of another battery energy control method shown according to an exemplary embodiment;

[0044] Figure 5 is a flowchart of another battery energy control method shown according to an exemplary embodiment;

[0045] Figure 6 is a block diagram of a battery energy control device shown according to an exemplary embodiment;

[0046] Figure 7 is a block diagram of an electronic device shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0048] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of this application are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0049] In the embodiments of this application, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, article or device including that element.

[0050] In the embodiments of this application, words such as "exemplary" or "for example" are used to mean for example, illustration or explanation. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0051] As a core component of new energy vehicles, the battery directly affects the performance, safety and endurance of the vehicle. Therefore, the energy control of the battery is particularly important. Most of the existing battery energy control methods predict the driving energy consumption of the vehicle based on cloud vehicle network data and road data. Since the existing battery energy control methods do not take into account that when the battery is close to full charge, the braking effect of the vehicle weakens and the energy recovery space is insufficient.

[0052] In the related art, a topological structure diagram of a driving route is constructed based on road condition parameter information, starting position and target position, and the topological structure diagram is searched using a target search model to obtain the driving route, only determining the driving route of the vehicle, so that the vehicle is on the driving route with the minimum energy consumption to improve the energy utilization rate of the vehicle. However, when improving the energy utilization rate of the vehicle, only the optimization of the driving route is concerned, ignoring the impact of excessive optimization of the energy utilization rate on the energy recovery function, thus affecting the driving experience of users.

[0053] In view of this, the present application provides a battery energy control method. Based on the road section information of the target road section, it can more accurately estimate the estimated energy consumption information corresponding to the vehicle driving in the target road section. Furthermore, based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road section, it can more accurately predict the operation data of the vehicle after driving the target road section. Further, based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road section, the power battery of the vehicle is controlled to release energy, which can improve the energy utilization rate while reserving space for energy recovery of the vehicle, and avoid suppressing the energy recovery function to prevent overcharging when the power battery has too much energy. That is to say, the battery energy control method provided by the present application can ensure the normal operation of the energy recovery function, thereby improving the braking effect during the driving of the vehicle, further reducing the use of mechanical braking, and better improving the driving experience and energy recovery efficiency of users.

[0054] For ease of understanding, the battery energy control method provided by the present application is specifically introduced below with reference to the accompanying drawings.

[0055] The battery energy control method provided by the present application can be applied to a Figure 1 battery energy control system as shown. The battery energy control system includes: a collector 110, a battery energy control device 120, and a power battery 130. Among them, the collector 110 is connected to the battery energy control device 120, and the battery energy control device 120 is connected to the power battery 130.

[0056] As a feasible implementation manner, the battery energy control device 120 can be connected to multiple collectors 110 through a Controller Area Network (CAN) bus to obtain the operation data of the vehicle in real time.

[0057] It should be understood that the CAN bus is a serial communication bus for real-time applications with high reliability. With its high reliability, real-time performance, and flexibility, the CAN bus forms an efficient information communication network inside the vehicle to improve the timeliness of vehicle operation data.

[0058] In some embodiments, the collector 110 is used to collect the real-time operation data of the vehicle.

[0059] Among them, the real-time operation data of the vehicle includes: vehicle speed, battery power, and ambient temperature.

[0060] The present application embodiment does not limit the specific form of the collector 110. The collector 110 can be any device capable of collecting the real-time operation data of the vehicle. Exemplarily, the collector 110 can include a speed sensor, a voltage sensor, a temperature sensor, etc.

[0061] In some embodiments, the battery energy control device 120 is configured to control the power battery 130 of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment. For example, the battery energy control device 120 estimates the estimated energy consumption information corresponding to the vehicle's travel in the target road segment based on the road segment information of the target road segment; and controls the power battery of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment.

[0062] It should be understood that the battery energy control device 120 can be any device or equipment that can estimate energy consumption information, such as a server cluster composed of multiple servers, or a single server, or a computer, or a processor or processing chip in a server or computer. The embodiments of the present application do not limit this.

[0063] In some embodiments, the battery energy control device 120 can also be connected to the control unit in the vehicle. For example, the battery energy control device 120 sends an instruction to the air-conditioning control unit, and the instruction is used to instruct the air-conditioning control unit to control the operation of the air conditioner so that the air conditioner operation consumes the power of the power battery, that is, to realize the energy release of the power battery.

[0064] It should be noted that the system architecture described in the embodiments of the present application is for more clearly explaining the technical solutions of the embodiments of the present application, and does not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art know that with the evolution of the system architecture, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0065] The battery energy control method provided by the embodiments of the present application can be applied to Figure 1 the battery energy control device in the battery energy management system as shown in Figure 2 As shown, the battery energy control method specifically includes the following steps:

[0066] S201. Estimate the estimated energy consumption information corresponding to the vehicle's travel in the target road segment based on the road segment information of the target road segment.

[0067] As a feasible implementation, the road segment information includes at least one of the following: road segment length, road segment slope, road segment saturation, and estimated travel time.

[0068] It should be understood that the road segment length is used to represent the total length of the target road segment. The road segment length can directly affect the energy information consumed by the vehicle during travel on the target road segment, and the road segment length is proportional to the energy information consumed by the vehicle passing through the target road segment. Therefore, the estimated energy consumption information corresponding to the vehicle's travel in the target road segment can be estimated based on the road segment length of the target road segment.

[0069] The road section gradient is used to characterize the angle of the target road section relative to the horizontal plane. The road section gradient determines the energy information consumed by the vehicle to overcome the gravitational force. Therefore, the estimated energy consumption information corresponding to the vehicle traveling in the target road section can be estimated based on the road section gradient of the target road section.

[0070] The road section saturation is used to characterize the traffic conditions of the target road section. The road section saturation directly affects the stop-and-go frequency of the vehicle when passing through the target road section. When the road section saturation is too high, it may cause the vehicle to accelerate multiple times, thereby affecting the energy information consumed by the vehicle during the driving process in the target road section. Therefore, the estimated energy consumption information corresponding to the vehicle traveling in the target road section can be estimated based on the road section saturation of the target road section.

[0071] The road section saturation can include: unobstructed, slow-moving, crowded, congested; or, the road section saturation can be set in the form of a percentage, such as 0% - 100%; or, the road section saturation can be represented by a congestion index. It should be noted that the specific manifestation form of the road section saturation can be set based on specific habits, and the present application does not limit the specific form of the road section saturation.

[0072] The estimated travel time is used to characterize the time required for the vehicle to travel in the target road section. The estimated travel time can affect the usage time of the vehicle's air conditioner or other equipment in the target road section, thereby affecting the energy information consumed by the vehicle during the driving process in the target road section. Therefore, the estimated energy consumption information corresponding to the vehicle traveling in the target road section can be estimated based on the estimated travel time of the target road section.

[0073] It should be noted that the road section information can obtain real-time road section information through the vehicle's built-in navigation system or a third-party map application. Or, the road section information can also be determined by collecting the longitude and latitude information of the road section by a collector and combining it with a third-party map application.

[0074] It should be understood that after obtaining the road section information of the target road section, the energy consumed by the vehicle passing through the target road section is predicted based on the road section information to obtain the estimated energy consumption information.

[0075] As a feasible implementation method, the target road section can be determined based on the following two methods:

[0076] Method 1: When the vehicle has a navigation path, the target road section is determined based on the navigation path.

[0077] As a feasible implementation method, the navigation path is used to characterize the driving path of the vehicle selected by the user in the vehicle's built-in navigation system or a third-party map application.

[0078] It can be understood that in the presence of a navigation path, the path that the vehicle is expected to travel is determined. Therefore, the target section can be determined based on the navigation path, and then the section information of the target section in the navigation path can be directly obtained to estimate the estimated energy consumption information corresponding to the vehicle's travel in the target section.

[0079] Method 2: In the case where the vehicle does not have a navigation path, the target section is determined based on the topological road network where the vehicle is located.

[0080] In some embodiments, a topological road network can be constructed based on the actual existing sections around the vehicle with the vehicle's current position as the center.

[0081] As a feasible implementation method, the topological road network can include: nodes, intersections, and the roads between nodes. It should be understood that when determining the target section, it is necessary to determine the target node based on the current node where the vehicle is located, and then determine the target section based on the target node.

[0082] As an implementation method, the target node is the node reached by the vehicle after traveling a distance greater than or equal to a preset distance threshold from the current node. It should be understood that the target node is the node that the vehicle may reach after traveling the preset distance threshold. Therefore, the estimated energy consumption information determined based on the target node can be used to represent the energy consumed by the vehicle when traveling the preset distance threshold.

[0083] It should be noted that the preset distance threshold can be determined based on the complexity of the section. For sections with higher complexity, the estimated energy consumption information changes rapidly during the vehicle's travel. To improve the accuracy of the estimated energy consumption information, a smaller preset distance threshold can be set to avoid excessive errors; for sections with lower complexity, the estimated energy consumption information changes slowly during the vehicle's travel, and a larger preset distance threshold can be set to reduce computing resources. Exemplarily, the preset distance threshold can be 5KM.

[0084] After determining the target node in the topological road network, the target section can be determined based on the section information between the target node and the current node. The specific implementation process can be referred to in the following embodiments.

[0085] It can be understood that when there is a navigation path, the target section is determined based on the navigation path, and when there is no navigation path, the target section is determined based on the topological road network where the vehicle is located, considering two possibilities of whether there is a navigation path, thereby improving the versatility and flexibility of the battery energy control method provided in this application.

[0086] S202: Control the energy release of the vehicle's power battery based on the vehicle's real-time operation data and the estimated energy consumption information corresponding to the target section.

[0087] It should be understood that the power battery is used to provide the required power output for the vehicle. Or, during the braking process of the vehicle, the power battery can recover part of the kinetic energy through the energy recovery system and convert the kinetic energy into electrical energy for storage in the battery.

[0088] As a feasible implementation method, the real-time operation data may include: vehicle speed, battery power, and ambient temperature.

[0089] It should be understood that based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target section, the remaining battery power information of the vehicle's power battery when driving on the target section can be estimated. Based on the estimated battery power information, it can be determined whether the vehicle will be in a state close to full charge. If the vehicle is in a state close to full charge, during driving on the target section, the power battery can be controlled to actively release energy.

[0090] It should be noted that when the power battery is close to full charge, in order to prevent overcharging of the power battery, the energy recovery function of the energy recovery system will be inhibited, resulting in the energy recovery system being unable to work properly, affecting the energy recovery efficiency and causing waste of some energy. Therefore, when the vehicle is in a state close to full charge, the power battery needs to be controlled to actively release energy.

[0091] As another feasible implementation method, controlling the power battery of the vehicle to release energy can be: in a low-temperature environment, the power battery can be used to heat other batteries in the vehicle, which can reduce the energy of the power battery while improving the operating efficiency of other batteries; or, in a high-temperature environment, the power of the air conditioner can be increased through the power battery to improve the riding comfort of users.

[0092] As a feasible implementation method, based on the real-time operation data and the estimated energy consumption information corresponding to the target section, the estimated battery power information of the vehicle's power battery during driving is determined; when the estimated battery power information is greater than or equal to the preset battery power threshold, the power battery of the vehicle is controlled to release energy. For the specific implementation method, refer to the following steps S2021~S2022, which will not be elaborated here.

[0093] It can be understood that based on the road segment information of the target road segment, the estimated energy consumption information corresponding to the vehicle driving in the target road segment can be more accurately estimated. The real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road segment can intuitively display the operation data of the vehicle after driving the target road segment. Furthermore, the power battery of the vehicle can be controlled to release energy, while improving the energy utilization rate and reserving space for energy recovery for the vehicle, so as to avoid suppressing the energy recovery function in order to prevent overcharging when the power battery has too much energy. That is to say, the battery energy control method provided by this application can ensure the normal operation of the energy recovery function, thereby improving the braking effect of the vehicle during driving, and then reducing the use of mechanical braking, and better improving the user's driving experience and energy recovery efficiency.

[0094] In some embodiments, in order to more accurately control the power battery of the vehicle to release energy, the power consumption information of the power battery within a future period of time can be determined first, and then the battery can be controlled based on the power consumption information.

[0095] As a feasible implementation method, as Figure 3 shown, the above step S202 can be specifically implemented as the following steps:

[0096] S2021. Based on the real-time operation data and the estimated energy consumption information corresponding to the target road segment, determine the estimated power consumption information of the power battery when the vehicle is driving.

[0097] It should be understood that the estimated power consumption information is used to represent the estimated remaining power consumption information of the vehicle after driving the target road segment.

[0098] Exemplarily, the estimated power consumption information of the power battery when the vehicle is driving can be determined according to the difference between the real-time power consumption information of the vehicle and the estimated energy consumption information (that is, the power consumption for driving the target road segment).

[0099] As a feasible implementation method, the above step S2021 can be specifically implemented as the following steps:

[0100] Sa1. Update the estimated energy consumption information based on the real-time operation data.

[0101] It should be noted that as the vehicle operation data changes, the energy consumption information of the vehicle in the target road segment may change. Therefore, the estimated energy consumption information can be updated after the vehicle has driven for a preset time interval. Exemplarily, the preset time interval can be determined based on the vehicle speed. For example, the preset time interval is 5 minutes.

[0102] Sa2. Based on the updated estimated energy consumption information and the real-time power consumption of the power battery, determine the estimated power consumption information of the power battery when the vehicle is driving.

[0103] It should be understood that the estimated power information of the power battery changes with the change of the estimated energy consumption information and the real-time power of the power battery. Therefore, after the estimated energy consumption information is updated, it is necessary to re-determine the estimated power information of the power battery when the vehicle is running to improve the timeliness of battery energy control.

[0104] It can be understood that by combining multiple factors such as the vehicle speed, battery power, and ambient temperature to update the estimated energy consumption information in real time, the accuracy of the estimated energy consumption information can be effectively improved. Furthermore, based on the updated estimated energy consumption information and the real-time power of the power battery, the estimated power information of the power battery can be determined in real time as the vehicle runs, improving the flexibility and timeliness of the estimated power information.

[0105] S2022. When the estimated power information is greater than or equal to the preset power threshold, control the power battery of the vehicle to release energy.

[0106] Among them, the preset power threshold is used to represent the maximum remaining power at which the power battery can perform energy recovery. Exemplarily, the preset power threshold can be determined based on the specific type and performance of the power battery, and the embodiments of the present application do not limit the preset power threshold.

[0107] It should be noted that when the vehicle is in a fully charged state and the estimated energy consumption information corresponding to the target road section of the vehicle is small, it can be determined that the estimated power information of the power battery when the vehicle is running is too large, resulting in the estimated power information being greater than or equal to the preset power threshold. To prevent overcharging of the battery, the energy recovery function of the vehicle will be inhibited, thus affecting the braking and energy recovery efficiency of the vehicle. Based on this, it is necessary to control the power battery of the vehicle to release energy to reserve space for the vehicle to perform energy recovery.

[0108] It can be understood that the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road section can more accurately estimate the energy consumption information. If the estimated power information is greater than or equal to the preset power threshold, that is, the power of the power battery is close to the full charge state, control the power battery of the vehicle to release energy to reserve space for energy recovery of the vehicle, and avoid inhibiting the energy recovery function to prevent excessive charging when the power of the power battery is too much, thereby improving the braking effect of the vehicle during driving, reducing the use of mechanical braking, and better enhancing the driving experience of the vehicle.

[0109] In some embodiments, when there is no navigation path for the vehicle, it is necessary to determine the corresponding target road section and the estimated energy consumption information of the target road section based on the topological road network where the vehicle is located.

[0110] As a feasible implementation method, the topological road network includes multiple road nodes; when there is no navigation path for the vehicle, such as Figure 4As shown, the above step S201 can be specifically implemented as the following steps:

[0111] S2011. Determine the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network.

[0112] Wherein, the driving section is the section between two road nodes.

[0113] As a feasible implementation manner, determine the weight corresponding to the driving section based on the section information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient. The weight can be used to characterize the estimated energy consumption information of the vehicle on the driving section.

[0114] Wherein, the section information of the driving section includes: section length, section slope, and section saturation.

[0115] Specifically, as an implementation manner, after obtaining the section information of the driving section, the slope correction coefficient and the traffic condition correction coefficient can be determined according to the section slope and the section saturation in the section information of the driving section.

[0116] Exemplarily, the section length is determined based on the section distance between two road nodes. The section length has a positive correlation with the estimated energy consumption information. It should be noted that the section length can be divided by itself according to the nodes in the topological road network, and the embodiments of the present application do not make limitations thereto. Among them, the nodes in the topological road network can be intersections existing in the map; or, the nodes in the topological road network can be the roads in the map divided by length.

[0117] Exemplarily, the slope correction coefficient is determined based on the slope of the driving section. For example, when the driving section is an uphill section, as the slope increases, the power battery is estimated to consume more energy, and the slope correction coefficient takes a positive value and decreases as the slope increases; when the driving section is a downhill section, the vehicle can recover energy, and the power battery is estimated to consume less energy, and the slope correction coefficient takes a negative value and increases as the slope increases. The slope correction coefficient is used to represent the energy consumed by the power battery to overcome gravity during the driving process of the vehicle and the energy that can be recovered. It should be noted that the setting of the slope correction coefficient can be determined according to the performance of the power battery and set by the user, and the embodiments of the present application do not make limitations thereto.

[0118] Exemplarily, the traffic condition correction coefficient is determined based on the saturation of the driving section. For example, assume that when the saturation of the driving section is smooth, the traffic condition correction coefficient is 10%; assume that when the saturation of the driving section is slow, the traffic condition correction coefficient is 40%; assume that when the saturation of the driving section is crowded, the traffic condition correction coefficient is 70%; assume that when the saturation of the driving section is congested, the traffic condition correction coefficient is 100%. It should be noted that the value setting of the traffic condition correction coefficient can be determined according to the actual situation, and the present application does not limit this.

[0119] In some embodiments, the energy recovery efficiency coefficient can be determined based on the real-time operation data of the vehicle, where the real-time operation data includes: vehicle speed, battery power, and ambient temperature.

[0120] Exemplarily, the energy recovery efficiency coefficient is determined through a preset correspondence relationship between the vehicle speed, battery power, ambient temperature and the energy recovery efficiency coefficient. The preset correspondence relationship is used to represent the energy recovery efficiency coefficients corresponding to different vehicle speeds, battery powers, and ambient temperatures respectively.

[0121] For example, assume that when the vehicle speed on the driving section is less than or equal to 80 km / h, the battery power is less than or equal to 90%, and the ambient temperature is greater than or equal to 0 °C, the energy recovery efficiency coefficient is 60%; assume that when the vehicle speed on the driving section is greater than 80 km / h, the battery power is less than or equal to 90%, and the ambient temperature is greater than or equal to 0 °C, the energy recovery efficiency coefficient is 40%; assume that when the vehicle speed on the driving section is less than or equal to 80 km / h, the battery power is greater than 90%, and the ambient temperature is greater than or equal to 0 °C, the energy recovery efficiency coefficient is 40%; assume that when the vehicle speed on the driving section is less than or equal to 80 km / h, the battery power is greater than 90%, and the ambient temperature is less than 0 °C, the energy recovery efficiency coefficient is 30%. It should be noted that the preset correspondence relationship between the energy recovery efficiency coefficient and the vehicle speed, battery power, and ambient temperature can be set according to the actual situation of the vehicle, and the present application does not limit this.

[0122] In some embodiments, the energy recovery efficiency coefficient is determined based on the vehicle speed, battery power, and ambient temperature of the vehicle.

[0123] In some embodiments, the historical energy consumption data of the vehicle is determined based on the driving behavior data. Among them, the driving behavior data can include: user driving habits and historical energy consumption data.

[0124] As a feasible implementation method, the user's driving habits are defined as multiple driving behavior tags, and calibration parameters are obtained by fitting based on each driving behavior tag and historical energy consumption data. Exemplarily, the calibration parameters are used to dynamically correct the energy recovery efficiency coefficient and road section information, and improve the accuracy of the weight.

[0125] Exemplarily, it is assumed that multiple driving behavior tags include: vehicle rapid acceleration frequency, speed fluctuation frequency, ramp handling method, driving mode in congested sections, and other tags, and the historical energy consumption data includes: air conditioner usage intensity and regenerative braking utilization rate, etc. Different corresponding relationships are set among the driving behavior tags, historical energy consumption data, and calibration parameters, and the corresponding relationships can be determined based on different users and vehicle performances, which are not limited in the embodiments of the present application.

[0126] As another feasible implementation method, the weight of the driving section can be determined by the following formula (1):

[0127] W ij = L ij ×(1 + α·S ij )×(1 + β·T ij )×(1 - γ·R ij ) Formula (1)

[0128] wherein, W ij is used to represent the weight of the driving section, α, β, and γ are used to represent calibration parameters, L ij is used to represent the section length, S ij is used to represent the slope correction coefficient, T ij is used to represent the traffic condition correction coefficient, and R ij is used to represent the energy recovery efficiency coefficient.

[0129] It can be understood that by combining multiple factors such as the section information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient, the weight corresponding to the driving section is determined more comprehensively, improving the accuracy of the battery energy control method.

[0130] S2012. Determine the target section based on the weight corresponding to each driving section, and the current node and target node where the vehicle is located.

[0131] wherein, the target node is a node whose distance from the current node is greater than or equal to a preset distance threshold. That is to say, in the topological road network, a node whose distance from the current node is greater than or equal to the preset distance threshold is used as the target node. Since the target node can represent the node reached after the vehicle travels the preset distance threshold, the target section can be determined based on the target node.

[0132] Exemplarily, the specific implementation method of the preset distance threshold can refer to the above step S201 and will not be elaborated here.

[0133] Exemplarily, the target node is a node with the lowest weight among the driving sections corresponding to multiple second nodes, and the current node is the first node.

[0134] As a feasible implementation method, based on the weight corresponding to each driving section, the Dijkstra's Algorithm is used to determine the target section. Exemplarily, the Dijkstra's Algorithm can determine the driving section with the minimum weight from the weights corresponding to each driving section.

[0135] Exemplarily, the Dijkstra's Algorithm specifically includes the following steps: determining the current node where the vehicle is located (the current position of the vehicle), arranging multiple target nodes in ascending order of the section length based on the section lengths between the current node and the multiple target nodes currently, preferentially calculating and recording the weight corresponding to the driving section from the second node with the minimum section length to the current node, and sequentially calculating the weights corresponding to the driving sections from the second node to the current node in ascending order of the section length. If the calculated weight is less than the recorded weight, updating the recorded weight to the calculated weight, finally determining the target node with the lowest weight of the driving section, and further determining the target section.

[0136] As a feasible implementation method, S2012 can also be implemented as: based on the weight corresponding to each driving section, determining the section with the lowest weight among the sections from the current node to any target node in the topological road network as the target section.

[0137] It should be noted that determining the section with the lowest weight among the sections from the current node to any target node in the topological road network can determine the section with the lowest estimated energy consumption, and can estimate the lowest energy consumption of the vehicle. When the estimated power information is less than the preset power threshold during the vehicle's driving on the target section, the estimated power information for any driving section of the vehicle is less than the preset power threshold, that is, the vehicle can perform energy recovery. Therefore, the section with the lowest weight among the sections from the current node to any target node in the topological road network can be used as the target section.

[0138] It can be understood that determining the section with the lowest weight among the sections from the current node to any target node in the topological road network as the target section, the estimated energy consumption information of the vehicle on the target section is optimal, and when the vehicle's navigation information cannot be obtained, the battery in the vehicle can also be accurately controlled, improving the accuracy of the battery energy control method.

[0139] S2013: Determining the estimated energy consumption information corresponding to the target section based on the weight of the target section.

[0140] It should be understood that the weight of the target section is positively correlated with the estimated energy consumption information corresponding to the target section. That is to say, the higher the weight of the target section, the higher the estimated energy consumption information; the lower the weight of the target section, the lower the estimated energy consumption information.

[0141] It can be understood that by means of the road segment information in the topological road network, the corresponding weight of each driving road segment can be obtained. The weight can be used to obtain the estimated energy consumption information of the target road segment. A more accurate estimated energy consumption information can timely control the energy of the battery in the vehicle, improving the accuracy of the battery energy control method.

[0142] In some embodiments, since different users have different driving habits, different driving habits will result in different energy consumption. Therefore, when determining the estimated energy consumption information, the driving behavior data of the user can also be combined to make the determined estimated energy consumption information more accurate.

[0143] As another feasible implementation manner, the above step S201 can also be implemented as: based on the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle, estimate the corresponding estimated energy consumption information when the vehicle travels in the target road segment.

[0144] It should be noted that the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle are interrelated and jointly act on the energy consumption process of the vehicle. Therefore, the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle can improve the accuracy of the estimated energy consumption information and the accuracy of the battery energy control method.

[0145] It can be understood that by combining multiple factors such as the road segment information of the target road segment, the driving behavior data, and the real-time operation data of the vehicle, the estimated energy consumption information can be estimated more accurately, thereby improving the accuracy of the battery energy control method.

[0146] In some embodiments, please refer to Figure 5 , the overall process of the battery energy control method provided by the embodiment of the present application when executed includes the following steps:

[0147] S501. Determine whether there is a navigation path.

[0148] Exemplarily, in the case where the vehicle has a navigation path, jump to step S502; in the case where the vehicle does not have a navigation path, jump to step S503.

[0149] S502. Determine the target road segment based on the navigation path.

[0150] S503. Construct a topological road network.

[0151] Exemplarily, with the current position of the vehicle as the center, based on the actually existing road segments, determine the target nodes through a preset distance threshold to construct a topological road network.

[0152] S504. Determine the weight corresponding to the driving section based on the section information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient.

[0153] Exemplarily, the driving section is the section between two road nodes.

[0154] S505. Based on the weight corresponding to each driving section, determine the section with the lowest weight among the sections from the current node to any target node in the topological road network as the target section.

[0155] S506. Determine the estimated energy consumption information corresponding to the target section based on the weight of the target section.

[0156] S507. Control the energy release of the vehicle's power battery based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target section.

[0157] The above mainly introduces the solution provided by the embodiments of the present application from the perspective of the method. To implement the above functions, the battery energy control device or electronic device includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0158] The embodiments of the present application can, according to the above method, exemplarily divide the function modules of the battery energy control device or electronic device. For example, the battery energy control device or electronic device can include each function module corresponding to each function division, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of a software function module. It should be noted that the division of modules in the embodiments of the present application is illustrative, only a logical function division, and there can be other division methods in actual implementation.

[0159] Figure 6 The block diagram of a battery energy control device shown according to an exemplary embodiment. Refer to Figure 6, the battery energy control device 600 includes: an estimation module 601 and a processing module 602; the estimation module 601 is configured to estimate the estimated energy consumption information corresponding to the vehicle traveling on the target section based on the section information of the target section; the processing module 602 is configured to control the power battery of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target section.

[0160] In a possible implementation manner, the processing module 602 is specifically configured to determine the estimated power consumption information of the power battery when the vehicle is traveling based on the real-time operation data and the estimated energy consumption information corresponding to the target section; and control the power battery of the vehicle to release energy when the estimated power consumption information is greater than or equal to a preset power threshold.

[0161] In a possible implementation manner, the real-time operation data includes: vehicle speed, battery power, and ambient temperature; the processing module 602 is specifically configured to update the estimated energy consumption information based on the real-time operation data; and determine the estimated power consumption information of the power battery when the vehicle is traveling based on the updated estimated energy consumption information and the real-time battery power of the power battery.

[0162] In a possible implementation manner, when the vehicle has a navigation path, the target section is determined based on the navigation path; and / or, when the vehicle does not have a navigation path, the target section is determined based on the topological road network where the vehicle is located.

[0163] In a possible implementation manner, the topological road network includes multiple road nodes; the estimation module 601 is specifically configured to determine the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network; the driving section is the section between two road nodes; determine the target section based on the weight corresponding to each driving section, and the current node and the target node where the vehicle is located; the target node is a node whose distance from the current node is greater than or equal to a preset distance threshold; determine the estimated energy consumption information corresponding to the target section based on the weight of the target section.

[0164] In a possible implementation manner, the estimation module 601 is specifically configured to determine the section with the lowest weight among the sections from the current node to any target node in the topological road network based on the weight corresponding to each driving section, as the target section.

[0165] In a possible implementation manner, the estimation module 601 is specifically configured to determine the weight corresponding to each driving section based on the weight corresponding to each driving section, the section information of the driving section, the historical energy consumption data of the vehicle, and the energy recovery efficiency coefficient.

[0166] In a possible implementation, the estimation module 601 is specifically configured to estimate the estimated energy consumption information corresponding to the vehicle traveling on the target road section based on the road section information of the target road section, the driving behavior data, and the real-time operation data of the vehicle.

[0167] In a possible implementation, the road section information includes at least one of the following: road section length, road section slope, road section saturation, estimated travel time; and / or, the driving behavior data includes: user driving habits and historical energy consumption data.

[0168] Figure 7 It is a block diagram of an electronic device shown according to an exemplary embodiment. As Figure 7 shown, the electronic device 700 includes, but is not limited to: a processor 701 and a memory 702.

[0169] Among them, the above-mentioned memory 702 is used to store the executable instructions of the above-mentioned processor 701. It can be understood that the above-mentioned processor 701 is configured to execute instructions to implement the battery energy control method in the above-mentioned embodiment.

[0170] It should be noted that those skilled in the art can understand that Figure 7 the structure of the electronic device shown in Figure 7 does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than

[0171] shown, or combine some components, or have different component arrangements.

[0171] The processor 701 is the control center of the electronic device, connecting various parts of the entire electronic device through various interfaces and lines. By running or executing the software programs and / or modules stored in the memory 702, and calling the data stored in the memory 702, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. The processor 701 may include one or more processing units. Optionally, the processor 701 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 701 either.

[0172] The memory 702 can be used to store software programs and various data. The memory 702 may mainly include a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required by at least one functional module (such as a determination unit, a processing unit, etc.). In addition, the memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0173] In an exemplary embodiment, a computer-readable storage medium including instructions is further provided, such as a memory 702 including instructions, and the above instructions can be executed by a processor 701 of an electronic device 700 to implement the energy control method in the above embodiment.

[0174] In actual implementation, Figure 6 the functions of the estimation module 601 and the processing module 602 in Figure 7 can be implemented by the processor 701 in

[0175] calling a computer program stored in the memory 702. The specific execution process can refer to the description of the method part in the above embodiment, which will not be elaborated here.

[0176] In an exemplary embodiment, the present application embodiment further provides a computer program product including one or more instructions, and the one or more instructions can be executed by a processor 701 of an electronic device to complete the battery energy control method in the above embodiment.

[0177] It should be noted that when the instructions in the above computer-readable storage medium or the one or more instructions in the computer program product are executed by the processor of the electronic device, the various processes of the above method embodiment are implemented, and the same technical effects as the above method can be achieved. To avoid repetition, it will not be elaborated here.

[0178] Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above division of each functional module is used as an example. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0179] In several embodiments provided by this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0180] The units described as separate components may or may not be physically separated. The components displayed as units may be one physical unit or multiple physical units, that is, they can be located in one place, or they can be distributed to multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0181] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0182] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods of the embodiments of this application. The aforementioned storage medium includes: USB flash drives, mobile hard disks, ROM, RAM, magnetic disks or optical discs and other various media that can store program codes.

[0183] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A battery energy control method, characterized in that: include: estimating estimated energy consumption information corresponding to the vehicle traveling in the target road section based on the road section information of the target road section; Based on the real-time operating data of the vehicle and the estimated energy consumption information corresponding to the target road section, the power battery of the vehicle is controlled to release energy.

2. The method according to claim 1, characterized in that The controlling the power battery of the vehicle to release energy based on the real-time operation data of the vehicle and the estimated energy consumption information corresponding to the target road section includes: Determining estimated power information of the power battery when the vehicle is traveling based on the real-time operating data and the estimated energy consumption information corresponding to the target road section; When the estimated power information is greater than or equal to a preset power threshold, the power battery of the vehicle is controlled to release energy.

3. The method according to claim 2, characterized in that The real-time operation data includes at least one of the following: vehicle speed, power, and ambient temperature; the estimated power information of the power battery when the vehicle is traveling is determined based on the real-time operation data and the estimated energy consumption information corresponding to the target road section, including: updating the estimated energy consumption information based on the real-time operation data; Based on the updated estimated energy consumption information and the real-time power level of the power battery, the estimated power level information of the power battery when the vehicle is traveling is determined.

4. The method according to claim 1, characterized in that In the case where the vehicle has a navigation path, the target road section is determined based on the navigation path; and / or, In the case that there is no navigation path for the vehicle, the target road section is determined based on the topological road network where the vehicle is located.

5. The method according to claim 4, characterized in that The topological road network includes a plurality of road nodes; when the vehicle does not have a navigation path, the estimated energy consumption information corresponding to the vehicle traveling in the target road section based on the road section information of the target road section includes: Determine a weight corresponding to each driving section based on section information of one or more driving sections in the topological road network; the driving section is a section between two road nodes; Determine the target road section based on the weight corresponding to each of the driving road sections, as well as the current node and the target node where the vehicle is located; the target node is a node whose distance from the current node is greater than or equal to a preset distance threshold; The estimated energy consumption information corresponding to the target section is determined based on the weight of the target section.

6. The method according to claim 5, characterized in that The determining the target road section based on the weight corresponding to each of the driving road sections, and the current node and the target node where the vehicle is located, comprises: Based on the weight corresponding to each of the driving sections, a section with the lowest weight among the sections starting from the current node and reaching at least one second node in the topological road network is determined as the target section.

7. The method according to claim 5, characterized in that The determining of the weight corresponding to each driving section based on the section information of one or more driving sections in the topological road network includes: The weight corresponding to the driving section is determined based on the section information of the driving section, the historical energy consumption data of the vehicle and the energy recovery efficiency coefficient.

8. The method according to claim 1, characterized in that The method of estimating the estimated energy consumption information corresponding to the vehicle traveling in the target road section based on the road section information of the target road section includes: Based on the road section information of the target road section, the driving behavior data and the real-time operation data of the vehicle, the estimated energy consumption information corresponding to the vehicle traveling in the target road section is estimated.

9. The method according to claim 8, characterized in that The road section information includes at least one of the following: road section length, road section slope, road section saturation, and estimated travel time; And / or, the driving behavior data includes: user driving habits and historical energy consumption data.

10. A battery energy control device, characterized in that: include: Estimation module and processing module; The estimation module is used to estimate the estimated energy consumption information corresponding to the vehicle traveling in the target road section based on the road section information of the target road section; The processing module is used to control the power battery of the vehicle to release energy based on the real-time operating data of the vehicle and the estimated energy consumption information corresponding to the target road section.

11. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable a computer device to implement the battery energy control method as described in any one of claims 1 to 9.

12. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 11.

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