Energy management strategy determination method, apparatus, device, and storage medium

Abstract

The present disclosure provides an energy management strategy determination method, device, equipment and storage medium, which can be applied to the field of hybrid electric vehicles. The method comprises: dividing a driving path of a target vehicle to obtain a plurality of path intervals; based on a preset energy management rule, simulating the driving of the target vehicle in each path interval multiple times by using a vehicle dynamics model to obtain a plurality of working condition information of the target vehicle in each path interval; for each path interval, determining a plurality of operating working condition parameters of the target vehicle in the path interval from an energy consumption distribution map according to the plurality of working condition information; determining a target working condition parameter corresponding to the path interval from the plurality of operating working condition parameters; and combining the working condition information corresponding to the target working condition parameter in each path interval to obtain an energy management strategy of the target vehicle on the driving path.

Description

Technical Field

[0001] This disclosure relates to the field of hybrid electric vehicles, and more particularly to a method, apparatus, device, and storage medium for determining an energy management strategy. Background Technology

[0002] With energy and environmental pollution becoming increasingly serious problems, hybrid vehicles have become the main energy-saving mode of transportation. Hybrid vehicles use one or more generators to work in conjunction with the engine, thereby reducing fuel consumption during driving.

[0003] In the process of realizing the concept of this invention, the inventors discovered that the related technology has at least the following problems: when a hybrid electric vehicle provides power to the vehicle through the cooperation of a generator and an engine, the torque fluctuation generated by the generator in the working range is large, resulting in low stability of the vehicle during operation. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a method, apparatus, device, storage medium and program product for determining energy management strategies.

[0005] According to a first aspect of this disclosure, a method for determining an energy management strategy is provided, comprising:

[0006] The driving path of the target vehicle is divided into multiple path intervals;

[0007] Based on the preset energy management rules, the vehicle dynamics model is used to simulate the driving of the target vehicle in each of the above-mentioned path intervals multiple times, so as to obtain multiple operating condition information of the target vehicle in each of the above-mentioned path intervals.

[0008] For each of the above-mentioned path intervals, based on the above-mentioned operating condition information, multiple operating condition parameters of the target vehicle in the above-mentioned path intervals are determined from the energy consumption distribution map.

[0009] Determine the target operating condition parameter corresponding to the above path interval from multiple operating condition parameters mentioned above;

[0010] By combining the operating condition information corresponding to the target operating condition parameters in each of the above path intervals, the energy management strategy of the target vehicle on the above driving path is obtained.

[0011] According to embodiments of this disclosure, based on preset energy management rules, the vehicle dynamics model is used to perform multiple simulations of the target vehicle's driving in each of the aforementioned path intervals, obtaining multiple operating condition information of the target vehicle in each of the aforementioned path intervals, including:

[0012] Based on the aforementioned preset energy management rules, the engine parameter range and generator parameter range of the target vehicle are determined.

[0013] Based on the aforementioned engine parameter range and generator parameter range, the vehicle dynamics model is used to perform multiple simulations of the target vehicle's driving in each of the aforementioned path ranges, thereby obtaining multiple operating condition information of the target vehicle in each of the aforementioned path ranges. The operating condition information includes engine parameters and generator parameters, wherein the engine parameters are within the aforementioned engine parameter range and the generator parameters are within the aforementioned generator parameter range.

[0014] According to embodiments of this disclosure, the energy consumption distribution map includes a fuel consumption distribution map and a speed fluctuation distribution map, and further includes:

[0015] The driving state of the target vehicle is simulated using the vehicle dynamics model described above to obtain driving information, which includes multiple rotational speeds of the target vehicle and the torque corresponding to each rotational speed.

[0016] Based on the multiple speeds and the torque corresponding to each speed in the above driving information, the above fuel consumption distribution map is generated.

[0017] According to embodiments of this disclosure, the above-mentioned speed fluctuation distribution map is generated in the following manner:

[0018] The above driving information is divided into T cycles.

[0019] For a given cycle, multiple rotational speeds within that cycle are sampled to obtain multiple rotational speed sampling points;

[0020] Using the rotational speed corresponding to each of the above rotational speed sampling points and the total number of cycles T, the rotational speed fluctuation value of the target vehicle in the above cycle is determined;

[0021] Based on the speed fluctuation values ​​of the target vehicle in each of the aforementioned cycles, the aforementioned speed fluctuation distribution map is generated.

[0022] According to embodiments of this disclosure, the aforementioned operating condition parameters include fuel consumption and speed fluctuation values. The determination of multiple operating condition parameters of the target vehicle within the aforementioned path interval from the energy consumption distribution map based on multiple sets of operating condition information includes:

[0023] Based on the above operating condition information, the fuel consumption and speed fluctuation values ​​of the target vehicle are determined from the above fuel consumption distribution map and the above speed fluctuation distribution map, respectively, using an interpolation algorithm.

[0024] According to embodiments of this disclosure, determining the target operating condition parameter corresponding to the path interval from a plurality of the aforementioned operating condition parameters includes:

[0025] Determine the performance parameter corresponding to the minimum fuel consumption from the above operating condition parameters:

[0026] When the speed fluctuation value in the above performance parameters is the minimum value among multiple above operating condition parameters, the above performance parameters are determined as the above target operating condition parameters.

[0027] If the speed fluctuation value in the above performance parameters is not the minimum value among the above operating condition parameters, the average fuel consumption and the average fluctuation value are determined based on the above operating condition parameters.

[0028] The target operating condition parameters are determined based on the above average fuel consumption and the above average fluctuation.

[0029] According to embodiments of this disclosure, the combination of operating condition information corresponding to the target operating condition parameters in each of the aforementioned path intervals to obtain the energy management strategy for the target vehicle on the aforementioned driving path includes:

[0030] Determine the operating condition information corresponding to the target operating condition parameters in each of the above path intervals;

[0031] Based on the operating condition information of each of the above-mentioned path intervals, the driving mode of the target vehicle in each of the above-mentioned path intervals is determined, wherein the driving mode includes engine driving and generator driving.

[0032] The driving mode and the corresponding operating condition information of the target vehicle in each of the above-mentioned path intervals are combined to generate the energy management strategy of the target vehicle on the above-mentioned driving path.

[0033] Another aspect of this disclosure provides an energy management strategy determination apparatus, comprising:

[0034] The path segmentation module is used to divide the driving path of the target vehicle into multiple path intervals;

[0035] The driving simulation module is used to perform multiple simulations of the driving of the target vehicle in each of the above-mentioned path intervals based on preset energy management rules and using vehicle dynamics models, so as to obtain multiple operating condition information of the target vehicle in each of the above-mentioned path intervals.

[0036] The parameter determination module is used to determine, for each of the above-mentioned path intervals, multiple operating condition parameters of the target vehicle in the above-mentioned path intervals from the energy consumption distribution map based on multiple of the above-mentioned operating condition information.

[0037] The target determination module is used to determine the target operating condition parameters corresponding to the above-mentioned path interval from multiple operating condition parameters mentioned above.

[0038] The strategy generation module is used to combine the operating condition information corresponding to the target operating condition parameters in each of the above-mentioned path intervals to obtain the energy management strategy of the target vehicle on the above-mentioned driving path.

[0039] Another aspect of this disclosure provides an electronic device, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0040] Another aspect of this disclosure provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0041] Another aspect of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0042] According to the energy management strategy determination method, apparatus, equipment, medium, and program products provided in this disclosure, the driving path of the target vehicle is divided into multiple path intervals. Based on preset energy management rules, multiple simulations of the target vehicle's driving in these multiple path intervals are performed. The preset energy management rules determine operating condition information intervals with relatively small fluctuations in fuel consumption and engine speed. By simulating the target vehicle's driving in multiple path intervals, the accuracy of the simulated operating condition parameters can be ensured to a certain extent. Target operating condition parameters are determined based on the multiple operating condition parameters obtained from the simulation, and the energy management strategy for the target vehicle on the driving path is determined based on the operating condition information corresponding to these multiple target operating condition parameters. This allows for further optimization of the energy management strategy based on the target vehicle driving rules defined by the preset energy rules. While ensuring low fuel consumption of the target vehicle on the driving path, the stability of the target vehicle during driving is further improved. Attached Figure Description

[0043] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0044] Figure 1 This diagram illustrates an application scenario of the energy management strategy determination method according to an embodiment of the present disclosure.

[0045] Figure 2 A flowchart illustrating a method for determining an energy management strategy according to an embodiment of the present disclosure is shown schematically.

[0046] Figure 3 A schematic diagram of a vehicle dynamics model according to an embodiment of the present disclosure is shown.

[0047] Figure 4 A flowchart illustrating a method for determining an energy management strategy according to another embodiment of this disclosure is shown schematically;

[0048] Figure 5 A schematic block diagram of an energy management strategy determination device according to an embodiment of the present disclosure is shown; and

[0049] Figure 6 A block diagram of an electronic device suitable for implementing an energy management strategy determination method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0050] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0051] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0052] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0053] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0054] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0055] With the increasing severity of energy and environmental pollution problems, hybrid power has become an effective means of energy conservation and emission reduction. Hybrid electric vehicles (HEVs), as a major energy-saving mode of transportation, possess the advantages of rapid response found in electric vehicles, while emitting lower emissions compared to traditional vehicles. In a series hybrid system, the electric motor serves as the primary power source, while the internal combustion engine acts as an auxiliary power source. This allows the electric motor to operate at its optimal efficiency as needed, maximizing fuel savings and reducing emissions while ensuring power output. However, due to the inherent properties of the electric motor, internal combustion engine, and transmission structure, as well as errors during assembly, torque fluctuations are unavoidable during vehicle operation, leading to unstable driving. Therefore, how to ensure both energy efficiency and stable system operation still requires further exploration.

[0056] Torque ripple control methods are divided into two categories: active control and passive control. Active control involves observing the engine's output speed and torque, and controlling parameters such as fuel injection quantity and intake air quantity to ultimately achieve a stable output. Passive control mainly modifies the system's output characteristics by optimizing the engine structure or adding damping devices to achieve a stable output. Due to the complexity of engine structure and the variability of output characteristics, researchers generally use passive control methods for torque ripple control, such as adding flexible couplings. Compared to traditional engines, series hybrid vehicles add one or more generators, resulting in more complex vehicle system operating characteristics. When controlling torque ripple in series hybrid vehicles, the nonlinear operating characteristics of the generators must also be considered.

[0057] Based on the above explanation, it is clear that due to the nonlinear characteristics of generators and their components in vehicles, optimizing solely for minimum fuel consumption neglects the torque fluctuations generated by the generators and their components within the operating range. This torque fluctuation negatively impacts the fatigue life of the mechanical system and performance characteristics such as noise, vibration, and acoustic roughness. Therefore, it is necessary to design an energy management strategy determination method to improve the overall stability of the vehicle while ensuring energy efficiency.

[0058] The embodiments of this disclosure provide a method for determining an energy management strategy, including: dividing the driving path of a target vehicle into multiple path intervals; performing multiple simulations of the target vehicle's driving in each path interval using a vehicle dynamics model based on preset energy management rules to obtain multiple operating condition information of the target vehicle in each path interval; for each path interval, determining multiple operating condition parameters of the target vehicle in the path interval from an energy consumption distribution map based on the multiple operating condition information; determining the target operating condition parameter corresponding to the path interval from the multiple operating condition parameters; and combining the operating condition information corresponding to the target operating condition parameter in each path interval to obtain the energy management strategy of the target vehicle on the driving path.

[0059] Figure 1 The diagram illustrates an application scenario of the energy management strategy determination method according to an embodiment of the present disclosure.

[0060] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0061] Users can use at least one of the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103.

[0062] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0063] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0064] It should be noted that the energy management strategy determination method provided in this embodiment can generally be executed by server 105. Correspondingly, the energy management strategy determination device provided in this embodiment can generally be located in server 105. The energy management strategy determination method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the energy management strategy determination device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0065] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0066] The following will be based on Figure 1 The described scene, through Figures 2-6 The energy management strategy determination method of the disclosed embodiments is described in detail.

[0067] Figure 2 A flowchart illustrating a method for determining an energy management strategy according to an embodiment of the present disclosure is shown schematically.

[0068] like Figure 2 As shown, the energy management strategy determination method in this embodiment includes operations S210 to S250.

[0069] In operation S210, the driving path of the target vehicle is divided into multiple path intervals.

[0070] In operation S220, based on preset energy management rules, the vehicle dynamics model is used to perform multiple simulations of the target vehicle's driving in each path interval, obtaining multiple operating condition information of the target vehicle in each path interval.

[0071] In operation S230, for each path interval, based on multiple operating condition information, multiple operating condition parameters of the target vehicle in the path interval are determined from the energy consumption distribution map.

[0072] In operation S240, the target operating condition parameter corresponding to the path interval is determined from multiple operating condition parameters.

[0073] In operation S250, the operating condition information corresponding to the target operating condition parameters in each path interval is combined to obtain the energy management strategy of the target vehicle on the driving path.

[0074] According to embodiments of this disclosure, the path of a target vehicle is divided into multiple path intervals, and various methods are used to divide the path intervals. For example, the travel path can be divided into multiple path intervals according to road segments, or the travel path can be divided into multiple path intervals according to time intervals. This embodiment preferably uses the method of dividing the path intervals according to road segments, so that the travel path is divided into multiple path intervals relatively evenly.

[0075] According to embodiments of this disclosure, the vehicle dynamics model is constructed by simulation software based on the parameters of the target vehicle, and is used to simulate vehicle dynamics under different operating conditions. The parameters of the target vehicle may include the power of the engine and generator, transmission ratio, and the frictional force of the ground on the vehicle, etc.

[0076] Figure 3 A schematic diagram of a vehicle dynamics model according to an embodiment of the present disclosure is shown.

[0077] like Figure 3 As shown, the vehicle dynamics model is mainly divided into five modules: engine module 301, generator module 302, gearbox module 303, external load module 304, and base module 305. Engine module 301 simulates the engine of the target vehicle during operation; generator module 302 simulates the generator of the target vehicle during operation; gearbox module 303 simulates the mechanical connection between the engine, generator, and external load; external load module 304 simulates external loads requiring additional power from the engine; and base module 305 simulates the constraints exerted by the ground on the target vehicle, including friction forces.

[0078] According to embodiments of this disclosure, based on preset energy management rules, the driving of the target vehicle in each path interval is simulated multiple times using a vehicle dynamics model. The preset energy management rules are pre-defined parameter ranges for various operating conditions, including battery state of charge, engine speed, engine torque, generator speed, generator torque, initial battery state of charge, and final battery state of charge. The vehicle speed can be controlled using the generator speed and engine speed.

[0079] According to embodiments of this disclosure, multiple simulations of the target vehicle are performed on each path interval based on the vehicle dynamics model, which can obtain multiple operating condition information, enriching the amount of operating condition information for each path interval and improving the accuracy of subsequent selection of target operating condition parameters.

[0080] According to embodiments of this disclosure, the energy consumption distribution map can be a universal characteristic diagram (MAP) of the target vehicle's operating condition parameters under different speeds and vehicle loads. The operating condition parameters can include the target vehicle's fuel consumption and speed fluctuation values ​​during driving. Multiple fuel consumption values ​​for the target vehicle within a path interval can be determined from the universal characteristic diagram (MAP) of fuel consumption based on multiple operating condition information. Similarly, multiple speed fluctuation values ​​for the target vehicle within a path interval can be determined from the universal characteristic diagram (MAP) of speed fluctuation values ​​based on multiple operating condition information. The universal characteristic diagram corresponding to fuel consumption can at least represent the correspondence between fuel consumption and speed / torque, and the universal characteristic diagram corresponding to speed fluctuation values ​​can at least represent the correspondence between speed fluctuation values ​​and speed / torque.

[0081] According to embodiments of this disclosure, target operating parameters are determined from multiple operating parameters obtained through multiple simulations of each path interval. These target operating parameters include the minimum fuel consumption of the target vehicle and the minimum speed fluctuation value corresponding to the minimum fuel consumption. The relationship between the target operating parameters and operating information for each path interval can be obtained from the energy consumption diagram, thereby determining the operating information corresponding to the target operating parameters.

[0082] According to embodiments of this disclosure, a preferred energy management strategy for the current path interval is determined based on the operating condition information corresponding to the target operating condition parameters. The energy management strategy for the entire driving path can be determined by combining the operating condition information from different path intervals to obtain a combination of operating condition information that simultaneously satisfies the minimum fuel consumption and the minimum speed fluctuation, thereby determining the energy management strategy for the target vehicle on the driving path.

[0083] According to embodiments of this disclosure, the driving path of the target vehicle is divided into multiple path intervals. Based on preset energy management rules, multiple simulations are performed on the target vehicle's driving within these multiple path intervals. The preset energy management rules determine operating condition information intervals with relatively small fluctuations in fuel consumption and engine speed. By simulating the target vehicle's driving within multiple path intervals, the accuracy of the simulated operating condition parameters can be ensured to a certain extent. Target operating condition parameters are determined based on the multiple operating condition parameters obtained from the simulation, and the energy management strategy for the target vehicle on the driving path is determined based on the operating condition information corresponding to these target operating condition parameters. This allows for further optimization of the energy management strategy based on the target vehicle driving rules defined by the preset energy rules. While ensuring low fuel consumption for the target vehicle on the driving path, this further improves the stability of the target vehicle during driving.

[0084] According to embodiments of this disclosure, based on preset energy management rules, the driving of the target vehicle in each path interval is simulated multiple times using a vehicle dynamics model to obtain multiple operating condition information of the target vehicle in each path interval. This includes: determining the engine parameter range and generator parameter range of the target vehicle based on preset energy management rules; and simulating the driving of the target vehicle in each path interval multiple times using a vehicle dynamics model based on the engine parameter range and generator parameter range to obtain multiple operating condition information of the target vehicle in each path interval. The operating condition information includes engine parameters and generator parameters, wherein the engine parameters are within the engine parameter range and the generator parameters are within the generator parameter range.

[0085] According to embodiments of this disclosure, the preset energy management rules require the target vehicle's system to meet certain constraints. These constraints may include setting engine parameter ranges and generator parameter ranges for the target vehicle. The engine parameters may include engine speed and torque, with the engine speed range and torque range determined by the preset energy management rules. Similarly, the generator parameters may include engine speed and torque, with the generator speed range and torque range determined by the preset energy management rules.

[0086] The operating condition information and the corresponding preset energy management rules are shown in the following formula:

[0087]

[0088] Among them, SOC k The current state of charge (SOC) of the battery. min The SOC is the minimum value of the battery's state of charge range at the current moment. max n represents the maximum value of the battery's state of charge range at the current moment; en_k Let n be the engine's current speed. en min n represents the minimum range of engine speeds at the current moment. en max T represents the maximum speed range of the engine at the current moment; en_k T represents the engine's torque at the current moment. en min T represents the minimum torque range of the engine at the current moment. en max n represents the maximum torque value within the engine's current torque range. mo_k Let n be the current rotational speed of the generator. mo max n represents the maximum speed range of the generator at the current moment. mo min T represents the minimum speed range of the generator at the current moment. mo_k T represents the torque of the generator at the current moment. mo max T represents the maximum torque value within the generator's current torque range. mo minThe minimum torque range of the generator at the current moment; SOC f and SOC l These represent the initial state of charge and the final state of charge of the battery.

[0089] According to embodiments of this disclosure, the state of charge (SOC) range, initial SOC range, and final SOC range of the target vehicle battery can also be determined by preset energy management rules. Because the SOC of a hybrid vehicle battery changes continuously with vehicle use during operation, and the SOC affects fuel consumption, maintaining a reasonable SOC range to balance charging and discharging can minimize fuel consumption. Based on the implementation process of this disclosure, setting the initial SOC and final SOC between 0.4 and 0.5 is optimal.

[0090] According to embodiments of this disclosure, the generator and engine parameters of the target vehicle used for simulation are kept within their respective ranges. The vehicle's driving process in each path range is simulated using a vehicle dynamics model established by simulation software, thereby obtaining multiple operating condition information for the vehicle in each path range. These multiple operating condition information include at least multiple generator parameters and multiple engine parameters, because the target vehicle is simulated based on generator parameter ranges and engine parameter ranges; therefore, the generator parameters are within the generator parameter range, and the engine parameters are within the engine parameter range. To ensure the accuracy of the operating condition information obtained from the simulation, multiple simulations can be performed.

[0091] According to embodiments of this disclosure, the engine parameter range and generator parameter range of the target vehicle are determined based on a preset energy management strategy, and the vehicle's driving on the path range is simulated multiple times based on the generator parameter range and engine parameter range to obtain multiple operating condition information of the target vehicle on the path range, providing data for constructing an energy consumption distribution map.

[0092] According to embodiments of this disclosure, the energy consumption distribution map includes a fuel consumption distribution map and a speed fluctuation distribution map, and further includes: simulating the driving state of the target vehicle using a vehicle dynamics model to obtain driving information, wherein the driving information includes multiple speeds of the target vehicle and the torque corresponding to each speed; and generating a fuel consumption distribution map based on the multiple speeds and the torque corresponding to each speed in the driving information.

[0093] According to embodiments of this disclosure, the optimization objective of the energy management strategy is divided into two parts: optimization of fuel consumption and output speed fluctuation. Therefore, at least a fuel consumption distribution map and a speed fluctuation distribution map are needed to determine the fuel consumption and speed fluctuation of the target vehicle within the path interval. The driving state of the target vehicle in each path interval is simulated using a vehicle dynamics model to obtain multiple engine speeds and torques during the driving process. Based on the correspondence between the simulated speeds and torques and the vehicle's fuel consumption, a fuel consumption distribution map of the target vehicle can be plotted, where each combination of speed and torque corresponds to a fuel consumption of the target vehicle. The fuel consumption distribution map may also include the correspondence between battery state of charge and fuel consumption.

[0094] According to an embodiment of this disclosure, the speed fluctuation distribution map is generated as follows: the driving information is divided into periods to obtain T periods; for one period, multiple speeds in the period are sampled to obtain multiple speed sampling points; the speed fluctuation value of the target vehicle in the period is determined using the speed corresponding to each speed sampling point and the total number of periods T; and the speed fluctuation distribution map is generated based on the speed fluctuation value of the target vehicle in each period.

[0095] According to the embodiments of this disclosure, during the simulation of the target vehicle using a vehicle dynamics model, multiple driving information can be obtained. The obtained driving information is divided into T cycles, and the rotational speed of one cycle is sampled to obtain multiple sampling points. The rotational speed fluctuation value of the target vehicle in that cycle can be calculated using formula (2), which is as follows:

[0096]

[0097] Where RMS represents the speed fluctuation value, n represents the number of sampling points, and i represents the variables in the calculation process.

[0098] According to embodiments of this disclosure, the speed fluctuation values ​​for multiple cycles can be calculated using formula (2). A speed fluctuation distribution diagram is drawn based on the correspondence between the average speed and average torque of the target vehicle in each cycle and the speed fluctuation value in that cycle. The speed fluctuation distribution diagram may also include the correspondence between the battery state of charge and the speed fluctuation values.

[0099] According to embodiments of this disclosure, a fuel consumption distribution map reflecting the relationship between engine speed, torque and fuel consumption of a target vehicle during driving is obtained through simulation, and a speed fluctuation distribution map reflecting the relationship between engine speed, torque and speed fluctuation value of a target vehicle during driving is obtained through simulation, saving experimental costs in the process of determining energy management strategies.

[0100] According to embodiments of this disclosure, the operating condition parameters include fuel consumption and speed fluctuation values. Based on multiple operating condition information, multiple operating condition parameters of the target vehicle in the path interval are determined from the energy consumption distribution map, including: based on the operating condition information, using an interpolation algorithm to determine the fuel consumption and speed fluctuation values ​​of the target vehicle from the fuel consumption distribution map and the speed fluctuation distribution map, respectively.

[0101] According to embodiments of this disclosure, a fuel consumption distribution map can characterize the relationship between multiple speeds and multiple torques and fuel consumption. Fuel consumption under different operating conditions can be obtained from the fuel consumption distribution map using an interpolation algorithm. Similarly, a speed fluctuation distribution map can characterize the relationship between multiple speeds and multiple torques and speed fluctuation values. Speed ​​fluctuation values ​​under different operating conditions can also be obtained from the speed fluctuation distribution map using an interpolation algorithm.

[0102] According to embodiments of this disclosure, by establishing a fuel consumption distribution map and a speed fluctuation distribution map, the fuel consumption and speed fluctuation values ​​corresponding to different operating conditions are obtained from the fuel consumption distribution map and the speed fluctuation distribution map, providing a reference for subsequent energy management strategy formulation.

[0103] According to embodiments of this disclosure, determining a target operating condition parameter corresponding to a path interval from multiple operating condition parameters includes: determining a performance parameter corresponding to minimum fuel consumption from multiple operating condition parameters; determining the performance parameter as the target operating condition parameter when the speed fluctuation value in the performance parameter is the minimum value among the multiple operating condition parameters; determining the average fuel consumption value and the average fluctuation value based on the multiple operating condition parameters when the speed fluctuation value in the performance parameter is not the minimum value among the multiple operating condition parameters; and determining the target operating condition parameter based on the average fuel consumption value and the average fluctuation value.

[0104] According to the embodiments of this disclosure, the minimum fuel consumption and minimum speed fluctuation value of the target vehicle in the path interval are found. The target vehicle may have multiple minimum fuel consumption and multiple speed fluctuation values ​​in the same path interval. When the minimum speed fluctuation value is included among the multiple speed fluctuation values ​​corresponding to the multiple minimum fuel consumption, the minimum speed fluctuation value and the minimum fuel consumption corresponding to the minimum speed fluctuation value are used as the target operating condition parameters.

[0105] According to embodiments of this disclosure, fuel consumption does not directly affect the speed fluctuation value. Therefore, the speed fluctuation value corresponding to the minimum fuel consumption is not necessarily the minimum speed fluctuation value in the path interval. If the minimum speed fluctuation value in the path interval is not included among the multiple speed fluctuation values ​​corresponding to multiple minimum fuel consumptions, the average value of the speed fluctuation value corresponding to the minimum fuel consumption is calculated with the minimum speed fluctuation value to obtain the average fluctuation value. The average value of the fuel consumption corresponding to the minimum speed fluctuation value is calculated with the minimum fuel consumption to obtain the average fuel consumption value. One or more sets of operating condition parameters where the fuel consumption is less than the average fuel consumption value and the speed fluctuation value is less than the average fluctuation value can be selected as the target operating condition parameters for the current path interval.

[0106] According to embodiments of this disclosure, the operating condition information corresponding to the target operating condition parameters in each path interval is combined to obtain the energy management strategy of the target vehicle on the driving path, including: determining the operating condition information corresponding to the target operating condition parameters in each path interval; determining the driving mode of the target vehicle in each path interval based on the operating condition information of each path interval, wherein the driving mode includes engine driving and generator driving; and combining the driving mode of the target vehicle in each path interval with the operating condition information corresponding to the driving mode to generate the energy management strategy of the target vehicle on the driving path.

[0107] According to embodiments of this disclosure, for each path interval, based on fuel consumption and speed fluctuation values ​​in the target operating condition parameters, the engine speed, engine torque, generator speed, generator torque, and initial state of charge of the target vehicle are determined. Based on the determined operating condition information, an energy management strategy for that path interval is then determined. The driving mode of the target vehicle in the current path interval is determined based on the energy management strategy. The vehicle driving mode includes generator drive, engine drive, and a hybrid generator and engine drive.

[0108] According to embodiments of this disclosure, an energy management strategy that minimizes fuel consumption and speed fluctuation can be obtained by combining the driving mode of the target vehicle in each path interval and the operating condition information corresponding to the driving mode, and used as the energy management strategy for the target vehicle throughout the entire driving path.

[0109] Figure 4 A flowchart illustrating a method for determining an energy management strategy according to another embodiment of this disclosure is shown schematically.

[0110] like Figure 4 As shown, the energy management strategy determination method in this embodiment includes operations S410 to S450.

[0111] In operation S410, the driving path of the target vehicle is divided into N path intervals.

[0112] When operating S420, based on preset energy management rules, the vehicle dynamics model is used to simulate the driving of the target vehicle in a certain path section to obtain the operating condition information of the target vehicle in the current path section.

[0113] When operating S430, the operating parameters of the target vehicle in the current path section are determined from the energy consumption distribution map based on the operating condition information.

[0114] In operation S440, determine whether the number of simulations for the current path interval is less than M.

[0115] If it is determined that the number of simulations for the current path interval is not less than M, execute operation S450; if it is determined that the number of simulations for the current path interval is less than M, execute operation S420.

[0116] When operating S450, the target operating parameters corresponding to the current path interval are determined from multiple operating parameters based on the operating parameters obtained in each simulation.

[0117] According to embodiments of this disclosure, N and M are both integers greater than 1. Figure 4 The method shown can obtain the target operating parameters of the target vehicle after multiple simulations along a path interval. By executing the above operations S420 to S450 N times, N target operating parameters corresponding to N path intervals can be obtained. By combining the operating information corresponding to the target operating parameters in each path interval, the energy management strategy of the target vehicle on the driving path can be obtained.

[0118] According to the embodiments of this disclosure, since simulating the entire driving path requires simulating all road condition information in the driving path, by dividing the driving path, performing multiple simulations on each path interval separately, and determining the energy management strategy on the current path interval, the step of calculating the operating condition parameters on each path interval is omitted, making the operation more convenient.

[0119] Based on the above-described method for determining energy management strategies, this disclosure also provides an apparatus for determining energy management strategies. The following will be combined with... Figure 5 The device is described in detail.

[0120] Figure 5 A schematic block diagram of an energy management strategy determination device according to an embodiment of the present disclosure is shown.

[0121] like Figure 5 As shown, the energy management strategy determination device 500 of this embodiment includes a path division module 510, a driving simulation module 520, a parameter determination module 530, a target determination module 540, and a strategy generation module 550.

[0122] The path division module 510 divides the driving path of the target vehicle into multiple path intervals. In one embodiment, the path division module 510 can be used to perform the operation S210 described above, which will not be repeated here.

[0123] The driving simulation module 520 is used to perform multiple simulations of the target vehicle's driving in each path interval based on preset energy management rules and using a vehicle dynamics model, thereby obtaining multiple operating condition information of the target vehicle in each path interval. In one embodiment, the driving simulation module 520 can be used to execute the operation S220 described above, which will not be repeated here.

[0124] The parameter determination module 530 is used to determine multiple operating condition parameters of the target vehicle in each path interval based on multiple operating condition information from the energy consumption distribution map. In one embodiment, the parameter determination module 530 can be used to perform the operation S230 described above, which will not be repeated here.

[0125] The target determination module 540 is used to determine the target operating condition parameters corresponding to the path interval from multiple operating condition parameters. In one embodiment, the target determination module 540 can be used to perform the operation S240 described above, which will not be repeated here.

[0126] The strategy generation module 550 is used to combine the operating condition information corresponding to the target operating condition parameters in each path interval to obtain the energy management strategy of the target vehicle on the driving path. In one embodiment, the strategy generation module 550 can be used to perform the operation S250 described above, which will not be repeated here.

[0127] According to an embodiment of this disclosure, the driving simulation module 520 includes an interval determination unit and a first acquisition unit.

[0128] The interval determination unit is used to determine the engine parameter interval and generator parameter interval of the target vehicle based on preset energy management rules.

[0129] The first acquisition unit is used to perform multiple simulations of the target vehicle's driving in each path interval based on the engine parameter interval and the generator parameter interval using the vehicle dynamics model, thereby obtaining multiple operating condition information of the target vehicle in each path interval. The operating condition information includes engine parameters and generator parameters, with the engine parameters within the engine parameter interval and the generator parameters within the generator parameter interval.

[0130] According to embodiments of this disclosure, the parameter determination module 530 further includes a second acquisition unit and a first generation unit.

[0131] The second acquisition unit is used to simulate the driving state of the target vehicle using a vehicle dynamics model to obtain driving information, which includes multiple rotational speeds of the target vehicle and the torque corresponding to each rotational speed.

[0132] The first generation unit is used to generate a fuel consumption distribution map based on multiple speeds and the torque corresponding to each speed in the driving information.

[0133] According to embodiments of this disclosure, the parameter determination module 530 further includes a period acquisition unit, a third acquisition unit, a first determination unit, and a second generation unit.

[0134] The cycle acquisition unit is used to divide the driving information into cycles to obtain T cycles;

[0135] The third acquisition unit is used to sample multiple rotational speeds within a cycle to obtain multiple rotational speed sampling points.

[0136] The first determining unit is used to determine the speed fluctuation value of the target vehicle in the cycle using the speed corresponding to each speed sampling point and the total number of cycles T.

[0137] The second generation unit generates a speed fluctuation distribution map based on the speed fluctuation value of the target vehicle in each cycle.

[0138] According to embodiments of this disclosure, the operating condition parameters include fuel consumption and speed fluctuation values, and the parameter determination module 530 includes a second determination unit.

[0139] The second determining unit is used to determine the fuel consumption and speed fluctuation values ​​of the target vehicle from the fuel consumption distribution map and the speed fluctuation distribution map respectively, based on the operating condition information and using an interpolation algorithm.

[0140] According to embodiments of this disclosure, the target determination module 540 includes: a third determination unit, a fourth determination unit, a fifth determination unit, and a sixth determination unit.

[0141] The third determining unit is used to determine the performance parameters corresponding to the minimum fuel consumption from multiple operating condition parameters:

[0142] The fourth determining unit is used to determine the performance parameter as the target operating condition parameter when the speed fluctuation value in the performance parameter is the minimum value among multiple operating condition parameters;

[0143] The fifth determining unit is used to determine the average fuel consumption and the average fluctuation value based on multiple operating condition parameters when the speed fluctuation value in the performance parameters is not the minimum value among multiple operating condition parameters.

[0144] The sixth determining unit is used to determine the target operating condition parameters based on the average fuel consumption and the average fluctuation.

[0145] According to embodiments of this disclosure, the strategy generation module 550 includes a seventh determining unit, an eighth determining unit, and a third generating unit.

[0146] The seventh determining unit is used to determine the working condition information corresponding to the target working condition parameters in each path interval;

[0147] The eighth determining unit determines the driving mode of the target vehicle in each path interval based on the working condition information of each path interval, wherein the driving mode includes engine driving and generator driving.

[0148] The third generation unit is used to combine the driving mode of the target vehicle in each path interval with the corresponding operating condition information to generate the energy management strategy of the target vehicle on the driving path.

[0149] According to embodiments of this disclosure, any multiple modules among the path division module 510, driving simulation module 520, parameter determination module 530, target determination module 540, and strategy generation module 550 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the path division module 510, driving simulation module 520, parameter determination module 530, target determination module 540, and strategy generation module 550 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the path division module 510, driving simulation module 520, parameter determination module 530, target determination module 540, and strategy generation module 550 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0150] Figure 6 A block diagram of an electronic device suitable for implementing an energy management strategy determination method according to an embodiment of the present disclosure is shown schematically.

[0151] like Figure 6As shown, an electronic device 600 according to an embodiment of this disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this disclosure.

[0152] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 602 and / or RAM 603. It should be noted that the programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0153] According to embodiments of this disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to a bus 604. The electronic device 600 may also include one or more of the following components connected to the input / output (I / O) interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0154] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0155] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 described above.

[0156] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the energy management strategy determination method provided in the embodiments of this disclosure.

[0157] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0158] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0159] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0160] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0162] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0163] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for determining an energy management strategy, comprising: The driving path of the target vehicle is divided into multiple path intervals; Based on preset energy management rules, the vehicle dynamics model is used to simulate the driving of the target vehicle in each path interval multiple times to obtain multiple operating condition information of the target vehicle in each path interval. For each of the path intervals, based on multiple operating condition information, multiple operating condition parameters of the target vehicle in the path interval are determined from the energy consumption distribution map; Determine the target operating condition parameter corresponding to the path interval from among the multiple operating condition parameters; The operating condition information corresponding to the target operating condition parameter in each path interval is combined to obtain the energy management strategy of the target vehicle on the driving path. The energy consumption distribution map includes a fuel consumption distribution map and a speed fluctuation distribution map, and the method further includes: The driving state of the target vehicle is simulated using the vehicle dynamics model to obtain driving information, wherein the driving information includes multiple engine speeds of the target vehicle and the torque corresponding to each engine speed; The fuel consumption distribution map is generated based on multiple speeds and the torque corresponding to each speed in the driving information. The driving information is divided into T periods. For a given cycle, multiple rotational speeds within that cycle are sampled to obtain multiple rotational speed sampling points; Using the rotational speed corresponding to each rotational speed sampling point and the total number of cycles T, the rotational speed fluctuation value of the target vehicle in the cycle is determined; Based on the speed fluctuation value of the target vehicle in each cycle, a speed fluctuation distribution map is generated.

2. The method according to claim 1, wherein, Based on preset energy management rules, the vehicle dynamics model is used to perform multiple simulations of the target vehicle's driving in each path interval, obtaining multiple operating condition information of the target vehicle in each path interval, including: Based on the preset energy management rules, the engine parameter range and generator parameter range of the target vehicle are determined; Based on the engine parameter range and the generator parameter range, the vehicle dynamics model is used to perform multiple simulations of the target vehicle's driving in each path range to obtain multiple operating condition information of the target vehicle in each path range. The operating condition information includes engine parameters and generator parameters, wherein the engine parameters are within the engine parameter range and the generator parameters are within the generator parameter range.

3. The method according to claim 1, wherein, The operating condition parameters include fuel consumption and speed fluctuation values. Determining multiple operating condition parameters of the target vehicle within the path interval from the energy consumption distribution map based on multiple operating condition information includes: Based on the operating condition information, the fuel consumption and speed fluctuation values ​​of the target vehicle are determined from the fuel consumption distribution map and the speed fluctuation distribution map using an interpolation algorithm. The fuel consumption distribution map represents the relationship between multiple speeds and multiple torques and fuel consumption, and the speed fluctuation distribution map represents the relationship between multiple speeds and multiple torques and speed fluctuation values.

4. The method according to claim 3, wherein, Determining the target operating condition parameter corresponding to the path interval from a plurality of operating condition parameters includes: The performance parameter corresponding to the minimum fuel consumption is determined from the multiple operating condition parameters; If the speed fluctuation value in the performance parameter is the minimum value among multiple operating condition parameters, then the performance parameter is determined as the target operating condition parameter. If the speed fluctuation value in the performance parameters is not the minimum value among the multiple operating condition parameters, the average fuel consumption and the average fluctuation value are determined based on the multiple operating condition parameters. The target operating condition parameters are determined based on the average fuel consumption and the average fluctuation.

5. The method according to claim 1, wherein, The step of combining the operating condition information corresponding to the target operating condition parameters in each of the path intervals to obtain the energy management strategy of the target vehicle on the driving path includes: Determine the operating condition information corresponding to the target operating condition parameter in each of the path intervals; Based on the operating condition information of each path interval, the driving mode of the target vehicle in each path interval is determined, wherein the driving mode includes engine driving and generator driving; The driving mode and the corresponding operating condition information of the target vehicle in each path interval are combined to generate the energy management strategy of the target vehicle on the driving path.

6. An energy management strategy determination device, comprising: The path segmentation module is used to divide the driving path of the target vehicle into multiple path intervals; The driving simulation module is used to perform multiple simulations of the target vehicle's driving in each of the path intervals based on preset energy management rules and using a vehicle dynamics model, so as to obtain multiple operating condition information of the target vehicle in each of the path intervals. The parameter determination module is used to determine, for each of the path intervals, multiple operating condition parameters of the target vehicle in the path interval from the energy consumption distribution map based on multiple operating condition information. The target determination module is used to determine the target operating condition parameter corresponding to the path interval from a plurality of operating condition parameters; The strategy generation module is used to combine the operating condition information corresponding to the target operating condition parameter in each path interval to obtain the energy management strategy of the target vehicle on the driving path. The energy consumption distribution map includes a fuel consumption distribution map and a speed fluctuation distribution map, and the device further includes: The second acquisition unit is used to simulate the driving state of the target vehicle using the vehicle dynamics model to obtain driving information, wherein the driving information includes multiple engine speeds of the target vehicle and the torque corresponding to each engine speed; The first generation unit is used to generate the fuel consumption distribution map based on multiple speeds and the torque corresponding to each speed in the driving information; A period acquisition unit is used to divide the driving information into T periods; The third acquisition unit is used to sample multiple rotational speeds in a cycle to obtain multiple rotational speed sampling points. The first determining unit is used to determine the speed fluctuation value of the target vehicle in the cycle using the speed corresponding to each speed sampling point and the total number of cycles T; The second generation unit is used to generate a speed fluctuation distribution map based on the speed fluctuation value of the target vehicle in each cycle.

7. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 5.

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