Methods, devices, equipment and media for determining the energy distribution mode of electric vehicles

Abstract

This application provides a method, apparatus, device, and medium for determining the energy distribution mode of an electric vehicle. The method includes: acquiring target mileage, remaining battery power, real-time vehicle speed, and energy consumption data related to each load on the electric vehicle; calculating the energy consumption per unit mileage for each load; determining candidate energy distribution modes from multiple preset energy distribution modes based on the target mileage, remaining battery power, and energy consumption per unit mileage for each load; outputting the energy consumption per unit mileage for each load and each candidate energy distribution mode for visual display; and determining the target energy distribution mode for the electric vehicle in response to user feedback on each candidate energy distribution mode. This method helps users accurately understand the energy consumption of their electric vehicle and select an energy distribution mode suitable for current operating conditions, alleviating range anxiety.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a method, apparatus, equipment and medium for determining the energy distribution mode of an electric vehicle. Background Technology

[0002] During the use of electric vehicles, the actual driving range is affected by the energy distribution method of the electric vehicle, and often differs from the driving range calculated according to the Chinese driving cycle test (CLTC) and the new European cycle test (NEDC). Therefore, users often experience "range anxiety" when using electric vehicles, worrying that the driving range of the electric vehicle is not accurate enough and that the vehicle does not have enough power to reach its destination.

[0003] Due to "range anxiety," users often focus more on the energy consumption and remaining energy of electric vehicles than on the driving range, and adjust the energy allocation mode based on these metrics. However, current electric vehicles only display the energy consumed by major energy-intensive loads such as the motor and air conditioning. Users can only adjust the energy allocation mode based on experience, which prevents them from accurately understanding the overall energy consumption of the electric vehicle. Furthermore, users cannot accurately select the appropriate energy allocation mode for the current operating conditions based on their own experience, thus perpetuating "range anxiety." Summary of the Invention

[0004] This application provides a method, apparatus, device, and medium for determining the energy distribution mode of an electric vehicle, in order to solve the problems in the prior art where users cannot accurately understand the overall energy consumption of the electric vehicle, cannot accurately select the energy distribution mode suitable for the current operating conditions, and have range anxiety.

[0005] According to a first aspect of this application, a method for determining the energy distribution mode of an electric vehicle is provided, comprising:

[0006] Acquire the target mileage, remaining battery power, and real-time vehicle speed of electric vehicles, as well as energy consumption data related to various loads on the electric vehicle;

[0007] Based on the real-time vehicle speed and energy consumption data of each load, calculate the energy consumption per unit mile of electric vehicle for each load per unit mile traveled.

[0008] Based on the target mileage, the remaining battery power, and the energy consumption per unit mileage corresponding to each load, at least one candidate energy allocation mode is determined from a variety of preset energy allocation modes.

[0009] Output the energy consumption per unit mileage for each load and the energy allocation mode for each candidate, so as to visualize the energy loss per unit mileage for each load and the energy allocation mode for each candidate.

[0010] In response to user feedback on each candidate energy allocation mode, the target energy allocation mode for the electric vehicle is determined.

[0011] Optionally, the load energy consumption related data includes the real-time current and real-time voltage corresponding to the load operation;

[0012] Based on the real-time vehicle speed and energy consumption data of each load, calculate the energy consumption per unit mile for each load corresponding to each unit mile traveled by the electric vehicle, including:

[0013] Based on the real-time vehicle speed, calculate the time range corresponding to each unit of mileage traveled by the electric vehicle.

[0014] The integral of the product of the real-time current and real-time voltage of each load within the time range is determined as the energy consumption per unit mileage for each load.

[0015] Optionally, the preset energy distribution mode includes the operating status of each load;

[0016] The step of determining at least one candidate energy allocation mode from a variety of preset energy allocation modes based on the target mileage, the remaining battery capacity, and the energy consumption per unit mileage corresponding to each load includes:

[0017] Based on the operating status of each load in each preset energy distribution mode and the energy consumption per unit mileage corresponding to each load, the remaining battery power is calculated, and the driving range corresponding to each preset energy distribution mode is calculated when the electric vehicle is driven in each preset energy distribution mode.

[0018] Based on the target mileage and the drivable mileage corresponding to each preset energy allocation mode, at least one candidate energy allocation mode is determined from each preset energy allocation mode.

[0019] Optionally, determining at least one candidate energy allocation mode from among the preset energy allocation modes based on the target mileage and the drivable mileage corresponding to each preset energy allocation mode includes:

[0020] In response to the existence of at least one corresponding preset energy allocation mode with a driving range greater than the target mileage, the preset energy allocation mode with a driving range greater than the target mileage is determined as a candidate energy allocation mode.

[0021] Optionally, the method further includes:

[0022] In response to the fact that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, the energy allocation mode with the largest corresponding drivable mileage among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0023] Optionally, the method further includes:

[0024] Obtain the nearest charging station to the electric vehicle and the charging distance the electric vehicle travels to the nearest charging station;

[0025] In response to the fact that the driving range corresponding to each preset energy allocation mode is less than the target range, and there is at least one preset energy allocation mode with a corresponding driving range greater than the charging range, the preset energy allocation mode with a corresponding driving range greater than the charging range is determined as a candidate energy allocation mode.

[0026] In response to the fact that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, and the drivable mileage corresponding to each preset energy allocation mode is less than the charging mileage, the energy allocation mode with the largest corresponding drivable mileage among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0027] Optionally, user feedback on each candidate energy allocation mode includes: the user not selecting information within a preset time or the candidate energy allocation mode selected by the user;

[0028] The step of determining the target energy allocation mode for the electric vehicle in response to user feedback on each candidate energy allocation mode includes:

[0029] In response to the feedback information being that no information was selected within a preset time and the number of candidate energy allocation modes is one, the candidate energy allocation mode is determined as the target energy allocation mode.

[0030] In response to the feedback information indicating the candidate energy allocation mode selected by the user, the energy allocation mode selected by the user is determined as the target energy allocation mode.

[0031] According to a second aspect of this application, an energy distribution mode determination device for an electric vehicle is provided, comprising:

[0032] The acquisition module is used to acquire the target mileage, remaining battery power, and real-time vehicle speed of the electric vehicle, as well as the real-time current and real-time voltage of each load on the electric vehicle.

[0033] The calculation module is used to calculate the energy consumption per unit mile of each load corresponding to each unit mile of electric vehicle travel, based on the real-time vehicle speed and the real-time current and real-time voltage of each load.

[0034] The first determining module is used to determine at least one candidate energy allocation mode from a variety of preset energy allocation modes based on the target mileage, the remaining battery power and the energy consumption per unit mileage corresponding to each load.

[0035] The output module is used to output the energy consumption per unit mileage and the candidate energy allocation mode for each load, so as to visualize the energy loss per unit mileage and the candidate energy allocation mode for each load.

[0036] The second determining module is used to determine the target energy allocation mode for the electric vehicle in response to user feedback on each candidate energy allocation mode.

[0037] According to a third aspect of this application, an electronic device is provided, comprising: a memory, a processor, and an output device;

[0038] The memory, the processor, and the output device are interconnected;

[0039] The memory stores computer-executed instructions;

[0040] The output device is used to output information;

[0041] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0042] According to a fourth aspect of this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor, are used to implement the method as described in the first aspect.

[0043] According to a fifth aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect.

[0044] The method, apparatus, device, and medium for determining the energy distribution mode of an electric vehicle provided in this application acquire the target mileage, remaining battery power, and real-time vehicle speed of the electric vehicle, as well as energy consumption-related data of each load on the electric vehicle; calculate the unit mileage energy consumption of each load corresponding to each unit mileage traveled by the electric vehicle based on the real-time vehicle speed and the energy consumption-related data of each load; determine at least one candidate energy distribution mode from a variety of preset energy distribution modes based on the target mileage, the remaining battery power, and the unit mileage energy consumption corresponding to each load; output the unit mileage energy consumption corresponding to each load and each candidate energy distribution mode to visualize the unit mileage loss corresponding to each load and each candidate energy distribution mode; and determine the target energy distribution mode of the electric vehicle in response to user feedback information on each candidate energy distribution mode. Since the energy-related data of each load can reflect the energy consumption of each load and calculate the energy consumption per unit mileage for each load, and based on the target mileage, the remaining battery power, and the energy consumption per unit mileage for each load, at least one candidate energy allocation mode that meets the current operating conditions can be determined from a variety of preset energy allocation modes. Then, the energy consumption per unit mileage for each load and each candidate energy allocation mode are output, and the energy consumption per unit mileage for each load and each candidate energy allocation mode are visualized to help users accurately understand the energy consumption of electric vehicles and select the energy allocation mode suitable for the current operating conditions. Furthermore, based on the user's feedback on each candidate energy allocation mode, the target energy allocation mode of the electric vehicle is determined, which can alleviate the user's range anxiety. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] Figure 1 This is a network architecture diagram corresponding to the application scenario of the electric vehicle energy distribution mode determination method provided in the embodiments of this application;

[0047] Figure 2 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 1 of this application;

[0048] Figure 3 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 2 of this application;

[0049] Figure 4 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 3 of this application;

[0050] Figure 5 This is a schematic diagram of the structure of the energy distribution mode determination device for an electric vehicle provided in Embodiment 4 of this application;

[0051] Figure 6 This is a schematic diagram of the structure of an electronic device provided according to Embodiment 5 of this application.

[0052] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0053] The terms "first," "second," "third," etc. (if present) in the specification, claims, and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0054] The prior art involved in this application will be described in detail and analyzed below.

[0055] The actual driving range of an electric vehicle (EV) is affected by its energy distribution mode. EVs typically use a high-voltage battery to power high-voltage loads and a DC-DC converter to power low-voltage loads. During operation, the number of high-voltage and low-voltage loads activated affects the EV's energy consumption, thus impacting its actual driving range. This results in a discrepancy between the actual driving range calculated according to the Chinese Car Driving Cycle (CLTC) and the New European Driving Cycle (NEDC) standards. Therefore, users are more concerned about the EV's energy consumption, remaining energy, and energy distribution mode than the inaccurate driving range. The energy distribution mode is entirely dependent on the driver's choice, which is usually based on the remaining energy and energy consumption. Currently, EVs only display the energy consumed by major energy-consuming loads such as the motor and air conditioning. This only allows users to understand the energy consumption of these major loads, not the overall energy consumption of the EV. Furthermore, users cannot choose the appropriate energy distribution mode based solely on their experience, failing to alleviate "range anxiety."

[0056] In summary, existing technologies have several drawbacks, including users' inability to understand the overall energy consumption of electric vehicles, their inability to accurately select the energy distribution mode suitable for the current operating conditions, and the existence of range anxiety.

[0057] Therefore, in the face of the problems in the existing technology, the inventors, through creative research, aim to alleviate users' range anxiety, enable users to understand the overall energy consumption of electric vehicles, and accurately select the energy allocation mode suitable for the current operating conditions. This requires outputting the energy consumption of each load on the electric vehicle to the user and recommending an energy allocation mode suitable for the current operating conditions. Therefore, the inventors proposed the technical solution of this application, which involves acquiring the target mileage, remaining battery power, and real-time vehicle speed of the electric vehicle, as well as energy consumption data related to each load on the electric vehicle; calculating the unit mileage energy consumption corresponding to each load for each unit of mileage driven by the electric vehicle based on the real-time vehicle speed and the energy consumption data of each load; determining at least one candidate energy allocation mode from multiple preset energy allocation modes based on the target mileage, remaining battery power, and unit mileage energy consumption corresponding to each load; outputting the unit mileage energy consumption corresponding to each load and each candidate energy allocation mode to visualize the unit mileage loss corresponding to each load and each candidate energy allocation mode; and determining the target energy allocation mode of the electric vehicle in response to user feedback on each candidate energy allocation mode. Since the energy-related data of each load can reflect the energy consumption of each load and calculate the energy consumption per unit mileage for each load, and based on the target mileage, remaining battery power, and energy consumption per unit mileage for each load, at least one candidate energy allocation mode that meets the current operating conditions can be determined from a variety of preset energy allocation modes. Then, the energy consumption per unit mileage for each load and each candidate energy allocation mode are output, and the energy consumption per unit mileage for each load and each candidate energy allocation mode are visualized to help users accurately understand the energy consumption of electric vehicles and select the energy allocation mode suitable for the current operating conditions. Furthermore, based on the user's feedback on each candidate energy allocation mode, the target energy allocation mode of the electric vehicle is determined, which can alleviate the user's range anxiety.

[0058] The method, apparatus, device, and medium for determining the energy distribution mode of electric vehicles provided in this application aim to solve the above-mentioned technical problems of the prior art. The technical solution of this application and how it solves the aforementioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0059] The network architecture and application scenarios of the electric vehicle energy distribution mode determination method provided in the embodiments of this application will be described below. When the following description refers to the accompanying drawings, unless otherwise indicated, the same data in different drawings represent the same or similar elements.

[0060] Figure 1 This is a network architecture diagram corresponding to the application scenario of the electric vehicle energy distribution mode determination method provided in the embodiments of this application. For example... Figure 1 As shown in the figure, the network architecture corresponding to an application scenario provided in this application embodiment includes: an electronic device 10 and an electric vehicle 11. The electronic device 10 and the electric vehicle 11 are communicatively connected.

[0061] The electric vehicle 11 includes: a high-voltage battery 111, a high-voltage power distribution unit 112, a high-voltage to low-voltage converter 113, a low-voltage battery 114, a low-voltage power distribution unit 115, at least one high-voltage load 116, an energy management unit 118, an input unit 119, a display unit 120, a speed sensor 121, a communication unit 122, and at least one other low-voltage load 117 besides the input unit 119, the display unit 120, and the communication unit 122.

[0062] The high-voltage battery 111 is electrically connected to the high-voltage power distribution unit 112, and the high-voltage power distribution unit 112 is electrically connected to each high-voltage load 116. The high-voltage battery 111 supplies power to each high-voltage load 116 through the high-voltage power distribution unit 112. The high-voltage power distribution unit 112 is used to obtain energy consumption related data of each high-voltage load 116 of the electric vehicle 11.

[0063] The high-voltage battery 111 is electrically connected to a high-voltage to low-voltage converter 113, which is in turn electrically connected to a low-voltage power distribution unit 115. The high-voltage battery 111 supplies power to low-voltage loads via the converter and distribution unit. These low-voltage loads include an input unit 119, a display unit 120, a communication unit 122, and at least one other low-voltage load 117 besides the input, display, and communication units. Furthermore, the high-voltage battery 111 charges the low-voltage battery 114 via the converter and distribution unit. The low-voltage power distribution unit 115 acquires energy consumption data related to each low-voltage load of the electric vehicle 11. The low-voltage battery 114 supplies power to the low-voltage loads when the high-voltage battery 111 has insufficient remaining charge.

[0064] Speed ​​sensor 121 is used to measure the real-time speed of electric vehicle 11.

[0065] The input unit 119 is used to interact with the driver of the electric vehicle 11. The driver can input the destination or target mileage in the input unit 119. When the driver inputs the destination, the input unit 119 can communicate with the navigation server through the communication unit 122 to obtain the target mileage between the current location of the electric vehicle and the destination.

[0066] The energy management unit 118 is communicatively connected to the input unit 119, the display unit 120, the speed sensor 121, the high-voltage power distribution unit 112, and the low-voltage power distribution unit 115. The energy management unit 118 is electrically connected to the high-voltage battery 111.

[0067] The energy management unit 118 can obtain the remaining battery power of the electric vehicle through an electrical connection with the high-voltage battery 111. The remaining battery power refers to the remaining power of the high-voltage battery 111.

[0068] The energy management unit 118 can also obtain the target mileage of the electric vehicle through a communication connection with the input unit 119.

[0069] The energy management unit 118 can also obtain the real-time speed of the electric vehicle through a communication connection with the speed sensor 121.

[0070] The energy management unit 118 can also obtain energy consumption data related to each load of the electric vehicle through communication connections with the high-voltage power distribution unit 112 and the low-voltage power distribution unit 115. The loads of the electric vehicle include all high-voltage and low-voltage loads on the electric vehicle.

[0071] Electronic device 10 can be located in electric vehicle 11 and can be part of electric vehicle 11. For example, electronic device 10 may include energy management unit 118 of electric vehicle 11. Electronic device 10 can also be independent of electric vehicle 11 and can communicate with electric vehicle 11 via wired or wireless means. For example, it can be connected to communication unit 122 of electric vehicle 11.

[0072] Electronic device 10 can obtain the target mileage, remaining battery power, and real-time vehicle speed of electric vehicle 11, as well as energy consumption data of each load on electric vehicle 11, through a communication connection with electric vehicle 11; calculate the unit mileage energy consumption of each load corresponding to each unit mileage traveled by electric vehicle 11 based on the real-time vehicle speed and energy consumption data of each load; and determine at least one candidate energy allocation mode from a variety of preset energy allocation modes based on the target mileage, remaining battery power, and unit mileage energy consumption of each load.

[0073] After determining at least one candidate energy allocation mode, the electronic device 10 can output the unit mileage energy consumption and each candidate energy allocation mode corresponding to each load, so as to visualize the unit mileage loss and each candidate energy allocation mode corresponding to each load. The electronic device 10 can receive user feedback information on each candidate energy allocation mode, and can determine the target energy allocation mode of the electric vehicle in response to the user feedback information on each candidate energy allocation mode.

[0074] The embodiments of this application will now be described with reference to the accompanying drawings. The embodiments described below do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0075] Example 1

[0076] Figure 2 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 1 of this application. Figure 2 As shown, the implementing entity of this application is an energy distribution mode determination device for electric vehicles, which is located in an electronic device. The energy distribution mode determination method for electric vehicles provided in this embodiment includes steps 201 to 205.

[0077] Step 201: Obtain the target mileage, remaining battery power, and real-time vehicle speed of the electric vehicle, as well as energy consumption data related to each load on the electric vehicle.

[0078] In this embodiment, the electronic device can be installed on the electric vehicle and communicate with the electric vehicle's speed sensor, high-voltage power distribution unit, low-voltage power distribution unit, and input unit. It is also electrically connected to the electric vehicle's high-voltage battery, thereby obtaining the electric vehicle's target mileage, remaining battery power, real-time vehicle speed, and energy consumption data related to each load.

[0079] For example, regarding the remaining battery power, the electronic device can obtain the battery's state of charge (SOC) through an electrical connection with the high-voltage battery, and then calculate the remaining battery power based on the total capacity and SOC of the high-voltage battery.

[0080] In this embodiment, the target mileage is the distance the electric vehicle needs to travel between its current location and the user's desired destination. Energy consumption-related data can be data reflecting the energy consumed by the load, such as the load's real-time power, real-time energy consumption, average power per unit time, average energy consumption per unit time, real-time current, and real-time voltage.

[0081] Step 202: Based on real-time vehicle speed and energy consumption data of each load, calculate the energy consumption per unit mile of electric vehicle for each load per unit mile traveled.

[0082] In this embodiment, the unit mileage can be one mile, one kilometer, one mile, etc. It can be understood that the driving mileage of an electric vehicle is the integral of real-time speed over time. Therefore, the time required for the electric vehicle to travel one unit mile can be calculated based on the real-time speed. Furthermore, the energy consumption per unit mile consumed by each load in the time required for the electric vehicle to travel one unit mile can be calculated based on the energy consumption data of each load.

[0083] Step 203: Based on the target mileage, remaining battery power, and energy consumption per unit mileage for each load, determine at least one candidate energy allocation mode from a variety of preset energy allocation modes.

[0084] In this embodiment, the candidate energy allocation mode is the energy allocation mode most suitable for the current operating conditions. The target mileage, the remaining battery power, and the energy consumption per unit mile corresponding to each load are a manifestation of the current operating conditions. Therefore, at least one candidate energy allocation mode can be determined from a variety of preset energy allocation modes based on the target mileage, the remaining battery power, and the energy consumption per unit mile corresponding to each load.

[0085] In this embodiment, the preset energy distribution mode can be pre-stored in the electronic device. The operating state of each load can be different in different preset energy distribution modes.

[0086] For example, in the first preset energy distribution mode, the PTC (Positive Temperature Coefficient) heater can be in a closed state; the in-vehicle navigation device can be in a closed state. In the second preset energy distribution mode, the PTC heater can be in a closed state; the in-vehicle navigation device can be in an open state. In the third preset energy distribution mode, the PTC heater can be in an open state; the in-vehicle navigation device can be in an open state.

[0087] In this embodiment, users can have different experiences when the electric vehicle operates in different energy distribution modes. For example, the operation of the PTC heater consumes energy from the electric vehicle, but when the PTC heater is on, if the ambient temperature is low, the user can turn on the air conditioning to raise the interior temperature and obtain a more comfortable experience.

[0088] Optionally, the preset energy distribution mode also includes the intensity of regenerative braking. Regenerative braking is the process by which the electric motor converts the mechanical energy of an electric vehicle into electrical energy when the vehicle brakes or decelerates. The intensity of regenerative braking affects the efficiency of converting mechanical energy into electrical energy, as well as the driving experience of the user in the electric vehicle. For example, it can affect the bumpiness of the electric vehicle.

[0089] For example, in the first preset energy distribution mode, the regenerative braking intensity can be a first preset intensity, and the braking torque can be a first preset value; in the second preset energy distribution mode, the regenerative braking intensity can be a second preset intensity, and the braking torque can be a second preset value. The first braking torque is greater than the second braking torque, and the efficiency of converting mechanical energy into electrical energy at the first preset intensity of regenerative braking is greater than that at the second preset intensity.

[0090] Optionally, the preset energy distribution mode also includes the acceleration of the electric vehicle during acceleration. Different accelerations require different amounts of energy to reach the preset speed; therefore, when the electric vehicle distributes energy using different preset energy distribution modes, it can have different accelerations during acceleration.

[0091] In this embodiment, the target mileage, the remaining battery power, and the energy consumption per unit mileage corresponding to each load can have a preset mapping relationship with at least one preset energy allocation mode. The electronic device can determine one or more preset energy allocation modes that have a preset mapping relationship with the target mileage, the remaining battery power, and the energy consumption per unit mileage corresponding to each load as candidate energy allocation modes.

[0092] Step 204: Output the energy consumption per unit mileage for each load and the energy allocation mode for each candidate, so as to visualize the energy loss per unit mileage for each load and the energy allocation mode for each candidate.

[0093] In this embodiment, the electronic device may have a display panel, and may output the unit mileage energy consumption and candidate energy allocation modes corresponding to each load in the form of text or pictures on the display panel.

[0094] In this embodiment, when outputting the energy consumption per unit mileage for each load, it may include the energy consumption per unit mileage for each load, and the percentage of the energy consumption per unit mileage for each load in the total energy consumption of all loads per unit mileage. For example, the motor energy consumption is 70KJ, accounting for 70%; the PCT heater energy consumption is 20KJ, accounting for 20%; the audio output device energy consumption is 5KJ, accounting for 5%; and the intelligent driving system energy consumption is 5KJ, accounting for 5%.

[0095] Step 205: In response to user feedback on each candidate energy allocation mode, determine the target energy allocation mode for the electric vehicle.

[0096] In this embodiment, the electronic device outputs the energy consumption per unit mile for each load and each candidate energy allocation mode, visually displaying the energy consumption per unit mile for each load and each candidate energy allocation mode, so that the user can obtain the energy consumption of each load on the electric vehicle and each candidate energy allocation mode. After knowing the energy consumption of each load and each candidate energy allocation mode, the user can interact with the electronic device. For example, the user can select an energy allocation mode from the candidate energy allocation modes. The electronic device can determine the candidate energy allocation mode selected by the user as the target energy allocation mode. Alternatively, the user can not select any candidate energy allocation mode and input an energy allocation mode themselves; the electronic device can determine the energy allocation mode input by the user as the target energy allocation mode.

[0097] The energy allocation mode determination method for electric vehicles provided in this embodiment acquires the target mileage, remaining battery power, real-time vehicle speed, and energy consumption data of each load on the electric vehicle; calculates the unit mileage energy consumption of each load corresponding to each unit mileage traveled by the electric vehicle based on the real-time vehicle speed and the energy consumption data of each load; determines at least one candidate energy allocation mode from a variety of preset energy allocation modes based on the target mileage, remaining battery power, and unit mileage energy consumption of each load; outputs the unit mileage energy consumption of each load and each candidate energy allocation mode to visualize the unit mileage loss of each load and each candidate energy allocation mode; and determines the target energy allocation mode of the electric vehicle in response to user feedback on each candidate energy allocation mode. Since the energy-related data of each load can reflect the energy consumption of each load and calculate the energy consumption per unit mileage for each load, and based on the target mileage, remaining battery power, and energy consumption per unit mileage for each load, at least one candidate energy allocation mode that meets the current operating conditions can be determined from a variety of preset energy allocation modes. Then, the energy consumption per unit mileage for each load and each candidate energy allocation mode are output, and the energy consumption per unit mileage for each load and each candidate energy allocation mode are visualized to help users accurately understand the energy consumption of electric vehicles and select the energy allocation mode suitable for the current operating conditions. Furthermore, based on the user's feedback on each candidate energy allocation mode, the target energy allocation mode of the electric vehicle is determined, which can alleviate the user's range anxiety.

[0098] Optionally, the load energy consumption related data includes the real-time current and real-time voltage corresponding to the load during operation, and the step 202 "calculate the unit mileage energy consumption of each load corresponding to each unit mileage driven by the electric vehicle based on the real-time vehicle speed and the energy consumption related data of each load" is further refined, then step 202 is further refined to include steps 2021 to 2022.

[0099] Step 2021: Calculate the time range corresponding to each unit of mileage traveled by the electric vehicle based on the real-time vehicle speed.

[0100] In this embodiment, the time range corresponding to a unit mileage traveled by the electric vehicle can be calculated using the following formula:

[0101]

[0102] Where v(t) is the real-time vehicle speed, s is the unit mileage, and [t1,t2] is the time range corresponding to the unit.

[0103] Step 2022: The integral of the product of the real-time current and real-time voltage of each load over the time range is determined as the energy consumption per unit mileage for each load.

[0104] In this embodiment, the product of real-time current and real-time voltage is the real-time power of the load. It can be understood that the integral of the real-time power of the load over a time range is the total energy consumption of the load within the corresponding range.

[0105] The energy distribution mode determination method for electric vehicles provided in this embodiment includes load energy consumption related data such as real-time current and real-time voltage corresponding to the load operation; calculating the time range corresponding to each unit mileage traveled by the electric vehicle based on the real-time vehicle speed; and determining the unit mileage energy consumption of each load by integrating the product of the real-time current and real-time voltage of each load over the time range. Since the unit mileage energy consumption of each load is determined by integrating the real-time current and real-time voltage of each load over the time range corresponding to each unit mileage, the unit mileage energy consumption of each load can be accurately calculated.

[0106] Example 2

[0107] Figure 3 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 2 of this application. Figure 3 As shown, the method for determining the energy distribution mode of an electric vehicle provided in this embodiment, based on Embodiment 1, includes the operating status of each load in the preset energy distribution mode. Furthermore, step 203, "determining at least one candidate energy distribution mode from multiple preset energy distribution modes based on the target mileage, the remaining battery power, and the energy consumption per unit mileage corresponding to each load," is further refined to include steps 301 to 302.

[0108] Step 301: Based on the operating status of each load in each preset energy distribution mode and the energy consumption per unit mileage corresponding to each load, calculate the remaining battery charge and the driving range corresponding to each preset energy distribution mode when the electric vehicle is driven in each preset energy distribution mode.

[0109] In this embodiment, the preset energy distribution mode includes the operating states of each load. For loads with only two states, namely, an on and off state, such as a windshield wiper, the operating state of the load in the preset energy distribution mode can be either the on or off state. For loads with multiple operating states, such as a motor having both a motoring state and a generator state, and the motoring and generator states can include different states, for example, the generator state can include multiple different regenerative braking intensities, the operating state of the load in the preset energy distribution mode can be any of the possible states of the load.

[0110] In this embodiment, the preset energy distribution mode also includes a reference energy consumption per unit mileage for each load. The reference energy consumption per unit mileage is the energy consumed by the load under the preset energy distribution mode when the electric vehicle travels a unit mile. The energy consumption-related data also includes the real-time status of each load.

[0111] For any preset energy distribution mode, the energy consumption per unit mileage corresponding to that energy distribution mode can be calculated first. Then, the driving range corresponding to that energy distribution mode can be calculated based on the remaining battery capacity and the energy consumption per unit mileage. For example, the driving range corresponding to the energy distribution mode can be calculated using the following formula: d = E1 / E2, where d represents the driving range corresponding to the energy distribution mode, E1 is the remaining battery capacity, and E2 is the energy consumption per unit mileage corresponding to the energy distribution mode.

[0112] In this embodiment, the energy consumption per unit mile corresponding to the preset energy allocation mode can be E3 + E4, where E3 can be the sum of the energy consumption per unit mile for loads whose operating state in this energy allocation mode is the same as the real-time state in the energy consumption-related data. E4 can be the sum of the reference energy consumption per unit mile for loads whose operating state in this energy allocation mode is different from the operating state in the energy consumption-related data. That is, E3 = E31 + ... + E3n. E31 to E3n are loads whose operating state in the preset energy allocation mode is the same as the real-time state in the energy consumption-related data. E4 = E41 + ... + E4n. E41 to E4n are loads whose operating state in the preset energy allocation mode is different from the real-time state in the energy consumption-related data.

[0113] It is understood that, in addition to the above-mentioned method for calculating the driving range corresponding to each preset energy distribution mode, other methods can also be used to calculate the driving range corresponding to each preset energy distribution mode. This embodiment does not limit this method.

[0114] Step 302: Based on the target mileage and the drivable mileage corresponding to each preset energy allocation mode, determine at least one candidate energy allocation mode from each preset energy allocation mode.

[0115] In this embodiment, a preset energy allocation mode that exceeds the target mileage can be determined as a candidate energy allocation mode. Alternatively, among the preset energy allocation modes that exceed the target mileage, a preset proportion or a preset number of preset energy allocation modes with a larger corresponding driving range can be determined as candidate energy allocation modes.

[0116] The energy distribution mode determination method for electric vehicles provided in this embodiment calculates the drivable mileage corresponding to each preset energy distribution mode when the electric vehicle is driven using each preset energy distribution mode, based on the operating status of each load and the energy consumption per unit mileage corresponding to each load in each preset energy distribution mode. Based on the target mileage and the drivable mileage corresponding to each preset energy distribution mode, at least one candidate energy distribution mode is determined from the preset energy distribution modes. Since at least one candidate energy distribution mode is determined based on the target mileage and the drivable mileage corresponding to each preset energy distribution mode after calculating the drivable mileage, it ensures that the determined candidate energy distribution mode conforms to the current operating conditions, helping users accurately select the energy distribution mode.

[0117] Optionally, step 302, "determine at least one candidate energy allocation mode from each preset energy allocation mode based on the target mileage and the drivable mileage corresponding to each preset energy allocation mode", can be further refined to include step 3021.

[0118] Step 3021: In response to the existence of at least one corresponding preset energy allocation mode with a driving range greater than the target range, the preset energy allocation mode with a driving range greater than the target range is determined as a candidate energy allocation mode.

[0119] The energy allocation mode determination method for electric vehicles provided in this embodiment determines the corresponding preset energy allocation mode with a mileage greater than the target mileage as a candidate energy allocation mode in response to the existence of at least one corresponding preset energy allocation mode with a mileage greater than the target mileage. Since the corresponding mileage is greater than the target mileage, it can ensure that the electric vehicle can reach its destination when energy is allocated according to the candidate energy allocation mode, thus alleviating the user's "range anxiety".

[0120] Optionally, the method for determining the energy distribution mode of an electric vehicle further includes step 401.

[0121] Step 401: In response to the fact that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, the energy allocation mode with the largest corresponding drivable mileage among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0122] In this embodiment, if the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, the remaining battery energy of the electric vehicle may not be sufficient to support the electric vehicle to reach its destination. Therefore, energy can be allocated to the electric vehicle using an energy allocation mode with lower energy consumption or a longer drivable mileage. Consequently, the energy allocation mode with the longest drivable mileage can be identified as a candidate energy allocation mode and recommended to the user.

[0123] Optionally, outputting the energy consumption per unit mileage for each load and each candidate energy allocation mode may also include: outputting the operating status of each load in each candidate energy allocation mode and / or the drivable mileage corresponding to each candidate energy allocation mode.

[0124] The energy distribution mode determination method for electric vehicles provided in this embodiment determines the energy distribution mode with the longest corresponding driving range as a candidate energy distribution mode when the driving range corresponding to each preset energy distribution mode is less than the target range. Since the energy distribution mode with the longest corresponding driving range is determined as the candidate energy distribution mode, the energy distribution mode with the longest driving distance can be recommended to the user when the battery is low, thereby increasing the electric vehicle's range.

[0125] Optionally, the method for determining the energy distribution mode of an electric vehicle further includes steps 501 to 503.

[0126] Step 501: Obtain the nearest charging station to the electric vehicle and the charging mileage of the electric vehicle to the nearest charging station.

[0127] In this embodiment, the electronic device can also acquire the location information of the electric vehicle. Specifically, the electric vehicle can be equipped with a positioning device, and the electronic device can communicate with the positioning device to acquire the location information of the electric vehicle. The electronic device can pre-store the location information of multiple charging piles, and can determine the nearest charging pile to the electric vehicle based on the location information of the electric vehicle and the location information of multiple charging piles, while also acquiring the charging mileage of the electric vehicle to the nearest charging pile.

[0128] Optionally, the electronic device can communicate with a navigation or positioning server to send the electric vehicle's location information to the navigation or positioning server, and receive information from the navigation or positioning server about the nearest charging station and the charging distance of the electric vehicle to the nearest charging station.

[0129] Step 502: In response to the fact that the driving range corresponding to each preset energy allocation mode is less than the target range, and there is at least one preset energy allocation mode with a driving range greater than the charging range, the preset energy allocation mode with the driving range greater than the charging range is determined as the candidate energy allocation mode.

[0130] In this embodiment, if the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, the remaining energy of the electric vehicle's battery may not be able to support the electric vehicle to its destination. At the same time, if there is at least one preset energy allocation mode with a corresponding drivable mileage greater than the charging mileage, the remaining energy of the electric vehicle's battery can support the electric vehicle to travel to the nearest charging station under some of the preset energy allocation modes. In this case, the electronic device can also output the location information of the nearest charging station and / or the charging mileage of the electric vehicle to the nearest charging station, to suggest that the vehicle should first drive to the nearest charging station to charge before proceeding to its destination.

[0131] In this embodiment, a preset energy allocation mode with a driving range greater than the charging range can be determined as a candidate energy allocation mode, and the unit mileage energy consumption and candidate energy allocation modes corresponding to each load are output to visualize the unit mileage loss and candidate energy allocation modes corresponding to each load, thereby informing the user that the remaining battery power can support the electric vehicle to drive to the nearest charging station.

[0132] Step 503: In response to the fact that the driving range corresponding to each preset energy allocation mode is less than the target range and the driving range corresponding to each preset energy allocation mode is less than the charging range, the energy allocation mode with the largest corresponding driving range among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0133] In this embodiment, if the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, and the drivable mileage corresponding to each preset energy allocation mode is less than the charging mileage, it means that the remaining battery power of the electric vehicle cannot support the electric vehicle to travel to its destination, nor can it support the electric vehicle to travel to the nearest charging station. Therefore, the energy allocation mode with the largest drivable mileage can be determined as the candidate energy allocation mode, so as to suggest that the user adopt the energy allocation mode with the largest drivable mileage to allocate energy to the electric vehicle.

[0134] Optionally, when the drivable mileage corresponding to each preset energy distribution mode is less than the target mileage, and the drivable mileage corresponding to each preset energy distribution mode is less than the charging mileage, an insufficient remaining energy alarm message can also be output, and / or the maximum drivable mileage corresponding to each preset energy distribution mode, to inform the user that the remaining battery power is insufficient to support the electric vehicle to travel to the destination and the nearest charging station, and / or the maximum drivable mileage corresponding to each preset energy distribution mode.

[0135] The energy allocation mode determination method for electric vehicles provided in this embodiment obtains the nearest charging station to the electric vehicle and the charging mileage of the electric vehicle to the nearest charging station. In response to the condition that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, and there exists at least one preset energy allocation mode with a drivable mileage greater than the charging mileage, the preset energy allocation mode with the drivable mileage greater than the charging mileage is determined as a candidate energy allocation mode. Similarly, in response to the condition that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, and the drivable mileage corresponding to each preset energy allocation mode is less than the charging mileage, the energy allocation mode with the largest corresponding drivable mileage among all preset energy allocation modes is determined as a candidate energy allocation mode. Since there exists at least one preset energy allocation mode with a drivable mileage greater than the charging mileage, and the preset energy allocation mode with a drivable mileage greater than the charging mileage is determined as a candidate energy allocation mode, it can ensure that the electric vehicle can reach the nearest charging station when energy is allocated according to the candidate energy allocation mode, alleviating the user's "range anxiety." Meanwhile, when the driving range corresponding to each preset energy distribution mode is less than the target range and the charging range, the energy distribution mode with the largest driving range is determined as the candidate energy distribution mode. Therefore, it can maximize the range of electric vehicles when energy is insufficient.

[0136] Example 3

[0137] Figure 4 This is a flowchart illustrating the method for determining the energy distribution mode of an electric vehicle according to Embodiment 3 of this application. Figure 4 As shown, the method for determining the energy allocation mode of an electric vehicle provided in this embodiment, based on any of the above embodiments, includes user feedback on each candidate energy allocation mode, such as information that the user did not select any option within a preset time or the candidate energy allocation mode selected by the user. Furthermore, step 205, "in response to the user's feedback information on each candidate energy allocation mode, determine the target energy allocation mode of the electric vehicle", is further refined to include steps 601 to 602.

[0138] Step 601: In response to the feedback information that no information was selected within a preset time and the number of candidate energy allocation modes is one, the candidate energy allocation mode is determined as the target energy allocation mode.

[0139] In this embodiment, when the electronic device outputs the unit mileage energy consumption and candidate energy allocation modes corresponding to each load, and visualizes the unit mileage loss and candidate energy allocation modes corresponding to each load, the user can interact with the electronic device, thereby enabling the electronic device to obtain feedback information from the user regarding each candidate energy allocation mode. The user's interaction with the electronic device can be: no interaction within a preset time, or selection of a candidate energy allocation mode. If the user does not interact within the preset time, the feedback information can be determined as the user not selecting any mode within the preset time; if the user selects a candidate energy allocation mode, the feedback information can be determined as the selected candidate energy allocation mode. Of course, in addition to the above methods, the electronic device can also determine the feedback information through other means, which is not limited in this embodiment.

[0140] Here, when the feedback information is that no information is selected within a preset time, if there is only one candidate energy allocation mode, the electronic device can determine the candidate energy allocation mode as the target energy allocation mode. If there are multiple candidate energy allocation modes, the electronic device can determine the one with the longest driving range among the candidate energy allocation modes as the target energy allocation mode to ensure that the electric vehicle can drive to the destination or the nearest charging station, or to determine that the electric vehicle can have the longest driving range.

[0141] Optionally, each preset energy allocation mode can have a pre-set priority, which can be set by the user. When the feedback information is no selection within a preset time and there are multiple candidate energy allocation modes, the electronic device can determine the preset energy allocation mode with the highest priority as the target energy allocation mode, so as to improve the user experience while ensuring that the electric vehicle can drive to the destination or the nearest charging station.

[0142] Step 602: In response to the feedback information regarding the candidate energy allocation mode selected by the user, the energy allocation mode selected by the user is determined as the target energy allocation mode.

[0143] In this embodiment, it can be understood that if the user selects from the candidate energy allocation modes, the energy allocation mode selected by the user will be determined as the target energy allocation mode according to the user's selection.

[0144] The energy allocation mode determination method for electric vehicles provided in this embodiment includes user feedback on candidate energy allocation modes: if the user does not select information within a preset time or selects a candidate energy allocation mode, the method determines the candidate energy allocation mode as the target energy allocation mode in response to the feedback information indicating no selection within the preset time and that there is only one candidate energy allocation mode; and in response to the feedback information indicating the user selects a candidate energy allocation mode, the method determines the energy allocation mode selected by the user as the target energy allocation mode. Since determining the candidate energy allocation mode as the target energy allocation mode when the feedback information indicates no selection within the preset time and that there is only one candidate energy allocation mode helps the user select the most energy-efficient energy allocation mode, and determining the user's selected energy allocation mode as the target energy allocation mode when the feedback information indicates the user selects a candidate energy allocation mode, the energy allocation mode is more in line with the user's preferences, improving the user experience.

[0145] Example 4

[0146] Figure 5 This is a schematic diagram of the structure of the energy distribution mode determination device for an electric vehicle according to Embodiment 4 of this application. Figure 5 As shown, the energy distribution mode determination device 50 for electric vehicles provided in this embodiment includes: an acquisition module 51, a calculation module 52, a first determination module 53, an output module 54, and a second determination module 55.

[0147] The acquisition module 51 is used to acquire the target mileage, remaining battery power, and real-time vehicle speed of the electric vehicle, as well as the real-time current and real-time voltage of each load on the electric vehicle.

[0148] The calculation module 52 is used to calculate the energy consumption per unit mile of each load corresponding to each unit mile of electric vehicle travel, based on the real-time vehicle speed and the real-time current and real-time voltage of each load.

[0149] The first determining module 53 is used to determine at least one candidate energy allocation mode from a variety of preset energy allocation modes based on the target mileage, the remaining battery power and the energy consumption per unit mileage corresponding to each load.

[0150] The output module 54 is used to output the unit mileage energy consumption and each candidate energy allocation mode corresponding to each load, so as to visualize the unit mileage loss and each candidate energy allocation mode corresponding to each load.

[0151] The second determining module 55 is used to determine the target energy allocation mode of the electric vehicle in response to user feedback information on each candidate energy allocation mode.

[0152] Optionally, the load energy consumption related data includes the real-time current and real-time voltage corresponding to the load operation. The calculation module 52 is specifically used for:

[0153] Calculate the time range corresponding to a unit distance traveled by an electric vehicle based on real-time vehicle speed;

[0154] The product of the real-time current and real-time voltage of each load is integrated over a time range to determine the energy consumption per unit mileage for each load.

[0155] Optionally, the preset energy distribution mode includes the operating status of each load, and the first determining module 53 is specifically used for:

[0156] Based on the operating status of each load in each preset energy distribution mode and the energy consumption per unit mileage corresponding to each load, calculate the remaining battery charge and the driving range corresponding to each preset energy distribution mode when the electric vehicle is driven in each preset energy distribution mode.

[0157] Based on the target mileage and the drivable mileage corresponding to each preset energy allocation mode, at least one candidate energy allocation mode is determined from each preset energy allocation mode.

[0158] Optionally, the first determining module 53 is further used for:

[0159] In response to the existence of at least one corresponding preset energy allocation mode with a driving range greater than the target range, the preset energy allocation mode with a driving range greater than the target range is determined as a candidate energy allocation mode.

[0160] Optionally, the energy distribution mode determination device 50 for electric vehicles further includes a third determination module, which is used for:

[0161] In response to the fact that the drivable mileage corresponding to each preset energy allocation mode is less than the target mileage, the energy allocation mode with the largest corresponding drivable mileage among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0162] Optionally, the energy distribution mode determination device 50 for electric vehicles further includes a fourth determination module, which is used for:

[0163] Obtain the nearest charging station to the electric vehicle and the charging distance the electric vehicle travels to the nearest charging station;

[0164] In response to the fact that the driving range corresponding to each preset energy allocation mode is less than the target range, and there is at least one preset energy allocation mode with a driving range greater than the charging range, the preset energy allocation mode with a driving range greater than the charging range is determined as the candidate energy allocation mode.

[0165] In response to the fact that the driving range corresponding to each preset energy allocation mode is less than the target range, and the driving range corresponding to each preset energy allocation mode is less than the charging range, the energy allocation mode with the largest corresponding driving range among the preset energy allocation modes is determined as the candidate energy allocation mode.

[0166] Optionally, user feedback on each candidate energy allocation mode includes: information that the user did not select within a preset time or the candidate energy allocation mode selected by the user. The second determining module 55 is used for:

[0167] If the feedback information is that no information is selected within a preset time and the number of candidate energy allocation modes is only one, the candidate energy allocation mode is determined as the target energy allocation mode.

[0168] In response to the feedback information regarding the candidate energy allocation mode selected by the user, the energy allocation mode selected by the user is determined as the target energy allocation mode.

[0169] The electric vehicle energy distribution mode determination device provided in this embodiment can execute the electric vehicle energy distribution mode determination method provided in any of the above embodiments. The specific implementation method and principle are similar, and will not be described again here.

[0170] Example 5

[0171] Figure 6 This is a schematic diagram of the structure of an electronic device according to Embodiment 5 of this application. Figure 6 As shown, the electronic device 60 provided in this embodiment includes a memory 61, a processor 62, and an output device 63.

[0172] The memory 61, processor 62, and output device 63 are interconnected.

[0173] Memory 61 stores computer-executed instructions.

[0174] Output device 63 is used to output information.

[0175] The processor 62 executes the computer execution instructions stored in the memory 61 to implement the energy distribution mode determination method for electric vehicles provided in any of the above embodiments. The specific implementation method and principle are similar and will not be described in detail here.

[0176] The memory 61, processor 62, and output device 63 can be interconnected via a bus. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be categorized into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0177] The memory 61 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk, etc.

[0178] The output device 63 can be a display screen, a transmitter, etc. The display screen can output the unit mileage energy consumption and candidate energy allocation modes for each load in text or image format, providing a visual representation of the unit mileage loss and candidate energy allocation modes for each load. The transmitter can send the unit mileage energy consumption and candidate energy allocation modes for each load to the display unit of the electric vehicle, enabling the display unit or audio output unit of the electric vehicle to visually display the unit mileage loss and candidate energy allocation modes for each load.

[0179] In an exemplary embodiment, the electronic device 60 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0180] Embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions. When executed by a processor, these instructions are used to implement the energy distribution mode determination method for an electric vehicle as provided in any of the above embodiments. Exemplarily, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), magnetic tape, floppy disk, or optical data storage device, etc.

[0181] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the method for determining the energy distribution mode of an electric vehicle as provided in any of the above embodiments.

[0182] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the module division in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple modules can be combined, or integrated into another system, or some features can be ignored or not executed.

[0183] Furthermore, unless otherwise specified, the functional modules in the various embodiments of this application can be integrated into one module, or each module can exist physically separately, or two or more modules can be integrated together. The integrated modules described above can be implemented in hardware or as software program modules.

[0184] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0185] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0186] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0187] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method of determining an energy distribution pattern of an electric vehicle, characterized by, The method comprises: acquiring a target mileage of an electric vehicle, a remaining battery capacity, a real-time vehicle speed, and energy consumption related data of each load on the electric vehicle; calculating, according to the real-time vehicle speed and the energy consumption related data of each load, a unit mileage energy consumption corresponding to each load per unit mileage of the electric vehicle; calculating, according to a running state of each load in each preset energy distribution mode and the unit mileage energy consumption corresponding to each load, a feasible mileage corresponding to each preset energy distribution mode when the electric vehicle travels in the preset energy distribution mode, based on the remaining battery capacity; determining at least one candidate energy distribution mode from the preset energy distribution modes according to the target mileage and the feasible mileage corresponding to each preset energy distribution mode; outputting the unit mileage energy consumption corresponding to each load and each candidate energy distribution mode to visually display the unit mileage energy consumption corresponding to each load and each candidate energy distribution mode; determining a target energy distribution mode of the electric vehicle in response to feedback information of the user on each candidate energy distribution mode.

2. The method of claim 1, wherein, The energy consumption related data of the load includes real-time current and real-time voltage corresponding to the running of the load; The method for calculating, according to the real-time vehicle speed and the energy consumption related data of each load, a unit mileage energy consumption corresponding to each load per unit mileage of the electric vehicle comprises: calculating, according to the real-time vehicle speed, a time range corresponding to a unit mileage of the electric vehicle; determining, as the unit mileage energy consumption corresponding to each load, an integral calculation result of a product of the real-time current and the real-time voltage of each load within the time range.

3. The method of claim 1, wherein, The method for determining at least one candidate energy distribution mode from the preset energy distribution modes according to the target mileage and the feasible mileage corresponding to each preset energy distribution mode comprises: in response to the existence of at least one preset energy distribution mode corresponding to a feasible mileage greater than the target mileage, determining the preset energy distribution mode corresponding to the feasible mileage greater than the target mileage as a candidate energy distribution mode.

4. The method of claim 3, wherein, The method further comprises: in response to the feasible mileage corresponding to each preset energy distribution mode being less than the target mileage, determining, as a candidate energy distribution mode, an energy distribution mode corresponding to the greatest feasible mileage among the preset energy distribution modes.

5. The method of claim 3, wherein, The method further comprises: acquiring a charging pile closest to the electric vehicle and a charging mileage of the electric vehicle to the closest charging pile; in response to the feasible mileage corresponding to each preset energy distribution mode being less than the target mileage and the existence of at least one preset energy distribution mode corresponding to a feasible mileage greater than the charging mileage, determining the preset energy distribution mode corresponding to the feasible mileage greater than the charging mileage as a candidate energy distribution mode; in response to the feasible mileage corresponding to each preset energy distribution mode being less than the target mileage and the feasible mileage corresponding to each preset energy distribution mode being less than the charging mileage, determining, as a candidate energy distribution mode, an energy distribution mode corresponding to the greatest feasible mileage among the preset energy distribution modes.

6. The method of claim 1, wherein, The feedback of the user on each candidate energy distribution mode includes that the user does not select information within a preset time or that the user selects a candidate energy distribution mode. The method comprises the following steps: In response to the feedback information, determining a target energy distribution mode of the electric vehicle, comprising: In response to the feedback information being no selection information within a preset time and the number of candidate energy distribution modes being one, determining the candidate energy distribution mode as the target energy distribution mode; 7. An energy distribution mode determining device for an electric vehicle, characterized by comprising: In response to the feedback information being a candidate energy distribution mode selected by the user, determining the energy distribution mode selected by the user as the target energy distribution mode. The method comprises the following steps: An acquisition module is configured to acquire a target mileage of the electric vehicle, a remaining battery capacity, and a real-time vehicle speed, and real-time currents and real-time voltages of each load on the electric vehicle; A calculation module is configured to calculate a unit mileage energy consumption corresponding to each load per unit mileage of the electric vehicle according to the real-time vehicle speed and the real-time currents and real-time voltages of each load; A first determination module is configured to determine at least one candidate energy distribution mode from a plurality of preset energy distribution modes according to the target mileage, the remaining battery capacity, and the unit mileage energy consumption corresponding to each load; An output module is configured to output the unit mileage energy consumption corresponding to each load and each candidate energy distribution mode, so as to visually display the unit mileage energy consumption corresponding to each load and each candidate energy distribution mode; A second determination module is configured to determine a target energy distribution mode of the electric vehicle in response to feedback information of each candidate energy distribution mode from the user; The first determination module is specifically configured to: According to the operating state of each load in each preset energy distribution mode and the unit mileage energy consumption corresponding to each load, calculate a drivable mileage corresponding to each preset energy distribution mode when the electric vehicle drives by using each preset energy distribution mode with the remaining battery capacity; 8. An electronic device, comprising: According to the target mileage and the drivable mileage corresponding to each preset energy distribution mode, determine at least one candidate energy distribution mode from each preset energy distribution mode. The method comprises the following steps: A memory, a processor, and an output device; The memory, the processor, and the output device are circuit-interconnected; The memory stores computer-executed instructions; The output device is configured to output information; 9. A computer-readable storage medium, characterized in that, The processor executes the computer-executed instructions stored in the memory, so as to implement the method according to any one of claims 1-6.

10. A computer program product, characterised in that, The computer-readable storage medium stores computer-executed instructions, and the computer-executed instructions are executed by the processor to implement the method according to any one of claims 1-6. The computer program is executed by the processor to implement the method according to any one of claims 1-6.

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