Flight time prediction method and device of flying car, electronic equipment and storage medium

Abstract

The application provides a flight time prediction method and device of a flying car, electronic equipment and a storage medium, comprising: when an instruction indicating that the flying car takes off is received, determining a battery parameter of the flying car, wherein the battery parameter comprises a first battery parameter and a second battery parameter; determining a first temperature corresponding to a maximum discharge power of the flying car based on a first temperature determination algorithm and the first battery parameter, and determining a second temperature corresponding to the maximum discharge power of the flying car based on a second temperature determination algorithm and the second battery parameter; determining a predicted state of charge of the flying car according to a relationship between the first temperature and the second temperature; determining a real-time state of charge of the flying car, and determining a target remaining flight time of the flying car according to the predicted state of charge and the real-time state of charge. Through the application, the flight time in the flight working condition can be predicted, the flight time is predicted in real time through the maximum discharge power, and the accuracy of the flight time prediction is improved.

Description

Technical Field

[0001] This application relates to the field of flying car technology, and more specifically, to a method, apparatus, electronic device, and storage medium for predicting flight time for a flying car. Background Technology

[0002] With the rapid development of technology, flying cars are poised to become a new mode of transportation. During the flight of a flying car, it's crucial to inform users of its real-time flight time upon takeoff to increase their confidence in the flight plan. Takeoff should be prohibited if the predicted flight time is insufficient to ensure user safety. However, currently, most methods rely on the remaining energy of conventional cars to estimate flight time. But because flying cars have a higher actual power output, factors such as temperature and cell voltage can affect the battery, leading to a decrease in the actual power delivered. This limits the flight power and consequently reduces the accuracy of flight time predictions, increasing the risk to users. Therefore, improving the accuracy of flight time prediction for flying cars is a pressing issue that needs to be addressed. Summary of the Invention

[0003] In view of this, embodiments of this application propose a flight time prediction method, apparatus, electronic device, and storage medium for flying cars to improve the above-mentioned problems.

[0004] According to one aspect of the embodiments of this application, a method for predicting flight time for a flying car is provided. The method includes: when receiving an instruction to instruct the flying car to take off, determining battery parameters of the flying car, wherein the battery parameters include first battery parameters and second battery parameters; determining a first temperature corresponding to the maximum discharge power of the flying car based on a first temperature determination algorithm and the first battery parameters, and determining a second temperature corresponding to the maximum discharge power of the flying car based on a second temperature determination algorithm and the second battery parameters; determining a predicted state of charge of the flying car according to the relationship between the first temperature and the second temperature; determining the real-time state of charge of the flying car, and determining the target remaining flight time of the flying car according to the predicted state of charge and the real-time state of charge.

[0005] According to one aspect of the embodiments of this application, a flight time prediction device for a flying car is provided. The device includes: a battery parameter determination module, configured to determine the battery parameters of the flying car when receiving an instruction instructing the flying car to take off, wherein the battery parameters include first battery parameters and second battery parameters; a temperature determination module, configured to determine a first temperature corresponding to the maximum discharge power of the flying car based on a first temperature determination algorithm and the first battery parameters, and to determine a second temperature corresponding to the maximum discharge power of the flying car based on a second temperature determination algorithm and the second battery parameters; a predicted state of charge determination module, configured to determine the predicted state of charge of the flying car according to the relationship between the first temperature and the second temperature; and a target remaining flight time determination module, configured to determine the real-time state of charge of the flying car, and to determine the target remaining flight time of the flying car according to the predicted state of charge and the real-time state of charge.

[0006] According to one aspect of the embodiments of this application, an electronic device is provided, including: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the flight time prediction method for a flying car as described above.

[0007] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided, on which computer-readable instructions are stored, which, when executed by a processor, implement the flight time prediction method for a flying car as described above.

[0008] In this application, after receiving an instruction to take off, the first and second battery parameters of the flying car are determined. Then, a first temperature is determined based on a first temperature determination algorithm and the first battery parameters, and a second temperature is determined based on a second temperature determination algorithm and the second battery parameters. This allows the predicted state of charge (SOC) of the flying car to be calculated based on the relationship between the first and second temperatures. Since the preset and real-time SOC of the flying car are related to flight time, the real-time SOC can be determined first, and then the target remaining flight time can be determined based on the predicted and real-time SOC. This application can predict the flight time of a flying car under flight conditions and improve the accuracy of flight time prediction by using maximum discharge power in real time.

[0009] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0010] 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. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0011] Figure 1 This is a schematic diagram of a flight time prediction model for a flying car according to an embodiment of this application.

[0012] Figure 2 This is a flowchart illustrating a flight time prediction method for a flying car according to an embodiment of this application.

[0013] Figure 3 This is a flowchart illustrating a flight time prediction method for a flying car according to another embodiment of this application.

[0014] Figure 4 This is a flowchart illustrating the specific steps of step 240 according to an embodiment of this application.

[0015] Figure 5 This is a schematic diagram illustrating the determination of the permissible flight range of a flying car based on the maximum discharge power ratio of its battery, the predicted state of charge, and the first temperature, according to an embodiment of this application.

[0016] Figure 6 This is a flowchart illustrating the specific steps of step 250 in one embodiment of this application.

[0017] Figure 7 This is a flowchart illustrating the specific steps of step 260 in one embodiment of this application.

[0018] Figure 8 This is a flowchart illustrating a flight time prediction method for a flying car according to another embodiment of this application.

[0019] Figure 9 This is a schematic diagram illustrating the determination of discharge power based on real-time state of charge and current battery temperature according to an embodiment of this application.

[0020] Figure 10 This is a graph of temperature versus SOC shown according to an embodiment of this application.

[0021] Figure 11 According to another embodiment of the application, a temperature versus SOC curve adjusted according to the battery health status is shown.

[0022] Figure 12 This is a block diagram illustrating a flight time prediction device for a flying car according to an embodiment of this application.

[0023] Figure 13 This is a hardware structure diagram of an electronic device according to an embodiment of this application.

[0024] The accompanying drawings have illustrated specific embodiments of the present invention, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the inventive concept in any way, but rather to illustrate the concept of the invention to those skilled in the art through specific embodiments. Detailed Implementation

[0025] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises 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.

[0027] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0028] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be decomposed, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0029] Figure 1 This is a flight time prediction model according to an embodiment of the present application, in which, as shown in the flight time prediction model, Figure 1 As shown, a Hall sensor is used to collect the battery pack current in real time, a battery total voltage sensor is used to collect the battery pack total voltage in real time, a cell voltage sensor is used to determine the cell voltage of the battery, a cell temperature sensor is used to collect the battery temperature, a flight control unit (FCU) is used to determine and control the flight status and flight mode of the flying car, and a thermal management unit (LDCU) is used to control the battery heating power and battery cooling power of the flying car. Among them, the Hall sensor, battery total voltage sensor, cell voltage sensor, cell temperature sensor, flight controller, and thermal management unit are all connected to the vehicle domain controller (EMU), and the vehicle domain controller is connected to the display instrument to display the determined flight time.

[0030] like Figure 1 As shown, the vehicle domain controller can determine the activation of flight time calculation for the flying car based on the flight status. After activating flight time calculation, it determines the battery health status of the flying car based on the number of charge and discharge cycles, determines the real-time state of charge (SOC) of the flying car based on the battery cell temperature and cell voltage, then determines the predicted SOC of the flying car based on the real-time SOC, the total battery voltage and battery current, determines the predicted cell temperature of the battery based on the cell temperature, battery heating power and battery cooling power, and determines the limits of the SOC and cell temperature based on the current cell temperature, real-time SOC, and battery health status, thereby determining the discharge capacity boundary of the flying car. Finally, it can predict the discharge power based on the cell temperature, predicted SOC, predicted cell temperature, the flight mode of the flying car, and the discharge boundary capability of the flying car to determine the first remaining flight time, and predict the remaining energy based on the flight conditions of the flying car to determine the second remaining flight time. Based on the first and second remaining flight times, it predicts the flight time to determine the target remaining flight time of the flying car.

[0031] Please see Figure 2 , Figure 2 This application illustrates a flight time prediction method for a flying car according to an embodiment of the present application. In a specific embodiment, this flight time prediction method for a flying car can be applied to, for example... Figure 12 The flight time prediction device 400 of the flying car shown and the electronic equipment 500 equipped with the flight time prediction device 400 of the flying car are shown. Figure 13 The specific process of this embodiment will be described below. It is understood that this method can be executed by a cloud server with computing power or by an in-vehicle server. The following will focus on... Figure 2 The process shown will be described in detail. The control method for the flying car may specifically include the following steps:

[0032] Step 110: When an instruction is received to instruct the flying car to take off, the battery parameters of the flying car are determined, wherein the battery parameters include first battery parameters and second battery parameters.

[0033] In one approach, when the flying car's rotors are in the open state, it receives a command instructing the flying car to take off. Optionally, the flying car's flight states include at least the rotor open state, takeoff state, and rotor folded state, where the flight states include hovering state, flight state, and landing state. Optionally, when the flying car is in the rotor open state, the flying car's processor generates a command instructing the flying car to fly, and then the flying car's flight controller receives this command and determines the flying car's battery parameters.

[0034] Optionally, when the flying car is in a land-based operating condition, the remaining flight time of the flying car is predicted using the traditional method of calculating the remaining range. When the flying car is in a rotor-folded state, the prediction of the remaining flight time of the flying car is stopped, and the remaining flight time is set to an invalid value on the display device of the flying car. The display can be in the form of "--" or in the form of the text "invalid", which can be set according to actual needs.

[0035] In one approach, battery parameters refer to the parameters corresponding to the battery pack of the flying car. Optionally, battery parameters can be the battery temperature, remaining battery capacity, state of charge (SOC), and battery discharge capacity. Optionally, the first battery parameter and the second battery parameter can be a set of multiple different battery parameters, or they can be a set of the same battery parameters. The first battery parameter and the second battery parameter can be set according to actual needs, and no specific limitation is made here.

[0036] Step 120: Determine the first temperature corresponding to the maximum discharge power of the flying car based on the first temperature determination algorithm and the first battery parameters, and determine the second temperature corresponding to the maximum discharge power of the flying car based on the second temperature determination algorithm and the second battery parameters.

[0037] One approach is to pre-set different temperature determination algorithms, thereby facilitating the determination of the first and second temperatures based on different algorithms. Optionally, both the first and second temperatures are predicted temperatures corresponding to the maximum discharge power of the flying car under flight conditions. In other embodiments, the first and second temperatures can be predicted temperatures corresponding to the minimum discharge power of the flying car under flight conditions.

[0038] Optionally, the first temperature determination algorithm and the second temperature determination algorithm can be temperature determination algorithms using calculation formulas corresponding to battery parameters.

[0039] Optionally, the first battery parameter may include the discharge coefficient of the flying car's battery, wherein the discharge coefficient may include a first discharge coefficient and a second discharge coefficient, and the first discharge coefficient and the second discharge coefficient may be determined by curve fitting based on the current battery temperature of the flying car's battery and the current SOC of the flying car at the maximum discharge power.

[0040] Optionally, the discharge coefficient may also include a third discharge coefficient and a fourth discharge coefficient, which may be determined by curve fitting based on the current battery temperature of the flying car's battery and the current SOC of the flying car at the minimum discharge power.

[0041] Optionally, the second battery parameters may include the battery cell mass, cell specific heat capacity, and total self-heating of the battery cells.

[0042] Step 130: Determine the predicted state of charge of the flying car based on the relationship between the first temperature and the second temperature.

[0043] In one approach, both the first temperature and the second temperature are predicted temperatures of the flying car, and under the same discharge power, the first temperature and the second temperature are equal. Furthermore, both the first temperature determination algorithm and the second temperature determination algorithm are related to the predicted state of charge. Therefore, the predicted state of charge can be calculated based on the relationship between the first temperature and the second temperature, thereby determining the predicted state of charge of the flying car.

[0044] Optionally, the first temperature determination algorithm can be the formula T1 = K1 * SCO′ + K2, where K1 is the first discharge coefficient, K2 is the second discharge coefficient, and SOC′ is the predicted state of charge; the second determination algorithm can be the formula T2 = (Q / m / C + K Thm )*(SOC-SOC′) / I avg +T0, where Q is the total self-heating of the battery cells, m is the cell mass of the flying car battery, C is the specific heat capacity of the cell, SOC is the current state of charge of the flying car, SOC′ is the predicted state of charge, and I avg Let T0 be the average current of the flying car under the previous operating condition, and K be the current temperature of the flying car battery. Thm Let SOC′ be the temperature rise coefficient of the flying car battery. Since the first temperature is equal to the second temperature, we can obtain SOC′=[(Q / m / C+K)]. Thm )*SOC / I avg +T0-K2] / [(Q / m / C+K Thm )] / I avg +K1, thus obtaining the predicted state of charge.

[0045] Step 140: Determine the real-time state of charge of the flying car, and determine the target remaining flight time of the flying car based on the predicted state of charge and the real-time state of charge.

[0046] One approach is to first obtain the current state of charge (SOC) of the flying car and the real-time current of its battery. Based on this, the SOC for the next moment can be estimated using the ampere-hour method. Then, the actual voltage of the flying car's battery can be obtained, and the real-time SOC can be corrected accordingly. Alternatively, the formula SOC = SOCf K+1 +K′*(UH*U0) is used to determine the real-time state of charge (SOC) of the flying car, where SOC is... K+1 The state of charge at the next moment is estimated using the ampere-hour method based on the current state of charge and real-time current. K′ is the Kalman gain, U is the actual voltage of the flying car battery, and U0 is the cell voltage predicted by the battery RC model based on the real-time current, the state of charge at the next moment, and the cell temperature of the flying car battery.

[0047] Optionally, before determining the target remaining flight time of the flying car, the average current of the flying car in the previous operating condition can be read from the electronic control unit of the flying car. This average current can then be used to determine the target remaining flight time based on the predicted state of charge, the real-time state of charge, and the average current. Alternatively, the formula SOC′=SOC-I can be used. avg *t determines the prediction time, where SOC is the real-time state of charge, SOC′ is the predicted state of charge, and I avgLet t be the average current and t be the target remaining flight time. Optionally, the flying car can store the average current under the previous flight cycle conditions in the read-only memory (EEPROM) of the electronic control unit, so that the average current of the flying car in the previous operating condition can be read in the electronic control unit.

[0048] In the embodiments of this application, after receiving an instruction to instruct the flying car to take off, the first battery parameters and the second battery parameters of the flying car are determined. Then, a first temperature can be determined based on a first temperature determination algorithm and the first battery parameters, and a second temperature can be determined based on a second temperature determination algorithm and the second battery parameters. This allows the predicted state of charge (SOC) of the flying car to be calculated based on the relationship between the first and second temperatures. Since the preset SOC and real-time SOC of the flying car are related to flight time, the real-time SOC of the flying car can be determined first, and then the target remaining flight time of the flying car can be determined based on the predicted SOC and the real-time SOC. This application can predict the flight time of the flying car under flight conditions and predict the flight time in real time through maximum discharge power, thereby improving the accuracy of the flight time prediction for the flying car.

[0049] Please see Figure 3 , Figure 3 This paper illustrates a flight time prediction method 3 for a flying car according to an embodiment of this application. The following will focus on... Figure 3 The process shown will be described in detail. The control method for the flying car may specifically include the following steps:

[0050] Step 210: When an instruction is received to instruct the flying car to take off, the battery parameters of the flying car are determined, wherein the battery parameters include first battery parameters and second battery parameters.

[0051] Step 220: Determine the first temperature corresponding to the maximum discharge power of the flying car based on the first temperature determination algorithm and the first battery parameters, and determine the second temperature corresponding to the maximum discharge power of the flying car based on the second temperature determination algorithm and the second battery parameters.

[0052] Step 230: Determine the predicted state of charge of the flying car based on the relationship between the first temperature and the second temperature.

[0053] The specific steps of steps 210-230 can be found in steps 110-130, and will not be repeated here.

[0054] Step 240: Determine the flight mode and real-time state of charge of the flying car; based on the predicted state of charge and the real-time state of charge, determine the first remaining flight time of the flying car in the flight mode.

[0055] As one approach, since the average current of the flying car is different in different flight modes, the first remaining flight time is different in different flight modes. Therefore, before determining the first remaining flight time of the flying car, it is necessary to determine the flight mode of the flying car.

[0056] Optionally, the flight mode of the flying car can be determined based on the flight commands received by the flying car. The flight commands include an identifier corresponding to the flight mode, which can be used to determine the flying car's flight mode. For example, when the user selects automatic flight mode, a flight command carrying the automatic flight mode is generated, and the flight mode of the flying car is determined based on the identifier in the flight command.

[0057] Optionally, after determining the flight mode of the flying car, the average current of the flying car in the corresponding flight mode is obtained, so as to determine the first predicted flight time based on the real-time state of charge, the predicted state of charge, and the average current.

[0058] In some embodiments, such as Figure 4 As shown, step 240 includes:

[0059] Step 241: Determine the battery health status of the flying car, the real-time state of charge of the flying car, and the current battery temperature of the flying car.

[0060] As a method, in order to make the determination of the first remaining flight time more accurate, the battery health status of the flying car, the real-time state of charge of the flying car, and the current battery temperature of the flying car can be used as influencing factors to correct the first remaining flight time before determining the first remaining flight time.

[0061] Optionally, the battery health status of the flying car can be a score indicating its battery health. Different degradation ranges can be set for different levels of battery health, with different degradation coefficients corresponding to different degradation ranges. The initial remaining flight time can then be updated based on these degradation coefficients. Alternatively, different levels of battery health can correspond to different flight indicators. For example, if the battery health status of the flying car falls below a certain health threshold, it can be determined that the flying car cannot fly. In this case, an alarm message can be generated to notify the user.

[0062] Optionally, since the battery of the flying car will heat up during flight, the hotter the battery, the more electrical energy it consumes, and the shorter the remaining flight time. Therefore, the current battery temperature of the flying car also affects the remaining flight time. When determining the first remaining flight time of the flying car, the first remaining flight time can be updated based on the current battery temperature.

[0063] In some embodiments, step 241 includes: determining the nominal battery capacity of the flying car, the number of times the flying car is charged, the number of times the flying car is discharged, and the charging and discharging current of the flying car; determining the available battery capacity of the flying car based on the charging and discharging current; and determining the battery health status of the flying car based on the nominal battery capacity, the number of times the flying car is charged, the number of times the flying car is discharged, and the available battery capacity.

[0064] In one approach, the number of times a flying car is charged can refer to the number of times its battery has been charged before it performs the current flight mission, and the number of times its battery has been discharged can refer to the number of times its battery has been discharged before it performs the current flight mission. The nominal capacity of a flying car's battery can be the amount of current that the battery can output from the fully charged voltage to the discharge termination voltage after it leaves the factory. The nominal capacity of the battery affects the flight time of the flying car.

[0065] Optionally, the usable battery capacity of a flying car refers to the amount of current that the flying car can output from the fully charged voltage to the discharge termination voltage after multiple charge-discharge cycles. Optionally, the usable battery capacity can be determined by integrating the battery current over time.

[0066] One method is through formulas To determine the battery health status, A1 and A2 are coefficients less than 1, and A1 and A2 are not equal; M is the number of charge cycles; N is the number of discharge cycles; and R is the usable battery capacity. e This refers to the battery's nominal capacity.

[0067] Step 242: Determine whether the flying car meets the charge requirements based on the real-time state of charge and the battery health status, and determine whether the flying car meets the temperature requirements based on the current battery temperature and the first temperature or the second temperature.

[0068] As one approach, in order to ensure the flight safety of the flying car and the accuracy of the determined first remaining flight time, it is necessary to determine whether the flying car meets the charge and temperature requirements, and then determine the first remaining flight time.

[0069] Optionally, the charge requirement can be that the real-time state of charge (SOC) of the flying car is within a target charge range. After determining the battery health state of the flying car, the corresponding target charge range is determined based on the battery health state. This determines whether the real-time SOC of the flying car is within the target charge range. If the real-time SOC of the flying car is determined to be within the target charge range, then the flying car is determined to meet the charge requirement. Optionally, a mapping relationship between different battery health states and charge ranges can be pre-set. After determining the battery health state of the flying car, the corresponding target charge range is determined based on this mapping relationship, which facilitates the determination of whether the flying car meets the charge requirement. For example, if the target charge ranges are [40, 80] and [80, 100], and the real-time SOC is determined to satisfy SOC ≥ 80 or 40 < SOC < 100, then the flying car is determined to meet the charge requirement.

[0070] One approach is to perform curve fitting based on the flying car's maximum battery discharge power ratio, predicted state of charge, and initial temperature to determine the flying car's permissible flight range, and then predict flight time within that range. Figure 5 As shown, region A is defined as the permissible flight range for the flying car. Within region A, flight time is predicted in the direction indicated by the arrow, thereby determining the corresponding charge and temperature requirements for the flying car.

[0071] Optionally, the temperature requirement can be that the current battery temperature of the flying car is within a target temperature range. After determining a first or second temperature, a third or fourth temperature at minimum power is determined based on the first or second battery parameters. Then, the target temperature range is determined based on the first and third temperatures, or the second or fourth temperature. This allows the flying car to determine whether it meets the temperature requirement. For example, if the target temperature range is [T3, T4], where T3 < T0 < T4, then the flying car meets the temperature requirement. Optionally, the target temperature range can also be [0, 40], and can be set according to actual needs; no specific limitation is made here.

[0072] Step 243: When it is determined that the flying car meets the charge requirement and the temperature requirement, the first remaining flight time is determined according to the flight mode, the predicted state of charge and the real-time state of charge.

[0073] As one approach, if it is determined that the real-time state of charge of the flying car is greater than a first preset state of charge and the current battery temperature of the flying car is greater than a first temperature threshold and less than a second temperature threshold, then the flying car is determined to meet both the charge and temperature requirements. If it is determined that the state of charge of the flying car is greater than the second state of charge and less than the first state of charge, and the current battery temperature of the flying car is less than the first temperature and less than a third temperature, then the flying car is determined to meet both the charge and temperature requirements. Here, the second state of charge is greater than the first state of charge. The first and third temperature thresholds are set according to actual needs. The first temperature is the battery temperature corresponding to the flying car at maximum discharge power, and the third temperature is the battery temperature corresponding to the flying car at minimum discharge power. The determination of the first and third temperatures can be referred to the specific steps described in step 120, and will not be repeated here. Optionally, the first state of charge can be 80%, the second state of charge can be 40%, the first temperature threshold can be 0℃, and the second temperature threshold can be 40℃. When the initial SOC ≥ 80% and 0℃ < T0 < 40℃; or 40% < SOC < 80% and T0 > K3*SOC0 + K4 and T0 < K1*SOC0 + K2, it is determined that the flying car meets the charge and temperature requirements.

[0074] As one approach, since the average current of the flying car differs across flight modes, the flight mode can be determined before determining the first remaining flight time. This facilitates determining the first remaining flight time within the corresponding flight mode. Optionally, the flight mode can be determined based on flight commands received by the flying car. These flight commands include an identifier corresponding to the flight mode, which can be used to determine the flight mode. For example, when the user selects automatic flight mode, a flight command carrying the automatic flight mode information is generated, and the flight mode is determined based on the identifier in the flight command.

[0075] As another method, if it is determined that the flying car does not meet the charge or temperature requirements, the flight time of the flying car can be set to 0, thus determining that the flying car cannot fly. Optionally, the flying car not meeting the charge or temperature requirements can be SOC ≤ 40%, 40% < SOC < 80% and T0 ≤ K3*SOC0 + K4 or T0 ≥ K1*SOC0 + K2, SOC ≥ 40% and T0 ≤ 0℃ or T0 ≥ 40℃. In this case, the flying car can be determined to be prohibited from flying.

[0076] In some embodiments, step 243 includes: if the flight mode is an automatic flight mode, determining the first remaining flight time based on the first average battery current, the predicted battery state of charge, and the real-time state of charge, wherein the first average battery current is the average current of the flying vehicle in the previous operating condition; if the flight mode is a manual flight mode, determining the first remaining flight time based on the second average battery current, the predicted battery state of charge, and the real-time state of charge, wherein the second average battery current is the average current of the flying vehicle within a calibrated time.

[0077] One approach is to directly read the average battery current (i.e., the first average battery current) of the flying car during the previous operating condition (the entire flight process from start to finish) from the controller of the flying car, once the flight mode is determined to be automatic. This allows for the determination of the first remaining flight time based on the first average battery current, the predicted state of charge (SOC), and the real-time SOC. Alternatively, this can be achieved using the formula t1 = (SOC - SOC′) / I1, where I1 is the average battery current of the flying car during the previous operating condition.

[0078] One approach is to use the Hall effect sensors of the flying car to collect current data after determining the flight mode as manual. This data characterizes the pilot's operating condition. Since the battery's instantaneous current changes with the pilot's actions (abrupt changes to a larger instantaneous current with rougher actions and a smaller instantaneous current with gentler actions), the average current over a preset duration can be read from the flying car's flight history data as the average current of the flying car in the previous operating condition (i.e., the second battery average current). This allows for the determination of the first remaining flight time based on the second battery average current, the predicted state of charge (SOC), and the real-time SOC. Optionally, the formula t1 = (SOC - SOC′) / I2 can be used, where I2 is the average current of the flying car within the calibration time. Optionally, the preset duration is the calibration duration, which can be 2 minutes or other durations, and can be set as needed without specific limitations.

[0079] Please continue reading. Figure 3 Step 250: Obtain the historical power consumption of the flying car during flight, and determine the second remaining flight time of the flying car in the flight mode based on the historical power consumption.

[0080] In one approach, to ensure the accuracy of the target remaining flight time for the flying car, a first remaining flight time at maximum power can be determined, and a second remaining flight time can be determined based on the remaining battery power and the flying car's historical power consumption. This allows the target remaining flight time to be determined based on the first and second remaining flight times.

[0081] Optionally, the second remaining flight time is determined differently under different flight modes. Therefore, before determining the second remaining flight time, the flight mode of the flying car can be determined first, so as to determine the second remaining flight time of the flying car under the corresponding flight mode.

[0082] In some embodiments, such as Figure 6 As shown, step 250 includes:

[0083] Step 251: Obtain the historical power consumption of the flying car during flight.

[0084] One approach is to consider the historical power consumption of a flying car during flight as the average power consumption over its previous complete flight, i.e., the historical power consumption from takeoff to landing. Optionally, this historical power consumption can be the historical average power consumption. Alternatively, the historical power consumption during flight can be directly read from the flying car's electronic control unit.

[0085] Step 252: If the flight mode is automatic flight mode, then determine the second remaining flight time based on the historical power consumption and the remaining power of the flying car.

[0086] As one approach, after determining that the flying car's flight mode is autonomous flight mode, historical power consumption can be used as the power consumption for the current autonomous flight, thereby enabling the determination of the flying car's second remaining flight time in autonomous flight mode based on historical data.

[0087] Optionally, the remaining battery power of the flying car can be determined by obtaining its battery parameters. Alternatively, it can be determined using the formula t2 = SOE / E. Auto To determine the second remaining flight time of the flying car in automatic flight mode, where SOE is the remaining battery power of the flying car, and E... Auto This refers to the historical power consumption of the flying car.

[0088] Step 253: If the flight mode is manual flight mode, the second remaining flight time is determined based on the remaining battery power of the flying car, the average current of the second battery, the flight distance of the flying car, and the actual battery voltage of the flying car, wherein the average current of the second battery is the average current of the flying car within the calibrated time.

[0089] As one approach, after determining the flight mode to be manual flight mode, since the flying car is operated by the driver during flight, the historical power consumption of the flying car cannot be directly obtained in the automatic flight mode. Therefore, to determine the second remaining flight time of the flying car in manual flight mode, the power consumption of the flying car in manual flight mode can be determined first. This allows the second remaining flight time of the flying car in manual flight mode to be determined based on the power consumption of the flying car in manual flight mode and the remaining power of the flying car.

[0090] Optionally, the power consumption of the flying car in manual flight mode can be determined by first obtaining the actual battery voltage, flight distance, and average current of the second battery within the calibrated time period. Optionally, the flight distance refers to the distance already flown by the flying car. Optionally, the power consumption can be determined using the formula t2 = SOE / E. manu =SOE / U bat *I2*△t / L determines the second remaining flight time of the flying car in manual flight mode. Where E manu U represents the historical power consumption of the flying car in manual flight mode. bat I2 is the actual battery voltage, L is the average current of the second battery, Δt is the flight distance of the flying car, and Δt is the time the flying car has been flying or the calibration time.

[0091] Please continue reading. Figure 3 Step 260: Determine the target remaining flight time of the flying car based on the first remaining flight time and the second remaining flight time.

[0092] As a method, after determining the first remaining flight time and the second remaining flight time, in order to avoid the problem that the flying car cannot fly even though the remaining power is sufficient, which would be caused by directly determining the second remaining flight time as the target remaining flight time, and also to avoid the problem that the first remaining flight time and the second remaining flight time differ greatly due to the influencing factors of determining the first remaining flight time, the target remaining flight time of the flying car can be determined based on the first remaining flight time and the second remaining flight time.

[0093] As one approach, the second remaining flight time can be adjusted based on the first remaining flight time. Optionally, different flight time weights can be set for the first remaining flight time and the second remaining flight time, and then the target remaining flight time can be determined based on the first remaining flight time and the first flight time weight corresponding to the first remaining flight time, as well as the second remaining flight time and the second flight time weight corresponding to the second remaining flight time.

[0094] Optionally, the first remaining flight time can be used as the primary flight time. When the first remaining flight time is greater than the flight time threshold, the target remaining flight time can be determined based on the first remaining flight time and the first flight time weight corresponding to the first remaining flight time, the second remaining flight time and the second flight time weight corresponding to the second remaining flight time. If the first remaining flight time is less than or equal to the flight time threshold, the target remaining flight time of the flying car can be determined to be 0, which does not meet the flight conditions. At this time, an alarm message can be generated to prompt the driver that the flying car cannot fly at present.

[0095] Alternatively, one could first determine whether the first remaining flight time is greater than a flight time threshold, and then, if the first remaining flight time is greater than the flight time threshold, determine the relationship between the first remaining flight time and the second remaining flight time, and then determine the target remaining flight time based on this relationship.

[0096] In some embodiments, such as Figure 7 As shown, step 260 includes:

[0097] Step 261: Determine the relationship between the first remaining flight time and the second remaining flight time.

[0098] As a method, in order to avoid the discrepancy between the first or second remaining flight time (which is the target remaining flight time) and the actual state of the flying car due to inaccurate first or second remaining flight time, which could lead to flight safety accidents, the relationship between the first and second remaining flight times can be determined first.

[0099] Optionally, the relationship between the first remaining flight time and the second remaining flight time includes the first remaining flight time being greater than the second remaining flight time, the first remaining flight time being equal to the second remaining flight time, and the first remaining flight time being less than the second remaining flight time.

[0100] Step 262: If the size relationship indicates that the first remaining flight time is less than or equal to the second remaining flight time, then the first remaining flight time is determined as the target remaining flight time.

[0101] As one approach, since the first remaining flight time takes into account different operating conditions, the real-time state of charge of the battery, the health status of the battery, the real-time temperature of the battery, and the temperature, the first remaining flight time is more accurate than the second remaining flight time. Therefore, if the relationship between the first remaining flight time and the second remaining flight time is determined to be that the first remaining flight time is less than or equal to the second remaining flight time, then the first remaining flight time is determined as the target remaining flight time, thereby ensuring the accuracy of the target remaining flight time.

[0102] Step 263: If the size relationship indicates that the first remaining flight time is greater than the second remaining flight time, then the second remaining flight time is determined as the target remaining flight time.

[0103] As one approach, if the first remaining flight time is determined to be greater than the second remaining flight time, then to ensure the flight safety of the flying car, the smaller remaining flight time is set as the target remaining flight time, and thus the second remaining flight time is set as the target remaining flight time.

[0104] In this embodiment, by first determining the first remaining flight time of the flying car in flight mode and at maximum discharge power, and the second remaining flight time determined by the remaining battery power of the flying car in flight mode, the first remaining flight time and the second remaining flight time can be compared to determine the target remaining flight time. Since the first remaining flight time takes into account changes in different operating conditions, initial battery state, battery recovery state, battery temperature rise, and state of charge, it compensates for the problem of large remaining energy but vehicle inability to fly in traditional systems, thus improving the accuracy of determining the target remaining flight time.

[0105] Please see Figure 8 , Figure 8 This paper illustrates a flight time prediction method 8 for a flying car according to an embodiment of this application. The following will focus on... Figure 8 The process shown is described in detail. The first battery parameters include the current battery state of charge and the current battery current. The control method of the flying car may specifically include the following steps:

[0106] Step 310: When an instruction is received to instruct the flying car to take off, the battery parameters of the flying car are determined, wherein the battery parameters include first battery parameters and second battery parameters.

[0107] Step 320: Determine a reference state of charge based on the current state of charge and the current battery current.

[0108] One approach is to first obtain the current state of charge (SOC) of the flying car and the real-time current of the flying car's battery. Then, based on the current SOC and the real-time current, the SOC at the next moment can be estimated using the ampere-hour method, and the next suitable SOC can be determined as the reference SOC.

[0109] Step 330: Determine the battery voltage of the flying car, and determine the real-time state of charge based on the battery voltage and the reference state of charge.

[0110] One approach is to first determine the actual battery voltage in the flying car's battery parameters as the flying car's battery voltage, and then correct the real-time state of charge (SOC) based on this battery voltage. Alternatively, the formula SOC = SOC K+1 +K′*(UH*U0) is used to determine the real-time state of charge (SOC) of the flying car, where SOC is... K+1For the reference state of charge, which is the state of charge at the next moment estimated using the ampere-hour method based on the current state of charge and real-time current, K′ is the Kalman gain, U is the actual voltage of the flying car battery, and U0 is the cell voltage predicted by the battery RC model based on the real-time current, the state of charge at the next moment, and the cell temperature of the flying car battery.

[0111] Step 340: Determine the discharge coefficient corresponding to the maximum discharge power of the flying car, and determine the first temperature corresponding to the maximum discharge power of the flying car based on the first temperature determination algorithm, the discharge coefficient and the real-time state of charge.

[0112] One approach is to first determine the maximum and minimum discharge power of the flying car based on its current battery temperature and state of charge. Optionally, a mapping relationship between different temperatures, states of charge, and discharge power can be pre-set. Then, based on this mapping relationship, the corresponding discharge power at the current battery temperature and state of charge can be determined, and the permissible flight range of the flying car can be determined based on this discharge power. Figure 9 As shown, if the minimum discharge power of the flying car is 300 kW, then region A in the figure represents the permissible flight range for the flying car; areas outside this range are prohibited flight zones. Optionally, after determining the maximum discharge power of the flying car, the discharge coefficient can be obtained by fitting the discharge power.

[0113] As one approach, after determining the real-time state of charge (SOC) and maximum discharge power of the flying car, curve fitting can be performed based on the real-time SOC and maximum discharge coefficient to obtain a curve with SOC as the independent variable and temperature as the dependent variable, such as... Figure 10 As shown, the permissible flight range of the flying car under the preset discharge power (300kW) can be obtained.

[0114] As another approach, since the battery health of the flying car also affects its discharge power, a weighting factor for the discharge power can be determined based on the battery health. This weighting factor can then be used to adjust the discharge power accordingly. Figure 10 Adjust the curve shown to obtain the following: Figure 11 The curve shown is in Figure 11 In the diagram, region A represents the permissible flight range of the flying car when the battery health status is 100%, and region B represents the reduced permissible flight range of the flying car after weighted processing.

[0115] One approach is to determine the first temperature of the flying car at its minimum discharge power using the formula T1 = K1 * SOC′ + K2, where K1 is the first discharge coefficient, K2 is the second discharge coefficient, and SOC′ is the predicted state of charge. Alternatively, the third temperature can be determined using the formula T3 = K3 * SOC′ + K4, where K3 is the third discharge coefficient and K4 is the fourth discharge coefficient.

[0116] Step 350: Determine the predicted state of charge of the flying car based on the relationship between the first temperature and the second temperature.

[0117] Step 360: Determine the real-time state of charge of the flying car, and determine the target remaining flight time of the flying car based on the predicted state of charge and the real-time state of charge.

[0118] The specific steps of steps 310 and 350-360 can be found in steps 110 and 130-140, and will not be repeated here.

[0119] In some embodiments, the second battery parameters include cell mass, cell specific heat capacity, and cell self-heating. After step 310, the method further includes: obtaining the current ambient temperature of the environment where the flying car is located, and determining the cell temperature rise coefficient based on the current ambient temperature; determining the second temperature based on the second temperature determination algorithm and the cell temperature rise coefficient, the cell mass, the cell specific heat capacity, and the cell self-heating.

[0120] One approach is to use temperature sensors on the flying car to obtain the current ambient temperature of the environment in which the flying car is located. After determining the current ambient temperature, a pre-set mapping relationship between the ambient temperature and the corresponding temperature rise coefficient and correction coefficient can be used to determine the corresponding target temperature rise coefficient and target correction coefficient. Then, the cell temperature rise coefficient can be determined based on the target temperature rise coefficient and target correction coefficient. Optionally, the cell temperature rise coefficient can be the sum of the target temperature rise coefficient and the correction coefficient.

[0121] Optionally, before determining the second temperature, the cell mass, specific heat capacity, and self-released heat of the flying car can be determined from the battery parameters. This allows the second temperature to be determined based on the cell temperature rise coefficient, cell mass, specific heat capacity, and self-released heat. The self-released heat can be determined based on the heat generated by the cell's ohmic impedance, the heat generated by concentration polarization, the heat generated by diffusion polarization difference, the heat generated by self-discharge, the heat lost through convection between the cell and the external environment, and the heat lost through radiation. Optionally, it can be determined using the formula T2 = (Q / m / C + K). Thm)*(SOC-SOC′) / I avg +T0 determines the second temperature, where Q is the total self-heating of the battery cells, m is the cell mass of the flying car battery, C is the specific heat capacity of the cell, SOC is the current state of charge of the flying car, SOC′ is the predicted state of charge, and I avg Let T0 be the average current of the flying car under the previous operating condition, and K be the current temperature of the flying car battery. Thm This refers to the temperature rise coefficient of the battery cell in the flying car.

[0122] In this embodiment, the first temperature and the second temperature are determined by different parameters of the flying car and the first temperature determination algorithm and the second temperature determination algorithm, respectively. The first temperature involves the discharge coefficient corresponding to the maximum discharge power of the flying car, and the second temperature involves the current ambient temperature of the environment in which the flying car is located. This improves the accuracy of the first temperature and the second temperature, thereby improving the accuracy of the predicted state of charge and ensuring the accuracy of the determined target remaining flight time of the flying car.

[0123] Figure 12 This is a block diagram of a flight time prediction device for a flying car according to an embodiment of this application, such as... Figure 12 As shown, the flight time prediction device 400 of the flying car includes: a battery parameter determination module 410, a temperature determination module 420, a predicted state of charge determination module 430, and a target remaining flight time determination module 440.

[0124] A battery parameter determination module 410 is used to determine the battery parameters of the flying car when receiving an instruction to instruct the flying car to take off, wherein the battery parameters include first battery parameters and second battery parameters; a temperature determination module 420 is used to determine a first temperature corresponding to the maximum discharge power of the flying car based on a first temperature determination algorithm and the first battery parameters, and to determine a second temperature corresponding to the maximum discharge power of the flying car based on a second temperature determination algorithm and the second battery parameters; a predicted state of charge determination module 430 is used to determine the predicted state of charge of the flying car according to the relationship between the first temperature and the second temperature; and a target remaining flight time determination module 440 is used to determine the real-time state of charge of the flying car and to determine the target remaining flight time of the flying car according to the predicted state of charge and the real-time state of charge.

[0125] In some embodiments, the target remaining flight time determination module 440 includes: a first remaining flight time determination submodule, configured to determine the flight mode of the flying car and the real-time state of charge of the flying car, and determine a first remaining flight time of the flying car in the flight mode based on the predicted state of charge and the real-time state of charge; a second remaining flight time determination submodule, configured to acquire the historical power consumption of the flying car during flight, and determine a second remaining flight time of the flying car in the flight mode based on the historical power consumption; and a target remaining flight time determination submodule, configured to determine a target remaining flight time of the flying car based on the first remaining flight time and the second remaining flight time.

[0126] In some embodiments, the target remaining flight time determination submodule includes: a size relationship determination unit, configured to determine the size relationship between the first remaining flight time and the second remaining flight time; a target remaining flight time first determination unit, configured to determine the first remaining flight time as the target remaining flight time if the size relationship indicates that the first remaining flight time is less than or equal to the second remaining flight time; and a target remaining flight time second determination unit, configured to determine the second remaining flight time as the target remaining flight time if the size relationship indicates that the first remaining flight time is greater than the second remaining flight time.

[0127] In some embodiments, the first remaining flight time determination submodule includes: a first determination unit, configured to determine the battery health status of the flying vehicle, the real-time state of charge of the flying vehicle, and the current battery temperature of the flying vehicle; a second determination unit, configured to determine whether the flying vehicle meets the charge requirements based on the real-time state of charge and the battery health status, and to determine whether the flying vehicle meets the temperature requirements based on the current battery temperature and the first temperature or the second temperature; and a first remaining flight time determination unit, configured to determine the first remaining flight time based on the flight mode, the predicted state of charge, and the real-time state of charge when it is determined that the flying vehicle meets the charge requirements and the temperature requirements.

[0128] In some embodiments, the first remaining flight time determination unit includes: a first determination subunit, configured to determine the first remaining flight time based on a first battery average current, the predicted battery state of charge, and the real-time state of charge if the flight mode is an automatic flight mode, wherein the first battery average current is the average current of the flying vehicle in the previous operating condition; and a second determination subunit, configured to determine the first remaining flight time based on a second battery average current, the predicted battery state of charge, and the real-time state of charge if the flight mode is a manual flight mode, wherein the second battery average current is the average current of the flying vehicle within a calibrated time.

[0129] In some embodiments, the first determining unit includes: a third determining subunit, configured to determine the nominal battery capacity of the flying vehicle, the number of times the flying vehicle has been charged, the number of times the flying vehicle has been discharged, and the charging and discharging current of the flying vehicle; a battery available capacity determining subunit, configured to determine the battery available capacity of the flying vehicle based on the charging and discharging current; and a battery health status determining subunit, configured to determine the battery health status of the flying vehicle based on the nominal battery capacity, the number of times the vehicle has been charged, the number of times the vehicle has been discharged, and the battery available capacity.

[0130] In some embodiments, the second remaining flight time determination submodule includes: a historical power consumption acquisition unit, configured to acquire the historical power consumption of the flying car during flight; a third determination unit, configured to determine the second remaining flight time based on the historical power consumption and the remaining power of the flying car if the flight mode is automatic flight mode; and a fourth determination unit, configured to determine the second remaining flight time based on the remaining power of the flying car, the average current of the second battery, the flight distance of the flying car, and the actual battery voltage of the flying car if the flight mode is manual flight mode, wherein the average current of the second battery is the average current of the flying car within the calibration time.

[0131] In some embodiments, the first battery parameters include the current battery state of charge and the current battery current. The temperature determination module 420 includes: a reference state of charge determination submodule, configured to determine a reference state of charge based on the current state of charge and the current battery current; a real-time state of charge determination submodule, configured to determine the battery voltage of the flying vehicle and determine the real-time state of charge based on the battery voltage and the reference state of charge; and a first temperature determination submodule, configured to determine the discharge coefficient corresponding to the maximum discharge power of the flying vehicle and determine the first temperature corresponding to the maximum discharge power of the flying vehicle based on a first temperature determination algorithm, the discharge coefficient, and the real-time state of charge.

[0132] In some embodiments, the second battery parameters include cell mass, cell specific heat capacity, and cell self-heating. The temperature determination module 420 further includes: a cell temperature rise coefficient determination submodule, used to obtain the current ambient temperature of the environment where the flying car is located, and determine the cell temperature rise coefficient based on the current ambient temperature; and a second temperature determination submodule, used to determine the second temperature based on the second temperature determination algorithm and the cell temperature rise coefficient, the cell mass, the cell specific heat capacity, and the cell self-heating.

[0133] According to one aspect of the embodiments of this application, an electronic device is also provided, such as... Figure 12As shown, the vehicle 500 includes a processor 510 and one or more memories 520. The one or more memories 520 are used to store program instructions executed by the processor 510. When the processor 510 executes the program instructions, it implements the flight time prediction method of the flying car described above.

[0134] Furthermore, the processor 510 may include one or more processing cores. The processor 510 runs or executes instructions, programs, code sets, or instruction sets stored in the memory 520, and retrieves data stored in the memory 520. Optionally, the processor 510 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 510 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor and may be implemented using a separate communication chip.

[0135] According to one aspect of this application, a computer-readable storage medium is also provided, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable storage medium carries computer-readable instructions that, when executed by a processor, implement the methods in any of the above embodiments.

[0136] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0137] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0138] 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 application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains 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, can 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.

[0139] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments 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.

[0140] 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 for predicting flight time for a flying car, characterized in that, The method includes: When an instruction is received to instruct the flying car to take off, the battery parameters of the flying car are determined. The battery parameters include first battery parameters and second battery parameters. The first battery parameters include the current state of charge and the current current. The second battery parameters include the cell mass, the cell specific heat capacity, and the cell self-heating. The first temperature corresponding to the maximum discharge power of the flying car is determined based on the first temperature determination algorithm, the discharge coefficient corresponding to the maximum discharge power of the flying car, and the first battery parameters. The second temperature is determined based on the second temperature determination algorithm, the current ambient temperature of the environment where the flying car is located, and the second battery parameters, at the maximum discharge power of the flying car. Based on the relationship between the first temperature and the second temperature, the predicted state of charge of the flying car is determined; The real-time state of charge of the flying car is determined, and the target remaining flight time of the flying car is determined based on the predicted state of charge and the real-time state of charge.

2. The method according to claim 1, characterized in that, The step of determining the real-time state of charge of the flying car and determining the target remaining flight time of the flying car based on the predicted state of charge and the real-time state of charge includes: The flight mode and real-time state of charge of the flying car are determined, and the first remaining flight time of the flying car in the flight mode is determined based on the predicted state of charge and the real-time state of charge. The historical power consumption of the flying car during flight is obtained, and the second remaining flight time of the flying car in the flight mode is determined based on the historical power consumption. The target remaining flight time of the flying car is determined based on the first remaining flight time and the second remaining flight time.

3. The method according to claim 2, characterized in that, Determining the target remaining flight time of the flying car based on the first remaining flight time and the second remaining flight time includes: Determine the relationship between the first remaining flight time and the second remaining flight time; If the size relationship indicates that the first remaining flight time is less than or equal to the second remaining flight time, then the first remaining flight time is determined as the target remaining flight time; If the size relationship indicates that the first remaining flight time is greater than the second remaining flight time, then the second remaining flight time is determined as the target remaining flight time.

4. The method according to claim 2, characterized in that, Determining the first remaining flight time of the flying car in the flight mode based on the predicted state of charge and the real-time state of charge includes: Determine the battery health status, real-time state of charge, and current battery temperature of the flying car; The flying car is determined to meet the charge requirements based on the real-time state of charge and the battery health status, and the flying car is determined to meet the temperature requirements based on the current battery temperature and the first temperature or the second temperature. When it is determined that the flying car meets the charge requirement and the temperature requirement, the first remaining flight time is determined based on the flight mode, the predicted state of charge, and the real-time state of charge.

5. The method according to claim 4, characterized in that, Determining the first remaining flight time based on the flight mode, the predicted state of charge, and the real-time state of charge includes: If the flight mode is automatic flight mode, the first remaining flight time is determined based on the first battery average current, the predicted battery state of charge and the real-time state of charge, wherein the first battery average current is the average current of the flying car in the previous operating condition. If the flight mode is manual flight mode, the first remaining flight time is determined based on the second battery average current, the predicted battery state of charge, and the real-time state of charge, wherein the second battery average current is the average current of the flying car within the calibrated time.

6. The method according to claim 4, characterized in that, Determining the battery health status of the flying car includes: Determine the nominal battery capacity of the flying car, the number of times the flying car is charged, the number of times the flying car is discharged, and the charging and discharging current of the flying car; The available battery capacity of the flying car is determined based on the charging and discharging current. The battery health status of the flying car is determined based on the battery's nominal capacity, the number of charging cycles, the number of discharging cycles, and the battery's available capacity.

7. The method according to claim 2, characterized in that, The step of acquiring the historical power consumption of the flying car during flight and determining the second remaining flight time of the flying car in the flight mode based on the historical power consumption includes: Obtain the historical power consumption of the flying car during flight; If the flight mode is automatic flight mode, then the second remaining flight time is determined based on the historical power consumption and the remaining power of the flying car; If the flight mode is manual flight mode, the second remaining flight time is determined based on the remaining battery power of the flying car, the average current of the second battery, the flight distance of the flying car, and the actual battery voltage of the flying car, wherein the average current of the second battery is the average current of the flying car within the calibrated time.

8. The method according to claim 1, characterized in that, The determination of the first temperature corresponding to the maximum discharge power of the flying car based on the first temperature determination algorithm, the discharge coefficient corresponding to the maximum discharge power of the flying car, and the first battery parameters includes: A reference state of charge is determined based on the current battery state of charge and the current battery current; Determine the battery voltage of the flying car, and determine the real-time state of charge based on the battery voltage and the reference state of charge; The discharge coefficient corresponding to the maximum discharge power of the flying car is determined, and the first temperature corresponding to the maximum discharge power of the flying car is determined based on the first temperature determination algorithm, the discharge coefficient and the real-time state of charge.

9. The method according to claim 1, characterized in that, The determination of the second temperature corresponding to the maximum discharge power of the flying car based on the second temperature determination algorithm, the current ambient temperature of the environment where the flying car is located, and the second battery parameters includes: The current ambient temperature of the environment where the flying car is located is obtained, and the cell temperature rise coefficient is determined based on the current ambient temperature. The second temperature is determined based on the second temperature determination algorithm, the cell temperature rise coefficient, the cell mass, the cell specific heat capacity, and the cell self-released heat.

10. A flight time prediction device for a flying car, characterized in that, The device includes: A battery parameter determination module is used to determine the battery parameters of the flying car when it receives an instruction to take off. The battery parameters include a first battery parameter and a second battery parameter. The first battery parameter includes the current state of charge and the current current. The second battery parameter includes the cell mass, the cell specific heat capacity, and the cell self-heating. A temperature determination module is used to determine a first temperature corresponding to the maximum discharge power of the flying car based on a first temperature determination algorithm, a discharge coefficient corresponding to the maximum discharge power of the flying car, and the first battery parameters; and to determine a second temperature corresponding to the maximum discharge power of the flying car based on a second temperature determination algorithm, the current ambient temperature of the environment where the flying car is located, and the second battery parameters. A predicted state of charge determination module is used to determine the predicted state of charge of the flying car based on the relationship between the first temperature and the second temperature. The target remaining flight time determination module is used to determine the real-time state of charge of the flying car, and determine the target remaining flight time of the flying car based on the predicted state of charge and the real-time state of charge.

11. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1 to 9.

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