An energy management method for a ground unmanned mobile platform

Abstract

The present application relates to a kind of ground unmanned mobile platform energy management method, belong to hybrid system energy management technical field, the present application includes remote control terminal, unmanned domain controller, whole vehicle controller, motor controller, power battery management unit and engine-generator set controller;The remote control terminal is interacted with operation hand, and the instruction is issued to the whole vehicle controller;The unmanned domain controller reports current unmanned mobile platform chassis position information, by the remote control terminal, path planning is carried out, and navigation path information and task information are sent to the whole vehicle controller;The whole vehicle controller is according to navigation path information and task information, coordinates power battery management unit, engine-generator set controller and motor controller to carry out energy control, the problem that existing energy management control system cannot well guarantee the task execution condition of unmanned mobile platform and the working efficiency of power system is solved.

Description

Technical Field

[0001] This invention relates to the field of energy management technology for hybrid systems, and more particularly to an energy management method for a ground-based unmanned aerial vehicle (UAV) platform. Background Technology

[0002] A ground-based unmanned mobile platform is a type of autonomous ground-based unmanned vehicle capable of carrying various types of superstructures and autonomously performing multiple tasks. It can be widely used in various scenarios such as logistics support, reconnaissance and surveillance, combat readiness transport, and collaborative operations. The power drive system of a ground-based unmanned mobile platform is a core component, directly affecting the platform's mission performance. Because hybrid electric drive systems not only allow for pure electric driving, meeting requirements such as low noise and low infrared signature, but also ensure sufficient range, while simultaneously powering the superstructure to achieve integrated power supply, it is currently the mainstream solution for various types of ground-based unmanned mobile platforms.

[0003] How to efficiently allocate the output power of the internal combustion engine and the power battery is an important research topic in hybrid system energy management. Since ground-based unmanned aerial vehicle platforms may perform different tasks in different regions, traditional rule-based and optimization-based energy management systems and control methods cannot adapt to complex and ever-changing application scenarios and tasks. They cannot efficiently allocate energy according to region and task, or meet the power requirements of the superstructure. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide an energy management method for ground-based unmanned aerial vehicle (UAV) power platforms, in order to solve the problem that existing rule-based and optimization-based energy management control systems cannot effectively allocate the power output of the internal combustion engine and the power battery to ensure the mission execution and power system efficiency of the UAV power platform.

[0005] On one hand, the present invention provides an energy management method for a ground-based unmanned aerial vehicle (UAV) platform, including a remote control terminal, an unmanned driving domain controller, a vehicle controller, a motor controller, a power battery management unit, and an engine-generator set controller;

[0006] The remote control terminal interacts with the operator and issues commands to the vehicle controller.

[0007] The unmanned driving domain controller reports the current position information of the unmanned vehicle platform chassis, and the remote control terminal performs path planning, obtains navigation path information and task information, and sends them to the vehicle controller.

[0008] The vehicle controller coordinates the power battery management unit, engine-generator controller, and motor controller to perform energy control based on navigation path information and task information.

[0009] Furthermore, after the remote control terminal issues the task command, it performs path planning and obtains path information, including the total driving path mileage, the altitude information of the path segment, and the uphill and downhill mileage information of the path segment.

[0010] Furthermore, the mission instructions include destination instructions and mission instructions, and both the remote control terminal and the unmanned domain controller are equipped with high-precision satellite maps.

[0011] On the other hand, the present invention provides an energy management method for a ground-based unmanned aerial vehicle (UAV) platform, employing the aforementioned energy management system for the ground-based UAV platform, comprising the following steps:

[0012] Step S1: Obtain the remaining battery power (SOC) of the first target. final_tar ;

[0013] Step S2: Obtain the total mileage D of the planned route. total The final SOC-corrected mileage D cor Second target remaining power SOC K_tar ;

[0014] Step S3: Feature road segment identification;

[0015] Step S4: Obtain the target SOC at the start and end points of the feature road segment;

[0016] Step S5: Correct and charge the power generation.

[0017] Furthermore, the specific steps of step S2 include:

[0018] Step S2.1: The remote control terminal can perform route planning based on high-precision satellite maps and obtain the total mileage D of the planned route. total ;

[0019] Step S2.2: At the optimal vehicle speed V corresponding to the power consumption per 100 kilometers d Driving through the final SOC-corrected mileage D cor The mileage length is based on the total mileage D. total Sure;

[0020] Step S2.3: Obtain the target SOC at point K after the first d kilometers of total driving distance as the second target remaining battery SOC. K_tar .

[0021] Furthermore, in step S2,

[0022]

[0023] P batchg =MIN(P Gen_min -P Req,P Chg_min ),

[0024] Among them, P Gen_min P is the minimum generating power of the engine-generator set controller. Req For the power required by the whole vehicle, P Chg_min T is the minimum charging power for the battery. d To determine the time required to traverse the final d kilometers, W total This refers to the battery level at 100% SOC.

[0025] Furthermore, step S3 specifically includes the following steps:

[0026] Step S3.1: Transfer mileage D total -d is divided into several unit segments every S kilometers, and the elevation information of the start and end points of each unit segment is obtained;

[0027] Step S3.2: Calculate the elevation difference of each unit road segment to determine the type of unit road segment;

[0028] Step S3.3: Based on the change in elevation difference of each unit road segment, starting from the starting point of the path, identify the entire path as a combination of feature segments according to the positive and negative characteristics of the elevation difference of the unit road segments.

[0029] Furthermore, step S4 specifically includes the following steps:

[0030] Step S4.1: Obtain the target SOC at the end of the uphill section. uphill_end and the target SOC at the starting point of the downhill section downhill_begin ;

[0031] SOC downhill_begin =SOC min_Lim SOC uphill_end =SOC min_Lim ;

[0032] Among them, SOC min_Lim This is the lower limit of the battery's SOC;

[0033] Step S4.2: Obtain the target SOC at the end of the downhill road downhill_end and the starting point of the uphill road, the target SOC uphill_begin ;

[0034] Step S4.3: Set the target SOC for other characteristic road segments.

[0035] Furthermore, in step S4.2,

[0036] SOC downhill_end =SOC downhill_begin +ΔSOC,

[0037]

[0038] Among them, Trq mtr_gen It is the maximum recovery torque of the motor, n mtr It is the motor speed, L hilldown It is the mileage of the downhill section, V hilldown It is the speed of vehicles passing through the downhill section, and K is a correction factor with a value range of 1 to 1.2.

[0039] Furthermore, in step S4.2, the power demand of the entire vehicle during the uphill process is entirely borne by the power battery, and the estimated ΔSOC required to complete the uphill climb in pure electric mode is calculated. uphill :

[0040] ΔSOC uphill =P Req ×T uphill / W total ,but:

[0041] SOC uphill_begin =(SOC) uphill_end +ΔSOC uphill )×K,

[0042] Among them, P Req For the power required by the whole vehicle, T uphill The uphill passage time is denoted by K, which is a correction factor ranging from 1 to 1.2.

[0043] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0044] (1) Based on high-precision map navigation path information and the type of task to be performed, the present invention can adaptively allocate the power output of the power battery and the internal combustion engine, which can improve the working efficiency and fuel economy of the power system, and ensure the energy reserves required for task execution.

[0045] (2) Since the battery has limited recoverable capacity when it is at high SOC, mechanical braking or engine reverse braking is usually used when going downhill. Therefore, the downhill terrain cannot be fully utilized to charge the battery. In order to ensure that the UAV power platform chassis can recover energy as much as possible when going downhill, this invention utilizes the battery SOC to a low point before going downhill, so as to recover energy by utilizing the downhill terrain and improve the economy of the power system.

[0046] (3) The vehicle controller of the present invention will perform energy management control on the entire path according to the above path information and target SOC, so as to ensure that the SOC of the UAV platform when performing the task at the destination is greater than or equal to the target SOC, so as to ensure the task execution, and perform adaptive energy allocation in combination with path information during driving to improve the fuel economy and working efficiency of the system.

[0047] (4) The ground unmanned aerial vehicle platform of the present invention adaptively manages energy according to the region and the task being performed, ensuring the task execution of the unmanned aerial vehicle platform and the working efficiency of the power system, thereby improving the working efficiency and fuel economy of the power system.

[0048] (5) This invention divides the navigation path into several characteristic road segments and sets the target SOC at the start and end of each characteristic road segment. The projected SOC is obtained based on the power generation and transit time. By comparing the target SOC and projected SOC of each road segment, the transit time and recovered power of each road segment are functionally corrected, and the SOC at point K is set. K_tar To ensure that the final d kilometers of mileage can be adjusted to ensure that the power generation reaches the SOC (State of Charge). final_tar .

[0049] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0050] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0051] Figure 1 This is a schematic diagram of the energy management process of a ground-based unmanned aerial vehicle (UAV) platform according to a specific embodiment. Detailed Implementation

[0052] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0053] Example 1

[0054] One specific embodiment of the present invention discloses a management system for a ground-based unmanned aerial vehicle (UAV) platform, including a remote control terminal, an unmanned driving domain controller, a vehicle controller, a motor controller, a power battery unit, and an engine-generator set controller.

[0055] Both the remote control terminal and the unmanned driving domain controller are equipped with high-precision satellite maps. The remote control terminal interacts with the operator and issues commands to the vehicle controller. The unmanned driving domain controller reports the current chassis position information (based on satellite positioning information). The remote control terminal performs path planning, obtains the geographical information (i.e., navigation path information) and task information along the path, and sends them to the vehicle controller.

[0056] The instructions include destination instructions and task instructions.

[0057] The vehicle controller coordinates the power battery unit, engine-generator set controller, and motor controller to perform energy control based on navigation path information and task information.

[0058] After the remote control terminal issues a task command, it can perform route planning and obtain route information, including the total driving route mileage, altitude information on the route segment, and uphill and downhill mileage on the route segment. In addition, if a task is selected, the power consumption required to execute the target task can be set, and the final target SOC (battery charge) can be calculated.

[0059] In this embodiment, the vehicle controller will perform energy management control along the entire path based on the aforementioned path information and target SOC, ensuring that the SOC of the UAV platform when performing the task at the destination is greater than or equal to the target SOC, so as to guarantee task execution. During the journey, the controller will also perform adaptive energy allocation based on the path information to improve the system's fuel economy and work efficiency.

[0060] Example 2

[0061] Another specific embodiment of the present invention, such as Figure 1 As shown, an energy management method for a ground-based unmanned aerial vehicle (UAV) platform is disclosed, implemented using the energy management system for the ground-based UAV platform described in Example 1. The steps include:

[0062] Step S1: Obtain the remaining battery power (SOC) of the first target. final_tar .

[0063] After the remote control terminal issues a task command, it can calculate the power consumption (W) required for task execution based on the issued task command. task .

[0064] W task =P task ×T task (1)

[0065] P task T represents the average power consumption for performing the task. task The time required to execute the task.

[0066] It should be noted that in this embodiment, the unit of battery remaining charge SOC is %, the unit of power P is kWh, the unit of energy W is kW, the unit of time T is h, the unit of mileage D, d, s, L is km, the unit of speed V is km / h, the unit of motor torque Trq is Nm, and the unit of rotational speed n is rpm.

[0067] By combining the lower limit of the SOC of the power battery and the power consumption of the task, the target SOC is calculated and used as the first target SOC, i.e., SOC. final_tar .

[0068] SOC final_tar =SOC low_Lim +W Task / W Total (2)

[0069] SOC low_Lim It is the lower limit of the SOC of the power battery, determined by the characteristics of the power battery; W Total It is the total capacity of the power battery.

[0070] Step S2: Obtain the total mileage D of the planned route. total The final SOC-corrected mileage D cor Second target remaining power SOC K_tar .

[0071] Step S2 includes the following steps:

[0072] Step S2.1: The remote control terminal can perform route planning based on high-precision satellite maps and obtain the total mileage D of the planned route. total .

[0073] Step S2.2: Final SOC Corrected Road Mileage D cor Based on the optimal vehicle speed V corresponding to the energy consumption per 100 kilometers d (Measured through testing) The distance traveled is d, which is based on the total mileage D. total Sure.

[0074] d = k d ×D total (3)

[0075] Where, k d This is the proportionality coefficient.

[0076] Step 2.3: Obtain the target SOC at point K within the first d kilometers of the total driving distance as the second target SOC, i.e., SOC K_tar .

[0077]

[0078] Among them, Pbatchg The minimum power output (P) of the engine-generator set controller Gen_min - Vehicle power requirement (P) Req ) and minimum battery charging power (P) Chg_min The minimum value of ), that is

[0079] P batchg =MIN(P Gen_min -P Req ,P Chg_min (5)

[0080] Vehicle power requirement P Req Including drive power P Mtr and high voltage accessory power P Hv The driving power is used to overcome the drag of the UAV's moving platform, since the vehicle speed is V at this time. d The driving power is V d The corresponding drive power (obtainable from the driving resistance curve) and the high-voltage accessory power can be the calibrated value.

[0081] P Req =P Mtr +P Hv (6)

[0082] T d The time required to pass the last d kilometers.

[0083] T d =d / V d (7)

[0084] In this embodiment, the target SOC at point K within the first d kilometers of the total driving distance is obtained as the second target SOC, i.e., SOC. K_tar This is to ensure that in the last d kilometers of the total driving distance, the engine-generator set can charge the power battery with minimal power generation capacity, and also ensure that the State of Charge (SOC) is greater than or equal to the State of Charge (SOC) when reaching the end of the journey. final_tar .

[0085] Step S3: Feature segment identification.

[0086] Step S3 specifically includes the following steps:

[0087] Step S3.1: Transfer mileage D total -d divides each S-kilometer segment into several unit segments and obtains the elevation information of the start and end points of each unit segment.

[0088] The S parameter is set based on the total mileage D. totalIf the last unit segment is less than S kilometers, the remaining mileage will be assigned to the final SOC correction mileage. This determination method is performed by a program stored on the remote control terminal. The principle of determination is to ensure the accuracy of the unit segment division without consuming too many computing resources.

[0089] Step S3.2: Calculate the elevation difference of each unit road segment to determine the type of unit road segment.

[0090] Based on the elevation information of the starting and ending points of each unit road segment obtained in step 3.1, the elevation difference of each road segment is obtained by subtracting the elevation of the starting point from the elevation of the ending point [[h1,h2,.....h]. n If h n A positive value indicates an uphill slope, 0 indicates a flat road, and a negative value indicates a downhill slope. This determines whether the road segment is flat, uphill, or downhill.

[0091] Step S3.3: Based on the change in elevation difference of each unit road segment, starting from the starting point of the route, identify the entire route into feature segment combinations according to the positive and negative characteristics of the elevation difference of the unit road segments. Those with consistent positive and negative characteristics are planned as the same feature road segment, and those with changing positive and negative characteristics are planned as another feature road segment. This planning includes flat road segments, uphill sections, and downhill sections. If the continuous elevation difference is positive, the road segment is an uphill road segment. The end point of the last road segment with a positive elevation difference is the end point of the uphill road segment. The mileage of each feature segment is known, and the slope can be calculated based on the elevation of the starting unit road segment and the elevation of the ending unit road segment.

[0092] In this embodiment, the identification of different characteristic road sections aims to maximize the use of the power battery output power on uphill sections, thereby reducing the battery's SOC. This allows for the reservation of more capacity for energy recovery on downhill sections, making full use of the downhill terrain to charge the battery, reducing the power generation of the engine-generator, and improving the system's economy.

[0093] Step S4: Obtain the target SOC of the start and end points of the feature road segment.

[0094] Step S4.1: Obtain the target SOC at the end of the uphill section. uphill_end and the target SOC at the starting point of the downhill section downhill_begin .

[0095] To ensure full utilization of battery output power during uphill driving and to fully utilize terrain-based energy recovery during downhill driving, the target SOC at the end of the uphill route will be achieved. uphill_end and downhill starting point target SOC downhill_begin All are set to the lower limit of the battery's SOC.

[0096] SOC downhill_begin =SOCmin_Lim (8)

[0097] SOC uphill_end =SOC min_Lim (9)

[0098] Step S4.2: Obtain the target SOC at the end of the downhill road downhill_end and the starting point of the uphill road, the target SOC uphill_begin .

[0099] To ensure that the engine-generator set is used to charge the battery as little as possible on downhill sections, and that only regenerative braking charges the battery, the target SOC at the end of the downhill section is set based on this rule. downhill_end .

[0100] SOC downhill_end =SOC downhill_begin +ΔSOC (10)

[0101] ΔSOC is obtained based on the mileage of the downhill section and the maximum recovery torque of the motor.

[0102]

[0103] Among them, Trq mtr_gen It is the maximum recovery torque of the motor, n mtr It is the motor speed, L hilldown It is the mileage of that downhill section, V hilldown This refers to the speed of vehicles passing through downhill sections. K is a correction factor, mainly used to meet the power consumption of accessories, and is usually set to 1 to 1.2.

[0104] To ensure that the power output of the battery is used as much as possible during uphill driving, the entire power demand of the vehicle during uphill driving is borne by the battery. The estimated ΔSOC required to complete the uphill driving in pure electric mode is calculated. uphill .

[0105] ΔSOC uphill =P Req ×T uphill / W total (12)

[0106] but:

[0107] SOC uphill_begin =(SOC) uphill_end +ΔSOC uphill )×K (13)

[0108] Among them, P Req The required power for the entire vehicle can be obtained from the uphill speed and the gradient; T uphillThe uphill passage time is denoted by K; K is a correction factor, mainly used to meet the power consumption of accessories, and is usually set to 1 to 1.2.

[0109] Step S4.3: Set the target SOC for other characteristic road segments.

[0110] After setting the target SOC at the start and end points of uphill and downhill road sections, set the target SOC for other characteristic road sections.

[0111] If the preceding characteristic road segment of the downhill section is a flat road segment, then the target SOC at the starting point of the flat road segment is set as the target SOC at the starting point of the downhill section plus a function correction value based on the flat road passage time and the flat road power demand, which is used as the target SOC.

[0112] SOC lvr_begin =SOC downhill_begin +ΔSOC lvr (14)

[0113] ΔSOC lvr =P Req ×T lvr / W total (15)

[0114] Among them, P Req The required power for the entire vehicle on a flat road (vehicle speed is fixed, and can be obtained from the driving resistance curve); T lvr This refers to the time taken to travel on flat ground.

[0115] If the preceding characteristic road segment of the uphill section is a flat road segment, then the target SOC of the flat road starting point is set as the target SOC of the uphill road starting point plus a function correction value based on the flat road passage time and the flat road demand power, which is used as the target SOC.

[0116] SOC lvr_begin =SOC uphill_begin +ΔSOC lvr (16)

[0117] ΔSOC lvr =P Req ×T lvr / W total (17)

[0118] Among them, P Req The required power for the entire vehicle on a flat road (vehicle speed is fixed, and can be obtained from the driving resistance curve); T lvr This refers to the time taken to travel on flat ground.

[0119] If the starting or ending point of the aforementioned characteristic road segment coincides with the starting or ending point of another characteristic road segment, then the target SOC of the changed point is the larger of the two values, such as the starting point of an uphill road being the ending point of the previous downhill road.

[0120] This yields the target SOC trajectory at the starting and ending points of several characteristic road segments along the entire path.

[0121] Step S5: Correct and charge the power generation.

[0122] Based on the target SOC at the end of the aforementioned road segment and the projected SOC at the expected end of the road segment, the control mode of the engine-generator set is adaptively selected from the following three modes:

[0123] Control mode 1: When the target SOC is equal to or the difference is less than the calibrated value, the power generation of the engine-generator set is not corrected, and it operates according to the current working condition.

[0124] Control method 2: When the expected SOC is less than the target SOC calibration value, the current power generation of the engine-generator set is corrected and the power generation is increased. This power generation can generate electricity at a constant power, part of which is used for the power demand of the whole vehicle and part of which is used for battery charging.

[0125] Control method 3: When the expected SOC is greater than the target SOC calibration value, the engine-generator set will stop and will not output power to the outside, and the power output will be entirely from the battery.

[0126] Step S5 specifically includes the following steps:

[0127] Step S5.1: Obtain the actual SOC of the starting point of each characteristic road segment of the ground-based UAV mobile platform and the target SOC of the ending point of the road segment obtained in the above steps.

[0128] Step S5.2: Obtain the actual SOC at the starting point and the target SOC at the end point of each characteristic road segment by the ground-based UAV platform. Based on the SOC difference ΔSOC and the arrival time T1, derive the reference power generation P for that segment. GEN :

[0129]

[0130] Step S5.3: Based on the mileage and estimated travel time of the road segment, and based on the vehicle power demand, power generation capacity and actual SOC of the road segment, obtain the estimated SOC of the end point of the road segment.

[0131] Step S5.4: Obtain the difference between the expected SOC and the target SOC, and adaptively select control mode 1, 2 or 3 of the engine-engine group for this road segment to correct the power generation; at the same time, the above SOC difference can be obtained again when 50% of the time is left in the current characteristic road segment (this value can be calibrated) to perform a second power correction.

[0132] Step S5.5: When the ground-based unmanned aerial vehicle (UAV) platform reaches the end of the characteristic road segment, compare the difference between the current actual SOC and the target SOC with the target SOC at the end of the next characteristic road segment. Add this difference to the correction for the power generation of the next characteristic road segment (meaning if the correction is not made in the current segment, it will be made in the next segment). The predicted SOC at the end of the segment can be calculated by combining the corrected power generation with the transit time of the characteristic road segment. The above correction judgment is performed for each segment.

[0133] Optionally, the remaining passage time and current SOC of each feature road segment can be obtained in real time, and the speed of the road segment can be corrected to adjust the charging time and charging amount of the road segment, so as to approach the target SOC at the end of each road segment.

[0134] Step S5.6: Before entering the final correction section, point K is the starting point of the final SOC correction section. When the motorized platform reaches this point, it obtains the current SOC. K and the time T to reach the destination d According to SOC final_tar -SOC K The difference is used to calculate the estimated power generation W. final .

[0135] According to W final and T d Calculate the expected power generation P of this road section. final :

[0136]

[0137] Compare P final With the maximum power generation of the APU P APU_MAX :

[0138] If P GEN >P final Then according to P APU_MAX The generator power is used for charging;

[0139] If 0 < P final <P APU_MAX If the power generation capacity is sufficient, the power generation capacity of that section of road will be charged accordingly; at the same time, the power generation capacity will be adjusted based on the real-time ΔSOC and the remaining passage time t to ensure the power generation capacity.

[0140] If P final If the value is less than 0, then the current section does not need to generate electricity, and the APU will shut down.

[0141] If the SOC is reached ahead of schedule during the final correction phase... final_tar If the engine-generator set does not stop, the power output of the engine-generator will follow the power demand of the vehicle, thus maintaining the battery's SOC. final_tar Continue unchanged until the end of the total mileage.

[0142] Compared with the prior art, the technical solution provided in this embodiment can achieve at least one of the following beneficial effects:

[0143] (1) In this embodiment, the power output of the power battery and the internal combustion engine can be adaptively allocated based on the high-precision map navigation path information and the type of task to be performed, which can improve the working efficiency and fuel economy of the power system, and ensure the energy reserves required for task execution.

[0144] (2) The vehicle controller in this embodiment will perform energy management control on the entire path according to the above path information and target SOC, so as to ensure that the SOC of the UAV platform when it arrives at the destination to perform the task is greater than or equal to the target, so as to ensure the task execution. During the driving process, it will combine the path information to perform adaptive energy allocation, thereby improving the fuel economy and working efficiency of the system.

[0145] (3) The ground unmanned aerial vehicle platform in this embodiment adaptively manages energy according to the region and the task being performed, which ensures the task execution of the unmanned aerial vehicle platform and the working efficiency of the power system, and improves the working efficiency and fuel economy of the power system.

[0146] (4) In this embodiment, the navigation path is divided into several characteristic road segments, and the target SOC of the starting and ending points of the characteristic road segments is set. The expected SOC is obtained based on the power generation and the passage time. By comparing the target SOC and the expected SOC of each road segment, the passage time and power recovery of each road segment are corrected by a function, and the SOC of point K is set. K_tar To ensure that the final d kilometers of mileage can be adjusted to ensure that the power generation reaches the SOC (State of Charge). final_tar .

[0147] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An energy management method for a ground-based unmanned aerial vehicle (UAV) platform, characterized in that, The energy management system using a ground-based unmanned aerial vehicle (UAV) platform includes the following steps: Step S1: Obtain the remaining battery power of the first target ; Step S2: Obtain the total mileage of the planned route The final Corrected road mileage D cor The second target remaining power The specific steps of step S2 include: Step S2.1: The remote control terminal plans the route based on the high-precision satellite map and obtains the total mileage of the planned route. ; Step S2.2: At the speed corresponding to the optimal power consumption per 100 kilometers Driving through the final Corrected road mileage D cor The mileage length is based on the total driving distance. Sure; Step S2.3: Before obtaining the total mileage kilometer K Point Target The remaining power as the second target ; , = , in, This is the minimum power output of the engine-generator set controller. For the power required by the whole vehicle, Minimum charging power for the battery. To pass the final Time required to travel 1,000 kilometers for Battery level at 100%; Step S3: Feature road segment identification; Step S4: Obtain the target of the start and end points of the feature road segment ; Step S5: Correct and charge the power generation.

2. The energy management method for a ground-based unmanned aerial vehicle (UAV) platform according to claim 1, characterized in that, Step S3 specifically includes the following steps: Step S3.1: Transfer mileage Before each The kilometer is divided into several unit segments, and the elevation information of the start and end points of each unit segment is obtained; Step S3.2: Calculate the elevation difference of each unit road segment to determine the type of unit road segment; Step S3.3: Based on the change in elevation difference of each unit road segment, starting from the starting point of the path, identify the entire path as a combination of feature segments according to the positive and negative characteristics of the elevation difference of the unit road segments.

3. The energy management method for a ground-based unmanned aerial vehicle (UAV) platform according to claim 1, characterized in that, Step S4 specifically includes the following steps: Step S4.1: Obtain the target at the end of the uphill section. and the starting point of the downhill section ; ， ； in, SOC min_Lim For batteries The lower limit; Step S4.2: Obtain the destination of the downhill road and the starting point of the uphill road ; Step S4.3: Set targets for other characteristic road segments .

4. The energy management method for a ground-based unmanned aerial vehicle (UAV) platform according to claim 3, characterized in that, In step S4.2, ， ， in, It is the maximum recovery torque of the motor. It is the motor speed. It is the mileage of the downhill section. This refers to the speed of vehicles traveling downhill. It is a correction factor, with a value range of 1 to 1.

2.

5. The energy management method for a ground-based unmanned aerial vehicle (UAV) platform according to claim 3, characterized in that, In step S4.2, the power demand of the entire vehicle during the uphill process is entirely borne by the power battery. The estimated power required to complete the uphill climb in pure electric mode is... : ,but: ， in, For the power required by the whole vehicle, For the time taken to pass through the uphill section, It is a correction factor, with a value range of 1 to 1.

2.

6. An energy management system for a ground-based unmanned aerial vehicle (UAV) platform, characterized in that, The energy management method for the ground unmanned aerial vehicle platform according to any one of claims 1-5 includes a remote control terminal, an unmanned driving domain controller, a vehicle controller, a motor controller, a power battery management unit, and an engine-generator set controller; The remote control terminal interacts with the operator and issues commands to the vehicle controller. The unmanned driving domain controller reports the current position information of the unmanned vehicle platform chassis, and the remote control terminal performs path planning, obtains navigation path information and task information, and sends them to the vehicle controller. The vehicle controller coordinates the power battery management unit, engine-generator controller, and motor controller to perform energy control based on navigation path information and task information.

7. The energy management system for a ground-based unmanned aerial vehicle (UAV) platform according to claim 6, characterized in that, After the remote control terminal issues the task command, it performs route planning and obtains route information, including the total driving route mileage, the altitude information of the route segment, and the mileage of the uphill and downhill sections of the route segment.

8. The energy management system for a ground-based unmanned aerial vehicle (UAV) platform according to claim 7, characterized in that, The mission instructions include destination instructions and mission instructions, and both the remote control terminal and the unmanned domain controller are equipped with high-precision satellite maps.

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