Whole vehicle demand power prediction method and device, vehicle control device and hybrid vehicle

Abstract

Embodiments of the present application provide a vehicle demand power prediction method and device, a vehicle control device and a hybrid vehicle. The present application relates to the technical field of automobiles. The method comprises: obtaining the current gear, first shaft speed, second shaft speed, current throttle opening, current road slope information and current vehicle weight information of a target hybrid vehicle; calculating the third shaft speed of the drive motor on the target hybrid vehicle according to the first shaft speed and the second shaft speed, and using the gear transmission information of the hybrid transmission; calculating the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the drive motor; and correcting the initial peak demand power according to the current throttle opening, the current road slope information and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle. The present application effectively improves the prediction accuracy of demand power and achieves the optimization goal of fuel economy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobiles, in particular to a whole vehicle demand power prediction method and device, a vehicle control device and a hybrid vehicle. BACKGROUND

[0002] Under the dual pressures of energy crisis and environmental pollution, hybrid electric vehicles have become the development trend of the automobile industry, especially in the commercial vehicle field, and many vehicle manufacturers have focused on the research and development of hybrid power systems. However, the demand power prediction of hybrid electric vehicles has always been an important problem in the development of new energy vehicles.

[0003] Since the opening degree of the accelerator pedal can most intuitively reflect the driving demand of the driver during vehicle driving, one of the commonly used methods is to calculate the demand power of the vehicle based on the opening degree of the accelerator pedal.

[0004] However, the demand power of the vehicle during driving will change with the road conditions and the load conditions, for example, when the vehicle is driving on an uphill or muddy road, the response increment of the demand power of the vehicle to the opening degree of the accelerator should be greater than that on a flat road, on the contrary, when the vehicle is driving on a downhill or smooth road, the response increment of the demand power of the vehicle to the opening degree of the accelerator should be smaller than that on a flat road, but the road conditions and the state of the vehicle are not considered in the prior art, so that the error of the demand power of the vehicle obtained by the prior art is large, and the vehicle is prone to jerk when driving according to the demand power. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a whole vehicle demand power prediction method and device, a vehicle control device and a hybrid vehicle. The initial peak demand power of the target hybrid vehicle is calculated in real time according to the input planetary gear structure and parameters of the hybrid vehicle, combined with the external characteristics of the engine ECU, the generator GM and the drive motor TM, and the size of the target demand power of the whole vehicle is corrected in real time according to the accelerator opening degree requested by the driver, the road slope information and the vehicle weight information, so as to effectively improve the prediction accuracy of the demand power, and realize the optimization target of fuel economy.

[0006] In order to achieve the above-mentioned purpose, the technical solutions adopted by the embodiments of the present application are as follows:

[0007] In a first aspect, the embodiments of the present application provide a whole vehicle demand power prediction method, which comprises:

[0008] obtaining the current gear of the target hybrid vehicle, the first shaft speed of the engine, the second shaft speed of the generator, the current accelerator opening degree, the current road slope information and the current vehicle weight information;

[0009] According to the first shaft speed, the second shaft speed, and gear transmission information of a hybrid transmission on the target hybrid vehicle, a third shaft speed of a drive motor on the target hybrid vehicle is calculated;

[0010] According to the first shaft speed of the engine, the second shaft speed of the generator, and the third shaft speed of the drive motor, an initial peak demand power of the target hybrid vehicle is calculated;

[0011] According to the current throttle opening, the current road slope information, and the current vehicle weight information, the initial peak demand power is corrected to obtain a target demand power of the target hybrid vehicle, which is used for torque distribution of the engine, the generator, and the drive motor.

[0012] Optionally, the calculation of the third shaft speed of the drive motor according to the gear transmission information of the hybrid transmission on the target hybrid vehicle comprises:

[0013] According to the gear transmission information, a first speed relationship of an input shaft in the engine, the generator, and the hybrid transmission structure is determined;

[0014] According to the gear transmission information and the current gear, a second speed relationship of the input shaft and the drive motor in the current gear is determined;

[0015] According to the first shaft speed and the second shaft speed, the first speed relationship is used to calculate the speed of the input shaft;

[0016] According to the speed of the input shaft, the second speed relationship is used to calculate the third shaft speed of the drive motor.

[0017] Optionally, the gear transmission information comprises information of an input planetary gear structure used for transmission connection of the engine, the generator, and the input shaft;

[0018] The determination of the first speed relationship of the input shaft in the engine, the generator, and the hybrid transmission structure according to the gear transmission information comprises:

[0019] According to the information of the input planetary gear structure, a gear transmission ratio value of the input planetary gear structure is calculated;

[0020] According to the gear transmission ratio value, the first speed relationship is determined.

[0021] Optionally, the gear transmission information comprises information of a gear structure used for transmission connection of the drive motor, an auxiliary power output device, and the input shaft;

[0022] The second speed relationship of the input shaft and the drive motor in the current gear is determined according to the gear transmission information and the current gear, including:

[0023] According to the information of the gear structure of the gear and the current gear, the gear transmission ratio value in the current gear is obtained;

[0024] According to the gear transmission ratio value in the current gear, the second speed relationship is determined.

[0025] Optionally, the initial peak demand power of the target hybrid vehicle is calculated according to the first shaft speed of the engine, the second shaft speed of the generator, and the third shaft speed of the drive motor, including:

[0026] The external characteristic parameters of the engine, the external characteristic parameters of the generator, and the external characteristic parameters of the drive motor are obtained respectively;

[0027] According to the first shaft speed, the second shaft speed, and the third shaft speed, the first peak torque of the engine, the second peak torque of the generator, and the third peak torque of the drive motor are obtained from the external characteristic parameters of the engine, the external characteristic parameters of the generator, and the external characteristic parameters of the drive motor respectively;

[0028] The first peak demand power of the engine is calculated according to the first shaft speed and the first peak torque;

[0029] The second peak demand power of the generator is calculated according to the second shaft speed and the second peak torque;

[0030] The third peak demand power of the drive motor is calculated according to the second shaft speed and the second peak torque;

[0031] The initial peak demand power is calculated according to the first peak demand power, the second peak demand power, and the third peak demand power.

[0032] Optionally, the initial peak demand power is corrected according to the current throttle opening, the current road slope information, and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle, including:

[0033] The initial peak demand power is corrected according to the current throttle opening to obtain a first corrected demand power;

[0034] The first corrected demand power is corrected according to the current road slope information and the current vehicle weight information to obtain the target demand power.

[0035] Optionally, before the step of performing secondary correction on the primary corrected demand power according to the current road slope information and the current vehicle weight information to obtain the target demand power, the method further comprises:

[0036] obtaining a plurality of sets of historical data of the target hybrid vehicle, each set of historical data comprising historical road slope information, historical vehicle weight information, historical accelerator opening degree, and historical initial peak demand power;

[0037] performing primary correction on the historical initial peak demand power according to the historical accelerator opening degree to obtain historical primary corrected demand power;

[0038] performing polynomial fitting on an initial multi-cloud regression function with unknown slope influence factor and vehicle weight influence factor according to the historical road slope information, the historical vehicle weight information, and the corresponding historical primary corrected demand power in the plurality of sets of historical data to obtain a target multi-cloud regression function with known slope influence factor and vehicle weight influence factor;

[0039] performing secondary correction on the primary corrected demand power according to the current road slope information, the current vehicle weight information, and the primary corrected demand power by using the target multi-cloud regression function to obtain the target demand power.

[0040] In a second aspect, an embodiment of the present application provides a vehicle demand power prediction device, the device comprising:

[0041] an obtaining module configured to obtain a current gear of a target hybrid vehicle, a first shaft speed of an engine, a second shaft speed of a generator, a current accelerator opening degree, current road slope information, and current vehicle weight information;

[0042] a first calculating module configured to calculate a third shaft speed of a drive motor on the target hybrid vehicle according to the first shaft speed, the second shaft speed, and gear transmission information of a hybrid transmission on the target hybrid vehicle;

[0043] a second calculating module configured to calculate an initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator, and the third shaft speed of the drive motor;

[0044] a correcting module configured to correct the initial peak demand power according to the current accelerator opening degree, the current road slope information, and the current vehicle weight information to obtain a target demand power of the target hybrid vehicle, the target demand power being used for torque distribution of the engine, the generator, and the drive motor.

[0045] In a third aspect, the embodiments of the present application provide a vehicle control device, comprising: a memory and a processor, the memory stores a computer program executable on the processor, and the processor executes the computer program to perform the method of any one of the first aspect.

[0046] In a fourth aspect, the embodiments of the present application provide a hybrid vehicle, comprising: a vehicle control device, an engine, a generator, a drive motor and a hybrid transmission; the engine, the generator and the drive motor are all connected with a vehicle drive shaft through the hybrid transmission.

[0047] The vehicle control device is respectively connected with the engine, the generator and the drive motor, and is configured to perform the method of any one of the first aspect.

[0048] Compared with the prior art, the vehicle demand power prediction method, device, vehicle control device and hybrid vehicle provided by the embodiments of the present application have the following beneficial effects:

[0049] The embodiments of the present application provide a vehicle demand power prediction method, device, vehicle control device and hybrid vehicle. It relates to the technical field of automobiles. The method comprises: obtaining the current gear of a target hybrid vehicle, the first shaft speed of an engine, the second shaft speed of a generator, the current throttle opening, the current road slope information and the current vehicle weight information; calculating the third shaft speed of the drive motor on the target hybrid vehicle by using the gear transmission information of the hybrid transmission on the target hybrid vehicle according to the first shaft speed and the second shaft speed; calculating the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the drive motor; correcting the initial peak demand power according to the current throttle opening, the current road slope information and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle, and the target demand power is used for torque distribution of the engine, the generator and the drive motor, so that the hybrid vehicle maintains a stable driving state under different working conditions. Therefore, the present application comprehensively considers the current gear, the shaft speed, the throttle opening, the road slope and the vehicle weight, and calculates the vehicle demand power in real time. The size of the vehicle demand power is corrected in real time according to the throttle pedal opening requested by the driver, the vehicle information and the road slope information, so that the target demand power is obtained. The hybrid vehicle distributes the torque according to the target demand power. If the vehicle demand power at the current time is small, the torque distributed by the engine is small, and the fuel consumption is reduced. If the demand power at the current time is large, the torque distributed by the engine is large, and the power of the vehicle is improved. Therefore, the accurate and real-time calculation of the target demand power is of great significance to improving the power and fuel economy of the hybrid vehicle. At the same time, the prediction accuracy of the demand power of the hybrid vehicle can also be effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0051] Figure 1 A structural schematic diagram of a hybrid vehicle provided by the embodiments of the present application;

[0052] Figure 2 A structural schematic diagram of a vehicle control device provided by the embodiments of the present application;

[0053] Figure 3 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 1 ;

[0054] Figure 4 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 2 ;

[0055] Figure 5 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 3 ;

[0056] Figure 6 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 4 ;

[0057] Figure 7 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 5 ;

[0058] Figure 8 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 6 ;

[0059] Figure 9 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 7 ;

[0060] Figure 10 A flowchart of a whole vehicle demand power prediction method provided by the embodiments of the present application Figure 8 ;

[0061] Figure 11 A structural schematic diagram of a whole vehicle demand power prediction device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0063] Therefore, the detailed description of the embodiments of the present application provided in the drawings below is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0064] It should be noted that the relational terms such as "first" and "second" and the like are used only to distinguish one entity or operation from another, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements not only includes those elements, but also includes other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0065] To clearly describe a whole vehicle demand power prediction method and device, vehicle control device and hybrid vehicle provided by the embodiments of the present application, the hybrid vehicle is first described in detail in combination with the drawings. Figure 1 A structural schematic diagram of a hybrid vehicle provided by the embodiments of the present application is shown. As shown in the figure, the hybrid vehicle 200 can include a vehicle control device 100, an engine ECU, a generator GM, a drive motor TM and a hybrid transmission 210. Figure 1

[0066] The hybrid vehicle 200 can be selected according to actual conditions. For example, the hybrid vehicle 200 can be selected as a vehicle with DHT hybrid architecture.

[0067] ​The engine ECU, the generator GM and the drive motor TM are all connected with the vehicle drive shaft through the hybrid transmission 210, so that the engine ECU, the generator GM and the drive motor TM can closely cooperate to integrate and deploy the outputs of different power sources through the hybrid transmission 210; the vehicle control device 100 is communicatively connected (such as CAN communication) with the engine ECU, the generator GM and the drive motor TM, and through the communication connection with the engine ECU, the generator GM and the drive motor TM, the working state information of each power component can be obtained in real time, and precise cooperative control of the power sources in the hybrid vehicle 200 can be realized.

[0068] The vehicle control device 100 is used to execute the whole vehicle demand power prediction method. The vehicle control device 100 can be selected according to the actual situation, for example, the vehicle control device 100 can be a whole vehicle controller.

[0069] It should be noted that the engine ECU, the generator GM, the drive motor TM and the vehicle control device 100 are all communicatively connected with the gateway controller. The engine ECU is communicatively connected with the gateway controller through P-CAN; the generator GM and the drive motor TM are both communicatively connected with the gateway controller through EV-CAN; and the vehicle control device 100 is communicatively connected with the gateway controller through EP-CAN.

[0070] The hybrid vehicle provided by the embodiment of the present application can be composed of at least a vehicle control device, an engine, a generator, a drive motor and a hybrid transmission; the engine, the generator and the drive motor are all connected with the vehicle drive shaft through the hybrid transmission, so that the power sources can be closely and efficiently matched and distributed according to the running state of the hybrid vehicle; the vehicle control device is communicatively connected with the engine, the generator and the drive motor to obtain detailed running parameters of each power source in real time, and the vehicle control device is used to execute the whole vehicle demand power prediction method to accurately coordinate the working modes of the power sources.

[0071] Further, the present application also provides a vehicle control device structure schematic diagram. Figure 2 A vehicle control device structure schematic diagram is provided in the embodiment of the present application. As shown in the figure, the vehicle control device 100 can include a memory 110 and a processor 120. Figure 2

[0072] The memory 110 stores machine executable instructions that can be executed by the processor 120, that is, when the hybrid vehicle 200 is running, the above machine readable instructions are executed, and the processor 120 and the memory 110 are communicatively connected through a bus. The processor 120 can execute the machine executable instructions to implement the whole vehicle demand power prediction method.

[0073] ​The memory 110, the processor 120 and the bus elements are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the elements can be electrically connected to each other through one or more communication buses or signal lines. The mobile storage device includes at least one software function module stored in the memory 110 in the form of software or firmware or solidified in the operating system (OS) of the electronic device. The processor 120 is used to execute the executable modules stored in the memory 110, such as the software function modules and computer programs included in the whole vehicle demand power prediction method of the mobile storage medium.

[0074] The memory 110 can be, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0075] The whole vehicle demand power prediction method provided by the embodiment of the present application can be executed by the processor in the vehicle control device 100. The whole vehicle demand power prediction method provided by the above embodiment of the present application will be explained and described in detail in combination with the drawings as follows. The whole vehicle demand power prediction method provided by the embodiment of the present application will be explained as follows, Figure 3 The flowchart of the whole vehicle demand power prediction method provided by the embodiment of the present application Figure 1 As shown in Figure 3 , the vehicle control device 100 applied to a hybrid vehicle, the method can include:

[0076] S301, acquiring the current gear of the target hybrid vehicle, the first shaft speed of the engine, the second shaft speed of the generator, the current throttle opening, the current road slope information and the current vehicle weight information.

[0077] In one possible implementation, through the communication connection between the vehicle control device and the engine ECU, the generator GM and the drive motor TM, the current gear of the target hybrid vehicle, the first shaft speed of the engine ECU , the second shaft speed of the generator GM , the current throttle opening current road gradient information and current vehicle weight information.

[0078] It should be noted that the target hybrid vehicle gear can include 1st gear, 2nd gear, 3rd gear, 4th gear, 5th gear, 6th gear and PTO gear (parking gear).

[0079] S302, according to the first shaft speed, the second shaft speed, the gear transmission information of the hybrid transmission on the target hybrid vehicle is used to calculate the third shaft speed of the drive motor on the target hybrid vehicle.

[0080] In one possible implementation, the first shaft speed , the second shaft speed obtained according to the above step S301 , the second shaft speed , and the gear transmission information of the hybrid transmission on the target hybrid vehicle is obtained through CAN communication, and finally the third shaft speed of the drive motor TM on the target hybrid vehicle is calculated according to the first shaft speed , the second shaft speed

[0081] and the gear transmission information of the hybrid transmission on the target hybrid vehicle.

[0082] In one possible implementation, the first shaft speed , the second shaft speed and the third shaft speed of the drive motor TM are used to calculate the initial peak demand power of the target hybrid vehicle , so that the hybrid vehicle can reasonably distribute power output according to the respective speeds of the engine ECU, the generator GM and the drive motor TM under various working conditions (such as sudden acceleration, high-speed overtaking, climbing, etc.).

[0083] S304, according to the current throttle opening, the current road gradient information and the current vehicle weight information, the initial peak demand power is corrected to obtain the target demand power of the target hybrid vehicle.

[0084] The target demand power is used to distribute the torque of the ECU, the generator GM and the drive motor TM.

[0085] In one possible implementation, the initial peak demand power is corrected according to the current throttle opening , the current road gradient information and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle.At the moment of acceleration of the hybrid vehicle, the current throttle opening directly reflects the demand of the driver for power, while the road slope and the vehicle weight increase the driving resistance. By comprehensively considering the influence of the three factors on the initial peak demand power , the hybrid vehicle can accurately provide the required power. The target demand power calculation can make the hybrid vehicle better cope with various working condition changes during driving, and improve the driving stability and maneuverability.

[0086] The embodiment of the present application provides a vehicle demand power prediction method, which obtains the current gear of a target hybrid vehicle, the first shaft speed of an engine, the second shaft speed of a generator, the current throttle opening, the current road slope information and the current vehicle weight information; according to the first shaft speed and the second shaft speed, the third shaft speed of a driving motor on the target hybrid vehicle is calculated by using the gear transmission information of a hybrid transmission on the target hybrid vehicle; according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the driving motor, the initial peak demand power of the target hybrid vehicle is calculated; according to the current throttle opening, the current road slope information and the current vehicle weight information, the initial peak demand power is corrected to obtain the target demand power of the target hybrid vehicle, and the target demand power is used for torque distribution of the engine, the generator and the driving motor, so that the hybrid vehicle maintains a stable driving state under different working conditions. Therefore, the present application comprehensively considers the current gear, the shaft speed, the throttle opening, the road slope and the vehicle weight, and calculates the vehicle demand power in real time, and the vehicle demand power is corrected in real time according to the throttle opening requested by the driver, the vehicle information and the road slope information, so that the target demand power is obtained, the hybrid vehicle performs corresponding torque distribution according to the target demand power, if the vehicle demand power at the current moment is small, the torque distributed by the engine is small, and the fuel consumption is reduced; if the demand power at the current moment is large, the torque distributed by the engine is large, and the vehicle power is improved. Therefore, the accurate and real-time calculation of the target demand power is of great significance to improve the power and fuel economy of the hybrid vehicle. Meanwhile, the prediction accuracy of the demand power of the hybrid vehicle can be effectively improved.

[0087] On the basis Figure 3 , the vehicle demand power prediction method provided by the above embodiment of the present application is explained and described in detail in combination with the accompanying drawings as follows. Figure 4 The flowchart of the vehicle demand power prediction method provided by the embodiment of the present application Figure 2 . As shown in Figure 4 , the above method uses the gear transmission information of the hybrid transmission on the target hybrid vehicle to calculate the third shaft speed of the driving motor, which can include:

[0088] S401. Based on the gear transmission information, determine the first speed relationship of the input shaft in the engine, generator and hybrid transmission structure.

[0089] In one possible implementation, the first rotational speed relationship between the engine ECU, generator GM, and input shaft in the hybrid transmission structure can be derived based on gear transmission information. This first rotational speed relationship enables the intrinsic connection between the rotational speeds of various components in the hybrid vehicle, thus providing an indispensable key data foundation for the efficient operation, intelligent control, and performance optimization of the entire power source. This ensures that power can be rationally distributed and coordinated under different operating conditions, guaranteeing the reliability and safety of the vehicle.

[0090] S402. Based on the gear transmission information and the current gear position, determine the second speed relationship between the input shaft and the drive motor in the current gear position.

[0091] In one possible implementation, a second speed relationship between the input shaft and the drive motor TM is determined based on gear transmission information and the current gear position. This second speed relationship provides a core basis for the intelligent control and efficient operation of the hybrid vehicle, enabling real-time and precise coordinated control of the input shaft and drive motor TM in various complex driving scenarios. This ensures the smoothness, efficiency, and adaptability of power output, guaranteeing the reliability, stability, and safety of the hybrid vehicle throughout its entire lifecycle.

[0092] S403. Based on the first shaft speed and the second shaft speed, and using the first speed relationship, calculate the input shaft speed.

[0093] In one possible implementation, based on the first rotational speed relationship, according to the first shaft rotational speed... Second axis speed Precisely calculate the input shaft speed This allows the vehicle control equipment in hybrid vehicles to better understand the status of key aspects of power transmission in real time. Furthermore, during energy recovery phases, such as braking or deceleration, knowing the input shaft speed helps the vehicle control equipment better manage the motor's power generation. Based on the first speed relationship, the motor can generate electricity at its optimal efficiency point, efficiently converting the kinetic energy of the hybrid vehicle into electrical energy and storing it. This improves energy recovery efficiency, increases the pure electric range of the hybrid vehicle, reduces fuel consumption and exhaust emissions, and promotes energy conservation and environmental protection.

[0094] S404. Based on the input shaft speed, use the second speed relationship to calculate the third shaft speed of the drive motor.

[0095] In one possible implementation, based on the rotational speed of the input shaft... Using the second speed relationship, the third shaft speed of the drive motor TM is calculated. This allows the vehicle control equipment of hybrid vehicles to precisely adjust the operating parameters of the drive motor according to real-time driving conditions, ensuring it always operates within its optimal efficiency range. Furthermore, when the hybrid vehicle accelerates, decelerates, or handles complex road conditions, it can quickly adjust the input shaft speed based on the speed of the drive motor. The output of the drive motor™ is adjusted according to the changes, enhancing the responsiveness of the power source.

[0096] The vehicle power demand prediction method provided in this application first determines the first rotational speed relationship between the engine, generator, and input shaft in the hybrid transmission structure based on gear transmission information to achieve high coordination and optimization of the power sources. Then, based on the gear transmission information and the current gear, it determines the second rotational speed relationship between the input shaft and the drive motor at the current gear. Based on the first and second rotational speed relationships, it precisely controls the power generation state of the drive motor, enabling it to convert the kinetic energy of the hybrid vehicle into electrical energy and store it at the most suitable speed, thus improving energy recovery and management efficiency. Next, based on the first and second shaft rotational speeds and using the first rotational speed relationship, it calculates the rotational speed of the input shaft. Finally, based on the input shaft rotational speed and using the second rotational speed relationship, it calculates the third shaft rotational speed of the drive motor. Therefore, the hybrid vehicle provided in this application can achieve more intelligent and automated control functions, improving the adaptability and reliability of the hybrid vehicle.

[0097] Optionally, the gear transmission information in the above method may include: information about the input planetary gear set structure, which is used to drive the engine ECU, generator GM, and input shaft. The information about the input planetary gear set structure may include: the planet carrier, the sun gear, and the external ring gear.

[0098] In one possible implementation, Figure 5 A flowchart illustrating a method for predicting the power demand of a vehicle as provided in this application embodiment. Figure 3 .like Figure 5 As shown, the method described above, which determines the first speed relationship of the input shaft in the engine, generator, and hybrid transmission structure based on gear transmission information, may include:

[0099] S501. Calculate the gear ratio of the input planetary gear set structure based on the information of the input planetary gear set structure.

[0100] In one possible implementation, refer to the above. Figure 1 The engine ECU, generator GM and input shaft correspond to the three parts of the input planetary gear structure: planet carrier 1, sun gear 1 and external gear ring 1. Based on the gear ratio of external gear ring 1 and sun gear 1, the gear transmission ratio K of the input planetary gear structure is calculated using the following formula (1).

[0101] Formula (1)

[0102] S502, determining a first speed relationship according to the gear transmission ratio.

[0103] In a possible implementation manner, with continuous reference to the above Figure 1 , according to the gear transmission ratio K, the transmission ratio relationship between the planetary carrier 1, the sun gear 1 and the outer ring gear 1 can be obtained, which respectively corresponds to the first shaft speed of the engine ECU, the second shaft speed of the generator GM and the speed of the input shaft in the hybrid vehicle architecture, that is, the first speed relationship. The first speed relationship can be determined by using the following formula (2).

[0104] Formula (2)

[0105] The vehicle demand power prediction method provided by the embodiment of the present application can be composed of gear transmission information of the input planetary gear structure. The input planetary gear structure is used for transmission connection of the engine, the generator and the input shaft. Then, according to the information of the input planetary gear structure, the gear transmission ratio of the input planetary gear structure can be calculated according to the engine, the generator and the input shaft corresponding to the planetary carrier, the sun gear and the outer ring gear in the input planetary gear structure, respectively. Finally, according to the gear transmission ratio, the first speed relationship is determined, so that the engine and the generator can realize accurate power distribution and collaborative work under different working conditions. When the hybrid vehicle is decelerated or braked, based on the known gear transmission ratio and the first speed relationship, the power generation state of the generator can be accurately controlled, the kinetic energy of the hybrid vehicle can be efficiently converted into electric energy and stored, the efficiency and effect of energy recovery can be improved, the pure electric cruising range of the hybrid vehicle can be increased, the fuel consumption and exhaust emission can be reduced, and energy saving and environmental protection can be realized. At the same time, a calculation basis is provided for subsequent accurate control and intelligent management of the power source.

[0106] Optionally, the gear transmission information in the above method includes information of a gear structure of a gear position. The gear structure of the gear position is used for transmission connection of the drive motor TM, the auxiliary power output device and the input shaft. The information of the gear structure of the gear position can refer to the number of gear rings corresponding to the gear position information in the above Figure 1 . For example, the number of gear rings in the gear structure of the gear position corresponding to 2 gears, for example, 28, 67, 42 and 63.

[0107] In a possible implementation embodiment, Figure 6 a flowchart of a vehicle demand power prediction method provided by the embodiment of the present application is shown in Figure 4 . As shown in Figure 6 , the above method can include the following steps. ​​​

[0108] S601. Based on the information of the gear structure and the current gear, obtain the gear ratio value of the current gear.

[0109] S602. Determine the second speed relationship based on the gear ratio value of the current gear.

[0110] In one possible implementation, if the gear ratio K1 for the current gear is obtained based on the information of the gear structure and the current gear, it means that the drive motor TM and the input shaft of the target hybrid vehicle are not directly connected, but connected through the gear structure. Depending on the current gear setting, the gear ratio between the drive motor TM and the input shaft will vary, and in PTO mode, the drive motor TM and the input shaft are not connected. Therefore, it is necessary to first determine the current gear and the gear ratio K1 between the drive motor TM and the input shaft. Then, based on the gear ratio K1 for the current gear, the second speed relationship can be determined, i.e., the speed of the input shaft can be obtained. and the third axis speed of the drive motor™ The correspondence between them.

[0111] For example, refer to the above Figure 1 ,by Figure 1 Taking the current gear as 2nd gear as an example, when the input shaft and drive motor TM are in 2nd gear, the corresponding gear structure information is: 28, 67, 42, and 63. Therefore, the input shaft speed... and the third axis speed of the drive motor™ The relationship between them can be expressed by the following formula (3).

[0112] Formula (3)

[0113] It should be noted that if the input shaft and the drive motor TM are directly connected, the rotational speed of the input shaft can be obtained. and the third axis speed of the drive motor™ Equal, that is = Then the above formula (2) can be expressed by the following formula (4).

[0114] Formula (4)

[0115] The whole vehicle demand power prediction method provided by the embodiment of the application, the gear transmission information can be composed of information of a gear structure, wherein the gear structure is used for driving connection of a driving motor, an auxiliary power output device and an input shaft; a gear transmission ratio under a current gear is acquired according to the information of the gear structure and the current gear; and a second speed relationship is determined according to the gear transmission ratio under the current gear, so that the hybrid vehicle can flexibly adjust the power output and distribution mode according to different driving conditions (such as starting, accelerating, cruising, climbing, etc.), and according to the second speed relationship, the generation state of the driving motor can be better controlled during deceleration or braking of the hybrid vehicle, and the energy recovery efficiency is enhanced.

[0116] The whole vehicle demand power prediction method provided by the embodiment of the application will be explained and described in detail in combination with the accompanying drawings as follows. Figure 7 The flowchart of the whole vehicle demand power prediction method provided by the embodiment of the application Figure 5 . As shown in Figure 7 , the method for calculating the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the driving motor can include:

[0117] S701, respectively acquiring the external characteristic parameters of the engine, the external characteristic parameters of the generator and the external characteristic parameters of the driving motor.

[0118] In a possible implementation manner, the external characteristic parameters of the engine ECU, the external characteristic parameters of the generator GM and the external characteristic parameters of the driving motor TM are respectively acquired from the preset storage information of the hybrid vehicle.

[0119] It should be noted that the external characteristic parameters of the engine ECU, the external characteristic parameters of the generator GM and the external characteristic parameters of the driving motor TM are all provided by the manufacturer of the hybrid vehicle and are fixed data. These external characteristic parameters can be the MAP graph of each component.

[0120] S702, acquiring the first peak torque of the engine, the second peak torque of the generator and the third peak torque of the driving motor from the external characteristic parameters of the engine, the external characteristic parameters of the generator and the external characteristic parameters of the driving motor respectively according to the first shaft speed, the second shaft speed and the third shaft speed.

[0121] In a possible implementation manner, according to the current gear, the first shaft speed , the second shaft speed and the third shaft speed and the first peak torque of the engine ECU is acquired from the external characteristic parameter of the engine ECU, the external characteristic parameter of the generator GM, and the external characteristic parameter of the drive motor TM, respectively , the second peak torque of the generator GM , and the third peak torque of the drive motor TM .

[0122] S703, the first peak demand power of the engine is calculated according to the first shaft speed and the first peak torque.

[0123] In one possible implementation, the first peak demand power of the engine ECU is calculated according to the first shaft speed and the first peak torque using the following formula (5) .

[0124] Formula (5)

[0125] S704, the second peak demand power of the generator is calculated according to the second shaft speed and the second peak torque.

[0126] In one possible implementation, the second peak demand power of the generator GM is calculated according to the second shaft speed and the second peak torque using the following formula (6) .

[0127] Formula (6)

[0128] S705, the third peak demand power of the drive motor is calculated according to the third shaft speed and the third peak torque.

[0129] In one possible implementation, the third peak demand power of the drive motor TM is calculated according to the third shaft speed and the third peak torque using the following formula (7) .

[0130] Formula (7)

[0131] It should be noted that the unit of the peak demand power is KW, the unit of the peak torque is Nm, and the unit of the shaft speed is rpm. In addition, it should be noted that if the current gear is the PTO gear, the third shaft speed of the drive motor TM is 0, and the third peak demand power is also 0.

[0132] S706, calculating the initial peak demand power according to the first peak demand power, the second peak demand power and the third peak demand power.

[0133] In one possible implementation, the initial peak demand power is calculated according to the first peak demand power , the second peak demand power and the third peak demand power using the following formula (8) .

[0134] Formula (8)

[0135] It should be noted that, as can be seen from Figure 1 , the generator GM can provide power for the engine ECU, and then the current input shaft (i.e. the drive motor TM) speed can be obtained according to the above formula (2) and the gear ratio K of the input planetary gear set structure. The first speed relationship between the engine ECU and the generator GM is issued, and in the case of meeting the first speed relationship, the maximum value of the first peak demand power of the engine ECU and the second peak demand power of the generator GM (PE+PG) is calculated according to the external characteristic parameters of the engine ECU and the generator GM, and then the initial peak demand power is obtained according to the above formula (8).

[0136] The vehicle power demand prediction method provided in this application obtains the external characteristic parameters of the engine, the generator, and the drive motor, respectively. Then, based on the first shaft speed, the second shaft speed, and the third shaft speed, it obtains the first peak torque of the engine, the second peak torque of the generator, and the third peak torque of the drive motor from the external characteristic parameters of the engine, the generator, and the drive motor, respectively. Next, based on the first shaft speed and the first peak torque, it calculates the first peak power demand of the engine; based on the second shaft speed and the second peak torque, it calculates the second peak power demand of the generator; and based on the second shaft speed and the second peak torque, it calculates the third peak power demand of the drive motor. Finally, based on the first peak power demand, the first peak power demand, and the first peak power demand, it calculates the initial peak power demand. Therefore, this application can obtain the external characteristic parameters of each power source (engine, generator, drive motor) and combine them with the corresponding shaft speeds to calculate peak torque and peak power demand, thereby accurately understanding the optimal operating state of each power source under different operating conditions and achieving efficient power output for hybrid vehicles. Meanwhile, different driving scenarios have different power requirements. The calculation method provided in this application helps to flexibly select the best power source combination according to the actual situation, thereby enhancing the reliability and safety of hybrid vehicles.

[0137] The method for predicting the power demand of a vehicle according to the above embodiments of this application will be explained and described in detail below with reference to the accompanying drawings. Figure 8 A flowchart illustrating a method for predicting the power demand of a vehicle as provided in this application embodiment. Figure 6 .like Figure 8 As shown, the above method corrects the initial peak power demand based on the current throttle opening, current road gradient, and current vehicle weight to obtain the target power demand of the target hybrid vehicle, which may include:

[0138] S801. Based on the current throttle opening, the initial peak power demand is corrected to obtain the corrected power demand.

[0139] In one possible implementation, based on the current throttle opening... %, for initial peak power demand To make corrections, the required power for the first correction is obtained using the following formula (9). .

[0140] ppr(%) formula (9)

[0141] S802. Based on the current road slope information and the current vehicle weight information, the power demand of the first correction is corrected a second time to obtain the target power demand.

[0142] In a possible implementation manner, the target demand power is obtained by performing secondary correction on the once corrected demand power according to current road slope information and current vehicle weight information . The target demand power can be adaptively adjusted based on the current road slope information, the current vehicle weight information and the current accelerator opening degree, and the prediction accuracy of the demand power is effectively improved, so that the optimization target of fuel economy is achieved.

[0143] The vehicle demand power prediction method provided by the embodiment of the present application corrects the initial peak demand power to obtain the once corrected demand power according to the current accelerator opening degree, and performs secondary correction on the once corrected demand power to obtain the target demand power according to the current road slope information and the current vehicle weight information. When the hybrid vehicle faces roads with different slopes, the power is secondarily corrected by combining the current road slope information and the vehicle weight information, so that the hybrid vehicle can be accurately provided with appropriate power. Since the changes of the vehicle weight and the road slope have a significant influence on the driving resistance and energy consumption of the hybrid vehicle, the target demand power obtained by the secondary correction can make the hybrid vehicle more accurately adjust the power output and energy distribution according to the actual working conditions.

[0144] The vehicle demand power prediction method provided by the embodiment of the present application will be explained and described in detail in combination with the accompanying drawings as follows. Figure 9 The flowchart of the vehicle demand power prediction method provided by the embodiment of the present application Figure 7 is shown in FIG. 1. Figure 9 Before the target demand power is obtained by performing secondary correction on the once corrected demand power according to the current road slope information and the current vehicle weight information in the above method, the method can further include the following steps.

[0145] S901, obtaining a plurality of sets of historical data of a target hybrid vehicle.

[0146] In a possible implementation manner, the vehicle control device can obtain the plurality of sets of historical data of the target hybrid vehicle through the communication connection between the vehicle control device and the engine ECU, the generator GM and the drive motor TM, and each set of historical data includes historical road slope information, historical vehicle weight information, historical accelerator opening degree and historical initial peak demand power .

[0147] S902, performing once correction on the historical initial peak demand power according to the historical accelerator opening degree to obtain historical once corrected demand power.

[0148] In a possible implementation manner, the historical accelerator opening degree %, the above formula (9) can be used to the historical initial peak demand power is modified to obtain the historical first modified demand power .

[0149] S903, according to the historical road slope information, historical vehicle weight information and corresponding historical first modified demand power in the historical data, polynomial fitting is performed on the initial multi-cloud regression function with unknown slope influence factor and vehicle weight influence factor to obtain the target multi-cloud regression function with known slope influence factor and vehicle weight influence factor.

[0150] In a possible implementation manner, in a preset software (such as matlab), according to the historical road slope information, historical vehicle weight information and corresponding historical first modified demand power in the historical data , a preset function (such as nonlinear function lsqcurvefit) is called to perform polynomial fitting on the initial multi-cloud regression function modelFun with unknown slope influence factor and vehicle weight influence factor, for example, historical road slope information, historical vehicle weight information and corresponding historical first modified demand power and the like data in the historical data are imported, and the initial multi-cloud regression function modelFun is defined, where the modelFun = (b, x) b (1) * x (:, 1) ^ b (2) + b (3) exp (b (4) * x (2) + b (5), where b (1) and b (2) are slope influence factors, b (3) and b (4) are vehicle weight influence factors, and b (5) is a correction bias. Then, b (1), b (2), b (3), b (4) and b (5) are initialized and valued, for example, b (1) = 1, b (2) = 0.5, b (3) = 1, b (4) = 0.1, b (5) = 0. Then, a preset function (such as nonlinear function lsqcurvefit) is called to perform polynomial fitting on the initial multi-cloud regression function modelFun, and the target multi-cloud regression function modelFun1 with known slope influence factor and vehicle weight influence factor can be obtained.

[0151] S904, according to the current road slope information, current vehicle weight information and first modified demand power, the target multi-cloud regression function is used for secondary modification to obtain the target demand power.

[0152] In a possible implementation manner, according to the current road slope information and the current vehicle weight information, the first modified demand power is secondarily modified by using the target multi-cloud regression function modelFun1, and the following formula (10) is used to obtain the target demand power .

[0153] Equation (10)

[0154] wherein x1 represents a variable of current vehicle weight information, x2 represents a variable of current road slope information, a and b both represent influence factors of current vehicle weight information on target demand power , c and d both represent influence factors of current road slope information on target demand power , and f corrects bias. Wherein a, b, c, d, and f are parameters to be estimated in the target multi-cloud regression function modelFun1, i.e., b(1), b(2), b(3), b(4), and b(5) described above.

[0155] The vehicle demand power prediction method provided by the embodiments of the present application obtains a plurality of sets of historical data of a target hybrid vehicle, each set of historical data can be composed of historical road slope information, historical vehicle weight information, historical throttle opening, and historical initial peak demand power, etc. According to the historical throttle opening, the historical initial peak demand power is corrected once to obtain the historical first corrected demand power. According to the historical road slope information, the historical vehicle weight information, and the corresponding historical first corrected demand power in the plurality of sets of historical data, the initial multi-cloud regression function with unknown slope influence factor and vehicle weight influence factor is polynomial fitted to obtain the target multi-cloud regression function with known slope influence factor and vehicle weight influence factor. According to the current road slope information, the current vehicle weight information, and the first corrected demand power, the target multi-cloud regression function is used for secondary correction to obtain the target demand power. Through the use of the plurality of sets of historical data, the power demand of the hybrid vehicle is analyzed and modeled in depth, and the hybrid vehicle can accurately adapt to the power output in various actual driving scenarios. The accurate target demand power calculation provides a key decision basis for the hybrid vehicle, so that the hybrid vehicle can realize efficient use of energy under different working conditions.

[0156] To facilitate understanding of the above vehicle demand power prediction method, the embodiments of the present application also provide an example of a flow of a vehicle demand power prediction method, which will be described below in combination with the accompanying drawings, Figure 10 a flowchart of a vehicle demand power prediction method provided by the embodiments of the present application Figure 8 . As shown in Figure 10 , the schematic Figure 8 provided by the embodiments of the present application can include:

[0157] S1001, obtaining the current gear, the first shaft speed of the engine, the second shaft speed of the generator, the current throttle opening, the current road slope information, and the current vehicle weight information of the target hybrid vehicle.

[0158] Specifically, through the communication connection between the vehicle control device and the engine ECU, the generator GM, and the drive motor TM, the current gear of the target hybrid vehicle, the first shaft speed of the engine ECU , the second shaft speed of the generator GM , the current throttle opening , the current road slope information, and the current vehicle weight information are further obtained.

[0159] S1002, according to the gear transmission information, the first speed relationship of the input shaft in the engine, the generator and the hybrid transmission structure is determined.

[0160] Specifically, referring to the above Figure 1 , the engine ECU, the generator GM and the input shaft correspond to the planetary carrier 1, the sun gear 1 and the outer ring gear 1 in the input planetary gear structure respectively. According to the gear ratio of the outer ring gear 1 and the sun gear 1, the gear transmission ratio K of the input planetary gear structure is calculated by using the above formula (1). According to the gear transmission ratio K, the transmission proportional relationship between the planetary carrier 1, the sun gear 1 and the outer ring gear 1 can be obtained, which corresponds to the speed relationship between the first shaft speed of the engine ECU , the second shaft speed of the generator GM and the speed of the input shaft in the hybrid vehicle structure, that is, the first speed relationship, which can be determined by using the above formula (2).

[0161] S1003, according to the gear transmission information and the current gear, the second speed relationship between the input shaft and the drive motor under the current gear is determined.

[0162] Specifically, referring to the above Figure 1 , if the gear transmission ratio K1 under the current gear is obtained according to the information of the gear structure and the current gear, it means that the drive motor TM and the input shaft of the target hybrid vehicle are not directly connected, but connected through the gear structure. According to the different settings of the current gear, the ring gear ratio between the drive motor TM and the input shaft will be different, and in the PTO gear mode, the drive motor TM and the input shaft are not connected. Therefore, it is necessary to determine the gear transmission ratio K1 between the current gear and the drive motor TM and the input shaft, and then the second speed relationship can be determined according to the gear transmission ratio K1 under the current gear, that is, the corresponding relationship between the speed of the input shaft and the third shaft speed of the drive motor TM is obtained.

[0163] If the input shaft and the drive motor TM are directly connected, the speed of the input shaft and the third shaft speed of the drive motor TM are equal, that is = . Then the above formula (4) can be used to express it.

[0164] S1004, according to the first shaft speed and the second shaft speed, the first speed relationship is used to calculate the speed of the input shaft.

[0165] Specifically, the gear transmission ratio K of the input planetary gear structure is accurately calculated according to the first shaft speed and the second shaft speed based on the first speed relationship .

[0166] S1005, according to the speed of the input shaft, the second speed relationship is used to calculate the third shaft speed of the drive motor.

[0167] Specifically, according to the speed of the input shaft corresponding to the current gear and the gear ratio of the drive motor TM, i.e. the second speed relationship, the third shaft speed of the drive motor TM is calculated .

[0168] S1006, according to the first shaft speed of the engine, the second shaft speed of the generator, and the third shaft speed of the drive motor, the initial peak demand power of the target hybrid vehicle is calculated.

[0169] Specifically, the external characteristic parameters of the engine ECU, the external characteristic parameters of the generator GM, and the external characteristic parameters of the drive motor TM are respectively obtained from the preset storage information of the hybrid vehicle. Then according to the current gear, the first shaft speed , the second shaft speed , and the third shaft speed corresponding to the current gear are determined, and the first peak torque of the engine ECU, the second peak torque of the generator GM, and the third peak torque of the drive motor TM are respectively obtained from the external characteristic parameters of the engine ECU, the external characteristic parameters of the generator GM, and the external characteristic parameters of the drive motor TM. The above formula (5), formula (6) and formula (7) are used to calculate the first peak demand power of the engine ECU, the second peak demand power of the generator GM, and the third peak demand power of the drive motor TM. The sum of the three demand powers is calculated, and the above formula (8) is used to calculate the initial peak demand power .

[0170] S1007, according to the current throttle opening, the current road slope information and the current vehicle weight information, the initial peak demand power is corrected to obtain the target demand power of the target hybrid vehicle.

[0171] Specifically, according to the current throttle opening , the initial peak demand power is corrected, the first corrected demand power is obtained by using the above formula (9), then the first corrected demand power is twice corrected by using the target multiple regression function modelFun1, and the target demand power is obtained by using the above formula (10).

[0172] The vehicle demand power prediction method provided in the embodiments of the present application obtains the current gear of the target hybrid vehicle, the first shaft speed of the engine, the second shaft speed of the generator, the current throttle opening, the current road slope information and the current vehicle weight information, determines the first speed relationship of the input shaft in the engine, the generator and the hybrid transmission structure according to the gear transmission information, determines the second speed relationship of the input shaft and the drive motor under the current gear according to the gear transmission information and the current gear, calculates the speed of the input shaft by using the first speed relationship according to the first shaft speed and the second shaft speed, calculates the third shaft speed of the drive motor by using the second speed relationship according to the speed of the input shaft, calculates the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the drive motor, and corrects the initial peak demand power according to the current throttle opening, the current road slope information and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle. Thus, the vehicle demand power is calculated in real time by comprehensively considering the current gear, the shaft speed, the throttle opening, the road slope and the vehicle weight, and the size of the vehicle demand power is corrected in real time according to the throttle pedal opening requested by the driver, the vehicle information and the road slope information, so that the target demand power is obtained, the hybrid vehicle distributes the torque according to the target demand power, the torque distributed by the engine is smaller if the vehicle demand power at the current moment is smaller, and the fuel consumption is reduced, and the torque distributed by the engine is larger if the demand power at the current moment is larger, and the vehicle power is improved. Thus, the accurate and real-time calculation of the target demand power is of great significance to improving the power and fuel economy of the hybrid vehicle. Meanwhile, the prediction accuracy of the demand power of the hybrid vehicle can also be effectively improved.

[0173] Based on the same inventive concept, the embodiments of the present application also provide a vehicle demand power prediction device. Since the principle of solving problems in the device of the embodiments of the present application is similar to the above-mentioned vehicle demand power prediction method, the implementation of the device can be referred to the implementation of the method, and the repeated parts will not be described here.

[0174] Figure 11 A structural schematic diagram of a vehicle demand power prediction device provided in the embodiments of the present application. As shown in Figure 11As shown, the vehicle control equipment applied in hybrid vehicles, the vehicle demand power prediction device 1100 may include:

[0175] The acquisition module 1101 is used to acquire the target hybrid vehicle's current gear, engine first shaft speed, generator second shaft speed, current throttle opening, current road slope information, and current vehicle weight information;

[0176] The first calculation module 1102 is used to calculate the third shaft speed of the drive motor on the target hybrid vehicle based on the first shaft speed and the second shaft speed, using the gear transmission information of the hybrid transmission on the target hybrid vehicle.

[0177] The second calculation module 1103 is used to calculate the initial peak power demand of the target hybrid vehicle based on the first shaft speed of the engine, the second shaft speed of the generator, and the third shaft speed of the drive motor.

[0178] The correction module 1104 is used to correct the initial peak demand power based on the current throttle opening, current road slope information and current vehicle weight information to obtain the target demand power of the target hybrid vehicle. The target demand power is used to distribute torque among the engine, generator and drive motor.

[0179] In one optional implementation, the first calculation module 1102 is specifically used for: determining a first speed relationship between the input shaft in the engine, generator, and hybrid transmission structure based on gear transmission information; determining a second speed relationship between the input shaft and the drive motor in the current gear based on the gear transmission information and the current gear; calculating the speed of the input shaft based on the first speed relationship and the second speed relationship; and calculating the third speed of the drive motor based on the second speed relationship and the speed of the input shaft.

[0180] In one optional implementation, the gear transmission information includes: information about the input planetary gear structure, which is used to drive the engine, generator, and input shaft; and a first calculation module 1102, specifically used to: calculate the gear ratio of the input planetary gear structure based on the information about the input planetary gear structure; and determine a first speed relationship based on the gear ratio.

[0181] In one optional implementation, the gear transmission information includes: information on the gear position structure, which is used to transmit power to the drive motor, the auxiliary power output device, and the input shaft; and a first calculation module 1102, specifically used to: obtain the gear transmission ratio value of the current gear based on the information on the gear position structure and the current gear; and determine the second speed relationship based on the gear transmission ratio value of the current gear.

[0182] In an optional implementation, the second calculation module 1103 is specifically configured to: acquire the external characteristic parameter of the engine, the external characteristic parameter of the generator, and the external characteristic parameter of the drive motor respectively; acquire the first peak torque of the engine, the second peak torque of the generator, and the third peak torque of the drive motor from the external characteristic parameter of the engine, the external characteristic parameter of the generator, and the external characteristic parameter of the drive motor respectively according to the first shaft speed, the second shaft speed, and the third shaft speed; calculate the first peak demand power of the engine according to the first shaft speed and the first peak torque; calculate the second peak demand power of the generator according to the second shaft speed and the second peak torque; calculate the third peak demand power of the drive motor according to the second shaft speed and the second peak torque; and calculate the initial peak demand power according to the first peak demand power, the second peak demand power, and the third peak demand power.

[0183] In an optional implementation, the correction module 1104 is specifically configured to: correct the initial peak demand power according to the current throttle opening to obtain a first corrected demand power; and correct the first corrected demand power according to the current road slope information and the current vehicle weight information to obtain the target demand power.

[0184] In an optional implementation, the correction module 1104 is further configured to: acquire a plurality of groups of historical data of the target hybrid vehicle, each group of historical data including historical road slope information, historical vehicle weight information, historical throttle opening, and historical initial peak demand power; correct the historical initial peak demand power according to the historical throttle opening to obtain historical first corrected demand power; perform polynomial fitting on the initial multi-cloud regression function with unknown slope influence factor and vehicle weight influence factor according to the historical road slope information, the historical vehicle weight information, and the corresponding historical first corrected demand power in the plurality of groups of historical data to obtain a target multi-cloud regression function with known slope influence factor and vehicle weight influence factor; and perform secondary correction by using the target multi-cloud regression function according to the current road slope information, the current vehicle weight information, and the first corrected demand power to obtain the target demand power.

[0185] It should be noted that details not disclosed in the vehicle demand power prediction device of the embodiments of the present application can refer to the details disclosed in the vehicle demand power prediction method of the embodiments of the present application, which will not be described here in detail.

[0186] The modules above can be one or more integrated circuits configured to implement the methods above, for example, one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors, or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, when a certain module above is implemented in the form of a processing element scheduling code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can invoke code. For another example, the modules can be integrated together in the form of a system-on-a-chip (SOC).

[0187] Optionally, the embodiments of the present application further provide a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is run by a processor, the processor executes the steps of the whole vehicle demand power prediction method of the mobile storage medium in the above embodiments. The specific implementation and technical effects are similar, and will not be repeated here.

[0188] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other means. For example, the apparatus embodiment described above is only illustrative, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0189] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0190] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software function unit.

[0191] The integrated unit implemented in the form of software function unit can be stored in a computer readable storage medium. The software function unit is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute part of steps of the method described in various embodiments of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.

[0192] The above merely provides preferred embodiments of the present application but not for limiting the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of predicting the power demand of a vehicle, characterized in that, The method comprises: obtaining the current gear of the target hybrid vehicle, the first shaft speed of the engine, the second shaft speed of the generator, the current throttle opening, the current road slope information and the current vehicle weight information; calculating the third shaft speed of the drive motor on the target hybrid vehicle according to the first shaft speed, the second shaft speed and the gear transmission information of the hybrid transmission on the target hybrid vehicle; calculating the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the drive motor; correcting the initial peak demand power according to the current throttle opening, the current road slope information and the current vehicle weight information to obtain the target demand power of the target hybrid vehicle, which is used for torque distribution of the engine, the generator and the drive motor; wherein the calculation of the initial peak demand power of the target hybrid vehicle according to the first shaft speed of the engine, the second shaft speed of the generator and the third shaft speed of the drive motor comprises: obtaining the external characteristic parameters of the engine, the external characteristic parameters of the generator and the external characteristic parameters of the drive motor respectively; obtaining the first peak torque of the engine, the second peak torque of the generator and the third peak torque of the drive motor from the external characteristic parameters of the engine, the external characteristic parameters of the generator and the external characteristic parameters of the drive motor respectively according to the first shaft speed, the second shaft speed and the third shaft speed; calculating the first peak demand power of the engine according to the first shaft speed and the first peak torque; calculating the second peak demand power of the generator according to the second shaft speed and the second peak torque; calculating the third peak demand power of the drive motor according to the third shaft speed and the third peak torque; calculating the initial peak demand power according to the first peak demand power, the second peak demand power and the third peak demand power.

2. The method of claim 1, wherein, The calculation of the third shaft speed of the drive motor according to the gear transmission information of the hybrid transmission on the target hybrid vehicle comprises: determining the first speed relationship of the input shaft in the engine, the generator and the hybrid transmission structure according to the gear transmission information; determining the second speed relationship of the input shaft and the drive motor in the current gear according to the gear transmission information and the current gear; calculating the speed of the input shaft according to the first shaft speed and the second shaft speed by using the first speed relationship; calculating the third shaft speed of the drive motor according to the speed of the input shaft by using the second speed relationship.

3. The method of claim 2, wherein, The gear transmission information comprises the information of the input planetary gear structure used for transmission connection of the engine, the generator and the input shaft. The determination of the first speed relationship of the input shaft in the engine, the generator and the hybrid transmission structure according to the gear transmission information comprises: According to the information of the input planetary gear structure, a gear transmission ratio of the input planetary gear structure is calculated; According to the gear transmission ratio, the first rotational speed relationship is determined.

4. The method of claim 2, wherein, The gear transmission information includes information of a gear structure of a gear position, which is used for transmission connection of the driving motor, an auxiliary power output device and the input shaft; According to the gear transmission information and the current gear position, the second rotational speed relationship between the input shaft and the driving motor in the current gear position is determined, including: According to the information of the gear structure of the gear position and the current gear position, a gear transmission ratio in the current gear position is obtained; According to the gear transmission ratio in the current gear position, the second rotational speed relationship is determined.

5. The method of claim 1, wherein, According to the current throttle opening degree, the current road slope information and the current vehicle weight information, the initial peak demand power is corrected to obtain a target demand power of the target hybrid vehicle, including: According to the current throttle opening degree, the initial peak demand power is corrected to obtain a first corrected demand power; According to the current road slope information and the current vehicle weight information, the first corrected demand power is secondly corrected to obtain the target demand power.

6. The method of claim 5, wherein, Before the first corrected demand power is secondly corrected to obtain the target demand power according to the current road slope information and the current vehicle weight information, the method further includes: A plurality of groups of historical data of the target hybrid vehicle are obtained, each group of historical data including historical road slope information, historical vehicle weight information, historical throttle opening degree and historical initial peak demand power; According to the historical throttle opening degree, the historical initial peak demand power is firstly corrected to obtain a historical first corrected demand power; According to the historical road slope information, the historical vehicle weight information and the corresponding historical first corrected demand power in the plurality of groups of historical data, an initial multi-cloud regression function with unknown slope influence factor and vehicle weight influence factor is polynomially fitted to obtain a target multi-cloud regression function with known slope influence factor and vehicle weight influence factor; According to the current road slope information, the current vehicle weight information and the first corrected demand power, the target multi-cloud regression function is adopted for second correction to obtain the target demand power.

7. A vehicle total demand power prediction device characterized by comprising: The device includes: An acquisition module is configured to acquire a current gear position of a target hybrid vehicle, a first shaft rotational speed of an engine, a second shaft rotational speed of a generator, a current throttle opening degree, current road slope information and current vehicle weight information; A first calculation module is configured to calculate a third shaft rotational speed of a driving motor on the target hybrid vehicle according to the first shaft rotational speed, the second shaft rotational speed and gear transmission information of a hybrid transmission on the target hybrid vehicle; A second calculation module is configured to calculate an initial peak demand power of the target hybrid vehicle according to the first shaft rotational speed of the engine, the second shaft rotational speed of the generator and the third shaft rotational speed of the driving motor; A correction module is configured to correct the initial peak demand power according to the current throttle opening, the current road slope information, and the current vehicle weight information, so as to obtain a target demand power of the target hybrid vehicle, and the target demand power is used for torque distribution of the engine, the generator, and the drive motor. The second calculation module is specifically configured to: acquire the external characteristic parameters of the engine, the external characteristic parameters of the generator, and the external characteristic parameters of the drive motor respectively; acquire the first peak torque of the engine, the second peak torque of the generator, and the third peak torque of the drive motor from the external characteristic parameters of the engine, the external characteristic parameters of the generator, and the external characteristic parameters of the drive motor respectively according to the first shaft speed, the second shaft speed, and the third shaft speed; calculate the first peak demand power of the engine according to the first shaft speed and the first peak torque; calculate the second peak demand power of the generator according to the second shaft speed and the second peak torque; calculate the third peak demand power of the drive motor according to the third shaft speed and the third peak torque; and calculate the initial peak demand power according to the first peak demand power, the second peak demand power, and the third peak demand power.

8. A vehicle control apparatus characterized by comprising: The computer program is stored in the memory and can be run on the processor. The computer program is stored in the memory and can be run on the processor.

9. A hybrid vehicle characterized by comprising: The vehicle control device, the engine, the generator, the drive motor, and the hybrid transmission are included. The vehicle control device is in communication connection with the engine, the generator, and the drive motor, and is configured to execute the method in any one of claims 1-6. The vehicle control device is in communication connection with the engine, the generator, and the drive motor, and is configured to execute the method in any one of claims 1-6.

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