Method and device for generating vehicle driving strategy information and electronic equipment

Abstract

The invention provides a vehicle driving strategy information generation method and device and electronic equipment, and relates to the technical field of vehicles. The method comprises the following steps: acquiring driving data of automatic variable-speed driving of a vehicle; extracting driving style information from the driving data; based on the driving style information, vehicle driving strategy information used for reducing energy consumption is generated for a plurality of driving styles corresponding to the driving style information, and the vehicle driving strategy information comprises power parameters of an execution vehicle. According to the method and the device, different vehicle driving strategy information is generated according to different driving styles through the driving style information, so that the power parameters in the strategy information are applied in the driving process to achieve an energy-saving effect.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle technology, and in particular to a method, device, and electronic device for generating vehicle driving strategy information. Background Art

[0002] The actual operating environment of commercial vehicles is complex and ever-changing. Even vehicles of the same type (for example, standard-load tractors equipped with the same engine model) face diverse challenges during operation, such as energy consumption. For example, the engine is the "source" of the vehicle's energy consumption chain. It converts the chemical energy of diesel / natural gas into mechanical energy from the crankshaft. The efficiency of this conversion directly determines how much fuel is burned per kilometer.

[0003] In related technologies, energy consumption is a difficult problem to solve due to the complex and ever-changing operating environment. This results in significant consistency and dispersion in the energy consumption performance of vehicles operating on the market, especially on national highways and in complex transportation. Summary of the Invention

[0004] In view of this, the purpose of the present disclosure is to propose a method, device and electronic device for generating vehicle driving strategy information, which can specifically solve existing problems.

[0005] Based on the above-mentioned purpose, in a first aspect, the present disclosure proposes a method for generating vehicle driving strategy information, including: obtaining driving data of a vehicle with automatic speed change; extracting driving style information from the driving data; based on the driving style information, generating vehicle driving strategy information for reducing energy consumption for multiple driving styles corresponding to the driving style information, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

[0006] In a second aspect, a device for generating vehicle driving strategy information is also provided, including: an acquisition unit configured to acquire driving data of a vehicle with automatic speed change; an extraction unit configured to extract driving style information from the driving data; and a generation unit configured to generate vehicle driving strategy information for reducing energy consumption for multiple driving styles corresponding to the driving style information based on the driving style information, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

[0007] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.

[0008] In a fourth aspect, a computer-readable storage medium is further provided, on which a computer program is stored, and the computer program is executed by a processor to implement any method described in the first aspect.

[0009] In a fifth aspect, a computer program product is also provided, comprising a computer program, wherein the computer program is executed by a processor to implement any one of the methods described in the first aspect.

[0010] In general, the present disclosure has at least the following beneficial effects: through driving style information, different vehicle driving strategy information is generated for different driving styles, so that the power parameters in the strategy information are applied during the driving process to save energy and improve fuel consumption consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present disclosure and should not be regarded as limiting the scope of the present disclosure.

[0012] Figure 1 A flow chart showing a method for generating vehicle driving strategy information according to an embodiment of the present disclosure is shown; Figure 2 Another flowchart of a method for generating vehicle driving strategy information according to an embodiment of the present disclosure is shown; Figure 3 A schematic diagram showing a device for generating vehicle driving strategy information according to an embodiment of the present disclosure is shown; Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure is shown; Figure 5 A schematic diagram of a storage medium provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0013] The present disclosure will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0014] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0015] Figure 1 The method for generating vehicle driving strategy information of the present disclosure is shown. In an embodiment of the present disclosure, the method includes: Step S101, obtaining driving data of a vehicle with automatic speed change.

[0016] Step S102: extracting driving style information from the driving data.

[0017] Step S103 : Based on the driving style information, for each of the plurality of driving styles corresponding to the driving style information, generating vehicle driving strategy information for reducing energy consumption, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

[0018] In this embodiment, there can be multiple driving styles, such as at least two driving styles divided according to the degree of urgency or slowness. Driving style is also known as driving habit.

[0019] Reducing energy consumption here is also called energy conservation, which can refer to saving various energy sources, such as oil, electricity, natural gas, etc.

[0020] The present disclosure generates different vehicle driving strategy information for different driving styles through driving style information, thereby realizing the application of power parameters in the strategy information during driving to achieve energy saving and improve fuel consumption consistency.

[0021] In some optional implementations of any embodiment of the present disclosure, if the vehicle has an engine, the power parameters include engine-related parameters; the vehicle driving strategy information includes transient correction strategy information and collaborative correction strategy information; the transient correction strategy information indicates that during vehicle driving, a first parameter among the engine-related parameters is transiently corrected according to the current driving style; the collaborative correction strategy information indicates that a second parameter among the engine-related parameters is corrected according to the current driving style, and the second parameter includes a parameter for transient correction and a parameter for calibration correction.

[0022] The current development process typically involves conducting on-vehicle validation for a specific vehicle model and driver after the engine is finalized. This approach fails to fully account for the impact of varying driving styles on engine transient performance and vehicle fuel consumption, resulting in insufficient optimization of the engine's transient response and difficulty meeting market demand for overall vehicle fuel consumption and consistency. Furthermore, because the development process fails to fully account for the diversity of driving styles, engine and AMT calibration often requires multiple optimization adjustments based on market performance. This not only prolongs the development cycle, but also wastes resources and increases development costs.

[0023] This proposal proposes an AMT vehicle optimization method and system, develops engine transient correction strategy information based on different driving styles and AMT collaborative correction strategy information based on different driving styles, so as to improve the consistency of vehicle fuel consumption while shortening the AMT vehicle development cycle.

[0024] AMT: Automated Mechanical Transmission is an improvement on the traditional manual gear transmission. It combines the advantages of automatic transmission and manual transmission to realize the automation of the gear shifting process. AMT maintains the basic structure of the original mechanical transmission and controls a robotic system by adding a microcomputer control to complete the two actions of operating the clutch and selecting gears. It has the advantages of low cost, high transmission efficiency and simple structure.

[0025] The first parameter may include an engine combustion parameter, which may include: an advance angle, a pre-injection amount, a rail pressure, an EGR valve, and an intake throttle valve.

[0026] A new transient correction strategy based on different driving styles has been added to the engine ECU to dynamically adjust various combustion parameters and valve opening control.

[0027] In some optional implementations of any embodiment of the present disclosure, the second parameter corresponding to the collaborative correction strategy information includes the dynamic adjustment coefficient of the engine external characteristics, the dynamic adjustment coefficient of both the ECU original exhaust real-time calculation parameters and the margin, and the throttle filter, the throttle MAP adjustment coefficient, the smoke limit calibration parameter and the fan thermal management calibration parameter; based on the driving style information, for multiple driving styles corresponding to the driving style information, the vehicle driving strategy information for reducing energy consumption is generated respectively, including: based on the driving style information, the AMT vehicle weight, slope and gear signal, generating the dynamic adjustment coefficient of the engine external characteristics; based on the driving style information and road spectrum information, generating the dynamic adjustment coefficient of both the ECU original exhaust real-time calculation parameters and the margin; based on the driving style information, generating the throttle filter, the throttle MAP adjustment coefficient, the smoke limit calibration parameter and the fan thermal management calibration parameter.

[0028] A new AMT collaborative correction strategy based on different driving habits has been added to the engine ECU, which takes driving needs into consideration while improving fuel consumption consistency.

[0029] In some optional implementations of any embodiment of the present disclosure, the multiple driving styles are divided according to the degree of driving urgency; and the vehicle driving strategy information for reducing energy consumption is generated for each of the multiple driving styles corresponding to the driving style information, including: for a first driving style, a second driving style, and a third driving style corresponding to the driving style information, the vehicle driving strategy information for reducing energy consumption is generated, respectively, wherein the first driving style, the second driving style, and the third driving style are arranged in order from urgency to slowness.

[0030] The plurality of driving styles may include a first driving style, a second driving style, and a third driving style.

[0031] In some optional implementations of any embodiment of the present disclosure, the method further includes: inputting the driving style information into an engine-in-the-loop platform; and generating, based on the driving style information, vehicle driving strategy information for reducing energy consumption for each of the multiple driving styles corresponding to the driving style information, including: on the engine-in-the-loop platform, based on the driving style information, generating, for each of the multiple driving styles corresponding to the driving style information, vehicle driving strategy information for reducing energy consumption.

[0032] In some optional implementations of any embodiment of the present disclosure, the method further includes: extracting road spectrum information and environmental information from the driving data, inputting the road spectrum information and the environmental information into the engine-in-the-loop platform, the road spectrum information including a road spectrum curve, and the road spectrum curve is used to indicate the correspondence between vehicle speed and slope and time respectively; and using the road spectrum information and the environmental information, performing a fuel consumption test on the vehicle driving strategy information on the engine-in-the-loop platform.

[0033] During the engine development phase, these implementation methods utilize EIL to verify and calibrate relevant strategy information, thereby improving the consistency of vehicle fuel consumption while shortening the AMT vehicle development cycle.

[0034] EIL: Engine-in-the-Loop, short for Engine-in-the-Loop, is a method of evaluating the entire vehicle through vehicle transmission and cooling model simulation combined with engine hardware. It generally includes a real engine, controller, post-processing and other hardware.

[0035] These implementations introduce EIL platform-based calibration and test verification during the engine development phase, breaking the limitations of the traditional development process that separates the engine from the vehicle and reducing repeated optimization. This shortens the development cycle and reduces development costs. Furthermore, it improves the consistency of fuel consumption across different driving habits, increasing user satisfaction.

[0036] In some optional implementations of any embodiment of the present disclosure, the driving style information includes: drive control parameters, shift control parameters and braking control parameters; the drive control parameters include at least one of the following: vehicle speed following PID, drive force feedforward MAP, throttle pedal MAP and throttle change rate limit; the shift control parameters include at least one of the following: upshift MAP, downshift MAP and skip shift MAP associated with throttle opening and gear position; the braking control parameters include at least one of the following: brake pedal opening during full braking, deceleration during full braking, brake opening-braking force curve, and brake response time.

[0037] Among them, MAP is the manifold absolute pressure.

[0038] These implementation methods can build a new driver model unit in the EIL platform software model, set three sub-modules of throttle, gear shifting, and braking, and multiple characteristic parameters, to simulate and switch different driving habits, thereby improving the coverage of driving habits.

[0039] Figure 2 The method for generating vehicle driving strategy information according to an embodiment of the present disclosure is shown. Figure 2 As shown, this method for generating vehicle driving strategy information is an AMT vehicle optimization method and system based on the EIL (Engine-in-the-Loop) platform. It develops transient engine correction strategy information based on different driving styles and AMT collaborative correction strategy information based on different driving styles. Furthermore, during the engine development phase, EIL is used to verify and optimize the calibration of relevant strategy information, thereby improving vehicle fuel consumption consistency and shortening the AMT vehicle development cycle. The specific steps are as follows: 1. Extraction of Typical Road Spectra and Different Driving Styles During the engine development phase, the target sales regions and specific application scenarios for AMT-equipped vehicles are first determined, such as nationwide trunk haulage. Next, for this specific scenario, batch data on vehicles matching engines with the same or similar horsepower is extracted through big data or cloud platforms, representing the aforementioned driving data. Then, through cluster analysis and feature extraction, a variety of typical road profiles (e.g., east-west horizontal highways and mountain highways, north-south vertical highways, and southwest expressways from the east to the mountainous areas of Yunnan, Guizhou, and Sichuan) and various driver styles are obtained. These profiles are then mapped to speed-slope versus time, along with characteristic value combinations for various driving styles, including throttle position, throttle change rate, speed-acceleration curves, shift patterns, braking force based on speed and slope, braking percentage, and duration. The braking percentage refers to the percentage of time the brake is applied.

[0040] 2. Introducing Roadmap and Driving Style into the EIL Platform The EIL platform's host computer software model incorporates a driver model unit capable of simulating and switching between different driving styles. Multiple sets of adjustable parameters are configured within the driver model unit to define different driving behavior characteristics. Drive control includes parameters such as the vehicle speed following PID, drive force feedforward map, throttle pedal map, and throttle rate limit. Shift control includes parameters such as upshift, downshift, and skip maps based on throttle position and gear position. Braking control includes parameters such as brake pedal position during full braking, deceleration during full braking, brake position-braking force curve, and brake response time. By adjusting these parameter combinations, the system can simulate typical driving styles, including aggressive (sporty mode, also known as the first driving style), smooth (comfort mode, also known as the second driving style), and economical (economy mode, also known as the third driving style). A driving style status flag (using a 0-2 integer value) enables real-time recognition and switching between modes. Aggressive drivers tend to accelerate and brake frequently, which can increase fuel consumption because the engine requires more power. A smooth driver is more gentle, accelerating and decelerating gently, which may improve fuel efficiency. An economical driver may also proactively adjust their driving style, such as slowing down early and reducing braking to save fuel. This allows for the simulation and integration of various driving styles in real vehicles into the EIL platform.

[0041] In the EIL platform's host software model, the multiple speed-slope road profile curves extracted in step 1 are sequentially imported into the road profile input module. This allows the simulation and import of multiple typical road profiles in real-world application scenarios into the EIL platform.

[0042] 3. Development of engine transient and AMT collaborative correction strategy information based on different driving styles The engine ECU has added transient correction strategy information based on different driving styles. According to the different driving mode signals (also known as driving style signals) sent by the vehicle CAN bus or the different driving style status identification flag signals simulated by the driver model unit in the EIL host computer software, the ECU adjusts and switches the combustion parameters of the engine transient correction based on different driving styles, including correction calibration of advance angle, pre-injection amount, rail pressure, EGR valve, intake throttle valve, etc., to meet the driver's power needs while optimizing fuel efficiency.

[0043] New AMT collaborative correction strategy information based on different driving styles has been added to the engine ECU, including adjustment of the engine external characteristic dynamic coefficient based on driving style, AMT vehicle weight, slope, and gear signal; dynamic adjustment of the ECU original exhaust real-time calculation and margin coefficient based on road conditions and driving style; adjustment of throttle filtering and throttle MAP coefficient based on driving style; adjustment of the smoke limit calibration parameter adjustment coefficient based on driving style; adjustment of the fan thermal management calibration parameter adjustment coefficient based on driving style, etc.

[0044] After completing strategy development, the relevant logic functions are verified and optimized on the EIL platform. By developing ECU-related control strategy information, the engine and transmission can dynamically adjust based on factors such as driving style and real-time road conditions (i.e., road spectrum information), improving fuel consumption consistency and reducing fuel consumption variations caused by driving variability.

[0045] 4. Calibration and fuel consumption testing based on the EIL platform On the EIL platform, a virtual vehicle model is constructed, integrating driver behavior, road conditions, and environmental parameters to achieve a fully closed-loop simulation environment encompassing driving style-operation coupling. Based on driving style state indicators (0: Aggressive / Sport Mode, 1: Smooth / Comfort Mode, 2: Economy / Energy Saving Mode), systematic adaptive calibration of engine transient control strategy information and AMT collaborative control strategy information based on different driving styles is performed. Dynamic coupling analysis of key parameters such as throttle, shifting, braking, engine combustion, and valve control under different driving styles allows for precise adjustment of engine transient correction factors and collaborative control correction factors. This significantly improves the controllability of vehicle energy flow, enhances engine and transmission matching accuracy under transient conditions, and reduces vehicle fuel consumption dissipation by over 10%. If the vehicle fuel consumption test meets the consistency target, the software strategy information and calibration data are consolidated. Otherwise, the strategy information and calibration are continuously optimized until the consistency target is met.

[0046] This proposal uses the EIL platform to quantitatively analyze the impact of different driving styles on energy consumption, forming a forward-iterative dual-path energy-saving strategy of "hardware calibration optimization-driving behavior guidance", ultimately achieving the dual engineering goals of improving energy efficiency and improving fuel consumption consistency among market vehicles.

[0047] The embodiment of the present disclosure provides a device for generating vehicle driving strategy information, which is used to execute the method for generating vehicle driving strategy information described in the above embodiment, such as Figure 3 As shown, the device 300 includes: an acquisition unit 301, configured to acquire driving data of a vehicle with automatic gear shifting; an extraction unit 302, configured to extract driving style information from the driving data; and a generation unit 303, configured to generate vehicle driving strategy information for reducing energy consumption for a plurality of driving styles corresponding to the driving style information based on the driving style information, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

[0048] The device for generating vehicle driving strategy information provided in the above-mentioned embodiment of the present disclosure and the method for generating vehicle driving strategy information provided in the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0049] The embodiments of the present disclosure further provide an electronic device corresponding to the method for generating vehicle driving strategy information provided in the aforementioned embodiments, so as to execute the aforementioned method for generating vehicle driving strategy information.

[0050] Please refer to Figure 4 , which shows a schematic diagram of an electronic device provided by some embodiments of the present disclosure. Figure 4 As shown, the electronic device 40 includes: a processor 400, a memory 401, a bus 402 and a communication interface 403, and the processor 400, the communication interface 403 and the memory 401 are connected via the bus 402; the memory 401 stores a computer program that can be run on the processor 400, and when the processor 400 runs the computer program, it executes the method provided in any of the aforementioned embodiments of the present disclosure.

[0051] Memory 401 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between the system network element and at least one other network element is achieved through at least one communication interface 403 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0052] Bus 402 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. Memory 401 is used to store programs, and processor 400 executes the programs upon receiving execution instructions. The method for generating vehicle driving strategy information disclosed in any of the aforementioned embodiments of the present disclosure may be applied to or implemented by processor 400.

[0053] The processor 400 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method may be completed by hardware integrated logic circuits or software instructions in the processor 400. The processor 400 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure may be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 401 , and the processor 400 reads the information in the memory 401 and completes the steps of the above method in combination with its hardware.

[0054] The electronic device provided by the embodiment of the present disclosure and the method for generating vehicle driving strategy information provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented by them.

[0055] The present disclosure also provides a computer-readable storage medium corresponding to the method for generating vehicle driving strategy information provided in the above embodiment. Figure 5 The computer-readable storage medium shown is a CD 50 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, the method for generating vehicle driving strategy information provided by any of the aforementioned embodiments will be executed.

[0056] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0057] The computer-readable storage medium provided by the above-mentioned embodiments of the present disclosure and the method for generating vehicle driving strategy information provided by the embodiments of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0058] It should be noted that: In the above text, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present disclosure is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0059] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, hardware can also be used, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the existing technology, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present disclosure.

[0060] The embodiments of the present disclosure are described above in conjunction with the accompanying drawings, which are only specific implementation methods of the present disclosure. However, the present disclosure is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present disclosure, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present disclosure and the claims, which are all within the protection of the present disclosure.

Claims

1. A method for generating vehicle driving strategy information, characterized in that: include: Acquiring driving data of a vehicle with automatic speed change; extracting driving style information from the driving data; Based on the driving style information, vehicle driving strategy information for reducing energy consumption is generated for each of the plurality of driving styles corresponding to the driving style information, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

2. The method according to claim 1, characterized in that If the vehicle has an engine, the power parameters include engine-related parameters, and the vehicle driving strategy information includes transient correction strategy information and coordinated correction strategy information; The transient correction strategy information indicates that during vehicle driving, a transient correction is performed on a first parameter among the engine-related parameters according to a current driving style; The coordinated correction strategy information indicates that a second parameter among the engine-related parameters is corrected according to the current driving style, where the second parameter includes a parameter for transient correction and a parameter for calibration correction.

3. The method according to claim 2, characterized in that The second parameters corresponding to the coordinated correction strategy information include a dynamic adjustment coefficient of the engine external characteristics, a dynamic adjustment coefficient of both the ECU original exhaust real-time calculation parameter and the margin, a throttle filter, a throttle MAP adjustment coefficient, a smoke limit calibration parameter, and a fan thermal management calibration parameter; The generating, based on the driving style information, vehicle driving strategy information for reducing energy consumption for each of the plurality of driving styles corresponding to the driving style information, includes: generating a dynamic adjustment coefficient for an engine external characteristic based on the driving style information, the AMT vehicle weight, the slope, and the gear position signal; Based on the driving style information and the road spectrum information, a dynamic adjustment coefficient of both the ECU original exhaust real-time calculation parameter and the margin is generated; Based on the driving style information, a throttle filter, a throttle MAP adjustment coefficient, a smoke limit calibration parameter, and a fan thermal management calibration parameter are generated.

4. The method according to claim 1, wherein The multiple driving styles are divided according to the degree of driving urgency; The generating of vehicle driving strategy information for reducing energy consumption for each of the plurality of driving styles corresponding to the driving style information includes: For a first driving style, a second driving style, and a third driving style corresponding to the driving style information, vehicle driving strategy information for reducing energy consumption is generated respectively, wherein the first driving style, the second driving style, and the third driving style are arranged in order from fast to slow.

5. The method according to claim 1, wherein The method further includes: inputting the driving style information into an engine-in-the-loop platform; The generating, based on the driving style information, vehicle driving strategy information for reducing energy consumption for each of the plurality of driving styles corresponding to the driving style information, includes: On the engine-in-the-loop platform, based on the driving style information, vehicle driving strategy information for reducing energy consumption is generated for each of the plurality of driving styles corresponding to the driving style information.

6. The method according to claim 1, characterized in that The method further comprises: Extracting road spectrum information and environmental information from the driving data, and inputting the road spectrum information and environmental information into an engine-in-the-loop platform, wherein the road spectrum information includes a road spectrum curve, and the road spectrum curve is used to indicate the corresponding relationship between vehicle speed and slope and time; The vehicle driving strategy information is tested for fuel consumption on the engine-in-the-loop platform using the road spectrum information and the environmental information.

7. The method according to claim 1, characterized in that The driving style information includes: Driving control parameters, gear shifting control parameters and braking control parameters; The driving control parameters include at least one of the following: vehicle speed following PID, driving force feedforward MAP, accelerator pedal MAP and throttle change rate limit; The shift control parameter includes at least one of the following: an upshift MAP, a downshift MAP, and a skip shift MAP associated with the throttle opening and the gear position; The braking control parameter includes at least one of the following: brake pedal opening during full braking, deceleration during full braking, brake opening-braking force curve, and brake response time.

8. The method according to claim 1, characterized in that Transient correction strategy information for different driving styles is stored in an engine electronic control unit (ECU) of the vehicle. The method further includes: If the ECU receives a signal indicating a driving style, the engine-related parameters of the vehicle driving strategy information corresponding to the driving style are used for the current driving. The sender of the signal is the CAN bus of the vehicle or the driver model unit of the host computer software in the engine-in-the-loop platform.

9. A device for generating vehicle driving strategy information, characterized in that: include: an acquisition unit configured to acquire driving data of the vehicle during automatic speed change; an extraction unit configured to extract driving style information from the driving data; The generating unit is configured to generate vehicle driving strategy information for reducing energy consumption for each of a plurality of driving styles corresponding to the driving style information based on the driving style information, wherein the vehicle driving strategy information includes power parameters for executing the vehicle.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor runs the computer program to implement the method according to any one of claims 1 to 8.

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