Vehicle control method and device, equipment, storage medium, product and vehicle

Abstract

The invention provides a vehicle control method, device and equipment, a storage medium, a product and a vehicle wherein the vehicle control method comprises: obtaining a vehicle weight and a driving environment, the driving environment comprising a gradient; according to the vehicle weight and the driving environment, a power adjustment coefficient is determined, and the power adjustment coefficient represents the stepless adjustment degree among a plurality of driving modes of the vehicle; and determining a target control strategy of the vehicle according to the power adjustment coefficient, and performing power control on the vehicle according to the target control strategy. According to the method, stepless adjustment among the control strategies corresponding to the multiple driving modes of the vehicle can be automatically achieved according to the real-time vehicle weight and the driving environment, and consideration of the dynamic property and the economical efficiency is achieved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle control method, device, equipment, storage medium, product and vehicle. Background Art

[0002] With the continuous development of vehicle technology and the improvement of intelligence level, vehicle control systems are gradually evolving towards a more sophisticated and intelligent direction. Traditional vehicle control systems often rely on different driving modes, such as economic mode, sports mode, etc. Each driving mode is set with a fixed control strategy. The driver manually switches the driving mode according to actual needs to achieve different power performance.

[0003] However, the driving environment of vehicles is often complex and changeable, and the manual switching of driving modes in traditional solutions cannot fully balance the performance of vehicle power and economy. Especially when facing complex road conditions, such as sections that require frequent uphill and downhill driving, the driving mode needs to be adjusted frequently to adapt to changing road conditions. In this case, the power output is easily too large or too small, and it is difficult to accurately adapt to the actual working conditions, which has a negative impact on the performance of the vehicle and also reduces the driving experience. Summary of the invention

[0004] In view of this, the embodiments of the present application are committed to providing a vehicle control method, device, equipment, storage medium, product and vehicle, which can automatically achieve infinite adjustment between the control strategies corresponding to multiple driving modes of the vehicle according to the real-time vehicle weight and driving environment, so as to achieve a balance between power and economy.

[0005] According to a first aspect of an embodiment of the present application, a vehicle control method is provided, comprising:

[0006] Acquiring the vehicle weight and driving environment of the vehicle, wherein the driving environment includes a slope;

[0007] Determining a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between a plurality of driving modes of the vehicle;

[0008] A target control strategy for the vehicle is determined according to the power adjustment coefficient, and power control of the vehicle is performed according to the target control strategy.

[0009] Optionally, determining the power adjustment coefficient according to the vehicle weight and the driving environment includes:

[0010] A power adjustment coefficient is determined according to the vehicle weight, the driving environment and a preset first mapping relationship, wherein the first mapping relationship includes a correspondence between a first data set and the power adjustment coefficient, and the first data set includes the vehicle weight and the vehicle driving environment.

[0011] Optionally, determining the target control strategy of the vehicle according to the power adjustment coefficient includes:

[0012] According to the power adjustment coefficient and the control strategies corresponding to each driving mode, a target control strategy of the vehicle is determined, wherein the control strategy includes an accelerator pedal power request strategy and / or a gear shift speed strategy.

[0013] Optionally, determining the target control strategy of the vehicle according to the power adjustment coefficient and the control strategies corresponding to each driving mode includes:

[0014] Determining a vehicle control parameter corresponding to the current state information in each driving mode according to the current state information of the vehicle and the control strategies corresponding to each driving mode;

[0015] Determining a target control parameter of the vehicle according to the power adjustment coefficient and a vehicle control parameter corresponding to the current state information in each driving mode;

[0016] The performing power control on the vehicle according to the target control strategy includes:

[0017] The vehicle is controlled according to the target control parameter.

[0018] Optionally, determining the power adjustment coefficient according to the vehicle weight and the driving environment includes:

[0019] Determining a power adjustment coefficient corresponding to each of a plurality of power modules according to the vehicle weight and the driving environment, wherein the power modules include an accelerator pedal module and / or a gear adjustment module;

[0020] Determining the target control strategy of the vehicle according to the power adjustment coefficient and the control strategies corresponding to each driving mode includes:

[0021] According to the power adjustment coefficient corresponding to the first power module and the control strategies corresponding to the first power module in each driving mode, the target control strategy corresponding to the first power module is determined.

[0022] Optionally, the method further includes:

[0023] Acquire a first slope within a preset distance in front of the vehicle;

[0024] determining a first power adjustment coefficient according to the vehicle weight and the first slope;

[0025] When the difference between the first power adjustment coefficient and the current power adjustment coefficient is greater than a preset difference threshold, a first control strategy of the vehicle is determined according to the first power adjustment coefficient, and power control of the vehicle is performed according to the first control strategy.

[0026] Optionally, performing power control on the vehicle according to the first control strategy includes:

[0027] Determining, according to the current state information of the vehicle, a first control parameter of the vehicle by the first control strategy and a second control parameter of the vehicle by the current control strategy;

[0028] The control parameter for power control of the vehicle is changed from a first control parameter to a second control parameter according to a preset parameter change rate.

[0029] According to a second aspect of an embodiment of the present application, a vehicle control device is provided, comprising:

[0030] The first unit is used to obtain the vehicle weight and driving environment of the vehicle, wherein the driving environment includes a slope;

[0031] A second unit is used to determine a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between multiple driving modes of the vehicle;

[0032] The third unit is used to determine a target control strategy for the vehicle according to the power adjustment coefficient, and perform power control on the vehicle according to the target control strategy.

[0033] According to a third aspect of an embodiment of the present application, there is provided an electronic device, including a memory and a processor;

[0034] The memory is connected to the processor and is used to store programs;

[0035] The processor is used to implement the vehicle control method as described in any one of the first aspects of the embodiments of the present application by running the program in the memory.

[0036] According to a fourth aspect of an embodiment of the present application, a storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the vehicle control method as described in any one of the first aspects of the embodiment of the present application is implemented.

[0037] According to a fifth aspect of an embodiment of the present application, a computer program product is provided, comprising computer program instructions, which, when executed by a processor, enable the processor to implement a vehicle control method as described in any one of the first aspects of the embodiments of the present application.

[0038] According to a sixth aspect of an embodiment of the present application, a vehicle is provided, comprising: the electronic device as described in the third aspect of the embodiment of the present application.

[0039] The vehicle control method proposed in the present application first obtains the vehicle weight and the driving environment of the vehicle, wherein the driving environment includes the slope; then, according to the vehicle weight and the driving environment, a power adjustment coefficient is determined, wherein the power adjustment coefficient represents the degree of infinite adjustment between multiple driving modes of the vehicle; finally, the target control strategy of the vehicle is determined according to the power adjustment coefficient, and the vehicle is power-controlled according to the target control strategy. On the one hand, the present application no longer relies on the driver to manually switch the driving mode, but automatically adjusts the power output according to the real-time vehicle weight and the driving environment, thereby reducing the burden on the driver and significantly improving the driving experience; on the other hand, the present application introduces the power adjustment coefficient, realizes the infinite adjustment between multiple driving modes of the vehicle, automatically determines the power adjustment coefficient according to the real-time vehicle weight and the driving environment, and controls the vehicle according to the power adjustment coefficient, which can realize the infinite adjustment of power output according to the real-time driving conditions, avoiding the situation of excessive or insufficient power, thereby ensuring the vehicle's power while also improving the economy, achieving a balance between power and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0041] Figure 1 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application.

[0042] Figure 2 A flow chart of a vehicle control method provided in an embodiment of the present application.

[0043] Figure 3 A flowchart of a vehicle control method provided in accordance with another embodiment of the present application.

[0044] Figure 4 A flowchart of a vehicle control method provided in accordance with another embodiment of the present application.

[0045] Figure 5 A schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application.

[0046] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The technical solution of the embodiment of the present application is suitable for use in various scenarios where power control of the vehicle is required, especially in scenarios where fine power control of the vehicle is required, such as driving on complex road conditions, driving on rugged mountain roads, etc. In these scenarios, the vehicle often needs to go uphill, downhill or on roads with different slopes, which puts higher requirements on the vehicle's power, economy and driving experience. The technical solution of the embodiment of the present application can determine the power adjustment coefficient in real time based on the vehicle weight and driving environment (especially slope information), and realize infinite adjustment between multiple driving modes of the vehicle, thereby accurately controlling the vehicle's power output, making it more adaptable to complex and changeable driving environments, and achieving a balance between vehicle economy and power.

[0048] The technical solution provided in the embodiments of the present application can be exemplarily applied to hardware devices such as processors, electronic devices, servers (including cloud servers), or packaged into software programs to be run. When the hardware device executes the processing of the technical solution of the embodiments of the present application, or the above-mentioned software program is run, the automatic splitting of the target task and the automatic calling of the application program interface required for the task can be achieved to complete the purpose of the target task. The embodiments of the present application only exemplarily introduce the specific processing of the technical solution of the present application, and do not limit the specific implementation form of the technical solution of the present application. Any technical implementation form that can execute the processing of the technical solution of the present application can be adopted by the embodiments of the present application.

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] Before introducing this application solution, the relevant technologies are first introduced:

[0051] With the continuous development of vehicle technology and the improvement of intelligence level, vehicle control systems are gradually evolving towards a more sophisticated and intelligent direction. Traditional vehicle control systems often rely on different driving modes, such as economic mode, sports mode, etc. Each driving mode is set with a fixed control strategy. The driver manually switches the driving mode according to actual needs to achieve different power performance.

[0052] However, the driving environment of vehicles is often complex and changeable, and the manual switching of driving modes in traditional solutions cannot fully balance the performance of vehicle power and economy. Especially when facing complex road conditions, such as sections that require frequent uphill and downhill driving, the driving mode needs to be adjusted frequently to adapt to changing road conditions. In this case, the power output is easily too large or too small, and it is difficult to accurately adapt to the actual working conditions, which has a negative impact on the performance of the vehicle and also reduces the driving experience.

[0053] In view of this, the embodiments of the present application are committed to providing a vehicle control method, device, equipment, storage medium, product and vehicle, which can automatically achieve infinite adjustment between the control strategies corresponding to multiple driving modes of the vehicle according to the real-time vehicle weight and driving environment, so as to achieve a balance between power and economy.

[0054] Example Vehicles

[0055] For ease of understanding, firstly, an exemplary introduction to the implementation environment of the vehicle control method provided in the embodiment of the present application is given. Figure 1 , Figure 1 Schematic diagram of the structure of a vehicle, the vehicle control method provided in the present application can be exemplarily applied to the vehicle.

[0056] like Figure 1 As shown, vehicle 100 includes a vehicle control device 110 .

[0057] The vehicle 100 is provided with all the basic structures required for the normal operation of the vehicle.

[0058] Optionally, the vehicle 100 is also provided with a weight detection device that is communicatively connected to the vehicle control device 110 , and the weight detection device is used to detect the vehicle weight in real time or intermittently and send it to the vehicle control device 110 .

[0059] Optionally, the vehicle is also provided with environmental detection devices corresponding to different environmental factors respectively connected to the vehicle control device 110 for communication, and the environmental detection devices are used to obtain environmental information around the vehicle in real time and send it to the vehicle control device 110, wherein the environmental information includes slope information.

[0060] Optionally, the vehicle is also provided with an information receiving device, which can be used to receive environmental information sent by an external device in real time.

[0061] It should be noted that the types, number and location of weight detection equipment, environmental detection equipment and information receiving equipment are all determined based on actual conditions, and this application does not impose any restrictions on this.

[0062] The vehicle control device 110 includes a memory and a processor, and the memory is connected to the processor. The memory is used to store programs. The processor is used to execute the vehicle control method provided in the embodiment of the present application. Specifically, the vehicle weight and the driving environment are first obtained, and then the power adjustment coefficient representing the degree of infinite adjustment between multiple driving modes of the vehicle is determined according to the vehicle weight and the driving environment, and finally the vehicle is power-controlled according to the power adjustment coefficient. As for other specific implementations of the vehicle control method, they will be specifically expanded in the subsequent content and will not be described in detail here.

[0063] It should be noted that the vehicle control device 110 can be various types of processing devices, can be a separately set processor, or can be integrated on other controllers, such as a vehicle controller, etc. The specific type of the vehicle control device 110 is determined according to the application scenario and performance requirements, and this application does not limit this.

[0064] It should be noted that the communication connection may be a wireless communication connection or a wired communication connection or any combination thereof, and may be a direct communication connection or an indirect communication connection or any combination thereof, and this application does not limit this.

[0065] Exemplary Methods

[0066] Figure 2 A flow chart of a vehicle control method provided in an embodiment of the present application. Figure 2 As shown, the vehicle control method can be exemplarily applied to Figure 1 The method comprises steps S201-S203:

[0067] S201. Obtain vehicle weight and driving environment of the vehicle, where the driving environment includes a slope.

[0068] The vehicle weight can be understood as the weight of the vehicle. Optionally, the vehicle weight can be the total weight of the vehicle, including the weight of the vehicle itself and the weight of the items and passengers on board. Optionally, the vehicle weight can be the weight of the vehicle when it is unloaded, that is, the weight of the vehicle itself.

[0069] Optionally, the vehicle is provided with a weight detection device (such as a weight sensor, a suspension system compression detection device, etc.), which can directly or indirectly detect the vehicle weight information, and send the detected real-time vehicle weight information to the vehicle control device, and the vehicle control device can obtain the real-time vehicle weight. Optionally, the pre-set and stored weight of the vehicle when unloaded can be determined as the vehicle weight at each moment. Optionally, the current vehicle weight is calculated based on the information input by the user (such as the number of passengers and the weight of the cargo) and the pre-set and stored weight of the vehicle when unloaded.

[0070] The driving environment can be understood as the external environmental conditions in which the vehicle is traveling, and may include slope information, road conditions (such as slippery, muddy, sandy, etc.), weather conditions (such as rain, snow, fog, etc.) and other environmental factors that directly or indirectly affect the vehicle's power requirements, which are not limited in this application. The driving environment at least includes slope information.

[0071] The driving environment may be acquired through a variety of sensors built into the vehicle (such as a road surface humidity sensor, a camera, a radar, etc.) and / or external data sources (such as a weather forecast, a traffic information system, etc.).

[0072] Optionally, the vehicle is equipped with detection equipment corresponding to each environmental factor, such as using wheel speed sensors, acceleration sensors, etc. to sense the slip rate and vibration frequency of the road surface, so as to judge the road condition, such as using temperature sensors, humidity sensors and raindrop sensors outside the vehicle to detect weather conditions, etc.

[0073] Optionally, the road slope is estimated using an acceleration sensor, gyroscope or GPS data. Optionally, the vehicle is equipped with a laser radar, a depth camera and other equipment, which can scan the scene information in front of the vehicle to obtain the road slope information in front of the vehicle. Optionally, the vehicle's high-precision navigation system is used to obtain real-time road slope information.

[0074] S202: Determine a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between a plurality of driving modes of the vehicle.

[0075] The power adjustment coefficient can be understood as a numerical parameter, which is used to quantify the degree of infinite adjustment of the vehicle between multiple driving modes. It is calculated based on the vehicle weight and driving environment information obtained in real time through a certain algorithm or rule, and is used to guide the control strategy of the vehicle power system to achieve precise adjustment of power output. The "infinite adjustment degree" here specifically refers to the smooth transition and continuous adjustability of power output between driving modes, rather than the traditional jump-type switching between fixed gears or preset modes. The power adjustment coefficient can be regarded as a "regulator" used to smoothly transition between multiple driving modes of the vehicle and dynamically adjust the vehicle's control strategy to adapt to the power requirements under different driving conditions. The power adjustment coefficient is not a fixed value, but changes dynamically with changes in vehicle weight and / or driving environment.

[0076] Specifically, the power adjustment coefficient can be a dimensionless value, a percentage or other quantitative indicators. The specific form and value range of the power adjustment coefficient depend on the design and implementation of the vehicle control system in actual applications.

[0077] Exemplarily, the vehicle has two basic driving modes, a sports mode and an economic mode, and each driving mode has its corresponding control strategy. In the sports mode, the vehicle tends to provide higher power output and faster acceleration response to meet the driver's needs for speed and performance. In this mode, the vehicle's throttle response is more sensitive, and the shift point may be delayed to obtain a higher speed and power output. In the economic mode, the vehicle pays more attention to fuel economy, and achieves the purpose of saving fuel by reducing power output, optimizing shift logic, and reducing unnecessary energy consumption. In this mode, the vehicle's throttle response may be smoother, and the shift point may be advanced to reduce the load on the engine. In this example, the power adjustment coefficient is a value ranging from 0 to 1, representing the degree to which the power control strategy required by the vehicle is more inclined to the economic mode. When the power adjustment coefficient is closer to 0, it means that the power control strategy of the vehicle is more inclined to the economic mode. On the contrary, when the power adjustment coefficient is closer to 1, it means that the power control strategy of the vehicle is closer to the sports mode. Because the power adjustment coefficient can take any continuous value between 0 and 1, the vehicle's power control strategy can achieve infinite adjustment between economic mode and sports mode, with continuous and smooth transition.

[0078] Furthermore, vehicle weight and driving environment are important factors that affect the power demand of the vehicle. The difference in vehicle weight directly reflects the change in vehicle load, which will affect the power demand of the vehicle. For example, heavier vehicles usually require more power to overcome inertia, which usually corresponds to a greater power demand. The driving environment, especially the slope information, will also affect the power demand of the vehicle. For example, when going uphill, the greater the slope value, the more power the vehicle usually needs to overcome gravity, which usually corresponds to a greater power demand. Optionally, when the slope value is positive, it means that the vehicle is in an uphill condition, and when the slope value is negative, it means that the vehicle is in a downhill condition.

[0079] Specifically, after obtaining the current vehicle weight and the current driving environment, the first strategy is executed to determine the power adjustment coefficient at the current moment, and the first strategy represents the processing process of determining the power adjustment coefficient at the current moment according to the current vehicle weight and the current driving environment. The first strategy can be implemented based on a variety of processing concepts.

[0080] As an optional implementation, the first strategy is implemented based on a processing concept of a preset rule. In this implementation, step 202 "determining a power adjustment coefficient according to the vehicle weight and the driving environment" includes: determining a power adjustment coefficient according to the vehicle weight, the driving environment, and a preset first mapping relationship, the first mapping relationship including a correspondence between a first data set and a power adjustment coefficient, the first data set including the vehicle weight and the vehicle driving environment.

[0081] The first mapping relationship can be understood as a mapping relationship that is pre-set and stored in the cloud or device side, which establishes a correspondence between vehicle weight, driving environment (such as slope) and power adjustment coefficient, including power adjustment coefficients corresponding to different combinations of vehicle weight and driving environment. The first mapping relationship can be determined through experiments, simulations or empirical data.

[0082] Optionally, the first mapping relationship is calibrated and stored in the form of a Map.

[0083] Specifically, a first mapping relationship is pre-set and stored in the cloud or on the device side. After obtaining the current vehicle weight and the current driving environment, the vehicle control device calls the first mapping relationship and determines the power adjustment coefficient corresponding to the current moment according to the current vehicle, the current driving environment and the first mapping relationship. This implementation method based on preset rules is relatively simple, has a small amount of calculation, and is easy to implement and apply.

[0084] As an optional implementation, the first strategy is implemented based on the processing concept of a neural network model. In this implementation, step S202 includes: inputting the vehicle weight and the driving environment into a pre-trained coefficient determination model, and the coefficient determination model determines the power adjustment coefficient according to the vehicle weight and the driving environment.

[0085] Optionally, the coefficient determination model is obtained by performing power adjustment coefficient determination training on the first training sample. The first training sample includes a sample vehicle weight, a sample driving environment, and a sample label (marked power adjustment coefficient). The power adjustment coefficient determination training is performed so that the coefficient determination model can determine the power adjustment coefficient according to the sample vehicle weight and the sample driving environment, and the loss function value determined according to the power adjustment coefficient predicted by the model and the marked power adjustment coefficient meets the preset requirements as the goal. Optionally, the first prediction model can be implemented based on a variety of deep learning neural network structures, such as CNN (Convolutional Neural Networks) network structure, RNN (Recurrent Neural Networks) network structure, CRNN (Convolutional Recurrent Neural Network) network structure, etc., and this application does not limit this.

[0086] This implementation relies on a machine learning algorithm and has strong adaptive capabilities, which can continuously optimize the power output strategy as the driving environment changes.

[0087] S203: Determine a target control strategy for the vehicle according to the power adjustment coefficient, and perform power control on the vehicle according to the target control strategy.

[0088] The target control strategy can be understood as a comprehensive vehicle power control rule determined based on the power adjustment coefficient, which is used to guide the operation of the vehicle power system to achieve precise adjustment of power output. The target control strategy may include adjustments in throttle response, shifting logic, torque distribution, energy recovery and other aspects.

[0089] According to the above content, the power adjustment coefficient, as a quantitative indicator, can reflect the degree of power demand of the vehicle under the current working conditions. By associating the power adjustment coefficient with the control strategy, the vehicle's control strategy can be dynamically adjusted according to actual needs to achieve power output characteristics and operation responses that meet the actual power needs of the vehicle, thereby meeting the driver's intentions and vehicle performance requirements.

[0090] As an optional implementation, the target control strategy of the vehicle can also be determined based on the power adjustment coefficient based on the processing concept of the model. In this implementation, a power control model is constructed, which is designed based on comprehensive considerations of vehicle dynamics, engine characteristics, transmission system efficiency and other related factors. The model input includes real-time parameters such as power adjustment coefficient, vehicle weight, driving environment (such as slope, road conditions, etc.), and the output is the optimized target control strategy.

[0091] Specifically, the power control model may use machine learning algorithms, such as neural networks, support vector machines or decision trees, to learn the optimal power control strategy under different working conditions by training a large amount of historical driving data. In actual application, the model can calculate the most suitable control strategy for the current situation in real time based on the input power adjustment coefficient and other environmental parameters.

[0092] As another optional implementation, "determining the target control strategy of the vehicle according to the power adjustment coefficient" includes: determining the target control strategy of the vehicle according to the power adjustment coefficient and the control strategies corresponding to each driving mode.

[0093] In this implementation, the vehicle control system predefines multiple driving modes, and each driving mode is provided with a corresponding control strategy. Among them, the control strategy corresponding to each driving module can be understood as a preset parameter set, which defines the power performance and control behavior of the vehicle in this driving mode. Optionally, the control strategy corresponding to each driving module is determined by the vehicle manufacturer after careful design and testing based on factors such as the vehicle's technical specifications, market demand, and driving safety.

[0094] The control strategy includes control strategies of multiple power modules, such as an accelerator pedal response module, a gear shift control module, a traction control module, a brake system module, etc.

[0095] Optionally, the control strategy includes an accelerator pedal power request strategy and / or a gear shift speed strategy.

[0096] The accelerator pedal power request strategy is a rule for the accelerator pedal response module, which can be understood as referring to the rules for the influence of the accelerator pedal opening on the vehicle torque output. Furthermore, the accelerator pedal power request strategy includes the rules for the influence of the accelerator pedal opening on the vehicle torque output at different vehicle speeds. Exemplarily, the accelerator pedal power request strategy includes a second mapping relationship, and the second mapping relationship includes the correspondence between a data set consisting of vehicle speed and accelerator pedal opening and a target output torque. Optionally, the second mapping relationship takes the form of a map.

[0097] The shift speed strategy is a rule for the shift control module, which involves the vehicle's shift logic, that is, the shift timing and shift speed of the transmission, and the shift speed can be represented by the output shaft speed of the shift transmission. Furthermore, the shift speed strategy includes the shift speeds corresponding to each target gear under different accelerator pedal openings. Exemplarily, the shift speed strategy includes a third mapping relationship, and the third mapping relationship includes the correspondence between a data set consisting of the accelerator pedal opening and the target gear and the shift speed. Optionally, the third mapping relationship is in the form of a Map diagram.

[0098] Specifically, after determining the power adjustment coefficient, the second strategy is executed to determine the target control strategy of the vehicle. The second strategy is a predefined strategy mapping mechanism, which can establish a corresponding relationship or conversion mechanism between the current demand of the vehicle and multiple predefined driving mode control strategies according to the value of the power adjustment coefficient, and then perform a difference or mix between the control strategies of multiple predefined driving modules according to the power adjustment coefficient to achieve a smooth transition between the control strategies of multiple driving modes.

[0099] The second strategy can be implemented based on a variety of processing concepts. Optionally, the second strategy is an interpolation-based strategy mapping mechanism, which smoothly transitions between the control parameters of each driving module through an interpolation algorithm according to the power adjustment coefficient to generate a target control strategy under the working condition. The interpolation algorithm can be linear, quadratic or higher order, depending on the required smoothness and accuracy, which is not limited in this application.

[0100] Exemplarily, the vehicle includes two driving modes, namely, sports mode and economic mode. The two driving modes correspond to different control strategies, and the target control strategy = economic mode control strategy + power adjustment coefficient * (sports mode control strategy - economic mode control strategy). When the power adjustment coefficient is 0, the target control strategy is completely equal to the economic mode control strategy; when the power adjustment coefficient is 1, the target control strategy is completely equal to the sports mode control strategy. When the power adjustment coefficient is between 0 and 1, the target control strategy is a linear combination of the economic mode control strategy and the sports mode control strategy, and the ratio of this combination is determined by the power adjustment coefficient.

[0101] Optionally, the second strategy can also be a rule-based strategy mapping mechanism (predefine a set of rules to directly specify the corresponding target control strategy according to the range of the power adjustment coefficient), a hybrid-based strategy mapping mechanism, etc., which is not limited in this application.

[0102] Further, as an optional implementation, after determining the target control strategy of the vehicle, the target control parameters of the vehicle are determined according to the current state information of the vehicle and the target control strategy.

[0103] The current state information can be understood as the real-time operating status and / or external environmental conditions of the vehicle at the current moment, which is the basis for the vehicle control system to make decisions and adjustments. The current state information may include but is not limited to vehicle dynamic information (such as vehicle speed, acceleration, engine speed, transmission gear, accelerator pedal position, brake pedal position), vehicle load information, external environmental information, vehicle system status (such as engine temperature, coolant temperature, battery power, tire pressure), etc.

[0104] Optionally, when the target control strategy includes an accelerator pedal power request strategy, the vehicle is power controlled according to the target control strategy, including: determining the target torque requested by the current accelerator pedal opening according to the current vehicle speed, the current accelerator pedal opening and the second mapping relationship, and controlling the power providing mechanism (engine or motor) according to the target torque. Optionally, the target torque is the engine torque or the motor torque. Optionally, the target torque is the wheel end torque.

[0105] Optionally, when the target control strategy includes a gear shifting speed strategy, the vehicle is dynamically controlled according to the target control strategy, including: determining whether a gear shifting operation is required at the current moment and the target gear to be switched to based on the current accelerator pedal opening, the current gear shifting transmission output shaft speed and a preset third mapping relationship.

[0106] As another optional implementation method, based on the current state information of the vehicle and the control strategy corresponding to each driving mode, the vehicle control parameters corresponding to the current state information in each driving mode are determined, and then based on the power adjustment coefficient and the vehicle control parameters corresponding to the current state information in each driving mode, the target control parameters of the vehicle are determined.

[0107] In this implementation, the system needs to determine the vehicle control parameters corresponding to the current state information in each driving mode based on the current state information of the vehicle. This can be achieved by referring to a predefined mapping table or using an algorithm. The mapping table or algorithm stores the correspondence between the vehicle control parameters and the vehicle state information under different driving modes.

[0108] Further, after the target control parameters of the vehicle are determined, the vehicle is controlled based on the target control parameters.

[0109] Optionally, during the power control process, the vehicle control system can use sensor data (such as vehicle speed, engine speed, acceleration, etc.) for closed-loop feedback control. The system will continuously monitor the actual response of the vehicle and fine-tune the control strategy as needed to eliminate any deviations or deficiencies, thereby ensuring the accuracy and stability of power control.

[0110] Through this dynamic, real-time adjustment of power control strategies, the vehicle can better adapt to various driving conditions, reduce unnecessary power waste, and provide a smoother and more consistent acceleration feeling, thereby significantly improving the driving experience.

[0111] The vehicle control method proposed in the present application first obtains the vehicle weight and the driving environment of the vehicle, wherein the driving environment includes the slope; then, according to the vehicle weight and the driving environment, a power adjustment coefficient is determined, wherein the power adjustment coefficient represents the degree of infinite adjustment between multiple driving modes of the vehicle; finally, the target control strategy of the vehicle is determined according to the power adjustment coefficient, and the vehicle is power-controlled according to the target control strategy. On the one hand, the present application no longer relies on the driver to manually switch the driving mode, but automatically adjusts the power output according to the real-time vehicle weight and the driving environment, thereby reducing the burden on the driver and significantly improving the driving experience; on the other hand, the present application introduces the power adjustment coefficient, realizes the infinite adjustment between multiple driving modes of the vehicle, automatically determines the power adjustment coefficient according to the real-time vehicle weight and the driving environment, and controls the vehicle according to the power adjustment coefficient, which can realize the infinite adjustment of power output according to the real-time driving conditions, avoiding the situation of excessive or insufficient power, thereby ensuring the vehicle's power while also improving the economy, achieving a balance between power and economy.

[0112] The "infinite degree of adjustment" here specifically refers to the smooth transition and continuous adjustability of power output between driving modes, rather than the traditional jump-style switching between fixed gears or preset modes. The change in power output between driving modes is smooth, without obvious mutations or setbacks. This means that when the driver switches from one driving mode to another, the vehicle's power response will gradually change to adapt to the new driving needs, rather than suddenly increasing or decreasing power output. The power adjustment coefficient allows continuous adjustment between multiple driving modes, rather than just choosing between a few preset modes. This continuous adjustability provides drivers with greater flexibility and personalization space to fine-tune the vehicle's power output according to specific driving conditions and personal preferences. The power adjustment coefficient is usually adjusted in real time according to the vehicle's driving environment and status (such as vehicle weight, slope, speed, etc.) to ensure that the vehicle maintains optimal power performance under different conditions. This adaptability makes the vehicle's power output more intelligent and efficient, and can meet complex and changing driving needs.

[0113] As an optional implementation method, the vehicle's power system contains multiple power modules, such as the accelerator pedal module, gear adjustment module, engine control module, etc. Each module plays a different role in the vehicle's power transmission and control. Due to functional differences, efficiency and response requirements, the influence of driving modes, hardware characteristics, and safety and comfort considerations, the power adjustment coefficients between different power modules of the vehicle may be different. This differentiated adjustment helps to optimize the performance of each module, thereby improving the power performance and driving experience of the entire vehicle. Figure 3 A flow chart of a vehicle control method provided in another embodiment of the present application is as follows: Figure 3 As shown, the vehicle control method provided in this embodiment includes steps S301-S304:

[0114] S301, obtaining vehicle weight and driving environment, wherein the driving environment includes a slope.

[0115] Step S301 and Figure 2 Corresponding to step S201 in the illustrated embodiment, the specific content of step S301 can refer to step S201 and will not be elaborated here.

[0116] S302: Determine a power adjustment coefficient corresponding to each of a plurality of power modules according to the vehicle weight and the driving environment, wherein the power modules include an accelerator pedal module and / or a gear adjustment module.

[0117] Since different power modules play different roles in vehicle power transmission and control, their power adjustment coefficients may also be different. For example, when going uphill, it may be necessary to increase the engine's output torque and adjust the transmission's shifting strategy to maintain the continuity of power output. This requires calculating different power adjustment coefficients for the engine control module and the gear adjustment module.

[0118] S303: Determine a target control strategy corresponding to the first power module according to a power adjustment coefficient corresponding to the first power module and control strategies corresponding to the first power module in each driving mode.

[0119] The first power module can be understood as any module of the vehicle, such as an accelerator pedal module, a gear adjustment module, etc. Step S303 is intended to determine the target control strategies corresponding to each of the multiple power modules of the vehicle.

[0120] S304: Perform power control on the first power module according to the target control strategy corresponding to the first power module.

[0121] After determining the target control strategy for the first power module, the system will send control instructions to the actuators of the power module (such as the throttle actuator, transmission actuator, etc.) according to this strategy. These control instructions will accurately control the behavior of the power module, such as adjusting the throttle opening, selecting the appropriate gear, etc., to achieve optimized vehicle power output and improved driving experience. This step is for a single power module. In actual applications, the system will perform similar control and adjustments on all power modules in the vehicle power system simultaneously or sequentially to ensure that the power performance and driving experience of the entire vehicle are in the best state.

[0122] Figure 4 A flow chart of a vehicle control method provided in another embodiment of the present application is as follows: Figure 4 As shown, the vehicle control method provided in this embodiment also includes steps S401-S403:

[0123] S401. Obtain a first slope within a preset distance in front of the vehicle.

[0124] The first slope can help the vehicle predict the slope changes ahead and make corresponding power adjustments.

[0125] Optionally, a sensor (such as a radar, a camera, a laser radar LiDAR, a combination of GPS and a digital map, etc.) is used to detect and obtain the road slope within a preset distance in front of the vehicle (such as 50 meters, 100 meters, etc., and this distance can be adjusted according to actual conditions), that is, the first slope.

[0126] Optionally, a high-precision map is used to determine the first slope within a preset distance in front of the vehicle based on the vehicle's current position and planned driving route.

[0127] The preset distance is an adjustable parameter, which determines how far in advance the vehicle can sense the slope change ahead. The distance can be set based on various factors such as the vehicle's driving speed, the sensor's detection capability, and road conditions.

[0128] S402: Determine a first power adjustment coefficient according to the vehicle weight and the first slope.

[0129] The first power adjustment coefficient is a new power adjustment coefficient calculated by the vehicle control device according to the weight of the vehicle (vehicle weight) and the first slope at a preset distance.

[0130] After determining the first power adjustment coefficient, the difference between the first power adjustment coefficient and the current power adjustment coefficient is calculated. If the difference is greater than a preset difference threshold, it means that the slope change ahead has a significant impact on the power demand of the vehicle, and the control strategy needs to be adjusted, and step S403 is executed.

[0131] S403: When the difference between the first power adjustment coefficient and the current power adjustment coefficient is greater than a preset difference threshold, determine a first control strategy for the vehicle according to the first power adjustment coefficient, and perform power control on the vehicle according to the first control strategy.

[0132] When the conditions are met, the system will recalculate the vehicle's control strategy based on the first power adjustment coefficient, that is, the first control strategy. The first control strategy will be more adaptable to the slope changes ahead and can ensure that the vehicle's power output and handling performance remain in the best state.

[0133] After determining the first control strategy, the vehicle will be powered and controlled in advance before the vehicle reaches a preset distance ahead according to the first control strategy. This may include adjusting the engine's throttle opening, the transmission's shifting logic, the motor's output power, etc., to ensure that the vehicle can smoothly and safely pass through the slope change area ahead.

[0134] As an optional implementation method, "controlling the power of the vehicle according to the first control strategy" in step S403 includes: determining the first control parameter of the vehicle under the first control strategy and the second control parameter of the vehicle under the current control strategy based on the current state information of the vehicle; changing the control parameter for power control of the vehicle from the first control parameter to the second control parameter at a preset parameter change rate.

[0135] In this implementation, in order to avoid sudden changes in control parameters causing shock or instability to the vehicle, the system will smoothly transition the control parameters from the current value to the new target value according to the preset parameter change rate. This process can be linear, gradual, or follow other predetermined change rules. Through this implementation, the vehicle's power output and handling performance can gradually adapt to the slope changes ahead, thereby providing a smoother and more comfortable driving experience.

[0136] Exemplary Devices

[0137] Corresponding to the above-mentioned vehicle control method, an embodiment of the present application also provides a vehicle control device. Figure 5 is a schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application, such as Figure 5 As shown, the vehicle control device provided in the embodiment of the present application includes:

[0138] The first unit 501 is used to obtain the vehicle weight and driving environment, wherein the driving environment includes a slope;

[0139] The second unit 502 is used to determine a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between multiple driving modes of the vehicle;

[0140] The third unit 503 is used to determine a target control strategy for the vehicle according to the power adjustment coefficient, and perform power control on the vehicle according to the target control strategy.

[0141] The vehicle control device proposed in the present application, on the one hand, no longer relies on the driver to manually switch driving modes, but automatically adjusts the power output according to the real-time vehicle weight and driving environment, thereby reducing the burden on the driver and significantly improving the driving experience; on the other hand, the power adjustment coefficient is introduced to realize infinite adjustment between multiple driving modes of the vehicle. The power adjustment coefficient is automatically determined according to the real-time vehicle weight and driving environment, and the vehicle is controlled according to the power adjustment coefficient. The power output can be infinitely adjusted according to the real-time driving conditions, avoiding the situation of excessive or insufficient power, thereby ensuring the vehicle's power while improving its economy, achieving a balance between power and economy.

[0142] Optionally, the second unit 502 may be specifically used for:

[0143] A power adjustment coefficient is determined according to the vehicle weight, the driving environment and a preset first mapping relationship, wherein the first mapping relationship includes a correspondence between a first data set and the power adjustment coefficient, and the first data set includes the vehicle weight and the vehicle driving environment.

[0144] Optionally, the third unit 503 may be specifically used for:

[0145] According to the power adjustment coefficient and the control strategies corresponding to each driving mode, a target control strategy of the vehicle is determined, wherein the control strategy includes an accelerator pedal power request strategy and / or a gear shift speed strategy.

[0146] Optionally, the third unit 503 may be specifically used for:

[0147] Determining a vehicle control parameter corresponding to the current state information in each driving mode according to the current state information of the vehicle and the control strategies corresponding to each driving mode;

[0148] Determining a target control parameter of the vehicle according to the power adjustment coefficient and a vehicle control parameter corresponding to the current state information in each driving mode;

[0149] The vehicle is controlled according to the target control parameter.

[0150] Optionally, the second unit 502 may be specifically used for:

[0151] Determining a power adjustment coefficient corresponding to each of a plurality of power modules according to the vehicle weight and the driving environment, wherein the power modules include an accelerator pedal module and / or a gear adjustment module;

[0152] The third unit 503 can be specifically used for:

[0153] According to the power adjustment coefficient corresponding to the first power module and the control strategies corresponding to the first power module in each driving mode, the target control strategy corresponding to the first power module is determined.

[0154] Optionally, the device further comprises:

[0155] The fourth unit is used to obtain a first slope within a preset distance in front of the vehicle; determine a first power adjustment coefficient based on the vehicle weight and the first slope; when the difference between the first power adjustment coefficient and the current power adjustment coefficient is greater than a preset difference threshold, determine a first control strategy for the vehicle based on the first power adjustment coefficient, and perform power control on the vehicle based on the first control strategy.

[0156] Optionally, the fourth unit may be specifically used for:

[0157] Determining, according to the current state information of the vehicle, a first control parameter of the vehicle by the first control strategy and a second control parameter of the vehicle by the current control strategy;

[0158] The control parameter for power control of the vehicle is changed from a first control parameter to a second control parameter according to a preset parameter change rate.

[0159] The vehicle control device provided in this embodiment belongs to the same application concept as the vehicle control method provided in the above embodiments of this application, can execute the vehicle control method provided in any of the above embodiments of this application, and has the corresponding functional modules and beneficial effects of executing the vehicle control method. For technical details not fully described in this embodiment, please refer to the specific processing content of the vehicle control method provided in the above embodiments of this application, and will not be repeated here.

[0160] The functions implemented by the above first unit 501, the second unit 502 and the third unit 503 may be implemented by the same or different processors, respectively, and the embodiment of the present application is not limited thereto.

[0161] It should be understood that the units in the above devices can be implemented in the form of a processor calling software. For example, the device includes a processor, the processor is connected to a memory, and instructions are stored in the memory. The processor calls the instructions stored in the memory to implement any of the above methods or realize the functions of each unit of the device, wherein the processor can be a general-purpose processor, such as a CPU or a microprocessor, etc., and the memory can be a memory in the device or a memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits, and the functions of some or all units can be realized by designing the hardware circuits. The hardware circuit can be understood as one or more processors; for example, in one implementation, the hardware circuit is an ASIC, and the functions of some or all of the above units are realized by designing the logical relationship of the components in the circuit; for another example, in another implementation, the hardware circuit can be implemented by PLD, taking FPGA as an example, which can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by the configuration file, so as to realize the functions of some or all of the above units. All units of the above devices can be implemented in the form of a processor calling software, or in the form of hardware circuits, or in part by a processor calling software, and the remaining part is implemented in the form of hardware circuits.

[0162] In an embodiment of the present application, a processor is a circuit with the ability to process signals. In one implementation, the processor may be a circuit with the ability to read and run instructions, such as a CPU, a microprocessor, a GPU, or a DSP; in another implementation, the processor may implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of the hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by an ASIC or PLD, such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as an NPU, TPU, DPU, etc.

[0163] It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0164] In addition, all or part of the units in the above device can be integrated together, or can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a SOC. The SOC may include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device. The type of the at least one processor may be different, for example, including a CPU and an FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

[0165] Exemplary Electronic Devices

[0166] Another embodiment of the present application also provides an electronic device, see Figure 6 As shown, the device includes:

[0167] Memory 200 and processor 210;

[0168] The memory 200 is connected to the processor 210 and is used to store programs;

[0169] The processor 210 is used to implement the vehicle control method disclosed in any of the above embodiments by running the program stored in the memory 200.

[0170] Specifically, the electronic device may further include: a bus, a communication interface 220 , an input device 230 and an output device 240 .

[0171] The processor 210, the memory 200, the communication interface 220, the input device 230 and the output device 240 are connected to each other via a bus.

[0172] A bus may include a pathway that transfers information between components of a computer system.

[0173] The processor 210 may be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the scheme of the present invention. 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, discrete hardware components.

[0174] The processor 210 may include a main processor, and may also include a baseband chip, a modem, and the like.

[0175] The memory 200 stores a program for executing the technical solution of the present invention, and may also store an operating system and other key services. Specifically, the program may include a program code, and the program code includes a computer operation instruction. More specifically, the memory 200 may include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk storage, a flash, and the like.

[0176] The input device 230 may include a device for receiving data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor.

[0177] Output device 240 may include devices that allow information to be output to a user, such as a display screen, printer, speaker, etc.

[0178] The communication interface 220 may include any transceiver or the like to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0179] The processor 210 executes the program stored in the memory 200 and calls other devices, which can be used to implement each step of any vehicle control method provided in the above embodiments of the present application.

[0180] An embodiment of the present application also proposes a chip, which includes a processor and a data interface. The processor reads and runs a program stored in a memory through the data interface to execute the vehicle control method introduced in any of the above embodiments. The specific processing process and its beneficial effects can be found in the introduction to the above-mentioned embodiment of the vehicle control method.

[0181] Exemplary computer program products and storage media

[0182] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the vehicle control method according to various embodiments of the present application described in any of the above-mentioned embodiments of this specification.

[0183] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0184] In addition, the embodiment of the present application may also be a storage medium on which a computer program is stored. The computer program is executed by a processor to execute the steps of the vehicle control method according to various embodiments of the present application described in any of the above embodiments of this specification, and specifically the following steps may be implemented:

[0185] Step S201: Obtain vehicle weight and driving environment, where the driving environment includes a slope.

[0186] Step S202: determining a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between a plurality of driving modes of the vehicle.

[0187] Step S203: determining a target control strategy for the vehicle according to the power adjustment coefficient, and performing power control on the vehicle according to the target control strategy.

[0188] For the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0189] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0190] The steps in the methods of each embodiment of the present application can be adjusted in order, combined and deleted according to actual needs, and the technical features recorded in each embodiment can be replaced or combined.

[0191] The modules and sub-modules in the devices and terminals of the various embodiments of the present application can be combined, divided and deleted according to actual needs.

[0192] In the several embodiments provided in the present application, it should be understood that the disclosed terminals, devices and methods can be implemented in other ways. For example, the terminal embodiments described above are only schematic, for example, the division of modules or submodules is only a logical function division, and there may be other division methods in actual implementation, for example, multiple submodules or modules can be combined or integrated into another module, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0193] The modules or submodules described as separate components may or may not be physically separated, and the components of the modules or submodules may or may not be physical modules or submodules, that is, they may be located in one place, or they may be distributed on multiple network modules or submodules. Some or all of the modules or submodules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0194] In addition, each functional module or submodule in each embodiment of the present application may be integrated into one processing module, or each module or submodule may exist physically separately, or two or more modules or submodules may be integrated into one module. The above-mentioned integrated modules or submodules may be implemented in the form of hardware or in the form of software functional modules or submodules.

[0195] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0196] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly by hardware, software units executed by a processor, or a combination of the two. The software units may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0197] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including 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, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0198] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle control method, characterized in that: include: Acquiring the vehicle weight and driving environment of the vehicle, wherein the driving environment includes a slope; Determining a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between a plurality of driving modes of the vehicle; A target control strategy for the vehicle is determined according to the power adjustment coefficient, and power control of the vehicle is performed according to the target control strategy.

2. The method according to claim 1, characterized in that The determining of the power adjustment coefficient according to the vehicle weight and the driving environment includes: A power adjustment coefficient is determined according to the vehicle weight, the driving environment and a preset first mapping relationship, wherein the first mapping relationship includes a corresponding relationship between a first data set and the power adjustment coefficient, and the first data set includes the vehicle weight and the driving environment.

3. The method according to claim 1, characterized in that Determining the target control strategy of the vehicle according to the power adjustment coefficient includes: According to the power adjustment coefficient and the control strategies corresponding to each driving mode, a target control strategy of the vehicle is determined, wherein the control strategy includes an accelerator pedal power request strategy and / or a gear shift speed strategy.

4. The method according to claim 3, characterized in that Determining the target control strategy of the vehicle according to the power adjustment coefficient and the control strategies corresponding to each driving mode includes: Determining a vehicle control parameter corresponding to the current state information in each driving mode according to the current state information of the vehicle and the control strategies corresponding to each driving mode; Determining a target control parameter of the vehicle according to the power adjustment coefficient and a vehicle control parameter corresponding to the current state information in each driving mode; The performing power control on the vehicle according to the target control strategy includes: The vehicle is controlled according to the target control parameter.

5. The method according to claim 3, characterized in that: The determining of the power adjustment coefficient according to the vehicle weight and the driving environment includes: Determining a power adjustment coefficient corresponding to each of a plurality of power modules according to the vehicle weight and the driving environment, wherein the power modules include an accelerator pedal module and / or a gear adjustment module; Determining the target control strategy of the vehicle according to the power adjustment coefficient and the control strategies corresponding to each driving mode includes: According to the power adjustment coefficient corresponding to the first power module and the control strategies corresponding to the first power module in each driving mode, the target control strategy corresponding to the first power module is determined.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Acquire a first slope within a preset distance in front of the vehicle; determining a first power adjustment coefficient according to the vehicle weight and the first slope; When the difference between the first power adjustment coefficient and the current power adjustment coefficient is greater than a preset difference threshold, a first control strategy of the vehicle is determined according to the first power adjustment coefficient, and power control of the vehicle is performed according to the first control strategy.

7. The method according to claim 6, characterized in that The performing power control on the vehicle according to the first control strategy includes: Determining, according to the current state information of the vehicle, a first control parameter of the vehicle by the first control strategy and a second control parameter of the vehicle by the current control strategy; The control parameter for power control of the vehicle is changed from a first control parameter to a second control parameter according to a preset parameter change rate.

8. A vehicle control device, characterized in that: include: The first unit is used to obtain the vehicle weight and driving environment, wherein the driving environment includes a slope; A second unit is used to determine a power adjustment coefficient according to the vehicle weight and the driving environment, wherein the power adjustment coefficient represents a degree of infinite adjustment between multiple driving modes of the vehicle; The third unit is used to perform power control on the vehicle according to the power adjustment coefficient.

9. An electronic device, characterized in that: including memory and processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the vehicle control method as described in any one of claims 1 to 7 by running the program in the memory.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the vehicle control method according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The method comprises computer program instructions, which, when executed by a processor, enable the processor to implement the vehicle control method as claimed in any one of claims 1 to 7.

12. A vehicle, characterized in that: include: The electronic device as claimed in claim 9.

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