Oil-electricity hybrid power control method, device and equipment and storage medium

Abstract

The invention relates to an oil-electric hybrid power control method, device and equipment and a storage medium, and the method comprises the steps: obtaining the current driving state data of a target vehicle and the real-time road condition information of a driving road of the target vehicle, and determining the current target demand total power of the target vehicle; and a target fuel-electricity ratio between the fuel power and the electric power of the target vehicle. According to the target demand total power and the target oil-electricity ratio, the current demand fuel oil power and demand electric power of the target vehicle are determined, the fuel oil mass flow of the target vehicle is adjusted according to the demand fuel oil power, and the motor output power of the target vehicle is adjusted according to the demand electric power. On one hand, potential safety hazards caused by power mismatching can be reduced, and driving stability and safety are ensured. On the other hand, the energy utilization efficiency can be optimized, the endurance mileage can be prolonged, and meanwhile the driving stability and safety can be improved.

Description

Technical Field

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

[0002] With the rapid development of new energy vehicles, extended-range electric vehicles (also known as hybrid vehicles) have become one of the most popular types of modern vehicles because they combine the advantages of internal combustion engines and electric motors. In extended-range electric vehicles, the optimization of the oil-electric ratio is the key to improving energy efficiency, reducing energy consumption and reducing emissions.

[0003] In the prior art, extended-range electric vehicles use a rule-based control strategy to adjust the fuel-electric ratio. The rule-based control strategy is, for example, to pre-set the correspondence between different vehicle speeds and fuel-electric ratios, and use the correspondence as a control rule to adjust the fuel-electric ratio according to the vehicle's driving speed.

[0004] Although this method can, to a certain extent, optimize the fuel-electricity ratio in real time during vehicle driving, improve energy efficiency, save energy and reduce emissions, the rules and conditions it relies on are too simple, and the fuel-electricity ratio is only adjusted according to the vehicle speed. This makes it very likely that the best fuel-electricity ratio optimization effect will not be achieved in actual applications, and thus the best energy efficiency and energy-saving emission performance cannot be achieved. Summary of the invention

[0005] The present application provides a hybrid power control method, device, equipment and storage medium to solve the problem that the prior art method of adjusting the oil-electric ratio based solely on vehicle speed cannot achieve the best oil-electric ratio optimization effect, and thus cannot achieve the best energy utilization efficiency and energy-saving emission performance.

[0006] In a first aspect, the present application provides a hybrid power control method, the method comprising:

[0007] Acquire the current driving status data of the target vehicle, and acquire the real-time road condition information of the road on which the target vehicle is traveling;

[0008] Determine the current target required total power of the target vehicle and the target oil-electricity ratio between the fuel power and the electric power of the target vehicle according to the driving state data and the real-time road condition information;

[0009] Determining the current required fuel power and required electric power of the target vehicle according to the target required total power and the target fuel-electricity ratio;

[0010] The fuel mass flow of the target vehicle is adjusted according to the required fuel power, and the motor output power of the target vehicle is adjusted according to the required electric power.

[0011] In a possible implementation manner, determining the current target required total power of the target vehicle according to the driving state data and the real-time road condition information includes:

[0012] Determining the predicted required total power of the target vehicle according to the driving state data;

[0013] Determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0014] The predicted required total power is corrected using the road condition adaptability coefficient to obtain the current target required total power of the target vehicle.

[0015] In a possible implementation manner, determining a target fuel-electricity ratio between fuel power and electric power of the target vehicle according to the driving state data and the real-time road condition information includes:

[0016] Determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0017] The current target fuel-power weight coefficient and target electric power weight coefficient of the target vehicle are determined according to the road condition adaptability coefficient; wherein the ratio of the target fuel-power weight coefficient to the target electric power weight coefficient is the target fuel-electricity ratio.

[0018] In a possible implementation manner, determining the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information includes:

[0019] Determine the traffic congestion index of the road where the target vehicle is currently traveling based on the driving status data and the real-time road condition information;

[0020] According to the traffic congestion index, the current road condition adaptability coefficient of the target vehicle is determined.

[0021] In a possible implementation manner, determining the current target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient includes:

[0022] Obtaining a basic fuel power weight coefficient of the target vehicle;

[0023] The basic fuel-power weight coefficient is corrected by using the road condition adaptability coefficient to obtain the current target fuel-power weight coefficient of the target vehicle;

[0024] A target electric power weight coefficient is determined according to the target fuel power weight coefficient.

[0025] In a possible implementation manner, determining the current road condition adaptability coefficient of the target vehicle according to the traffic congestion index includes:

[0026] Determining a first adjustment coefficient and a second adjustment coefficient according to the traffic congestion index; wherein the first adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on fuel consumption, and the second adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on vehicle response speed;

[0027] The traffic congestion index, the first adjustment coefficient, and the second adjustment coefficient are used to perform a setting operation to obtain the current road condition adaptability coefficient of the target vehicle.

[0028] In a second aspect, the present application provides a hybrid power control device, the device comprising:

[0029] An information acquisition module is used to acquire the current driving state data of the target vehicle and to acquire the real-time road condition information of the road on which the target vehicle is traveling;

[0030] A power prediction module, used to determine the current target required total power of the target vehicle according to the driving state data and the real-time road condition information;

[0031] A fuel-electricity ratio determination module, used to determine a target fuel-electricity ratio between fuel power and electric power of the target vehicle according to the driving state data and the real-time road condition information;

[0032] A power decomposition module, used to determine the current required fuel power and required electric power of the target vehicle according to the target required total power and the target oil-electricity ratio;

[0033] The regulating module is used to regulate the fuel mass flow of the target vehicle according to the required fuel power, and to regulate the motor output power of the target vehicle according to the required electric power.

[0034] In a possible implementation, the power prediction module includes:

[0035] A power determination unit, configured to determine a predicted required total power of the target vehicle according to the driving state data;

[0036] A road condition determination unit, used to determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0037] The correction processing unit is used to use the road condition adaptability coefficient to correct the predicted required total power to obtain the current target required total power of the target vehicle.

[0038] In a possible implementation, the power prediction module includes:

[0039] A road condition determination unit, used to determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0040] A ratio determination unit is used to determine the current target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient; wherein the ratio of the target fuel power weight coefficient to the target electric power weight coefficient is the target fuel-electric ratio.

[0041] In a possible implementation manner, the road condition determination unit includes:

[0042] A congestion index determination subunit, used to determine the traffic congestion index of the road on which the target vehicle is currently traveling based on the driving state data and the real-time road condition information;

[0043] The road condition coefficient determination subunit is used to determine the current road condition adaptability coefficient of the target vehicle according to the traffic congestion index.

[0044] In a possible implementation manner, the ratio determination unit includes:

[0045] A fuel coefficient acquisition subunit, used to acquire a basic fuel power weight coefficient of the target vehicle;

[0046] A correction processing subunit, used for correcting the basic fuel power weight coefficient by using the road condition adaptability coefficient to obtain the current target fuel power weight coefficient of the target vehicle;

[0047] The power coefficient determination subunit is used to determine a target electric power weight coefficient according to the target fuel power weight coefficient.

[0048] In a possible implementation manner, the road condition coefficient determination subunit includes:

[0049] An adjustment coefficient determination subunit, used to determine a first adjustment coefficient and a second adjustment coefficient according to the traffic congestion index; wherein the first adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on fuel consumption, and the second adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on vehicle response speed;

[0050] The setting operation subunit is used to perform setting operation using the traffic congestion index, the first adjustment coefficient and the second adjustment coefficient to obtain the current road condition adaptability coefficient of the target vehicle.

[0051] In a third aspect, the present application provides a device comprising: a processor and a memory, wherein the processor is used to execute a hybrid power control program stored in the memory to implement the hybrid power control method described in any one of the first aspects.

[0052] In a fourth aspect, the present application provides a storage medium storing one or more programs, wherein the one or more programs can be executed by one or more processors to implement the hybrid power control method described in any one of the first aspects.

[0053] The above technical solution provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application determines the current target total power demanded by the target vehicle and the target oil-electric ratio between the fuel power and the electric power of the target vehicle by acquiring the current driving state data of the target vehicle and the real-time road condition information of the road on which the target vehicle is traveling. According to the target total power demanded and the target oil-electric ratio, the current required fuel power and required electric power of the target vehicle are determined, and the fuel mass flow of the target vehicle is adjusted according to the required fuel power, and the motor output power of the target vehicle is adjusted according to the required electric power. Since the real-time road condition information of the road on which the target vehicle is currently traveling is combined when predicting the current target total power demanded by the target vehicle and the optimal oil-electric ratio, the predicted target total power demanded can be closer to the actual demand and more accurate, and thus the ratio between the fuel power and the electric power can be adjusted more intelligently and accurately. On the one hand, this method enables the target vehicle to adjust the power output faster to adapt to road changes, thereby reducing the safety hazards caused by power mismatch, and on the other hand, it can obtain the oil-electric ratio adapted to the current road conditions, which helps to optimize energy efficiency and extend the cruising range. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0055] 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, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0056] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0057] Figure 1 A flow chart of an embodiment of a hybrid power control method provided in an embodiment of the present application.

[0058] Figure 2 A flow chart of another embodiment of a hybrid power control method provided in an embodiment of the present application.

[0059] Figure 3 A flow chart of another embodiment of a hybrid power control method provided in the present application.

[0060] Figure 4 This is a block diagram of an embodiment of a hybrid power control device provided in an embodiment of the present application.

[0061] Figure 5 A schematic diagram of the structure of a device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are 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 making creative work are within the scope of protection of this application.

[0063] The disclosure below provides many different embodiments or examples to realize the different structures of the present application. In order to simplify the disclosure of the present application, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present application. In addition, the present application can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0064] In order to solve the technical problem that the existing method of adjusting the oil-electric ratio based solely on vehicle speed cannot achieve the best oil-electric ratio optimization effect, and thus cannot achieve the best energy utilization efficiency and energy-saving emission performance, the present application provides an oil-electric hybrid power control method, device, equipment and storage medium. The method provided in the embodiment of the present application dynamically adjusts the oil-electric ratio according to the vehicle's driving status data and real-time road condition information. On the one hand, it can reduce the safety hazards caused by power mismatch and ensure the stability and safety of driving. On the other hand, it helps to optimize energy utilization efficiency, extend the cruising range, and at the same time improve the stability and safety of driving.

[0065] Figure 1 This is a flow chart of an embodiment of a hybrid power control method provided in an embodiment of the present application. In one embodiment, the execution subject of the method is a device, such as a vehicle-mounted device.

[0066] like Figure 1 As shown, the process includes the following steps:

[0067] Step 101: Acquire the current driving state data of the target vehicle, and acquire the real-time road condition information of the road on which the target vehicle is traveling.

[0068] The above-mentioned target vehicle refers to an extended-range electric vehicle equipped with the subject of the execution of this application. An extended-range electric vehicle refers to a new energy vehicle that is equipped with a range extender (usually consisting of a small engine and a generator) on the basis of a pure electric vehicle. Its vehicle drive system is composed of two or more single drive systems that can operate simultaneously, usually including a fuel drive system and an electric drive system.

[0069] Driving status data refers to a series of parameters that can reflect the actual state of the target vehicle during driving, and the driving status data in the embodiment of the present application specifically refers to a series of parameters that can affect the oil-electric ratio of the target vehicle, including but not limited to: acceleration, road slope angle, rolling resistance coefficient, vehicle speed, vehicle mass, vehicle front area, air resistance coefficient, air density, gravity acceleration, etc.

[0070] Among them, data such as vehicle mass, vehicle frontal area, and air resistance coefficient depend on the specific vehicle model and are fixed values. Data such as air density and gravity acceleration are constant values. Optionally, a database can be pre-set in the execution subject of this application, and constant values ​​and fixed values ​​depending on the specific vehicle model can be pre-stored in a preset database to facilitate the search and use of these fixed values ​​and constant values.

[0071] The acceleration can be measured by an acceleration sensor mounted on the target vehicle. The vehicle speed can be measured by a speed sensor mounted on the target vehicle.

[0072] The road slope angle is derived from the navigation system or the terrain database.

[0073] The rolling resistance coefficient ranges from 0.01 to 0.35, and the specific value depends on the road surface information. The following table shows the rolling resistance coefficients of common roads:

[0074] Table 1

[0075]

[0076]

[0077] The real-time traffic condition information of the target vehicle's driving road refers to a series of parameters that can reflect the current road condition of the target vehicle, including but not limited to: actual traffic flow, road capacity, free flow speed (referring to the average speed of vehicles in the absence of congestion), average speed of driving vehicles and other information.

[0078] In one embodiment, during the driving process of the target vehicle, the execution entity of this application can obtain the current driving status data of the target vehicle and the real-time road condition information of the road on which the target vehicle is driving according to a set cycle, that is, at regular intervals, so as to optimize the oil-electricity ratio of the target vehicle in real time based on this information, so that the target vehicle can basically achieve the best oil-electricity ratio optimization effect during the entire driving process.

[0079] Step 102: Determine the current target total power demand of the target vehicle and the target oil-electricity ratio between the fuel power and the electric power of the target vehicle according to the driving status data and the real-time road condition information.

[0080] The current target total power demand of the target vehicle is a predicted value, which reflects the power required by the target vehicle in the current driving state. It can be seen from the description of step 102 that in the technical solution provided by the embodiment of the present application, when predicting the current target total power demand of the target vehicle, it is not only based on the current driving state data of the target vehicle, but also combined with the real-time road condition information of the road where the target vehicle is currently traveling. On the one hand, this makes the predicted target total power demand closer to the actual demand and more accurate, thereby reducing the safety hazards caused by power mismatch. On the other hand, it enables the target vehicle to adjust the power output more quickly to adapt to road changes, thereby ensuring driving stability and safety.

[0081] The target fuel - electricity ratio, also being a predicted value, refers to the ratio between the required fuel power and the required electric power. Similarly, in the technical solution provided by the embodiments of the present application, when determining the target fuel - electricity ratio between the fuel power and the electric power of the target vehicle, it is not only based on the driving state data of the target vehicle itself, but also combines the real - time road condition information of the road where the target vehicle is currently traveling. For example, on a flat and unobstructed road, the vehicle can rely more on electric drive to reduce fuel consumption and emissions; while on a slope or in a traffic - congested section, the output of fuel power can be appropriately increased to ensure the power performance and driving stability of the vehicle. Thus, combining real - time road condition information enables the target vehicle to more intelligently and accurately adjust the ratio between fuel power and electric power. This adjustment method helps to optimize energy utilization efficiency, extend the cruising range, and at the same time can also improve the smoothness and safety of driving.

[0082] As for how to determine the current total target required power of the target vehicle according to the driving state data and real - time road condition information, and how to determine the target fuel - electricity ratio between the fuel power and the electric power of the target vehicle, it will be explained through specific embodiments below and will not be elaborated here first.

[0083] Step 103: Determine the current required fuel power and required electric power of the target vehicle according to the total target required power and the target fuel - electricity ratio.

[0084] Based on the relevant descriptions of the total target required power and the target fuel - electricity ratio in the above - mentioned step 102, here, the total target required power can be decomposed according to the target fuel - electricity ratio to obtain the current required fuel power and required electric power of the target vehicle.

[0085] For example, assuming the target fuel - electricity ratio is ω1:ω2, then the current required fuel power and required electric power of the target vehicle can be determined by the following formula (1):

[0086]

[0087] In the above formula (1), Paj represents the total target required power; E_fuel represents the required fuel power of the target vehicle.

[0088] Given that the target fuel - electricity ratio is ω1:ω2 and the total target required power Paj is fixed, the current required fuel power E_fuel of the target vehicle can be calculated through the above formula (1). Similarly, the current required electric power E_electric of the target vehicle can be obtained by using the total target required power Paj and the target fuel - electricity ratio ω1:ω2.

[0089] Step 104: Adjust the fuel mass flow rate of the target vehicle according to the required fuel power, and adjust the motor output power of the target vehicle according to the required electric power.

[0090] Mass flow rate refers to the mass of fluid passing through the effective cross-section of a closed pipe or an open trough per unit time. Here, the fuel mass flow rate refers to the mass of fuel consumed per unit time (such as per hour or per minute).

[0091] The output power of an electric motor refers to the amount of energy that the electric motor can output when driving a load.

[0092] Those skilled in the art can understand that the following formula (II) is the calculation formula for fuel power:

[0093]

[0094] In the above formula (II), mf represents the fuel mass flow rate; ηoil represents the thermal efficiency of the engine; QL represents the lower heating value of the fuel, that is, the heat released by the complete combustion of unit mass of fuel.

[0095] Among them, the values of ηoil and QL are fixed, and Eoil has been predicted through step 103. Then, according to the above formula (II), the fuel mass flow rate mf required to achieve Eoil can be calculated, and then the fuel mass flow rate of the target vehicle can be adjusted to this calculated value to achieve the required fuel power Eoil of the target vehicle currently.

[0096] The following formula (III) is the calculation formula for electric power:

[0097]

[0098] In the above formula (III), Pelec represents the output power of the electric motor; ηelec represents the efficiency of the electric motor. Among them, the values of the electric motor efficiency for different vehicle models are fixed, so the value of ηelec is also fixed. Eelec has been predicted through the above step 103. Then, according to the above formula (III), the output power Pelec of the electric motor required to achieve Eelec can be calculated, and then the output power of the electric motor of the target vehicle can be adjusted to this calculated value to achieve the required electric power Eelec of the target vehicle currently.

[0099] The method provided in the embodiment of the present application determines the current target total power demand of the target vehicle and the target oil-electric ratio between the fuel power and the electric power of the target vehicle by acquiring the current driving state data of the target vehicle and the real-time road condition information of the road on which the target vehicle is traveling. According to the target total power demand and the target oil-electric ratio, the current required fuel power and required electric power of the target vehicle are determined, and the fuel mass flow of the target vehicle is adjusted according to the required fuel power, and the motor output power of the target vehicle is adjusted according to the required electric power. Since the real-time road condition information of the road on which the target vehicle is currently traveling is combined when predicting the current target total power demand and the optimal oil-electric ratio of the target vehicle, the predicted target total power demand can be closer to the actual demand and more accurate, and thus the ratio between the fuel power and the electric power can be adjusted more intelligently and accurately. On the one hand, this method enables the target vehicle to adjust the power output faster to adapt to road changes, thereby reducing the safety hazards caused by power mismatch. On the other hand, it can obtain the oil-electric ratio adapted to the current road conditions, which helps to optimize energy efficiency and extend the cruising range.

[0100] Figure 2 This is a flow chart of another embodiment of a hybrid power control method provided in the present application. Figure 2 The process shown in Figure 1 Based on the process shown in FIG. 1 , this paper describes how to determine the current target required total power of the target vehicle based on the driving status data and real-time road condition information. Figure 2 As shown, the process includes the following steps:

[0101] Step 201: Determine the predicted required total power of the target vehicle according to the driving status data.

[0102] In one embodiment, the predicted required total power Pe of the target vehicle may be determined according to the power demand prediction model exemplified by the following formula (IV):

[0103]

[0104] In the above formula (IV), m represents the mass of the target vehicle; a represents the acceleration of the target vehicle; ρ represents the air density, which can usually be 1.225; A represents the front area of ​​the vehicle; Cd represents the air resistance coefficient, which can usually be between 0.23-0.5, depending on the specific vehicle model; V represents the speed of the target vehicle, which can be calculated by the vehicle speed sensor; g represents the acceleration of gravity, which is a constant; represents the road slope angle, which can be obtained through the navigation system or terrain database; μ represents the rolling resistance coefficient, which ranges from 0.01 to 0.35. In practical applications, the above Figure 1 Table 1 shown in the Examples is obtained.

[0105] Step 202: Determine the current road condition adaptability coefficient of the target vehicle according to the driving status data and the real-time road condition information.

[0106] The road adaptability coefficient is a comprehensive evaluation index of the adaptability and performance of a car under different road conditions. This coefficient can reflect the driving performance of a vehicle under various road conditions, including smooth roads, damaged roads, gravel roads and other conditions.

[0107] In one embodiment, the specific implementation of determining the current road condition adaptability coefficient of the target vehicle based on the driving status data and the real-time road condition information includes: determining the traffic congestion index of the road where the target vehicle is currently traveling based on the current driving status data of the target vehicle and the real-time road condition information of the road where the target vehicle is currently traveling, and determining the current road condition adaptability coefficient of the target vehicle based on the traffic congestion index.

[0108] Among them, the traffic congestion index can reflect the congestion of the road where the target vehicle is currently traveling. For example, the value range of the traffic index is between 0 and 1, where 0 indicates no congestion and 1 indicates extreme congestion. It can be seen that the larger the traffic congestion index, the more congested the current road is. Generally speaking, it is considered that a traffic congestion index greater than 0.6 is considered to be in the congestion range.

[0109] The traffic congestion index is a comprehensive indicator that can be calculated based on traffic flow, average speed, road capacity and free flow speed. For example, the traffic congestion index can be calculated using the following formula (5):

[0110]

[0111] In the above formula (V), actual traffic flow refers to the number of vehicles passing through the same direction of the road in a specific time period. Road capacity refers to the maximum number of vehicles that a road can bear in the same direction. Average speed refers to the average speed of the target vehicle during its driving process. Free flow speed refers to the average speed of vehicles in the absence of congestion.

[0112] As an optional implementation method, the specific implementation of determining the current road condition adaptability coefficient of the target vehicle according to the traffic congestion index includes: determining a first adjustment coefficient and a second adjustment coefficient according to the traffic congestion index; wherein the first adjustment coefficient is used to reflect the influence of the congestion of the road on which the target vehicle is traveling on fuel consumption, and the second adjustment coefficient is used to reflect the influence of the congestion of the road on which the target vehicle is traveling on the vehicle response speed; and setting operations are performed using the traffic congestion index, the first adjustment coefficient, and the second adjustment coefficient to obtain the current road condition adaptability coefficient of the target vehicle.

[0113] Since the road condition adaptability coefficient is not a fixed value, its value depends on the current real-time road condition information. In order to accurately calculate the adaptability coefficient of the current road condition, we can introduce the first adjustment coefficient and the second adjustment coefficient. Among them, β represents the first adjustment coefficient, γ represents the second adjustment coefficient, and we can determine the first adjustment coefficient β and the second adjustment coefficient γ according to the traffic congestion index. The first adjustment coefficient β is usually a positive value, which can be used to measure the impact of traffic congestion on fuel consumption. For example, the larger the value of β, the greater the fuel consumption of the vehicle, indicating that it is in a traffic congested section. The second adjustment coefficient γ is used to measure the impact of traffic conditions on the power consumption of the vehicle's power system. For example, the larger the γ, the greater the power consumption of the vehicle's power system. Conversely, the smaller the γ, the smaller the power consumption of the vehicle's power system.

[0114] In one embodiment, the traffic congestion index, the first adjustment coefficient, and the second adjustment coefficient are used to perform a setting operation to obtain the current road condition adaptability coefficient of the target vehicle. For example, the setting operation can be the following formula (VI):

[0115]

[0116] In the above formula (six), frode represents the road condition adaptability coefficient; β represents the first adjustment coefficient, which can reflect the fuel consumption in the current vehicle power system; γ represents the second adjustment coefficient, which can reflect the electricity consumption in the current vehicle power system; Trode(t) represents the traffic congestion index at time t; e represents a constant.

[0117] Among them, the execution subject of this application will calculate the traffic congestion coefficient Trode(t) according to the current driving situation of the target vehicle and the real-time road condition information using the above formula (V), and adjust the values ​​of β and γ accordingly. For example, if the traffic congestion index is greater than 0.6, it means that the current road condition is severely congested. At this time, the value of the first adjustment coefficient β can be reduced to increase the priority of electric drive, and the value of the second adjustment coefficient γ can be increased, thereby increasing the power consumption of the power system of the target vehicle and reducing the fuel consumption of the target vehicle.

[0118] In the case of congested traffic, the driver needs to frequently start and stop the target vehicle. Since the starting response speed of the electric motor in the vehicle power system is faster than that of the fuel engine, the electric motor in the vehicle power system can assist the driver to quickly start the vehicle in the case of congested traffic, avoid rear-end collisions caused by slow vehicle start, and improve user experience. Therefore, in the case of congested traffic, the power consumption of the electric motor in the vehicle power system can be increased, that is, the value of the second adjustment coefficient γ can be increased, and the fuel consumption of the engine in the vehicle power system can be reduced, that is, the value of the first adjustment coefficient β can be reduced.

[0119] The above step 202 calculates the traffic congestion index according to the real-time road condition information, and uses the traffic congestion index, the first adjustment coefficient and the second adjustment coefficient to perform setting operations to obtain the current road condition adaptability coefficient of the target vehicle, which can more accurately reflect the adaptability coefficient of the target vehicle under the current road condition and improve the accuracy of the road condition adaptability coefficient. This helps to accurately calculate the oil-electricity ratio in the subsequent process and improve energy utilization.

[0120] Step 203: Use the road condition adaptability coefficient to correct the predicted total power demand to obtain the current target total power demand of the target vehicle.

[0121] Due to different road conditions, the power requirements of the target vehicle are different. For example, when driving on urban roads, due to traffic congestion and frequent starts and stops, the power requirements of the vehicle are relatively low. When driving on highways, the power requirements of the vehicle increase significantly, and when driving on mountain roads, the power requirements of the vehicle are even higher. Therefore, the specific value of the target required total power also depends on the specific road conditions. Based on this, we can introduce the road condition adaptability coefficient frode to more accurately predict the current target required total power of the target vehicle.

[0122] In one embodiment, the predicted total power demand Pe is corrected using the road condition adaptability coefficient frode to obtain the current target total power demand of the target vehicle. For example, the correction process is expressed as the following formula (VII):

[0123] P aj =P e ×f rode ……………………………………Formula (VII)

[0124] Paj calculated by the above formula is the power demand after adjustment based on the road conditions, which can better reflect the total power demand of the target vehicle under the current road conditions and the current driving speed, that is, the target required total power.

[0125] Figure 2 In the embodiment shown, the predicted total power required by the target vehicle is determined by acquiring the driving state data of the target vehicle, and the predicted total power required is corrected using the road condition adaptability coefficient, thereby obtaining the current target total power required by the target vehicle. This achieves accurate calculation of the total power required by the target vehicle under specific road conditions and driving conditions, which helps to accurately calculate the oil-electricity ratio in the subsequent process and improve energy utilization.

[0126] Figure 3 A flowchart of another embodiment of a hybrid power control method provided in the present application is shown below. Figure 3 The process shown in Figure 1Based on the process shown in FIG. 1 , a description is given of how to determine the target fuel-electricity ratio between the required fuel power and the required electric power of the target vehicle according to the driving status data and the real-time road condition information. Figure 3 As shown, the process includes the following steps:

[0127] Step 301: Determine the current road condition adaptability coefficient of the target vehicle according to the driving status data and the real-time road condition information.

[0128] For a detailed description of step 301, please refer to the above Figure 2 The relevant description of step 202 in the embodiment will not be repeated here.

[0129] Step 302: Determine the current target fuel power weight coefficient and target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient; wherein the ratio of the target fuel power weight coefficient to the target electric power weight coefficient is the target fuel-electric ratio.

[0130] The target fuel power weight coefficient (denoted as ω1) is used to reflect the relative importance of fuel cost in the optimization target of oil-electricity ratio. The target electric power weight coefficient (denoted as ω2) is used to reflect the relative importance of electric power cost in the optimization target of oil-electricity ratio.

[0131] From the description of step 302, it can be seen that the target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle are determined here in combination with the road condition adaptability coefficient, so that the target oil-electricity ratio can be predicted more accurately, and then the target oil-electricity ratio can be used to more accurately adjust the required fuel power E oil and required electric power E electric of the target vehicle. This method can more intelligently and accurately adjust the required fuel power E oil and required electric power E electric of the vehicle according to the current road condition information, which helps to reduce energy consumption and improve energy utilization.

[0132] In one embodiment, the specific implementation of determining the current target fuel-power weight coefficient and the target electric power weight coefficient of the target vehicle based on the road condition adaptability coefficient includes: obtaining the basic fuel-power weight coefficient of the target vehicle; using the road condition adaptability coefficient to correct the basic fuel-power weight coefficient to obtain the current target fuel-power weight coefficient of the target vehicle.

[0133] The basic fuel power weight coefficient (denoted as h) of the target vehicle indicates the initial importance of fuel cost when there is no traffic impact. The basic fuel power weight coefficient h can be determined based on historical fuel consumption data, historical power consumption data, user preferences, local policies and regulations, etc. For example, in practical applications, it can be calculated by the following formula (VIII):

[0134]

[0135] In the above formula (eight), h represents the basic fuel power weight coefficient; C oil represents the fuel consumption cost per unit time, for example, the fuel consumption cost of all fuel used in normal driving for 1 minute; C electricity represents the electric energy consumption cost per unit time; B represents the cost price data of the vehicle; C represents the driving habit data, which is used to reflect the user's emphasis on fuel economy and driving performance; D represents the user's vehicle usage ratio data; E represents the local policy orientation data; and F represents other data.

[0136] As an optional implementation, the basic fuel power weight coefficient h is corrected using the road condition adaptability coefficient to obtain the current target fuel power weight coefficient ω1 of the target vehicle. For example, the above correction process is expressed as the following formula (IX):

[0137] ω 1 =h×f rode ………………………………Formula (9)

[0138] In the above formula (IX), ω1 represents the target fuel-power weight coefficient; h represents the basic fuel-power weight coefficient; frode represents the road condition adaptability coefficient, which can be adjusted according to the real-time road condition information. The target fuel-power weight coefficient that can reflect the real-time road condition can be calculated through the above formula (IX).

[0139] Furthermore, if the target fuel power weight coefficient ω1 is known, the target electric power weight coefficient ω2 can be calculated by the following formula (10):

[0140] ω 2 =1-ω 1 …………………………………………Formula (10)

[0141] Referring to the description of step 302 above, it can be known that the ratio of the target fuel power weight coefficient to the target electric power weight coefficient is the target fuel-electricity ratio. Then, the target fuel power weight coefficient ω1 and the target electric power coefficient ω2 calculated according to the above formula can obtain the target fuel-electricity ratio ω1:ω2.

[0142] Figure 3 The illustrated embodiment determines the target fuel-electricity ratio of the target vehicle by combining the driving status data and real-time road condition information of the target vehicle, and can dynamically and accurately adjust the fuel mass flow rate and motor output power of the target vehicle according to different driving conditions and driving states, thereby achieving better fuel-electricity ratio optimization effects and improving the energy utilization efficiency of the target vehicle.

[0143] Figure 4 This is a block diagram of an embodiment of a hybrid power control device provided in an embodiment of the present application. Figure 4 As shown, the device comprises:

[0144] The information acquisition module 41 is used to acquire the current driving state data of the target vehicle and the real-time road condition information of the road on which the target vehicle is traveling;

[0145] A power prediction module 42, used to determine the current target required total power of the target vehicle according to the driving state data and the real-time road condition information;

[0146] The fuel-electricity ratio determination module 43 is used to determine the target fuel-electricity ratio between the fuel power and the electric power of the target vehicle according to the driving state data and the real-time road condition information;

[0147] A power decomposition module 44 is used to determine the current required fuel power and required electric power of the target vehicle according to the target required total power and the target fuel-electricity ratio;

[0148] The regulating module 45 is used to regulate the fuel mass flow of the target vehicle according to the required fuel power, and to regulate the motor output power of the target vehicle according to the required electric power.

[0149] In a possible implementation, the power prediction module 42 includes:

[0150] A power determination unit, configured to determine a predicted required total power of the target vehicle according to the driving state data;

[0151] A road condition determination unit, used to determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0152] The correction processing unit is used to use the road condition adaptability coefficient to correct the predicted required total power to obtain the current target required total power of the target vehicle.

[0153] In a possible implementation, the power prediction module 42 includes:

[0154] A road condition determination unit, used to determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information;

[0155] A ratio determination unit is used to determine the current target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient; wherein the ratio of the target fuel power weight coefficient to the target electric power weight coefficient is the target fuel-electric ratio.

[0156] In a possible implementation manner, the road condition determination unit includes:

[0157] A congestion index determination subunit, used to determine the traffic congestion index of the road on which the target vehicle is currently traveling based on the driving state data and the real-time road condition information;

[0158] The road condition coefficient determination subunit is used to determine the current road condition adaptability coefficient of the target vehicle according to the traffic congestion index.

[0159] In a possible implementation manner, the ratio determination unit includes:

[0160] A fuel coefficient acquisition subunit, used to acquire a basic fuel power weight coefficient of the target vehicle;

[0161] A correction processing subunit, used for correcting the basic fuel power weight coefficient by using the road condition adaptability coefficient to obtain the current target fuel power weight coefficient of the target vehicle;

[0162] The power coefficient determination subunit is used to determine a target electric power weight coefficient according to the target fuel power weight coefficient.

[0163] In a possible implementation manner, the road condition coefficient determination subunit includes:

[0164] An adjustment coefficient determination subunit, used to determine a first adjustment coefficient and a second adjustment coefficient according to the traffic congestion index; wherein the first adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on fuel consumption, and the second adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on vehicle response speed;

[0165] The setting operation subunit is used to perform setting operation using the traffic congestion index, the first adjustment coefficient and the second adjustment coefficient to obtain the current road condition adaptability coefficient of the target vehicle.

[0166] like Figure 5 As shown, an embodiment of the present application provides a device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0167] Memory 113, used for storing computer programs;

[0168] In one embodiment of the present application, the processor 111 is used to execute the program stored in the memory 113 to implement a hybrid power control method provided by any of the above method embodiments, including:

[0169] Acquire the current driving status data of the target vehicle, and acquire the real-time road condition information of the road on which the target vehicle is traveling;

[0170] Determine the current target required total power of the target vehicle and the target oil-electricity ratio between the fuel power and the electric power of the target vehicle according to the driving state data and the real-time road condition information;

[0171] Determining the current required fuel power and required electric power of the target vehicle according to the target required total power and the target fuel-electricity ratio;

[0172] The fuel mass flow of the target vehicle is adjusted according to the required fuel power, and the motor output power of the target vehicle is adjusted according to the required electric power.

[0173] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of a hybrid power control method provided by any of the aforementioned method embodiments are implemented.

[0174] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0175] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0176] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0177] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can 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 range consistent with the principles and novel features applied for herein.

Claims

1. A hybrid power control method, characterized in that: The method comprises: Acquire the current driving status data of the target vehicle, and acquire the real-time road condition information of the road on which the target vehicle is traveling; Determine the current target required total power of the target vehicle and the target oil-electricity ratio between the fuel power and the electric power of the target vehicle according to the driving state data and the real-time road condition information; Determining the current required fuel power and required electric power of the target vehicle according to the target required total power and the target fuel-electricity ratio; The fuel mass flow of the target vehicle is adjusted according to the required fuel power, and the motor output power of the target vehicle is adjusted according to the required electric power.

2. The method according to claim 1, characterized in that Determining the current target required total power of the target vehicle according to the driving state data and the real-time road condition information includes: Determining the predicted required total power of the target vehicle according to the driving state data; Determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information; The predicted required total power is corrected using the road condition adaptability coefficient to obtain the current target required total power of the target vehicle.

3. The method according to claim 1, characterized in that Determining a target fuel-electricity ratio between fuel power and electric power of the target vehicle according to the driving state data and the real-time road condition information includes: Determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information; The current target fuel-power weight coefficient and target electric power weight coefficient of the target vehicle are determined according to the road condition adaptability coefficient; wherein the ratio of the target fuel-power weight coefficient to the target electric power weight coefficient is the target fuel-electricity ratio.

4. The method according to claim 2 or 3, characterized in that: The determining the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information includes: Determining the traffic congestion index of the road on which the target vehicle is currently traveling based on the driving status data and the real-time road condition information; According to the traffic congestion index, the current road condition adaptability coefficient of the target vehicle is determined.

5. The method according to claim 3, characterized in that: The step of determining the current target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient includes: Obtaining a basic fuel power weight coefficient of the target vehicle; The basic fuel-power weight coefficient is corrected by using the road condition adaptability coefficient to obtain the current target fuel-power weight coefficient of the target vehicle; A target electric power weight coefficient is determined according to the target fuel power weight coefficient.

6. The method according to claim 4, characterized in that Determining the current road condition adaptability coefficient of the target vehicle according to the traffic congestion index includes: Determining a first adjustment coefficient and a second adjustment coefficient according to the traffic congestion index; wherein the first adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on fuel consumption, and the second adjustment coefficient is used to reflect the degree of influence of the congestion of the road on which the target vehicle is traveling on vehicle response speed; The traffic congestion index, the first adjustment coefficient, and the second adjustment coefficient are used to perform a setting operation to obtain the current road condition adaptability coefficient of the target vehicle.

7. A hybrid power control device, characterized in that: The device comprises: An information acquisition module is used to acquire the current driving state data of the target vehicle and to acquire the real-time road condition information of the road on which the target vehicle is traveling; A power prediction module, used to determine the current target required total power of the target vehicle according to the driving state data and the real-time road condition information; A fuel-electricity ratio determination module, used to determine a target fuel-electricity ratio between fuel power and electric power of the target vehicle according to the driving state data and the real-time road condition information; A power decomposition module, used to determine the current required fuel power and required electric power of the target vehicle according to the target required total power and the target oil-electricity ratio; The regulating module is used to regulate the fuel mass flow of the target vehicle according to the required fuel power, and to regulate the motor output power of the target vehicle according to the required electric power.

8. The device according to claim 7, characterized in that The oil-electricity ratio determination module includes: A road condition determination unit, used to determine the current road condition adaptability coefficient of the target vehicle according to the driving state data and the real-time road condition information; A ratio determination unit is used to determine the current target fuel power weight coefficient and the target electric power weight coefficient of the target vehicle according to the road condition adaptability coefficient; wherein the ratio of the target fuel power weight coefficient to the target electric power weight coefficient is the target fuel-electric ratio.

9. A device, characterized in that: include: A processor and a memory, wherein the processor is used to execute a hybrid power control program stored in the memory to implement the hybrid power control method according to any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the hybrid power control method according to any one of claims 1-6.

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