Hybrid power vehicle energy management method, device, equipment and medium

Abstract

The invention provides a hybrid vehicle energy management method, device and equipment and a medium, and the method comprises the steps: obtaining the real-time traffic information and configuration information of a vehicle, and calculating the demand power and demand torque of the vehicle according to the real-time traffic information and configuration information; calculating energy consumption of the battery according to the battery remaining capacity, the capacity information and the temperature information to obtain energy consumption information of the battery; power parameters of the vehicle are obtained, and the actual power and the actual torque of the vehicle are calculated according to the energy consumption information and the power parameters; actual energy consumption of the vehicle is calculated according to the actual power and the actual torque, and an energy distribution strategy is made according to the actual energy consumption; and constructing a dynamic programming algorithm to perform power distribution on an engine and a motor of the vehicle according to the energy distribution strategy. According to the technical scheme of the embodiment, through real-time interaction of the Internet of Vehicles, the vehicle can complete efficient energy distribution according to the processing information, and energy consumption and environmental pollution of the hybrid power vehicle are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle energy management, and particularly relates to a hybrid vehicle energy management method, device, equipment and medium. Background Art

[0002] As one of the current main means of transportation, under the pressures of environmental pollution, energy security, greenhouse effect and fuel consumption, it is necessary to optimize the energy utilization of automobiles. Based on technologies such as vehicle networking and intelligent transportation, combined with the inherent architecture advantages of hybrid vehicles with coexistence of multiple energy sources for peak shaving and valley filling, and the real-time interaction of vehicle information with the outside world, the accuracy and real-time performance of vehicle energy management are improved, and it is no longer limited to the calibrated values calculated offline by rule algorithms. However, the energy management of hybrid vehicles in the prior art generally adopts the method of rule or offline calculation and calibration, and cannot timely manage the vehicle energy according to the driving route, traffic conditions or road gradient of the vehicle. To a certain extent, rule algorithms and theoretical calculations may optimize energy management and achieve an energy-saving effect, but they cannot cover real driving scenarios, and can only manage energy according to established calibrations or algorithms, and cannot allocate energy in the most optimal way, resulting in waste of energy and further environmental pollution. Summary of the Invention

[0003] The present invention aims to at least solve one of the technical problems existing in the prior art. For this purpose, the present invention provides a hybrid vehicle energy method, device, equipment and medium, which can allocate vehicle energy as needed, timely adjust the control strategies of the vehicle engine and motor, reduce waste of vehicle energy, and reduce environmental pollution.

[0004] In a first aspect, an embodiment of the present invention provides a hybrid vehicle energy management method, including:

[0005] Connect the vehicle to the network, obtain the real-time traffic information and configuration information of the vehicle, and calculate the required power and required torque of the vehicle according to the real-time traffic information and the configuration information;

[0006] Calculate the remaining battery power, capacity information and temperature information of the vehicle, and calculate the energy consumption of the battery according to the remaining battery power, the capacity information and the temperature information to obtain the energy consumption information of the battery;

[0007] Obtain the power parameters of the vehicle, and calculate the actual power and actual torque of the vehicle according to the energy consumption information and the power parameters;

[0008] Calculate the actual energy consumption of the vehicle according to the actual power and the actual torque, and formulate an energy allocation strategy according to the actual energy consumption;

[0009] Construct a dynamic programming algorithm that distributes power between the vehicle's engine and motor according to the energy distribution strategy.

[0010] In some embodiments of the present invention, calculating the required power and required torque of the vehicle based on the real-time traffic information and the configuration information includes:

[0011] Obtain the air density, drag coefficient, and vehicle frontal area of the vehicle during driving, and calculate the air resistance of the vehicle based on the air density, the drag coefficient, and the vehicle frontal area;

[0012] Obtain the rolling resistance of the vehicle's wheels, vehicle mass, gravitational acceleration, and road gradient, and calculate the rolling resistance of the vehicle based on the rolling resistance of the wheels, the vehicle mass, the gravitational acceleration, and the road gradient;

[0013] Calculate the gradient resistance of the vehicle based on the vehicle mass, the gravitational acceleration, and the road gradient;

[0014] Obtain the vehicle acceleration of the vehicle, and calculate the acceleration resistance of the vehicle based on the vehicle acceleration and the vehicle mass;

[0015] Calculate the total resistance of the vehicle based on the air resistance, the rolling resistance, the gradient resistance, and the acceleration resistance;

[0016] Obtain the real-time driving speed and vehicle transmission efficiency of the vehicle, and calculate the required power of the vehicle based on the real-time driving speed, the vehicle transmission efficiency, and the total resistance;

[0017] Obtain the wheel radius of the vehicle, and calculate the wheel angular velocity of the vehicle based on the wheel radius and the real-time driving speed;

[0018] Calculate the required torque of the vehicle based on the required power, the vehicle transmission efficiency, and the wheel angular velocity.

[0019] In some embodiments of the present invention, calculating the actual power and actual torque of the vehicle based on the energy consumption information and the power parameters includes:

[0020] Obtain the transmission efficiency of the vehicle;

[0021] Obtain the engine power and motor power of the vehicle, and calculate the actual power of the vehicle based on the engine power, the motor power, and the transmission efficiency;

[0022] Obtain the engine torque and motor torque of the vehicle, and calculate the actual torque of the vehicle based on the engine torque, the motor torque, and the transmission efficiency.

[0023] In some embodiments of the present invention, calculating the remaining battery power, capacity information, and temperature information of the vehicle includes:

[0024] Obtain the battery voltage information and battery power information of the vehicle, and calculate the battery current of the vehicle according to the battery voltage information and the battery power information;

[0025] Obtain the initial capacity information and nominal capacity of the battery, and calculate the remaining battery power of the battery according to the initial capacity information, the nominal capacity, and the battery current;

[0026] Obtain the temperature influence coefficient and aging influence coefficient of the battery, and calculate the battery capacity of the battery according to the temperature influence coefficient, the aging influence coefficient, and the nominal capacity of the battery;

[0027] Obtain the internal resistance of the battery, and calculate the joule heat of the battery according to the internal resistance of the battery and the battery current;

[0028] Obtain the heat dissipation coefficient, battery surface area, and ambient temperature of the battery, and calculate the battery temperature of the battery according to the heat dissipation coefficient, the battery surface area, the ambient temperature, and the joule heat;

[0029] Adjust the remaining battery power, the battery capacity, and the battery temperature according to the required power and the required torque until the charging power, discharging power, and energy output efficiency of the battery reach the energy distribution strategy.

[0030] In some embodiments of the present invention, formulating the energy distribution strategy according to the actual energy consumption includes:

[0031] Obtain the real-time output power of the vehicle's engine, the engine thermal efficiency, and the low calorific value of the fuel, and calculate the fuel consumption of the vehicle according to the real-time output power of the engine, the low calorific value, and the engine power;

[0032] Obtain the motor power and motor efficiency of the vehicle, and calculate the motor electrical energy consumption of the vehicle according to the motor power and the motor efficiency;

[0033] Obtain the equipment energy consumption and working time of the vehicle, and calculate the equipment energy consumption of the vehicle according to the equipment energy consumption and the working time;

[0034] Calculate the total energy consumption of the vehicle according to the fuel consumption, the electrical energy consumption, the low calorific value, and the equipment energy consumption;

[0035] Perform energy distribution on the vehicle according to the total energy consumption and the energy distribution strategy.

[0036] In some embodiments of the present invention, the dynamic programming algorithm performs power distribution on the vehicle internal combustion engine and the vehicle drive motor according to the energy distribution strategy, including:

[0037] Obtain the load demand information and vehicle speed information of the vehicle, and determine the working mode of the vehicle according to the load demand, the vehicle speed information, and the remaining battery power;

[0038] When the vehicle speed information is in the first driving speed range, the load demand is in the first load demand range, and the remaining battery power is in the first remaining battery power range, the vehicle is in the pure electric mode, the vehicle is driven by the motor, and the engine of the vehicle stops working;

[0039] When the vehicle speed information is in the second driving speed range, the load demand is in the second load demand range, and the remaining battery power is in the second remaining battery power range, the vehicle is in the hybrid mode, and the engine and the motor work together;

[0040] When the vehicle speed information is in the third driving speed range, the load demand is in the third load demand range, and the remaining battery power is in the third remaining battery power range, the vehicle is in the engine drive mode, the vehicle is driven by the engine, the motor stops working, and the battery is charged at the same time;

[0041] When the vehicle brakes or decelerates, the vehicle is in the energy recovery mode, and the vehicle is converted from being driven by the motor to being driven by the engine;

[0042] Obtain the real-time road condition information and the running stage of the vehicle, and perform real-time adjustment on the motor and the engine according to the real-time road condition information and the running stage.

[0043] In some embodiments of the present invention, the real-time adjustment of the motor and the engine according to the real-time road condition information and the running stage includes:

[0044] When the vehicle is in the starting stage, it is determined that the priority of the motor is greater than the priority of the engine, the vehicle is driven by the motor, and the engine stops running;

[0045] When the vehicle is in the acceleration stage, the motor and the engine work together to enable the vehicle to obtain the maximum torque;

[0046] When the vehicle is in the cruising stage, determine the driving mode of the vehicle according to the real-time road condition information and the remaining battery power;

[0047] When the real-time road condition information indicates a flat road, the priority of the motor drive is higher than that of the engine. When the real-time road condition information indicates an uphill slope, the motor and the engine work together. When the real-time road condition information indicates a downhill slope, the vehicle enters the energy recovery mode;

[0048] When the real-time road condition information indicates a congested section, the driving state of the vehicle is adjusted to motor drive;

[0049] When the real-time road condition information indicates a highway section, the driving state of the vehicle is engine drive, and the motor drive assists the vehicle in accelerating and climbing slopes.

[0050] In a second aspect, an embodiment of the present invention provides a hybrid vehicle energy management device, including at least one control processor and a memory communicatively connected to the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the hybrid vehicle energy management method as described in the first aspect above.

[0051] In a third aspect, an embodiment of the present invention provides an electronic device, including the hybrid vehicle energy management device as described in the second aspect above.

[0052] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, storing computer-executable instructions for executing the hybrid vehicle energy management method as described in the first aspect above.

[0053] The hybrid vehicle energy management method according to the embodiment of the present invention has at least the following beneficial effects:

[0054] Obtain the real-time traffic information and configuration information of the vehicle, calculate the required power and required torque of the vehicle according to the real-time traffic information and configuration information; calculate the remaining battery power, capacity information and temperature information of the vehicle, calculate the energy consumption of the battery according to the remaining battery power, capacity information and temperature information to obtain the energy consumption information of the battery; obtain the power parameters of the vehicle, calculate the actual power and actual torque of the vehicle according to the energy consumption information and power parameters; calculate the actual energy consumption of the vehicle according to the actual power and actual torque, formulate an energy distribution strategy according to the actual energy consumption; construct a dynamic programming algorithm, and the dynamic programming algorithm distributes the power of the engine and the motor of the vehicle according to the energy distribution strategy. According to the technical solution of this embodiment, through the real-time interaction of the vehicle network, the vehicle can judge the road conditions of the planned section and complete the efficient energy distribution according to the processed information, thereby reducing the energy consumption of the hybrid vehicle and further reducing environmental pollution. Description of the Drawings

[0055] Figure 1 is a flowchart of an energy management method for a hybrid vehicle provided by an embodiment of the present invention;

[0056] Figure 2 is a flowchart of calculating the required power and required torque of a vehicle provided by an embodiment of the present invention;

[0057] Figure 3 is a flowchart of calculating the actual power and actual torque of a vehicle provided by an embodiment of the present invention;

[0058] Figure 4 is a flowchart of calculating the remaining battery power, capacity information, and temperature information of a vehicle provided by an embodiment of the present invention;

[0059] Figure 5 is a flowchart of formulating an energy distribution strategy according to actual energy consumption provided by an embodiment of the present invention;

[0060] Figure 6 is a flowchart of a dynamic programming algorithm for power distribution of the engine and motor of a vehicle according to an energy distribution strategy provided by an embodiment of the present invention;

[0061] Figure 7 is a flowchart of real-time adjustment of the motor and engine according to real-time road condition information and operation stages provided by an embodiment of the present invention;

[0062] Figure 8 is a structural diagram of an energy management device for a hybrid vehicle provided by another embodiment of the present invention. Detailed Embodiment

[0063] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0064] In the description of the present invention, it should be understood that for the orientation description, such as up, down, front, back, left, right, etc., the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0065] In the description of the present invention, "several" means one or more, "multiple" means more than two, "greater than", "less than", "exceeding", etc. are understood not to include the present number, and "above", "below", "within", etc. are understood to include the present number. If the first and the second are described, it is only for the purpose of distinguishing technical features and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0066] In the description of the present invention, unless otherwise clearly defined, terms such as "set", "install", "connect", etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0067] The embodiment of the present invention provides an energy management for a hybrid vehicle, which is applied to an intelligent transportation system. The intelligent transportation system includes a traffic information collection module, a navigation module, a vehicle networking control module, and a cloud computing processing platform. The vehicle networking control module is respectively connected to the cloud computing processing platform and the information publishing module, and the information publishing module is also connected to the information collection module. The navigation module is respectively connected to the traffic information collection module and the vehicle networking control module. The vehicle networking control module includes a vehicle data collection unit, a vehicle control unit, a power unit, and a storage unit. The vehicle control unit is respectively connected to the vehicle data collection unit and the power unit, and the storage unit is used to store vehicle driving data.

[0068] Specifically, the traffic information collection module includes, but is not limited to, a GPS in-vehicle navigation instrument, an infrared radar detection device, a vehicle passing electronic information card, etc., and obtains the real-time traffic information of the location where the vehicle is located through traffic information. The navigation module is used to navigate the vehicle and obtain the route information that the vehicle may travel. The vehicle data collection unit is a plurality of vehicle sensors, which are used to obtain parameters such as the acceleration, driving speed, road gradient, and temperature information of the power unit of the vehicle. The vehicle control unit is used to process the information obtained by the vehicle data collection unit and perform control execution on the obtained information. After the vehicle control unit obtains the information obtained by the data collection unit, the obtained information is encrypted and transmitted to the cloud computing processing platform, and the cloud computing processing platform performs an optimized calculation of energy management, and sends the calculated control instruction to the vehicle control unit to control the generator and the engine of the vehicle to work, so as to complete the energy optimization and vehicle control of the vehicle.

[0069] Further, based on conditions such as the real-time road conditions of the vehicle, the operating conditions of the vehicle engine, the operating conditions of the motor, the current battery power and temperature, etc., this embodiment gives the optimal energy management analysis strategy of the vehicle through a preset optimization algorithm (such as the Bellman optimality principle). The storage unit can store the finally obtained optimization results for comparison with similar road conditions or driving scenarios, and optimize the vehicle energy management calculation algorithm through continuous learning and training.

[0070] Further, an information transmission encryption algorithm is set between each module to protect the information transmission during the vehicle driving process. The specific encryption algorithm is as follows:

[0071] Select the first prime number and the second prime number. Specifically, the first prime number is Pp and the second prime number is Qq;

[0072] Calculate the first assignment number and the second assignment number according to the first prime number and the second prime number;

[0073] That is, N = P×Q, n = p×q, ∮(N) = (P - 1)(Q - 1), ∮(n) = (p - 1)(q - 1)

[0074] Among them, ∮(N) is the first assignment number and ∮(n) is the second assignment number;

[0075] Select a public key that is relatively prime to the first assignment number and the second assignment number;

[0076] Among them, the public key is Ee, E is relatively prime to ∮(N), and e is relatively prime to ∮(n);

[0077] Calculate the private key according to the public key, the first assignment number and the second assignment number.

[0078] Among them, the private key is Dd, and the private key satisfies E×D = 1 mod ∮(N), e×d = 1 mod ∮(n);

[0079] It should be noted that the encryption process is: C = ME mod N, c = me mod n;

[0080] The decryption process is M = Cd mod n, m = cd mod n.

[0081] Next, based on the accompanying drawings, the control method of the embodiment of the present invention will be further elaborated.

[0082] Refer to Figure 1 , Figure 1 which is a flowchart of a hybrid vehicle energy management method provided by an embodiment of the present invention. The hybrid vehicle energy management method includes but is not limited to the following steps:

[0083] Step S11: Obtain the real-time traffic information and configuration information of the vehicle, and calculate the required power and required torque of the vehicle according to the real-time traffic information and configuration information.

[0084] It should be noted that the traffic information collection module obtains the real-time position and speed of the vehicle, combines the map data in the navigation module, and predicts the road conditions ahead of the vehicle (such as slopes, curves, etc.). When the vehicle is connected to the network, the vehicle networking control module can obtain vehicle information and real-time road condition information (such as congestion, accidents, etc.); the vehicle data collection unit identifies road signs and obstacles through cameras and radars, so that the vehicle networking control module can adjust the energy distribution of the power unit according to the real-time traffic information.

[0085] Furthermore, the vehicle networking control module is also provided with a battery management unit, which is used to monitor the voltage, current, temperature and state of charge of the battery in real time to ensure that the vehicle's battery operates within the range of various indicators.

[0086] It should be noted that the power unit can also monitor parameters such as the engine speed, load, temperature, combustion efficiency and knocking conditions in real time, as well as data such as the motor speed, torque and temperature, and send the obtained engine parameter data and motor parameter data to the battery management unit, so that the vehicle networking control module can optimize the engine operating state and evaluate the load and efficiency of the motor.

[0087] It should be noted that the vehicle data collection unit is provided with a vehicle speed sensor, a brake sensor and an air conditioner sensor. The vehicle speed sensor is used to monitor the vehicle speed, and the vehicle networking control module adjusts the energy distribution. The brake sensor is used to monitor the vehicle braking state to help the power unit recover energy during braking. The air conditioner sensor is used to monitor the air conditioner load to help the vehicle optimize the energy distribution data processing and optimization.

[0088] Step S12: Calculate the remaining battery power, capacity information and temperature information of the vehicle, and calculate the energy consumption of the battery according to the remaining battery power, capacity information and temperature information to obtain the battery energy consumption information.

[0089] It should be noted that according to the remaining battery power and energy consumption information, the battery management unit can more accurately control the energy distribution between the engine and the motor. By mastering the energy consumption of the battery in real time, the battery management unit can intelligently select the pure electric mode, hybrid mode or engine direct drive mode to adapt to different driving needs and road conditions, thereby improving the overall energy utilization efficiency.

[0090] Furthermore, by monitoring the remaining battery power and temperature information, the battery management unit can prevent the battery from overcharging or over-discharging. By monitoring the temperature information of the battery, the battery management unit can intelligently adjust the cooling or heating system to keep the battery operating within the optimal temperature range, thereby extending the battery's service life.

[0091] Step S13: Obtain the vehicle's power parameters, and calculate the actual power and actual torque of the vehicle based on the energy consumption information and power parameters.

[0092] It should be noted that by calculating the actual power and actual torque of the vehicle, the vehicle control unit can more accurately determine the power demand under the current driving conditions, thereby optimizing the energy distribution between the engine and the motor. By calculating the actual power and actual torque in real time, the vehicle can respond more quickly to the driver's operation instructions. When rapid acceleration or overtaking is required, the vehicle control unit can immediately adjust the power output to provide effective power support. By monitoring the actual power and actual torque in real time, it can effectively prevent the engine and the motor from overloading. When the power output approaches the limit value, the vehicle control unit will take timely measures, such as restricting the throttle pedal opening or starting the protection mode, to protect the safety of the power unit.

[0093] Step S14: Calculate the actual energy consumption of the vehicle based on the actual power and actual torque, and formulate an energy distribution strategy according to the actual energy consumption.

[0094] It should be noted that by accurately calculating the actual energy consumption, the energy management system can more precisely understand the energy demand under the current driving conditions, thereby optimizing the energy distribution between the engine and the motor and avoiding unnecessary energy losses. Based on the real-time calculated actual power and actual torque, the energy management system can quickly adjust the power output to meet the actual driving needs of the vehicle and intelligently select the most suitable driving mode for the current driving conditions. For example, on congested urban roads, the system can select the pure electric mode or the hybrid mode to reduce fuel consumption and exhaust emissions; on highways, the system can select the engine direct drive mode to improve driving efficiency and stability.

[0095] Step S15: Construct a dynamic programming algorithm, and the dynamic programming algorithm distributes the power between the vehicle's engine and motor according to the energy distribution strategy.

[0096] It should be noted that power distribution is carried out through a dynamic programming algorithm to optimize the operating points of the engine and the motor, enabling the vehicle to potentially operate within an efficient and energy-saving range. The dynamic programming algorithm takes into account the state of health and service life of the battery, and reduces the overcharging and over-discharging of the battery by optimizing the power distribution strategy, thereby extending the service life of the battery. Exemplarily, when the battery power is low, the dynamic programming algorithm can limit the power output of the motor to avoid over-discharging the battery; when the battery power is high, more power can be provided by the motor to reduce the load on the engine. In addition, the dynamic programming algorithm has strong adaptability and can formulate different energy distribution strategies according to different driving conditions (such as urban roads, highways, mountain roads, etc.) and vehicle parameters (such as vehicle weight, air resistance coefficient, etc.) to ensure that the hybrid vehicle can maintain the best performance and fuel economy under various conditions.

[0097] It should be noted that in this embodiment, through the real-time interaction of the vehicle networking, the vehicle can judge the road conditions of the planned section and complete the efficient energy distribution according to the processed information, thereby reducing the energy consumption of the hybrid vehicle and further reducing environmental pollution.

[0098] It should be noted that the path planning in this embodiment specifically includes dynamic path planning: adjusting the driving path according to the real-time road conditions to avoid congested or dangerous sections. Multi-objective optimization: finding the optimal path among multiple objectives such as time, energy consumption, and comfort.

[0099] The speed control specifically includes: Adaptive Cruise Control (ACC): automatically adjusting the vehicle speed according to the speed of the vehicle ahead and the road conditions. Speed limit reminder: reminding the driver to adjust the vehicle speed according to the road speed limit and the road conditions.

[0100] The driving mode selection specifically includes energy management: selecting the optimal driving mode (such as pure electric, hybrid, etc.) according to the road conditions and energy consumption prediction. Driving style adjustment: adjusting parameters such as acceleration and braking according to the road conditions and the driver's preferences.

[0101] The safety warning specifically includes collision warning: sending a warning to the driver when a collision risk is detected. Lane departure warning: reminding the driver to correct the direction when the vehicle deviates from the lane.

[0102] The specific application scenarios of this embodiment include urban traffic signal optimization: adjusting the vehicle speed according to the traffic signal information to reduce the waiting time. Congestion avoidance: selecting the optimal path to avoid congestion according to the real-time congestion information.

[0103] Highway platoon cooperation: realizing platoon cooperative driving through V2V communication to improve the traffic efficiency. Accident warning: obtaining accident information in advance and adjusting the vehicle speed and lane.

[0104] Adverse weather road condition warning: Obtain information such as road slipperiness and icing, and adjust driving strategies. Visibility assistance: Obtain the road conditions ahead through V2I communication to make up for insufficient visibility.

[0105] Furthermore, constructing the dynamic programming algorithm specifically includes multi-objective optimization; objective functions: minimizing fuel consumption, minimizing power consumption, maximizing power performance, and minimizing emissions. Optimization algorithms: Use algorithms such as the equivalent fuel consumption minimum strategy (ECMS) and dynamic programming (DP) to achieve multi-objective optimization.

[0106] Based on road condition prediction: Adjust the energy distribution in advance according to the predicted road conditions (such as uphill and downhill, etc.); based on driving prediction: Adjust the energy distribution in advance according to the predicted driving behaviors (such as frequent acceleration, etc.).

[0107] In addition, in one embodiment, referring to Figure 2 , in Figure 1 the step S11 of the illustrated embodiment, it further includes but is not limited to the following steps:

[0108] Step S21, obtain the air density, wind resistance coefficient and vehicle frontal area during vehicle driving, and calculate the air resistance of the vehicle according to the air density, wind resistance coefficient and vehicle frontal area;

[0109] Step S22, obtain the wheel rolling resistance, vehicle mass, gravitational acceleration and road gradient of the vehicle, and calculate the rolling resistance of the vehicle according to the wheel rolling resistance, vehicle mass, gravitational acceleration and road gradient;

[0110] Step S23, calculate the gradient resistance of the vehicle according to the vehicle mass, gravitational acceleration and road gradient;

[0111] Step S24, obtain the vehicle acceleration of the vehicle, and calculate the acceleration resistance of the vehicle according to the vehicle acceleration and vehicle mass;

[0112] Step S25, calculate the total resistance of the vehicle according to the air resistance, rolling resistance, gradient resistance and acceleration resistance;

[0113] Step S26, obtain the real-time driving speed and vehicle transmission efficiency of the vehicle, and calculate the vehicle demand power according to the real-time driving speed, vehicle transmission efficiency and total resistance;

[0114] Step S27, obtain the wheel radius of the vehicle, and calculate the wheel angular velocity of the vehicle according to the wheel radius and real-time driving speed;

[0115] Step S28, calculate the demand torque of the vehicle according to the demand power, vehicle transmission efficiency and wheel angular velocity.

[0116] It should be noted that the air resistance of the vehicle is expressed by the following first formula:

[0117]

[0118] Among them, for F air air resistance, ρ air density, C d is the wind resistance coefficient, A is the frontal area of the vehicle, v is the vehicle speed; the rolling resistance of the vehicle is expressed by the following second formula:

[0119] F roll = C r × m × g × cosθ;

[0120] Among them, F roll is the rolling resistance, C r is the rolling resistance coefficient, m is the vehicle mass, g is the acceleration due to gravity, θ is the road slope;

[0121] The gradient resistance of the vehicle is expressed by the following third formula:

[0122] F grade = m × g × sinθ;

[0123] Among them, F grade is the gradient resistance;

[0124] The acceleration resistance of the vehicle is expressed by the following fourth formula:

[0125] F acc = m × a;

[0126] Among them, F acc is the acceleration resistance;

[0127] The total resistance of the vehicle is expressed by the following fifth formula:

[0128] F total = F air + F roll + F grade + F acc ;

[0129] Among them, F total is the total resistance;

[0130] The required torque of the vehicle is expressed by the following sixth formula:

[0131]

[0132] Among them, P demand is the required power, η is the vehicle transmission efficiency, ω is the wheel angular velocity.

[0133] In addition, in one embodiment, referring to Figure 3 , in Figure 1In step S13 of the illustrated embodiment, it further includes but is not limited to the following steps:

[0134] Step S31, obtaining the transmission efficiency of the vehicle;

[0135] Step S32, obtaining the engine power and motor power of the vehicle, and calculating the actual power of the vehicle according to the engine power, motor power and transmission efficiency;

[0136] Step S33, obtaining the engine torque and motor torque of the vehicle, and calculating the actual torque of the vehicle according to the engine torque, motor torque and transmission efficiency.

[0137] It should be noted that in a hybrid vehicle, the engine and the motor are the main power sources. Calculating the actual power and actual torque of the vehicle helps to optimize the energy management strategy, achieve reasonable power distribution between the engine and the motor, and improve the energy utilization efficiency of the vehicle. Further, through the actual power and actual torque, the vehicle control unit can intelligently select the most suitable driving mode under the current road conditions, such as pure electric mode, hybrid mode or direct drive mode, to adapt to different driving requirements and reduce unnecessary power losses, thereby improving the fuel economy of the vehicle.

[0138] It should be noted that the calculation of the actual power of the vehicle is expressed by the following seventh formula:

[0139] P actual =(P ice +P tm )×η;

[0140] Wherein, P ice is the engine power, P tm is the motor power;

[0141] The calculation of the actual torque of the vehicle is expressed by the following eighth formula:

[0142] T actual =(T ice +T tm )×η;

[0143] Wherein, T ice is the engine torque, T tm is the motor torque;

[0144] It should be noted that the actual power of the vehicle is the sum of the engine power and the motor power, and the actual torque is the sum of the engine torque and the motor torque. Since the transmission efficiency of the vehicle will affect the output of the actual power and actual torque of the vehicle, the actual power and actual torque need to consider the influence of the transmission efficiency on the vehicle.

[0145] In addition, in an embodiment, referring to Figure 4 , inFigure 1 In step S12 of the illustrated embodiment, it further includes but is not limited to the following steps:

[0146] Step S41, obtain the battery voltage information and battery power information of the vehicle, and calculate the battery current of the vehicle according to the battery voltage information and battery power information;

[0147] Step S42, obtain the initial capacity information and nominal capacity of the battery, and calculate the remaining battery power of the battery according to the initial capacity information, nominal capacity and battery current;

[0148] Step S43, obtain the temperature influence coefficient and aging influence coefficient of the battery, and calculate the battery capacity of the battery according to the temperature influence coefficient, aging influence coefficient and nominal capacity of the battery;

[0149] Step S44, obtain the internal resistance of the battery, and calculate the Joule heat of the battery according to the internal resistance of the battery and the battery current;

[0150] Step S45, obtain the heat dissipation coefficient, battery surface area and ambient temperature of the battery, and calculate the battery temperature of the battery according to the heat dissipation coefficient, battery surface area, ambient temperature and Joule heat;

[0151] Step S46, adjust the remaining battery power, battery capacity and battery temperature according to the required power and required torque until the charging power, discharging power and energy output efficiency of the battery reach the energy distribution strategy.

[0152] It should be noted that when the required power is low and the battery capacity is lower than the set threshold, the engine is preferentially started to charge the battery. During the charging process, the charging power is adjusted according to the temperature and charging current of the battery to avoid overcharging and overheating of the battery. When the battery capacity is close to the upper limit, the charging power of the battery is gradually reduced to protect the battery; when the vehicle's required power is high and the battery capacity is high, the battery is preferentially used for discharging. During the discharging process, the torque output of the motor and the engine is reasonably distributed according to the required torque and the battery performance curve.

[0153] Furthermore, according to the charge-discharge characteristic curve of the battery, a reasonable charge-discharge rate range is set to avoid damage to the battery capacity caused by high-rate charge and discharge. The thermal management device of the power unit is used to maintain the battery within an appropriate operating temperature range (usually 15°C - 35°C), slowing down the attenuation of the battery capacity. When the battery temperature is too high, the cooling device (such as liquid cooling, air cooling, etc.) is started to lower the battery temperature. According to the heat generation of the battery and the ambient temperature, the power and flow rate of the cooling system are adjusted to ensure that the battery temperature is within a safe range. When the battery temperature is too low, the heating device (such as PTC heater, heat pump, etc.) is started to raise the battery temperature. According to the heating requirement of the battery and the ambient temperature, the power and temperature setting of the heating system are adjusted to avoid overheating and excessive energy consumption. Through reasonable battery capacity regulation, capacity management, and temperature control, the battery is ensured to work in the best state, improving the energy utilization efficiency of the hybrid vehicle, reducing the working time of the battery under harsh conditions such as high-rate charge and discharge, high temperature, and low temperature, reducing the battery capacity attenuation rate, and extending the battery service life. By optimizing the energy management strategy, unnecessary energy losses and emissions are reduced, achieving the energy conservation and emission reduction goals of the hybrid vehicle.

[0154] It should be noted that the battery current of the vehicle is calculated by the following ninth formula:

[0155]

[0156] Where P demand is the required power, V battery is the battery voltage, and I battery is the battery current;

[0157] The required power of the vehicle is calculated by the following tenth formula:

[0158] P demand = V battery × I battery ;

[0159] Where p demand is the required power, V battery is the battery voltage, and I battery is the battery current;

[0160] The remaining battery charge is calculated by the following eleventh formula:

[0161]

[0162] Where SOC(t) is the remaining battery charge, SOC0 is the initial battery capacity, C nominal is the nominal battery capacity, is the real-time battery current;

[0163] Calculate the capacity of the battery, which is expressed by the following twelfth formula:

[0164] C actual = C nominal × f temp × f aging ;

[0165] Wherein, C actual is the battery capacity, f temp is the temperature influence coefficient, f aging is the aging influence coefficient;

[0166] Calculate the temperature of the battery, which is expressed by the following thirteenth formula:

[0167]

[0168] Wherein, T battery is the battery temperature, T ambient is the ambient temperature, is the battery current, R internal is the battery internal resistance, h is the heat dissipation coefficient, and A is the battery surface area;

[0169] In addition, in one embodiment, referring to Figure 5 , in Figure 1 the step S14 of the illustrated embodiment, it further includes but is not limited to the following steps:

[0170] Step S51, obtain the real-time output power of the vehicle's engine, the engine thermal efficiency, and the low calorific value of the fuel, and calculate the fuel consumption of the vehicle according to the real-time output power of the engine, the low calorific value, and the engine power;

[0171] Step S52, obtain the motor power and motor efficiency of the vehicle, and calculate the motor electrical energy consumption of the vehicle according to the motor power and motor efficiency;

[0172] Step S53, obtain the equipment energy consumption and working time of the vehicle, and calculate the equipment energy consumption of the vehicle according to the equipment energy consumption and working time;

[0173] Step S54, calculate the total energy consumption of the vehicle according to the fuel consumption, electrical energy consumption, low calorific value, and equipment energy consumption;

[0174] Step S55, perform energy distribution on the vehicle according to the total energy consumption and the energy distribution strategy.

[0175] It should be noted that global optimization algorithms such as dynamic programming are used to globally optimize the energy distribution during the vehicle's driving. By predicting future driving information, the optimal energy distribution strategy for the whole journey is calculated to achieve the best fuel economy and emission performance within the global scope of the vehicle.

[0176] It should be noted that the fuel consumption of the vehicle is expressed by the following fourteenth formula:

[0177]

[0178] Wherein, m fuel is the fuel consumption, η ice is the thermal efficiency, and LHV is the lower heating value;

[0179] The electrical energy consumption of the motor is expressed by the following fifteenth formula:

[0180]

[0181] Wherein, E tm is the electrical energy consumption, and η tm is the motor efficiency;

[0182] The equipment energy consumption of the vehicle is expressed by the following sixteenth formula:

[0183] E aum = ∑P aux × t;

[0184] Wherein, E aux is the energy consumption, P aux is the equipment energy consumption, and t is the working time;

[0185] The total energy consumption of the vehicle is expressed by the following seventeenth formula:

[0186] E total = m fuel × LHV + E tm + E aux .

[0187] In addition, in one embodiment, referring to Figure 6 , in Figure 1 step S15 of the embodiment shown, it further includes but is not limited to the following steps:

[0188] Step S61, obtain the load demand information and vehicle speed information of the vehicle, and determine the working mode of the vehicle according to the load demand, vehicle speed information and remaining battery power;

[0189] Step S62, when the vehicle speed information is in the first driving speed range, the load demand is in the first load demand range, and the remaining battery power is in the first remaining battery power range, the vehicle is in pure electric mode, the vehicle is driven by the motor, and the engine of the vehicle stops working;

[0190] Step S63, when the vehicle speed information is in the second driving speed range, the load demand is in the second load demand range, and the remaining battery power is in the second remaining battery power range, the vehicle is in hybrid mode, and the engine and the motor work together;

[0191] Step S64, when the vehicle speed information is in the third driving speed range, the load demand is in the third load demand range, and the remaining battery power is in the third remaining battery power range, the vehicle is in engine drive mode, the vehicle is driven by the engine, the motor stops working, and the battery is charged at the same time;

[0192] Step S65, when the vehicle brakes or decelerates, the vehicle is in energy recovery mode, and the vehicle is converted from being driven by the motor to being driven by the engine;

[0193] Step S66, obtain the real-time road condition information and the running stage of the vehicle, and perform real-time adjustment on the motor and the engine according to the real-time road condition information and the running stage.

[0194] It should be noted that obtaining real-time road condition information includes communication between vehicles, communication between vehicles and infrastructure, communication between vehicles and the cloud, and communication between vehicles and pedestrian mobile devices. Specifically, communication between vehicles shares real-time information such as vehicle speed, position, and acceleration through V2V communication, and cooperates with multiple vehicles to sense the road conditions ahead (such as congestion, accidents, construction, etc.), so as to complete information sharing between vehicles; communication between vehicles and infrastructure includes obtaining signal phase and timing information from traffic lights and obtaining road conditions (such as slippery, icy, obstacles, etc.) from roadside units; communication between vehicles and the cloud obtains the global traffic conditions (such as congestion hotspots, accident distribution, etc.) from the cloud, and predicts future road condition changes based on historical data and real-time data; communication between vehicles and pedestrian mobile devices obtains pedestrian positions and movement trajectories through smartphones or wearable devices to avoid collisions.

[0195] Furthermore, fuse the data obtained above to form comprehensive road condition information, and ensure that the data from different sources are synchronized in time, so as to avoid information lag. Predict road condition changes within the next few minutes based on the current road conditions and vehicle behavior, and predict road condition trends within the next few hours based on historical data and weather information. The vehicle networking control module evaluates whether there is a collision risk in the front section of the road (such as sudden braking, pedestrians crossing the road, etc.), and evaluates whether the road conditions are safe (such as slippery, icy, etc.).

[0196] It should be noted that the first driving speed range, the second driving speed range, and the third driving speed range increase in sequence, the first load demand range, the second load demand range, and the third load demand range increase in sequence, and the first remaining battery power range, the second remaining battery power range, and the third remaining battery power range decrease in sequence.

[0197] Based on the predicted energy demand and vehicle state, the EMS will formulate the following energy distribution strategies

[0198] The pure electric mode specifically includes applicable scenarios: low-speed driving, low load demand, and high SOC. Energy distribution: Only use the motor for driving, and the engine does not work. Advantages: Zero emissions, low noise.

[0199] The hybrid mode specifically includes applicable scenarios: medium-speed driving, medium load demand, and moderate SOC. Energy distribution: The engine and the motor work together, and the power distribution is dynamically adjusted according to the demand. Advantages: Balanced fuel economy and power performance.

[0200] The engine drive mode specifically includes applicable scenarios: high-speed driving, high load demand, and low SOC. Energy distribution: Only use the engine for driving, and charge the battery at the same time. Advantages: Suitable for long-term high-speed driving.

[0201] The energy recovery mode specifically includes applicable scenarios: when braking or decelerating. Energy distribution: The motor is converted into a generator, and the kinetic energy is converted into electrical energy and stored in the battery. Advantages: Improve energy utilization efficiency.

[0202] Furthermore, the vehicle networking control module can dynamically adjust the energy distribution based on road condition changes, according to real-time road conditions (such as sudden congestion, accidents, etc.), and dynamically adjust the energy distribution based on the driver's driving behavior (such as sudden acceleration, sudden braking, etc.).

[0203] In addition, in one embodiment, referring to Figure 7 , in Figure 6 the step S66 of the illustrated embodiment, it further includes but is not limited to the following steps:

[0204] Step S71, when the vehicle is in the starting stage, it is determined that the priority of the motor is greater than that of the engine, and the vehicle is driven by the motor while the engine stops running;

[0205] Step S72, when the vehicle is in the acceleration stage, the motor and the engine work together to enable the vehicle to obtain the maximum torque;

[0206] Step S73, when the vehicle is in the cruising stage, determine the driving mode of the vehicle according to the real-time road condition information and the remaining battery power;

[0207] Step S74, when the real-time road condition information is a flat road, the priority of motor drive is greater than that of the engine. When the real-time road condition information is an uphill slope, the motor and the engine work together. When the real-time road condition information is a downhill slope, the vehicle enters the energy recovery mode;

[0208] Step S75, when the real-time road condition information is a congested section, adjust the driving state of the vehicle to motor drive;

[0209] Step S76: When the real-time traffic condition information is for a highway section, set the driving state of the vehicle to engine drive, and the motor drives to assist the vehicle in accelerating and climbing slopes.

[0210] It should be noted that when the vehicle is in the starting stage, since the motor has high efficiency at low speeds and is suitable for starting, the vehicle preferentially uses motor drive and the engine does not work; when the vehicle is in the acceleration stage, in order to meet the vehicle's acceleration requirements and avoid engine overload, the vehicle's engine and motor work together to provide the maximum torque; when the vehicle is in the cruising state, the optimal driving mode of the vehicle needs to be selected according to the road conditions and the remaining battery capacity. When the vehicle is driving on a flat road, motor drive is preferentially used. When the vehicle is driving on an uphill road, the engine and motor work together. When the vehicle is driving on a downhill road, since the vehicle needs to balance energy consumption and power demand, the vehicle enters the energy recovery mode.

[0211] When the vehicle is in the braking stage, since the vehicle needs to recover braking energy to improve the vehicle's energy utilization efficiency, the vehicle enters the energy recovery mode and is converted from motor drive to generator drive; when the vehicle is driving in a congested section, since it is necessary to reduce the idling loss of the vehicle's engine and reduce emissions, the vehicle preferentially uses motor drive and the engine remains off. When the vehicle is driving on a highway section, since the engine has high efficiency at high speeds and is suitable for long-term high-speed driving, the vehicle's power unit preferentially uses engine drive, and the motor assists in accelerating or climbing slopes.

[0212] In this embodiment, the energy optimization of the vehicle is modeled as a multi-objective optimization problem to predict the vehicle's power demand. The constructed objectives include but are not limited to minimizing fuel consumption, minimizing power consumption, maximizing power performance, and minimizing emissions, and the objectives are constructed by building constraint conditions.

[0213] First, calculate the total energy consumption of the vehicle, which is expressed by the following eighteenth formula:

[0214] j = ∑(m fuel + m elec );

[0215] Where j is the total energy consumption, m fuel is the fuel consumption, and m elec is the equivalent power consumption;

[0216] The constructed constraint conditions include:

[0217] Battery remaining capacity range: SOC min ≤ SOC ≤ SOC max ;

[0218] Power limits of the engine and motor:

[0219] P eng，min ≤ P emg ≤ P eng，max ,P motor，min ≤ P motor ≤ P motor，max

[0220] Vehicle power demand: P demand = P eng + P motor 。

[0221] In this embodiment, the optimal energy distribution and real-time optimization of the vehicle are completed through learning training and optimizing the real-time calculation algorithm. The specific process is as follows:

[0222] Collect real-time data from the vehicle data acquisition unit (such as engines, motors, batteries, GPS, etc.), accumulate historical driving data through the storage unit, including road conditions, driving behaviors, energy consumption, etc., and obtain external environment data (such as traffic conditions, weather, etc.) through the traffic information acquisition module.

[0223] Perform data preprocessing operations on the collected data to remove noise, outliers, and missing data. Label the data (such as driving mode, energy consumption label, etc.) for use in supervised learning, and extract useful features (such as average speed, acceleration, slope, etc.) from the collected data. Standardize the data so that the model can converge better.

[0224] Select traditional machine learning models, including but not limited to decision trees, random forests, support vector machines, etc. applicable to small-scale data sets. Select deep learning models suitable for processing time series data and high-dimensional data, such as neural networks (RNN, LSTM, Transformer, etc.); strengthen the learning model through those applicable to dynamic decision-making, such as Q-learning, deep Q network (DQN).

[0225] Use the labeled data to train the model so that it can predict energy demand or optimization strategies, conduct supervised training on the model, and discover potential patterns in the data through clustering or dimensionality reduction methods. Train the model through a simulated environment so that the model can make optimal decisions in a dynamic environment.

[0226] Define the optimization objective (such as minimizing energy consumption, maximizing efficiency, etc.), construct a loss function; use optimization algorithms such as gradient descent, Adam, etc. to adjust the model parameters to optimize the algorithm; evaluate the model performance through cross-validation to prevent overfitting.

[0227] Tune the parameters of the model, including traversing hyperparameter combinations to find the optimal parameters. Use probability models to guide hyperparameter search to improve efficiency. Optimize the parameters through simulating the evolutionary process.

[0228] Remove redundant parameters, reduce the amount of computation, convert floating-point parameters to low-precision values, reduce the computational complexity, use a large model to guide the training of a small model, improve the performance of the small model, and thus complete the compression and acceleration of the model.

[0229] During the operation of the vehicle, update the model parameters in real time to adapt to the dynamic environment, and adjust the algorithm strategy according to the real-time data (such as adjusting the energy distribution ratio) to complete the real-time optimization of the model.

[0230] As Figure 8 shown, Figure 8 is the structural diagram of the hybrid vehicle energy management device provided by an embodiment of the present invention. The present invention also provides a hybrid vehicle energy management device, including:

[0231] A processor 801, which can be implemented in ways such as a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;

[0232] A memory 802, which can be implemented in forms such as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 802 and are called by the processor 801 to execute the hybrid vehicle energy management method of the embodiments of the present application;

[0233] An input / output interface 803, which is used to implement information input and output;

[0234] A communication interface 804, which is used to implement the communication interaction between this device and other devices, and can implement communication through a wired method (such as USB, network cable, etc.) or through a wireless method (such as a mobile network, WIFI, Bluetooth, etc.);

[0235] A bus 805, which transmits information between the various components of the device (such as the processor 801, the memory 802, the input / output interface 803, and the communication interface 804);

[0236] Among them, the processor 801, the memory 802, the input / output interface 803, and the communication interface 804 are communicatively connected to each other inside the device through the bus 805.

[0237] An embodiment of the present application further provides an electronic device, including the hybrid vehicle energy management device as described above.

[0238] An embodiment of the present application further provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned hybrid vehicle energy management method is implemented.

[0239] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include memories remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above-mentioned network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and may be located in one place, or may be distributed to 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.

[0240] Those of ordinary skill in the art will understand that all or some of the steps and systems disclosed in the above methods can be implemented as software, firmware, hardware, and their appropriate combinations. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0241] The above is a specific description of the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present invention.

Claims

1. A method for energy management of a hybrid vehicle, characterized in that Including: Connect the vehicle to the network, obtain the real-time traffic information and configuration information of the vehicle, and calculate the required power and required torque of the vehicle according to the real-time traffic information and the configuration information; Calculate the remaining battery power, capacity information and temperature information of the vehicle, and calculate the energy consumption of the battery according to the remaining battery power, the capacity information and the temperature information to obtain the energy consumption information of the battery; Obtain the power parameters of the vehicle, and calculate the actual power and actual torque of the vehicle according to the energy consumption information and the power parameters; Calculate the actual energy consumption of the vehicle according to the actual power and the actual torque, and formulate an energy distribution strategy according to the actual energy consumption; Construct a dynamic programming algorithm, and the dynamic programming algorithm distributes the power of the vehicle's engine and motor according to the energy distribution strategy.

2. The hybrid vehicle energy management method according to claim 1, characterized in that The calculating the required power and required torque of the vehicle according to the real-time traffic information and the configuration information includes: Obtain the air density, wind resistance coefficient and vehicle frontal area of the vehicle during driving, and calculate the air resistance of the vehicle according to the air density, the wind resistance coefficient and the vehicle frontal area; Obtain the rolling resistance of the vehicle's wheels, vehicle mass, gravitational acceleration and road gradient, and calculate the rolling resistance of the vehicle according to the rolling resistance of the vehicle's wheels, the vehicle mass, the gravitational acceleration and the road gradient; Calculate the gradient resistance of the vehicle according to the vehicle mass, the gravitational acceleration and the road gradient; Obtain the vehicle acceleration of the vehicle, and calculate the acceleration resistance of the vehicle according to the vehicle acceleration and the vehicle mass; Calculate the total resistance of the vehicle according to the air resistance, the rolling resistance, the gradient resistance and the acceleration resistance; Obtain the real-time driving speed and vehicle transmission efficiency of the vehicle, and calculate the required power of the vehicle according to the real-time driving speed, the vehicle transmission efficiency and the total resistance; Obtain the wheel radius of the vehicle, and calculate the angular velocity of the vehicle's wheels according to the wheel radius and the real-time driving speed; Calculate the required torque of the vehicle according to the required power, the vehicle transmission efficiency and the angular velocity of the wheels.

3. The energy management method for a hybrid vehicle according to claim 1, characterized in that The calculating the actual power and actual torque of the vehicle according to the energy consumption information and the power parameters includes: Obtain the transmission efficiency of the vehicle; Obtain the engine power and motor power of the vehicle, and calculate the actual power of the vehicle according to the engine power, the motor power and the transmission efficiency; Obtain the engine torque and motor torque of the vehicle, and calculate the actual torque of the vehicle according to the engine torque, the motor torque and the transmission efficiency.

4. The energy management method for a hybrid vehicle according to claim 1, characterized in that, The calculating the remaining battery power, capacity information and temperature information of the vehicle includes: Obtain the battery voltage information and battery power information of the vehicle, and calculate the battery current of the vehicle according to the battery voltage information and the battery power information; Obtain the initial capacity information and nominal capacity of the battery, and calculate the remaining battery power of the battery according to the initial capacity information, the nominal capacity and the battery current; Obtain the temperature influence coefficient and aging influence coefficient of the battery, and calculate the battery capacity of the battery according to the temperature influence coefficient, the aging influence coefficient and the nominal capacity of the battery; Obtain the internal resistance of the battery, and calculate the Joule heat of the battery according to the internal resistance of the battery and the battery current; Obtain the heat dissipation coefficient, battery surface area and ambient temperature of the battery, and calculate the battery temperature of the battery according to the heat dissipation coefficient, the battery surface area, the ambient temperature and the Joule heat; Adjust the remaining battery power, the battery capacity and the battery temperature according to the required power and the required torque until the charging power, the discharging power and the energy output efficiency of the battery reach the energy distribution strategy.

5. The energy management method for a hybrid vehicle according to claim 1, wherein The energy distribution strategy formulated according to the actual energy consumption includes: Obtain the real-time output power of the vehicle's engine, the engine thermal efficiency and the low calorific value of the fuel, and calculate the fuel consumption of the vehicle according to the real-time output power of the engine, the low calorific value and the engine power; Obtain the motor power and motor efficiency of the vehicle, and calculate the motor power consumption of the vehicle according to the motor power and the motor efficiency; Obtain the equipment energy consumption and working time of the vehicle, and calculate the equipment energy consumption of the vehicle according to the equipment energy consumption and the working time; Calculate the total energy consumption of the vehicle according to the fuel consumption, the power consumption, the low calorific value and the equipment energy consumption; Perform energy distribution on the vehicle according to the total energy consumption and the energy distribution strategy.

6. The energy management method for a hybrid vehicle according to claim 1, wherein The dynamic programming algorithm performs power distribution on the vehicle internal combustion engine and the vehicle drive motor according to the energy distribution strategy, including: Obtain the load demand information and vehicle speed information of the vehicle, and determine the working mode of the vehicle according to the load demand, the vehicle speed information and the remaining battery power; When the vehicle speed information is in the first driving speed range, the load demand is in the first load demand range, and the remaining battery power is in the first remaining battery power range, the vehicle is in pure electric mode, the vehicle is driven by the motor, and the engine of the vehicle stops working; When the vehicle speed information is in the second driving speed range, the load demand is in the second load demand range, and the remaining battery power is in the second remaining battery power range, the vehicle is in hybrid mode, and the engine and the motor work together; When the vehicle speed information is in the third driving speed range, the load demand is in the third load demand range, and the remaining battery power is in the third remaining battery power range, the vehicle is in engine drive mode, the vehicle is driven by the engine, the motor stops working, and the battery is charged at the same time; When the vehicle brakes or decelerates, the vehicle is in energy recovery mode, and the vehicle is converted from being driven by the motor to being driven by the engine; Obtain the real-time road condition information and the running stage of the vehicle, and perform real-time adjustment on the motor and the engine according to the real-time road condition information and the running stage.

7. The energy management method for a hybrid vehicle according to claim 6, wherein Performing real-time adjustment on the motor and the engine according to the real-time road condition information and the operation stage includes: When the vehicle is in the starting stage, it is determined that the priority of the motor is higher than that of the engine. The vehicle is driven by the motor and the engine stops running; When the vehicle is in the acceleration stage, the motor and the engine work together to enable the vehicle to obtain the maximum torque; When the vehicle is in the cruising stage, determine the driving mode of the vehicle according to the real-time road condition information and the remaining battery power; When the real-time road condition information is a flat road, the driving priority of the motor is higher than that of the engine. When the real-time road condition information is an uphill slope, the motor and the engine work together. When the real-time road condition information is a downhill slope, the vehicle enters the energy recovery mode; When the real-time road condition information is a congested section, adjust the driving state of the vehicle to be driven by the motor; When the real-time road condition information is a highway section, the driving state of the vehicle is engine-driven, and the motor drive assists the vehicle in accelerating and climbing slopes.

8. An energy management device for a hybrid vehicle, characterized in that, Comprising at least one control processor and a memory for communicatively connecting with the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the hybrid vehicle energy management method according to any one of claims 1 to 7.

9. An electronic device, characterized in that, Comprising the hybrid vehicle energy management device according to claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to execute the hybrid vehicle energy management method according to any one of claims 1 to 7.

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