A hybrid vehicle energy management method, device, equipment and medium

Abstract

This invention proposes a method, device, equipment, and medium for energy management of hybrid vehicles. The method includes acquiring real-time traffic and configuration information of the vehicle; calculating the vehicle's required power and torque based on the real-time traffic and configuration information; calculating the battery's energy consumption based on the battery's remaining charge, capacity, and temperature information; acquiring the vehicle's power parameters; calculating the vehicle's actual power and torque based on the energy consumption information and power parameters; calculating the vehicle's actual energy consumption based on the actual power and torque; formulating an energy allocation strategy based on the actual energy consumption; and constructing a dynamic programming algorithm to allocate power between the vehicle's engine and motor according to the energy allocation strategy. According to the technical solution of this embodiment, through real-time interaction with the vehicle network, the vehicle can efficiently allocate energy based on processed information, reducing the energy consumption and environmental pollution of hybrid vehicles.

Description

Technical Field

[0001] This invention relates to the field of vehicle energy management technology, and in particular to a method, device, equipment and medium for energy management of hybrid vehicles. Background Technology

[0002] As one of the main modes of transportation today, automobiles face pressures from environmental pollution, energy security, the greenhouse effect, and fuel consumption, necessitating optimized energy utilization. Based on technologies such as vehicle-to-everything (V2X) and intelligent transportation, coupled with the inherent peak-shaving and valley-filling advantages of hybrid electric vehicles (HEVs) that utilize multiple energy sources, and real-time interaction between the vehicle and external information, the accuracy and real-time performance of vehicle energy management can be improved, moving beyond the limitations of offline calibration calculations using rule-based algorithms. However, current HEV energy management technologies generally employ rule-based or offline calibration methods, failing to manage vehicle energy in real-time according to factors such as the vehicle's route, traffic conditions, or road gradient. While rule-based algorithms and computational calculations may optimize energy management and achieve energy savings to some extent, they cannot cover real-world driving scenarios. They can only manage energy according to predetermined calibrations or algorithms, failing to allocate energy optimally, leading to energy waste and environmental pollution. Summary of the Invention

[0003] This invention aims to address at least one of the technical problems existing in the prior art. To this end, this invention proposes a hybrid vehicle energy method, apparatus, device, and medium that can allocate vehicle energy on demand, make timely adjustments to the control strategies of the vehicle's engine and motor, reduce vehicle energy waste, and reduce environmental pollution.

[0004] In a first aspect, embodiments of the present invention provide a hybrid vehicle energy management method, comprising:

[0005] The vehicle is connected to the network to obtain real-time traffic information and configuration information, and the required power and torque of the vehicle are calculated based on the real-time traffic information and configuration information.

[0006] Calculate the remaining battery power, capacity information, and temperature information of the vehicle's battery; calculate the energy consumption of the battery based on the remaining battery power, capacity information, and temperature information to obtain the energy consumption information of the battery.

[0007] Obtain the vehicle's power parameters, and calculate the vehicle's actual power and actual torque based on the energy consumption information and the power parameters;

[0008] The actual energy consumption of the vehicle is calculated based on the actual power and the actual torque, and an energy distribution strategy is formulated based on the actual energy consumption.

[0009] A dynamic programming algorithm is constructed, which allocates power between the vehicle's engine and motor according to the energy allocation 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] The air density, drag coefficient, and frontal area of ​​the vehicle during driving are obtained, and the air resistance of the vehicle is calculated based on the air density, drag coefficient, and frontal area.

[0012] The rolling resistance of the vehicle's wheels, vehicle mass, gravitational acceleration, and road slope are obtained, and the rolling resistance of the vehicle is calculated based on the rolling resistance of the wheels, the vehicle mass, the gravitational acceleration, and the road slope.

[0013] The gradient resistance of the vehicle is calculated based on the vehicle mass, the gravitational acceleration, and the road gradient.

[0014] The vehicle acceleration is obtained, and the acceleration drag of the vehicle is calculated based on the vehicle acceleration and the vehicle mass.

[0015] The total resistance of the vehicle is calculated based on the air resistance, rolling resistance, gradient resistance, and acceleration resistance.

[0016] The real-time driving speed and vehicle transmission efficiency of the vehicle are obtained, and the required power of the vehicle is calculated 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] The required torque of the vehicle is calculated 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] The engine power and motor power of the vehicle are obtained, and the actual power of the vehicle is calculated based on the engine power, the motor power and the transmission efficiency;

[0022] The engine torque and motor torque of the vehicle are obtained, and the actual torque of the vehicle is calculated based on the engine torque, the motor torque and the transmission efficiency.

[0023] In some embodiments of the present invention, calculating the remaining battery charge, 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 based on the battery voltage information and battery power information;

[0025] Obtain the initial capacity information and nominal capacity of the battery, and calculate the remaining battery power based on 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 based on 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 based on the internal resistance and the battery current;

[0028] Obtain the heat dissipation coefficient, battery surface area, and ambient temperature of the battery; calculate the battery temperature based on the heat dissipation coefficient, battery surface area, ambient temperature, and Joule heat.

[0029] The remaining battery charge, battery capacity, and battery temperature are adjusted according to the required power and required torque until the battery's charging power, discharging power, and energy output efficiency reach the energy distribution strategy.

[0030] In some embodiments of the present invention, the step of formulating an energy allocation strategy based on the actual energy consumption includes:

[0031] The engine's real-time output power, engine thermal efficiency, and fuel's lower heating value are obtained, and the vehicle's fuel consumption is calculated based on the engine's real-time output power, the lower heating value, and the engine power.

[0032] Obtain the motor power and motor efficiency of the vehicle, and calculate the motor energy consumption of the vehicle based on the motor power and motor efficiency;

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

[0034] The total energy consumption of the vehicle is calculated based on the fuel consumption, the electrical energy consumption, the lower calorific value, and the equipment energy consumption.

[0035] The energy is allocated to the vehicle based on the total energy consumption and the energy allocation strategy.

[0036] In some embodiments of the present invention, the dynamic programming algorithm allocates power between the vehicle's internal combustion engine and the vehicle's drive motor according to the energy allocation strategy, including:

[0037] Obtain the vehicle's load demand information and vehicle speed information, and determine the vehicle's operating mode based on the load demand, vehicle speed information, and 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 pure electric mode, the vehicle is driven by the electric motor, and the vehicle's engine 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 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 engine drive mode. When the vehicle is in engine drive mode, the motor stops working and the battery is charged at the same time.

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

[0042] The system acquires real-time traffic information and the vehicle's operating phase, and adjusts the motor and engine in real time based on the real-time traffic information and the operating phase.

[0043] In some embodiments of the present invention, the step of adjusting the motor and the engine in real time according to the real-time traffic information and the operating stage includes:

[0044] When the vehicle is in the starting phase, if the priority of the electric motor is determined to be higher than that of the engine, the vehicle is driven by the electric motor and the engine stops running.

[0045] When the vehicle is accelerating, the electric motor and the engine work together to enable the vehicle to obtain maximum torque;

[0046] When the vehicle is in the cruising phase, the driving mode of the vehicle is determined based on the real-time traffic information and the remaining battery power.

[0047] When the real-time road condition information indicates a flat road, the priority of the electric motor drive is higher than that of the engine. When the real-time road condition information indicates an uphill slope, the electric 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 traffic information indicates a congested road section, the vehicle's driving state is adjusted to electric motor drive;

[0049] When the real-time traffic information indicates a highway section, the vehicle's driving state is set to engine drive, with the electric motor assisting the vehicle in acceleration and hill climbing.

[0050] In a second aspect, embodiments of the present invention provide a hybrid vehicle energy management device, including at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, the instructions being executed by the at least one control processor to enable the at least one control processor to perform the hybrid vehicle energy management method as described in the first aspect above.

[0051] Thirdly, embodiments of the present invention provide an electronic device including a hybrid vehicle energy management device as described in the second aspect above.

[0052] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer-executable instructions for performing the hybrid vehicle energy management method as described in the first aspect above.

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

[0054] The system acquires real-time traffic and configuration information of the vehicle, calculates the vehicle's required power and torque based on this information, calculates the remaining battery charge, capacity, and temperature, and calculates the battery's energy consumption. It also acquires the vehicle's power parameters, calculates the vehicle's actual power and torque based on the energy consumption information and power parameters, calculates the vehicle's actual energy consumption based on the actual power and torque, and formulates an energy allocation strategy based on the actual energy consumption. A dynamic programming algorithm is constructed, which allocates power between the vehicle's engine and motor according to the energy allocation strategy. According to the technical solution of this embodiment, through real-time interaction with the vehicle network, the vehicle can judge the road conditions of the planned road segment and complete efficient energy allocation based on the processed information, thereby reducing the energy consumption of hybrid vehicles and thus reducing environmental pollution. Attached Figure Description

[0055] Figure 1 This is a flowchart of a hybrid vehicle energy management method provided in one embodiment of the present invention;

[0056] Figure 2 This is a flowchart for calculating the required power and torque of a vehicle according to one embodiment of the present invention;

[0057] Figure 3 This is a flowchart for calculating the actual power and actual torque of a vehicle, provided in one embodiment of the present invention;

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

[0059] Figure 5 This is a flowchart of an embodiment of the present invention for formulating an energy allocation strategy based on actual energy consumption;

[0060] Figure 6 This is a flowchart of a dynamic programming algorithm provided in one embodiment of the present invention, which allocates power between the engine and motor of a vehicle according to an energy allocation strategy.

[0061] Figure 7 This is a flowchart of real-time adjustment of the motor and engine based on real-time road conditions and operating phases, provided by an embodiment of the present invention.

[0062] Figure 8 This is a structural diagram of a hybrid vehicle energy management device provided in another embodiment of the present invention. Detailed Implementation

[0063] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0064] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0065] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0066] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0067] This invention provides a hybrid vehicle energy management system applied to an intelligent transportation system. The intelligent transportation system includes a traffic information collection module, a navigation module, a vehicle-to-everything (V2X) control module, and a cloud computing platform. The V2X control module is connected to both the cloud computing platform and an information publishing module. The information publishing module is also connected to the information collection module. The navigation module is connected to both the traffic information collection module and the V2X control module. The V2X control module includes a vehicle data acquisition unit, a vehicle control unit, a power unit, and a storage unit. The vehicle control unit is connected to both the vehicle data acquisition unit and the power unit. The storage unit stores vehicle driving data.

[0068] Specifically, the traffic information acquisition module includes, but is not limited to, GPS vehicle navigation instruments, infrared radar detection devices, and electronic vehicle access cards. It acquires real-time traffic information about the vehicle's location. The navigation module is used for vehicle navigation and to obtain information about possible routes the vehicle may take. The vehicle data acquisition unit consists of multiple vehicle sensors used to acquire parameters such as vehicle acceleration, speed, road gradient, and power unit temperature. The vehicle control unit processes the information acquired by the vehicle data acquisition unit and executes control commands accordingly. After acquiring the information from the data acquisition unit, the vehicle control unit encrypts the information and transmits it to the cloud computing platform. The cloud computing platform performs energy management optimization calculations and sends the calculated control commands to the vehicle control unit to control the vehicle's generator and engine, thereby completing vehicle energy optimization and vehicle control.

[0069] Furthermore, based on real-time road conditions, engine operation status, motor operation status, current battery charge and temperature, etc., this embodiment provides the optimal energy management analysis strategy for the vehicle through a preset optimization algorithm (such as Bellman optimality principle). The storage unit can store the final optimization results for comparison with similar road conditions or driving scenarios. Through continuous learning and training, the vehicle energy management calculation algorithm is optimized.

[0070] Furthermore, each module is equipped with an information transmission encryption algorithm to protect information transmission during vehicle operation. The specific encryption algorithms are as follows:

[0071] Choose 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 assigned number and the second assigned number based on 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] Where ∮(N) is the first assignment number and ∮(n) is the second assignment number;

[0075] Choose a public key that is coprime to the first and second assigned numbers;

[0076] The public key is Ee, where E is coprime to ∮(N) and e is coprime to ∮(n).

[0077] Calculate the private key based on the public key, the first assignment number, and the second assignment number.

[0078] The private key is Dd, which satisfies E×D=1mod∮(N)e×d=1mod∮(n);

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

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

[0081] The control method of the present invention will be further described below with reference to the accompanying drawings.

[0082] Reference Figure 1 , Figure 1 This is a flowchart of a hybrid vehicle energy management method provided in 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 real-time traffic information and configuration information of the vehicle, and calculate the required power and torque of the vehicle based on the real-time traffic information and configuration information;

[0084] It should be noted that the traffic information collection module acquires the vehicle's real-time location and speed, and combines this with map data from the navigation module to predict road conditions ahead (such as slopes and curves). Once the vehicle is connected to the network, the vehicle network control module can acquire vehicle information and real-time road condition information (such as congestion and accidents). The vehicle data acquisition unit uses cameras and radar to identify road signs and obstacles, enabling the vehicle network control module to adjust the energy distribution of the power unit based on real-time traffic information.

[0085] Furthermore, the vehicle network control module is also equipped with a battery management unit, which is used to monitor the battery's voltage, current, temperature and state of charge 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 engine speed, load, temperature, combustion efficiency, and knocking in real time, as well as data such as motor speed, torque, and temperature. The acquired engine and motor parameter data are sent to the battery management unit, thereby enabling the vehicle network control module to optimize the engine's operating status and evaluate the motor's load and efficiency.

[0087] It should be noted that the vehicle data acquisition unit is equipped with a vehicle speed sensor, a brake sensor, and an air conditioning sensor. The vehicle speed sensor is used to monitor the vehicle speed, and the vehicle network control module adjusts the energy distribution. The brake sensor is used to monitor the vehicle's braking status and help the power unit recover energy during braking. The air conditioning sensor is used to monitor the air conditioning load and help the vehicle optimize energy distribution data processing and optimization.

[0088] Step S12: Calculate the remaining battery power, capacity information and temperature information of the vehicle's battery, and calculate the energy consumption of the battery based on the remaining battery power, capacity information and temperature information to obtain the battery's energy consumption information;

[0089] It should be noted that, based on the battery's remaining charge and energy consumption information, the battery management unit can more accurately control the energy distribution between the engine and the electric motor. By monitoring the battery's energy consumption in real time, the battery management unit can intelligently select 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 charge and temperature information, the battery management unit can prevent the battery from being overcharged or over-discharged. By monitoring the battery temperature information, 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 lifespan.

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

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

[0093] Step S14: Calculate the vehicle's actual energy consumption based on the actual power and actual torque, and formulate an energy distribution strategy based on the actual energy consumption;

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

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

[0096] It's important to note that dynamic programming algorithms optimize power allocation, thereby optimizing the operating points of the engine and motor. This allows the vehicle to operate within a highly efficient and energy-saving range. Dynamic programming considers battery health and lifespan, optimizing power allocation strategies to reduce overcharging and discharging of the battery, thus extending its lifespan. For example, when the battery charge is low, dynamic programming can limit the motor's power output to prevent over-discharge; when the battery charge is high, more power can be provided by the motor, reducing the engine load. Furthermore, dynamic programming is highly adaptable, capable of developing different energy allocation strategies based on various driving conditions (such as city roads, highways, and mountain roads) and vehicle parameters (such as vehicle weight and drag coefficient), ensuring that hybrid vehicles maintain optimal performance and fuel economy under various conditions.

[0097] It should be noted that this embodiment uses real-time interaction with the Internet of Vehicles to enable vehicles to judge the road conditions of the planned road segment and complete the efficient energy allocation based on the processed information, thereby reducing the energy consumption of hybrid vehicles and thus reducing environmental pollution.

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

[0099] Speed ​​control specifically includes: Adaptive Cruise Control (ACC): Automatically adjusts the vehicle speed based on the speed of the vehicle ahead and road conditions. Speed ​​Limit Reminder: Reminds the driver to adjust the vehicle speed based on road speed limits and road conditions.

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

[0101] Safety warnings specifically include collision warnings: issuing a warning to the driver when a collision risk is detected; and lane departure warnings: reminding the driver to correct the vehicle's course when it deviates from its lane.

[0102] Specific application scenarios in this embodiment include: urban traffic light optimization: adjusting vehicle speed based on traffic signal information to reduce waiting time; and congestion avoidance: selecting the optimal route to avoid congestion based on real-time congestion information.

[0103] Highway platoon collaboration: Enables coordinated driving across platoons via V2V communication, improving traffic efficiency. Accident warning: Provides advance warning of accidents, allowing for adjustments to vehicle speed and lanes.

[0104] Severe Weather and Road Condition Warning: Receives information on slippery or icy roads to adjust driving strategies. Visibility Assist: Uses V2I communication to obtain information about road conditions ahead, compensating for insufficient visibility.

[0105] Furthermore, the construction of dynamic programming algorithms specifically includes multi-objective optimization; the objective functions are: minimizing fuel consumption, minimizing electrical energy consumption, maximizing power performance, and minimizing emissions. The optimization algorithms use algorithms such as the Equivalent Minimum Fuel Consumption Strategy (ECMS) and dynamic programming (DP) to achieve multi-objective optimization.

[0106] Road condition prediction: Adjust energy distribution in advance based on predicted road conditions (such as uphill, downhill, etc.); Driving prediction: Adjust energy distribution in advance based on predicted driving behavior (such as frequent acceleration, etc.).

[0107] Additionally, in one embodiment, reference is made to Figure 2 ,exist Figure 1 Step S11 in the illustrated embodiment also includes, but is not limited to, the following steps:

[0108] Step S21: Obtain the air density, drag coefficient, and frontal area of ​​the vehicle during driving; calculate the air resistance of the vehicle based on the air density, drag coefficient, and frontal area.

[0109] Step S22: Obtain the vehicle's wheel rolling resistance, vehicle mass, gravitational acceleration, and road slope; calculate the vehicle's rolling resistance based on the wheel rolling resistance, vehicle mass, gravitational acceleration, and road slope.

[0110] Step S23: Calculate the vehicle's slope resistance based on the vehicle's mass, gravitational acceleration, and road gradient;

[0111] Step S24: Obtain the vehicle acceleration and calculate the vehicle's acceleration resistance based on the vehicle acceleration and vehicle mass;

[0112] Step S25: Calculate the total resistance of the vehicle based on air resistance, rolling resistance, gradient resistance, and acceleration resistance;

[0113] Step S26: Obtain the vehicle's real-time driving speed and transmission efficiency, and calculate the vehicle's required power based on the real-time driving speed, transmission efficiency, and total resistance.

[0114] Step S27: 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.

[0115] Step S28: Calculate the required torque of the vehicle based on the required power, vehicle transmission efficiency, and wheel angular velocity.

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

[0117]

[0118] Where, is F air Air resistance, ρ air density, C d Let A be the drag coefficient, A be the vehicle's frontal area, and v be the vehicle speed; the rolling resistance of the vehicle is calculated using the following second formula:

[0119] F roll =C r ×m×g×cosθ;

[0120] Among them, F roll For rolling resistance, C r Here, m is the rolling resistance coefficient, g is the vehicle mass, and θ is the road gradient.

[0121] The gradient resistance of a vehicle is calculated using the following third formula:

[0122] F grade = m × g × sinθ;

[0123] Among them, F grade For slope resistance;

[0124] The acceleration drag of a vehicle is calculated using the following fourth formula:

[0125] F acc =m×a;

[0126] Among them, F acc To increase resistance;

[0127] The total resistance of a vehicle is calculated using the following fifth formula:

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

[0129] Among them, F total Total resistance;

[0130] The required torque for a vehicle is calculated using the following sixth formula:

[0131]

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

[0133] Additionally, in one embodiment, reference is made to Figure 3 ,exist Figure 1Step S13 of the illustrated embodiment also includes, but is not limited to, the following steps:

[0134] Step S31: Obtain the vehicle's transmission efficiency;

[0135] Step S32: Obtain the engine power and motor power of the vehicle, and calculate the actual power of the vehicle based on the engine power, motor power and transmission efficiency;

[0136] Step S33: Obtain the engine torque and motor torque of the vehicle, and calculate the actual torque of the vehicle based on the engine torque, motor torque and transmission efficiency.

[0137] It's important to note that in hybrid vehicles, the engine and electric motor are the primary power sources. Calculating the vehicle's actual power and torque helps optimize energy management strategies, achieving a reasonable power distribution between the engine and motor, and improving the vehicle's energy efficiency. Furthermore, by using actual power and torque, the vehicle control unit can intelligently select the most suitable driving mode for the current road conditions, such as pure electric mode, hybrid mode, or direct drive mode, to adapt to different driving needs and reduce unnecessary power loss, thereby improving the vehicle's fuel economy.

[0138] It should be noted that the actual power of a vehicle is calculated using the following seventh formula:

[0139] P actual =(P ice +P tm )×η;

[0140] Among them, P ice For engine power, P tm Motor power;

[0141] The actual torque of a vehicle is calculated using the following eighth formula:

[0142] T actual =(T ice +T tm )×η;

[0143] Among them, T ice For engine torque, T tm This refers to the motor torque;

[0144] It should be noted that the actual power of a 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 a vehicle affects the output of the actual power and actual torque, the impact of transmission efficiency on the vehicle needs to be taken into account when calculating the actual power and actual torque.

[0145] Additionally, in one embodiment, reference is made to Figure 4 ,exist Figure 1 Step S12 of the illustrated embodiment also includes, but is not limited to, the following steps:

[0146] Step S41: Obtain the vehicle's battery voltage information and battery power information, and calculate the vehicle's battery current based on 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 capacity based on 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 based on the temperature influence coefficient, aging influence coefficient and the nominal capacity of the battery.

[0149] Step S44: Obtain the battery internal resistance and calculate the battery Joule heat based on the battery internal resistance and battery current.

[0150] Step S45: Obtain the heat dissipation coefficient, battery surface area, and ambient temperature of the battery; calculate the battery temperature based on the heat dissipation coefficient, battery surface area, ambient temperature, and Joule heat.

[0151] Step S46: Adjust the remaining battery charge, battery capacity, and battery temperature according to the required power and torque until the battery's charging power, discharging power, and energy output efficiency reach the energy distribution strategy.

[0152] It should be noted that when the power demand is low and the battery capacity is below the set threshold, the engine is started first to charge the battery. During the charging process, the charging power is adjusted according to the battery temperature and charging current 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 power demand is high and the battery capacity is high, the battery is used to discharge first. During the discharge process, the torque output of the motor and engine is reasonably allocated according to the required torque and the battery performance curve.

[0153] Furthermore, based on the battery's charge-discharge characteristic curve, a reasonable charge-discharge rate range is set to avoid damage to battery capacity caused by high-rate charging and discharging. The power unit's thermal management device maintains the battery within a suitable operating temperature range (typically 15℃-35℃) to slow down battery capacity decay. When the battery temperature is too high, cooling devices (such as liquid cooling or air cooling) are activated to lower the battery temperature. The power and flow rate of the cooling system are adjusted according to the battery's heat generation and ambient temperature to ensure the battery temperature remains within a safe range. When the battery temperature is too low, heating devices (such as PTC heaters or heat pumps) are activated to raise the battery temperature. The power and temperature settings of the heating system are adjusted according to the battery's heating requirements and ambient temperature to avoid overheating and excessive energy consumption. Through reasonable battery capacity adjustment, capacity management, and temperature control, the battery is ensured to operate in optimal condition, improving the energy utilization efficiency of hybrid vehicles, reducing the battery's operating time under harsh conditions such as high-rate charging and discharging, high temperatures, and low temperatures, slowing down the rate of battery capacity decay, and extending battery life. By optimizing energy management strategies, unnecessary energy loss and emissions are reduced, achieving the energy-saving and emission-reduction goals of hybrid vehicles.

[0154] It should be noted that the vehicle's battery current is calculated using the following ninth formula:

[0155]

[0156] Among them, P demand For required power, V battery For battery voltage, I battery This refers to the battery current.

[0157] The required power of a vehicle can be calculated using the following formula (number ten):

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

[0159] Where, p demand For required power, V battery For battery voltage, I battery This refers to the battery current.

[0160] The remaining battery power is calculated using the following eleventh formula:

[0161]

[0162] Where SOC(t) is the remaining battery capacity, SOC0 is the initial battery capacity, and C is the current capacity. nominal For the battery's nominal capacity, This represents the real-time current of the battery.

[0163] The battery capacity is calculated using the following twelfth formula:

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

[0165] Among them, C actual For battery capacity, f temp Temperature effect coefficient, f aging The aging effect coefficient;

[0166] The battery temperature is calculated using the following formula (number thirteen):

[0167]

[0168] Among them, T battery For battery temperature, T ambient For ambient temperature, Battery current, R internal Where is the battery internal resistance, h is the heat dissipation coefficient, and A is the battery surface area;

[0169] Additionally, in one embodiment, reference is made to Figure 5 ,exist Figure 1 Step S14 of the illustrated embodiment also includes, but is not limited to, the following steps:

[0170] Step S51: Obtain the real-time output power of the vehicle's engine, engine thermal efficiency, and low calorific value of the fuel; calculate the vehicle's fuel consumption based on the real-time output power, low calorific value, and engine power.

[0171] Step S52: Obtain the motor power and motor efficiency of the vehicle, and calculate the motor energy consumption of the vehicle based on the motor power and motor efficiency.

[0172] Step S53: Obtain the vehicle's equipment energy consumption and working time, and calculate the vehicle's equipment energy consumption based on the equipment energy consumption and working time;

[0173] Step S54: Calculate the vehicle's total energy consumption based on fuel consumption, electrical energy consumption, low calorific value, and equipment energy consumption;

[0174] Step S55: Distribute energy to the vehicle based on total energy consumption and energy distribution strategy.

[0175] It should be noted that dynamic programming and other global optimization algorithms are used to globally optimize energy distribution during vehicle operation. By predicting future driving information, the optimal energy distribution strategy for the entire journey is calculated, achieving optimal fuel economy and emissions performance across the entire vehicle.

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

[0177]

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

[0179] The energy consumption of the motor is calculated using the following fifteenth formula:

[0180]

[0181] Among them, E tm For power consumption, η tm For motor efficiency;

[0182] The energy consumption of a vehicle's equipment is calculated using the following sixteenth formula:

[0183] E aum =∑P aux ×t;

[0184] Among them, E aux For energy consumption, P aux t represents equipment energy consumption, and t represents working time.

[0185] The total energy consumption of a vehicle can be calculated using the following formula (number seventeen):

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

[0187] Additionally, in one embodiment, reference is made to Figure 6 ,exist Figure 1 Step S15 of the illustrated embodiment also includes, but is not limited to, the following steps:

[0188] Step S61: Obtain vehicle load demand information and vehicle speed information, and determine the vehicle's working mode based on 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 electric motor, and the vehicle's engine 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 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 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 switches from electric motor drive to engine drive.

[0193] Step S66: Obtain real-time traffic information and vehicle operating stage, and adjust the motor and engine in real time according to the real-time traffic information and operating stage.

[0194] It should be noted that obtaining real-time traffic information includes communication between vehicles, between vehicles and infrastructure, between vehicles and the cloud, and between vehicles and pedestrian mobile devices. Specifically, vehicle-to-vehicle communication shares real-time information, such as vehicle speed, location, and acceleration, through V2V communication. Multi-vehicle collaboration is used to perceive road conditions ahead (such as congestion, accidents, and construction), thereby achieving information sharing between vehicles. Communication between vehicles and infrastructure includes obtaining signal phase and timing information from traffic lights and road conditions (such as slippery conditions, icy conditions, and obstacles) from roadside units. Communication between vehicles and the cloud obtains global traffic conditions (such as congestion hotspots and accident distribution) from the cloud and predicts future traffic changes based on historical and real-time data. Communication between vehicles and pedestrian mobile devices obtains pedestrian location and movement trajectory through smartphones or wearable devices to avoid collisions.

[0195] Furthermore, the acquired data is integrated to form comprehensive traffic information, ensuring that data from different sources are synchronized in time to avoid information lag. Based on current traffic conditions and vehicle behavior, traffic changes in the next few minutes are predicted, and based on historical data and weather information, traffic trends in the next few hours are predicted. The vehicle-to-everything (V2X) control module assesses whether there is a collision risk ahead (such as sudden braking, pedestrian crossing, etc.) and assesses whether 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 sequentially, the first load demand range, the second load demand range, and the third load demand range increase sequentially, and the first battery remaining power range, the second battery remaining power range, and the third battery remaining power range decrease sequentially.

[0197] Based on the predicted energy demand and vehicle status, EMS will formulate the following energy allocation strategies.

[0198] The pure electric mode is applicable in the following scenarios: low-speed driving, low load demand, and high SOC (State of Charge). Energy distribution: Only the electric motor is used for drive; the engine does not operate. Advantages: zero emissions and low noise.

[0199] Hybrid mode is specifically applicable to scenarios such as medium-speed driving, medium load demand, and moderate SOC. Energy distribution: The engine and electric motor work together, dynamically adjusting power distribution according to demand. Advantages: Balances fuel economy and power performance.

[0200] Engine drive mode is applicable in the following scenarios: high-speed driving, high load demand, and low SOC. Energy distribution: Only engine power is used, while the battery is charged. Advantages: Suitable for long-term high-speed driving.

[0201] The energy recovery mode is specifically applicable to scenarios such as braking or deceleration. Energy distribution: The motor converts into a generator, converting kinetic energy into electrical energy stored in the battery. Advantages: Improved energy utilization efficiency.

[0202] Furthermore, the vehicle-to-everything (V2X) control module can dynamically adjust energy distribution based on changes in road conditions, such as sudden traffic jams or accidents, and also dynamically adjust energy distribution based on the driver's driving behavior (such as rapid acceleration or emergency braking).

[0203] Additionally, in one embodiment, reference is made to Figure 7 ,exist Figure 6 Step S66 in the illustrated embodiment also includes, but is not limited to, the following steps:

[0204] Step S71: When the vehicle is in the starting phase, it is determined that the priority of the electric motor is greater than that of the engine, the vehicle is driven by the electric motor, and the engine stops running.

[0205] Step S72: When the vehicle is in the acceleration phase, the electric motor and the engine work together to enable the vehicle to obtain maximum torque;

[0206] Step S73: When the vehicle is in the cruise phase, determine the vehicle's driving mode based on real-time road condition information and remaining battery power.

[0207] Step S74: When the real-time road condition information is a flat road, the priority of the electric motor drive is greater than that of the engine. When the real-time road condition information is an uphill slope, the electric 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 traffic information indicates a congested road section, adjust the vehicle's drive status to electric motor drive.

[0209] Step S76: When the real-time traffic information indicates a highway section, the vehicle's driving state is changed to engine drive, with the electric motor assisting the vehicle in acceleration and hill climbing.

[0210] It's important to note that during vehicle start-up, the electric motor is highly efficient at low speeds, making it ideal for initial acceleration; therefore, the vehicle prioritizes electric motor drive, and the engine remains inactive. During acceleration, to meet acceleration demands while avoiding engine overload, the engine and electric motor work together to provide maximum torque. During cruising, the optimal driving mode is selected based on road conditions and remaining battery capacity. On flat roads, electric motor drive is prioritized. When driving uphill, the engine and electric motor work together. When driving downhill, the vehicle enters energy recovery mode to balance energy consumption and power demand.

[0211] When a vehicle is braking, it needs to recover braking energy to improve energy efficiency, so it enters energy recovery mode, switching from electric motor drive to generator drive. When driving in congested traffic, to reduce engine idling losses and emissions, the vehicle prioritizes electric motor drive, keeping the engine off. When driving on highways, because the engine is more efficient at high speeds and suitable for prolonged high-speed driving, the vehicle's power unit prioritizes engine drive, with the electric motor assisting in acceleration or hill climbing.

[0212] In this embodiment, vehicle energy optimization 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 electrical energy consumption, maximizing power performance, and minimizing emissions. The objectives are constructed by establishing constraints.

[0213] First, calculate the vehicle's total energy consumption, expressed using the following formula (number eighteen):

[0214] j=∑(m fuel +m elec );

[0215] Where j is the total energy consumption, m fuel For fuel consumption, m elec This is the equivalent electrical energy consumption;

[0216] The constraints to be constructed include:

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

[0218] Engine and motor power limits:

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

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

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

[0222] Real-time data is collected from vehicle data acquisition units (such as engine, motor, battery, GPS, etc.), historical driving data, including road conditions, driving behavior, energy consumption, etc., is accumulated through storage units, and external environmental data (such as traffic conditions, weather, etc.) is obtained through traffic information acquisition modules.

[0223] The collected data undergoes preprocessing to remove noise, outliers, and missing data. The data is labeled (e.g., driving mode, energy consumption labels) for supervised learning, and useful features (e.g., average speed, acceleration, gradient) are extracted. The data is then standardized to improve model convergence.

[0224] Choose traditional machine learning models, including but not limited to decision trees, random forests, and support vector machines suitable for small datasets. Choose deep learning models suitable for processing time series and high-resolution data, such as neural networks (RNN, LSTM, Transformer, etc.); enhance the learning model by being suitable for dynamic decision-making, such as Q-learning and deep Q-networks (DQN).

[0225] Models are trained using labeled data to predict energy requirements or optimization strategies. Supervised training of these models involves discovering latent patterns in the data through clustering or dimensionality reduction methods. Finally, models are trained in simulated environments to enable them to make optimal decisions in dynamic situations.

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

[0227] The model's parameters are tuned, including iterating through hyperparameter combinations to find the optimal parameters. Probabilistic models are used to guide the hyperparameter search, improving efficiency. Parameters are also optimized by simulating an evolutionary process.

[0228] By removing redundant parameters and reducing computational load, converting floating-point parameters to low-precision values ​​to reduce computational complexity, and using a large model to guide the training of a small model, the performance of the small model is improved, thereby completing the compression and acceleration of the model.

[0229] The model parameters are updated in real time during vehicle operation to adapt to the dynamic environment, and the algorithm strategy (such as adjusting the energy distribution ratio) is adjusted according to real-time data to complete the real-time optimization of the model.

[0230] like Figure 8 As shown, Figure 8 This is a structural diagram of a hybrid vehicle energy management device according to an embodiment of the present invention. The present invention also provides a hybrid vehicle energy management device, comprising:

[0231] The processor 801 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0232] The memory 802 can be implemented 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 the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 802 and is called and executed by the processor 801 using the hybrid vehicle energy management method of the embodiments of this application.

[0233] The 803 input / output interface is used to implement information input and output.

[0234] The communication interface 804 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0235] Bus 805 transmits information between various components of the device (e.g., processor 801, memory 802, input / output interface 803, and communication interface 804);

[0236] The processor 801, memory 802, input / output interface 803, and communication interface 804 are connected to each other within the device via bus 805.

[0237] This application also provides an electronic device, including the hybrid vehicle energy management device described above.

[0238] This application embodiment also provides a storage medium, which is a computer-readable storage medium, storing a computer program that, when executed by a processor, implements the above-described hybrid vehicle energy management method.

[0239] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate, and may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0240] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or 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 computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media 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 disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0241] The above provides a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A hybrid vehicle energy management method characterized by, include: Connect the vehicle to the network, obtain the vehicle's real-time traffic information and configuration information, and calculate the vehicle's required power and torque based on the real-time traffic information and configuration information; Calculate the remaining battery power, capacity information, and temperature information of the vehicle's battery; calculate the energy consumption of the battery based on the remaining battery power, capacity information, and temperature information to obtain the energy consumption information of the battery. Obtain the vehicle's power parameters, and calculate the vehicle's actual power and actual torque based on the energy consumption information and the power parameters; The actual energy consumption of the vehicle is calculated based on the actual power and the actual torque, and an energy distribution strategy is formulated based on the actual energy consumption. A dynamic programming algorithm is constructed, which allocates power between the vehicle's engine and motor according to the energy allocation strategy.

2. The hybrid vehicle energy management method according to claim 1, characterized in that, The step of calculating the vehicle's required power and torque based on the real-time traffic information and the configuration information includes: The air density, drag coefficient, and frontal area of ​​the vehicle during driving are obtained, and the air resistance of the vehicle is calculated based on the air density, drag coefficient, and frontal area. The rolling resistance of the vehicle's wheels, vehicle mass, gravitational acceleration, and road slope are obtained, and the rolling resistance of the vehicle is calculated based on the rolling resistance of the wheels, the vehicle mass, the gravitational acceleration, and the road slope. The gradient resistance of the vehicle is calculated based on the vehicle mass, the gravitational acceleration, and the road gradient. The vehicle acceleration is obtained, and the acceleration drag of the vehicle is calculated based on the vehicle acceleration and the vehicle mass. The total resistance of the vehicle is calculated based on the air resistance, rolling resistance, gradient resistance, and acceleration resistance. The real-time driving speed and vehicle transmission efficiency of the vehicle are obtained, and the required power of the vehicle is calculated based on the real-time driving speed, the vehicle transmission efficiency and the total resistance. 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; The required torque of the vehicle is calculated based on the required power, the vehicle transmission efficiency, and the wheel angular velocity.

3. The hybrid vehicle energy management method according to claim 1, characterized in that, The calculation of the vehicle's actual power and actual torque based on the energy consumption information and the power parameters includes: Obtain the transmission efficiency of the vehicle; The engine power and motor power of the vehicle are obtained, and the actual power of the vehicle is calculated based on the engine power, the motor power and the transmission efficiency; The engine torque and motor torque of the vehicle are obtained, and the actual torque of the vehicle is calculated based on the engine torque, the motor torque and the transmission efficiency.

4. The hybrid vehicle energy management method according to claim 1, characterized in that, The calculation of the vehicle's remaining battery power, capacity information, and temperature information includes: Obtain the battery voltage information and battery power information of the vehicle, and calculate the battery current of the vehicle based on the battery voltage information and battery power information; Obtain the initial capacity information and nominal capacity of the battery, and calculate the remaining battery power based on 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 based on 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 based on the internal resistance and the battery current; Obtain the heat dissipation coefficient, battery surface area, and ambient temperature of the battery; calculate the battery temperature based on the heat dissipation coefficient, battery surface area, ambient temperature, and Joule heat. The remaining battery charge, battery capacity, and battery temperature are adjusted according to the required power and required torque until the battery's charging power, discharging power, and energy output efficiency reach the energy distribution strategy.

5. The hybrid vehicle energy management method according to claim 1, characterized in that, The step of formulating an energy allocation strategy based on the actual energy consumption includes: The engine's real-time output power, engine thermal efficiency, and fuel's lower calorific value are obtained, and the vehicle's fuel consumption is calculated based on the engine's real-time output power, the lower calorific value, and the engine thermal efficiency. Obtain the motor power and motor efficiency of the vehicle, and calculate the motor energy consumption of the vehicle based on the motor power and motor efficiency; Obtain the equipment energy consumption and working time of the vehicle, and calculate the equipment energy consumption of the vehicle based on the equipment energy consumption and the working time; The total energy consumption of the vehicle is calculated based on the fuel consumption, the electrical energy consumption, the lower calorific value, and the equipment energy consumption. The energy is allocated to the vehicle based on the total energy consumption and the energy allocation strategy.

6. The hybrid vehicle energy management method according to claim 1, characterized in that, The dynamic programming algorithm allocates power between the vehicle's internal combustion engine and the vehicle's drive motor according to the energy allocation strategy, including: Obtain the vehicle's load demand information and vehicle speed information, and determine the vehicle's operating mode based on the load demand, vehicle speed information, and 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 electric motor, and the vehicle's engine 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. When the vehicle is in engine drive mode, 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 switched from being driven by the electric motor to being driven by the engine. The system acquires real-time traffic information and the vehicle's operating phase, and adjusts the motor and engine in real time based on the real-time traffic information and the operating phase.

7. The hybrid vehicle energy management method according to claim 6, characterized in that, The real-time adjustment of the motor and the engine based on the real-time traffic information and the operating stage includes: When the vehicle is in the starting phase, if the priority of the electric motor is determined to be higher than that of the engine, the vehicle is driven by the electric motor and the engine stops running. When the vehicle is accelerating, the electric motor and the engine work together to enable the vehicle to obtain maximum torque; When the vehicle is in the cruising phase, the driving mode of the vehicle is determined based on the real-time traffic information and the remaining battery power. When the real-time road condition information indicates a flat road, the priority of the electric motor drive is higher than that of the engine. When the real-time road condition information indicates an uphill slope, the electric motor and the engine work together. When the real-time road condition information indicates a downhill slope, the vehicle enters the energy recovery mode. When the real-time traffic information indicates a congested road section, the vehicle's driving state is adjusted to electric motor drive; When the real-time traffic information indicates a highway section, the vehicle's driving state is set to engine drive, with the electric motor assisting the vehicle in acceleration and hill climbing.

8. An energy management device for a hybrid vehicle, characterized in that, It includes at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the hybrid vehicle energy management method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, Includes the hybrid vehicle energy management device as described in 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 perform the hybrid vehicle energy management method as described in any one of claims 1 to 7.

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