Hybrid power energy management method suitable for multiple environmental conditions

Abstract

The invention discloses a hybrid power energy management method suitable for multiple environmental conditions, relates to the field of energy management, and solves the problem that the vehicle performance and the energy use economy can be reduced in different environments by the existing hybrid power energy management strategy. The method comprises the following steps: acquiring environment data and running state data of a vehicle; performing preliminary modeling according to the environment data and the running state data of the vehicle to generate an automobile dynamics model and a power output model; and outputting a power distribution parameter signal according to the automobile dynamics model and the power output model so as to enable the automobile to keep excellent energy efficiency performance under the multi-environment condition. According to the method, the influence of the environment on the vehicle performance is considered in the aspect of energy management optimization of the whole vehicle, the excellent energy efficiency performance of the vehicle under the multi-environment condition is kept, and the energy economy of the hybrid vehicle is improved.

Description

Technical Field

[0001] The present invention relates to the field of energy management, and more particularly to a hybrid power energy management method adaptable to multiple environmental conditions. Background Art

[0002] Hybrid electric vehicles (HEV) are one of the important technologies to achieve the goals of "carbon peak" and "carbon neutrality". Compared with traditional vehicles, the power system of HEV is more complex in design and management. This type of vehicle usually integrates multiple power sources, such as internal combustion engines and electric motors. Effective energy distribution and real-time regulation are essential to achieve optimal performance.

[0003] Although existing energy management strategies can effectively allocate resources under fixed environmental conditions, they often ignore the impact of climate change (such as extreme temperature and humidity), terrain (such as plains and mountains), and different road conditions (such as urban roads and highways) on power management. For example, under low temperature conditions, engine oil may become thicker, seriously affecting engine performance, and low temperatures will also reduce battery efficiency; when driving uphill or on soft roads, more torque is required to support engine operation, which also increases energy consumption. Taking these environmental factors into consideration will reduce the performance of the vehicle under various conditions and the economy of energy use, and it will not be possible to achieve the optimal ratio of energy output. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a hybrid power energy management method that is adaptable to multiple environmental conditions in view of the deficiencies of the existing technology, so as to solve the problem that the existing hybrid power energy management strategy will reduce vehicle performance and the economy of energy use in different environments.

[0005] The present invention provides a hybrid power energy management method adapted to multiple environmental conditions, the method comprising:

[0006] Collect environmental data and vehicle operating status data;

[0007] Performing preliminary modeling based on the environmental data and the vehicle's operating state data to generate a vehicle dynamics model and a power output model;

[0008] A power distribution parameter signal is output according to the vehicle dynamics model and the power output model, so that the vehicle can maintain excellent energy efficiency performance under multiple environmental conditions.

[0009] As a further improvement, the method for generating the vehicle dynamics model is: obtaining the vehicle torque under different terrains and the current vehicle driving speed from the vehicle's operating status data, calculating the vehicle's total torque demand through the vehicle torque under the different terrains, obtaining the power required for the vehicle to travel by multiplying the vehicle's total torque demand by the current vehicle driving speed, and constructing the vehicle dynamics model based on the power required for the vehicle to travel and the vehicle torque under different terrains.

[0010] Further, the vehicle torque under different terrains includes torque to overcome slope resistance, torque to overcome rolling resistance, torque to overcome air resistance and torque to overcome acceleration resistance;

[0011] The expression for calculating the vehicle torque demand is:

[0012] T=T hill +T slip +T aero +T a ;

[0013] Where T is the total torque demand of the vehicle, T hill is the torque to overcome the slope resistance, T slip is the torque to overcome rolling resistance, T areo is the torque to overcome air resistance, T a It is the torque that overcomes the resistance to acceleration.

[0014] Furthermore, the torque expression for overcoming the slope resistance is calculated as:

[0015] T hill =m·g·sinθ·r / η;

[0016] Among them, T hill is the torque to overcome the slope resistance, m is the mass of the car, g is the acceleration of gravity, θ is the slope angle, r is the wheel radius, and η is the mechanical transmission efficiency.

[0017] Furthermore, the method for generating the power output model is: obtaining the battery temperature in the environmental data, obtaining the battery internal resistance, battery voltage and battery current corresponding to the battery temperature, and calculating the output power of the battery through the battery internal resistance, battery voltage and battery current;

[0018] Obtaining the thermal efficiency and mechanical efficiency of the engine in the running state data of the vehicle and the mass flow rate of wet air and the higher calorific value of the fuel in the environmental data, and calculating the output power of the engine through the thermal efficiency, mechanical efficiency, mass flow rate of wet air and the higher calorific value of the fuel;

[0019] The power distribution parameters are calculated by the output power of the battery, the output power of the engine and the power required for the vehicle to travel, and a power output model is constructed according to the output power of the battery, the output power of the engine and the power required for the vehicle to travel.

[0020] Furthermore, the expression for obtaining the battery internal resistance corresponding to the battery temperature is:

[0021]

[0022] Among them, R 0 is the preset standard internal resistance at battery temperature, E α is the activation energy of the battery, P is the gas constant, T is the battery temperature, R int is the internal resistance of the battery.

[0023] Furthermore, the expression for calculating the output power of the battery is:

[0024] P batter =V·IP loss =V·II 2 ·R int ;

[0025] Among them, P loss is the power loss value caused by the internal resistance of the battery, I is the battery current, V is the battery voltage, P battery is the output power of the battery, R int is the internal resistance of the battery.

[0026] Furthermore, the expression for calculating the output power of the engine is:

[0027]

[0028] Among them, η mech is the mechanical efficiency, Q HV is the higher calorific value of the fuel, η r is the thermal efficiency of the engine, is the mass flow rate of moist air, P engine is the output power of the engine.

[0029] Furthermore, the expression for calculating the power allocation parameter is:

[0030]

[0031] Among them, P engine is the output power of the engine, P battery is the output power of the battery, P total is the power required for vehicle travel, and α is the power allocation parameter.

[0032] Furthermore, the vehicle dynamics model and power output model are optimized through the DQN algorithm to output a power distribution parameter signal.

[0033] Beneficial Effects

[0034] The advantages of the present invention are:

[0035] The present invention collects environmental data and vehicle operating status data; performs preliminary modeling based on the environmental data and vehicle operating status data to generate a vehicle dynamics model and a power output model; outputs a power distribution parameter signal based on the vehicle dynamics model and the power output model, thereby taking the impact of the environment on the vehicle performance into consideration in the energy management optimization of the entire vehicle, achieving the vehicle maintaining excellent energy efficiency performance under multiple environmental conditions, and improving the energy economy of hybrid vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the energy management method flow of the present invention. DETAILED DESCRIPTION

[0037] The present invention will be further described below in conjunction with the embodiments, but it does not constitute any limitation to the present invention. Any limited number of modifications made by anyone within the scope of the claims of the present invention are still within the scope of the claims of the present invention.

[0038] See also Figure 1 , a hybrid power energy management method adapted to multiple environmental conditions of the present invention comprises:

[0039] Step 1: Collect environmental data and vehicle operation status data. Collect environmental data and vehicle operation status data through the information collection module. The information collection module consists of a vehicle body information collection module and an environmental information collection module.

[0040] Among them, the vehicle body information acquisition module includes a speed sensor, an acceleration sensor and a slope sensor. The vehicle body information acquisition module determines whether the vehicle is on a bad road surface such as slippery or muddy by monitoring the speed changes of each wheel. The speed and acceleration information of the vehicle change dynamically, and the sampling frequency range of the speed sensor, acceleration sensor and slope sensor needs to be set to 10-100Hz. The road slope changes slowly, and the sampling frequency range of the speed sensor, acceleration sensor and slope sensor needs to be set to 1-10Hz. Therefore, the sensor sampling frequency of the vehicle body information acquisition module is usually set to 20Hz to suit different driving environments.

[0041] The environmental information acquisition module includes a temperature sensor and a humidity sensor. The environmental information acquisition module is used to detect the temperature and humidity in the environment that affect the battery performance and engine performance. The changes in ambient temperature and humidity are relatively slow, so the sampling frequency of the temperature sensor and the humidity sensor are both set to 0.1Hz (i.e. once every 10 seconds).

[0042] The information output by the information acquisition module passes through the data processing module, which filters the signal, removes noise, normalizes the data, and models it. The data processing module performs preliminary processing on the information, thereby effectively reducing the impact of inaccurate data to improve the effectiveness of the algorithm model.

[0043] Step 2: Perform preliminary modeling based on environmental data and vehicle operating status data to generate a vehicle dynamics model and a power output model.

[0044] The method for generating a vehicle dynamics model is as follows: obtaining the vehicle torque under different terrains and the current vehicle driving speed from the vehicle's operating status data, calculating the total torque demand of the vehicle through the vehicle torque under different terrains, obtaining the power required for the vehicle to travel by multiplying the total torque demand of the vehicle by the current vehicle driving speed, and constructing a vehicle dynamics model according to the power required for the vehicle to travel and the vehicle torque under different terrains.

[0045] The vehicle torque under different terrains includes the torque to overcome slope resistance, the torque to overcome rolling resistance, the torque to overcome air resistance and the torque to overcome acceleration resistance;

[0046] The expression for calculating the vehicle torque demand is:

[0047] T=T hill +T slip +T aero +T a ;

[0048] Where T is the total torque demand of the vehicle, T hill is the torque to overcome the slope resistance, T slip is the torque to overcome rolling resistance, T areo is the torque to overcome air resistance, T a It is the torque that overcomes the resistance to acceleration.

[0049] The torque expression for overcoming the slope resistance is:

[0050] T hill =m·g·sinθ·r / η;

[0051] Among them, T hill is the torque to overcome the slope resistance, m is the mass of the car, g is the acceleration of gravity, θ is the slope angle, r is the wheel radius, and η is the mechanical transmission efficiency.

[0052] The torque expression to overcome rolling resistance is:

[0053] T slip =f r ·m·g·cosθ·r / η;

[0054] Among them, T slip is the torque to overcome the slope resistance, m is the mass of the car, g is the acceleration of gravity, θ is the slope angle, r is the wheel radius, η is the mechanical transmission efficiency, and f r is the coefficient of rolling friction.

[0055] The expression for calculating the torque to overcome air resistance is:

[0056]

[0057] Among them, T aero is the torque to overcome air resistance, C d is the air resistance coefficient, A is the front projection area of ​​the vehicle, v is the vehicle speed, r is the wheel radius, η is the mechanical transmission efficiency, and ρ is the air density.

[0058] The expression for calculating the torque to overcome the acceleration resistance is,

[0059] T a =m·a·r / η;

[0060] Among them, T a is the torque to overcome the acceleration resistance, m is the mass of the car, a is the vehicle acceleration, r is the wheel radius, and η is the mechanical transmission efficiency.

[0061] The expression for calculating the power required by the vehicle is:

[0062] P total =T·v;

[0063] Among them, P total is the power required for the vehicle to travel, T is the total torque demand of the vehicle; v is the current speed of the vehicle.

[0064] The method for generating a power output model is: obtaining the battery temperature in the environmental data, obtaining the battery internal resistance, battery voltage and battery current corresponding to the battery temperature, and calculating the battery output power through the battery internal resistance, battery voltage and battery current.

[0065] The thermal efficiency and mechanical efficiency of the engine in the vehicle's operating status data and the mass flow rate of wet air and the high calorific value of the fuel in the environmental data are obtained, and the output power of the engine is calculated by the thermal efficiency, mechanical efficiency, mass flow rate of wet air and the high calorific value of the fuel.

[0066] The power distribution parameters are obtained by calculating the output power of the battery, the output power of the engine and the power required for the vehicle to travel, and a power output model is constructed based on the output power of the battery, the output power of the engine and the power required for the vehicle to travel.

[0067] The expression for obtaining the battery internal resistance corresponding to the battery temperature is:

[0068]

[0069] Among them, R 0 is the preset standard internal resistance at battery temperature, E α is the activation energy of the battery, P is the gas constant, T is the battery temperature, R int is the internal resistance of the battery.

[0070] The expression for calculating the output power of the battery is:

[0071] P battery =V·IP loss =V·II 2 ·R int ;

[0072] Among them, P loss is the power loss value caused by the internal resistance of the battery, I is the battery current, V is the battery voltage, P battery is the output power of the battery, R int is the internal resistance of the battery.

[0073] Calculate the engine output power P engine The expression is:

[0074]

[0075] Among them, η mech is the mechanical efficiency, Q HV is the higher calorific value of the fuel, η r is the thermal efficiency of the engine, is the mass flow rate of moist air, P engine is the output power of the engine.

[0076] The thermal efficiency of the engine T The engine's thermal efficiency is also affected by temperature. The higher the temperature, the greater the engine's cooling needs, which may lead to reduced efficiency. Calculate the engine's thermal efficiency η T The Carnot thermal efficiency formula is:

[0077]

[0078] Among them, T c is the cooling temperature, T h is the combustion temperature.

[0079] As air humidity increases, the proportion of water vapor in the intake air increases, reducing the intake air quality, which in turn affects combustion efficiency and power output. Calculate the mass flow rate of wet air The expression is:

[0080]

[0081] Among them, P atm is the atmospheric pressure, V is the intake volume, Q is the gas constant, H 2 O% is the water vapor content in the air, M air is the molar mass of air.

[0082] The expression for calculating the power allocation parameters is:

[0083]

[0084] Among them, P engine is the output power of the engine, P battery is the output power of the battery, P total is the power required for vehicle driving, and α is the power allocation parameter. Among them, α∈[0,1].

[0085] Step 3: Optimize the vehicle dynamics model and power output model through the DQN algorithm to output the power distribution parameter signal.

[0086] The optimization algorithm module obtains environmental data in real time and uses the DQN algorithm to train the vehicle dynamics model and power output model. The modeling results of the vehicle dynamics model and power output model are used as initial values, the working condition is used as input, and the action value function is constructed based on the deep neural network to establish a nonlinear mapping relationship between the vehicle's working condition and the control action value.

[0087] Parameters that affect the operating state include the road conditions of the hybrid vehicle in different environments, including road surface conditions, temperature conditions, and humidity conditions.

[0088] The observables that affect the operating conditions include the vehicle's speed, the vehicle's acceleration, the slope of the road, the temperature of the driving environment, and the humidity of the driving environment.

[0089] The action space is discretized into several possible allocation ratios. For example, to represent different allocation schemes from fully using the battery to fully using the engine, the action space can be defined as {0, 0.1, 0.2, 0.3, ..., 1.0}.

[0090] The optimization algorithm module also includes a memory unit. It is used to memorize the training results of each previous moment to help simplify and effectively process the training results at any moment. The final action value function for the power allocation parameters is:

[0091] α k =f(v, a, θ, T temp , H, α k-1 );

[0092] Where v is the speed of the vehicle, a is the acceleration of the vehicle, θ is the slope of the road, T temp is the temperature of the driving environment, H is the humidity of the driving environment, α k is the output power allocation parameter, α k-1 It is the power allocation parameter of the previous moment.

[0093] The control module generates a control signal for energy management of hybrid vehicles using the trained power distribution parameters to adjust the power output of the engine and battery. The microcontroller receives the α value output by the optimization algorithm and generates a PWM signal through the PID control algorithm to control the power output of the motor and the throttle opening of the engine, thereby adjusting the power output of the engine and battery.

[0094] Based on the above information, combined with the real-time information of the power source, a power distribution mode is established for real-time switching between pure electric mode output power (α=0), pure engine mode output power (α=1), and hybrid mode. The hybrid mode mentioned includes a more detailed battery and engine output ratio (α∈(0,1)). The impact of the environment on the performance of the vehicle is taken into account in the energy management optimization of the whole vehicle, so that the vehicle can maintain excellent energy efficiency performance under multiple environmental conditions and improve the energy economy of the hybrid vehicle.

[0095] The above is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A hybrid energy management method adapted to multiple environmental conditions, characterized in that: The method includes: Collect environmental data and vehicle operating status data; Performing preliminary modeling based on the environmental data and the vehicle's operating state data to generate a vehicle dynamics model and a power output model; A power distribution parameter signal is output according to the vehicle dynamics model and the power output model, so that the vehicle can maintain excellent energy efficiency performance under multiple environmental conditions.

2. A hybrid power energy management method adapted to multiple environmental conditions according to claim 1, characterized in that: The method for generating the vehicle dynamics model is: obtaining the vehicle torque under different terrains and the current vehicle driving speed in the vehicle's operating status data, calculating the total torque demand of the vehicle through the vehicle torque under the different terrains, obtaining the power required for the vehicle to travel by multiplying the total torque demand of the vehicle by the current vehicle driving speed, and constructing the vehicle dynamics model according to the power required for the vehicle to travel and the vehicle torque under different terrains.

3. A hybrid power energy management method adapted to multiple environmental conditions according to claim 2, characterized in that: The vehicle torque under different terrains includes torque to overcome slope resistance, torque to overcome rolling resistance, torque to overcome air resistance and torque to overcome acceleration resistance; The expression for calculating the vehicle torque demand is: T=T hill +T slip +T aero +T a ; Where T is the total torque demand of the vehicle, T hill is the torque to overcome the slope resistance, T slip is the torque to overcome rolling resistance, T areo is the torque to overcome air resistance, T a It is the torque that overcomes the resistance to acceleration.

4. A hybrid power energy management method adapted to multiple environmental conditions according to claim 3, characterized in that , the torque expression for overcoming the slope resistance is calculated as: T hill =m·g·sinθ·r / η; Among them, T hill is the torque to overcome the slope resistance, m is the mass of the car, g is the acceleration of gravity, θ is the slope angle, r is the wheel radius, and η is the mechanical transmission efficiency.

5. The hybrid power energy management method adapted to multiple environmental conditions according to claim 2, characterized in that: The method for generating the power output model is: obtaining the battery temperature in the environmental data, obtaining the battery internal resistance, battery voltage and battery current corresponding to the battery temperature, and calculating the output power of the battery through the battery internal resistance, battery voltage and battery current; Obtaining the thermal efficiency and mechanical efficiency of the engine in the running state data of the vehicle and the mass flow rate of wet air and the higher calorific value of the fuel in the environmental data, and calculating the output power of the engine through the thermal efficiency, mechanical efficiency, mass flow rate of wet air and the higher calorific value of the fuel; The power distribution parameters are calculated by the output power of the battery, the output power of the engine and the power required for the vehicle to travel, and a power output model is constructed according to the output power of the battery, the output power of the engine and the power required for the vehicle to travel.

6. A hybrid power energy management method adapted to multiple environmental conditions according to claim 5, characterized in that: The expression for obtaining the battery internal resistance corresponding to the battery temperature is: Among them, R0 is the preset standard internal resistance at battery temperature, E α is the activation energy of the battery, P is the gas constant, T is the battery temperature, R int is the internal resistance of the battery.

7. A hybrid power energy management method adapted to multiple environmental conditions according to claim 6, characterized in that: The expression for calculating the output power of the battery is: P battery =V·I-P loss =V·I-I 2 ·R int ; Among them, P loss is the power loss value caused by the internal resistance of the battery, I is the battery current, V is the battery voltage, P battery is the output power of the battery, R int is the internal resistance of the battery.

8. A hybrid power energy management method adapted to multiple environmental conditions according to claim 7, characterized in that: The expression for calculating the output power of the engine is: Among them, η mech is the mechanical efficiency, Q HV is the higher calorific value of the fuel, η r is the thermal efficiency of the engine, is the mass flow rate of moist air, P engine is the output power of the engine.

9. A hybrid power energy management method adapted to multiple environmental conditions according to claim 8, characterized in that: The expression for calculating the power allocation parameter is: Among them, P engine is the output power of the engine, P battery is the output power of the battery, P total is the power required for vehicle travel, and α is the power allocation parameter.

10. The hybrid power energy management method adapted to multiple environmental conditions according to claim 1, characterized in that: The vehicle dynamics model and the power output model are optimized by the DQN algorithm to output a power distribution parameter signal.

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