Control method and device applied to hybrid vehicle and computer equipment

Abstract

The invention discloses a control method and device applied to a hybrid vehicle and computer equipment, and belongs to the vehicle-mounted field. The method comprises the steps that operation parameters corresponding to a power system in the hybrid vehicle are obtained; driving the vehicle according to the operation parameters, and determining a system control time sequence corresponding to the power system; determining state change data corresponding to the power system according to the system control time sequence and the operation parameters; according to the first change data, the second change data and the third change data, the operation cost corresponding to the power system is determined; under the condition that the operation cost does not meet the preset requirement, the operation parameters are iteratively adjusted, and the step of driving the hybrid vehicle according to the operation parameters is executed; and under the condition that the operation cost meets the preset requirement, the hybrid vehicle is controlled to be driven according to the vehicle state information indicated by the system control time sequence. And the power output and the energy utilization of the hybrid vehicle are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicles, and particularly to a control method, device and computer device applied to hybrid vehicles. Background Art

[0003] In the prior art, the development of electric vehicles and hybrid vehicles in new energy vehicles includes key technologies such as internal combustion engines, motor systems, energy storage systems, power control technologies, and integrated control technologies for combustion and motors.

[0004] However, there are deficiencies in the hybrid system of existing hybrid vehicles in terms of efficiency and vehicle parameter optimization, including but not limited to the power and speed range of engines and generators, transmission systems, output / input control strategies and logical structures of battery systems. To a certain extent, the cooperative control efficiency of hybrid vehicles is reduced. Summary of the Invention

[0005] The present application provides a control method, device and computer device applied to hybrid vehicles. By formulating the matching optimization of the parameters and control of the power system in the hybrid vehicle, it helps users to consider the matching relationship between parameters and control simultaneously at the initial stage of vehicle design, and realizes a more comprehensive optimization of the power system in the hybrid vehicle. The technical solutions are as follows:

[0006] According to one aspect of the present application, there is provided a control method applied to a hybrid vehicle, the method comprising:

[0007] Obtain the operating parameters corresponding to the power system in the hybrid vehicle;

[0008] Drive the hybrid vehicle according to the operating parameters, and determine the system control time series corresponding to the power system, where the system control time series includes energy data of the power system at at least two time nodes;

[0009] According to the system control time series and the operating parameters, determine the state change data corresponding to the power system, where the state change data includes first change data corresponding to the battery unit, second change data corresponding to the engine, and third change data corresponding to the generator;

[0010] According to the first change data, the second change data and the third change data, determine the operating cost corresponding to the power system;

[0011] In the case where the operating cost does not meet the preset requirements, iteratively adjust the operating parameters, and execute the step of driving the hybrid vehicle according to the operating parameters;

[0012] When the operating cost meets the preset requirements, control the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series.

[0013] According to one aspect of the present application, a control device for a hybrid vehicle is provided. The device includes:

[0014] An acquisition module, configured to acquire the operating parameters corresponding to the power system in the hybrid vehicle;

[0015] A determination module, configured to drive the hybrid vehicle according to the operating parameters, and determine the system control time series corresponding to the power system, where the system control time series includes energy data of the power system at at least two time nodes;

[0016] The determination module is further configured to determine the state change data corresponding to the power system according to the system control time series and the operating parameters, where the state change data includes first change data corresponding to the battery unit, second change data corresponding to the engine, and third change data corresponding to the generator;

[0017] The determination module is further configured to determine the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data;

[0018] A control module, configured to iteratively adjust the operating parameters when the operating cost does not meet the preset requirements, and execute the step of driving the hybrid vehicle according to the operating parameters;

[0019] The control module is further configured to control the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series when the operating cost meets the preset requirements.

[0020] According to another aspect of the present application, a computer-readable storage medium is provided. The storage medium stores a computer program, and the computer program is loaded and executed by a processor to implement the above control method for a hybrid vehicle.

[0021] According to another aspect of the present application, a computer program product or a computer program is provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above control method for a hybrid vehicle.

[0022] The beneficial effects brought by the technical solutions provided in the embodiments of the present application at least include:

[0023] Determine the system control time series corresponding to the driving of the power system in the vehicle according to the operating parameters, and then determine the change data corresponding to the battery unit, engine, and generator in the power system in combination with the operating parameters. Finally, use the change data corresponding to the battery unit, engine, and generator respectively to determine the operating cost of the hybrid vehicle, and iteratively adjust the vehicle state information for driving the hybrid vehicle based on the operating cost to improve the power output and energy utilization of the hybrid vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0025] Figure 1 is a structural block diagram of a vehicle provided by an exemplary embodiment of the present application;

[0026] Figure 2 is an execution flow block diagram of a control method applied to a hybrid vehicle provided by an exemplary embodiment of the present application;

[0027] Figure 3 is an execution flow block diagram of a control method applied to a hybrid vehicle provided by another exemplary embodiment of the present application;

[0028] Figure 4 is a module block diagram for executing a control method applied to a hybrid vehicle provided by an exemplary embodiment of the present application;

[0029] Figure 5 is a structural block diagram of a control device applied to a hybrid vehicle provided by an exemplary embodiment of the present application;

[0030] Figure 6 is a structural block diagram of a computer device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To make the objectives, technical solutions, and advantages of the present application clearer, the following will further describe the embodiments of the present application in detail in conjunction with the accompanying drawings.

[0032] Figure 1The structural block diagram of a vehicle provided by an exemplary embodiment is shown. Based on this structural block diagram, the execution process of the control method provided by the embodiments of the present application applied to a hybrid vehicle is introduced. The structural block diagram includes a vehicle 10, and the vehicle 10 includes a power system 100, which is composed of core components such as a generator 101 and an engine 102. The generator 101 and the engine 102 work together through an intelligent control system to achieve efficient power output and energy utilization.

[0033] Optionally, the vehicle 10 includes at least one of a fuel vehicle, an electric vehicle, a hybrid vehicle, a fuel cell vehicle, a solar vehicle, etc. Among them, a hybrid vehicle refers to a combination of a fuel vehicle and an electric vehicle.

[0034] In the embodiments of the present application, the vehicle 10 is implemented as a hybrid vehicle (i.e., a hybrid vehicle) as an example for illustration.

[0035] Optionally, the power system 100 is the core part of the vehicle 10 responsible for providing power, including the above-mentioned generator 101, engine 102, drive motor, battery unit, and control system, etc.

[0036] The power system 101 switches among the following multiple modes according to different working conditions.

[0037] Pure electric mode: The vehicle 10 is powered by the battery unit, and the drive generator 101 drives the vehicle 10 alone. In this mode, the engine 102 does not work.

[0038] Series mode: The engine 102 drives the generator 101 to generate electricity, and the electric energy is supplied to the drive motor or stored in the battery unit.

[0039] Parallel mode: The engine 102, the generator 101, and the drive motor work simultaneously to jointly drive the vehicle 10.

[0040] Kinetic energy recovery mode: When the vehicle 10 decelerates or brakes, it is converted from the drive motor to the generator 101, and the kinetic energy is converted into electric energy and stored in the battery unit.

[0041] Fuel mode: In this mode, the drive engine 102 drives the vehicle 10 alone, and the generator 101 does not work.

[0042] The vehicle 10 monitors the parameters generated during the driving process in real time through the control system, and automatically selects the optimal driving mode adapted to the current parameters to achieve efficient power output and energy utilization.

[0043] Optionally, the generator 101 is a device in the vehicle 10 that converts mechanical energy into electrical energy. In a hybrid vehicle, the generator 101 is connected to the engine 102. When the engine 101 operates, the rotor of the generator 101 is driven to rotate by a belt or a gear. The magnetic field in the rotor interacts with the coils in the stator to generate an induced electromotive force, thereby generating electrical energy. This electrical energy can be used to charge the battery unit of the vehicle 10 or directly supplied to the drive motor for use.

[0044] Optionally, the engine 102 is a device that converts the chemical energy of fuel into mechanical energy. In a hybrid vehicle, the engine 102 is connected to the generator 101. The engine 102 generates high-temperature and high-pressure gas by burning fuel (such as gasoline or diesel, etc.), which drives the piston to move, converting chemical energy into mechanical energy. In a hybrid vehicle, the engine 102 can directly drive the hybrid vehicle under specified operating conditions or drive the generator 101 to generate electricity.

[0045] In the embodiments of the present application, the system control time series corresponding to the driving of the power system in the vehicle according to the operating parameters is determined, and then the change data corresponding to the battery unit, the engine, and the generator in the power system is determined in combination with the operating parameters. Finally, the operating cost of the hybrid vehicle is determined by using the change data corresponding to the battery unit, the engine, and the generator respectively, and the vehicle state information for driving the hybrid vehicle is iteratively adjusted based on the operating cost, so as to improve the power output and energy utilization of the hybrid vehicle.

[0046] As Figure 2 shown, Figure 2 The execution flow block diagram of the control method applied to a hybrid vehicle provided by an exemplary embodiment of the present application is shown. Taking the vehicle 10 shown as the execution subject of this method for description. Figure 1 is shown for the vehicle 10.

[0047] Step 200, obtain the operating parameters corresponding to the power system in the hybrid vehicle.

[0048] Optionally, for the specific content of the power system, reference can be made to the above embodiments, which will not be elaborated here.

[0049] In the embodiments of the present application, the power system includes an engine, a generator, and a battery unit.

[0050] The operating parameters refer to the hardware parameter values corresponding to each unit module in the power system.

[0051] Schematically, the operating parameters include but are not limited to the fixed transmission ratio between the engine and the generator, the open-circuit voltage of the battery corresponding to the battery unit, and the initial value of the battery capacity parameter corresponding to the battery unit.

[0052] Among them, the fixed transmission ratio is determined by the ratio of the engine speed to the generator speed, or the fixed transmission ratio is determined by the ratio of the generator speed to the engine speed. This application does not limit this. Schematically, the speed can be the rated speed of the engine and / or the generator.

[0053] In another alternative embodiment, the fixed transmission ratio can be a preset fixed value. For example, the fixed transmission ratio between the engine and the generator is 0.5, that is, the generator speed is twice that of the engine.

[0054] The open-circuit voltage of the battery is measured through experiments at different states of charge. Schematically, a pulse discharge test is used to determine the open-circuit voltage of the battery. After discharging the battery unit by a certain proportion and then leaving it static for a period of time, the voltage after standing is measured as the open-circuit voltage at this state of charge.

[0055] In another alternative embodiment, the open-circuit voltage of the circuit is determined by a linear fitting method. Schematically, during the charging or discharging process of the battery unit, the voltages at different rates are recorded, and the voltage at a charging rate of 0 is calculated through linear fitting. This voltage is recorded as the open-circuit voltage.

[0056] The initial value of the battery capacity parameter is a parameter used to describe the battery performance of the battery unit. The initial value of the battery capacity parameter is used for accurate modeling, state estimation, and life prediction of the battery unit.

[0057] The initial value of the battery capacity parameter includes, but is not limited to, any one of the following parameters.

[0058] Rated capacity: The theoretical capacity that the battery unit can output under standard conditions. Schematically, the standard conditions are a temperature environment of 25°C and discharging at the rated discharge rate.

[0059] Actual capacity: The actual capacity that the battery unit can output in the current state. The actual capacity is affected by factors such as battery aging, temperature change, and charge-discharge rate. Generally, the actual capacity is less than or equal to the rated capacity.

[0060] Optionally, the actual capacity is calculated by measuring the current and time charged or discharged by the battery unit, or the battery unit is regularly subjected to a complete charge-discharge cycle to determine the actual capacity.

[0061] Initial state of charge: The state of charge of the battery unit at the initial moment, which is used to represent the proportion of the remaining power of the battery unit in the total capacity, usually expressed as a percentage.

[0062] Initial state of health: The state of health of the battery unit at the initial moment, which is used to represent the ratio of the current capacity of the battery unit to the rated capacity, usually expressed as a percentage.

[0063] Initial internal resistance: The internal resistance of the battery cell at the initial moment, which is used to represent the resistance inside the battery cell.

[0064] Initial self-discharge rate: The self-discharge rate of the battery cell at the initial moment, which is used to represent the natural loss rate of the battery cell's charge in the static state.

[0065] Initial temperature: The temperature of the battery cell at the initial moment. Schematically, the initial temperature of the battery cell can be directly measured by a temperature sensor.

[0066] Initial charge-discharge rate: The charge-discharge rate of the battery cell at the initial moment, which is used to represent the ratio of the charge-discharge current to the rated capacity.

[0067] Initial cycle number: The cycle number of the battery cell at the initial moment, which is used to represent the number of charge-discharge cycles that the battery cell has completed.

[0068] Initial voltage: The voltage of the battery cell at the initial moment.

[0069] It should be noted that the above-mentioned initial moment includes any one of the battery factory moment, the battery installation moment, the battery start moment, the start moment of the battery charge-discharge cycle, the moment of reuse after long-term storage of the battery, and the reference moment for battery health state assessment.

[0070] Among them, the battery factory moment refers to the moment when the battery cell comes off the production line and undergoes preliminary inspection and calibration. The battery installation moment refers to the moment when the battery cell is first installed in the hybrid vehicle. The battery start moment refers to the moment when the battery cell is in the battery management system and the battery management system starts to run. The start moment of the battery charge-discharge cycle refers to the moment when the battery cell starts the first charge-discharge cycle. The moment of reuse after long-term storage of the battery refers to the moment when the battery cell is put back into use after a period of storage (static). The reference moment for battery health state assessment refers to any time point selected in the battery health state assessment.

[0071] In the embodiments of the present application, the initial moment refers to the battery start moment.

[0072] Step 210, drive the hybrid vehicle according to the operating parameters, and determine the system control time series corresponding to the power system.

[0073] Optionally, drive the hybrid vehicle according to the above operating parameters. In other words, the hybrid vehicle operates under the current operating parameters.

[0074] Among them, the system control time series includes energy data of the power system at at least two time nodes, and the at least two time nodes are arranged in the order of natural time.

[0075] That is, the energy data corresponding to at least two time nodes in the system control time series are arranged in the natural time order to reflect the change of the vehicle state information of the hybrid vehicle over time. The system control time series includes a plurality of energy data, including but not limited to the driving speed, acceleration, engine speed, braking state, sensor parameters corresponding to various sensors in the hybrid vehicle, and so on.

[0076] In the embodiments of the present application, the system control time series is used to monitor the vehicle state of the hybrid vehicle, optimize the control strategy of the hybrid vehicle, perform fault diagnosis of the hybrid vehicle, and so on.

[0077] In an alternative embodiment, the system control time series includes one or more of the following uses.

[0078] Hybrid vehicle state monitoring and diagnosis: By recording the time series data of the hybrid vehicle during operation, the health state of the hybrid vehicle is monitored in real time, and the potential faults of the hybrid vehicle are predicted. Schematically, the system control time series is used to record the vehicle dynamic data before and after a vehicle collision event, such as vehicle speed, acceleration, etc.

[0079] Autopilot and assisted driving system: The autopilot system relies on the system control time series to predict the future states of the hybrid vehicle and surrounding traffic participating vehicles. For example, by processing the problem of the change of the hybrid vehicle state over time through models such as dynamic Bayesian networks, more accurate trajectory prediction and vehicle state prediction can be achieved.

[0080] Vehicle performance optimization: The system control time series is used to analyze performance indicators such as the energy consumption and power output of the hybrid vehicle, assist in optimizing the control strategy, and improve the fuel efficiency or the battery unit endurance mileage.

[0081] Fault injection and testing: In the development and testing stages of the hybrid vehicle, by injecting the parameters corresponding to the fault mode through the system control time series, different working conditions of the hybrid vehicle can be simulated, so as to verify the reliability and robustness of the power system.

[0082] In another alternative embodiment, the operating parameters include operating sub-parameters under at least two operating conditions, that is, at least two operating conditions correspond one-to-one with at least two operating sub-parameters.

[0083] The vehicle is driven according to at least two operating sub-parameters, and at least two system control time sub-series corresponding to the at least two operating sub-parameters are obtained.

[0084] Compare at least two system control time sub-series, and determine the target time sub-series from the at least two system control time sub-series.

[0085] The target time subsequence can be determined based on the driving speed, acceleration, engine speed, braking state, sensor parameters corresponding to each sensor in the hybrid vehicle, and so on. Schematically, the system control time subsequence with the minimum / maximum average driving speed of the hybrid vehicle within at least two system control time subsequences is determined as the target time subsequence.

[0086] In another alternative embodiment, each energy data within each system control time subsequence is subjected to fitting processing to obtain multiple fitting relation expressions. Taking any one of the multiple energy data as a standard, the at least two fitting relation expressions corresponding to at least two system control time subsequences are compared, and the system control time subsequence corresponding to the fitting relation expression with the smallest change trend among the at least two fitting relation expressions is determined as the target time subsequence.

[0087] Step 220: Determine the state change data corresponding to the power system according to the system control time series and the operating parameters.

[0088] Optionally, the state change data includes the first change data corresponding to the battery unit, the second change data corresponding to the engine, and the third change data corresponding to the generator. Schematically, the state change data includes the battery capacity corresponding to the battery unit, the battery terminal voltage corresponding to the battery unit, the engine speed, the engine displacement, the engine intake air volume, the generator speed, and so on.

[0089] In an alternative embodiment, the multiple energy data included in the system control time series are classified to obtain the first energy data related to the battery unit, the second energy data related to the engine, and the third energy data related to the generator. Schematically, the first energy data includes the battery capacity and the battery terminal voltage, the second energy data includes the engine speed, the engine displacement, and the engine intake air volume, and the third energy data includes the generator speed.

[0090] Data analysis is performed on the first energy data related to the battery unit to obtain the first change data; data analysis is performed on the second energy data related to the engine to obtain the second change data; data analysis is performed on the third energy data related to the generator to obtain the third change data.

[0091] The above change data are all used to indicate the change of the energy data within the specified time period.

[0092] Step 230: Determine the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data.

[0093] Optionally, the operating cost refers to the sum of various costs generated by internal components and external factors during the operation of a hybrid vehicle, including but not limited to the fuel consumption cost related to the engine, the power consumption cost related to the generator, the battery capacity consumption cost related to the battery unit, and the transmission consumption cost related to the engine and the generator.

[0094] Optionally, the sum of the first change data, the second change data, and the third change data is determined as the operating cost of the power system.

[0095] In an optional embodiment, according to the second change data and the third change data, the power consumption data, the gas emission data, and the power transmission change data corresponding to the power system are determined.

[0096] Among them, the power consumption data is used to indicate the energy consumption of the engine and the generator during the operation of the hybrid vehicle.

[0097] The gas emission data is used to indicate the quantitative information of greenhouse gases and other pollutants released into the atmosphere during the operation of the hybrid vehicle.

[0098] The power transmission change data is used to indicate the efficiency change data corresponding to the gearbox in the power system.

[0099] According to the first change data, the battery capacity change data corresponding to the battery unit in the hybrid vehicle is determined.

[0100] Perform a weighted process on the power consumption data, the gas emission data, the power transmission change data, and the battery capacity change data to determine the operating cost.

[0101] Obtain the first weight coefficient corresponding to the power consumption data, the second weight coefficient corresponding to the gas emission data, the third weight coefficient corresponding to the power transmission change data, and the fourth weight coefficient corresponding to the battery capacity change data; determine the first sum value as the product of the first weight coefficient and the power consumption data; determine the second sum value as the product of the second weight coefficient and the gas emission data; determine the third sum value as the product of the third weight coefficient and the power transmission data; determine the fourth sum value as the product of the fourth weight coefficient and the battery capacity change data; perform a summation process on the first sum value, the second sum value, the third sum value, and the fourth sum value to obtain the operating cost.

[0102] Step 240, in the case where the operating cost does not meet the preset requirements, iteratively adjust the operating parameters, and perform the step of driving the hybrid vehicle according to the operating parameters.

[0103] Optionally, the preset requirement is a fixed value or a fixed range preset by relevant personnel.

[0104] Schematically, when the operating cost is not a fixed value or not within a fixed range, obtain the current operating parameters of the hybrid vehicle in the current state, and execute the above step 210 to determine the current system control time series corresponding to the current operating parameters, etc.

[0105] Step 250, when the operating cost meets the preset requirements, control the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series.

[0106] Optionally, the preset requirements are fixed values or fixed ranges preset by relevant personnel.

[0107] Schematically, when the operating cost is a fixed value or within a fixed range, obtain the system control time series obtained in the above step, and determine the vehicle state information corresponding to the system control time series.

[0108] In the embodiment of the present application, the vehicle state information includes at least one of engine state information, generator state information, battery state information, and transmission state information between the engine and the generator.

[0109] Control the hybrid vehicle to adjust the engine, generator, and transmission coefficient between the engine and the generator according to the above vehicle state information, and optimize the battery.

[0110] Schematically, if the vehicle state information includes the engine speed a, the generator speed b, and the transmission coefficient c between the engine and the generator, control the engine speed to be adjusted to a, the generator speed to be b, and the transmission coefficient between the engine and the generator to be c.

[0111] In the embodiment of the present application, determine the system control time series corresponding to the driving of the power system in the vehicle according to the operating parameters, and then combine the operating parameters to determine the change data corresponding to the battery unit, engine, and generator in the power system respectively. Finally, use the change data corresponding to the battery unit, engine, and generator respectively to determine the operating cost of the hybrid vehicle, and iteratively adjust the vehicle state information for driving the hybrid vehicle based on the operating cost to improve the power output and energy utilization of the hybrid vehicle.

[0112] As Figure 3 shown, Figure 3 shows a flowchart of the execution process of a control method applied to a hybrid vehicle provided by an exemplary embodiment of the present application. Taking the vehicle 10 shown as the Figure 1 executing subject of the method for illustration.

[0113] Step 300, when the hybrid vehicle is in the driving process, obtain the driving speed of the hybrid vehicle.

[0114] In the embodiments of the present application, the driving modes of the hybrid vehicle include pure electric drive, fuel drive, and hybrid drive.

[0115] Optionally, a speed sensor / acceleration sensor is used to monitor the driving speed of the hybrid vehicle during driving.

[0116] Step 310: Determine the driving mode of the hybrid vehicle according to the driving speed.

[0117] When the driving speed is less than the first speed, obtain the state of charge of the hybrid vehicle. When the state of charge meets the preset charge requirement, control the generator to drive the hybrid vehicle and turn off the engine. Schematically, the first speed is 30 km / h, and the preset charge requirement is greater than or equal to 60%.

[0118] In the pure electric drive mode, when the hybrid vehicle is in an emergency acceleration or climbing condition, the engine and the generator output torque synchronously, and the generator instantaneously compensates for the engine response delay. In the emergency acceleration or climbing condition, the throttle pedal opening of the hybrid vehicle is greater than 80%.

[0119] When the driving speed is greater than the second speed, control the engine to drive the hybrid vehicle, and control the generator to provide electrical energy input for the battery unit in the hybrid vehicle. Schematically, the second speed is 80 km / h.

[0120] In the fuel drive mode, the hybrid vehicle can turn on the high-speed cruise function. The engine directly drives the wheels, and at the same time charges the battery unit through the generator to maintain the balance of the state of charge of the battery unit.

[0121] Schematically, to maintain the balance of the state of charge of the battery unit, the engine starts only when the state of charge of the battery unit is less than 40% or the power demand exceeds the capacity of the generator, avoiding inefficient idling conditions.

[0122] Again schematically, through Atkinson cycle optimization, the engine operating range is limited to the high-efficiency area with a thermal efficiency ≥ 35% (engine speed 1500 - 3500 rpm, torque 150 - 250 Nm), and the state of charge safety window (20% - 80%) of the battery unit is set.

[0123] In the hybrid drive mode, during the driving of the hybrid vehicle, obtain the position information and environmental information of the hybrid vehicle, where the position information includes position slope, bend curvature, and altitude data.

[0124] Determine the power distribution ratio of the power system according to the position slope, bend curvature, and altitude data.

[0125] Optionally, the power distribution ratio is used to indicate the proportion of the energy provided by the engine and the generator in the power system to drive the hybrid vehicle respectively.

[0126] Determine the candidate operating cost corresponding to the power distribution ratio of the power system. When the candidate operating cost meets the above preset requirements, control the power system to drive the hybrid vehicle according to the power distribution ratio.

[0127] In an alternative embodiment, obtain the fuel consumption price and the power consumption price, and calculate the fuel consumption cost at the fuel consumption price according to the first ratio of the engine in the power distribution ratio.

[0128] Calculate the power consumption cost at the power consumption price according to the second ratio of the generator in the power distribution ratio. Determine the sum of the fuel consumption cost and the power consumption cost as the candidate operating cost.

[0129] In the embodiment of the present application, determine the system control time series corresponding to the driving of the power system in the vehicle according to the operating parameters, and then determine the change data corresponding to the battery unit, the engine, and the generator in the power system in combination with the operating parameters. Finally, use the change data corresponding to the battery unit, the engine, and the generator respectively to determine the operating cost of the hybrid vehicle, and iteratively adjust the vehicle state information for driving the hybrid vehicle based on the operating cost, so as to improve the power output and energy utilization of the hybrid vehicle.

[0130] As Figure 4 shown, Figure 4 FIG. shows a block diagram of a module for executing a control method applied to a hybrid vehicle provided by an exemplary embodiment of the present application. The module includes a parameter selection module 400, a control optimization module 410, a response solving module 420, a comprehensive cost measurement module 430, a condition judgment module 440, a load condition module 450, and an optimal value module 460.

[0131] The parameter selection module 400 is used to obtain the parameters of the power system in the hybrid vehicle. The parameters include the fixed transmission ratio between the engine and the generator, the open-circuit voltage of the battery, and the initial value of the battery pack capacity parameter.

[0132] The control optimization module 410 is used to obtain the optimal system control time series based on the parameters obtained by the parameter selection module 400 and the load condition of the power system. In the embodiment of the present application, the specific definition and acquisition process of the system control time series can be referred to the above embodiment, and will not be elaborated here.

[0133] In another alternative embodiment, based on the parameters determined in the parameter selection module 400 and the load conditions of the hybrid drive system, the electronic stability program monitors the wheel speed difference and slip ratio in real time. When the detected front axle slip ratio exceeds 15%, the system triggers the motor to intervene within 100 ms to supplement the torque. Torque vector control is used to achieve negative torque distribution (-200 Nm maximum) for a single wheel on one side during cornering, and positive torque compensation (+350 Nm) for the outer wheel, suppressing understeer and improving handling stability.

[0134] Among them, the load condition is the load cycle condition designed for the system. The load cycle condition refers to the repeated load changes experienced by the hybrid vehicle during operation. The load cycle condition reflects various conditions that the hybrid vehicle may encounter during actual use, that is, it is used to describe the change of the resistance torque borne by the hybrid vehicle under different road conditions and working conditions.

[0135] The response solving module 420 obtains the system state change under the load condition based on the parameters obtained by the above-mentioned parameter selection module 400, the load condition recorded in the control optimization module 410, and the optimal system control time series determined in the above-mentioned control optimization module 410. Among them, the system state change includes the battery pack capacity, the battery pack terminal voltage, and the engine speed change.

[0136] In another alternative embodiment, key variables of the system state change determined in the response solving module 420 are extracted, such as at least one of the average battery power consumption, engine fuel consumption, and engine fuel emissions.

[0137] In another alternative embodiment, the energy distribution strategy is dynamically adjusted according to the driving mode (Sport / ECO) of the hybrid vehicle, the state of charge of the battery unit, and the ambient temperature. The driving module includes a first driving mode and a second driving mode. The first driving mode preferentially calls the supercapacitor and the high-power motor to improve the power response. For example, the first driving mode is implemented as the Sport mode; the second driving mode limits the engine intervention threshold and enhances the energy recovery efficiency. For example, the second driving mode is implemented as the ECO mode.

[0138] The comprehensive cost measurement module 430 takes the parameters obtained by the above-mentioned parameter selection module 400 and the system state change determined in the above-mentioned response solving module 420 as inputs, and determines the comprehensive cost measurement result. In the embodiment of the present application, the comprehensive cost measurement result has the same meaning as the operating cost mentioned in the above embodiment.

[0139] In an alternative embodiment, the calculation method of the comprehensive cost measurement result includes, but is not limited to, a linear combination of engine fuel consumption, emissions, battery pack capacity, and transmission ratio. The specific calculation formula can be seen in Formula 1 below.

[0140] Formula 1: C total = α * C fuel + β * C emission + γ * C battery + δ * C ratio ;

[0141] In Formula 1, C fuel is the engine fuel consumption cost (unit: yuan per 100 kilometers), which is directly related to fuel economy and can be calculated by weighted average of the test values under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions. C emission is the emission cost (unit: yuan per kilometer), which is converted based on the emissions of carbon dioxide, nitrogen monoxide, nitrogen dioxide, etc. and the carbon tax policy. C battery is the battery pack capacity cost (unit: yuan / kWh), which is related to the type of battery cells (such as ternary lithium, lithium iron phosphate) and the cycle life. C ratio is the driveline cost (unit: yuan per unit transmission ratio), which reflects the impact of transmission efficiency optimization on energy consumption. α, β, γ, and δ are weight coefficients, which are set according to technical priorities and standard requirements (for example, environmental protection standards emphasize β, and range requirements standards emphasize γ).

[0142] Illustratively, for the fuel consumption cost C fuel :

[0143] If the WLTC fuel consumption of the target engine is 5.2 L / 100 km and the fuel price is 8 yuan / L, then C fuel = 5.2 × 8 = 41.6 yuan per 100 kilometers, and the weight α can be set to 0.3 (the fuel economy accounts for 30% of the cost weight).

[0144] For the emission cost C emission :

[0145] If the carbon dioxide emission is 120 g / km and the carbon tax is 0.1 yuan / g, then C emission = 120 × 0.1 = 12 yuan per kilometer, and the weight β is set to 0.2 (required by environmental protection standards).

[0146] For the battery pack capacity cost C battery :

[0147] The battery capacity of the battery cells in the target hybrid vehicle is 18 kWh and the cost is 800 yuan / kWh, then C battery = 18 × 800 = 14400 yuan, and the weight γ is set to 0.4 (the battery cost accounts for 40% of the total system cost).

[0148] For the driveline cost C ratio:

[0149] Increasing the transmission ratio of the target optimization requires an additional transmission cost of 2,000 yuan. If the transmission ratio optimization coefficient is 1.2, then C ratio = 2,000 × 1.2 = 2,400 yuan. The weight δ is set to 0.1 (the impact of transmission efficiency on energy consumption is relatively small).

[0150] Substitute into the above formula 1:

[0151] C total = 0.3 × 41.6 + 0.2 × 12 + 0.4 × 14,400 + 0.1 × 2,400 = 12.48 + 2.4 + 5,760 + 240 = 6,014.88 yuan.

[0152] The condition judgment module 440 is used to judge whether the comprehensive cost measurement result meets the optimization convergence condition. If it meets, the optimal value module 460 obtains the current parameters of the hybrid vehicle and the system control time series, and drives the hybrid vehicle with the current parameters and the system control time series; if it does not meet, it returns to the above parameter selection module 400 to continue obtaining the parameters of the hybrid vehicle at the current moment.

[0153] It should be noted that the optimization convergence condition here has the same meaning as the preset requirements mentioned in the above embodiments.

[0154] In the working processes of the above modules, the optimal control is introduced in each iteration cycle. Therefore, each step is evaluated by applying the optimal control under dynamic load, and the cost includes the cumulative values of system parameters and dynamic process responses. The obtained system parameters and control schemes are optimally matched. This is convenient for comprehensively evaluating the parameters and control design schemes at the initial stage of system design. That is, the embodiments of the present application tightly couple the parameter selection and system control, consider the cost measurement result while optimizing the parameter selection, and finally perform optimization iteration by judging whether the optimization convergence condition is met.

[0155] Figure 5 The block diagram of the control device applied to a hybrid vehicle provided by an exemplary embodiment of the present application is shown. The device includes: an acquisition module 500, a determination module 501, and a control module 502.

[0156] The acquisition module 500 is used to acquire the operating parameters corresponding to the power system in the hybrid vehicle;

[0157] The determination module 501 is used to drive the hybrid vehicle according to the operating parameters and determine the system control time series corresponding to the power system. The system control time series includes energy data of the power system at at least two time nodes;

[0158] The determining module 501 is further configured to determine state change data corresponding to the power system according to the system control time series and the operating parameters, where the state change data includes first change data corresponding to a battery unit, second change data corresponding to an engine, and third change data corresponding to a generator;

[0159] The determining module 501 is further configured to determine the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data;

[0160] The control module 502 is configured to iteratively adjust the operating parameters when the operating cost does not meet the preset requirements, and perform the step of driving the hybrid vehicle according to the operating parameters;

[0161] The control module 502 is further configured to control the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series when the operating cost meets the preset requirements.

[0162] In an alternative embodiment, the determining module 501 is further configured to determine power consumption data, gas emission data, and power transmission change data corresponding to the power system according to the second change data and the third change data, where the power transmission change data is used to indicate efficiency change data corresponding to a gearbox in the power system;

[0163] The determining module 501 is further configured to determine battery capacity change data corresponding to the battery unit in the hybrid vehicle according to the first change data;

[0164] The determining module 501 is further configured to perform weighted processing on the power consumption data, the gas emission data, the power transmission change data, and the battery capacity change data to determine the operating cost.

[0165] In an alternative embodiment, the obtaining module 500 is further configured to obtain a first weight coefficient corresponding to the power consumption data, a second weight coefficient corresponding to the gas emission data, a third weight coefficient corresponding to the power transmission change data, and a fourth weight coefficient corresponding to the battery capacity change data;

[0166] The determining module 501 is further configured to determine a first sum value as the product of the first weight coefficient and the power consumption data;

[0167] The determining module 501 is further configured to determine a second sum value as the product of the second weight coefficient and the gas emission data;

[0168] The determining module 501 is further configured to determine the product of the third weight coefficient and the power transmission data as the third sum value;

[0169] The determining module 501 is further configured to determine the product of the fourth weight coefficient and the battery capacity change data as the fourth sum value;

[0170] The determining module 501 is further configured to perform a summation process on the first sum value, the second sum value, the third sum value, and the fourth sum value to obtain the operating cost.

[0171] In an optional embodiment, the obtaining module 500 is further configured to obtain the driving speed of the hybrid vehicle during the driving process of the hybrid vehicle;

[0172] The obtaining module 500 is further configured to obtain the state of charge of the hybrid vehicle when the driving speed is less than the first speed;

[0173] The control module 502 is further configured to control the generator to drive the hybrid vehicle and turn off the engine when the state of charge meets the preset charge requirement.

[0174] In an optional embodiment, the obtaining module 500 is further configured to obtain the driving speed of the hybrid vehicle during the driving process of the hybrid vehicle;

[0175] The control module 502 is further configured to control the engine to drive the hybrid vehicle and control the generator to provide electrical energy input to the battery unit in the hybrid vehicle when the driving speed is greater than the second speed.

[0176] In an optional embodiment, the obtaining module 500 is further configured to obtain the position information and environmental information of the hybrid vehicle during the driving process of the hybrid vehicle, where the position information includes position slope, curve curvature, and altitude data;

[0177] The determining module 501 is further configured to determine the power distribution ratio of the power system according to the position slope, the curve curvature, and the altitude data, where the power distribution ratio is used to indicate the proportion of the energy provided by the engine and the generator in the power system to drive the hybrid vehicle respectively;

[0178] The determining module 501 is further configured to determine the candidate operating cost corresponding to the power system under the power distribution ratio;

[0179] The control module 502 is further configured to control the power system to drive the hybrid vehicle according to the power distribution ratio when the candidate operating cost meets the preset requirement.

[0180] In an optional embodiment, the obtaining module 500 is further configured to obtain the fuel consumption price and the power consumption price;

[0181] The determining module 501 is further configured to calculate the fuel consumption cost according to the first ratio of the engine in the power distribution ratio at the fuel consumption price;

[0182] The determining module 501 is further configured to calculate the power consumption cost according to the second ratio of the generator in the power distribution ratio at the power consumption price;

[0183] The determining module 501 is further configured to determine the sum value of the fuel consumption cost and the power consumption cost as the candidate operating cost.

[0184] In the embodiment of the present application, the compensation torque of the engine is determined by adjusting the intake air volume of the engine. On the one hand, the purpose of dynamically adjusting the intake air volume of the engine through strategy analysis is achieved, and on the other hand, the purpose of improving the engine efficiency is achieved, so that the vehicle can effectively load the compensation torque, ensuring the smoothness of the output torque of the whole vehicle during the engine startup or mode switching process, and improving the driving smoothness and comfort.

[0185] Figure 6 FIG. shows a structural block diagram of a computer device 600 provided by an exemplary embodiment of the present application. The computer device 600 may be a portable mobile terminal, such as: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a notebook computer or a desktop computer. The computer device 600 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, etc. Optionally, the computer device 600 may also be implemented as a mobile device, such as: a vehicle-mounted terminal and other mobile intelligent terminals.

[0186] Generally, the computer device 600 includes: a processor 601 and a memory 602.

[0187] The processor 601 may include one or more processing cores, such as a quad-core processor, a hexa-core processor, etc. The processor 601 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 601 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 601 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 601 may further include an AI (Artificial Intelligence) processor, and the AI processor is used to process computational operations related to machine learning.

[0188] The memory 602 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 602 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage media in the memory 602 is used to store at least one instruction, and the at least one instruction is used to be executed by the processor 601 to implement the model training method or behavior encoding method provided in the method embodiments of the present application.

[0189] In some embodiments, the computer device 600 may also optionally include: a peripheral device interface 603 and at least one peripheral device. The processor 601, the memory 602, and the peripheral device interface 603 may be connected through a bus or signal lines. Each peripheral device may be connected to the peripheral device interface 603 through a bus, signal lines, or a circuit board. By way of example, the peripheral device may include at least one of: a radio frequency circuit 604, a display screen 605, a camera assembly 606, an audio circuit 607, a positioning assembly 615, and a power supply 608.

[0190] The peripheral device interface 603 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 601 and the memory 602. In some embodiments, the processor 601, the memory 602, and the peripheral device interface 603 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 601, the memory 602, and the peripheral device interface 603 can be implemented on a separate chip or circuit board, and this embodiment does not limit this.

[0191] The radio frequency circuit 604 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 604 communicates with a communication network and other communication devices through electromagnetic signals. The radio frequency circuit 604 converts an electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 604 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and so on. The radio frequency circuit 604 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, each generation of mobile communication network (2G, 3G, 4G, and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 604 may further include a circuit related to NFC (Near Field Communication), and this application does not limit this.

[0192] The display screen 605 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 605 is a touch display screen, the display screen 605 also has the ability to collect touch signals on or above the surface of the display screen 605. The touch signals can be input to the processor 601 as control signals for processing. At this time, the display screen 605 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there can be one display screen 605, which is provided on the front panel of the computer device 600; in other embodiments, there can be at least two display screens 605, which are respectively provided on different surfaces of the computer device 600 or are in a foldable design; in other embodiments, the display screen 605 can be a flexible display screen, which is provided on the curved surface or the folding surface of the computer device 600. Even, the display screen 605 can also be set to an irregular non-rectangular shape, that is, a special-shaped screen. The display screen 605 can be prepared using materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0193] The camera module 606 is used to capture images or videos. Optionally, the camera module 606 includes a front camera and a rear camera. Generally, the front camera is provided on the front panel of the terminal, and the rear camera is provided on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera respectively, to achieve functions such as the combination of the main camera and the depth-of-field camera to achieve the background blurring function, the combination of the main camera and the wide-angle camera to achieve panoramic shooting and VR (Virtual Reality) shooting functions or other combined shooting functions. In some embodiments, the camera module 606 can also include a flash. The flash can be a single-color temperature flash or a two-color temperature flash. A two-color temperature flash refers to the combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0194] The audio circuit 607 may include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into electrical signals for input to the processor 601 for processing, or input to the radio frequency circuit 604 to achieve voice communication. For the purpose of stereo collection or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the computer device 600. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert the electrical signals from the processor 601 or the radio frequency circuit 604 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert electrical signals into sound waves audible to humans, but also convert electrical signals into sound waves inaudible to humans for uses such as ranging. In some embodiments, the audio circuit 607 may further include a headphone jack.

[0195] The positioning component 615 is used to locate the current geographical location of the computing device 600 to implement navigation or LBS (Location Based Service). The positioning component 615 may be a positioning component based on the US GPS (Global Positioning System) or the Chinese Beidou system.

[0196] The power supply 608 is used to supply power to each component in the computer device 600. The power supply 608 may be alternating current, direct current, a disposable battery or a rechargeable battery. When the power supply 608 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charging technology.

[0197] In some embodiments, the computer device 600 further includes one or more sensors 609. The one or more sensors 609 include but are not limited to: an acceleration sensor 610, a gyroscope sensor 611, a pressure sensor 612, an optical sensor 613, and a proximity sensor 614.

[0198] The acceleration sensor 610 can detect the magnitudes of accelerations on the three coordinate axes of the coordinate system established with the computer device 600. For example, the acceleration sensor 610 can be used to detect the components of the gravitational acceleration on the three coordinate axes. The processor 601 can control the display screen 605 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 610. The acceleration sensor 610 can also be used for collecting game or user's motion data.

[0199] The gyroscope sensor 611 can detect the body orientation and rotation angle of the computer device 600. The gyroscope sensor 611 can cooperate with the acceleration sensor 610 to collect the 3D actions of the user on the computer device 600. Based on the data collected by the gyroscope sensor 611, the processor 601 can implement the following functions: motion sensing (such as changing the UI according to the user's tilting operation), image stabilization during shooting, game control, and inertial navigation.

[0200] The pressure sensor 612 can be disposed on the side frame of the computer device 600 and / or the lower layer of the display screen 605. When the pressure sensor 612 is disposed on the side frame of the computer device 600, it can detect the holding signal of the user on the computer device 600, and the processor 601 can perform left / right hand recognition or quick operation based on the holding signal collected by the pressure sensor 612. When the pressure sensor 612 is disposed on the lower layer of the display screen 605, the processor 601 can control the operable controls on the UI interface according to the pressure operation of the user on the display screen 605. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0201] The optical sensor 613 is used to collect the ambient light intensity. In one embodiment, the processor 601 can control the display brightness of the display screen 605 according to the ambient light intensity collected by the optical sensor 613. For example, when the ambient light intensity is high, the display brightness of the display screen 605 is increased; when the ambient light intensity is low, the display brightness of the display screen 605 is decreased. In another embodiment, the processor 601 can also dynamically adjust the shooting parameters of the camera module 606 according to the ambient light intensity collected by the optical sensor 613.

[0202] The proximity sensor 614, also known as the distance sensor, is usually disposed on the front panel of the computer device 600. The proximity sensor 614 is used to collect the distance between the user and the front of the computer device 600. In one embodiment, when the proximity sensor 614 detects that the distance between the user and the front of the computer device 600 is gradually decreasing, the processor 601 controls the display screen 605 to switch from the lit state to the off state; when the proximity sensor 614 detects that the distance between the user and the front of the computer device 600 is gradually increasing, the processor 601 controls the display screen 605 to switch from the off state to the lit state.

[0203] Those skilled in the art can understand that Figure 6 the structure shown in does not constitute a limitation on the computer device 600, and it may include more or fewer components than shown in the figure, or combine some components, or adopt different component arrangements.

[0204] The present application also provides a computer-readable storage medium, in which at least one instruction, at least one segment of program, a code set or an instruction set is stored, and the at least one instruction, the at least one segment of program, the code set or the instruction set is loaded and executed by a processor to implement the control method for a hybrid vehicle provided in the above method embodiment.

[0205] The present application provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the control method for a hybrid vehicle provided in the above method embodiment.

[0206] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a magnetic disk or an optical disc, etc. The above are only optional embodiments of the present application and are not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A control method applied to a hybrid vehicle, characterized in that The method includes: Obtaining the operating parameters corresponding to the power system in the hybrid vehicle; Driving the hybrid vehicle according to the operating parameters to determine the system control time series corresponding to the power system, where the system control time series includes energy data of the power system at at least two time nodes; Determining the state change data corresponding to the power system according to the system control time series and the operating parameters, where the state change data includes first change data corresponding to the battery unit, second change data corresponding to the engine, and third change data corresponding to the generator; Determining the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data; When the operating cost does not meet the preset requirements, iteratively adjusting the operating parameters and performing the step of driving the hybrid vehicle according to the operating parameters; When the operating cost meets the preset requirements, controlling the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series.

2. The method according to claim 1, wherein The determining the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data includes: Determining the power consumption data, gas emission data, and power transmission change data corresponding to the power system according to the second change data and the third change data, where the power transmission change data is used to indicate the efficiency change data corresponding to the transmission in the power system; Determining the battery capacity change data corresponding to the battery unit in the hybrid vehicle according to the first change data; Performing a weighted process on the power consumption data, the gas emission data, the power transmission change data, and the battery capacity change data to determine the operating cost.

3. The method according to claim 2, wherein The performing a weighted process on the power consumption data, the gas emission data, the power transmission change data, and the battery capacity change data to determine the operating cost includes: Obtaining a first weight coefficient corresponding to the power consumption data, a second weight coefficient corresponding to the gas emission data, a third weight coefficient corresponding to the power transmission change data, and a fourth weight coefficient corresponding to the battery capacity change data; Determining the product of the first weight coefficient and the power consumption data as a first sum value; Determining the product of the second weight coefficient and the gas emission data as a second sum value; Determining the product of the third weight coefficient and the power transmission data as a third sum value; Determining the product of the fourth weight coefficient and the battery capacity change data as a fourth sum value; Performing a summation process on the first sum value, the second sum value, the third sum value, and the fourth sum value to obtain the operating cost.

4. The method according to any one of claims 1 to 3, characterized in that The method further includes: When the hybrid vehicle is in the driving process, obtaining the driving speed of the hybrid vehicle; When the driving speed is less than a first speed, obtaining the state of charge of the hybrid vehicle; When the state of charge meets the preset charge requirement, controlling the generator to drive the hybrid vehicle and turning off the engine.

5. The method according to any one of claims 1 to 3, characterized in that, The method further includes: During the running of the hybrid vehicle, obtaining the running speed of the hybrid vehicle; When the running speed is greater than a second speed, controlling the engine to drive the hybrid vehicle and controlling the generator to provide power input to the battery unit in the hybrid vehicle.

6. The method according to any one of claims 1 to 3, characterized in that The method further includes: During the running of the hybrid vehicle, obtaining the position information and environmental information of the hybrid vehicle, where the position information includes position slope, curve curvature, and altitude data; According to the position slope, the curve curvature, and the altitude data, determining a power distribution ratio of the power system, where the power distribution ratio is used to indicate the proportion of the energy provided by the engine and the generator in the power system for driving the hybrid vehicle respectively; Determining a candidate operating cost corresponding to the power system under the power distribution ratio; When the candidate operating cost meets the preset requirements, controlling the power system to drive the hybrid vehicle according to the power distribution ratio.

7. The method according to claim 6, wherein The determining the candidate operating cost corresponding to the power system under the power distribution ratio includes: Obtaining the price of fuel consumption and the price of power consumption; Calculating the fuel consumption cost at the price of fuel consumption according to a first ratio of the engine in the power distribution ratio; Calculating the power consumption cost at the price of power consumption according to a second ratio of the generator in the power distribution ratio; Determining the sum of the fuel consumption cost and the power consumption cost as the candidate operating cost.

8. A control device applied to a hybrid vehicle, characterized in that, The device includes: An obtaining module, configured to obtain the operating parameters corresponding to the power system in the hybrid vehicle; A determining module, configured to drive the hybrid vehicle according to the operating parameters and determine a system control time series corresponding to the power system, where the system control time series includes energy data of the power system at at least two time nodes; The determining module is further configured to determine state change data corresponding to the power system according to the system control time series and the operating parameters, where the state change data includes first change data corresponding to the battery unit, second change data corresponding to the engine, and third change data corresponding to the generator; The determining module is further configured to determine the operating cost corresponding to the power system according to the first change data, the second change data, and the third change data; A control module, configured to iteratively adjust the operating parameters when the operating cost does not meet the preset requirements, and execute the step of driving the hybrid vehicle according to the operating parameters; The control module is further configured to control the hybrid vehicle to drive according to the vehicle state information indicated by the system control time series when the operating cost meets the preset requirements.

9. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by a processor to implement the control method for a hybrid vehicle as described in any one of claims 1 to 7.

10. A computer program product or a computer program, characterized in that, The computer program product or computer program includes computer instructions that are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to implement the control method applied to a hybrid vehicle as described in any one of claims 1 to 7.

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