Vehicle energy management method, device, equipment, medium and product

Abstract

The application discloses a vehicle energy management method, device, equipment, medium and product, and belongs to the field of vehicle energy utilization. The method comprises the following steps: acquiring driving state information of a target vehicle, wherein the driving state information is used for indicating the state of the target vehicle and the state of a driving environment during driving; acquiring driver state information of the target vehicle, wherein the driver state information is used for indicating the state of the target vehicle operated by a driver during driving; generating an energy distribution strategy of the target vehicle based on the driving state information and the driver state information, wherein the energy distribution strategy is used for the distribution mode of energy used for driving the target vehicle; and distributing the energy of the target vehicle based on the energy distribution strategy, and driving the target vehicle. In the process of energy distribution, the driving state of the vehicle and the state of the driver are considered, so that the use of fuel and / or electricity is optimized under different driving states of the vehicle, and the overall energy utilization efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle energy utilization, and in particular to a vehicle energy management method, device, equipment, medium and product. BACKGROUND

[0002] With the continuous improvement of environmental awareness, hybrid electric vehicles (HEV) have become an important development direction of the automobile market. A hybrid electric vehicle is a vehicle that combines an internal combustion engine (usually a gasoline or diesel internal combustion engine) and an electric motor as a power source.

[0003] The energy management of a hybrid electric vehicle is achieved by managing energy according to the energy storage of different energy sources. For example, when there is more fuel and less battery power stored in the hybrid electric vehicle, the fuel mode is preferred for driving, that is, the vehicle is driven by consuming fuel through the internal combustion engine, and when there is more battery power and less fuel in the hybrid electric vehicle, the pure electric mode is preferred for driving. However, the above energy management method is relatively single and the energy utilization efficiency is low. SUMMARY

[0004] The embodiments of the present application provide a vehicle energy management method, device, equipment, medium and product. The technical solution is as follows:

[0005] In one aspect, a vehicle energy management method is provided, the method comprising:

[0006] obtaining driving state information of a target vehicle, the driving state information being used to indicate the state of the target vehicle and the state of the driving environment during driving;

[0007] obtaining driver state information of the target vehicle, the driver state information being used to indicate the state of the driver operating the target vehicle during driving;

[0008] generating an energy distribution strategy of the target vehicle based on the driving state information and the driver state information, the energy distribution strategy being used to indicate the distribution mode of the energy used to drive the target vehicle;

[0009] distributing the energy of the target vehicle based on the energy distribution strategy, and driving the target vehicle.

[0010] In another aspect, a vehicle energy management device is provided, the device comprising:

[0011] an obtaining module configured to obtain driving state information of a target vehicle, the driving state information being used to indicate the state of the target vehicle and the state of the driving environment during driving;

[0012] The acquisition module is further configured to acquire driver state information of the target vehicle, the driver state information being used to indicate a state of the driver operating the target vehicle during driving;

[0013] The generation module is configured to generate an energy distribution strategy of the target vehicle based on the driving state information and the driver state information, the energy distribution strategy being used to indicate a distribution manner of energy used for driving the target vehicle;

[0014] The driving module is configured to distribute energy of the target vehicle based on the energy distribution strategy, and drive the target vehicle.

[0015] In another aspect, a computer device is provided, which includes a processor and a memory, the memory storing at least one instruction, at least one program, a code set or an instruction set, the at least one instruction, the at least one program, the code set or the instruction set being loaded and executed by the processor to implement the vehicle energy management method according to any one of the above embodiments of the present application.

[0016] In another aspect, a computer readable storage medium is provided, which stores at least one instruction, at least one program, a code set or an instruction set, the at least one instruction, the at least one program, the code set or the instruction set being loaded and executed by a processor to implement the vehicle energy management method according to any one of the above embodiments of the present application.

[0017] In another aspect, a computer program product or a computer program is provided, 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 to cause the computer device to perform the vehicle energy management method according to any one of the above embodiments.

[0018] The technical solutions provided by the present application have at least the following beneficial effects:

[0019] When driving a vehicle by energy, an energy distribution strategy of the vehicle is generated according to driving state information and driver state information of the vehicle, and then the energy is intelligently distributed according to the generated energy distribution strategy. Since the driving state of the vehicle and the object state of the driver are considered in the process of energy distribution, the use of fuel and / or electricity is optimized in different driving states of the vehicle, thereby improving the overall energy utilization efficiency. Moreover, the generation of the above energy distribution strategy takes into account the object state of the driver, so that the intelligently adjusted energy distribution provides a better driving experience for the driver. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0021] Figure 1 is a flow chart of a vehicle energy management method provided by an exemplary embodiment of the present application;

[0022] Figure 2 is a structure block diagram of a vehicle energy management device provided by an exemplary embodiment of the present application;

[0023] Figure 3 is a structure block diagram of a vehicle energy management device provided by an exemplary embodiment of the present application;

[0024] Figure 4 is a schematic diagram of an energy system of a target vehicle provided by an exemplary embodiment of the present application;

[0025] Figure 5 is a schematic diagram of an energy management device provided by an exemplary embodiment of the present application;

[0026] Figure 6 is a structure schematic diagram of an on-board controller provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0028] It should be noted that, before collecting the relevant data of the user and during the process of collecting the relevant data of the user, the present application can display a prompt interface, a pop-up window or output voice prompt information, the prompt interface, the pop-up window or the voice prompt information is used to prompt that the present application is currently collecting the relevant data of the user, so that the present application only starts to perform the related steps of obtaining the relevant data of the user after obtaining the confirmation operation of the user to the prompt interface or the pop-up window, otherwise (i.e. without obtaining the confirmation operation of the user to the prompt interface or the pop-up window), ending the related steps of obtaining the relevant data of the user, i.e. not obtaining the relevant data of the user. In other words, all the user data collected by the present application is collected under the condition that the user agrees and authorizes, and the collection, use and processing of the relevant user data need to comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0029] Please refer to Figure 1Fig. 1 shows a flowchart of a method for managing energy of a vehicle according to an example embodiment of the present application, which includes steps 110-140.

[0030] In step 110, driving state information of the target vehicle is acquired.

[0031] Optionally, the target vehicle can be implemented as an Internal Combustion Engine Vehicle (ICEV), an Electric Vehicle (EV), a hybrid vehicle, a Plug-in Hybrid Electric Vehicle (PHEV), a Range-Extended Electric Vehicle (REEV), a Fuel Cell Electric Vehicle (FCEV), a Mild Hybrid Vehicle (MHV), etc., which is not limited herein.

[0032] In the embodiments of the present application, the driving state information is used to indicate the state of the target vehicle and the state of the driving environment during driving. Optionally, the vehicle driving state information can include at least one of speed information, engine speed information, battery state information, oil pressure and water temperature information, tire pressure information, total driving distance information, this trip driving distance information, engine load information, gearbox state information, brake system state information, Global Positioning System (GPS) position information, ambient temperature information, vehicle interior temperature information, vehicle stability information, road condition information, navigation path information, remaining fuel amount information, remaining electric quantity information, vehicle health information, etc.

[0033] In some embodiments, the driving state information of the target vehicle can be detected by sensors on the target vehicle, for example, speed information is detected by a speed sensor, oil pressure is detected by a pressure sensor, water temperature is detected by a temperature sensor, tire pressure is detected by a pressure sensor, etc.

[0034] In some embodiments, the driving state information of the target vehicle can be acquired by instruments carried by the target vehicle itself, for example, engine speed information is acquired by a tachometer, speed information is acquired by a speedometer, total driving distance information is acquired by an odometer, etc.

[0035] In step 120, driver state information of the target vehicle is acquired.

[0036] In the embodiments of the present application, the driver state information is used to indicate the state of the driver operating the target vehicle during driving. Optionally, the driver state information includes at least one of a physiological state, a psychological state, a behavior characteristic, etc. of the driver, wherein the physiological state includes a heart rate, a blood pressure, a fatigue degree, a body posture, etc. of the driver, the psychological state includes an emotion, a concentration degree, a driving stress, etc. of the driver, and the behavior characteristic includes a driving behavior mode (such as sudden acceleration, sudden deceleration, sudden turning, etc.), a driving habit (such as overspeeding, frequent lane changing, etc.), a driving skill level, etc. of the driver.

[0037] In some embodiments, the physiological state of the driver can be detected by a detection device connected to the target vehicle. In one example, the driver wears a smart watch, and a vehicle terminal of the target vehicle is connected to the smart watch to obtain a detection result of the physiological state of the driver by the smart watch.

[0038] In some embodiments, the psychological state of the driver can be detected by facial recognition of the driver. For example, the target vehicle captures a facial expression of the driver by a vehicle camera to identify the current emotion and concentration degree of the driver.

[0039] In some embodiments, the psychological state of the driver can also be predicted by a pre-trained Artificial Intelligence (AI) model. Illustratively, the target vehicle continuously collects a video of the driver during driving of the vehicle, inputs the video image into the pre-trained AI model, and analyzes the video image by the AI model to automatically identify the psychological state of the driver, such as whether the driver is tired or in a stress state.

[0040] Optionally, the AI model can be implemented by a Convolutional Neural Networks (CNN), a Feedforward Neural Network (FNN), a Residual Network (ResNet), a Transformer, etc. neural network model, which is not specifically limited herein.

[0041] In some embodiments, the behavior characteristic of the driver can be obtained by recording the operation habit of the driver during driving, wherein the operation habit includes a steering wheel turning angle, a driving speed, a driving trajectory, an acceleration change, a lane deviation frequency, etc.

[0042] In some embodiments, the behavior characteristics of the driver can also be predicted by a pre-trained AI model. Illustratively, the target vehicle continuously collects videos of the driver during vehicle driving, inputs the video images into the pre-trained AI model, and automatically identifies the behavior characteristics of the driver, such as whether the driver smokes or plays with the mobile phone during driving, by analyzing the video images with the AI model.

[0043] In step 130, an energy distribution strategy of the target vehicle is generated based on the driving state information and the driver state information.

[0044] In some embodiments, when the target vehicle is a gasoline car, the energy of the target vehicle comes from gasoline, i.e., the chemical energy is converted into mechanical energy for driving the vehicle by burning gasoline in the internal combustion engine. When the target vehicle is an electric car, the energy of the target vehicle comes from the battery, i.e., the mechanical energy is converted from the electrical energy stored in the battery for driving the vehicle. When the target vehicle is a hybrid car, since the hybrid car combines the internal combustion engine and the electric motor, the energy of the target vehicle includes both the mechanical energy produced by the gasoline and the mechanical energy produced by the electrical energy.

[0045] In the embodiments of the present application, the energy distribution strategy is used to indicate the distribution mode of the energy used to drive the target vehicle, i.e., the distribution mode of the energy when the energy of the target vehicle is managed, so as to achieve adaptive distribution of the mechanical energy produced by the target vehicle.

[0046] In some embodiments, the above-mentioned energy distribution strategy can be predicted by a pre-trained AI model, i.e., the driving state information and the driver state information are input into the pre-trained AI model, and the energy distribution mode matching the driving state information and the driver state information is predicted by the AI model, so as to generate the energy distribution strategy.

[0047] In some embodiments, the energy distribution strategy is used to control the driving mode and / or the driving mode of the target vehicle.

[0048] The driving mode is used to indicate the power transmission mode of the target vehicle, i.e., different power transmission and performance settings that the car can be configured to adapt to different driving conditions and driver preferences. Optionally, the above-mentioned driving mode includes standard mode, economy mode, sports mode, snow mode, off-road mode, trailer mode, electric mode, hybrid mode, internal combustion engine driving mode, regenerative braking mode, range extending mode, four-wheel drive mode, front-wheel drive mode, rear-wheel drive mode, etc.

[0049] The driving mode is used to indicate the setting of the operation mode of the target vehicle. Optionally, the above-mentioned driving mode includes automatic driving mode, manual driving mode, assisted driving mode, etc.

[0050] In some embodiments, the driving mode of the target vehicle is determined according to the driving state information, the driving mode of the target vehicle is determined according to the driving state information and the driver state information, and the energy distribution strategy of the target vehicle is generated according to the driving mode and the driving mode.

[0051] In some embodiments, taking the target vehicle as a hybrid vehicle for example, the driving mode of the target vehicle includes a pure electric mode, a hybrid mode and a fuel mode, and the driving mode includes an automatic driving mode, a manual driving mode and an assisted driving mode, and the driving mode and the driving mode are combined to obtain nine kinds.

[0052] In some embodiments, the driving mode of the target vehicle can be determined according to the road condition information in the driving state information, that is, the driving state information includes the road condition information, the path planning result is generated according to the road condition information, the path planning result is used to indicate the driving path of the target vehicle under the current road condition, and the matching driving mode is determined according to the path planning result.

[0053] Optionally, the path planning result includes at least one of the road type, the traffic condition, the road slope and the road surface condition of the planned driving road. The road type includes an urban road, an expressway and a rural road; the traffic condition includes a congested section, a multi-intersection section and a smooth section; the road slope includes a flat road, an uphill and a downhill; and the road surface condition includes a wet or icy road surface and a dry road surface.

[0054] Taking the target vehicle as a hybrid vehicle for example, when the road type of the current driving road is included in the path planning result, when the path planning result indicates that the planned driving section is an urban road, since the vehicle speed is usually low and the vehicle frequently starts and stops in the urban road, the matching driving mode can be set to the pure electric mode; when the path planning result indicates that the planned driving section is an expressway, since the vehicle speed is high and relatively constant on the expressway, the matching driving mode can be set to the hybrid mode or the fuel mode to provide continuous power output; when the path planning result indicates that the planned driving section is a rural road, since the rural road may contain some slopes and uneven road surfaces, the vehicle speed is usually low and the vehicle frequently starts and stops, and the matching driving mode can be set to the pure electric mode.

[0055] Optionally, when the traffic condition is included in the path planning result, when the path planning result indicates that the planned driving section is a congested section, since the vehicle needs to frequently start and stop on the congested section, the matching driving mode can be set to the pure electric mode or the hybrid mode to reduce energy consumption by using the energy recovery system; when the path planning result indicates that the planned driving section is a smooth section, since the vehicle speed can be kept high and relatively constant on the smooth section, the matching driving mode can be set to the hybrid mode or the fuel mode to provide stable power output.

[0056] Optionally, when the road slope is included in the path planning result, when the path planning result indicates that the planned driving section is flat ground, the matched driving mode can be set as the pure electric mode or the hybrid mode; when the path planning result indicates that the planned driving section is uphill, since a larger power output is required for uphill, the matched driving mode can be set as the hybrid mode or the fuel mode; when the path planning result indicates that the planned driving section is downhill, since the downhill can utilize the brake energy recovery, the matched driving mode can be set as the hybrid mode or the pure electric mode.

[0057] Optionally, when the road surface condition is included in the path planning result, when the path planning result indicates that the road surface condition of the planned driving section is wet or icy road surface, since higher grip and stability are required under this road surface condition, the matched driving mode can be set as the hybrid mode; when the path planning result indicates that the road surface condition of the planned driving section is dry road surface, the matched driving mode can be set as the pure electric mode.

[0058] In some embodiments, the driving state information includes vehicle state information. In a case where a vehicle state indicated by the vehicle state information meets an automatic driving requirement, a state analysis is performed on a driver state indicated by the driver state information to obtain a driver state score, in a case where the driver state score is lower than a preset score threshold, it is determined that the driving mode of the target vehicle is the automatic driving mode and / or the auxiliary driving mode, and in a case where the driver state score reaches the preset score threshold, it is determined that the driving mode of the target vehicle is the manual driving mode.

[0059] Optionally, the vehicle state information includes at least one of remaining fuel amount information, remaining electric quantity information, and vehicle health degree information. In some embodiments, when the remaining fuel amount information and / or the remaining electric quantity information reaches a first preset threshold, and / or when the vehicle health degree information reaches a second preset threshold, it is determined that the vehicle state indicated by the vehicle state information meets the automatic driving requirement.

[0060] In a case where it is determined that the vehicle state indicated by the vehicle state information meets the automatic driving requirement, a state analysis is performed on a driver state indicated by the driver state information to obtain a driver state score. In some embodiments, the driver state information includes a plurality of candidate state information, and the state analysis is performed according to the plurality of candidate state information to obtain the driver state score.

[0061] Optionally, the determination manner of the driver state score can be implemented by a pre-designed calculation formula. Illustratively, different weights are assigned to different candidate state information, a corresponding state score is determined according to the candidate state information, and the state scores of the plurality of candidate state information are weighted and summed according to the corresponding weights, so as to obtain the driver state score. For example, when the candidate state information is the fatigue degree of the driver, the current fatigue degree of the driver is 68%, and the corresponding matching state score is 0.32, that is, the fatigue degree and the state score are in a negative correlation relationship, and the higher the fatigue degree of the driver, the lower the state score.

[0062] Optionally, the above-mentioned preset score threshold can be a fixed value set by the system or a custom value set by the user, which is not limited herein.

[0063] In the embodiments of the present application, after the driving mode and the driving mode are determined, the energy distribution strategy is determined according to the driving mode and the driving mode.

[0064] Optionally, when the driving mode is the automatic driving mode and the driving mode is the pure electric driving mode, the energy distribution strategy can be implemented as follows:

[0065] 1. Starting and low-speed driving: using the electric motor to output power energy with low power to ensure smooth starting and low-speed driving, and distributing the power energy to the automatic driving system to control the starting and low-speed driving through sensors and algorithms to reduce unnecessary acceleration and deceleration to optimize energy efficiency;

[0066] 2. Medium-speed driving and cruising: maintaining stable electric motor output power in medium-speed and cruising states to run at the best efficiency, and distributing the power energy to the automatic driving system to automatically adjust the vehicle speed according to traffic flow and the front road condition to avoid frequent acceleration and deceleration;

[0067] 3. Deceleration and parking: using the regenerative braking system to maximize energy recovery during deceleration and parking, and distributing the power energy to the automatic driving system to perceive the front obstacles and signal light state in advance to optimize the deceleration process.

[0068] Optionally, when the driving mode is the manual driving mode and the driving mode is the pure electric driving mode, the energy distribution strategy can be implemented as follows:

[0069] 1. Starting and low-speed driving: using the electric motor to output power energy with low power to ensure smooth starting and low-speed driving;

[0070] 2. Medium-speed driving and cruising: maintaining stable electric motor output power in medium-speed and cruising states to run at the best efficiency;

[0071] 3. Deceleration and parking: using the regenerative braking system to maximize energy recovery when the driver decelerates and parks.

[0072] Optionally, when the driving mode is the automatic driving mode and the driving mode is the fuel mode, the energy distribution strategy can be implemented as:

[0073] 1. Starting and low-speed driving: when starting and low-speed driving, the internal combustion engine runs at a low speed to ensure smooth starting and low-speed driving, and the chemical energy is distributed to convert into electric energy to supply the automatic driving system to accurately control the starting and low-speed driving through sensors and algorithms, and unnecessary acceleration and deceleration are reduced to optimize energy efficiency;

[0074] 2. Medium-speed driving and cruising: in the medium-speed and cruising state, stable internal combustion engine output power is maintained to run at the best efficiency, and the chemical energy is distributed to convert into electric energy to supply the automatic driving system to automatically adjust the vehicle speed according to the traffic flow and the road conditions ahead to avoid frequent acceleration and deceleration;

[0075] 3. Deceleration and parking: when decelerating and parking, the internal combustion engine braking and coasting strategy is used to maximize fuel efficiency.

[0076] Optionally, when the driving mode is the manual driving mode and the driving mode is the fuel mode, the energy distribution strategy can be implemented as:

[0077] 1. Starting and low-speed driving: when starting and low-speed driving, the internal combustion engine runs at a low speed to ensure smooth starting and low-speed driving;

[0078] 2. Medium-speed driving and cruising: in the medium-speed and cruising state, stable internal combustion engine output power is maintained to run at the best efficiency;

[0079] 3. Deceleration and parking: when decelerating and parking, the internal combustion engine braking and coasting strategy is used to maximize fuel efficiency.

[0080] Step 140, distributing the energy of the target vehicle based on the energy distribution strategy to drive the target vehicle.

[0081] Optionally, the stored energy of the target vehicle is distributed according to the energy distribution strategy to drive the target vehicle; and / or, the internal combustion engine and / or the electric motor of the target vehicle is controlled to perform energy production according to the energy distribution strategy to drive the target vehicle.

[0082] In some embodiments, the kinetic energy generated by the target vehicle during braking is recovered, and illustratively, the kinetic energy generated by the target vehicle during braking is recovered under the condition that the target vehicle is in the braking state to obtain recovered energy, and the recovered energy is distributed based on the energy distribution strategy to drive the target vehicle.

[0083] In some embodiments, when the target vehicle is implemented as a hybrid vehicle, since the hybrid vehicle is provided with both an internal combustion engine and an electric motor, the amount of energy that needs to be produced by the internal combustion engine and the electric motor needs to be determined according to the energy distribution strategy, so as to control the internal combustion engine and the electric motor to produce energy respectively. Illustratively, the first energy consumption demand corresponding to the internal combustion engine and the second energy consumption demand corresponding to the electric motor are determined based on the energy distribution strategy; and the internal combustion engine and the electric motor are called to produce energy based on the first energy consumption demand and the second energy consumption demand, so as to drive the target vehicle.

[0084] In summary, when driving the vehicle by energy, the energy distribution strategy of the vehicle is generated according to the driving state information and the driver state information of the vehicle, so that the intelligent distribution of energy is performed according to the generated energy distribution strategy. Since the driving state of the vehicle and the object state of the driver are considered in the process of energy distribution, the use of fuel and / or electricity is optimized in different driving states of the vehicle, so as to improve the overall energy utilization efficiency. Moreover, the generation of the above energy distribution strategy takes into account the object state of the driver, so that the intelligent adjustment of the energy distribution provides a better driving experience for the driver.

[0085] Please refer to Figure 2 which shows a structure block diagram of a vehicle energy management device provided by an exemplary embodiment of the present application, the device comprising the following modules:

[0086] The acquisition module 210 is configured to acquire driving state information of a target vehicle, the driving state information being used to indicate the state of the target vehicle and the state of the driving environment during driving;

[0087] The acquisition module 210 is further configured to acquire driver state information of the target vehicle, the driver state information being used to indicate the state of the driver operating the target vehicle during driving;

[0088] The generation module 220 is configured to generate an energy distribution strategy of the target vehicle based on the driving state information and the driver state information, the energy distribution strategy being used to indicate the distribution mode of energy used when driving the target vehicle;

[0089] The driving module 230 is configured to distribute energy of the target vehicle based on the energy distribution strategy, and drive the target vehicle.

[0090] In some optional embodiments, as shown in Figure 3 The generation module 220 further comprises:

[0091] The first determination unit 221 is configured to determine a driving mode of the target vehicle according to the driving state information, the driving mode being used to indicate the power transmission mode of the target vehicle;

[0092] The first determination unit 221 is further configured to determine a driving mode of the target vehicle according to the driving state information and the driver state information, the driving mode being used to indicate a setting of an operation mode of the target vehicle.

[0093] The generation unit 222 is configured to generate an energy distribution strategy of the target vehicle according to the driving mode and the driving mode.

[0094] In some optional embodiments, the driving state information includes road condition state information.

[0095] The generation unit 222 is further configured to generate a path planning result according to the road condition state information, the path planning result being used to indicate a driving path of the target vehicle in a current road condition.

[0096] The first determination unit 221 is further configured to determine a matched driving mode according to the path planning result.

[0097] In some optional embodiments, the driving state information includes vehicle state information.

[0098] The first determination unit 221 is further configured to perform state analysis on a driver state indicated by the driver state information to obtain a driver state score, in a case where a vehicle state indicated by the vehicle state information meets an automatic driving demand.

[0099] The first determination unit 221 is further configured to determine that the driving mode of the target vehicle is an automatic driving mode, in a case where the driver state score is lower than a preset score threshold.

[0100] The first determination unit 221 is further configured to determine that the driving mode of the target vehicle is a manual driving mode, in a case where the driver state score reaches the preset score threshold.

[0101] In some optional embodiments, the apparatus further includes:

[0102] The recycling module 240 is configured to recycle kinetic energy generated by the target vehicle in a braking process, to obtain recycled energy, in a case where the target vehicle is in a braking state.

[0103] The driving module 230 is further configured to distribute the recycled energy based on the energy distribution strategy, and drive the target vehicle.

[0104] In some optional embodiments, the driving module 230 further includes:

[0105] The second determination unit 231 is configured to determine a first energy consumption demand of the internal combustion engine and a second energy consumption demand of the electric motor based on the energy distribution strategy.

[0106] The driving unit 232 is configured to invoke the internal combustion engine and the electric motor to produce energy based on the first energy consumption demand and the second energy consumption demand, so as to drive the target vehicle.

[0107] In summary, when driving the vehicle by energy, the energy distribution strategy of the vehicle is generated according to the driving state information and the driving state information of the vehicle, so that the intelligent distribution of energy is performed according to the generated energy distribution strategy. Since the driving state of the vehicle and the object state of the driver are considered in the process of energy distribution, the use of fuel and / or electricity is optimized in different driving states of the vehicle, thereby improving the overall energy utilization efficiency, and the generation of the above-mentioned energy distribution strategy takes into account the object state of the driver, so that the intelligent adjustment of the energy distribution provides a better driving experience for the driver.

[0108] It should be noted that the vehicle energy management device provided in the above embodiment is only exemplified by the division of the above functional modules. In actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions. In addition, the vehicle energy management device and the vehicle energy management method provided in the above embodiment belong to the same concept, and the specific implementation process is described in detail in the method embodiment, which will not be repeated here.

[0109] Please refer to Figure 4 which shows an energy system 400 of a target vehicle provided by an example embodiment of the present application, the energy system 400 comprising an energy storage device 410, an energy recovery device 420, an energy management device 430, and an energy output device 440.

[0110] The energy storage device 410 is configured to store the electric energy and / or chemical energy produced by the target vehicle.

[0111] In the embodiments of the present application, the energy storage device 410 is a device for performing energy storage in the target vehicle. Optionally, the energy storage device 410 comprises a battery, a lead-acid battery, a lithium-ion battery, a super capacitor, a fuel cell and other devices capable of storing energy.

[0112] Optionally, when the target vehicle is a fuel automobile, the energy storage device 410 is implemented as a lead-acid battery; optionally, when the target vehicle is a pure electric vehicle, the energy storage device 410 is implemented as a lithium-ion battery; optionally, when the target vehicle is a hybrid vehicle, the energy storage device 410 is implemented as at least one of a nickel-hydrogen battery, a lithium-ion battery and a lead-acid battery.

[0113] In some embodiments, the energy storage device 410 adopts a combination of lithium-ion batteries and super capacitors, which can provide higher energy density and fast charging and discharging performance.

[0114] An energy recovery device 420 is configured to recover kinetic energy generated by the target vehicle in a braking state, and obtain recovered energy.

[0115] In the embodiments of the present application, the energy recovery device 420 recovers part of the kinetic energy when the target vehicle is decelerating or braking, and converts the kinetic energy into electrical energy for storage for subsequent use. Optionally, the energy recovery device 420 can be implemented as a generator and a motor.

[0116] Illustratively, when it is detected that the driver steps on the brake pedal or releases the accelerator pedal, the vehicle starts to decelerate, and the energy recovery device 420 controls the electric motor to switch to a generator mode. When the vehicle is decelerating, the wheels drive the rotor of the electric motor to rotate through the transmission system. In the generator mode, the rotation of the rotor drives the magnetic field change in the generator, and according to Faraday's law of electromagnetic induction, an electric current is generated. That is, the electric motor can work in both directions, that is, it can drive the wheels as an electric motor, and it can also recover energy as a generator. During regenerative braking, the electric motor switches to the generator mode to realize the recovery of electrical energy during braking.

[0117] Illustratively, the energy recovery device 420 transmits the electric current generated during braking to the energy storage device 410 and stores it as electrical energy.

[0118] In some embodiments, the energy recovery device 420 is also used for heat energy recovery, that is, the exhaust heat energy during the driving of the target vehicle is recovered and used to heat the vehicle or stored in the battery.

[0119] In some embodiments, the energy recovery device 420 uses a permanent magnet synchronous motor as a generator, which can achieve efficient energy recovery.

[0120] An energy management device 430 is configured to manage and control the entire energy system 400.

[0121] Optionally, the management of the energy management device 430 on the energy system 400 includes energy state monitoring, energy distribution, and optimized control.

[0122] In some embodiments, the energy management device 430 is configured to obtain driving state information of the target vehicle, the driving state information being used to indicate a state of the target vehicle and a state of a driving environment during driving; obtain driver state information of the target vehicle, the driver state information being used to indicate a state of the driver operating the target vehicle during driving; generate an energy distribution strategy of the target vehicle based on the driving state information and the driver state information, the energy distribution strategy being used to indicate a distribution manner of energy used for driving the target vehicle; and distribute energy of the target vehicle based on the energy distribution strategy, and drive the target vehicle.

[0123] In some embodiments, the energy management device 430 is further configured to determine a driving mode of the target vehicle according to the driving state information, the driving mode being used to indicate a power transmission mode of the target vehicle; determine a driving mode of the target vehicle according to the driving state information and the driver state information, the driving mode being used to indicate a setting of an operation mode of the target vehicle; and generate an energy distribution strategy of the target vehicle according to the driving mode and the driving mode.

[0124] In some embodiments, the driving state information includes road condition state information, and the energy management device 430 is further configured to generate a path planning result according to the road condition state information, the path planning result being used to indicate a driving path of the target vehicle under a current road condition; and determine a matched driving mode according to the path planning result.

[0125] In some embodiments, the driving state information includes vehicle state information, and the energy management device 430 is further configured to, in a case where a vehicle state indicated by the vehicle state information meets an automatic driving demand, perform state analysis on a driver state indicated by the driver state information to obtain a driver state score; in a case where the driver state score is lower than a preset score threshold, determine that the driving mode of the target vehicle is an automatic driving mode; and in a case where the driver state score reaches the preset score threshold, determine that the driving mode of the target vehicle is a manual driving mode.

[0126] In some embodiments, the energy management device 430 is further configured to distribute the recovered energy based on the energy distribution strategy, and control the energy output device 440 to drive the target vehicle. The recovered energy is kinetic energy generated by the target vehicle in a braking process and recovered by the energy recovery device 420 in a case where the target vehicle is in a braking state.

[0127] In some embodiments, the energy management device 430 is further configured to determine a first energy consumption demand corresponding to the internal combustion engine and a second energy consumption demand corresponding to the electric motor based on the energy distribution strategy; and call the internal combustion engine and the electric motor to produce energy based on the first energy consumption demand and the second energy consumption demand, and control the energy output device 440 to drive the target vehicle.

[0128] In some embodiments, the energy management device 430 uses a microcontroller as a core controller, collects energy state and driving state data of the vehicle through a sensor, and controls energy distribution and optimization control after algorithm processing.

[0129] In the embodiments of the present application, the energy output device 440 is used to convert stored electrical energy and chemical energy into driving power of the target vehicle, i.e., convert electrical energy and / or chemical energy into mechanical energy.

[0130] In some embodiments, the energy output device 440 is a combination of a motor, an engine and a transmission, and can automatically switch the driving mode according to the driving state of the vehicle and the demand of the driver.

[0131] In some embodiments, as shown in FIG. 5, which shows a schematic diagram of an energy management device according to an exemplary embodiment of the present application, the energy management device further comprises an information collection module 510, an information processing module 520 and a decision module 530. Figure 5

[0132] The information collection module 510 is configured to collect information related to the target vehicle during driving for generating an energy distribution strategy. Illustratively, the information collection module 510 comprises a driver state monitoring unit 511, a road condition monitoring unit 512 and a vehicle state monitoring unit 513.

[0133] The driver state monitoring unit 511 is configured to monitor driver state information, which is used to indicate the objective state of the driver of the target vehicle during driving. Optionally, the driver state information comprises at least one of the physiological state, the psychological state and the behavior characteristics of the driver, wherein the physiological state comprises the heart rate, the blood pressure, the fatigue degree and the body posture of the driver, the psychological state comprises the emotion, the attention concentration and the driving stress of the driver, and the behavior characteristics comprise the driving behavior mode (such as sudden acceleration, sudden deceleration and sudden turn), the driving habit (such as overspeed and frequent lane changing) and the driving skill level of the driver.

[0134] The road condition monitoring unit 512 is configured to monitor the road condition of the current driving road of the target vehicle. Optionally, the road condition can comprise the road type, the real-time traffic condition, the construction information, the traffic signal, the weather condition, the road surface condition and the public transportation information.

[0135] The vehicle state monitoring unit 513 is configured to monitor the vehicle state information of the target vehicle. Optionally, the vehicle state information comprises at least one of the remaining fuel amount information, the remaining electric quantity information and the vehicle health degree information.

[0136] The information processing module 520 is configured to process the information collected by the information collection module 510. Illustratively, the information processing module 520 comprises a driver state evaluation unit 521, a road condition analysis processing unit 522 and a vehicle state analysis processing unit 523.

[0137] ​The driver state evaluation unit 521 is configured to perform state analysis on the driver state information monitored by the driver state monitoring unit 511 to obtain a driver state score. In some embodiments, the driver state information includes a plurality of candidate state information, and the state analysis is performed on the plurality of candidate state information to obtain the driver state score. Alternatively, the driver state score can be determined by a pre-designed calculation formula. For example, different weights are assigned to different candidate state information, and a corresponding state score is determined according to the candidate state information. The state scores of the plurality of candidate state information are weighted and summed according to the corresponding weights to obtain the driver state score. For example, when the candidate state information is the fatigue degree of the driver, the current fatigue degree of the driver is 68%, and the corresponding matching state score is 0.32. That is, the fatigue degree and the state score are negatively correlated. The higher the fatigue degree of the driver, the lower the state score.

[0138] The road condition analysis processing unit 522 is configured to analyze and process the road condition monitored by the road condition monitoring unit 512. Alternatively, the analysis and processing can be implemented by analyzing the traffic flow of the driving section, i.e., analyzing the change trend of the traffic flow to identify peak hours. Alternatively, the analysis and processing can also be implemented by calculating the average speed of the vehicle to identify congestion areas. Alternatively, the analysis and processing can also be implemented by detecting traffic accidents through abnormal data or user reports. Alternatively, the analysis and processing can also be implemented by analyzing the influence of weather conditions on the road. Alternatively, the road condition analysis processing unit 522 can establish a prediction model for road condition analysis by using historical data to analyze and process the road condition. Alternatively, the road condition analysis processing unit 522 can use a machine learning algorithm (such as a neural network) to analyze and process the road condition.

[0139] The vehicle state analysis processing unit 523 is configured to analyze the vehicle state of the target vehicle according to the vehicle state information monitored by the vehicle state monitoring unit 513. Illustratively, the vehicle state analysis processing unit 523 performs cleaning and standardization processing on the obtained vehicle state information to ensure the accuracy and consistency of the data. The vehicle state analysis processing unit 523 determines whether the vehicle state of the target vehicle is within the normal working range according to the vehicle state information, for example, whether the engine temperature exceeds a pre-set temperature threshold. The vehicle state analysis processing unit 523 evaluates the performance of the vehicle according to the vehicle state information, such as fuel efficiency, power output, and emission level.

[0140] The decision module 530 is configured to generate decisions according to the information processed by the information processing module 520. The decision module 530 includes a path generation unit 531, an automatic driving switching unit 532, an automatic adjustment unit 533, and an emergency assistance unit 534.

[0141] The path generation unit 531 is configured to generate a path planning result of the target vehicle, and the path planning result is configured to indicate a driving path of the target vehicle under a current road condition.

[0142] The automatic driving switching unit 532 is configured to switch a driving mode of the target vehicle, including switching from a manual driving mode to an automatic driving mode, and switching from the automatic driving mode to the manual driving mode.

[0143] The automatic adjustment unit 533 is configured to generate an energy distribution strategy of the target vehicle according to the driving state information and the driver state information, and control an energy output device of an energy system to output energy to drive the target vehicle according to the energy distribution strategy.

[0144] The emergency assistance unit 534 is configured to perform emergency treatment on the target vehicle. Illustratively, the emergency assistance unit 434 detects an accident of the target vehicle, and automatically contacts an emergency service when detecting that the vehicle has an accident.

[0145] In some embodiments, the energy system 400 described above can realize the following functions: real-time monitoring of the energy state of the vehicle, including battery power, engine temperature, and fuel consumption; automatic energy distribution according to the driving state of the vehicle and the demand of the driver, optimizing energy utilization efficiency; automatically recovering braking energy when the vehicle brakes, improving energy recovery effect; automatically switching the driving mode according to the driving state of the vehicle and the demand of the driver, improving driving experience and energy saving effect.

[0146] The energy system 400 provided by the embodiments of the present application has at least the following beneficial effects: improving energy utilization rate: reducing unnecessary energy waste by optimizing energy distribution and control strategy; improving energy recovery effect: recovering and storing the energy generated during braking through an efficient energy recovery system; reducing energy consumption and emissions: reducing energy consumption and emissions by optimizing control strategy and automatically switching driving mode; improving driving experience: improving driving experience and energy saving effect by automatically switching driving mode.

[0147] The present application also provides a vehicle-mounted controller for implementing the vehicle energy management method provided by the embodiments of the present application. The vehicle-mounted controller includes a processor and a memory, and the memory stores at least one instruction. The at least one instruction is loaded and executed by the processor to implement the engine start-stop control method provided by each of the above-mentioned method embodiments. It should be noted that the vehicle-mounted controller can be, for example, Figure 6 the vehicle-mounted controller provided by the present application.

[0148] Figure 6 is a structural schematic diagram of the vehicle-mounted controller provided by the embodiments of the present application. As shown in Figure 6 the vehicle-mounted controller 600 includes a processor 601 and a memory 602.

[0149] The processor 601 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 601 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 601 can also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also referred to as a CPU (Central Processing Unit), and the coprocessor being a low-power processor for processing data in a standby state. In some embodiments, the processor 601 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing of content to be displayed by the display screen. In some embodiments, the processor 601 can further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

[0150] The memory 602 can include one or more computer-readable storage media that can be non-transitory. The memory 602 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 602 is used to store at least one instruction for being executed by the processor 601 to implement the control method of the hybrid vehicle provided in the embodiments of the present disclosure.

[0151] Those skilled in the art can understand that the structure shown in the figure does not constitute a limitation on the vehicle controller 600, and can include more or fewer components than shown, or combine certain components, or adopt different component arrangements. Figure 6 The vehicle controller 600 shown in the figure does not constitute a limitation on the vehicle controller 600, and can include more or fewer components than shown, or combine certain components, or adopt different component arrangements.

[0152] The memory further includes one or more programs stored in the memory, the one or more programs containing a method for managing the energy source of the vehicle.

[0153] The application further provides a computer device, comprising a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory medium, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to realize the vehicle energy management method provided by each method embodiment.

[0154] The application further provides a computer readable storage medium, and at least one instruction, at least one program, a code set or an instruction set is stored in the storage medium, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to realize the vehicle energy management method provided by each method embodiment.

[0155] The application further provides a computer program product or a computer program, and the computer program product or the computer program comprises computer instructions 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 vehicle energy management method provided in the above optional implementation.

[0156] The above-mentioned application embodiment serial numbers are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0157] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiments can be completed by hardware, or by program to instruct related hardware to complete, and the program can be stored in a computer readable storage medium. The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk.

[0158] The above-mentioned is only an exemplary embodiment which can be implemented by the application, and is not used to limit the application. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method of managing energy sources of a vehicle, characterized by, The method comprises: obtaining driving state information of a target vehicle, the driving state information being used to indicate states of the target vehicle and states of a driving environment during driving, and the driving state information comprising road condition state information and vehicle state information; obtaining driver state information of the target vehicle, the driver state information being used to indicate a state of a driver operating the target vehicle during driving; generating a path planning result according to the road condition state information, the path planning result being used to indicate a driving path of the target vehicle under a current road condition; determining a matched driving mode according to the path planning result, the driving mode being used to indicate a power transmission mode of the target vehicle; in a case where a vehicle state indicated by the vehicle state information meets an automatic driving demand, performing state analysis on a driver state indicated by the driver state information to obtain a driver state score; in a case where the driver state score is lower than a preset score threshold, determining that a driving mode of the target vehicle is an automatic driving mode; in a case where the driver state score reaches the preset score threshold, determining that the driving mode of the target vehicle is a manual driving mode; generating an energy distribution strategy of the target vehicle according to the driving mode and the driving mode, the energy distribution strategy being used to indicate a distribution mode of energy used for driving the target vehicle; distributing energy of the target vehicle based on the energy distribution strategy to drive the target vehicle.

2. The method of claim 1, wherein, The distributing energy of the target vehicle based on the energy distribution strategy to drive the target vehicle comprises: in a case where the target vehicle is in a braking state, recycling kinetic energy generated by the target vehicle during braking to obtain recycled energy; distributing the recycled energy based on the energy distribution strategy to drive the target vehicle.

3. The method of claim 1, wherein, The distributing energy of the target vehicle based on the energy distribution strategy to drive the target vehicle comprises: determining a first energy consumption demand corresponding to an internal combustion engine and a second energy consumption demand corresponding to an electric motor based on the energy distribution strategy; calling the internal combustion engine and the electric motor to produce energy based on the first energy consumption demand and the second energy consumption demand to drive the target vehicle.

4. A device for managing energy sources of a vehicle, characterized in that The device comprises: an obtaining module, configured to obtain driving state information of a target vehicle, the driving state information being used to indicate states of the target vehicle and states of a driving environment during driving, and the driving state information comprising road condition state information and vehicle state information; the obtaining module is further configured to obtain driver state information of the target vehicle, the driver state information being used to indicate a state of a driver operating the target vehicle during driving; a generating unit, configured to generate a path planning result according to the road condition state information, the path planning result being used to indicate a driving path of the target vehicle under a current road condition; a first determining unit, configured to determine a matched driving mode according to the path planning result, the driving mode being used to indicate a power transmission mode of the target vehicle; The first determination unit is further configured to perform state analysis on the driver state indicated by the driver state information to obtain a driver state score, in a case where the vehicle state indicated by the vehicle state information meets an automatic driving requirement. The first determination unit is further configured to determine that the driving mode of the target vehicle is an automatic driving mode, in a case where the driver state score is lower than a preset score threshold. The first determination unit is further configured to determine that the driving mode of the target vehicle is a manual driving mode, in a case where the driver state score reaches the preset score threshold. The generation unit is further configured to generate an energy distribution strategy of the target vehicle according to the driving mode and the driving mode, the energy distribution strategy being used to indicate a distribution manner of energy used for driving the target vehicle. The driving module is configured to distribute energy of the target vehicle based on the energy distribution strategy, and drive the target vehicle.

5. A computer device, comprising: The computer device includes a processor and a memory, and the memory stores at least one program, which is loaded and executed by the processor to implement the vehicle energy management method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one program code, which is loaded and executed by the processor to implement the vehicle energy management method according to any one of claims 1 to 3.

7. A computer program product, characterised in that, The computer program or instruction is executed by the processor to implement the vehicle energy management method according to any one of claims 1 to 3.

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