10623results about "Hybrid vehicles" patented technology

A dual-motor mixed-hybrid powertrain system, by performing pulse modulation control, i.e., series-hybrid intelligent start-stop control or parallel-hybrid intelligent power switching control, on the instantaneous power time-varying functions of an engine and a battery pack, can convert the surface working condition of an analog electric control engine into a simpler line working condition of a digital pulse control (DPC) engine, either a pre-determined high-state line working condition in the high-efficiency combustion area or a pre-determined non-combustion low-state line working condition with zero fuel consumption and zero pollutant emissions multiplexed in time. The traditional fixed one-to-one bidirectional mapping between an engine working condition and a vehicle working condition is converted into a dynamically adjustable many-to-many bidirectional mapping to achieve the full coverage of any overall vehicle working condition, achieving decoupling between a DPC engine working condition and the overall vehicle working condition and decoupling between software and hardware of a hybrid powertrain.

A Level IV fuel-saving robot system for ACE HDTs of the present disclosure focuses on the minimization of actual fuel consumption (L / 100 km) for long-haul freight at first based on an electrical power split device (ePSD) and a mixed hybrid powertrain architecture. A basic model Level I fuel-saving robot realizes a longitudinal L1 automatic driving function through a predictive adaptive cruise (PACC) technology within an Operational Design Domain (ODD) for highways and reduces the actual fuel consumption of an ACE HDT by more than 20% compared with modern diesel HDTs, and the energy-saving and emission-reducing effect of the basic model Level I fuel-saving robot is decoupled from both the technical level of a vehicle engine and the driving level of a driver; an advanced Level IV fuel-saving robot has a L4 automatic driving function within the ODD for highways, operates in a “shadow mode” or “detached mode”, automatically generates a discrepancy report or detachment report, completes the “3R” batch validation for an L4 system on a billion mile scale quickly with high cost effectiveness on the premise of ensuring the traffic safety of existing road users and reduces the total validation expense by more than 65% compared with the modern HDT with internal combustion engine equipped with the L4 system, promoting the early commercialization of the Level IV fuel-saving robot.

This application discloses a method, system, and related equipment for intelligent energy management of new energy vehicles. Based on the vehicle's starting and ending points, at least one candidate energy-saving path is determined. The predicted energy consumption of the vehicle along at least one candidate energy-saving path is lower than that of other paths. The total energy consumption is predicted based on road condition information and energy consumption impact information for each path. In response to the selection of at least one candidate energy-saving path, a preset travel route is determined. The preset travel route includes multiple road segments, and the total energy consumption includes the energy consumption of each road segment. With the goal of minimizing fuel consumption along the preset travel route, the engine's operating state is controlled based on the initial state of charge (SOC) of the power battery in each road segment, the energy consumption of the road segment, and the vehicle's actual overall demand, ensuring the engine operates within its high-efficiency range. Using this application can reduce fuel consumption for users and improve the driving experience.

There is provided a control system for an electric vehicle comprising a power train, the control system comprising: a first controller configured to automatically select a drive mode for the vehicle based on a whole vehicle operation model; and a second controller coupled to the first controller, the second controller configured to adjust a set of tuning parameters for the vehicle, whereby the second controller is configured to receive a signal from the first controller to adjust the set of tuning parameters such that the vehicle operates in the selected drive mode. Thus enhancing the operation and durability characteristics of the vehicle.

The invention relates to the technical field of new energy vehicles, in particular to a multi-working-condition energy management method and system for a hybrid chariot, and the method comprises the steps: determining a corresponding working condition weight coefficient through obtaining the altitude, environment temperature and road condition data in real time, and the real-time working parameters of three power sources, namely an engine, a fuel cell and a lithium battery, so as to achieve the multi-working-condition energy management of the hybrid chariot; the system constructs a multi-objective optimization model based on the data to realize comprehensive fuel consumption minimization, lithium battery SOC balance and lithium battery life protection, and the model comprises establishment of a power source efficiency parameter mapping relation, determination of a corresponding relation between lithium battery power and cycle life, and construction of a membership function of an optimization objective. By adopting a method of combining Pareto local optimization and fuzzy evaluation, the optimal power distribution proportion among the engine, the fuel cell and the lithium battery is calculated, the overall efficiency of the hybrid chariot is effectively improved, and the service life of the hybrid chariot is effectively prolonged.

The invention relates to the technical field of extended-range electric vehicle control, and discloses an engine starting control method and system for an extended-range electric vehicle, and the method comprises the following steps: obtaining the operation information of the extended-range electric vehicle, the operation information comprises the actual temperature of an engine, the actual rotating speed of a range extender, the state of charge (SOC) of a power battery and the maximum dischargeable power; when the starting request mark position of the engine is set, the generator is controlled to enter a torque control mode, and the engine enters a starting mode; and based on the actual temperature of the engine and the actual rotating speed of the range extender, the pre-control torque of the generator is activated through the enabling flag bit. By accurately controlling the rotating speed and the torque of the generator, smooth starting of the engine is achieved, the requirement for starting the engine in various vehicle using scenes is met, meanwhile, the actual temperature of the engine, the SOC of a power battery and the like are considered, the target rotating speed of the started engine and the starting torque of the generator are flexibly controlled, and the starting efficiency is improved. The starting performance of the engine is improved.

The invention discloses a multi-mode energy recovery optimization control system of a hybrid electric vehicle, and relates to the technical field of energy recovery control. The state sensing module is integrated with a sensor to collect vehicle speed, acceleration, battery state and road condition signals, and data accuracy is ensured through Kalman filtering fusion; the driving mode recognition module is used for recognizing modes such as urban congestion and high-speed cruise through an algorithm based on driving behaviors and road conditions; the energy recovery strategy decision module is used for dynamically adjusting recovery priorities and parameters according to different modes, and balancing efficiency and smoothness; the power distribution execution module converts and stores energy through cooperative control of double clutches and a gearbox, and is linked with an ABS (Anti-lock Brake System) to guarantee safety; and the feedback module is optimized in real time, battery and motor states are monitored, strategies are dynamically corrected, and efficiency and component protection are both considered. The energy recovery efficiency is improved, the driving smoothness and the braking safety are improved, the system adapts to multiple scenes, the service life of the battery is prolonged, and the performance of the hybrid electric vehicle is comprehensively improved.

The invention provides a power generation control method and device for an extended-range hybrid power loader. According to the scheme, the current working mode of the range extending type hybrid power loader is determined according to the real-time operation parameters and the driving operation information; the current working mode of the range extender is determined according to the current working mode of the range-extended hybrid power loader and the charge state of the power battery, and the current required power generation power of the range extender is determined based on the current working mode of the range extender, the required power of the range-extended hybrid power loader and the charge state of the power battery; according to the current required power generation power of the range extender, a preset range extender output electric power curve and a preset engine fuel efficiency characteristic curve, the target rotating speed of a generator and the target torque of the engine are determined, and according to the current working mode of the range-extended hybrid power loader, the target rotating speed of the generator and the target torque of the engine; and controlling the operation states of the engine and the generator. According to the scheme, the problem of low energy efficiency of an extended-range hybrid power loader is solved.

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

The invention provides a range extending type tractor power system and a control method, and solves the problems that in the prior art, a tractor power system is low in energy conversion rate, a stepless speed change structure is complex to achieve, walking drive PTO drive cannot be coupled, and multiple controllers are difficult to cooperate. The range extender is electrically connected with the power battery and can provide electric energy for the power battery; the motor assembly comprises a driving motor and a PTO motor; the control assembly comprises a vehicle control unit, a range extender controller and an all-in-one controller, the range extender controller and the all-in-one controller are connected with the vehicle control unit, the range extender controller is electrically connected with the range extender, the all-in-one controller is electrically connected with the power battery, the range extender and the motor assembly, and the vehicle control unit controls the range extender controller and the all-in-one controller according to specific working conditions. The range extender is controlled by the range extender controller to supply power to the power battery or / and the all-in-one controller, and then the all-in-one controller is used for carrying out power distribution on the driving motor and the PTO motor.

A safety strategy determining method, applied to a hybrid transmission control unit (HTCU), and comprising: monitoring an environment signal in a hybrid transmission; when an error occurs to the environment signal, determining an abnormal event corresponding to the environment signal; analyzing the abnormal event, and determining a safety state corresponding to the abnormal event; on the basis of the safety state and the current gear of a vehicle, determining a safety strategy corresponding to the abnormal event, wherein the current gear comprises one gear in different driving modes, and the safety strategy comprises at least one of the following: maintaining the current gear, reverting the gear in the hybrid transmission to the current gear, and switching from the current gear to a corresponding downshifted gear; sending a gear switching request carrying the safety strategy to a vehicle electronic control unit (VECU), wherein the gear switching request is used for requesting the VECU to switch to a target gear on the basis of the safety strategy; and switching the gear in the hybrid transmission to the target gear. The problem of over-protection or under-protection in the hybrid transmission is avoided, and therefore the driving safety is improved. Also provided is a security strategy determining apparatus.

The invention provides a gear switching method, a vehicle and a storage medium, the method is applied to the technical field of hybrid power control, and the method comprises the steps that in the process that the vehicle runs based on a direct drive mode, if it is determined that the vehicle needs to switch gears, the whole vehicle driving power corresponding to the direct drive mode and the discharging power of a power battery are determined; based on the whole vehicle driving power, the discharging power and the gear change state of the vehicle, a target torque reduction gradient is determined; based on the target torque reduction gradient, the actual torque of the engine is controlled to be reduced to the target torque; and under the condition that the actual torque of the engine is equal to the target torque, the clutch is controlled to be in an open state, so that the vehicle is shifted under the condition that the clutch is in the open state. The method can ensure that the power is not interrupted in the vehicle gear shifting process, the vehicle stability is improved, and the user driving experience is improved.

The invention discloses a hybrid electric vehicle predictive energy management system based on multi-layer cooperative control, and aims to improve the vehicle performance and energy efficiency. According to the method, a hierarchical cooperative control architecture is adopted, and the reinforcement learning, vehicle speed multi-step prediction and model prediction control technologies are combined, so that joint optimization control over vehicle acceleration and power distribution is achieved. The system obtains the vehicle running state and the surrounding environment information in real time through the state sensing module, and determines the expected acceleration by using a strategy network trained by a PPO algorithm. In addition, the future vehicle speed is predicted in combination with an XGBoost multi-step regression model, the optimization module is designed through an MPC strategy, oil consumption, the battery state and driving smoothness are comprehensively considered, and therefore efficient management of the power system is achieved. According to the scheme, the obvious energy-saving advantage is achieved, the driving smoothness and comfort are improved, the good self-adaptive capacity and a real-time feedback mechanism are achieved, and the method is suitable for the complex urban road traffic environment.

The invention discloses a new energy automobile hybrid power system cooperative control device and method.The new energy automobile hybrid power system cooperative control device comprises a multi-source data collection module, a cooperative control center and an execution unit, and the multi-source data collection module transmits collected information data to the cooperative control center; the cooperative control center comprises a data fusion unit, an energy management module, a heat management module and a cooperative decision-making unit, the data fusion unit receives data information of the multi-source data acquisition module, carries out fusion processing, and transmits the data information to the energy management module and the heat management module; the energy management module and the heat management module output a control strategy to the collaborative decision-making unit, and the collaborative decision-making unit judges a correction strategy and then sends a control instruction to the execution unit. The method has the advantages that cooperative control of energy management and heat management is achieved, various dimension data of road conditions, driving behaviors, power states and heat source states are fused, the problem of system unbalance caused by single module optimization is solved, and dynamic cooperation of energy management and heat management is achieved.

A battery system includes a lithium ion battery configured to couple to an electrical system, and a battery management system configured to electrically couple to the lithium ion battery and to control one or more recharge parameters of the lithium ion battery. The battery management system is programmed with an electrochemical model, and the battery management system is configured to monitor parameters of the lithium ion battery, and to control the one or more recharge parameters of the lithium ion battery based on the electrochemical model and the one or more monitored parameters. The electrochemical model determines lithium plating reaction kinetics at an anode of the lithium ion battery, determines a quantity of plated lithium at the anode of the lithium ion battery, or both, and indicates a relationship between the one or more monitored parameters and the lithium plating reaction kinetics, the quantity of plated lithium, or both.

The invention discloses a hybrid power AMT gear shifting control method and system, and relates to the technical field of vehicle gear shifting. The method comprises the steps that whether a transmission meets gear shifting conditions or not is judged according to driving information; determining a target gear value according to the current vehicle state; the power source output torque is gradually reduced according to the target gear value; gear picking operation is carried out through an actuator; adjusting the rotating speed of the motor according to the rotating speed difference of the actuator; controlling the transmission to engage a gear according to the target gear value; and gradually restoring the power source output torque according to the target torque value. According to the technical scheme, high-precision control over the rotating speed of the motor of the commercial vehicle can be achieved, the gear shifting success rate of the hybrid power AMT system can be effectively increased, and high application value is achieved.

A Level IV fuel-saving robot system for heavy-duty trucks (HDT) focuses on the minimization of actual fuel consumption (L / 100 km) for long-haul freight based on an electrical power split device and a mixed hybrid powertrain architecture. The Level IV fuel-saving robot has an L4 autonomous driving function within the Operational Design Domain (ODD) of expressways, operates in a “shadow mode” or “Disengagement Mode,” automatically generates a discrepancy report or detachment report, completes the “3R” (Real Vehicle, Real Road, Real Payload) batch validation for an L4 system on a billion mile scale quickly with high performance to cost ratio under the condition of ensuring the traffic safety of existing road users and reduces the total validation expense by more than 65% compared with the modern HDT with internal combustion engine equipped with the L4 system, promoting the early commercialization of the fuel-saving robot.

The invention provides a series-parallel hybrid power tractor driving system. The series-parallel hybrid power tractor driving system comprises an engine, a P1 motor used for generating electricity or starting the engine, a PS motor used for independent or coupled driving and a series-parallel hybrid power tractor transmission system. The invention further provides a control method of the driving system. Confluence and diversion of engine power and speed change of the tractor are controlled through the P1 motor, the PS motor, the rotating speed coupling mechanism, the torque coupling mechanism, the clutch and the brake. According to the series-parallel connection type hybrid power tractor driving system, a multi-mode driving mode can be achieved to adapt to operation in a complex environment, the dynamic property and economical efficiency of a tractor are improved, and the series-parallel connection type hybrid power tractor driving system has the advantages of interval stepless speed change, precise control and the like.

The invention provides a vehicle control method and device, electronic equipment and a vehicle, which are applied to the technical field of vehicle intelligent control, and the method comprises the following steps: in response to determining that a current driving mode of the vehicle is a target driving mode, obtaining operation data of the vehicle; determining whether the current vehicle speed of the vehicle is within a target vehicle speed interval in response to determining that the operation data meets the sliding friction direct drive condition; and in response to determining that the vehicle speed is within the target vehicle speed interval, controlling a clutch of the vehicle to be switched from the current state to a sliding friction state. According to the method, the vehicle can safely run on the wet and slippery road surface, meanwhile, the consumption of the power battery can be reduced, particularly when the electric quantity of the power battery is low, the power of the engine can be effectively utilized, the service life of the battery is prolonged, and the running distance of the vehicle is prolonged.

A new energy vehicle energy intelligent management method and system, and a related device. The method comprises: determining at least one candidate energy-saving path on the basis of a starting point and an ending point of a vehicle, wherein path-based vehicle energy consumption predicted on the basis of the at least one candidate energy-saving path is lower than path-based vehicle energy consumption predicted on the basis of other paths, and the path-based vehicle energy consumption is predicted on the basis of road condition information of each path and energy consumption impact information; in response to a selection operation on the at least one candidate energy-saving path, determining a preset travel path, wherein the preset travel path comprises a plurality of road sections, and the path-based vehicle energy consumption comprises road section-based vehicle energy consumption of the plurality of road sections; and by taking the minimization of fuel consumption along the preset travel path as an objective, controlling an operation state of an engine on the basis of an initial SOC of a power battery and the road section-based vehicle energy consumption at each road section and an actual vehicle demand of the vehicle, so that the engine is in an efficient operation range during operation.

A battery control component of an electric vehicle may limit charging of a battery on the electric vehicle to a target state of charge (SOC), such as to reserve battery capacity for regenerative braking during downgrades. A computing device associated with the vehicle may calculate an estimated gradient profile and / or an estimated total energy consumption of a predicted upcoming route of the vehicle based on one or more data items, such as GPS data, altitude data, and / or map data. The computing device may determine a target SOC based on the estimated gradient profile. The computing device may determine a confidence factor associated with the estimated gradient profile, where the confidence factor depends on the quantity of data items used to calculate the estimated gradient profile. The computing device may adjust the target SOC based on the confidence factor.

The invention provides a vehicle control method and device, a vehicle and a storage medium, the method is applied to the technical field of hybrid power control, and the method comprises the steps that based on the current electric quantity of a power battery of the vehicle and the whole vehicle demand power of the vehicle, an initial driving mode of the vehicle is firstly determined; calculating the total power consumption corresponding to each of multiple candidate power distribution proportions in the initial driving mode, determining a target power distribution proportion in the multiple candidate power distribution proportions according to the total power consumption corresponding to each of the multiple candidate power distribution proportions, and finally determining the target power distribution proportion in the multiple candidate power distribution proportions based on the target power distribution proportion. And correcting the initial driving mode to obtain a target driving mode, and controlling the vehicle to run in the target driving mode. According to the method, the energy utilization efficiency of the whole vehicle can be maximized, it is ensured that the engine and the motor operate in respective efficient intervals as much as possible, and more stable power output can be provided for the vehicle under different road conditions.

Systems, methods, and computer program products for providing recommendations and features related to charging of batteries for electrically powered motor vehicles are provided herein. Various systems and methods utilize current motor vehicle data and / or user preference data to determine recommended charge devices for a user as they travel, removing the need to research / plan out charge device options during travel and the worry of running out of charge. Various systems and methods provide tailored recommendations and features that help a user select which charge device to use and provide options to occupy the user while the charging occurs. Additionally, relevant offers or promotions for nearby accommodations are provided herein. Various systems and methods also recommend turning off certain devices to elongate the estimated travel distance. Desirable maps for aiding in travel planning and visualizing where the current amount of charge will reach are also provided herein.

The invention discloses an energy management method and device for a parallel hybrid power vehicle. The method comprises the steps that an initial vehicle state signal is obtained; constructing a vehicle kinetic equation; according to the vehicle kinetic equation, a parallel hybrid power vehicle structure model is constructed; constructing a battery thermal model and a battery life model according to the parallel hybrid power vehicle structure model; constructing a parameter-free return function according to the battery thermal model and the battery life model; generating a reinforcement learning space state and a reinforcement learning control action according to the parameter-free return function; constructing a target double-delay depth deterministic strategy gradient network; constructing a vehicle energy management learning strategy; according to the initial vehicle state signal, target engine equivalent torque is determined through a vehicle energy management learning strategy, and the target engine equivalent torque is used for controlling operation of an engine. Energy management of the parallel hybrid power vehicle is achieved, and accuracy, applicability and efficiency are improved. The method can be widely applied to the technical field of vehicle engineering.

The invention discloses a hybrid crawler tractor for hills and mountains and a control method. The hybrid crawler tractor comprises a power system, a transmission system, an energy storage system, a driving system and a control system, the power system comprises an engine, a generator and a clutch; the transmission system comprises a mechanical coupling device, a gearbox, a power output shaft and the like; the energy storage system comprises a photovoltaic power generation panel and an energy storage device; the driving system comprises a driving system input shaft, left and right traction motors, left and right planet rows, driving wheels and the like; the control system comprises a whole vehicle controller, an energy storage device controller, a motor controller, an engine controller, a vehicle information sensor, a clutch control unit, a brake control unit and the like. According to the crawler tractor, a double-engine and motor mixed connection double-power flow structure is adopted, operation and running under various complex working conditions in hills and mountains are met, rich solar resources in the region are fully utilized, the advantages of a traditional crawler tractor and a new energy tractor are considered, and long-time operation in busy farming seasons is guaranteed.

An intelligent energy management system, includes: a drive device including an engine configured to output power to a wheel of the vehicle, a drive motor configured to output power to the wheel, and an electric generator connected to the engine and driven by the engine to generate electricity; a power battery configured to supply electricity to the drive motor and charged with an alternating current outputted from the electric generator or the drive motor; and a control device configured to acquire multi-domain data fusion information, predict, according to the multi-domain data fusion information, a route-specific vehicle energy consumption corresponding to a preset travel route, plan, according to a road section-specific vehicle energy consumption corresponding to each road section, a target SOC corresponding to each road section, and control, according to the target SOC and an actual vehicle demand corresponding to each road section, the drive device.

The invention discloses a hybrid power energy-saving control method suitable for mining equipment, and belongs to the technical field of mining equipment energy-saving control, and the method comprises the following steps: collecting real-time operation state data, including load power, gradient, speed and battery SOC, of the mining equipment through multiple sensors; based on the collected real-time operation data and historical data, predicting a load demand in a future time window by using a time sequence prediction model; according to the current load prediction result, the power distribution proportion of the internal combustion engine and the motor is dynamically adjusted, so that the hybrid power system meets the operation requirement; and in the deceleration or idling stage of the equipment, the braking energy is recovered through reverse working of the motor, and the recovered energy is stored in the battery or the super capacitor. Through dynamic load prediction, energy distribution optimization and flexible energy recovery, efficient energy saving of mining equipment and reasonable utilization of energy of the internal combustion engine and the motor under complex working conditions are achieved.

The invention provides a vehicle control method and device, a vehicle and a storage medium, the method is applied to the field of vehicles, and the method comprises the steps that under the condition that the vehicle is in a direct drive mode, whether the vehicle is in an emergency braking working condition or not is judged; if the vehicle is in the emergency braking working condition, it is determined that the vehicle needs to be controlled to exit from the direct drive mode, and a target torque reduction gradient in the process that the vehicle exits from the direct drive mode is determined; and according to the target torque reduction gradient, torque reduction of the engine is controlled, and under the condition that the output torque of the engine is reduced to the target torque, a clutch of the vehicle is controlled to be in an open state, so that the vehicle is controlled to exit the direct drive mode. According to the method, the vehicle can be controlled to exit the direct-drive mode in advance, the problem of clutch opening delay is solved, the situation that an engine is reversely dragged is avoided, and the safety of the vehicle is improved.

The invention relates to a heavy-duty commercial vehicle train hybrid energy management equivalent factor adaptive method, which comprises the steps of classifying operation conditions based on cloud historical data of the operation conditions, and calculating an optimal equivalent factor under each operation condition in an off-line manner by utilizing simulation software after classification is completed; selecting a working condition updating period taking mileage as a reference, identifying the working condition according to the characteristic parameters in the period, and obtaining a corresponding optimal equivalent factor as a reference equivalent factor of the next control period; the equivalent factors are adjusted in real time based on the whole vehicle state parameters; adjusting equivalent factors considering terrain prediction according to the difference between the allowable maximum SOC before downhill and the current SOC in combination with front terrain prediction; corresponding control instructions are sent to the motor and the engine; periodically updating the reference equivalent factor to realize continuous loop iteration of the optimal equivalent factor; and the fuel economy of the whole vehicle is improved.

The invention relates to an energy management method and system for a hybrid electric vehicle, and the method comprises the steps: obtaining the actual driving condition data of a target vehicle under a current energy distribution strategy; based on the actual driving condition data, dynamically optimizing a first student model deployed in the target vehicle to obtain a second student model; the first student model is obtained by performing knowledge distillation based on a pre-trained teacher model; and processing the real-time sensor data of the target vehicle through the second student model to obtain a latest energy distribution strategy of the target vehicle, and controlling the target vehicle according to the latest energy distribution strategy. Through the method and the device, the problem of poor vehicle energy efficiency performance caused by lack of dynamic adaptation capability for complex working conditions in an actual driving scene is solved, online continuous learning and performance iterative optimization of the model are realized, and the working condition adaptation capability and generalization capability of the model are enhanced, so that the complex working conditions in the driving scene are dynamically adapted, and the vehicle energy efficiency is improved. And the vehicle energy efficiency performance is optimized.