CN112389272A - Energy management method and device for plug-in hybrid electric vehicle, electronic equipment and storage medium - Google Patents

Energy management method and device for plug-in hybrid electric vehicle, electronic equipment and storage medium Download PDF

Info

Publication number
CN112389272A
CN112389272A CN202011087570.0A CN202011087570A CN112389272A CN 112389272 A CN112389272 A CN 112389272A CN 202011087570 A CN202011087570 A CN 202011087570A CN 112389272 A CN112389272 A CN 112389272A
Authority
CN
China
Prior art keywords
vehicle
electric quantity
determining
predicted
time period
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202011087570.0A
Other languages
Chinese (zh)
Other versions
CN112389272B (en
Inventor
曹开发
王效杰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang Geely Holding Group Co Ltd
Geely Automobile Research Institute Ningbo Co Ltd
Original Assignee
Zhejiang Geely Holding Group Co Ltd
Geely Automobile Research Institute Ningbo Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang Geely Holding Group Co Ltd, Geely Automobile Research Institute Ningbo Co Ltd filed Critical Zhejiang Geely Holding Group Co Ltd
Priority to CN202011087570.0A priority Critical patent/CN112389272B/en
Publication of CN112389272A publication Critical patent/CN112389272A/en
Application granted granted Critical
Publication of CN112389272B publication Critical patent/CN112389272B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/50—Control modes by future state prediction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/50—Control modes by future state prediction
    • B60L2260/52—Control modes by future state prediction drive range estimation, e.g. of estimation of available travel distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/50—Control modes by future state prediction
    • B60L2260/54—Energy consumption estimation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

Landscapes

  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The energy management method, the device, the electronic equipment and the storage medium for the plug-in hybrid electric vehicle disclosed by the embodiment of the application comprise the steps of obtaining the average speed of the vehicle, the running distance of the vehicle, the power consumption of the vehicle-mounted accessories, the predicted running speed and the pre-running distance of the vehicle in a waiting history time period, determining a current electric quantity of the vehicle according to an average speed of the vehicle, a travel distance of the vehicle and an electric quantity consumed by the vehicle-mounted accessories within a historical time period, determining an upper limit electric quantity and a lower limit electric quantity based on the current electric quantity, and determining the predicted electric quantity of the vehicle according to the average speed of the vehicle in the historical time period, the electric consumption of the vehicle-mounted accessories in the historical time period and the pre-travel distance, and determining and switching the target working mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period and the predicted travel speed of the vehicle. The method and the device have the advantages that modeling of the power system is not needed, the algorithm is simple, and the real-time requirement of the system can be met.

Description

Energy management method and device for plug-in hybrid electric vehicle, electronic equipment and storage medium
Technical Field
The invention relates to the technical field of vehicle energy management, in particular to an energy management method and device for a plug-in hybrid electric vehicle, electronic equipment and a storage medium.
Background
Under the dual pressure drive of energy conservation and emission reduction, the development of new energy automobiles becomes a necessary choice in the international society, and at present, plug in hybrid electric vehicles (PHEVs) become new energy automobiles which are vigorously popularized in China due to the characteristics of low oil consumption, long endurance and the like. The PHEV generally has three operation modes, namely an Electric Vehicle (EV), a Hybrid Electric Vehicle (HEV), and a reserve Battery mode (SAVE), wherein when the Vehicle is in the EV mode, the Vehicle directly drives the Electric machine using Electric energy, when the Vehicle is in the HEV mode, the Vehicle drives the Electric machine by means of an engine, and when the Vehicle is in the SAVE mode, the overall Vehicle goal is to control a Battery State of charge (SOC) to be maintained at a balance point. During actual operation, the switching of the vehicle running mode requires manual adjustment by the driver, and after the adjustment, the vehicle is fixedly controlled to be in the mode until the adjustment is performed again.
However, in the actual driving process, the road conditions encountered by the vehicle are very diversified, and the vehicle has a real-time dynamic change characteristic, so that the operation mode of the vehicle is regulated and switched in real time by a driver is dangerous, and the aim of saving energy cannot be achieved. Although the prior art has many research results on energy management, various problems exist, which cannot be applied to practical vehicles, and the main problems include the following:
1. algorithms such as dynamic programming and the like are adopted, and the calculation power of a vehicle-mounted hardware platform is limited and is not enough to support the algorithms, so that the algorithms cannot be practically applied;
2. a Model Predictive Control (MPC) based algorithm is used, which depends on the accuracy of modeling the power system and the Control method is very complex.
Disclosure of Invention
The embodiment of the application provides an energy management method and device for a plug-in hybrid electric vehicle, an electronic device and a storage medium, a power system does not need to be modeled, an algorithm is simple, and the requirement of the system on real-time performance can be met.
The embodiment of the application provides an energy management method of a plug-in hybrid electric vehicle, which comprises the following steps:
acquiring a data set to be processed; the data set to be processed comprises historical electric quantity, average speed of the vehicle in the historical time period, driving distance of the vehicle in the historical time period, power consumption of vehicle-mounted accessories in the historical time period, predicted driving speed and pre-driving distance of the vehicle;
determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the running distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle-mounted accessories in the historical time period;
determining an upper limit electric quantity and a lower limit electric quantity based on the current electric quantity;
determining the predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the power consumption of the vehicle-mounted accessories in the historical time period and the pre-travel distance;
determining a target working mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period and the predicted running speed of the vehicle;
and switching the current working mode of the vehicle to the target working mode.
Further, the target operation mode includes a first operation mode, a second operation mode, and a third operation mode.
Further, determining a target operation mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, and the predicted traveling speed of the vehicle includes:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a first threshold value according to the current electric quantity and the upper limit electric quantity;
and if the first difference is larger than the first threshold value, determining that the target working mode of the vehicle is the first working mode.
Further, determining a target operation mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, and the predicted traveling speed of the vehicle includes:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the first difference is larger than the second threshold value and the predicted running speed of the vehicle is larger than the running speed threshold value corresponding to the first working mode, determining that the target working mode of the vehicle is the second working mode.
Further, determining a target operation mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, and the predicted traveling speed of the vehicle includes:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the first difference is larger than the second threshold value and the predicted running speed of the vehicle is smaller than or equal to the running speed threshold value corresponding to the first working mode, determining that the target working mode of the vehicle is the first working mode.
Further, determining a target operation mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, and the predicted traveling speed of the vehicle includes:
determining a second electric quantity corresponding to the second working mode;
determining a second difference value according to the predicted electric quantity and the second electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the second difference is larger than the second threshold value, determining that the target working mode of the vehicle is the second working mode.
Further, determining a target operation mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, and the predicted traveling speed of the vehicle includes:
determining a second electric quantity corresponding to the second working mode;
determining a second difference value according to the predicted electric quantity and the second electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the second difference is smaller than or equal to the second threshold value and the predicted electric quantity is larger than the current electric quantity, determining that the target working mode of the vehicle is a third working mode.
Further, determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the driving distance of the vehicle in the historical time period and the electric consumption quantity of the vehicle-mounted accessories in the historical time period comprises the following steps:
and determining the current electric quantity of the vehicle according to the historical electric quantity, the first preset scalar, the driving distance of the vehicle in the historical time period, the average speed of the vehicle in the historical time period, the second preset scalar and the consumption quantity of the vehicle-mounted accessories in the historical time period.
Further, determining a predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the vehicle accessory consumption amount in the historical time period and the pre-travel distance comprises:
determining the pre-travel time according to the pre-travel distance and the average speed of the vehicle in the historical time period;
and determining the predicted electric quantity of the vehicle according to the current electric quantity, the third preset scalar, the pre-travel distance, the average speed of the vehicle in the historical time period, the second preset scalar and the pre-travel time.
Correspondingly, this application embodiment still provides a plug-in hybrid vehicle's energy management device, and the device includes:
the acquisition module is used for acquiring a data set to be processed; the data set to be processed comprises historical electric quantity, average speed of the vehicle in the historical time period, driving distance of the vehicle in the historical time period, power consumption of vehicle-mounted accessories in the historical time period, predicted driving speed and pre-driving distance of the vehicle;
the first determination module is used for determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the running distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle accessories in the historical time period;
the second determination module is used for determining the upper limit electric quantity and the lower limit electric quantity based on the current electric quantity;
the third determining module is used for determining the predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the consumed electric quantity of the vehicle-mounted accessories in the historical time period and the pre-running distance;
and the fourth determination module is used for determining the target working mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period and the predicted running speed of the vehicle.
And the switching module is used for switching the current working mode of the vehicle to the target working mode.
Correspondingly, the embodiment of the application also provides an electronic device, which comprises a processor and a memory, wherein at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize the energy management method of the plug-in hybrid electric vehicle.
Accordingly, the present application further provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set, or a set of instructions is stored, and the at least one instruction, the at least one program, the code set, or the set of instructions is loaded and executed by a processor to implement the above energy management method for a plug-in hybrid vehicle.
The embodiment of the application has the following beneficial effects:
the management method comprises the steps of obtaining a data set to be processed, wherein the data set to be processed comprises the average speed of a vehicle in a historical time period, the driving distance of the vehicle in the historical time period, the power consumption of accessories on the vehicle in the historical time period, the predicted driving speed and the pre-driving distance of the vehicle, further determining the current electric quantity of the vehicle according to the average speed of the vehicle in the historical time period, the driving distance of the vehicle in the historical time period and the power consumption of the accessories on the vehicle in the historical time period, determining the upper limit electric quantity and the lower limit electric quantity based on the current electric quantity, then determining the predicted electric quantity of the vehicle according to the average speed of the vehicle in the historical time period, the power consumption of the accessories on the vehicle in the historical time period and the pre-driving distance, and further determining the predicted electric quantity of the vehicle based on the current electric, Determining a target working mode of the vehicle according to the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period and the predicted running speed of the vehicle, and finally switching the current working mode of the vehicle to the target working mode. Based on the embodiment of the application, the current electric quantity, the predicted electric quantity and the target working mode of the vehicle are determined by combining the navigation global information, the instant information provided by V2X, the vehicle speed and the electric quantity consumed by the vehicle-mounted accessories, a reference electric quantity curve in a future period of time is comprehensively considered, mode switching is adopted for energy management, a power system does not need to be modeled, an algorithm is simple, and the real-time requirement of the system can be met.
Drawings
In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that 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 creative efforts.
FIG. 1 is a schematic diagram of an application environment provided by an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for energy management of a plug-in hybrid vehicle according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of three power consumption curves of a PHEV according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a method for determining a reference power curve according to an embodiment of the present disclosure;
FIG. 5 is a schematic flow chart illustrating selection of different target operating modes based on a current power amount, an upper limit power amount, a lower limit power amount, a predicted power amount, an average speed of the vehicle over a historical time period, and a predicted travel speed of the vehicle, according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an energy management device of a plug-in hybrid vehicle according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings. It should be apparent that the described embodiment is only one embodiment of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
An "embodiment" as referred to herein relates to a particular feature, structure, or characteristic that may be included in at least one implementation of the present application. In the description of the embodiments of the present application, it should be understood that the terms "first", "second" and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, features defined as "first", "second" and "third" may explicitly or implicitly include one or more of the features. Moreover, the terms "first," "second," and "third," etc. are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in other sequences than described or illustrated herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not expressly listed or inherent to such process, method, apparatus, article, or device.
Please refer to fig. 1, which is a schematic diagram of an application environment according to an embodiment of the present application, including: the system comprises a vehicle control unit 101, a road-end interaction system 103, a vehicle-mounted navigation system 105, a sensing device 107, a battery management system 109 and an electronic control unit 111. The vehicle control unit 101 receives road end interaction data information, vehicle end navigation data information, vehicle speed data, vehicle-mounted accessory consumption electric quantity data information and real-time electric quantity data information through a CAN bus, wherein the road end interaction data information is instant data information acquired by a road end interaction system 103 (V2X), and the vehicle end navigation data information is global information in a historical time period, a current time and a future time period determined based on a vehicle-mounted navigation system 105; the vehicle speed data comprises the average speed of the vehicle over a historical period of time, and in an alternative embodiment, the vehicle speed data is collected by a sensing device 107 mounted on the vehicle; the vehicle-mounted accessory power consumption data information comprises power consumed by vehicle-mounted electric devices such as an engine power consumption, a vehicle-mounted headlamp power consumption, a vehicle-mounted air conditioner power consumption and the like; the real-time electricity amount data information is provided by a battery management system 109 (BMS) in real time. Then the vehicle control unit 101 obtains a data set to be processed based on the received data information, the data set to be processed includes historical electric quantity, average speed of the vehicle in the historical time period, travel distance of the vehicle in the historical time period, vehicle accessory electricity consumption amount in the historical time period, predicted travel speed and pre-travel distance of the vehicle, further determines current electric quantity of the vehicle according to the historical electric quantity, average speed of the vehicle in the historical time period, travel distance of the vehicle in the historical time period and vehicle accessory electricity consumption amount in the historical time period, determines upper limit electric quantity and lower limit electric quantity based on the current electric quantity, then determines predicted electric quantity of the vehicle according to the current electric quantity, average speed of the vehicle in the historical time period, vehicle accessory electricity consumption amount in the historical time period and pre-travel distance, and determines predicted travel speed of the vehicle based on the current electric quantity, upper limit electric quantity, lower limit electric quantity, predicted electric quantity, average speed of, and determining a target working mode of the vehicle, and finally switching the current working mode of the vehicle to the target working mode.
While a specific embodiment of an energy management method for a plug-in hybrid vehicle according to the present application is described below, fig. 2 is a schematic flow chart of an energy management method for a plug-in hybrid vehicle according to the embodiment of the present application, and the present specification provides the method operation steps as shown in the embodiment or the flow chart, but more or less operation steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is only one of many possible orders of execution and does not represent the only order of execution, and in actual execution, the steps may be performed sequentially or in parallel as in the embodiments or methods shown in the figures (e.g., in the context of parallel processors or multi-threaded processing). Specifically, as shown in fig. 2, the method includes:
s201: acquiring a data set to be processed; the data set to be processed comprises historical electric quantity, average speed of the vehicle in the historical time period, driving distance of the vehicle in the historical time period, consumption amount of vehicle-mounted accessories in the historical time period, predicted driving speed and pre-driving distance of the vehicle.
In the embodiment of the application, the vehicle controller receives road end interaction data information, vehicle end navigation data information, vehicle speed data, vehicle-mounted accessory consumed electric quantity data information, real-time electric quantity data information and the like through the CAN bus, and obtains historical electric quantity, average speed of the vehicle in the historical time period, driving distance of the vehicle in the historical time period, power consumption of the vehicle-mounted accessory in the historical time period, predicted driving speed of the vehicle and pre-driving distance waiting processing data.
FIG. 3 is a schematic diagram of three charge loss curves for a PHEV. As is known, a PHEV performs a charge depleting mode during normal motion in a neutral line, as shown by the curve in the CD segment shown by the solid line in fig. 3, and then enters a charge sustaining mode, as shown by the curve in the CS segment shown by the solid line in fig. 3. Based on the electricity consumption change of the PHEV in the whole driving process, the fuel economy of the vehicle is considered, and the electricity consumption of the vehicle can be controlled to be in a CD mode to fully utilize the battery electricity without entering a CS mode.
In the embodiment of the application, the vehicle controller may determine the departure point information and the destination point information from the received navigation data information provided by the vehicle-mounted navigation system, and determine the distance between the departure point time and the destination point time, and theoretically, if the vehicle is always in the power consumption mode, the power consumption diagram shown by the dotted line in fig. 3 may be obtained. Here, the power consumption may be linear, and the coefficient thereof may be determined according to an initial power of the vehicle at the departure point, a termination power of the vehicle at the destination, and a distance between the departure point and the destination, or may be determined according to an initial power of the vehicle at the departure point, a real-time power of the vehicle at the current position, and a distance that the vehicle has traveled at the current time.
Figure BDA0002720356530000081
Wherein, CinitialRepresents the initial amount of electricity, CendIndicates the amount of electricity terminated, CtRepresenting real-time electric quantity, RrangeDistance between departure and destination, RtIndicating the distance traveled.
S203: and determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the driving distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle accessories in the historical time period.
In the embodiment of the application, the whole vehicle control system determines the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the running distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle accessories in the historical time period. Specifically, the predicted electric quantity of the vehicle may be determined according to the following calculation formula.
Ct＝Ct-1-[K1*V*S1+K2*Pacc*t]
Wherein, Ct-1Indicating the historical amount of electricity, CtRepresents the current amount of electricity, K1A first preset scalar is represented, and a second preset scalar is represented,v represents the average speed of the vehicle in the history period, S1Indicating the distance traveled by the vehicle during the historical period of time, K2Representing a second predetermined scalar quantity, PaccIndicating the amount of power consumed by the vehicle-mounted accessories during the historical time period, and t indicating the historical time period.
In the embodiment of the present application, the current electric quantity may be determined based on the above calculation method, or may be directly provided by the battery management system in real time.
S205: an upper limit electric quantity and a lower limit electric quantity are determined based on the current electric quantity.
In the embodiment of the application, the whole vehicle control system determines a magnitude value by taking the current electric quantity as a reference, and determines an upper deviation value and a lower deviation value based on the magnitude value and the current electric quantity to obtain an upper limit electric quantity and a lower limit electric quantity.
S207: and determining the predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the consumed electric quantity of the vehicle accessories in the historical time period and the pre-travel distance.
In the embodiment of the application, the whole vehicle control system determines the pre-driving time according to the preset driving distance and the average speed of the vehicle in the historical time period, and determines the predicted electric quantity of the vehicle according to the current electric quantity, the third preset scalar, the pre-driving time, the average speed of the vehicle in the historical time period, the second preset scalar and the pre-driving time. Specifically, the predicted electric quantity of the vehicle may be determined according to the following calculation formula.
Ct+1＝Ct-[K3*V*S2+K2*Pacc*(S2/V)]
Wherein, Ct+1Represents the predicted electric quantity, CtRepresents the current amount of electricity, K3Representing a third preset scalar, V representing the average speed of the vehicle over a historical period, S2Indicating a pre-travel distance, K2Representing a second predetermined scalar quantity, PaccIndicating the amount of power consumption of the vehicle accessories in the historical time period, S2and/V represents the pre-travel time.
In the embodiment of the present application, the entire vehicle control system may determine a predicted electric quantity determined based on the current electric quantity, similarly, may determine the predicted electric quantity again as a new current electric quantity, and determine the predicted electric quantity corresponding to the next time period based on the new current electric quantity, so a curve representing the reference electric quantity, that is, a curve composed of a plurality of current electric quantities may be obtained through continuous iteration, as shown in a curve with a frame in fig. 3, it is to be noted that the current electric quantity refers to current electric quantities at a plurality of different times. Here, each box represents the current amount of power at one time. Fig. 4 is a schematic flow chart of a method for determining a reference power curve according to an embodiment of the present application, and the present specification provides the method operation steps shown in the embodiment or the flowchart, specifically as shown in fig. 4.
S401: acquiring initial electric quantity, termination electric quantity and total distance.
S403: and determining the distance traveled at the current moment according to the pre-loss electric quantity corresponding to the pre-travel distance.
S405: and when the initial electric quantity is larger than the termination electric quantity, determining the residual electric quantity according to the initial electric quantity and the pre-loss electric quantity corresponding to the pre-travel distance.
S407: judging whether the residual electric quantity is greater than the termination electric quantity, and if so, turning to S409; otherwise, go to S411.
S409: judging whether the difference value between the total distance and the traveled distance is greater than a preset threshold value or not; if the value is larger than the value, turning to S401; otherwise go to S411.
S411: and determining the termination electric quantity as the residual electric quantity.
S209: a target operating mode of the vehicle is determined based on the current amount of power, the upper limit amount of power, the lower limit amount of power, the predicted amount of power, the average speed of the vehicle over the historical period of time, and the predicted travel speed of the vehicle.
In the embodiment of the application, the whole vehicle control system determines the target working mode of the vehicle based on the determined current electric quantity, the determined upper limit electric quantity, the determined lower limit electric quantity, the determined predicted electric quantity, the obtained average speed of the vehicle in the historical time period and the obtained predicted running speed of the vehicle. Here, the target operation mode may include a first operation mode, a second operation mode, and a third operation mode, and in an alternative embodiment, the first operation mode may be specifically an EV mode, the second operation mode may be specifically an HEV mode, and the third operation mode may be specifically a SAVE mode. The HEV mode may include sub-modes such as ECO, Comfort, save, etc.
The following description is based on three specific cases of the target operation mode, EV mode, HEV mode, and SAVE mode. Fig. 5 illustrates a flow chart for selecting different target operation modes based on the current power amount, the upper limit power amount, the lower limit power amount, the predicted power amount, the average speed of the vehicle in the history period, and the predicted traveling speed of the vehicle.
The whole vehicle control system firstly determines first electric quantity corresponding to a first working mode, namely the electric quantity required to be consumed when a vehicle is in an EV mode within a pre-travel distance, determines a first difference value according to the predicted electric quantity and the first electric quantity, specifically, determines a first threshold value according to the current electric quantity and an upper limit electric quantity, and specifically, sums the current electric quantity and the upper limit electric quantity to obtain the first threshold value.
If the first difference is larger than the first threshold value, the vehicle control system determines that the target mode of the vehicle is the first working mode, namely determines that the target working mode of the vehicle is the EV mode.
Otherwise, namely the first difference is smaller than or equal to the first threshold, the whole vehicle control system determines a second threshold according to the current electric quantity and the lower limit electric quantity, and specifically, the current electric quantity and the lower limit electric quantity are differentiated to obtain the second threshold.
If the first difference is larger than the second threshold, the vehicle control system determines the ratio of the predicted running speed of the vehicle to the running speed threshold corresponding to the EV mode, and if the predicted running speed of the vehicle is larger than the running speed threshold corresponding to the EV mode, determines that the target mode of the vehicle is the second operation mode, that is, determines that the target operation mode of the vehicle is the HEV mode, and specifically may be an ECO sub-mode in the HEV mode.
Otherwise, namely the first difference is smaller than or equal to a second threshold, the whole vehicle control system determines a second electric quantity corresponding to the second working mode, namely the electric quantity required to be consumed by the vehicle in the HEV mode within the pre-travel distance is determined, determines a second difference according to the predicted electric quantity and the second electric quantity, specifically, obtains the second difference by subtracting the predicted electric quantity from the second electric quantity, determines a second threshold according to the current electric quantity and a lower limit electric quantity, and specifically, obtains the second threshold by subtracting the current electric quantity from the lower limit electric quantity.
If the second difference is greater than the second threshold, the vehicle control system determines that the target mode of the vehicle is the second operating mode, that is, determines that the target operating mode of the vehicle is the HEV mode, and may specifically be an ECO sub-mode in the HEV mode.
Otherwise, namely the second difference is smaller than or equal to the second threshold, the whole vehicle control system determines the ratio of the predicted electric quantity to the current electric quantity, and if the predicted electric quantity is larger than the current electric quantity, the target working mode of the vehicle is determined to be the third working mode, namely the target working mode of the vehicle is determined to be the SAEV mode.
Let it be assumed that SOCrefRepresents the current electric quantity and SOCupRepresents the upper limit electric quantity and SOCdownRepresenting a lower limit electric quantity, SOC representing a predicted electric quantity, V representing an average speed of the vehicle over a historical period, VmIndicating the predicted travel speed of the vehicle.
S211: and switching the current working mode of the vehicle to the target working mode.
By adopting the energy management method of the plug-in hybrid electric vehicle provided by the embodiment of the application, the current electric quantity, the predicted electric quantity and the target working mode of the vehicle are determined by combining the navigation global information and the instant information provided by V2X, the vehicle speed and the electric quantity consumed by the vehicle-mounted accessories, the reference electric quantity curve in a future period of time is comprehensively considered, the mode switching is adopted for energy management, the modeling of a power system is not needed, the algorithm is simpler, and the real-time requirement of the system can be met.
Fig. 6 is a schematic structural diagram of an energy management device of a plug-in hybrid electric vehicle provided in an embodiment of the present application, and as shown in fig. 6, the energy management device includes:
the obtaining module 601 is configured to obtain a data set to be processed; the data set to be processed comprises the average speed of the vehicle in the historical time period, the running distance of the vehicle in the historical time period, the power consumption of the vehicle-mounted accessories in the historical time period, the predicted running speed and the pre-running distance of the vehicle;
the first determining module 603 is configured to determine a current electric quantity of the vehicle according to an average speed of the vehicle in the historical time period, a driving distance of the vehicle in the historical time period, and a power consumption amount of an accessory of the vehicle in the historical time period;
the second determining module 605 is configured to determine an upper limit power amount and a lower limit power amount based on the current power amount;
the third determination module 607 is configured to determine a predicted electric quantity of the vehicle according to the average speed of the vehicle in the historical time period, the electric consumption amount of the vehicle-mounted accessory in the historical time period, and the pre-travel distance;
the fourth determining module 609 is configured to determine the target operating mode of the vehicle based on the current electric quantity, the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period, and the predicted traveling speed of the vehicle.
The switching module 611 is configured to switch the current operating mode of the vehicle to the target operating mode.
The device and method embodiments in the embodiments of the present application are based on the same application concept.
The present application further provides an electronic device, where the electronic device may be disposed in a server to store at least one instruction, at least one program, a code set, or a set of instructions related to implementing the energy management method of the plug-in hybrid electric vehicle in the method embodiment, and the at least one instruction, the at least one program, the code set, or the set of instructions is loaded from the memory and executed to implement the energy management method of the plug-in hybrid electric vehicle.
The present application further provides a storage medium, which may be disposed in a server to store at least one instruction, at least one program, a code set, or a set of instructions related to implementing an energy management method for a plug-in hybrid electric vehicle according to the method embodiment, where the at least one instruction, the at least one program, the code set, or the set of instructions are loaded and executed by the processor to implement the energy management method for the plug-in hybrid electric vehicle.
Optionally, in this embodiment, the storage medium may be located in at least one network server of a plurality of network servers of a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, a storage medium including: various media that can store program codes, such as a usb disk, a Read-only Memory (ROM), a removable hard disk, a magnetic disk, or an optical disk.
As can be seen from the embodiments of the method, the apparatus, the electronic device or the storage medium for energy management of a plug-in hybrid vehicle provided by the present application, the method in the present application includes obtaining a data set to be processed, where the data set to be processed includes an average speed of a vehicle in a historical time period, a travel distance of the vehicle in the historical time period, a vehicle accessory power consumption elimination amount in the historical time period, a predicted travel speed and a pre-travel distance of the vehicle, determining a current power amount of the vehicle according to the average speed of the vehicle in the historical time period, the travel distance of the vehicle in the historical time period and the vehicle accessory power consumption elimination amount in the historical time period, determining an upper limit power amount and a lower limit power amount based on the current power amount, determining a predicted power amount of the vehicle according to the average speed of the vehicle in the historical time period, the vehicle accessory power consumption elimination amount in the historical time period and the, Determining a target working mode of the vehicle according to the upper limit electric quantity, the lower limit electric quantity, the predicted electric quantity, the average speed of the vehicle in the historical time period and the predicted running speed of the vehicle, and finally switching the current working mode of the vehicle to the target working mode. Based on the embodiment of the application, the current electric quantity, the predicted electric quantity and the target working mode of the vehicle are determined by combining the navigation global information, the instant information provided by V2X, the vehicle speed and the electric quantity consumed by the vehicle-mounted accessories, a reference electric quantity curve in a future period of time is comprehensively considered, mode switching is adopted for energy management, a power system does not need to be modeled, an algorithm is simple, and the real-time requirement of the system can be met.
It should be noted that: the foregoing sequence of the embodiments of the present application is for description only and does not represent the superiority and inferiority of the embodiments, and the specific embodiments are described in the specification, and other embodiments are also within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in the order of execution in different embodiments and achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown or connected to enable the desired results to be achieved, and in some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
All the embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment is described with emphasis on differences from other embodiments. Especially, for the embodiment of the device, since it is based on the embodiment similar to the method, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.

Claims (12)

1. A method of energy management for a plug-in hybrid vehicle, comprising:
acquiring a data set to be processed; the data set to be processed comprises historical electric quantity, average speed of the vehicle in a historical time period, driving distance of the vehicle in the historical time period, power consumption of vehicle-mounted accessories in the historical time period, predicted driving speed and pre-driving distance of the vehicle;
determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the driving distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle-mounted accessories in the historical time period;
determining an upper limit electric quantity and a lower limit electric quantity based on the current electric quantity;
determining the predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the consumed electric quantity of the vehicle-mounted accessories in the historical time period and the pre-travel distance;
determining a target operating mode of the vehicle based on the current amount of power, the upper limit amount of power, the lower limit amount of power, the predicted amount of power, an average speed of the vehicle over the historical period of time, and a predicted travel speed of the vehicle;
and switching the current working mode of the vehicle to the target working mode.
2. The method of claim 1, wherein the target operating mode comprises a first operating mode, a second operating mode, and a third operating mode.
3. The method of claim 2, wherein determining the target operating mode of the vehicle based on the current amount of power, the upper amount of power, the lower amount of power, the predicted amount of power, and the predicted travel speed of the vehicle comprises:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a first threshold value according to the current electric quantity and the upper limit electric quantity;
and if the first difference is larger than the first threshold, determining that the target working mode of the vehicle is the first working mode.
4. The method of claim 2, wherein determining the target operating mode of the vehicle based on the current amount of power, the upper amount of power, the lower amount of power, the predicted amount of power, and the predicted travel speed of the vehicle comprises:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the first difference is larger than the second threshold value and the predicted running speed of the vehicle is larger than the running speed threshold value corresponding to the first working mode, determining that the target working mode of the vehicle is the second working mode.
5. The method of claim 2, wherein determining the target operating mode of the vehicle based on the current amount of power, the upper amount of power, the lower amount of power, the predicted amount of power, and the predicted travel speed of the vehicle comprises:
determining a first electric quantity corresponding to the first working mode;
determining a first difference value according to the predicted electric quantity and the first electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the first difference is larger than the second threshold value and the predicted running speed of the vehicle is smaller than or equal to the running speed threshold value corresponding to the first working mode, determining that the target working mode of the vehicle is the first working mode.
6. The method of claim 2, wherein determining the target operating mode of the vehicle based on the current amount of power, the upper amount of power, the lower amount of power, the predicted amount of power, and the predicted travel speed of the vehicle comprises:
determining a second electric quantity corresponding to the second working mode;
determining a second difference value according to the predicted electric quantity and the second electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the second difference is larger than the second threshold, determining that the target working mode of the vehicle is the second working mode.
7. The method of claim 2, wherein determining the target operating mode of the vehicle based on the current amount of power, the upper amount of power, the lower amount of power, the predicted amount of power, and the predicted travel speed of the vehicle comprises:
determining a second electric quantity corresponding to the second working mode;
determining a second difference value according to the predicted electric quantity and the second electric quantity;
determining a second threshold value according to the current electric quantity and the lower limit electric quantity;
and if the second difference is smaller than or equal to the second threshold value and the predicted electric quantity is larger than the current electric quantity, determining that the target working mode of the vehicle is a third working mode.
8. The method of claim 1, wherein determining the current charge of the vehicle based on the historical charge, the average speed of the vehicle over the historical period of time, the distance traveled by the vehicle over the historical period of time, and the vehicle accessory consumption amount over the historical period of time comprises:
and determining the current electric quantity of the vehicle according to the historical electric quantity, the first preset scalar, the driving distance of the vehicle in the historical time period, the average speed of the vehicle in the historical time period, the second preset scalar and the consumed electric quantity of the vehicle-mounted accessory in the historical time period.
9. The method of claim 1, wherein determining the predicted amount of power for the vehicle based on the current amount of power, the average speed of the vehicle over the historical period of time, the on-board accessory consumption amount over the historical period of time, and the pre-travel distance comprises:
determining a pre-travel time according to the pre-travel distance and the average speed of the vehicle in the historical time period;
and determining the predicted electric quantity of the vehicle according to the current electric quantity, a third preset scalar quantity, the pre-travel distance, the average speed of the vehicle in the historical time period, the second preset scalar quantity and the pre-travel time.
10. An energy management device for a plug-in hybrid vehicle, comprising:
the acquisition module is used for acquiring a data set to be processed; the data set to be processed comprises historical electric quantity, average speed of the vehicle in a historical time period, driving distance of the vehicle in the historical time period, power consumption of vehicle-mounted accessories in the historical time period, predicted driving speed and pre-driving distance of the vehicle;
the first determining module is used for determining the current electric quantity of the vehicle according to the historical electric quantity, the average speed of the vehicle in the historical time period, the running distance of the vehicle in the historical time period and the consumed electric quantity of the vehicle accessories in the historical time period;
the second determination module is used for determining the upper limit electric quantity and the lower limit electric quantity based on the current electric quantity;
the third determination module is used for determining the predicted electric quantity of the vehicle according to the current electric quantity, the average speed of the vehicle in the historical time period, the consumed electric quantity of the vehicle-mounted accessories in the historical time period and the pre-travel distance;
a fourth determination module configured to determine a target operating mode of the vehicle based on the current amount of power, the upper limit amount of power, the lower limit amount of power, the predicted amount of power, an average speed of the vehicle over the historical period of time, and a predicted travel speed of the vehicle.
And the switching module is used for switching the current working mode of the vehicle to the target working mode.
11. An electronic device comprising a processor and a memory, wherein the memory has stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which are loaded and executed by the processor to implement the method of energy management for a plug-in hybrid vehicle of any one of claims 1-9.
12. A computer readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions that is loaded and executed by a processor to implement a method of energy management for a plug-in hybrid vehicle as claimed in any one of claims 1 to 9.
CN202011087570.0A 2020-10-12 2020-10-12 Energy management method and device for plug-in hybrid electric vehicle Active CN112389272B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011087570.0A CN112389272B (en) 2020-10-12 2020-10-12 Energy management method and device for plug-in hybrid electric vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011087570.0A CN112389272B (en) 2020-10-12 2020-10-12 Energy management method and device for plug-in hybrid electric vehicle

Publications (2)

Publication Number Publication Date
CN112389272A true CN112389272A (en) 2021-02-23
CN112389272B CN112389272B (en) 2022-12-13

Family

ID=74596522

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011087570.0A Active CN112389272B (en) 2020-10-12 2020-10-12 Energy management method and device for plug-in hybrid electric vehicle

Country Status (1)

Country Link
CN (1) CN112389272B (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180162358A1 (en) * 2016-12-12 2018-06-14 Hyundai Motor Company Method for controlling hybrid starter and generator for improving fuel efficiency and eco-friendly vehicle
US10493849B2 (en) * 2017-01-26 2019-12-03 Toyota Jidosha Kabushiki Kaisha Battery system and estimation system
CN111038334A (en) * 2019-12-31 2020-04-21 华人运通(江苏)技术有限公司 Method and device for predicting driving range of electric automobile
CN111186339A (en) * 2018-11-14 2020-05-22 北京宝沃汽车有限公司 Vehicle control method and system and vehicle

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180162358A1 (en) * 2016-12-12 2018-06-14 Hyundai Motor Company Method for controlling hybrid starter and generator for improving fuel efficiency and eco-friendly vehicle
US10493849B2 (en) * 2017-01-26 2019-12-03 Toyota Jidosha Kabushiki Kaisha Battery system and estimation system
CN111186339A (en) * 2018-11-14 2020-05-22 北京宝沃汽车有限公司 Vehicle control method and system and vehicle
CN111038334A (en) * 2019-12-31 2020-04-21 华人运通(江苏)技术有限公司 Method and device for predicting driving range of electric automobile

Also Published As

Publication number Publication date
CN112389272B (en) 2022-12-13

Similar Documents

Publication Publication Date Title
US10415986B2 (en) Route-based distance to empty calculation for a vehicle
US9902392B2 (en) Mobility information processing apparatus, mobility information processing method, and driving support system
JP5077195B2 (en) Driving support device, method and program
US8521408B2 (en) Method for estimating remaining travel distance of electric vehicle
CN102867430B (en) Information terminal and cruise controller for electric-powered vehicle
US9616771B2 (en) Method of managing the energy consumed by an automotive vehicle and system implementing such a method
US20140167680A1 (en) System and method for periodically charging sub-battery for electric vehicle
CN107933317A (en) Method, apparatus, equipment and the pure electric automobile of the remaining continual mileage of estimation
CN103802675A (en) Detecting method and system for remaining mileage of electric automobile
CN112224089A (en) Energy consumption-based travel planning method and device, electronic equipment and storage medium
CN111824117B (en) Hybrid electric vehicle energy efficiency optimization control method and system based on working condition prediction
CN112824196A (en) Driver model estimation, classification, and adaptation for range prediction
CN112373319B (en) Power system control method and system of range-extended vehicle and vehicle
CN109649392A (en) Autonomous vehicle acceleration profile
KR20190120794A (en) Method and placement for balancing battery packs
KR20140095780A (en) Apparatus and method for estimating a drivable distance of an electronic vehecle
CN115817183A (en) Method and device for predicting driving range of pure electric vehicle
CN112389272B (en) Energy management method and device for plug-in hybrid electric vehicle
CN117584772A (en) Electric vehicle charging based on targets
Atmaca Energy management of solar car in circuit race
JP2015123822A (en) Control device of hybrid electric automobile
CN114834433A (en) Hybrid vehicle power mode management method, hybrid vehicle power mode management device, electronic apparatus, and medium
CN109466377A (en) For automatically updating the method, apparatus and storage medium of SOC distance reference value
US11827208B2 (en) Driving guide setting system of electric operating vehicle and method of setting the driving guide
JP2020061861A (en) Charge control device

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant