CN110281904B - Energy management method and device for hybrid vehicle and terminal - Google Patents
Energy management method and device for hybrid vehicle and terminal Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W20/00—Control systems specially adapted for hybrid vehicles
- B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2510/00—Input parameters relating to a particular sub-units
- B60W2510/24—Energy storage means
- B60W2510/242—Energy storage means for electrical energy
- B60W2510/244—Charge state
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/06—Combustion engines, Gas turbines
- B60W2710/0666—Engine torque
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/08—Electric propulsion units
- B60W2710/083—Torque
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- 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
- Y02T10/62—Hybrid vehicles
Abstract
The invention discloses an energy management method, a device and a terminal of a hybrid vehicle, wherein the method comprises the following steps: acquiring vehicle running information in a preset first time period before the current running time of the vehicle; obtaining at least one typical running condition type of a vehicle and characteristic parameters corresponding to each typical running condition type; obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions; acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition; acquiring an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition; controlling vehicle engine and electric machine output torques based on the energy management strategy; the invention has high comprehensive efficiency and low oil consumption.
Description
Technical Field
The invention relates to the technical field of automobile energy management, in particular to an energy management method, device and terminal for a hybrid electric vehicle.
Background
At present, most energy management of hybrid electric vehicles is a regular energy management strategy, which is mainly formulated according to control curve (MAP) diagrams of main vehicle components such as an engine, a motor and the like and engineering practice experience; ensuring that each component works to keep the power distribution rule of the high-efficiency area in a threshold value form; in the process, the common control parameters include vehicle speed, power, torque and the like, and the basic working principle is as follows:
when the current state of charge (SOC) of the battery is higher than the set minimum value: if the vehicle speed is less than the set vehicle speed and the required power is less than the maximum set value, the motor is used for driving the vehicle independently; if the vehicle speed is greater than the set value, but the required power is less than the minimum value of the starting of the engine, the motor is used for driving the vehicle independently; if the vehicle speed is greater than the set value, the required power is greater than the minimum starting value of the engine and is less than the set maximum value of the engine, and the engine is used for driving the vehicle independently;
when the required power is greater than the maximum set power of the engine, namely the vehicle is in a climbing or rapid acceleration condition, the motor and the engine are driven in a combined manner to provide a sufficient power source for the vehicle to run; if the charge set point is lower, the engine provides the power required for vehicle operation and also charges the battery.
The conventional energy management strategy is not easy to quickly and accurately convert energy management when dealing with complicated and variable actual driving conditions of the vehicle, and has low efficiency and increased oil consumption.
Disclosure of Invention
In order to solve the technical problems, the invention discloses an energy management method of a hybrid vehicle, which adopts an energy management strategy corresponding to the vehicle running condition through the identification of the vehicle running condition so as to control the output torque of a vehicle engine and a motor in real time, thereby not only improving the comprehensive efficiency, but also reducing the oil consumption.
In order to achieve the above object, the present invention provides an energy management method of a hybrid vehicle, the method including:
acquiring vehicle running information in a preset first time period before the current running time of a vehicle, wherein the vehicle running information comprises the running speed and the acceleration of the vehicle;
obtaining at least one typical running condition type of a vehicle and characteristic parameters corresponding to each typical running condition type;
obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions;
acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition;
acquiring an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
controlling vehicle engine and electric machine output torques based on the energy management strategy.
Further, before obtaining at least one typical driving condition type of the vehicle and the characteristic parameter corresponding to each typical driving condition type, the method further includes:
acquiring running characteristic parameters of the vehicle under different running conditions;
preprocessing the driving characteristic parameters, and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working-condition scene data training.
Further, the obtaining, according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, a vehicle running condition of the vehicle at the current running time, where the vehicle running condition is one of the types of the typical running conditions, includes:
obtaining a first characteristic parameter of vehicle running according to the vehicle running information;
judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not;
if so, determining that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
Further, the obtaining an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery state of charge and the vehicle running condition includes:
acquiring the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
acquiring the working mode of a vehicle engine;
judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
and if so, judging that the energy management strategy is an engine and motor combined control strategy.
Further, the determining whether the operating mode of the vehicle engine satisfies the low-efficiency operating mode according to the driving demand of the vehicle includes:
judging whether the driving requirement of the vehicle meets a first preset condition or not;
and if so, determining that the working mode of the vehicle engine meets the low-efficiency working mode.
The present invention provides an energy management apparatus of a hybrid vehicle, the apparatus including:
the system comprises a running information acquisition module, a running information acquisition module and a running information acquisition module, wherein the running information acquisition module is used for acquiring vehicle running information in a preset first time period before the current running time of a vehicle, and the vehicle running information comprises the running speed and the acceleration of the vehicle;
the typical running condition acquisition module is used for acquiring at least one typical running condition type of the vehicle and characteristic parameters corresponding to each typical running condition type;
the vehicle running condition obtaining module is used for obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions;
the information acquisition module is used for acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition;
the energy management strategy acquisition module is used for acquiring an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
a control module for the energy management strategy to control vehicle engine and motor output torques.
Further, still include:
the characteristic parameter acquisition module is used for acquiring the driving characteristic parameters of the vehicle under different driving conditions;
the data processing module is used for preprocessing the driving characteristic parameters and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working-condition scene data training.
Further, the vehicle driving condition obtaining module includes:
the first acquisition unit is used for acquiring a first characteristic parameter of vehicle running according to the vehicle running information;
the first judging unit is used for judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not;
and the first judging unit is used for judging that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
Further, the energy management policy obtaining module includes:
the second acquisition unit is used for acquiring the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
a third acquisition unit for acquiring an operating mode of the vehicle engine;
the second judgment unit is used for judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
and the second judging unit is used for judging that the energy management strategy is an engine and motor combined control strategy.
The invention provides an energy management terminal of a hybrid vehicle, which comprises a processor and a memory;
the processor adapted to implement one or more instructions;
the memory stores one or more instructions adapted to be loaded and executed by the processor to implement the energy management method of the hybrid vehicle as described above.
The embodiment of the invention has the following beneficial effects:
according to the energy management method of the hybrid vehicle disclosed by the invention, the energy management strategy corresponding to the vehicle running condition is adopted through the identification of the vehicle running condition so as to control the output torque of the vehicle engine and the motor in real time, so that the comprehensive efficiency is improved, and the oil consumption is reduced.
Drawings
In order to more clearly illustrate the energy management method, device and terminal of the hybrid vehicle according to the present invention, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on the drawings without inventive labor.
FIG. 1 is a schematic flow chart illustrating a method for energy management of a hybrid vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for acquiring a driving condition of a vehicle according to an embodiment of the present invention;
fig. 3 is a schematic flowchart of an energy management policy obtaining method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an energy management device of a hybrid vehicle according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an energy management terminal of a hybrid vehicle according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above 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 invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention can be applied to the energy management of the plug-in hybrid electric vehicle; specifically, a typical driving condition library of the plug-in hybrid electric vehicle type can be established, online identification of driving conditions is completed through a neural network, an offline optimal energy distribution track under the driving conditions is obtained by applying a dynamic programming algorithm based on various types of typical driving conditions in the typical driving condition library, online application design is completed, a complete hybrid passenger energy management strategy is established by combining with the condition identification, and automatic identification and switching of an optimal control algorithm under different driving conditions are realized.
The invention sets the initial value of the state of charge of the battery and the final value of the state of charge to be 50% by taking the lowest fuel consumption as a target based on the built plug-in hybrid electric vehicle model, and obtains the optimal output torque distribution track of the globally optimal engine and motor under each typical driving working condition (which can be 11) by simulation calculation under a certain constraint condition. The comprehensive efficiency of the engine and the motor is highest by controlling the torque output of the engine and the motor, and the purpose of reducing the oil consumption is achieved.
Referring to fig. 1, which is a flow chart illustrating an energy management method for a hybrid vehicle according to an embodiment of the present invention, the present specification provides the method operation steps as described in the embodiment or the flow chart, but based on the conventional method; or the inventive process may include additional or fewer steps. The step sequence recited in the embodiments is only one of the execution sequences of the steps, and does not represent the only execution sequence, and the energy management method during the running of the vehicle can be executed according to the method sequence shown in the embodiments or the figures. Specifically, as shown in fig. 1, the method includes:
s101, obtaining vehicle running information in a preset first time period before the current running time of a vehicle, wherein the vehicle running information comprises the running speed and the acceleration of the vehicle;
it should be noted that, in the embodiment of the present specification, the vehicle running speed may include a maximum vehicle speed and an average vehicle speed of the vehicle running in a preset first time period; the acceleration may be a maximum acceleration, a minimum acceleration (which may be a negative value, that is, a deceleration), and an average acceleration of the vehicle traveling during a preset first period;
in the embodiment of the present specification, the vehicle running information may further include a period of time during which the vehicle is in a low-speed or stopped state, a period of time during which the vehicle is at a medium and low vehicle speed, a period of time during which the vehicle is at a medium and high vehicle speed, and a period of time during which the vehicle is at a high speed;
specifically, the vehicle speed is: when V is more than 0 and less than 15Km/h, the vehicle is in a low speed or parking state; when the vehicle speed is 15< V <30Km/h, the vehicle is at a medium and low speed; the vehicle speed is: when the V is more than 30 and less than 60Km/h, the vehicle is at a medium and high speed; the vehicle speed is: when V is more than 60 and less than 100Km/h, the vehicle is at high speed;
in the embodiment, the vehicle running information may further include a period during which the vehicle acceleration is large, a period during which the vehicle deceleration is large, and a period during which the vehicle acceleration is small;
specifically, the vehicle acceleration is: 1.5<a<2.5m/s2When the vehicle is in a high acceleration state, the vehicle is in a high acceleration state; vehicle acceleration of-2.5<a<-1.5m/s2When the vehicle deceleration is larger; the vehicle acceleration is: 0<a<1.5m/s2When the vehicle acceleration is small.
In a preferred embodiment of the present specification, if the current driving time is t, the preset first time period may be t- Δ t1,t]The time period in between;
s103, acquiring at least one typical running condition type of the vehicle and characteristic parameters corresponding to each typical running condition type;
in this embodiment of the present specification, before the obtaining at least one typical driving condition type of the vehicle and the characteristic parameter corresponding to each typical driving condition type, the method further includes:
s1, acquiring the driving characteristic parameters of the vehicle under different driving conditions;
in the embodiment of the specification, the driving information of the vehicle under different driving conditions under different scenes of the vehicle is acquired, and the driving characteristic parameters of the vehicle corresponding to the driving information of the vehicle are acquired according to the driving information of the vehicle;
s2, preprocessing the driving characteristic parameters, and inputting the preprocessed driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working condition scene data training;
in the embodiment of the specification, the driving characteristic parameters are preprocessed and input into the neural network, and typical driving conditions of various types can be obtained; the neural network is obtained by training the running data of a plurality of running conditions under a plurality of scenes.
Aiming at each typical running condition, an offline global optimization program is applied to obtain an offline optimal energy distribution track of each typical running condition; by adopting a neural network method, converting the optimal energy distribution track obtained off-line into a rule capable of being applied on-line, thereby establishing an optimal on-line energy management strategy aiming at each typical working condition; the design obviously improves the oil saving rate and the electric quantity maintenance of the whole vehicle.
S105, obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions;
in the embodiment of the specification, the actual driving condition of the vehicle is identified as a certain preset typical driving condition through a neural network according to the actual driving condition of the vehicle.
The typical running conditions can be 11 types, and the typical running conditions have strong representativeness, so that the covering of the running conditions in the actual running process of the vehicle is realized, namely the running conditions in the running process of the vehicle are all composed of one or more selected typical running conditions.
As shown in fig. 2, in the embodiment of the present disclosure, a flow chart of a method for obtaining a driving condition of a vehicle according to an embodiment of the present disclosure is shown; specifically, the following is:
s201, obtaining a first characteristic parameter of vehicle running according to vehicle running information;
in an embodiment of the present specification, the first characteristic parameter may include: the method comprises the following steps that the maximum vehicle speed and the average vehicle speed of the vehicle running in a preset first time period, the percentage of the time length of the vehicle in a low speed or parking state to the preset first time period, the percentage of the time length of the vehicle in a medium and low vehicle speed to the preset first time period, the percentage of the time length of the vehicle in a medium and high vehicle speed to the preset first time period, and the percentage of the time length of the vehicle in a high speed to the preset first time period are preset;
in an embodiment of the present specification, the first characteristic parameter may further include: the method comprises the following steps that the maximum acceleration, the minimum acceleration and the average acceleration of the running of the vehicle in a preset first time period, the percentage of the duration with larger vehicle acceleration to the preset first time period, the percentage of the duration with larger vehicle deceleration to the preset first time period and the percentage of the duration with smaller vehicle acceleration to the preset first time period are determined;
s203, judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical driving condition type is greater than or equal to a preset first threshold value or not;
in the present specification embodiment, the preset first threshold may be 0.95; namely, whether the goodness of fit of the first characteristic parameter and the second characteristic parameter corresponding to one typical running condition in various types of typical running conditions is greater than or equal to 95% is judged.
And S205, if yes, determining that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
In the embodiment of the present specification, if the matching degree of the first characteristic parameter and the second characteristic parameter corresponding to one typical driving condition type is greater than or equal to 95%, it is determined that the typical driving condition corresponding to the second characteristic parameter is the vehicle driving condition.
In the embodiment of the specification, the time length needed for acquiring the running condition of the vehicle is delta t2That is, the time required for identifying the driving condition is Δ t2Then at [ t, t + Δ t2]The running condition of the vehicle is the running condition determined according to the running information of the vehicle in the preset first time period; and the condition may last for a period of time.
S107, acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition;
in the embodiment of the present specification, the vehicle running condition may be one of various typical running conditions; acquiring vehicle speed information, required power and battery state of charge information under the typical running working condition;
specifically, the real-time vehicle speed information, the required power and the battery state of charge of the vehicle can be obtained.
S109, obtaining an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
in the embodiment of the specification, according to the typical running condition corresponding to the running condition of the vehicle and the optimal energy management strategy of the typical running condition obtained by offline calculation, the output torques of the engine and the motor of the vehicle can be controlled in real time based on the identification of the running condition of the vehicle, so that the comprehensive efficiency is higher, and the purpose of reducing the oil consumption is achieved.
As shown in fig. 3, in the embodiment of the present specification, a flowchart of an energy management policy obtaining method according to an embodiment of the present invention is shown; specifically, the method comprises the following steps:
s301, obtaining the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
in the embodiments of the present specification, the vehicle driving demand may be a driving demand set or controlled by the driver; the driving demand may be a demand for vehicle torque, vehicle speed.
S303, acquiring the working mode of the vehicle engine;
in the embodiments herein, the operating mode of the engine may be a high efficiency operating mode or a low efficiency operating mode.
S305, judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
in this embodiment, the determining whether the operation mode of the engine of the vehicle satisfies the low-efficiency operation mode according to the driving demand of the vehicle includes:
a1, judging whether the driving requirement of the vehicle meets a first preset condition;
in the embodiment of the present specification, the first preset condition may be that the vehicle torque is small and the running vehicle speed is low, and if the vehicle driving demand is that the torque is small and the vehicle speed is low, it is determined that the vehicle driving demand satisfies the first preset condition;
and A2, if yes, determining that the working mode of the vehicle engine meets the low-efficiency working mode.
In the embodiment of the specification, when the driving demand of the vehicle satisfies the first preset condition; determining that the operating mode of the vehicle engine satisfies a low-efficiency operating mode.
S307, if yes, the energy management strategy is judged to be an engine and motor combined control strategy.
In the embodiment of the specification, if the working mode of the vehicle engine is a low-efficiency working mode, the control transfer of the working condition point of the engine is required; if the driving demand is that the torque is small and the vehicle speed is low, the output torque of the engine is required to be improved so as to improve the efficiency of the engine, and the torque exceeding the efficiency corresponding part of the engine can be used for driving the motor so as to charge the battery of the vehicle;
under the condition that the running condition of the vehicle is determined, the working efficiency of the engine is analyzed on line according to the working condition information, and energy management is carried out according to the efficiency of the engine and the current vehicle speed and the current state of charge of the battery.
And S111, controlling the output torque of the engine and the motor of the vehicle based on the energy management strategy.
In the embodiment of the specification, the output torques of the engine and the motor of the vehicle are controlled based on the combined control strategy of the engine and the motor; at this time, the engine starts to drive the vehicle and charges the battery or the engine and the motor drive the vehicle at the same time; when the demand torque is great, the engine can not satisfy the demand, and the motor can carry out the helping hand, and when the demand torque is little, engine inefficiency can be given battery charging at this moment, improves engine efficiency.
In another preferred embodiment of the present specification, the energy management strategy may also be an electric machine individual control strategy and an engine individual control strategy;
in the pure electric mode, namely the electric quantity of the battery can meet the driving requirement of a driver, and a motor independent control strategy can be adopted generally at low vehicle speed and small accelerator;
when the generator is in a high-efficiency working state, an engine independent control strategy can be adopted.
As can be seen from the above embodiments of the energy management method, the energy management device and the terminal for the hybrid vehicle provided by the invention, in the embodiments of the invention, vehicle running information in a preset first time period before the current running time of the vehicle is obtained, where the vehicle running information includes the running speed and the acceleration of the vehicle; obtaining at least one typical running condition type of a vehicle and characteristic parameters corresponding to each typical running condition type; obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions; acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition; acquiring an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition; controlling vehicle engine and electric machine output torques based on the energy management strategy; by utilizing the technical scheme provided by the embodiment of the specification, the energy management strategy corresponding to the running condition of the vehicle is adopted by identifying the running condition of the vehicle so as to control the output torque of the engine and the motor of the vehicle in real time, so that the comprehensive efficiency is improved, and the oil consumption is reduced.
An embodiment of the present invention further provides an energy management device for a hybrid vehicle, as shown in fig. 4, which is a schematic structural diagram of the energy management device for a hybrid vehicle according to the embodiment of the present invention; specifically, the device comprises:
the driving information acquiring module 410 is configured to acquire vehicle driving information within a preset first time period before a current driving time of a vehicle, where the vehicle driving information includes a driving speed and an acceleration of the vehicle;
the typical running condition obtaining module 420 is configured to obtain at least one typical running condition type of the vehicle and a characteristic parameter corresponding to each typical running condition type;
a vehicle running condition obtaining module 430, configured to obtain a vehicle running condition of a vehicle at a current running time according to the vehicle running information and characteristic parameters corresponding to types of each typical running condition, where the vehicle running condition is one of the types of the typical running conditions;
the information acquisition module 440 is configured to acquire a vehicle speed, required power, and a battery state of charge under the vehicle driving condition;
the energy management strategy acquisition module 450 is configured to acquire an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery state of charge and the vehicle running condition;
the control module 460, for the energy management strategy, controls vehicle engine and motor output torques.
In the embodiment of this specification, still include:
the characteristic parameter acquisition module is used for acquiring the driving characteristic parameters of the vehicle under different driving conditions;
the data processing module is used for preprocessing the driving characteristic parameters and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working-condition scene data training.
In the embodiment of the present specification, the vehicle driving condition obtaining module 430 includes:
the first acquisition unit is used for acquiring a first characteristic parameter of vehicle running according to the vehicle running information;
the first judging unit is used for judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not;
and the first judging unit is used for judging that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
In this embodiment, the energy management policy obtaining module 450 includes:
the second acquisition unit is used for acquiring the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
a third acquisition unit for acquiring an operating mode of the vehicle engine;
the second judgment unit is used for judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
and the second judging unit is used for judging that the energy management strategy is an engine and motor combined control strategy.
In an embodiment of the present specification, the second determination unit includes:
the first judgment subunit is used for judging whether the driving requirement of the vehicle meets a first preset condition or not;
a first determination subunit for determining that the operation mode of the vehicle engine satisfies a low-efficiency operation mode.
The embodiment of the invention provides an energy management terminal of a hybrid vehicle, which comprises a processor and a memory;
the processor adapted to implement one or more instructions;
the memory stores one or more instructions adapted to be loaded and executed by the processor to implement the energy management method of the hybrid vehicle as described in the method embodiments above.
The memory may be used to store software programs and modules, and the processor may execute various functional applications and data processing by operating the software programs and modules stored in the memory. The memory can mainly comprise a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs needed by functions and the like; the storage data area may store data created according to use of the apparatus, and the like. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory may also include a memory controller to provide the processor access to the memory.
Fig. 5 is a schematic structural diagram of an energy management terminal of a hybrid vehicle according to an embodiment of the present invention, where the internal configuration of the energy management terminal of the hybrid vehicle may include, but is not limited to: the energy management terminal comprises a processor, a network interface and a memory, wherein the processor, the network interface and the memory in the energy management terminal of the hybrid vehicle can be connected through a bus or in other ways, and the processor, the network interface and the memory are connected through the bus in the embodiment shown in fig. 5.
The processor (or CPU) is a computing core and a control core of an energy management terminal of the hybrid vehicle. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI, mobile communication interface, etc.). A Memory (Memory) is a Memory device in an energy management terminal of a hybrid vehicle for storing programs and data. It is understood that the memory herein may be a high-speed RAM storage device, or may be a non-volatile storage device (non-volatile memory), such as at least one magnetic disk storage device; optionally, at least one memory device located remotely from the processor. The memory provides a storage space that stores an operating system of an energy management terminal of the hybrid vehicle, which may include, but is not limited to: windows system (an operating system), Linux (an operating system), etc., which are not limited thereto; also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. In the embodiment of the present specification, the processor loads and executes one or more instructions stored in the memory to implement the energy management method of the hybrid vehicle provided by the above method embodiment.
Embodiments of the present invention also provide a storage medium that is capable of being disposed in an energy management terminal of a hybrid vehicle to store at least one instruction, at least one program, a set of codes, or a set of instructions related to implementing an energy management method of the hybrid vehicle in the method embodiments, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is capable of being loaded and executed by a processor of an electronic device to implement the energy management method of the hybrid vehicle provided in the method embodiments.
Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
As can be seen from the above embodiments of the energy management method, the energy management device and the terminal for the hybrid vehicle provided by the invention, in the embodiments of the invention, vehicle running information in a preset first time period before the current running time of the vehicle is obtained, where the vehicle running information includes the running speed and the acceleration of the vehicle; acquiring running characteristic parameters of the vehicle under different running conditions; preprocessing the driving characteristic parameters, and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working condition scene data training; obtaining at least one typical running condition type of a vehicle and characteristic parameters corresponding to each typical running condition type; obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions; specifically, a first characteristic parameter of vehicle running is obtained according to vehicle running information; judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not; if so, determining that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle. Acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition; acquiring an energy management strategy corresponding to the vehicle running condition according to the vehicle speed, the required power, the battery charge state and the vehicle running condition; specifically, the driving requirement of the vehicle is obtained according to the vehicle speed, the required power, the battery charge state and the vehicle running condition; acquiring the working mode of a vehicle engine; judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle; specifically, if yes, judging whether the driving requirement of the vehicle meets a first preset condition or not; and if so, determining that the working mode of the vehicle engine meets the low-efficiency working mode. The energy management strategy is determined to be an engine and electric machine combined control strategy. Controlling vehicle engine and electric machine output torques based on the energy management strategy; by utilizing the technical scheme provided by the embodiment of the specification, the energy management strategy corresponding to the running condition of the vehicle is adopted by identifying the running condition of the vehicle so as to control the output torque of the engine and the motor of the vehicle in real time, so that the comprehensive efficiency is improved, and the oil consumption is reduced.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device and server embodiments, since they are substantially similar to the method embodiments, the description is simple, and the relevant points can be referred to the partial description of the method embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. A method of energy management of a hybrid vehicle, characterized by: the method comprises the following steps:
acquiring vehicle running information in a preset first time period before the current running time of a vehicle, wherein the vehicle running information comprises the running speed and the acceleration of the vehicle;
obtaining typical running conditions of each type, and obtaining an offline optimal energy distribution track of each typical running condition by applying an offline global optimization program; establishing an optimal online energy management strategy of each typical running condition based on the neural network and each typical running condition offline optimal energy distribution track;
obtaining at least one typical running condition type of a vehicle and characteristic parameters corresponding to each typical running condition type;
obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions;
acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition;
performing offline analysis on the running condition of the vehicle to obtain the working efficiency of the engine;
acquiring an energy management strategy corresponding to the running working condition of the vehicle according to the working efficiency of the engine, the speed of the vehicle, the required power and the state of charge of a battery; the energy management strategy is an optimal online energy management strategy; the energy management strategy comprises an engine and motor combined control strategy, a motor control strategy and an engine control strategy;
controlling vehicle engine and electric machine output torques based on the energy management strategy.
2. The energy management method of a hybrid vehicle according to claim 1, characterized in that: before obtaining at least one typical driving condition type of the vehicle and the characteristic parameters corresponding to each typical driving condition type, the method further includes:
acquiring running characteristic parameters of the vehicle under different running conditions;
preprocessing the driving characteristic parameters, and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working-condition scene data training.
3. The energy management method of a hybrid vehicle according to claim 1, characterized in that: the method for obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions, and comprises the following steps:
obtaining a first characteristic parameter of vehicle running according to the vehicle running information;
judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not;
if so, determining that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
4. The energy management method of a hybrid vehicle according to claim 1, characterized in that: the method for obtaining the energy management strategy corresponding to the vehicle running working condition according to the vehicle speed, the required power, the battery charge state and the vehicle running working condition comprises the following steps:
acquiring the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
acquiring the working mode of a vehicle engine;
judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
and if so, judging that the energy management strategy is an engine and motor combined control strategy.
5. The energy management method of a hybrid vehicle according to claim 4, characterized in that: the judging whether the working mode of the vehicle engine meets the low-efficiency working mode according to the driving requirement of the vehicle comprises the following steps:
judging whether the driving requirement of the vehicle meets a first preset condition or not;
and if so, determining that the working mode of the vehicle engine meets the low-efficiency working mode.
6. An energy management device of a hybrid vehicle, characterized in that: the device comprises:
the system comprises a running information acquisition module, a running information acquisition module and a running information acquisition module, wherein the running information acquisition module is used for acquiring vehicle running information in a preset first time period before the current running time of a vehicle, and the vehicle running information comprises the running speed and the acceleration of the vehicle;
the energy management strategy acquisition module is used for acquiring typical running conditions of various types and applying an offline global optimization program to acquire an offline optimal energy distribution track of each typical running condition; establishing an optimal online energy management strategy of each typical running condition based on the neural network and each typical running condition offline optimal energy distribution track;
the typical running condition acquisition module is used for acquiring at least one typical running condition type of the vehicle and characteristic parameters corresponding to each typical running condition type;
the vehicle running condition obtaining module is used for obtaining the vehicle running condition of the vehicle at the current running moment according to the vehicle running information and the characteristic parameters corresponding to the types of the typical running conditions, wherein the vehicle running condition is one of the types of the typical running conditions;
the information acquisition module is used for acquiring the vehicle speed, the required power and the battery charge state under the vehicle running working condition;
the energy management strategy acquisition module is used for carrying out offline analysis on the running condition of the vehicle to obtain the working efficiency of the engine; acquiring an energy management strategy corresponding to the running working condition of the vehicle according to the working efficiency of the engine, the speed of the vehicle, the required power and the state of charge of a battery; the energy management strategy is an optimal online energy management strategy; the energy management strategy comprises an engine and motor combined control strategy, a motor control strategy and an engine control strategy;
a control module for the energy management strategy to control vehicle engine and motor output torques.
7. The energy management device of a hybrid vehicle according to claim 6, characterized in that: further comprising:
the characteristic parameter acquisition module is used for acquiring the driving characteristic parameters of the vehicle under different driving conditions;
the data processing module is used for preprocessing the driving characteristic parameters and inputting the driving characteristic parameters into a neural network to obtain characteristic parameters of typical driving conditions of various types; the neural network is obtained through multi-working-condition scene data training.
8. The energy management device of a hybrid vehicle according to claim 6, characterized in that: the vehicle driving condition obtaining module comprises:
the first acquisition unit is used for acquiring a first characteristic parameter of vehicle running according to the vehicle running information;
the first judging unit is used for judging whether the goodness of fit of the first characteristic parameter and a second characteristic parameter corresponding to a typical running condition type is greater than or equal to a preset first threshold value or not;
and the first judging unit is used for judging that the typical running condition corresponding to the second characteristic parameter is the vehicle running condition at the current running time of the vehicle.
9. The energy management device of a hybrid vehicle according to claim 6, characterized in that: the energy management policy acquisition module includes:
the second acquisition unit is used for acquiring the driving requirement of the vehicle according to the vehicle speed, the required power, the battery charge state and the vehicle running condition;
a third acquisition unit for acquiring an operating mode of the vehicle engine;
the second judgment unit is used for judging whether the working mode of the vehicle engine meets the low-efficiency working mode or not according to the driving requirement of the vehicle;
and the second judging unit is used for judging that the energy management strategy is an engine and motor combined control strategy.
10. An energy management terminal of a hybrid vehicle, characterized in that: the terminal comprises a processor and a memory;
the processor adapted to implement one or more instructions;
the memory storing one or more instructions adapted to be loaded and executed by the processor to implement the energy management method of a hybrid vehicle as claimed in any one of claims 1 to 5.
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