CN112319459B - Method, device and medium for self-adapting to mountain road working condition of hybrid power vehicle - Google Patents
Method, device and medium for self-adapting to mountain road working condition of hybrid power vehicle Download PDFInfo
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- CN112319459B CN112319459B CN202011159001.2A CN202011159001A CN112319459B CN 112319459 B CN112319459 B CN 112319459B CN 202011159001 A CN202011159001 A CN 202011159001A CN 112319459 B CN112319459 B CN 112319459B
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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
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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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/18—Propelling the vehicle
- B60W30/182—Selecting between different operative modes, e.g. comfort and performance modes
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
- B60W40/076—Slope angle of the road
Abstract
The invention discloses a method for self-adapting to mountain road conditions of a hybrid electric vehicle, which comprises the following steps: when the state of charge of the battery is smaller than an electric quantity calibration value, judging whether the slope of the mountain road is larger than the slope calibration value or not; and when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode. The invention also discloses a device and a computer readable storage medium, which solve the problem that the hybrid electric vehicle can not intelligently and automatically switch the mountain mode when dealing with the mountain working condition in the prior art.
Description
Technical Field
The present invention relates to the field of control technologies, and in particular, to a method, an apparatus, and a computer storage medium for adaptive mountain road conditions of a hybrid vehicle.
Background
At present, the hybrid power vehicle can set a mountain mode in response to mountain working conditions, so that the vehicle power is enhanced, the vehicle power-preserving capability is improved, and the adaptability of the vehicle to mountain is improved. Normally, the driver starts the mountain mode through the mode selection switch, and this mode has the defects that:
1. after the vehicle enters a mountain working condition, a driver forgets to switch the mountain mode, and the electric quantity of a power battery can be suddenly reduced, so that the vehicle is powerless in hill start and weak in power during acceleration, and the driving experience is affected;
2. after the vehicle enters the mountain working condition, if the electric quantity of the power battery is too low, and the mountain slope is longer, the power performance of the vehicle cannot be ensured at the moment, so that the climbing capacity of the mountain of the vehicle is affected; if the electric quantity of the power battery is higher, when the mountain slope is shorter, the mountain mode is switched in advance, so that the oil consumption can be increased, the energy utilization rate can be reduced, and the advantages of energy conservation and emission reduction of the hybrid electric vehicle can not be furthest exerted. Therefore, the problem that the hybrid vehicle cannot intelligently and automatically switch the mountain mode when dealing with the mountain working condition exists in the prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device and a computer storage medium for self-adapting to mountain road conditions of a hybrid electric vehicle, and aims to solve the problem that the hybrid electric vehicle cannot intelligently and automatically switch mountain modes when the hybrid electric vehicle is corresponding to mountain road conditions in the prior art.
In order to achieve the above object, the present invention provides a method for adapting to a mountain road condition of a hybrid vehicle, the method for adapting to a mountain road condition of a hybrid vehicle comprising the steps of:
when the state of charge of the battery is smaller than an electric quantity calibration value, judging whether the slope of the mountain road is larger than the slope calibration value or not;
and when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode.
In one embodiment, the determining whether the slope of the mountain road is greater than the slope calibration value includes:
estimating the mountain road gradient by using a vehicle dynamics equation;
and judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
In one embodiment, the vehicle dynamics equation is:
T q /R＝m*g*(f 1 +f 2 *u+f 3 *u 2 )+C D *A*u 2 /21.25+δ*m*a+m*g*sinα
wherein:
T q total driving torque of the vehicle;
r, the radius of the wheel;
m, vehicle mass;
g, a gravitational constant;
f 1 、f 2 、f 3 a rolling resistance coefficient related to speed;
u, vehicle speed;
C D wind resistance coefficient;
a, the windward resistance area of the vehicle;
delta, the conversion coefficient of the rotating mass of the automobile;
a, vehicle acceleration;
α, ramp angle.
In one embodiment, the determining whether the slope of the mountain road is greater than the slope calibration value includes:
estimating the mountain road gradient by using a vehicle navigation system; the vehicle-mounted navigation system comprises a geographic information system and a global positioning system;
and judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
In one embodiment, the estimating the mountain road gradient using the vehicle navigation system includes:
acquiring a driving destination selected on the vehicle-mounted navigation system;
determining a driving path according to the driving destination, and judging whether mountain road conditions exist on the driving path;
when mountain road conditions exist on the driving path, determining a target sampling point;
acquiring a vehicle position in real time through the global positioning system receiver;
calculating the road surface driving distance between the current position of the vehicle and the target sampling point;
map matching is carried out by utilizing a geographic information system, and the altitude of the target sampling point and the altitude of the current position of the vehicle are obtained;
and calculating the mountain road gradient through a mountain road gradient value calculation formula.
In an embodiment, the mountain road gradient value calculation formula is as follows:
wherein i is a mountain road gradient value; e (E) 2 The elevation of the road surface of the target sampling point is obtained; e (E) 1 The elevation of the road surface at the current position of the vehicle is obtained; l is the running distance between the current position of the vehicle and the road surface of the vehicle at the target sampling point.
In one embodiment, the ramp length is the road surface distance travelled.
In an embodiment, after the step of automatically switching mountain modes, the method further includes:
and when the mountain road gradient is smaller than or equal to the mountain road gradient calibration value and the driving distance is greater than the ramp length calibration value, exiting the mountain land mode.
To achieve the above object, the present invention also provides an apparatus including a memory, a processor, and a program for adapting a hybrid vehicle to a mountain road condition stored in the memory and operable on the processor, the program for adapting a hybrid vehicle to a mountain road condition, when executed by the processor, implementing the steps of the method for adapting a hybrid vehicle to a mountain road condition as described above.
In order to achieve the above object, the present invention further provides a computer readable storage medium, wherein the computer readable storage medium stores a program for adapting to a mountain road condition of a hybrid vehicle, and the program for adapting to a mountain road condition of the hybrid vehicle implements each step of the method for adapting to a mountain road condition of the hybrid vehicle as described above when being executed by a processor.
The invention provides a method, a device and a computer storage medium for self-adapting to mountain road working conditions of a hybrid power vehicle, wherein when the charge state of a battery is smaller than an electric quantity calibration value, whether the gradient of the mountain road is larger than the gradient calibration value is judged in the charge state of the battery; when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, namely when the conditions are met, the hybrid vehicle automatically switches the mountain mode, so that the hybrid vehicle automatically switches the mountain mode when a user forgets to switch the mountain mode, and the intelligent automatic switching of the mountain mode when the user is in response to the mountain working condition is also ensured. Therefore, the problem that the hybrid power vehicle cannot intelligently and automatically switch the mountain mode when the hybrid power vehicle is corresponding to the mountain working condition in the prior art is solved.
Drawings
FIG. 1 is a schematic view of a device according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of a method for adapting a hybrid vehicle to a mountain road condition in accordance with the present invention;
FIG. 3 is a flow chart of a second embodiment of a method for adapting a hybrid vehicle to a mountain road condition in accordance with the present invention;
FIG. 4 is a flow chart of a third embodiment of a method for adapting a hybrid vehicle to a mountain road condition according to the present invention;
FIG. 5 is a schematic view of a mountain road gradient calculation;
FIG. 6 is a flow chart of a fourth embodiment of a method for adapting a hybrid vehicle to a mountain road condition.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The main solutions of the embodiments of the present invention are: when the state of charge of the battery is smaller than an electric quantity calibration value, judging whether the mountain road gradient is larger than the gradient calibration value or not in the state of charge of the battery; when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, namely when the conditions are met, the hybrid vehicle automatically switches the mountain mode, so that the hybrid vehicle automatically switches the mountain mode when a user forgets to switch the mountain mode, and the intelligent automatic switching of the mountain mode when the user is in response to the mountain working condition is also ensured. Therefore, the problem that the hybrid power vehicle cannot intelligently and automatically switch the mountain mode when the hybrid power vehicle is corresponding to the mountain working condition in the prior art is solved.
As an implementation manner, as shown in fig. 1, fig. 1 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
The processor 1100 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the methods described above may be performed by integrated logic circuitry in hardware or instructions in software in processor 1100. The processor 1100 described above may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 1200, and the processor 1100 reads information in the memory 1200, and in combination with its hardware, performs the steps of the method described above.
It is to be appreciated that memory 1200 in embodiments of the invention may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (Double Data Rate SDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (SLDRAM), and Direct RAM (DRRAM). The memory 1200 of the systems and methods described in embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
For a software implementation, the techniques described in embodiments of the present invention may be implemented by modules (e.g., procedures, functions, and so on) that perform the functions described in embodiments of the present invention. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
Based on the above-described structure, an embodiment of the present invention is presented.
Referring to fig. 2, fig. 2 is a first embodiment of a method for adapting to a mountain road condition of a hybrid vehicle according to the present invention, the method for adapting to a mountain road condition of a hybrid vehicle includes the steps of:
and step S110, judging whether the slope of the mountain road is larger than a slope calibration value or not when the charge state of the battery is smaller than the electric quantity calibration value.
In the present embodiment, the hybrid vehicle, also called a hybrid vehicle (Hybrid Power Automobile), means that two or more power sources are mounted on the vehicle: the current composite power automobile is generally an internal combustion locomotive generator and a car with the storage battery. There are a variety of vehicle-mounted power sources: the current composite power automobile is generally an internal combustion locomotive generator and a car with the storage battery. There are currently 3 main types of hybrid vehicles. One is a "parallel mode" in which the engine is the primary power and the electric motor is the auxiliary power of the auxiliary series hybrid electric vehicle. In this method, the engine is mainly driven to run, and the fuel consumption of the engine is reduced by assisting the electric motor when the fuel consumption of the engine is large, such as starting and accelerating, by utilizing the characteristic of the electric motor that the electric motor generates strong power during restarting. The structure of this mode is simpler, only need to add electric motor and storage battery on the car. In the other way, the electric motor is used only for driving at low speed, and the engine and the electric motor are used for driving in a series or parallel mode when the speed is increased. When the vehicle is started and driven at a low speed by the electric motor, the engine and the electric motor share power with high efficiency when the speed is increased, and a power sharing device, a generator and the like are needed in this way, so that the structure is complex. In addition, an electric vehicle is a "tandem system" in which only an electric motor is used to drive the vehicle, an engine is used as a power source, and the vehicle is driven by the electric motor only, and a driving system is used as the electric motor only, but the fuel engine is required to be installed in the same manner, so that the electric vehicle is also a hybrid vehicle.
HEV (Hybrid-electric vehicle) -Hybrid. The hybrid power is two driving modes of gasoline driving and electric driving, and has the advantages that when the vehicle starts and stops, the engine does not work only by being driven by the generator and not reaching a certain speed, so that the engine can be kept in an optimal working condition all the time, the power performance is good, the emission is very low, and the source of electric energy is the engine which only needs to be refueled. The key of the hybrid electric vehicle is a hybrid electric system, and the performance of the hybrid electric vehicle is directly related to the whole vehicle performance of the hybrid electric vehicle. Over ten years of development, hybrid power system assemblies have developed from the original discrete structure of an engine and a motor to the integrated structure of the engine, the motor and a gearbox, namely integrated hybrid power system. The hybrid power assembly is classified into three types of series, parallel and series-parallel power transmission lines.
In this embodiment, the battery refers to a power battery, including but not limited to: lead-acid batteries, nickel-cadmium batteries, nickel-hydrogen batteries, lithium ion batteries, etc., are selected according to the particular application. SOC (State ofcharge), i.e. the state of charge, is used to reflect the remaining capacity of the battery, and is defined numerically as the ratio of the remaining capacity to the battery capacity, commonly expressed as a percentage. The value range is 0-1, and the battery is completely discharged when soc=0 and completely full when soc=1. The battery SOC cannot be directly measured, and the size of the battery can be estimated only through parameters such as the voltage of the battery terminal, the charge and discharge current, the internal resistance and the like.
The estimation method of SOC includes, but is not limited to, the following: 1. the internal resistance measuring method is to excite the battery with alternating current of different frequencies, measure the internal alternating current resistance of the battery and obtain the SOC estimated value through the established calculation model. The state of charge of the battery measured by the method reflects the SOC value of the battery under a specific constant current discharge condition. 2. The principle of the linear model method is that the linear model is built based on the variation of the SOC, the current and the voltage and the SOC value at the last time point, and the model is applicable to the conditions of low current and slow variation of the SOC and has high robustness to initial conditions of measurement errors and errors. 3. The Kalman filtering method is based on an ampere-hour integration method. The main idea of the Kalman filtering method is to make an optimal estimate in the sense of minimum variance of the state of the power system. The method is applied to battery SOC estimation, and the battery is regarded as a power system, and the state of charge is an internal state of the system.
The hybrid vehicle detects the state of charge of the battery, determines whether the state of charge of the battery is less than an electrical calibration value, which may be set according to a specific application, without any limitation. When the hybrid power vehicle detects that the state of charge of the battery is smaller than the electric quantity calibration value, one of the battery SOC judgment conditions is adopted, so that unnecessary oil consumption and emission caused by early switching are avoided while the mountain dynamics of the vehicle is ensured; judging whether the mountain road gradient is greater than the gradient calibration value, and estimating the mountain road gradient by the following methods: and estimating by using a vehicle dynamics equation and estimating by using a vehicle navigation system. As specifically set forth in the examples that follow.
Step S120, when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode.
In this embodiment, when the result of the judgment is that the mountain road gradient is greater than the gradient calibration value, the road gradient is used as one of the judgment conditions, so as to avoid erroneous switching of the mountain mode; judging whether the ramp length is greater than a calibration value of the ramp length, wherein the estimation method of the ramp length can be obtained by using a vehicle navigation system and a vehicle computing system; the length of the ramp is used as one of judging conditions, so that poor driving experience caused by frequent starting of mountain modes is avoided; the hybrid vehicle automatically switches the mountain mode when the mountain slope is greater than the slope calibration value and the ramp length is greater than the ramp length calibration value. The mountain mode may be a combined drive mode in which the motor and the internal combustion engine operate simultaneously, or may be an independent operation mode of the internal combustion engine.
In the technical scheme provided by the embodiment, when the state of charge of the battery is smaller than an electric quantity calibration value, whether the mountain road gradient is larger than the gradient calibration value is judged in the state of charge of the battery; when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, namely when the conditions are met, the hybrid vehicle automatically switches the mountain mode, so that the hybrid vehicle automatically switches the mountain mode when a user forgets to switch the mountain mode, and the intelligent automatic switching of the mountain mode when the user is in response to the mountain working condition is also ensured. Therefore, the problem that the hybrid power vehicle cannot intelligently and automatically switch the mountain mode when the hybrid power vehicle is corresponding to the mountain working condition in the prior art is solved.
Referring to fig. 3, fig. 3 is a second embodiment of a method for adapting to a mountain road condition of a hybrid vehicle according to the present invention, including:
compared with the first embodiment, the second embodiment includes step S210 and step S220, and other steps are the same as those of the first embodiment, and will not be described again.
Step S210, estimating the mountain road gradient by using a vehicle dynamics equation when the state of charge of the battery is smaller than an electric quantity calibration value;
in this embodiment, the vehicle dynamics equation is used to estimate the road slope when the state of charge of the battery is less than the charge calibration value. The method comprises the following steps:
T q /R＝m*g*(f 1 +f 2 *u+f 3 *u 2 )+C D *A*u 2 /21.25+δ*m*a+m*g*sinα
wherein:
T q total driving torque of vehicle, unit: nm;
r, wheel radius, unit: m;
m, vehicle mass, unit: kg;
g, gravity constant, 9.8m/s 2 ；
f 1 、f 2 、f 3 A rolling resistance coefficient related to speed;
u, vehicle speed, km/h;
C D wind resistance coefficient;
a, the windward resistance area of the vehicle, unit: m is m 2 ；
Delta, conversion coefficient of automobile rotating mass, delta >1;
a, vehicle acceleration, unit: m/s 2 ；
α, ramp angle, unit: degree (°).
And step S220, judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
In this embodiment, whether the value of the slope of the mountain road estimated according to the vehicle dynamics equation is greater than the slope calibration value is determined.
Step S230, when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode.
Referring to fig. 4, fig. 4 is a third embodiment of a method for adapting to a mountain road condition of a hybrid vehicle according to the present invention, including:
compared with the first embodiment, the third embodiment includes step S310 and step S320, and other steps are the same as those of the first embodiment, and will not be described again.
In step S310, when the state of charge of the battery is less than the electric quantity calibration value, the vehicle navigation system is used to estimate the mountain road gradient.
In the present embodiment, the in-vehicle navigation system includes a Geographic Information System (GIS) and a Global Positioning System (GPS); with the widespread use of car navigation systems and the continual upgrade of navigation technology, GPS-based navigation systems have tended to be mature, and the use of GPS receivers can obtain the position of a vehicle in real time. GIS is off-tyre on the map, is a carrier of geographic information, has wide application in traffic, and can provide some basic information of roads, such as road elevation and road mileage. And when the charge state of the battery is smaller than the electric quantity calibration value, estimating the mountain road gradient by using the vehicle-mounted navigation system.
Step S310 includes the steps of:
step S311, acquiring a driving destination selected on the vehicle navigation system.
In the present embodiment, the hybrid vehicle acquires the driving destination selected by the driver on the in-vehicle navigation system.
Step S312, determining a driving path according to the driving destination, and judging whether mountain road conditions exist on the driving path.
In this embodiment, the vehicle navigation system determines a driving path according to a driving destination, and determines whether a mountain road condition exists on the driving path through the vehicle navigation system.
Step S313, determining a target sampling point when the mountain road condition exists on the driving path.
In this embodiment, when a mountain road condition exists on the driving path, a target sampling point is determined, where the target sampling point may be preferably a hill top.
Step S314, acquiring the vehicle position in real time through the global positioning system receiver.
In the present embodiment, the hybrid vehicle position is acquired in real time by the global positioning system receiver.
Step S315, calculating the road surface driving distance between the current position of the vehicle and the target sampling point.
In this embodiment, the vehicle-mounted computer system calculates the road surface travel distance of the current position of the hybrid vehicle from the target sampling point in real time. The calculated distance travelled by the road surface is an estimated value of the ramp length, and a data determination is provided for whether the subsequent ramp length is greater than the ramp length calibration value.
And step S316, utilizing geographic information system map matching to acquire the altitude of the target sampling point and the altitude of the current position of the vehicle.
In this embodiment, the altitude of the target sampling point and the altitude of the current position of the hybrid vehicle may be obtained by map matching using the geographic information system.
In step S317, the mountain road gradient is calculated by the mountain road gradient value calculation formula.
In the present embodiment, the mountain road gradient is calculated by a mountain road gradient value calculation formula. The calculation formula of the mountain road gradient value is as follows:
wherein i is a mountain road gradient value; e (E) 2 The elevation of the road surface is the target sampling point; e (E) 1 The elevation of the road surface at the current position of the vehicle; l is the vehicle road surface driving distance between the current position of the vehicle and the target sampling point.
Referring to fig. 5, fig. 5 is a schematic view of a mountain road gradient calculation value.
Step S320, judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
In this embodiment, whether the value of the mountain road gradient is greater than the gradient calibration value is determined according to the estimated value.
Step S330, when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode.
In the technical scheme provided by the embodiment, the mountain road gradient and the ramp length are estimated by using a mountain road gradient value calculation formula, so that data support is provided for subsequent judgment.
Referring to fig. 5, fig. 5 is a fourth embodiment of a method for adapting a hybrid vehicle to a mountain road condition according to the present invention, including:
in step S410, when the state of charge of the battery is less than the electric quantity calibration value, the vehicle navigation system is used to estimate the mountain road gradient.
And step S420, judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
Step S430, when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching the mountain mode.
Compared with the third embodiment, the fourth embodiment includes step S450 and step S460, and other steps are the same as those of the third embodiment, and will not be described again.
And step S440, when the mountain road gradient is smaller than or equal to the mountain road gradient calibration value and the driving distance is greater than the ramp length calibration value, exiting the mountain land mode.
In this embodiment, when the mountain road gradient is less than or equal to the mountain road gradient calibration value and the travel distance is greater than the ramp length calibration value, for example, the hybrid vehicle travels the current ramp according to the mountain mode, and when the subsequent road is flat or slow, that is, the mountain road gradient is less than or equal to the mountain road gradient calibration value, the hybrid vehicle exits the mountain mode, thereby exerting the advantages of energy saving and emission reduction of the hybrid vehicle to the maximum extent and increasing the energy utilization rate.
The invention also provides a device comprising a memory, a processor and a program stored in the memory and operable on the processor for adapting the mountain road conditions of the hybrid vehicle, which when executed by the processor, implements the steps of the method for adapting the mountain road conditions of the hybrid vehicle as described above.
The invention also provides a computer readable storage medium, characterized in that the computer readable storage medium stores a program for the hybrid vehicle to adapt to the mountain road conditions, and the program for the hybrid vehicle to adapt to the mountain road conditions realizes the steps of the method for the hybrid vehicle to adapt to the mountain road conditions when being executed by a processor.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A method for adapting a hybrid vehicle to a mountain road condition, the method comprising the steps of:
when the state of charge of the battery is smaller than an electric quantity calibration value, judging whether the slope of the mountain road is larger than the slope calibration value or not;
when the mountain road gradient is greater than the gradient calibration value and the ramp length is greater than the ramp length calibration value, automatically switching a mountain mode;
and after the mountain mode is automatically switched, when the mountain road gradient is smaller than or equal to the mountain road gradient calibration value and the driving distance is greater than the ramp length calibration value, exiting the mountain mode.
2. The method for adaptive mountain road operation of hybrid vehicle as claimed in claim 1, wherein said judging whether the mountain road gradient is greater than the gradient calibration value comprises:
estimating the mountain road gradient by using a vehicle dynamics equation;
and judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
3. The method for adapting a hybrid vehicle to a mountain road condition of claim 2, wherein the vehicle dynamics equation is:
T q /R＝m*g*(f 1 +f 2 *u+f 3 *u 2 )+C D *A*u 2 /21.25+δ*m*a+m*g*sinα
wherein:
T q total driving torque of the vehicle;
r, the radius of the wheel;
m, vehicle mass;
g, a gravitational constant;
f 1 、f 2 、f 3 a rolling resistance coefficient related to speed;
u, vehicle speed;
C D wind resistance coefficient;
a, the windward resistance area of the vehicle;
delta, the conversion coefficient of the rotating mass of the automobile;
a, vehicle acceleration;
α, ramp angle.
4. The method for adaptive mountain road operation of hybrid vehicle as claimed in claim 1, wherein said judging whether the mountain road gradient is greater than the gradient calibration value comprises:
estimating the mountain road gradient by using a vehicle navigation system; the vehicle-mounted navigation system comprises a geographic information system and a global positioning system;
and judging whether the value of the mountain road gradient obtained through estimation is larger than a gradient calibration value.
5. The method for adaptive mountain road conditions of a hybrid vehicle as set forth in claim 4, wherein estimating mountain road gradient using the vehicle navigation system comprises:
acquiring a driving destination selected on the vehicle-mounted navigation system;
determining a driving path according to the driving destination, and judging whether mountain road conditions exist on the driving path;
when mountain road conditions exist on the driving path, determining a target sampling point;
acquiring a vehicle position in real time through the global positioning system receiver;
calculating the road surface driving distance between the current position of the vehicle and the target sampling point;
map matching is carried out by utilizing a geographic information system, and the altitude of the target sampling point and the altitude of the current position of the vehicle are obtained;
and calculating the mountain road gradient through a mountain road gradient value calculation formula.
6. The method for adaptive mountain road conditions of hybrid vehicle as set forth in claim 5, wherein the mountain road gradient value calculation formula is:
wherein i is a mountain road gradient value; e (E) 2 The elevation of the road surface of the target sampling point is obtained; e (E) 1 The elevation of the road surface at the current position of the vehicle is obtained; l is the running distance between the current position of the vehicle and the road surface of the vehicle at the target sampling point.
7. The method for adapting a hybrid vehicle to a mountain road condition of claim 6, wherein the ramp length is the road surface travel distance.
8. An apparatus comprising a memory, a processor, and a program stored in the memory and operable on the processor for adapting a hybrid vehicle to a mountain road condition, the program for adapting a hybrid vehicle to a mountain road condition when executed by the processor performing the steps of the method for adapting a hybrid vehicle to a mountain road condition as claimed in any one of claims 1-7.
9. A computer readable storage medium, characterized in that it stores a program for hybrid vehicle adaptation of the mountain road conditions, which when executed by a processor implements the steps of the method for hybrid vehicle adaptation of the mountain road conditions according to any one of claims 1-7.
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