CN104129318B - A kind of Electric Vehicles Driving Cycle optimization method and device - Google Patents

Abstract

The present invention is applicable to electric vehicle engineering field, a kind of Electric Vehicles Driving Cycle optimization method and device are provided, and described method comprises: present speed information and maximum speed information and the minimum speed information of described vehicle in estimation range of obtaining vehicle; According to described present speed information, maximum speed information and minimum speed information, obtain the optimum acceleration information of described vehicle in described estimation range, and the optimum acceleration information in described estimation range obtains the optimal velocity information of described vehicle in described estimation range according to described vehicle; Described optimal velocity information is fed back to the driver of described vehicle, so that described driver adjusts the present speed of described vehicle according to described optimal velocity information, in realizing Electric Vehicles Driving Cycle optimization, reduce electric automobile energy consumption, shorten computing time.

Description

A kind of Electric Vehicles Driving Cycle optimization method and device

Technical field

The invention belongs to electric vehicle engineering field, relate in particular to a kind of Electric Vehicles Driving Cycle optimization methodAnd device.

Background technology

Automobile running working condition optimization problem is that automobile energy consumes minimized problem simultaneously. At origin and orderThe given situation in ground under, the driving path of vehicle depend on the surrounding that driver recognizes traffic,The information such as road conditions and vehicle-state, and different drivers' driving path difference to some extent, thus leadCause different vehicle energy consumption. Driver's recognition capability and identification range are all limited, if can predictThe information such as traffic and road conditions of vehicle front, and specify the happy festival time according to these information to driverCan drive path, this will have very large meaning to the energy-saving driving of automobile. At present, to global positioning system(GlobalPositioningSystem, GPS) and intelligent transportation system (IntelligentTransportSystem, ITS) etc. the research of technology very active. These technology can be applicable to predict vehicle front appointmentRoad condition information in scope, thereby according to the optimum drive road in the above-mentioned specified scope of these information searchesFootpath also offers driver's reference.

But the main purpose of automobile running working condition optimization is to subtract by online adjustment of the speed of a motor vehicle in adjustable extentThe total energy that few vehicle consumes, and current GPS and ITS also cannot provide the specifying informations such as the real-time speed of a motor vehicle.In addition, also there is the optimization that the theory of optimal control has been applied to automobile running working condition in prior art, utilizesThe traffic information predicting is also optimized driving cycle according to the target of minimum energy consumption. ButBecause computing time is long, be also not suitable for directly applying to actual vehicle.

Summary of the invention

The object of the embodiment of the present invention is to provide a kind of Electric Vehicles Driving Cycle optimization method and device, withIn realizing Electric Vehicles Driving Cycle optimization, reduce electric automobile energy consumption, and shorten while calculatingBetween.

The embodiment of the present invention is achieved in that a kind of Electric Vehicles Driving Cycle optimization method, described methodComprise:

Obtain maximum speed information in estimation range of the present speed information of vehicle and described vehicle andLittle velocity information;

According to described present speed information, maximum speed information and minimum speed information, obtain described vehicle and existOptimum acceleration information in described estimation range, and according to described vehicle the optimum in described estimation rangeAcceleration information obtains the optimal velocity information of described vehicle in described estimation range;

Described optimal velocity information is fed back to the driver of described vehicle, so that described driver is according to instituteState optimal velocity information and adjust the present speed of described vehicle.

Another object of the embodiment of the present invention is to provide a kind of Electric Vehicles Driving Cycle optimization device, described inDevice comprises:

Initial velocity acquiring unit, is predicting model for the present speed information and the described vehicle that obtain vehicleMaximum speed information and minimum speed information in enclosing;

Optimal velocity acquiring unit, for fast according to described present speed information, maximum speed information and minimumDegree information, obtains the optimum acceleration information of described vehicle in described estimation range, and according to described vehicleOptimum acceleration information in described estimation range obtains the optimum speed of described vehicle in described estimation rangeDegree information;

Optimal velocity feedback unit, for described optimal velocity information being fed back to the driver of described vehicle,So that described driver adjusts the present speed of described vehicle according to described optimal velocity information.

The beneficial effect that the embodiment of the present invention compared with prior art exists is: the embodiment of the present invention is by obtainingThe present speed information of vehicle and described vehicle maximum speed information and the minimum speed letter in estimation rangeBreath, according to described present speed information, maximum speed information and minimum speed information, obtains described vehicle and existsOptimum acceleration information in described estimation range, and according to described vehicle the optimum in described estimation rangeAcceleration information obtains the optimal velocity information of described vehicle in described estimation range, by described optimal velocityInformation feeds back to the driver of described vehicle, so that described driver is real-time according to described optimal velocity informationAdjust the present speed of described vehicle, reduce electric automobile energy consumption. Compared with prior art, the present inventionEmbodiment realizes simply, efficient, do not need to provide detailed traffic information in described estimation range, onlyMaximum speed information and minimum speed information in described estimation range need be provided, thereby can effectively alleviate GPSWith the burden of ITS, shorten computing time, be applicable to being applied to actual electric automobile, have stronger easy-to-useProperty and practicality.

Brief description of the drawings

In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, below will be to embodiment or existing skillIn art description, the accompanying drawing of required use is briefly described, and apparently, the accompanying drawing in the following describes onlyBe only some embodiments of the present invention, for those of ordinary skill in the art, do not paying creative laborUnder the prerequisite of moving property, can also obtain according to these accompanying drawings other accompanying drawing.

Fig. 1 is the composition structural representation of the electric automobile that provides of the embodiment of the present invention one;

Fig. 2 is the frame structure signal of the Electric Vehicles Driving Cycle optimization device that provides of the embodiment of the present invention oneFigure;

Fig. 3 is the schematic diagram that the Electric Vehicles Driving Cycle that provides of the embodiment of the present invention one is optimized;

Fig. 4 is the realization flow figure of the Electric Vehicles Driving Cycle optimization method that provides of the embodiment of the present invention two;

Fig. 5 is the composition structure chart of the Electric Vehicles Driving Cycle optimization device that provides of the embodiment of the present invention three.

Detailed description of the invention

In below describing, in order to illustrate instead of in order limiting, to have proposed such as particular system structure, technologyAnd so on detail, understand the embodiment of the present invention to thoroughly cut. But those skilled in the art shouldClear, in other embodiment that there is no these details, also can realize the present invention. In other situation,Omit the detailed description to well-known system, device, circuit and method, in order to avoid unnecessary detailsHinder description of the invention.

For technical solutions according to the invention are described, describe below by specific embodiment.

Embodiment mono-:

Fig. 1 shows the composition structure of the electric automobile that the embodiment of the present invention one provides, for convenience of explanation,Only show the part relevant to the present embodiment.

As shown in Figure 1, described electric automobile comprises battery, DCAC converter, motor and car body.

The power source of described electric automobile is energy-storage system (such as battery, super capacitor etc.). DCAC turnsThe direct current of energy-storage system is changed into interchange by parallel operation. Motor converts electric energy to mechanical energy (as motor turnsSpeed value ω_m, motor torque T_m) to drive car body. It should be noted that, electric automobile in the process of movingHave two kinds of mode of operations: one is drive pattern, the electric energy of energy-storage system converts machinery to by motorCan be delivered to car body, thereby drive car body; Another kind is take-back model, and the mechanical energy of car body is by electronicMachine converts electric energy to, and energy-storage system is charged. The Electric Vehicles Driving Cycle that the present invention proposes is optimizedTarget is by processing the information of obtaining from the external world and calculate the optimum speed of a motor vehicle in the vehicle speed range allowing, fromAnd that the energy that makes energy-storage system in the whole driving process of vehicle consumes is minimum.

The composition structure of the electric automobile based on shown in Fig. 1, the present embodiment also provides a kind of electric automobile capableSail the framework architecture of operation optimization device, for convenience of explanation, only show the part relevant to the present embodiment.

As shown in Figure 2, described Electric Vehicles Driving Cycle optimization device comprises entire car controller. Optionally,Described device also comprises GPS module, ITS module and vehicle speed sensor.

In the present embodiment, entire car controller 1 obtains vehicle in prediction from GPS module 2 and ITS module 3Maximum speed information in scope and minimum speed information, and obtain the current speed of vehicle from vehicle speed sensor 4Degree information. Entire car controller 1, according to the described information of obtaining, calculates vehicle in institute by the theory of optimal controlState the optimum acceleration information in estimation range, and the optimum in described estimation range adds according to described vehicleVelocity information obtains the optimal velocity information of described vehicle in described estimation range, by described optimal velocity letterBreath feeds back to the driver of described vehicle, so that described driver adjusts institute according to described optimal velocity informationState the present speed of vehicle, realize the optimization (as shown in Figure 3) of Electric Vehicles Driving Cycle.

It should be noted that, frame structure, only for explaining the present invention, is not limited to this described in Fig. 2Bright protection domain.

Embodiment bis-:

Fig. 4 shows the realization stream of the Electric Vehicles Driving Cycle optimization method that the embodiment of the present invention two providesJourney, details are as follows for the method process:

In step S401, obtain the present speed information of vehicle and described vehicle in estimation rangeLarge velocity information and minimum speed information.

Concrete can be that entire car controller obtains vehicle in estimation range from GPS module and ITS moduleMaximum speed information and minimum speed information, and obtain the present speed information of vehicle from vehicle speed sensor.

Wherein, described estimation range is the segment distance (as the L in Fig. 3) that vehicle will travel future. GPSModule and ITS module provide in real time vehicle in following one section of operating range (being described estimation range)The information of large velocity information and minimum speed, vehicle speed sensor provides the present speed information of vehicle in real time.

In step S402, according to described present speed information, maximum speed information and minimum speed information,Obtain the optimum acceleration information of described vehicle in described estimation range, and according to described vehicle described pre-Optimum acceleration information within the scope of survey obtains the optimal velocity information of described vehicle in described estimation range.

In the present embodiment, entire car controller is according to present speed information, maximum speed information and minimum speedInformation, calculates the optimum acceleration information of vehicle in described estimation range by the theory of optimal control, and rootOptimum acceleration information according to described vehicle in described estimation range obtains described vehicle in described estimation rangeInterior optimal velocity information.

Specific as follows:

Situation taking battery as energy-storage system describes as example. In the driving cycle optimal control of electric automobileIn problem, the dynamic characteristic equation that the state equation of control system is vehicle is as follows:

$\stackrel{\·}{v_{\mathrm{veh}}}=a_{\mathrm{veh}}---\left(1\right)$

Wherein, the speed v that the state variable of control system is vehicle_veh, the acceleration a that control variables is vehicle_veh，Represent v_vehFirst derivative.

The control target of this control problem is minimizing of energy content of battery consumption, therefore, performance index function asUnder:

$J={\∫}_0^N{P}_{\mathrm{bat},\mathrm{inn}}\mathrm{dt}---\left(2\right)$

Wherein, N is the time while finishing corresponding to the estimation range L of Fig. 3, P_bat,innFor inside battery occursPower considered the power of inside battery loss. P_bat,innWith battery terminal power P_bat,terThere is following passSystem:

P_bat,inn＝P_bat,ter+I²·R(3)

Wherein, the electric current that I is battery, the internal resistance that R is battery. In electric automobile, battery terminal power P_bat,terDepend on car speed v_vehAnd acceleration a_veh, the electric current I of battery and battery terminal power P_bat,terRelevant, because ofThis, can say P_bat,innAlso depend on v_vehAnd a_veh。

The concrete control target of this control problem is in 0 to N scope, to calculate the optimum acceleration of vehicleTrack also makes vehicle that the track of corresponding optimal velocity occur. Vehicle travels and can make electricity according to optimal velocity trackThe power consumption in pond reaches minimum of a value. This control problem simultaneously need to 0 to meet in the time range of N withLower constraints:

v_min(t)≤v_veh(t)≤v_max(t)

a_min(t)≤a_veh(t)≤a_max(t)(4)

${\∫}_0^N{v}_{\mathrm{veh}}\left(t\right)\mathrm{dt}=L$

Wherein, v_min，v_max, L is the information of obtaining from GPS module and ITS module, a_minAnd a (t)_max(t) rootAccording to described v_veh(t)、v_minAnd v (t+1)_max(t+1) determine v_veh(t) represent the speed of described vehicle in the time of time point t.

According to principle of minimum, when Hamilton function H is defined as when following:

H(v_veh(t),a_veh(t),p(t))＝P_bat,inn(v_veh(t),a_veh(t))+p(t)·a_veh(t),(5)

The optimal solution of above-mentioned control problem can draw by following necessary condition:

$\stackrel{\·}{{v_{\mathrm{veh}}}^{*}}\left(t\right)=\frac{\∂H}{\∂p}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right),p^{*}\left(t\right))={a_{\mathrm{veh}}}^{*}\left(t\right)$

$\stackrel{\·}{p^{*}}\left(t\right)=-\frac{\∂H}{\∂v_{\mathrm{veh}}}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right),p^{*}\left(t\right))=-\frac{\∂P_{\mathrm{bat},\mathrm{inn}}}{\∂v_{\mathrm{veh}}}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right))---\left(6\right)$

H(v_veh ^*(t),a_veh ^*(t),p^*(t))≤H(v_veh ^*(t),a_veh(t),p^*(t))

Wherein, p is Lagrange multiplier, is also common state variate-value, p^*Represent that optimum common state becomesValue. In above-mentioned necessary condition, the system state equation that first necessary condition is above-mentioned control problem, withTime be also the one constraint of this control problem; Second necessary condition provides the condition that p need to be satisfied; The 3rdIndividual necessary condition provides chooses optimum control variable a_vehCondition, the optimum control variable in a certain moment beAll permissible vehicle acceleration a of this moment_veh(at a_minAnd a_maxIn scope and meet the acceleration energy of vehicleThe vehicle acceleration of power) make a of Hamilton function H minimum in value_vehValue. Above-mentioned three necessary conditions are realIn time, provides, and is therefore instantaneous optimization. These three necessary conditions need to arrive in the scope of N 0 omnidistance satisfied,Make to calculate the optimum acceleration of vehicle and optimal velocity, thereby realize Electric Vehicles Driving Cycle optimization.

In addition, in step S402, also need the initial value of given common state variable, i.e. described prediction modelEnclose the common state variate-value of originating point.

The present embodiment obtains common state variable initial value and comprises:

To P_bat,inn(v_veh,a_veh) and a_vehCarry out the big or small initial range that obtains more afterwards common state variate-value;

Based on described initial range, obtain common state variable initial value by Computer Simulation.

Illustrate as follows: work as P_bat,inn(v_veh,a_veh) numerical value is 10000, a_vehNumerical value is 5 o'clock, through size ratio, the initial range of common state variate-value is defined as four figures (10000/5=2000, as 1000～9999);Described four figures is carried out to emulation and finally obtain common state variable initial value, by full in described initial rangeThe 3rd constraints (v in foot formula (4)_veh(t) relevant to p) common state variate-value as described commonWith state variable initial value.

After obtaining common state variable initial value, arrive in the scope of N, according to second of formula (6) 0Individual necessary condition is controlled described common state variable.

It should be noted that, common state variable initial value can obtain in advance described in the present embodiment, is kept atIn entire car controller.

In step S403, described optimal velocity information is fed back to the driver of described vehicle, so that instituteState driver adjusts described vehicle present speed according to described optimal velocity information.

It should be noted that, the present embodiment is to arrive 0 according to the optimum acceleration of the theoretical calculating of instantaneous optimization vehicleIn the scope of N, be also interior realization of an estimation range of GPS module and ITS module. But, realityTraffic changes at any time. In the time that vehicle really travels in described estimation range, friendship aroundPath condition may not with before prediction identical. In order to address this problem, the present embodiment is by described optimal velocityWhen information feeds back to the driver of described vehicle, also further comprise:

According to predetermined time interval or predetermined operating range upgrade described optimal velocity information, and will be moreDescribed optimal velocity information after new feeds back to the driver of described vehicle.

Further, the described driver that described optimal velocity information is fed back to described vehicle specifically comprises:

Described in the mode showing with chart and/or the mode of voice message feed back to described optimal velocity informationThe driver of vehicle.

Further, described in the present embodiment, vehicle can also be adjusted automatically according to calculating the described optimal velocity obtainingWhole current vehicle speed. Therefore described in the embodiment of the present invention, scheme is also particularly suitable for the situation of unmanned automatic driving.

The embodiment of the present invention provides a kind of Electric Vehicles Driving Cycle optimization side based on instantaneous optimization theoryCase. This scheme is by obtaining present speed information and the maximum speed of described vehicle in estimation range of vehicleDegree information and minimum speed information, according to described present speed information, maximum speed information and minimum speed letterBreath, obtain the optimum acceleration information of described vehicle in described estimation range, and according to described vehicle in instituteThe optimum acceleration information of stating in estimation range obtains the optimal velocity letter of described vehicle in described estimation rangeCease, described optimal velocity information is fed back to the driver of described vehicle, so that described driver is according to instituteState optimal velocity information and adjust in real time the present speed of described vehicle, thereby realizing Electric Vehicles Driving CycleWhen optimization, reduce electric automobile energy consumption. And it is described pre-that the embodiment of the present invention does not need to provideDetailed traffic information within the scope of survey, only need provide maximum speed information in described estimation range andLittle velocity information, thus the burden of GPS and ITS can effectively be alleviated, shorten computing time, be convenient to described sideThe realization of case, is applicable to being applied to actual electric automobile. In addition, the embodiment of the present invention is stated process in realizationIn do not need to increase extra hardware, can effectively reduce costs, there is stronger ease for use and practicality.

Embodiment tri-:

Fig. 5 shows the composition knot of the Electric Vehicles Driving Cycle optimization device that the embodiment of the present invention three providesStructure, for convenience of explanation, only shows the part relevant to the embodiment of the present invention.

This Electric Vehicles Driving Cycle optimization device specifically comprises:

Initial velocity acquiring unit 51, is predicting for the present speed information and the described vehicle that obtain vehicleMaximum speed information in scope and minimum speed information;

Optimal velocity acquiring unit 52, for according to described present speed information, maximum speed information and minimumVelocity information, obtains the optimum acceleration information of described vehicle in described estimation range, and according to described carOptimum acceleration information in described estimation range obtains the optimum of described vehicle in described estimation rangeVelocity information;

Optimal velocity feedback unit 53, for feeding back to described optimal velocity information the driving of described vehicleMember, so that described driver adjusts the present speed of described vehicle according to described optimal velocity information.

Further, described according to described present speed information, maximum speed information and minimum speed information,Obtain the optimum acceleration information of described vehicle in described estimation range, and according to described vehicle described pre-Optimum acceleration information within the scope of survey obtains the optimal velocity information of described vehicle in described estimation rangeRelational expression is:

$\stackrel{\·}{{v_{\mathrm{veh}}}^{*}}\left(t\right)=\frac{\∂H}{\∂p}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right),p^{*}\left(t\right))={a_{\mathrm{veh}}}^{*}\left(t\right)$ $\stackrel{\·}{p^{*}}\left(t\right)=-\frac{\∂H}{\∂v_{\mathrm{veh}}}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right),p^{*}\left(t\right))=-\frac{\∂P_{\mathrm{bat},\mathrm{inn}}}{\∂v_{\mathrm{veh}}}({v_{\mathrm{veh}}}^{*}\left(t\right),{a_{\mathrm{veh}}}^{*}\left(t\right))$

H(v_veh ^*(t),a_veh ^*(t),p^*(t))≤H(v_veh ^*(t),a_veh(t),p^*(t))

Wherein, H (v_veh(t),a_veh(t),p(t))＝P_bat,inn(v_veh(t),a_veh(t))+p(t)·a_veh(t), p represents common state variableValue, t represents the time point of Vehicle Driving Cycle, v_veh ^*Represent optimal velocity, a_veh ^*Represent optimum acceleration,v_min(t)≤v_veh(t)≤v_max(t)、a_min(t)≤a_veh(t)≤a_max(t)、v_minRepresent described minimum speedDegree, v_maxRepresent described maximal rate, v_veh(t) represent the speed of described vehicle in the time of time point t, a_minRepresentMinimum acceleration, a_maxRepresent peak acceleration, a_minAnd a (t)_max(t) according to described v_veh(t)、v_min(t+1) andv_max(t+1) determine, L represents described estimation range, and N represents the time that vehicle travels in described estimation range,P_bat,inn＝P_bat,ter+I²R, the electric current that I is battery, the internal resistance that R is battery, P_bat,terFor battery terminal power.

Further, described device also comprises:

Memory cell 54, for storing the common state variable initial value obtaining in advance.

Wherein, described in, obtaining common state variable initial value comprises:

To P_bat,inn(v_veh,a_veh) and a_vehCarry out the big or small initial range that obtains more afterwards common state variate-value, based onDescribed initial range, obtains common state variable initial value by Computer Simulation.

Further, described device also comprises:

Updating block 55, for according to predetermined time interval or predetermined operating range upgrade described optimumVelocity information, and the described optimal velocity information after upgrading is fed back to the driver of described vehicle.

Further, described optimal velocity feedback unit 53 specifically for:

Described in the mode showing with chart and/or the mode of voice message feed back to described optimal velocity informationThe driver of vehicle.

Those skilled in the art can be well understood to, for convenience of description and succinctly, only more thanThe division of stating each functional unit is illustrated, in practical application, and can be as required and by above-mentioned functionsDistribute and completed by different functional units, be divided into different functional units by the internal structure of described deviceOr module, to complete all or part of function described above. Each functional unit in embodiment can collectIn Cheng Yi processing unit, can be also that the independent physics of unit exists, also can two or two withUpper unit is integrated in a unit, and above-mentioned integrated unit both can adopt the form of hardware to realize, and also couldRealize with the form that adopts SFU software functional unit. In addition, the concrete title of each functional unit is also just for justIn mutual differentiation, be not limited to the application's protection domain. The specific works mistake of unit in said apparatusJourney, can, with reference to the corresponding process in preceding method embodiment, not repeat them here.

In sum, the embodiment of the present invention provides a kind of electric automobile during traveling work based on instantaneous optimization theoryCondition prioritization scheme. This scheme is obtained vehicle at prediction model by entire car controller from GPS module and ITS moduleEnclose interior maximum speed information and minimum speed information, and obtain the present speed letter of vehicle from vehicle speed sensorBreath, entire car controller, according to described present speed information, maximum speed information and minimum speed information, obtainsThe optimum acceleration information of described vehicle in described estimation range, and according to described vehicle at described prediction modelOptimum acceleration information in enclosing obtains the optimal velocity information of described vehicle in described estimation range, by instituteState the driver that optimal velocity information feeds back to described vehicle, so that described driver is according to described optimum speedDegree information is adjusted the present speed of described vehicle in real time, thereby is realizing the same of Electric Vehicles Driving Cycle optimizationTime, reduce electric automobile energy consumption. And the embodiment of the present invention does not need to provide in described estimation rangeDetailed traffic information, only need provide maximum speed information and minimum speed letter in described estimation rangeBreath, thus the burden of GPS and ITS can effectively be alleviated, shorten computing time, be convenient to the realization of described scheme,Be applicable to being applied to actual electric automobile. In addition, the embodiment of the present invention is stated in process in realization does not need to increaseAdd extra hardware, can effectively reduce costs, there is stronger ease for use and practicality.

In embodiment provided by the present invention, should be understood that disclosed apparatus and method, Ke YitongThe mode of crossing other realizes. For example, device embodiment described above is only schematically, for example,The division of described module or unit, is only that a kind of logic function is divided, and can have other when actual realizationDividing mode, for example multiple unit or assembly can in conjunction with or can be integrated into another system, or someFeature can be ignored, or does not carry out. Another point, shown or discussed coupling each other or directly couplingClose or communication to connect can be by some interfaces, device or the INDIRECT COUPLING of unit or communication connect, canElectrically, machinery or other form.

The described unit as separating component explanation can or can not be also physically to separate, asThe parts that unit shows can be or can not be also physical locations, can be positioned at a place, orAlso can be distributed on multiple NEs. Can select according to the actual needs wherein some or all ofThe object of the present embodiment scheme is realized in unit.

In addition, the each functional unit in each embodiment of the present invention can be integrated in a processing unit,Also can be that the independent physics of unit exists, also can be integrated in a unit in two or more unitIn. Above-mentioned integrated unit both can adopt the form of hardware to realize, and also can adopt SFU software functional unitForm realizes.

If described integrated unit using the form of SFU software functional unit realize and as production marketing independently orWhen use, can be stored in a computer read/write memory medium. Based on such understanding, the present inventionThe part that the technical scheme of embodiment contributes to prior art in essence in other words or this technical schemeAll or part of can embodying with the form of software product, this computer software product is stored in one and depositsIn storage media, comprise that some instructions are in order to make a computer equipment (can be personal computer, serveDevice, or the network equipment etc.) or processor (processor) execution each embodiment institute of the embodiment of the present inventionState all or part of step of method. And aforesaid storage medium comprises: USB flash disk, portable hard drive, read-only depositingReservoir (ROM, Read-OnlyMemory), random access memory (RAM, RandomAccessMemory), the various media that can be program code stored such as magnetic disc or CD.

The above embodiment only, in order to technical scheme of the present invention to be described, is not intended to limit; Although referencePrevious embodiment has been described in detail the present invention, and those of ordinary skill in the art is to be understood that: itsThe technical scheme that still can record aforementioned each embodiment is modified, or to part technology spy whereinLevy and be equal to replacement; And these amendments or replacement do not make the essence of appropriate technical solution depart from thisThe spirit and scope of the each embodiment technical scheme of bright embodiment.

Claims (10)

1. an Electric Vehicles Driving Cycle optimization method, is characterized in that, described method comprises:

Obtain present speed information and maximum speed information and the minimum speed information of described vehicle in estimation range of vehicle;

According to described present speed information, maximum speed information and minimum speed information, obtain the optimum acceleration information of described vehicle in described estimation range, and the optimum acceleration information in described estimation range obtains the optimal velocity information of described vehicle in described estimation range according to described vehicle;

Described optimal velocity information is fed back to the driver of described vehicle, so that described driver adjusts the present speed of described vehicle according to described optimal velocity information.

2. the method for claim 1, it is characterized in that, described according to described present speed information, maximum speed information and minimum speed information, obtain the optimum acceleration information of described vehicle in described estimation range, and the relational expression that the optimum acceleration information in described estimation range obtains the optimal velocity information of described vehicle in described estimation range according to described vehicle is:

Wherein,, p represents common state variate-value, t represents the time point of Vehicle Driving Cycle,Represent optimal velocity,Represent optimum acceleration,、、，Represent described minimum speed,Represent described maximal rate,Represent the speed of described vehicle in the time of time point t,Represent minimum acceleration,Represent peak acceleration,WithAccording to described、WithDetermine, L represents described estimation range, and N represents the time that vehicle travels in described estimation range,, the electric current that I is battery, the internal resistance that R is battery,For battery terminal power,For the power of inside battery generation,Represent、AndH during for optimum,Represent、For optimum butH while not being optimum.

3. the method for claim 1, is characterized in that, described method also comprises:

The common state variable initial value that storage is obtained in advance;

Wherein, described in, obtaining common state variable initial value comprises:

RightWithCarry out the big or small initial range that obtains more afterwards common state variate-value;

Based on described initial range, obtain common state variable initial value by Computer Simulation.

4. the method for claim 1, is characterized in that, described method also comprises:

According to predetermined time interval or predetermined operating range upgrade described optimal velocity information, and the described optimal velocity information after upgrading is fed back to the driver of described vehicle.

5. the method as described in claim 1 to 4 any one, is characterized in that, the described driver that described optimal velocity information is fed back to described vehicle comprises:

The mode showing with chart and/or the mode of voice message feed back to described optimal velocity information the driver of described vehicle.

6. an Electric Vehicles Driving Cycle optimization device, is characterized in that, described device comprises:

Initial velocity acquiring unit, for obtaining present speed information and maximum speed information and the minimum speed information of described vehicle in estimation range of vehicle;

Optimal velocity acquiring unit, be used for according to described present speed information, maximum speed information and minimum speed information, obtain the optimum acceleration information of described vehicle in described estimation range, and the optimum acceleration information in described estimation range obtains the optimal velocity information of described vehicle in described estimation range according to described vehicle;

Optimal velocity feedback unit, for described optimal velocity information being fed back to the driver of described vehicle, so that described driver adjusts the present speed of described vehicle according to described optimal velocity information.

7. device as claimed in claim 6, it is characterized in that, described according to described present speed information, maximum speed information and minimum speed information, obtain the optimum acceleration information of described vehicle in described estimation range, and the relational expression that the optimum acceleration information in described estimation range obtains the optimal velocity information of described vehicle in described estimation range according to described vehicle is:

Wherein,, p represents common state variate-value, t represents the time point of Vehicle Driving Cycle,Represent optimal velocity,Represent optimum acceleration,、、，Represent described minimum speed,Represent described maximal rate,Represent the speed of described vehicle in the time of time point t,Represent minimum acceleration,Represent peak acceleration,WithAccording to described、WithDetermine, L represents described estimation range, and N represents the time that vehicle travels in described estimation range,, the electric current that I is battery, the internal resistance that R is battery,For battery terminal power,For the power of inside battery generation,Represent、AndH during for optimum,Represent、For optimum butH while not being optimum.

8. device as claimed in claim 7, is characterized in that, described device also comprises:

Memory cell, for storing the common state variable initial value obtaining in advance.

9. device as claimed in claim 6, is characterized in that, described device also comprises:

Updating block, for according to predetermined time interval or predetermined operating range upgrade described optimal velocity information, and the described optimal velocity information after upgrading is fed back to the driver of described vehicle.

10. the device as described in claim 6 to 9 any one, is characterized in that, described optimal velocity feedback unit specifically for:

The mode showing with chart and/or the mode of voice message feed back to described optimal velocity information the driver of described vehicle.