CN107856670A - A kind of optimal control Rules extraction method of planetary hybrid power system - Google Patents
A kind of optimal control Rules extraction method of planetary hybrid power system Download PDFInfo
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- CN107856670A CN107856670A CN201711079082.3A CN201711079082A CN107856670A CN 107856670 A CN107856670 A CN 107856670A CN 201711079082 A CN201711079082 A CN 201711079082A CN 107856670 A CN107856670 A CN 107856670A
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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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
- B60K6/00—Arrangement or mounting of plural diverse prime-movers for mutual or common propulsion, e.g. hybrid propulsion systems comprising electric motors and internal combustion engines ; Control systems therefor, i.e. systems controlling two or more prime movers, or controlling one of these prime movers and any of the transmission, drive or drive units Informative references: mechanical gearings with secondary electric drive F16H3/72; arrangements for handling mechanical energy structurally associated with the dynamo-electric machine H02K7/00; machines comprising structurally interrelated motor and generator parts H02K51/00; dynamo-electric machines not otherwise provided for in H02K see H02K99/00
- B60K6/20—Arrangement or mounting of plural diverse prime-movers for mutual or common propulsion, e.g. hybrid propulsion systems comprising electric motors and internal combustion engines ; Control systems therefor, i.e. systems controlling two or more prime movers, or controlling one of these prime movers and any of the transmission, drive or drive units Informative references: mechanical gearings with secondary electric drive F16H3/72; arrangements for handling mechanical energy structurally associated with the dynamo-electric machine H02K7/00; machines comprising structurally interrelated motor and generator parts H02K51/00; dynamo-electric machines not otherwise provided for in H02K see H02K99/00 the prime-movers consisting of electric motors and internal combustion engines, e.g. HEVs
- B60K6/42—Arrangement or mounting of plural diverse prime-movers for mutual or common propulsion, e.g. hybrid propulsion systems comprising electric motors and internal combustion engines ; Control systems therefor, i.e. systems controlling two or more prime movers, or controlling one of these prime movers and any of the transmission, drive or drive units Informative references: mechanical gearings with secondary electric drive F16H3/72; arrangements for handling mechanical energy structurally associated with the dynamo-electric machine H02K7/00; machines comprising structurally interrelated motor and generator parts H02K51/00; dynamo-electric machines not otherwise provided for in H02K see H02K99/00 the prime-movers consisting of electric motors and internal combustion engines, e.g. HEVs characterised by the architecture of the hybrid electric vehicle
- B60K6/44—Series-parallel type
- B60K6/445—Differential gearing distribution type
-
- 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
- B60W40/10—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 vehicle motion
- B60W40/105—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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
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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 present invention provides a kind of optimal control Rules extraction method of planetary hybrid power system, belong to hybrid vehicle control technology field, pattern switching Rule Extraction including electric-only mode and hybrid mode, and under hybrid mode, the determination of each power source working condition allocation rule.The optimal control Rules extraction method, by the way that optimum results are applied into On-line Control strategy in the form of controlling rule, reduce computing cost, improve the real-time of control strategy, in addition, experience of this method independent of engineering staff, implementation can be automated and eliminate substantial amounts of nominal time and energy, foundation is provided for Automatic optimization and calibration.
Description
Technical field
The present invention relates to a kind of optimal control Rules extraction method of planetary hybrid power system, belong to hybrid power vapour
The control field of car.
Background technology
In face of energy shortage and the present situation of environmental pollution getting worse, consider the mileage anxiety problem of pure electric automobile, mix
It is still vehicle energy saving in middle or short term, the important channel of emission reduction to close power vehicle.In various hybrid power system configurations, planet
Formula hybrid power system has two motors and a set of planetary gear coupling mechanism, can realize engine using buncher
Rotating speed decouples, and using adjusting torsion motor to realize, the moment of torsion of engine decouples, that is, realizes the bilingual coupling of rotating speed, moment of torsion of engine, easily
In the optimum control for realizing engine, there is energy-saving potential the most prominent.However, when planetary hybrid power system is operated in
During engine optimum state, the electrical power flow in system can reduce the overall efficiency of the system, based on this, to give full play to planet
The energy-saving potential of formula hybrid power system, it is still very necessary to carry out optimal control to it.The optimization control of present hybrid system
Method processed includes online real-time optimal control, and extracts control rule based on optimum results and then realize vehicle air-conditioning two
Class.The former is limited to the computing cost of optimized algorithm and the calculation processing power of current real vehicle controller, is still difficult to actual answer
With；Optimal control rule is only applied to on-line controller by the latter, obtains approximate optimal solution, has preferable real-time and application
Condition, however, the more experiences based on researcher or engineering staff of current optimal control method extraction process, are not yet formed
The automation principle of optimality extracting method of system.
The content of the invention
It is an object of the invention to provide one kind to be applied to On-line Control strategy by optimum results, have computing cost it is low,
The characteristics of control strategy real-time is good, and can effectively solve current similar optimal control Rules extraction method and be unfavorable for automation in fact
The optimal control Rules extraction method of the planetary hybrid power system of problem is applied, its technology contents is：
The first step, extract the pattern switching rule of electric-only mode and hybrid mode：Based under typical travel operating mode
Carry out the obtained planetary hybrid power system power source working condition of global optimization with speed and system requirements change in torque
As a result, the pattern switching rule of electric-only mode and hybrid mode is extracted, specifically included：
Step 1.1：Under speed, system requirements moment of torsion coordinate, to the electric-only mode in global optimization result and mixing
Dynamic mode operating point is counted, and obtains the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode；
Step 1.2：Eliminating system demand torque is more than Tev1, and hybrid mode work when speed is higher than Vev1
Point, in remaining hybrid mode operating point, statistics obtains the minimum system requirements moment of torsion of hybrid mode operating point
Tevt1 and minimum vehicle velocity V evt1；
Step 1.3：Eliminating system demand torque is less than Tevt1, and electric-only mode work when speed is less than Vevt1
Point；
Step 1.4：Outlier detection is carried out to remaining electric-only mode operating point after step 1.2 processing, when pure electronic
When detecting outlier in pattern operating point, outlier, and return to step 1.1 are rejected, statistics obtains remaining electric-only mode work
Make the maximum system demand torque Tev2 and max. speed Vev2 in point, eliminating system demand torque is more than Tev2, and speed
Hybrid mode operating point during higher than Vev2；When being not detected by outlier in electric-only mode operating point, into step
1.5；
Described outlier detection algorithm can be distance-based outlier point detection algorithm, the outlier inspection based on density
Method of determining and calculating and the outlier detection algorithm based on cluster, it is therefore preferable to：A kind of outlier detection method based on minimum range, first
Each point and the minimum range nearby put are calculated, recycles Xiao Weile methods to find out the larger point of minimum range deviation, as peeling off
Point；
Step 1.5：Outlier detection is carried out to remaining hybrid mode operating point after step 1.3 processing, works as mixing
When detecting outlier in dynamic mode operating point, outlier, and return to step 1.2 are rejected, statistics obtains remaining hybrid power
Minimum system requirements torque T evt2 and minimum vehicle velocity V evt2 in pattern operating point, eliminating system demand torque are less than Tevt2,
And electric-only mode operating point of speed when being less than Vevt2；When being not detected by outlier in hybrid mode operating point,
Into step 1.6；
Step 1.6：For the electric-only mode operating point after step 1.4 and step 1.5 processing and hybrid mode work
Make a little, to find the external boundary point of two-mode, the external boundary point of electric-only mode is fitted, obtains electric-only mode to mixing
The curve Cev of dynamic mode switching, is fitted to the external boundary point of hybrid mode, obtains hybrid mode to pure electricity
The curve Cevt of dynamic pattern switching；
The external boundary point methods of described searching electric-only mode are, first the system requirements to electric-only mode operating point
Moment of torsion and speed are normalized, and then electric-only mode operating point are segmented with Vn distance on speed coordinate, pin
To every one piece of data, the envelope point Bevi that system requirements moment of torsion is maximum in external envelope point is found, then find speed and be more than or equal to
Bevi points correspond to speed and system requirements moment of torsion is more than the envelope point that Bevi point correspondence system demand torques subtract Tn, are designated as pure
The external boundary point that electric model switches to hybrid mode；Wherein, Vn and Tn is calibration value, and its scope is (0,1)；
The external boundary point methods of described searching hybrid mode are, first the system to hybrid mode operating point
Demand torque and speed are normalized, and then hybrid mode operating point is divided with Vm distance on speed coordinate
Section, for every one piece of data, the envelope point Bevti that system requirements moment of torsion is minimum in external envelope point is found, then find speed and be less than
Speed is corresponded to equal to Bevti points and system requirements moment of torsion is less than envelope point of the Bevti point correspondence systems demand torque plus Tm,
It is designated as the external boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm are calibration value, its scope be (0,
1)；
Second step, under hybrid mode, the determination of each power source working condition allocation rule, specifically include：
Step 2.1：Based on the speed in global optimization result, system demand power, battery charge state to hybrid power
Engine demand power under pattern carries out nonlinear fitting：Engine demand power is expressed as speed (v), system requirements work(
Rate (Preq) regression equation between battery charge state (SOC)：
Pe=β0+β1·v+β2·Preq+β3·SOC
Wherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3Be expressed as respectively on speed, system demand power,
The nonlinear curve of battery charge state, using least square method to four coefficients respectively with 12 kinds of situations of three variable changes
Nonlinear fitting is carried out respectively, the maximum fitting result of coefficient correlation is found out, as final engine demand power nonlinear
Expression formula；
Step 2.2：Based on two electric efficiencies of planetary hybrid power system with motor demand torque and rotation speed change
Working characteristics, the efficiency of two motors is expressed as piecewise polynomial function：Efficiency (the η of No.1 motorg,l) in small moment of torsion be with
The function of demand torque change, in high pulling torque for the function of rotation speed change：
Wherein, TgFor No.1 motor demand torque, ωgIt is global based on carrying out under typical travel operating mode for No.1 motor speed
Optimize obtained No.1 electric efficiency with system requirements moment of torsion and the distribution results of rotation speed change operating point, it is excellent using genetic algorithm
Change moment of torsion threshold value (Tg,t), optimized using least square method and complete polynomial function fgt(Tg) and fgω(ωg) fitting；
Efficiency (the η of No. two motorsm,l) in low speed to be as demand is turned round in high speed with the function of rotation speed change
The function of square change：
Wherein TmFor No. two motor demand torques, ωmIt is global based on carrying out under typical travel operating mode for No. two motor speeds
Optimize No. two obtained electric efficiencies with system requirements moment of torsion and the distribution results of rotation speed change operating point, it is excellent using genetic algorithm
Change rotation speed threshold values (ωm,t), optimized using least square method and complete polynomial function fmt(Tm) and fmω(ωm) fitting；
Step 2.3：It is optimal for target with system overall efficiency, engine demand power expression based on step 2.1 and
No.1 motor that step 2.2 obtains, No. two electric efficiency expression formulas, being obtained using genetic Optimization Algorithm utilizes engine power
The engine speed of efficiency optimization, moment of torsion；
Step 2.4：Engine speed, moment of torsion based on step 2.3 determination, using system requirements moment of torsion, speed as target, root
According to the kinetics relation of planetary hybrid power system, rotating speed, the moment of torsion of No.1 motor and No. two motors is calculated.
The present invention compared with prior art, has the beneficial effect that：
(1) the optimal control Rules extraction method of planetary hybrid power system of the present invention, compared to current work
The scaling method commonly used in journey, eliminates substantial amounts of nominal time and energy；
(2) the optimal control Rules extraction method of planetary hybrid power system of the present invention, compared to current
On-line optimizing and controlling method, optimum results are applied to On-line Control strategy in the form of controlling rule, computing cost is low, has
Good real-time；
(3) the optimal control Rules extraction method of planetary hybrid power system of the present invention, compared to existing
Control role extracting method, independent of the experience of engineering staff, implementation can be automated, being provided for Automatic optimization and calibration can
Can property.
Brief description of the drawings
Fig. 1 is the planetary mixed power system structure schematic diagram of the embodiment of the present invention.
Fig. 2 is that the embodiment of the present invention extracts planetary hybrid power system optimal control Rules extraction method flow chart.
Fig. 3 is that the electric-only mode of the planetary hybrid power system of the embodiment of the present invention and the pattern of hybrid mode are cut
Change Rule Extraction result schematic diagram.
Embodiment
The invention will be further described below in conjunction with the accompanying drawings：
A kind of optimal control Rules extraction method of planetary hybrid vehicle, based on a kind of planetary hybrid power system
System, as shown in figure 1, including engine, No.1 motor MG1, inverter, electrokinetic cell, No. two motor MG2, preceding planet row PG1,
Planet row PG2 and system output shaft afterwards；
The right-hand member of engine output shaft is connected with the left end of preceding planet row PG1 planet carriers, and No.1 motor MG1 empty sets are being started
Machine output shaft left end, No.1 motor MG1 right-hand member are connected with preceding planet row PG1 left end, the right-hand member of preceding planet row PG1 gear rings with
The left end connection of planet row PG2 planet carriers afterwards, No. two motor MG2 empty sets are on the right-hand member of system output shaft, a No. two motor MG2 left side
End is connected with the right-hand member of rear planet row PG2 sun gears, and the right-hand member of rear planet row PG2 planet carriers and the left end of system output shaft connect
Connect；
No.1 motor MG1, No. two motor MG2 are connected by three-phase high-voltage cable with inverter respectively, and inverter passes through two
Bar high-tension cable is connected with high-voltage energy storage device.
A kind of optimal control Rules extraction method of planetary hybrid vehicle of the present invention, as shown in Fig. 2 its
It is characterised by：
The first step, extract the pattern switching rule of electric-only mode and hybrid mode：Based under typical travel operating mode
Carry out the obtained planetary hybrid power system power source working condition of global optimization with speed and system requirements change in torque
As a result, the pattern switching rule of electric-only mode and hybrid mode is extracted, specifically included：
Step 1.1：Under speed, system requirements moment of torsion coordinate, to the electric-only mode in global optimization result and mixing
Dynamic mode operating point is counted, and obtains the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode；
Step 1.2：Eliminating system demand torque is more than Tev1, and hybrid mode work when speed is higher than Vev1
Point, in remaining hybrid mode operating point, statistics obtains the minimum system requirements moment of torsion of hybrid mode operating point
Tevt1 and minimum vehicle velocity V evt1；
Step 1.3：Eliminating system demand torque is less than Tevt1, and electric-only mode work when speed is less than Vevt1
Point；
Step 1.4：Outlier detection is carried out to remaining electric-only mode operating point after step 1.2 processing, when pure electronic
When detecting outlier in pattern operating point, outlier, and return to step 1.1 are rejected, statistics obtains remaining electric-only mode work
Make the maximum system demand torque Tev2 and max. speed Vev2 in point, eliminating system demand torque is more than Tev2, and speed
Hybrid mode operating point during higher than Vev2；When being not detected by outlier in electric-only mode operating point, into step
1.5；
Described outlier detection algorithm can be distance-based outlier point detection algorithm, the outlier inspection based on density
Method of determining and calculating and the outlier detection algorithm based on cluster, it is therefore preferable to：A kind of outlier detection method based on minimum range, first
Each point and the minimum range nearby put are calculated, recycles Xiao Weile methods to find out the larger point of minimum range deviation, as peeling off
Point；
Step 1.5：Outlier detection is carried out to remaining hybrid mode operating point after step 1.3 processing, works as mixing
When detecting outlier in dynamic mode operating point, outlier, and return to step 1.2 are rejected, statistics obtains remaining hybrid power
Minimum system requirements torque T evt2 and minimum vehicle velocity V evt2 in pattern operating point, eliminating system demand torque are less than Tevt2,
And electric-only mode operating point of speed when being less than Vevt2；When being not detected by outlier in hybrid mode operating point,
Into step 1.6；
In the case where step 1.4 and step 1.5 all detect outlier, when system requirements moment of torsion be less than Tevt1 and
Speed is less than Vev1, and either system requirements moment of torsion is less than Tevt2 and speed is less than Vev2 or system requirements moment of torsion is less than
Tev2 and speed are less than Vevt2, or system requirements moment of torsion is less than Tev1 and when speed is less than Vevt1, and system is operated in
Under electric-only mode；When system requirements moment of torsion is more than Tevt1, or system requirements moment of torsion is more than Tevt2 and speed is more than
Vevt1, either system requirements moment of torsion be more than Tevt1 and speed and be more than Vev2 or when system requirements moment of torsion is more than Tevt1,
System is operated in hybrid mode；When system requirements moment of torsion is more than Tevt2 and is less than Tev2, and speed more than Vevt2 and
During less than Vev2, if system is currently operating in electric-only mode, only when the system requirements moment of torsion under current vehicle speed is corresponding more than Cev
During system requirements moment of torsion under speed, system enters hybrid mode, if system is currently operating under hybrid mode, only
When the system requirements moment of torsion under current vehicle speed corresponds to the system requirements moment of torsion under speed less than Cevt, system enters pure electronic mould
Formula；
Step 1.6：For the electric-only mode operating point after step 1.4 and step 1.5 processing and hybrid mode work
Make a little, to find the external boundary point of two-mode, the external boundary point of electric-only mode is fitted, obtains electric-only mode to mixing
The curve Cev of dynamic mode switching, is fitted to the external boundary point of hybrid mode, obtains hybrid mode to pure electricity
The curve Cevt of dynamic pattern switching；
The external boundary point methods of described searching electric-only mode are, first the system requirements to electric-only mode operating point
Moment of torsion and speed are normalized, and then electric-only mode operating point are segmented with Vn distance on speed coordinate, pin
To every one piece of data, the envelope point Bevi that system requirements moment of torsion is maximum in external envelope point is found, then find speed and be more than or equal to
Bevi points correspond to speed and system requirements moment of torsion is more than the envelope point that Bevi point correspondence system demand torques subtract Tn, are designated as pure
The external boundary point that electric model switches to hybrid mode；Wherein, Vn and Tn is calibration value, and its scope is (0,1)；
The external boundary point methods of described searching hybrid mode are, first the system to hybrid mode operating point
Demand torque and speed are normalized, and then hybrid mode operating point is divided with Vm distance on speed coordinate
Section, for every one piece of data, the envelope point Bevti that system requirements moment of torsion is minimum in external envelope point is found, then find speed and be less than
Speed is corresponded to equal to Bevti points and system requirements moment of torsion is less than envelope point of the Bevti point correspondence systems demand torque plus Tm,
It is designated as the external boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm are calibration value, its scope be (0,
1)；
After above-mentioned steps, the electric-only mode of planetary hybrid power system and the pattern of hybrid mode are obtained
Switching law extracts result schematic diagram, as shown in Figure 3.
Second step, under hybrid mode, the determination of each power source working condition allocation rule, specifically include：
Step 2.1：Based on the speed in global optimization result, system demand power, battery charge state to hybrid power
Engine demand power under pattern carries out nonlinear fitting：Engine demand power is expressed as speed (v), system requirements work(
Rate (Preq) regression equation between battery charge state (SOC)：
Pe=β0+β1·v+β2·Preq+β3·SOC
Wherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3Be expressed as respectively on speed, system demand power,
The nonlinear curve of battery charge state, using least square method to four coefficients respectively with 12 kinds of situations of three variable changes
Nonlinear fitting is carried out respectively, is found out the maximum fitting result of coefficient correlation, finally, is obtained engine demand power nonlinear table
It is up to formula：
Pe=3.56+0.16v+0.98Preq+612·(SOC-SOCf)
Wherein, SOCfTo consider the aims of systems SOC of electric quantity balancing；
Step 2.2：Based on two electric efficiencies of planetary hybrid power system with motor demand torque and rotation speed change
Working characteristics, the efficiency of two motors is expressed as piecewise polynomial function：Efficiency (the η of No.1 motorg,l) in small moment of torsion be with
The function of demand torque change, in high pulling torque for the function of rotation speed change：
Wherein, TgFor No.1 motor demand torque, ωgIt is global based on carrying out under typical travel operating mode for No.1 motor speed
Optimize obtained No.1 electric efficiency with system requirements moment of torsion and the distribution results of rotation speed change operating point, it is excellent using genetic algorithm
Change moment of torsion threshold value (Tg,t), optimized using least square method and complete polynomial function fgt(Tg) and fgω(ωg) fitting；
Efficiency (the η of No. two motorsm,l) in low speed to be as demand is turned round in high speed with the function of rotation speed change
The function of square change：
Wherein TmFor No. two motor demand torques, ωmIt is global based on carrying out under typical travel operating mode for No. two motor speeds
Optimize No. two obtained electric efficiencies with system requirements moment of torsion and the distribution results of rotation speed change operating point, it is excellent using genetic algorithm
Change rotation speed threshold values (ωm,t), optimized using least square method and complete polynomial function fmt(Tm) and fmω(ωm) fitting；
Step 2.3：It is optimal for target with system overall efficiency, engine demand power expression based on step 2.1 and
No.1 motor that step 2.2 obtains, No. two electric efficiency expression formulas, being obtained using genetic Optimization Algorithm utilizes engine power
The engine speed of efficiency optimization, moment of torsion；Wherein, system overall efficiency is the product of engine efficiency and transmission efficiency, is started
Engine efficiency (ηe) it is on its fuel consumption (be) expression formula, fuel consumption (be) Engine Universal Characteristics profit can be based on
Obtained with engine speed, moment of torsion interpolation；Wherein, transmission efficiency refers to the ratio of system output power and engine output
Value, system output power are the mechanical output sum in the power of battery (it is negative to be charged as just, discharging) and system output shaft, by
The influence of gearratio and two electric efficiencies；
Step 2.4：Engine speed, moment of torsion based on step 2.3 determination, using system requirements moment of torsion, speed as target, root
According to the kinetics relation of planetary hybrid power system, rotating speed, the moment of torsion of No.1 motor and No. two motors is calculated.
Claims (2)
- A kind of 1. optimal control Rules extraction method of planetary hybrid power system, it is characterised in that：The first step, extract the pattern switching rule of electric-only mode and hybrid mode：Based on carrying out under typical travel operating mode The planetary hybrid power system power source working condition that global optimization obtains with speed and the result of system requirements change in torque, The pattern switching rule of electric-only mode and hybrid mode is extracted, specifically included：Step 1.1：Under speed, system requirements moment of torsion coordinate, to the electric-only mode and hybrid power in global optimization result Pattern operating point is counted, and obtains the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode；Step 1.2：Eliminating system demand torque is more than Tev1, and hybrid mode operating point when speed is higher than Vev1, In remaining hybrid mode operating point, statistics obtains the minimum system requirements moment of torsion of hybrid mode operating point Tevt1 and minimum vehicle velocity V evt1；Step 1.3：Eliminating system demand torque is less than Tevt1, and electric-only mode operating point when speed is less than Vevt1；Step 1.4：Outlier detection is carried out to remaining electric-only mode operating point after step 1.2 processing, works as electric-only mode When outlier is detected in operating point, outlier, and return to step 1.1 are rejected, statistics obtains remaining electric-only mode operating point In maximum system demand torque Tev2 and max. speed Vev2, eliminating system demand torque is more than Tev2, and speed is higher than Hybrid mode operating point during Vev2；When being not detected by outlier in electric-only mode operating point, into step 1.5；Step 1.5：Outlier detection is carried out to remaining hybrid mode operating point after step 1.3 processing, works as hybrid power When detecting outlier in pattern operating point, outlier, and return to step 1.2 are rejected, statistics obtains remaining hybrid mode Minimum system requirements torque T evt2 and minimum vehicle velocity V evt2 in operating point, eliminating system demand torque are less than Tevt2, and Speed is less than electric-only mode operating point during Vevt2；When being not detected by outlier in hybrid mode operating point, enter Step 1.6；Step 1.6：Electric-only mode operating point and hybrid mode operating point after being handled for step 1.4 and step 1.5, The external boundary point of two-mode is found, the external boundary point of electric-only mode is fitted, obtains electric-only mode to hybrid power The curve Cev of pattern switching, the external boundary point of hybrid mode is fitted, obtains hybrid mode to pure electronic mould The curve Cevt of formula switching；The external boundary point methods of described searching electric-only mode are, first the system requirements moment of torsion to electric-only mode operating point It is normalized, then electric-only mode operating point is segmented with Vn distance on speed coordinate, for every with speed One piece of data, the envelope point Bevi that system requirements moment of torsion is maximum in external envelope point is found, then find speed and be more than or equal to Bevi points Corresponding speed and system requirements moment of torsion are more than the envelope point that Bevi point correspondence system demand torques subtract Tn, are designated as pure electronic mould The external boundary point that formula switches to hybrid mode；Wherein, Vn and Tn is calibration value, and its scope is (0,1)；The external boundary point methods of described searching hybrid mode are, first the system requirements to hybrid mode operating point Moment of torsion and speed are normalized, and then hybrid mode operating point is segmented with Vm distance on speed coordinate, For every one piece of data, the envelope point Bevti that system requirements moment of torsion is minimum in external envelope point is found, then find speed and be less than or equal to Bevti points correspond to speed and system requirements moment of torsion is less than the envelope point that Bevti point correspondence systems demand torque adds Tm, are designated as The external boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm is calibration value, and its scope is (0,1)；Second step, under hybrid mode, the determination of each power source working condition allocation rule, specifically include：Step 2.1：Based on the speed in global optimization result, system demand power, battery charge state to hybrid mode Under engine demand power carry out nonlinear fitting：Engine demand power is expressed as speed (v), system demand power (Preq) regression equation between battery charge state (SOC)：Pe=β0+β1·v+β2·Preq+β3·SOCWherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3It is expressed as respectively on speed, system demand power, battery The nonlinear curve of state-of-charge, four coefficients are respectively distinguished with 12 kinds of situations of three variable changes using least square method Nonlinear fitting is carried out, the maximum fitting result of coefficient correlation is found out, is expressed as final engine demand power nonlinear Formula；Step 2.2：Work based on two electric efficiencies of planetary hybrid power system with motor demand torque and rotation speed change Characteristic, the efficiency of two motors is expressed as piecewise polynomial function：Efficiency (the η of No.1 motorg,l) in small moment of torsion be with need The function of change in torque is sought, in high pulling torque for the function of rotation speed change：<mrow> <msub> <mi>&eta;</mi> <mrow> <mi>g</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>f</mi> <mrow> <mi>g</mi> <mi>t</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mi>g</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <mo>|</mo> <msub> <mi>T</mi> <mi>g</mi> </msub> <mo>|</mo> <mo><</mo> <msub> <mi>T</mi> <mrow> <mi>g</mi> <mo>,</mo> <mi>t</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>f</mi> <mrow> <mi>g</mi> <mi>&omega;</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>&omega;</mi> <mi>g</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <mo>|</mo> <msub> <mi>T</mi> <mi>g</mi> </msub> <mo>|</mo> <mo>&GreaterEqual;</mo> <msub> <mi>T</mi> <mrow> <mi>g</mi> <mo>,</mo> <mi>t</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>Wherein, TgFor No.1 motor demand torque, ωgFor No.1 motor speed, based on carrying out global optimization under typical travel operating mode Obtained No.1 electric efficiency is turned round with system requirements moment of torsion and the distribution results of rotation speed change operating point using genetic algorithm optimization Square threshold value (Tg,t), optimized using least square method and complete polynomial function fgt(Tg) and fgω(ωg) fitting；Efficiency (the η of No. two motorsm,l) in low speed to be as demand torque becomes in high speed with the function of rotation speed change The function of change：<mrow> <msub> <mi>&eta;</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>f</mi> <mrow> <mi>m</mi> <mi>t</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <msub> <mi>&omega;</mi> <mi>m</mi> </msub> <mo>&GreaterEqual;</mo> <msub> <mi>&omega;</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>t</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>f</mi> <mrow> <mi>m</mi> <mi>&omega;</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>&omega;</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <msub> <mi>&omega;</mi> <mi>m</mi> </msub> <mo><</mo> <msub> <mi>&omega;</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>t</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>Wherein TmFor No. two motor demand torques, ωmFor No. two motor speeds, based on carrying out global optimization under typical travel operating mode No. two obtained electric efficiencies are turned with system requirements moment of torsion and the distribution results of rotation speed change operating point using genetic algorithm optimization Fast threshold value (ωm,t), optimized using least square method and complete polynomial function fmt(Tm) and fmω(ωm) fitting；Step 2.3：It is optimal for target with system overall efficiency, engine demand power expression and step based on step 2.1 2.2 obtained No.1 motors, No. two electric efficiency expression formulas, being obtained using genetic Optimization Algorithm makes engine power utilization ratio Optimal engine speed, moment of torsion；Step 2.4：Engine speed, moment of torsion based on step 2.3 determination, using system requirements moment of torsion, speed as target, according to row The kinetics relation of planetary hybrid power system, rotating speed, the moment of torsion of No.1 motor and No. two motors is calculated.
- 2. a kind of optimal control Rules extraction method of planetary hybrid power system according to claim 1, its feature It is：Described outlier detection algorithm can be distance-based outlier point detection algorithm, the outlier detection based on density Algorithm and the outlier detection algorithm based on cluster, it is therefore preferable to：A kind of outlier detection method based on minimum range, is first counted Each point and the minimum range nearby put are calculated, recycles Xiao Weile methods to find out the larger point of minimum range deviation, as outlier.
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