CN107856670B - 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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- 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
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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
- B60W40/10—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
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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
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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 to On-line Control strategy in the form of controlling rule, reduce operation cost, improve the real-time of control strategy, furthermore, experience of this method independent of engineering staff can automate implementation and eliminate a large amount of nominal time and energy, provide foundation for Automatic optimization and calibration.
Description
Technical field
The present invention relates to a kind of optimal control Rules extraction methods of planetary hybrid power system, belong to hybrid power vapour
The control field of vehicle.
Background technique
The status got worse in face of energy shortage and environmental pollution considers the mileage anxiety problem of pure electric automobile, mixes
Close the important channel that power vehicle is still vehicle energy saving in middle or short term, emission reduction.In various hybrid power system configurations, planet
There are two motor and a set of planetary gear coupling mechanisms for formula hybrid power system tool, can realize engine using speed regulating motor
Revolving speed decoupling realizes the bilingual coupling of revolving speed, torque of engine, easily using the torque decoupling turned round motor and realize engine is adjusted
In the optimum control for realizing engine, there is energy-saving potential the most outstanding.However, when the work of planetary hybrid power system exists
When engine optimum state, the electrical power flow in system can reduce the overall efficiency of the system, this is based on, to give full play to planet
It is still very necessary to carry out optimal control to it for the energy-saving potential of formula hybrid power system.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 operation cost of optimization algorithm and the calculation processing power of current real vehicle controller, is still difficult to actually 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 current optimal control method extraction process mostly experience based on researcher or engineering staff, not yet forms
The automation principle of optimality extracting method of system.
Summary of the invention
The object of the present invention is to provide one kind optimum results can be applied to On-line Control strategy, at low cost with operation,
The good feature of control strategy real-time, and can effectively solve current similar optimal control Rules extraction method and be unfavorable for automation in fact
Apply the optimal control Rules extraction method of the planetary hybrid power system of problem, technology contents are as follows:
The first step extracts the pattern switching rule of electric-only mode and hybrid mode: based under typical travel operating condition
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, being extracted to the pattern switching rule of electric-only mode and hybrid mode, specifically include:
Step 1.1: under speed, system requirements torque coordinate, in global optimization result electric-only mode and mixing
Dynamic mode operating point is counted, and the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode are obtained；
Step 1.2: eliminating system demand torque is greater than the hybrid mode work of Tev1 and speed higher than Vev1 when
Point, in remaining hybrid mode operating point, statistics obtains the minimum system requirements torque of hybrid mode operating point
Tevt1 and minimum vehicle velocity V evt1；
Step 1.3: eliminating system demand torque is less than the electric-only mode work of Tevt1 and speed lower than Vevt1 when
Point；
Step 1.4: outlier detection being carried out to remaining electric-only mode operating point after step 1.2 processing, works as pure electric vehicle
When detecting outlier in mode operating point, outlier, and return 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 greater than Tev2 and speed
Hybrid mode operating point when higher than Vev2；When outlier is not detected in electric-only mode operating point, enter step
1.5；
The outlier detection algorithm can be distance-based outlier point detection algorithm, the outlier inspection based on density
Method of determining and calculating and 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, Xiao Weile method is recycled to find out the biggish point of minimum range deviation, as peeling off
Point；
Step 1.5: outlier detection being 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 step 1.2 are rejected, statistics obtains remaining hybrid power
Minimum system requirements torque T evt2 and minimum vehicle velocity V evt2 in mode operating point, eliminating system demand torque are less than Tevt2,
And speed be lower than Vevt2 when electric-only mode operating point；When outlier is not detected in hybrid mode operating point,
Enter step 1.6；
Step 1.6: for step 1.4 and step 1.5 treated electric-only mode operating point and hybrid mode work
Make the outer boundary point for a little finding two-mode, the outer boundary point of electric-only mode is fitted, obtains electric-only mode to mixing
The curve Cev of dynamic mode switching, is fitted the outer boundary point of hybrid mode, obtains hybrid mode Xiang Chun electricity
The curve Cevt of dynamic pattern switching；
The outer boundary point methods of the searching electric-only mode are, first the system requirements to electric-only mode operating point
Torque and speed are normalized, and are then segmented with the distance of Vn to electric-only mode operating point on speed coordinate, needle
To every one piece of data, the maximum envelope point Bevi of system requirements torque in external envelope point is found, then find speed and be more than or equal to
Bevi point corresponds to speed and system requirements torque is greater than the envelope point that Bevi point correspondence system demand torque subtracts Tn, is denoted as pure
The outer boundary point that electric model switches to hybrid mode；Wherein, Vn and Tn is calibration value, and range is (0,1)；
The outer boundary point methods of the searching hybrid mode are, first the system to hybrid mode operating point
Demand torque and speed are normalized, and are then divided with the distance of Vm hybrid mode operating point on speed coordinate
Section, for every one piece of data, finds the smallest envelope point Bevti of system requirements torque in external envelope point, then find speed and be less than
Speed is corresponded to equal to Bevti point and system requirements torque is less than the envelope point that Bevti point correspondence system demand torque adds Tm,
It is denoted as the outer boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm are calibration value, range be (0,
1)；
Second step, under hybrid mode, the determination of each power source working condition allocation rule is specifically included:
Step 2.1: based in global optimization result speed, system demand power, battery charge state is to hybrid power
Engine demand power under mode carries out nonlinear fitting: engine demand power is expressed as speed (v), system requirements function
Rate (Preq) and battery charge state (SOC) between regression equation:
Pe=β0+β1·v+β2·Preq+β3·SOC
Wherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3Be expressed as respectively about 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, finds out the maximum fitting result of related coefficient, 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
The efficiency of two motors is expressed as piecewise polynomial function by working characteristics: the efficiency (η of No.1 motorg,l) in small torque for
Demand torque variation function, in large 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 condition for No.1 motor speed
Optimize obtained No.1 electric efficiency with the distribution results of system requirements torque and rotation speed change operating point, it is excellent using genetic algorithm
Change torque threshold value (Tg,t), optimized using least square method and completes polynomial function fgt(Tg) and fgω(ωg) fitting；
Efficiency (the η of No. two motorsm,l) in low speed for the function of rotation speed change, turned round in high speed with demand
The function of square variation:
Wherein TmFor No. two motor demand torques, ωmIt is global based on carrying out under typical travel operating condition for No. two motor speeds
Optimize obtained No. two electric efficiencies with the distribution results of system requirements torque and rotation speed change operating point, it is excellent using genetic algorithm
Change rotation speed threshold values (ωm,t), optimized using least square method and completes 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 utilize engine power using genetic Optimization Algorithm acquisition
The engine speed of efficiency optimization, torque；
Step 2.4: based on the determining engine speed of step 2.3, torque, using system requirements torque, speed as target, root
According to the kinetics relation of planetary hybrid power system, revolving speed, the torque of No.1 motor and No. two motors is calculated.
Compared with prior art, the present invention having the beneficial effect that:
(1) the optimal control Rules extraction method of planetary hybrid power system of the present invention, compared to current work
Common scaling method in journey, eliminates a large amount of nominal time and energy；
(2) the optimal control Rules extraction method of planetary hybrid power system of the present invention, compared to current
Optimum results are applied to On-line Control strategy in the form for controlling rule by on-line optimizing and controlling method, and operation is at low cost, 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 can automate implementation, providing for Automatic optimization and calibration can independent of the experience of engineering staff
It can property.
Detailed description of the invention
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 mode of hybrid mode are cut
Change Rule Extraction result schematic diagram.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings:
A kind of optimal control Rules extraction method of planetary hybrid vehicle is based on a kind of planetary hybrid power system
System, as shown in Figure 1, include engine, No.1 motor MG1, inverter, power battery, No. two motor MG2, preceding planet row PG1,
Planet row PG2 and system output shaft afterwards；
The right end of engine output shaft is connect with the left end of preceding planet row PG1 planet carrier, and No.1 motor MG1 empty set is being started
Machine output shaft left end, the right end of No.1 motor MG1 are connect with the left end of preceding planet row PG1, the right end of preceding planet row PG1 gear ring with
The left end connection of planet row PG2 planet carrier afterwards, right end of No. two motor MG2 empty sets in system output shaft, a left side of No. two motor MG2
End is connect with the right end of rear planet row PG2 sun gear, and the right end of rear planet row PG2 planet carrier and the left end of system output shaft connect
It connects；
No.1 motor MG1, No. two motor MG2 pass through three-phase high-voltage cable respectively and connect with inverter, and inverter passes through two
High-tension cable is connect 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 characterized in that:
The first step extracts the pattern switching rule of electric-only mode and hybrid mode: based under typical travel operating condition
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, being extracted to the pattern switching rule of electric-only mode and hybrid mode, specifically include:
Step 1.1: under speed, system requirements torque coordinate, in global optimization result electric-only mode and mixing
Dynamic mode operating point is counted, and the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode are obtained；
Step 1.2: eliminating system demand torque is greater than the hybrid mode work of Tev1 and speed higher than Vev1 when
Point, in remaining hybrid mode operating point, statistics obtains the minimum system requirements torque of hybrid mode operating point
Tevt1 and minimum vehicle velocity V evt1；
Step 1.3: eliminating system demand torque is less than the electric-only mode work of Tevt1 and speed lower than Vevt1 when
Point；
Step 1.4: outlier detection being carried out to remaining electric-only mode operating point after step 1.2 processing, works as pure electric vehicle
When detecting outlier in mode operating point, outlier, and return 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 greater than Tev2 and speed
Hybrid mode operating point when higher than Vev2；When outlier is not detected in electric-only mode operating point, enter step
1.5；
The outlier detection algorithm can be distance-based outlier point detection algorithm, the outlier inspection based on density
Method of determining and calculating and 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, Xiao Weile method is recycled to find out the biggish point of minimum range deviation, as peeling off
Point；
Step 1.5: outlier detection being 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 step 1.2 are rejected, statistics obtains remaining hybrid power
Minimum system requirements torque T evt2 and minimum vehicle velocity V evt2 in mode operating point, eliminating system demand torque are less than Tevt2,
And speed be lower than Vevt2 when electric-only mode operating point；When outlier is not detected in hybrid mode operating point,
Enter step 1.6；
In the case where step 1.4 and step 1.5 all detect outlier, when system requirements torque be less than Tevt1 and
Speed is less than Vev1, and perhaps system requirements torque is less than Tevt2 and speed is less than Vev2 or system requirements torque is less than
When Tev2 and speed are less than Vevt2 or system requirements torque is less than Tev1 and speed is less than Vevt1, system work exists
Under electric-only mode；When system requirements torque is greater than Tevt1 or system requirements torque is greater than Tevt2 and speed is greater than
Perhaps system requirements torque is greater than Tevt1 to Vevt1 and speed is greater than Vev2 or when system requirements torque is greater than Tevt1,
System works in hybrid mode；When system requirements torque be greater than Tevt2 and be less than Tev2, and speed be greater than Vevt2 and
It is only corresponding greater than Cev when the system requirements torque under current vehicle speed if system is currently operating in electric-only mode when less than Vev2
When system requirements torque under speed, system enters hybrid mode, if system is currently operating under hybrid mode, only
When the system requirements torque under current vehicle speed, which is less than Cevt, corresponds to the system requirements torque under speed, system enters pure electric vehicle mould
Formula；
Step 1.6: for step 1.4 and step 1.5 treated electric-only mode operating point and hybrid mode work
Make the outer boundary point for a little finding two-mode, the outer boundary point of electric-only mode is fitted, obtains electric-only mode to mixing
The curve Cev of dynamic mode switching, is fitted the outer boundary point of hybrid mode, obtains hybrid mode Xiang Chun electricity
The curve Cevt of dynamic pattern switching；
The outer boundary point methods of the searching electric-only mode are, first the system requirements to electric-only mode operating point
Torque and speed are normalized, and are then segmented with the distance of Vn to electric-only mode operating point on speed coordinate, needle
To every one piece of data, the maximum envelope point Bevi of system requirements torque in external envelope point is found, then find speed and be more than or equal to
Bevi point corresponds to speed and system requirements torque is greater than the envelope point that Bevi point correspondence system demand torque subtracts Tn, is denoted as pure
The outer boundary point that electric model switches to hybrid mode；Wherein, Vn and Tn is calibration value, and range is (0,1)；
The outer boundary point methods of the searching hybrid mode are, first the system to hybrid mode operating point
Demand torque and speed are normalized, and are then divided with the distance of Vm hybrid mode operating point on speed coordinate
Section, for every one piece of data, finds the smallest envelope point Bevti of system requirements torque in external envelope point, then find speed and be less than
Speed is corresponded to equal to Bevti point and system requirements torque is less than the envelope point that Bevti point correspondence system demand torque adds Tm,
It is denoted as the outer boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm are calibration value, range be (0,
1)；
After above-mentioned steps, the electric-only mode of planetary hybrid power system and the mode 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 is specifically included:
Step 2.1: based in global optimization result speed, system demand power, battery charge state is to hybrid power
Engine demand power under mode carries out nonlinear fitting: engine demand power is expressed as speed (v), system requirements function
Rate (Preq) and battery charge state (SOC) between regression equation:
Pe=β0+β1·v+β2·Preq+β3·SOC
Wherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3Be expressed as respectively about 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, finds out the maximum fitting result of related coefficient, finally, obtains engine demand power nonlinear table
Up to formula are as follows:
Pe=3.56+0.16v+0.98Preq+612·(SOC-SOCf)
Wherein, SOCfFor the aims of systems SOC for considering electric quantity balancing；
Step 2.2: based on two electric efficiencies of planetary hybrid power system with motor demand torque and rotation speed change
The efficiency of two motors is expressed as piecewise polynomial function by working characteristics: the efficiency (η of No.1 motorg,l) in small torque for
Demand torque variation function, in large 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 condition for No.1 motor speed
Optimize obtained No.1 electric efficiency with the distribution results of system requirements torque and rotation speed change operating point, it is excellent using genetic algorithm
Change torque threshold value (Tg,t), optimized using least square method and completes polynomial function fgt(Tg) and fgω(ωg) fitting；
Efficiency (the η of No. two motorsm,l) in low speed for the function of rotation speed change, turned round in high speed with demand
The function of square variation:
Wherein TmFor No. two motor demand torques, ωmIt is global based on carrying out under typical travel operating condition for No. two motor speeds
Optimize obtained No. two electric efficiencies with the distribution results of system requirements torque and rotation speed change operating point, it is excellent using genetic algorithm
Change rotation speed threshold values (ωm,t), optimized using least square method and completes 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 utilize engine power using genetic Optimization Algorithm acquisition
The engine speed of efficiency optimization, torque；Wherein, system overall efficiency is the product of engine efficiency and transmission efficiency, is started
Engine efficiency (ηe) it is about its fuel consumption rate (be) expression formula, fuel consumption rate (be) can be based on Engine Universal Characteristics benefit
It is obtained with engine speed, torque interpolation；Wherein, transmission efficiency refers to the ratio of system output power and engine output
Value, system output power are the sum of the mechanical output on the power of battery (charging is positive, and electric discharge is negative) and system output shaft, by
The influence of transmission ratio and two electric efficiencies；
Step 2.4: based on the determining engine speed of step 2.3, torque, using system requirements torque, speed as target, root
According to the kinetics relation of planetary hybrid power system, revolving speed, the torque of No.1 motor and No. two motors is calculated.
Claims (3)
1. a kind of optimal control Rules extraction method of planetary hybrid power system, it is characterised in that:
The first step extracts the pattern switching rule of electric-only mode and hybrid mode: based on carrying out under typical travel operating condition
The planetary hybrid power system power source working condition that global optimization obtains with speed and system requirements change in torque as a result,
The pattern switching rule of electric-only mode and hybrid mode is extracted, is specifically included:
Step 1.1: under speed, system requirements torque coordinate, to the electric-only mode and hybrid power in global optimization result
Mode operating point is counted, and the maximum system demand torque Tev1 and max. speed Vev1 under electric-only mode are obtained；
Step 1.2: eliminating system demand torque is greater than the hybrid mode operating point of Tev1 and speed higher than Vev1 when,
In remaining hybrid mode operating point, statistics obtains the minimum system requirements torque of hybrid mode operating point
Tevt1 and minimum vehicle velocity V evt1；
Step 1.3: eliminating system demand torque is less than the electric-only mode operating point of Tevt1 and speed lower than Vevt1 when；
Step 1.4: outlier detection being carried out to remaining electric-only mode operating point after step 1.2 processing, works as electric-only mode
When detecting outlier in operating point, outlier, and return 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 greater than Tev2 and speed and is higher than
Hybrid mode operating point when Vev2；When outlier is not detected in electric-only mode operating point, 1.5 are entered step；
Step 1.5: outlier detection being carried out to remaining hybrid mode operating point after step 1.3 processing, works as hybrid power
When detecting outlier in mode operating point, outlier, and return 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 lower than electric-only mode operating point when Vevt2；When outlier is not detected in hybrid mode operating point, enter
Step 1.6；
Step 1.6: for step 1.4 and step 1.5 treated electric-only mode operating point and hybrid mode operating point,
The outer boundary point for finding two-mode, is fitted the outer boundary point of electric-only mode, obtains electric-only mode to hybrid power
The curve Cev of pattern switching is fitted the outer boundary point of hybrid mode, obtains hybrid mode to pure electric vehicle mould
The curve Cevt of formula switching；
The outer boundary point methods of the searching electric-only mode are, first the system requirements torque to electric-only mode operating point
It is normalized, then electric-only mode operating point is segmented with the distance of Vn on speed coordinate, for every with speed
One piece of data finds the maximum envelope point Bevi of system requirements torque in external envelope point, then finds speed more than or equal to Bevi point
Corresponding speed and system requirements torque are greater than the envelope point that Bevi point correspondence system demand torque subtracts Tn, are denoted as pure electric vehicle mould
The outer boundary point that formula switches to hybrid mode；Wherein, Vn and Tn is calibration value, and range is (0,1)；
The outer boundary point methods of the searching hybrid mode are, first the system requirements to hybrid mode operating point
Torque and speed are normalized, and are then segmented with the distance of Vm to hybrid mode operating point on speed coordinate,
For every one piece of data, the smallest envelope point Bevti of system requirements torque in external envelope point is found, then find speed and be less than or equal to
Bevti point corresponds to speed and system requirements torque is less than the envelope point that Bevti point correspondence system demand torque adds Tm, is denoted as
The outer boundary point that hybrid mode switches to electric-only mode；Wherein, Vm and Tm is calibration value, and range is (0,1)；
Second step, under hybrid mode, the determination of each power source working condition allocation rule is specifically included:
Step 2.1: based in global optimization result speed, system demand power, battery charge state is 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·SOC
Wherein β0、β1、β2、β3For each term coefficient, by β0、β1、β2、β3It is expressed as respectively about speed, system demand power, battery
The nonlinear curve of state-of-charge respectively distinguishes four coefficients using least square method with 12 kinds of situations of three variable changes
Nonlinear fitting is carried out, the maximum fitting result of related coefficient is found out, is expressed as final engine demand power nonlinear
Formula；
Step 2.2: based on two electric efficiencies of planetary hybrid power system with the work of motor demand torque and rotation speed change
The efficiency of two motors is expressed as piecewise polynomial function: the efficiency eta of No.1 motor by characteristicg,lIn small torque for demand
The function of change in torque, in large torque for the function of rotation speed change:
Wherein, TgFor No.1 motor demand torque, ωgFor No.1 motor speed, based on carrying out global optimization under typical travel operating condition
Obtained No.1 electric efficiency is turned round with the distribution results of system requirements torque and rotation speed change operating point using genetic algorithm optimization
Square threshold Tg,t, optimized using least square method and complete polynomial function fgt(Tg) and fgω(ωg) fitting；
The efficiency eta of No. two motorsm,lIn low speed for the function of rotation speed change, change in high speed with demand torque
Function:
Wherein TmFor No. two motor demand torques, ωmFor No. two motor speeds, based on carrying out global optimization under typical travel operating condition
No. two obtained electric efficiencies are turned with the distribution results of system requirements torque and 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:, engine demand power expression and step based on step 2.1 optimal for target with system overall efficiency
2.2 obtain No.1 motor, No. two electric efficiency expression formulas, using genetic Optimization Algorithm acquisition make engine power utilization efficiency
Optimal engine speed, torque；
Step 2.4: based on the determining engine speed of step 2.3, torque, using system requirements torque, speed as target, according to row
Revolving speed, the torque of No.1 motor and No. two motors is calculated in the kinetics relation of planetary hybrid power system.
2. a kind of optimal control Rules extraction method of planetary hybrid power system according to claim 1, feature
Be: the outlier detection algorithm is distance-based outlier point detection algorithm, the outlier detection algorithm based on density
Or the outlier detection algorithm based on cluster.
3. a kind of optimal control Rules extraction method of planetary hybrid power system according to claim 1 or 2, special
Sign is: the outlier detection algorithm be a kind of outlier detection method based on minimum range, first calculate each point with it is attached
The minimum range of near point recycles Xiao Weile method to find out the biggish point of minimum range deviation, as outlier.
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| CN110435635B (en) * | 2019-08-30 | 2020-08-14 | 吉林大学 | Mode switching coordination control method for planetary hybrid system with wet clutch |
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