CN109552110A - A kind of rule-based electric car energy composite energy management method with nonlinear prediction method - Google Patents
A kind of rule-based electric car energy composite energy management method with nonlinear prediction method Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
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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
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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Abstract
The invention discloses a kind of rule-based electric car energy composite energy management method with nonlinear prediction method, this method carries out energy management according to the power demand of each moment vehicle, lithium battery and super capacitor SOC situation.In Nonlinear Predictive Control Strategy, controller will predict the speed of the following some cycles, power is converted by running velocity power module, and pass through quadratic programming active set m ethod, using minimum power loss as the output electric current of index optimization lithium battery, the power distribution of lithium battery and super capacitor is completed.On the basis of this method power needed for meeting, it is possible to reduce the loss of system capacity reduces the use of lithium battery and extends the service life of lithium battery, and improves the efficiency of hybrid power system.
Description
Technical field
The present invention relates to a kind of rule-based electric automobile energy management methods with nonlinear prediction method.
Background technique
Current automobile height relies on the theme that non-renewable fuel does not meet global environment sustainable development.In order to solve to pass
The exhausted problem of air pollution and resource caused by system automobile, great attention of the research of electric car by people.For electricity
The energy-storage system of electrical automobile, lithium battery since the features such as its is light-weight, energy storage is big, power is big, pollution-free, is used widely, but
Exclusive use lithium battery may cause battery pack and overheat and shorten its service life.And super capacitor has the service life long and instantaneous power height
The advantages that, there is good booster action to cell power systems.In addition, the wide temperature range of super capacitor work, and can be with
Fully absorb the braking energy of automobile.So the hybrid power system that lithium battery is combined with super capacitor can satisfy electric car
Demand.Therefore, the characteristics of how efficiently playing lithium battery and super capacitor and advantage, optimizing distribution to the two energy is
The core and key of dynamical system energy management.
Summary of the invention
Present invention aim to address the energy assignment problems of electric automobile hybrid power system, and this paper presents one kind
The rule-based compound energy management method with nonlinear prediction method, this method according to the power demand of each moment vehicle,
Lithium battery and super capacitor SOC situation carry out energy management.In Nonlinear Predictive Control Strategy, controller will be predicted
The speed of the following some cycles is converted into power by running velocity power module, and by Novel Algorithm, with most
Small-power loss is the output electric current of index optimization lithium battery, completes the power distribution of lithium battery and super capacitor.Experimental result
Show that this method to avoid the frequent charge and discharge of battery pack and can extend service life of lithium battery, while reducing the loss of system capacity,
Improve the efficiency of hybrid power system.
The present invention it is specific the technical solution adopted is as follows:
A kind of rule-based electric car energy composite energy management method with nonlinear prediction method, in the recombination energy buret
In reason method, the energy management strategies based on nonlinear prediction method are combined with rule-based energy management strategies, with
It completes to distribute the energy of hybrid power system；When the power needed for automobile is higher than power threshold, using based on nonlinear prediction
The energy management strategies of control obtain the output electric current of lithium battery and super capacitor by nonlinear predictive controller, thus complete
It is distributed at energy；When the power needed for automobile is lower than power threshold, lithium is directly obtained using rule-based energy management strategies
The output power of battery and super capacitor.
Based on the above-mentioned technical proposal, the present invention can also provide following preferred embodiment.
Preferably, electric car hybrid power system is made of lithium battery and super capacitor.
Preferably, this method passes through power P needed for each moment automobilismn, lithium battery SOC and super capacitor
SOC carry out lithium battery power PbWith super capacitor power PucDistribution, specific allocation strategy is as follows:
If Pn<0 and USOC>USOCH, then make Pb=PnAnd Puc=0；
If Pn< 0 and USOC≤USOCH, then make Pb=0 and Puc=Pn；
If 0≤Pn≤PLAnd USOC > USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn>PLAnd USOC > USOCLAnd BSOC > BSOCL, then the energy management strategies based on nonlinear prediction method are used
Carry out power distribution；
If Pn> 0 and USOC≤USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn> 0 and USOC > USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=Pn；
If Pn> 0 and USOC≤USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=0；
Wherein, PnPower needed for indicating each moment automobilism, BSOC indicate that the SOC of lithium battery, USOC indicate super
The SOC of capacitor；USOCH、USOCLRespectively indicate upper limit value, the lower limit value of super capacitor SOC, BSOCLIt indicates under lithium battery SOC
Limit value, PLIndicate two kinds of tactful power thresholds of hybrid power system.
Further, in the energy management strategies based on nonlinear prediction method, the following some cycles are predicted
Speed finds out required power in the following some cycles by car speed power module, and passes through quadratic programming active set m ethod, with
Minimum power loss is the output electric current of index optimization lithium battery, completes the power distribution of lithium battery and super capacitor；Based on non-
The step of energy management strategies of linear prediction control are as follows:
Step 1) predicts the speed in some cycles by the torque at current time and car speed；
Step 2) calculates power required for each moment in predetermined period；
Step 3) calculates the optimal solution of each moment objective function in predetermined period using quadratic programming active set m ethod, and
The solution at first moment is exported as optimum control order；
Step 4) calculates lithium battery and super capacitor power, Pb=iL·Ub,Puc=ic·Uc, and repeated at the next moment
Above-mentioned steps；Wherein, iLElectric current, i are exported for lithium batterycElectric current, U are exported for super capacitorbFor lithium battery voltage, UcIt is super
Capacitance voltage.
Further, step 1)~4) in, specific calculating process is as follows:
Assuming that driving torque exponentially declines in predetermined period, and indicate are as follows:
Wherein, TW(k) it indicates that the k moment acts on the driving torque on wheel, and accelerates to be positive, deceleration is negative；Δ t is indicated
Sampling time, τdIndicate attenuation coefficient, HFIndicate predetermined period step-length；
Predict car speed are as follows:
V (k)=ua；
Meanwhile car speed power module are as follows:
Wherein, V (k) indicates the car speed at k moment, PnPower needed for indicating automobilism, M indicate car mass, f table
Show that coefficient of rolling resistance, g indicate that acceleration of gravity, α indicate road grade, CarIndicate that coefficient of air resistance, A indicate automobile windward
Area, δ indicate rotating mass correction factor, ηTIndicate the efficiency of Transmission system, RWIndicate radius of wheel, uaIndicate that vehicle is current
Speed；
Based on predetermined speed, obtain predicting required power by car speed power module, then optimize by quadratic programming
Lithium battery exports electric current iLWith the output electric current i of super capacitorc；
If lithium battery exports electric current iLFor control amount, objective function J is defined as follows:
Wherein, iL(k) and icIt (k) is respectively that the lithium battery output electric current at k moment and super capacitor export electric current；RiFor lithium
The internal resistance of cell, RcFor super capacitor internal resistance, N is optimization step-length；Constraint condition is as follows simultaneously:
Pn=Puc+Pb；
Pb=iL·Ub；
Puc=ic·Uc；
0.2≤BSOC(k)≤1；
0.56≤USOC(k)≤0.92；
0≤iL(k)≤100；
40≤ic(k)≤200；
Wherein, it is the super capacitor SOC at k moment that BSOC (k), which is the lithium battery SOC, USOC (k) at k moment,；
One group of lithium battery, which is obtained, by optimization exports electric current: iL(0),iL(1),…,iL(N-1), first element i is selectedL
(0) it is used as optimum control order, i.e. current time lithium battery exports electric current.
Further, it solves objective function and uses quadratic programming active set m ethod, specific calculating process is as follows:
Each moment, objective function can be converted into following quadratic programming problem:
Wherein,
It is as follows using quadratic programming active set m ethod solution procedure:
1) feasible initial point x is given(0), enable A0=A (x(0)), parameter p=0, A indicate above-mentioned quadratic programming problem in the point
Active set；
2) quadratic programming problem is further converted to the equality constrained quadratic programming problem:
Wherein, Ap=A (x(p)), x(p)For the feasible point of pth wheel, d=[d is solved1,d2]T, d1,d2For quadratic programming after conversion
Element in the solution of problem；Quadratic programming problem is acquired in the solution d of pth wheel(p)And corresponding Lagrange multiplierq∈Ap；
If 3) d(p)≠ 0, then
x(p+1)=x(p)+αpd(p),Ap+1=Ap∪{q0}
Wherein, αpFor the feasible factor of pth wheel, q0For αpCorresponding sequential value when value；
P=p+1 is enabled, is gone to step 2)；
If 4) d(p)=0, then whenWhen, optimal solution x can be obtained(p)；Otherwise
x(p+1)=x(p),Ap+1=Ap\{qn}
Wherein, qnTo makeCorresponding sequential value when being minimized；
P=p+1 is enabled, is gone to step 2).
Method proposed by the present invention is according to the power demand of each moment vehicle, lithium battery and super capacitor SOC situation
To carry out energy management.In Nonlinear Predictive Control Strategy, controller will predict the speed of the following some cycles, pass through vehicle
Speed of service power module is converted into power, and by quadratic programming active set m ethod, using minimum power loss as index optimization
The output electric current of lithium battery completes the power distribution of lithium battery and super capacitor.On the basis of this method power needed for meeting,
The loss that system capacity can be reduced reduces the use of lithium battery and extends the service life of lithium battery, and improves hybrid power system
The efficiency of system.
Detailed description of the invention
Fig. 1 is electric car and bidirectional power conversion research experiment platform structure figure；
Fig. 2 is ECE driving cycles hodograph；
Fig. 3 is under ECE driving cycles, and each data compare in two kinds of strategies: (a) lithium battery exports electric current, (b) super electricity
Hold output electric current, (c) lithium battery output power, (d) super capacitor output power.
Specific embodiment
The present invention is further elaborated and is illustrated with reference to the accompanying drawings and detailed description.
The electric car energy composite energy management method of rule-based and nonlinear prediction method in the present invention, is mainly used for
Power-distribution management is carried out to the electric car of hybrid power, hybrid power system is made of lithium battery and super capacitor.It is logical
This method is crossed, the power of lithium battery and super capacitor when can export to electric car hybrid power carries out reasonable distribution, full
On the basis of power needed for foot, it is possible to reduce the loss of system capacity.
In the conjunction energy management method, by energy management strategies and rule-based energy based on nonlinear prediction method
Amount management strategy combines, to complete the energy distribution to hybrid power system；When the power needed for automobile is higher than power threshold,
Using the energy management strategies based on nonlinear prediction method, lithium battery and super capacitor are obtained by nonlinear predictive controller
Output electric current, thus complete energy distribution；When the power needed for automobile is lower than power threshold, using rule-based energy pipe
Reason strategy directly obtains the output power of lithium battery and super capacitor.
Specifically, this method passes through power P needed for each moment automobilismn, lithium battery SOC and super capacitor
SOC carry out lithium battery power PbWith super capacitor power PucDistribution, specific allocation strategy is as follows:
If Pn<0 and USOC>USOCH, then make Pb=PnAnd Puc=0；
If Pn< 0 and USOC≤USOCH, then make Pb=0 and Puc=Pn；
If 0≤Pn≤PLAnd USOC > USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn>PLAnd USOC > USOCLAnd BSOC > BSOCL, then the energy management strategies based on nonlinear prediction method are used
Carry out power distribution；
If Pn> 0 and USOC≤USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn> 0 and USOC > USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=Pn；
If Pn> 0 and USOC≤USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=0；
Wherein, PnPower needed for indicating each moment automobilism, BSOC indicate that the SOC of lithium battery, USOC indicate super
The SOC of capacitor；USOCH、USOCLRespectively indicate upper limit value, the lower limit value of super capacitor SOC, BSOCLIt indicates under lithium battery SOC
Limit value, PLIndicate two kinds of tactful power thresholds of hybrid power system.
In above-mentioned strategy, P is removedn>PLAnd USOC > USOCLAnd BSOC > BSOCLThe case where belong to based on nonlinear prediction control
Outside the energy management strategies of system, remaining is all based on the energy management strategies of rule, directly obtains lithium battery and super capacitor
Output power.
And in the energy management strategies based on nonlinear prediction method, need to predict the speed of the following some cycles,
Required power in the following some cycles is found out by car speed power module, and by quadratic programming active set m ethod, with minimum
Power loss is the output electric current of index optimization lithium battery, completes the power distribution of lithium battery and super capacitor.It chats in detail below
State the key step of the energy management strategies based on nonlinear prediction method:
Step 1) predicts the speed in some cycles by the torque at current time and car speed；
Step 2) calculates power required for each moment in predetermined period；
Step 3) calculates the optimal solution of each moment objective function in predetermined period using quadratic programming active set m ethod, and
The solution at first moment is exported as optimum control order；
Step 4) calculates lithium battery and super capacitor power, Pb=iL·Ub,Puc=ic·Uc, and repeated at the next moment
Above-mentioned steps；Wherein, iLElectric current, i are exported for lithium batterycElectric current, U are exported for super capacitorbFor lithium battery voltage, UcIt is super
Capacitance voltage.
In above-mentioned steps, torque, the specific calculating process of car speed are as follows:
Assuming that driving torque exponentially declines in predetermined period, and indicate are as follows:
Wherein, TW(k) it indicates that the k moment acts on the driving torque on wheel, and accelerates to be positive, deceleration is negative；Δ t is indicated
Sampling time, τdIndicate attenuation coefficient, HFIndicate predetermined period step-length；
According to current time vehicle traction torque TW(k), the following H is calculatedFDriving torque T in a momentW(k+1),
TW(k+2),…,TW(k+HF)。
Predict car speed are as follows:
V (k)=ua；
According to current time running velocity ua, when being calculated current and future HFPrediction vehicle in a moment
Speed V (k), V (k+1), V (k+2) ..., V (k+HF)。
Meanwhile car speed power module are as follows:
Wherein, V (k) indicates the car speed at k moment, PnPower needed for indicating automobilism, M indicate car mass, f table
Show that coefficient of rolling resistance, g indicate that acceleration of gravity, α indicate road grade, CarIndicate that coefficient of air resistance, A indicate automobile windward
Area, δ indicate rotating mass correction factor, ηTIndicate the efficiency of Transmission system, RWIndicate radius of wheel, uaIndicate that vehicle is current
Speed.
The speed V (k) that will be calculated, V (k+1), V (k+2) ..., V (k+HF) bring into above formula obtain current time with
And future HFPower needed for the prediction at a moment: Pn(k),Pn(k+1),Pn(k+2),…,Pn(k+HF)。
Based on predetermined speed, obtain predicting required power by car speed power module, then optimize by quadratic programming
Lithium battery exports electric current iLWith the output electric current i of super capacitorc；
If lithium battery exports electric current iLFor control amount, under the premise of guaranteeing to complete power demand, for make super capacitor and
The power of lithium battery loss is minimum, and objective function J is defined as follows:
Wherein, iL(k) and icIt (k) is respectively that the lithium battery output electric current at k moment and super capacitor export electric current；RiFor lithium
The internal resistance of cell, RcFor super capacitor internal resistance, N is optimization step-length；Simultaneously in order to guaranteed the energy supplies of paired systems with
System safety, constraint condition are as follows:
Pn=Puc+Pb；
Pb=iL·Ub；
Puc=ic·Uc；
0.2≤BSOC(k)≤1；
0.56≤USOC(k)≤0.92；
0≤iL(k)≤100；
40≤ic(k)≤200；
Wherein, it is the super capacitor SOC at k moment that BSOC (k), which is the lithium battery SOC, USOC (k) at k moment,.
Each moment, objective function can be converted into following quadratic programming problem:
Wherein,
It is as follows using quadratic programming active set m ethod solution procedure:
1) feasible initial point x is given(0), enable A0=A (x(0)), parameter p=0, A indicate above-mentioned quadratic programming problem in the point
Active set；
2) quadratic programming problem is further converted to the equality constrained quadratic programming problem:
Wherein, Ap=A (x(p)), x(p)For the feasible point of pth wheel, d=[d is solved1,d2]T, d1,d2For quadratic programming after conversion
Element in the solution of problem；Quadratic programming problem is acquired in the solution d of pth wheel(p)And corresponding Lagrange multiplierq∈Ap；
If 3) d(p)≠ 0, then
x(p+1)=x(p)+αpd(p),Ap+1=Ap∪{q0}
Wherein, αpFor the feasible factor of pth wheel, q0For αpCorresponding sequential value when value；
P=p+1 is enabled, is gone to step 2)；
If 4) d(p)=0, then whenWhen, optimal solution x can be obtained(p)；Otherwise
x(p+1)=x(p),Ap+1=Ap\{qn}
Wherein, qnTo makeCorresponding sequential value when being minimized；
P=p+1 is enabled, is gone to step 2).
Optimize to obtain each moment lithium battery output electric current: i by quadratic programming active set m ethodL(0),iL(1),…,iL
(N-1), first element i is selectedL(0) optimum control order, the i.e. optimal output electric current of current time lithium battery are used as.
The power that lithium battery and super capacitor can be obtained according to step 4) as a result, completes the power distribution at current time.
Subsequent time can continue to repeat these processes, re-start power distribution.
Below based on the above method, its technical effect is further shown in conjunction with specific embodiments, partial parameters
It is defined as described above, it repeats no more.
Embodiment
ECE (Economic is utilized using this method on electric car and bidirectional power conversion research experiment platform
Commission of Europe) driving cycles are tested.Experiment porch structure chart is as shown in Figure 1, entire research experiment is flat
Platform is managed collectively by industrial personal computer 1, and industrial personal computer 1 controls charger, inverter, battery management system and two-way by CAN network
DC/DC converter is communicated by Ethernet with electric dynamometer system industrial personal computer 2, thus motor and frequency converter.ECE drives work
Condition is as shown in Figure 2.
In energy composite energy management method, energy management strategies and rule-based energy based on nonlinear prediction method
Management strategy combines, to complete the energy distribution to hybrid power system.When the power needed for automobile is higher, use is non-linear
Predictive control strategy obtains the output electric current of lithium battery and super capacitor by nonlinear predictive controller, to complete energy
Distribution；When the power needed for automobile is lower, lithium battery and super capacitor are directly obtained using rule-based energy management strategies
Output power.And the foundation that the settable a certain threshold value of power needed for automobile is adjusted as policy selection.In the present embodiment, the party
Method passes through power (P needed for each moment automobilismn), the SOC (USOC) of the SOC (BSOC) of lithium battery and super capacitor into
Row lithium battery power (Pb) and super capacitor power (Puc) distribution, specific strategy is as follows:
If Pn<0 and USOC>USOCH, then make Pb=PnAnd Puc=0；
If Pn< 0 and USOC≤USOCH, then make Pb=0 and Puc=Pn；
If 0≤Pn≤PLAnd USOC > USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn>PLAnd USOC > USOCLAnd BSOC > BSOCL, then the energy management strategies based on nonlinear prediction method are used
Carry out power distribution；
If Pn> 0 and USOC≤USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn> 0 and USOC > USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=Pn；
If Pn> 0 and USOC≤USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=0；
Wherein, USOCH, USOCLThe upper lower limit value of super capacitor SOC is respectively indicated, their value is respectively 0.92 He
0.56。BSOCLIndicate the lower limit value of lithium battery SOC, its value is 0.2.PLIndicate two kinds of tactful power-thresholds of hybrid power system
It is worth, its value is 1500W in the present embodiment.
In the energy management strategies based on nonlinear prediction method, needs to predict the speed of the following some cycles, pass through
Car speed power module finds out required power in the following some cycles, and by quadratic programming active set m ethod, with minimum power
Loss is the output electric current of index optimization lithium battery, completes the power distribution of lithium battery and super capacitor.
Assuming that driving torque exponentially declines in predetermined period, and indicate are as follows:
Wherein, TWIndicating the driving torque (acceleration is positive, and deceleration is negative) acted on wheel, Δ t indicates the sampling time,
τdIndicate attenuation coefficient, HFIndicate predetermined period step-length.
Prediction car speed may be expressed as:
V (k)=ua；
Meanwhile car speed power module may be expressed as:
Wherein, PnPower needed for indicating automobilism, M indicate that car mass, f indicate that coefficient of rolling resistance, g indicate gravity
Acceleration, α indicate road grade, CarIndicate that coefficient of air resistance, A indicate that front face area of automobile, δ indicate rotating mass amendment system
Number, ηTIndicate the efficiency of Transmission system, RWIndicate radius of wheel, uaIndicate vehicle present speed.The value and unit of parameters are such as
Shown in table 1.
1 highway speeds model parameter of table
| Δt | 0.1s | α | 0 |
| τd | 7 | Car | 0.3 |
| HF | 3 | Α | 1.51m2 |
| M | 400kg | δ | 1.1 |
| f | 0.009 | ηT | 0.95 |
| g | 9.81m/s2 | RW | 0.282m |
Based on predetermined speed, can obtain predicting required power by car speed power module, then excellent by quadratic programming
Change lithium battery and exports electric current iLWith the output electric current i of super capacitorc。
If lithium battery exports electric current iLFor control amount.Under the premise of guaranteeing to complete power demand, in order to make super capacitor
Minimum with the power of lithium battery loss, objective function is defined as follows:
Wherein, RiFor lithium battery internal resistance, RCFor super capacitor internal resistance, N is optimization step-length, value 4.While in order to guarantee
Energy supply and system safety, the constraint condition for capableing of complete paired systems are as follows:
Pn=Puc+Pb；
Pb=iL·Ub；
Puc=ic·Uc；
0.2≤BSOC(k)≤1；
0.56≤USOC(k)≤0.92；
0≤iL(k)≤100；
40≤ic(k)≤200；
Lithium battery voltage and super-capacitor voltage can be sampled by equipment to be obtained.
Each moment, objective function can be converted into following quadratic programming problem:
Wherein,
It is as follows using quadratic programming active set m ethod solution procedure:
1) feasible initial point x is given(0), enable A0=A (x(0)), parameter p=0, A indicate above-mentioned quadratic programming problem in the point
Active set；
2) quadratic programming problem is further converted to the equality constrained quadratic programming problem:
Wherein, Ap=A (x(p)), x(p)For the feasible point of pth wheel, d=[d is solved1,d2]T, d1,d2For quadratic programming after conversion
Element in the solution of problem；Quadratic programming problem is acquired in the solution d of pth wheel(p)And corresponding Lagrange multiplierq∈Ap；
If 3) d(p)≠ 0, then
x(p+1)=x(p)+αpd(p),Ap+1=Ap∪{q0}
Wherein, αpFor the feasible factor of pth wheel, q0For αpCorresponding sequential value when value；
P=p+1 is enabled, is gone to step 2)；
If 4) d(p)=0, then whenWhen, optimal solution x can be obtained(p)；Otherwise
x(p+1)=x(p),Ap+1=Ap\{qn}
Wherein, qnTo makeCorresponding sequential value when being minimized；
P=p+1 is enabled, is gone to step 2).
Optimize to obtain each moment lithium battery output electric current: i by quadratic programming active set m ethodL(0),iL(1),…,iL
(N-1), first element i is selectedL(0) it is used as optimum control order, i.e. current time lithium battery exports electric current.
To sum up, Nonlinear Predictive Control Strategy step are as follows:
Step 1) predicts the speed in some cycles by the torque at current time and car speed.Sampling obtains current
Moment vehicle traction torque TW(k), and T (0)=T is enabledW(k), the driving in following 3 moment is calculated according to aforementioned formula
Torque T (1), T (2), T (3).Sampling obtains current time running velocity u simultaneouslya(k), it is calculated according to aforementioned formula
Prediction car speed V (0), V (1), V (2), V (3) in current time and following 3 moment；
Power required for step 2) calculates each moment in predetermined period according to car speed power module.By step 1
In obtain the prediction at current time and following 3 moment in the velocity vehicle speed-power model that is calculated needed for power Pn
(0),Pn(1),Pn(2),Pn(3)。
Step 3) calculates the optimal solution of each moment objective function in predetermined period using quadratic programming active set m ethod, and
The solution for exporting first moment samples to obtain current time lithium battery voltage U as optimum control orderb(k) and super electricity
Hold voltage Uc(k), it according to formula objective function and constraint condition, is respectively obtained using quadratic programming active set m ethod every in predetermined period
The lithium battery at a moment exports electric current: iL(0),iL(1),iL(2),iL(3), and first element i is selectedL(0) when being used as current
Optimum control order is carved, even iL(k)=iL(0), while the output electric current i of super capacitor can be obtainedc(k)。
Step 4) calculates current time lithium battery and super capacitor power:
Pb(k)=iL(k)·Ub(k),Puc(k)=ic(k)·Uc(k)
To complete the energy distribution of lithium battery and super capacitor.
At next moment, T (0)=T is enabledW(k+1), and continue to repeat the above steps 1)~4), re-start distribution.
System carries out the output of the lithium battery and super capacitor after energy management using this method (NPC-EMS) with base
It is as shown in Figure 3 in the output comparison of the energy management method (R-EMS) of rule.As can be seen from Figure, it under ECE operating condition, uses
Lithium battery output electric current in this method progress energy management is integrally lower with power, illustrates to make the method reduce lithium battery
With, facilitate extend service life of lithium battery.It can be calculated simultaneously, the energy for using this method system totally to need is adopted for 139830J
Needing energy with rule-based energy management method system is 144010J, it follows that this method can reduce system capacity
Loss.
Above-mentioned embodiment is only a preferred solution of the present invention, so it is not intended to limiting the invention.Have
The those of ordinary skill for closing technical field can also make various changes without departing from the spirit and scope of the present invention
Change and modification.Therefore all mode technical solutions obtained for taking equivalent substitution or equivalent transformation, all fall within guarantor of the invention
It protects in range.
Claims (6)
1. a kind of rule-based electric car energy composite energy management method with nonlinear prediction method, it is characterised in that: multiple
Close energy management method in, by based on nonlinear prediction method energy management strategies and rule-based energy management strategies phase
In conjunction with to complete the energy distribution to hybrid power system；When the power needed for automobile is higher than power threshold, using based on non-thread
The energy management strategies of property PREDICTIVE CONTROL, obtain the output electric current of lithium battery and super capacitor by nonlinear predictive controller,
To complete energy distribution；It is direct using rule-based energy management strategies when the power needed for automobile is lower than power threshold
Obtain the output power of lithium battery and super capacitor.
2. the rule-based electric car energy composite energy management method with nonlinear prediction method as described in claim 1,
Be characterized in that: electric car hybrid power system is made of lithium battery and super capacitor.
3. the rule-based electric car energy composite energy management method with nonlinear prediction method as described in claim 1,
Be characterized in that: this method passes through power P needed for each moment automobilismn, lithium battery SOC and super capacitor SOC into
Row lithium battery power PbWith super capacitor power PucDistribution, specific allocation strategy is as follows:
If Pn<0 and USOC>USOCH, then make Pb=PnAnd Puc=0；
If Pn< 0 and USOC≤USOCH, then make Pb=0 and Puc=Pn；
If 0≤Pn≤PLAnd USOC > USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn>PLAnd USOC > USOCLAnd BSOC > BSOCL, then carried out using the energy management strategies based on nonlinear prediction method
Power distribution；
If Pn> 0 and USOC≤USOCLAnd BSOC > BSOCL, then make Pb=PnAnd Puc=0；
If Pn> 0 and USOC > USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=Pn；
If Pn> 0 and USOC≤USOCLAnd BSOC≤BSOCL, then make Pb=0 and Puc=0；
Wherein, PnPower needed for indicating each moment automobilism, BSOC indicate that the SOC of lithium battery, USOC indicate super capacitor
SOC；USOCH、USOCLRespectively indicate upper limit value, the lower limit value of super capacitor SOC, BSOCLIndicate the lower limit value of lithium battery SOC,
PLIndicate two kinds of tactful power thresholds of hybrid power system.
4. the rule-based electric car energy composite energy management method with nonlinear prediction method as claimed in claim 3,
It is characterized in that: in the energy management strategies based on nonlinear prediction method, predicting the speed of the following some cycles, pass through
Car speed power module finds out required power in the following some cycles, and by quadratic programming active set m ethod, with minimum power
Loss is the output electric current of index optimization lithium battery, completes the power distribution of lithium battery and super capacitor；Based on nonlinear prediction
The step of energy management strategies of control are as follows:
Step 1) predicts the speed in some cycles by the torque at current time and car speed；
Step 2) calculates power required for each moment in predetermined period；
Step 3) calculates the optimal solution of each moment objective function in predetermined period using quadratic programming active set m ethod, and exports
The solution at first moment is as optimum control order；
Step 4) calculates lithium battery and super capacitor power, Pb=iL·Ub,Puc=ic·Uc, and it is above-mentioned in the repetition of next moment
Step；Wherein, iLElectric current, i are exported for lithium batterycElectric current, U are exported for super capacitorbFor lithium battery voltage, UcFor super capacitor
Voltage.
5. the rule-based electric car energy composite energy management method with nonlinear prediction method as claimed in claim 4,
It is characterized in that, step 1)~4) in, specific calculating process is as follows:
Assuming that driving torque exponentially declines in predetermined period, and indicate are as follows:
Wherein, TW(k) it indicates that the k moment acts on the driving torque on wheel, and accelerates to be positive, deceleration is negative；Δ t indicates sampling
Time, τdIndicate attenuation coefficient, HFIndicate predetermined period step-length；
Predict car speed are as follows:
V (k)=ua；
Meanwhile car speed power module are as follows:
Wherein, V (k) indicates the car speed at k moment, PnPower needed for indicating automobilism, M indicate that car mass, f indicate rolling
Dynamic resistance coefficient, g indicate that acceleration of gravity, α indicate road grade, CarIndicate that coefficient of air resistance, A indicate automobile windward side
Product, δ indicate rotating mass correction factor, ηTIndicate the efficiency of Transmission system, RWIndicate radius of wheel, uaIndicate that vehicle is currently fast
Degree；
Based on predetermined speed, obtain predicting required power by car speed power module, then optimize lithium electricity by quadratic programming
Pond exports electric current iLWith the output electric current i of super capacitorc；
If lithium battery exports electric current iLFor control amount, objective function J is defined as follows:
Wherein, iL(k) and icIt (k) is respectively that the lithium battery output electric current at k moment and super capacitor export electric current；RiFor lithium battery
Internal resistance, RcFor super capacitor internal resistance, N is optimization step-length；Constraint condition is as follows simultaneously:
Pn=Puc+Pb；
Pb=iL·Ub；
Puc=ic·Uc；
0.2≤BSOC(k)≤1；
0.56≤USOC(k)≤0.92；
0≤iL(k)≤100；
40≤ic(k)≤200；
Wherein, it is the super capacitor SOC at k moment that BSOC (k), which is the lithium battery SOC, USOC (k) at k moment,；
One group of lithium battery, which is obtained, by optimization exports electric current: iL(0),iL(1),…,iL(N-1), first element i is selectedL(0) make
For optimum control order, i.e. current time lithium battery exports electric current.
6. the rule-based electric car energy composite energy management method with nonlinear prediction method as claimed in claim 5,
It is characterized in that, solves objective function and use quadratic programming active set m ethod, specific calculating process is as follows:
Each moment, objective function can be converted into following quadratic programming problem:
Wherein,
It is as follows using quadratic programming active set m ethod solution procedure:
6.1) feasible initial point x is given(0), enable A0=A (x(0)), parameter p=0, A indicate above-mentioned quadratic programming problem in the point
Active set；
6.2) quadratic programming problem is further converted to the equality constrained quadratic programming problem:
Wherein, Ap=A (x(p)), x(p)For the feasible point of pth wheel, d=[d is solved1,d2]T, d1,d2For quadratic programming problem after conversion
Solution in element；Quadratic programming problem is acquired in the solution d of pth wheel(p)And corresponding Lagrange multiplier
If 6.3) d(p)≠ 0, then
x(p+1)=x(p)+αpd(p),Ap+1=Ap∪{q0}
Wherein, αpFor the feasible factor of pth wheel, q0For αpCorresponding sequential value when value；
P=p+1 is enabled, is gone to step 6.2)；
If 6.4) d(p)=0, then whenWhen, optimal solution x can be obtained(p)；Otherwise
x(p+1)=x(p),Ap+1=Ap\{qn}
Wherein, qnTo makeCorresponding sequential value when being minimized；
P=p+1 is enabled, is gone to step 6.2).
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