CN109031946A - A kind of control method and device of mixed energy storage system - Google Patents

A kind of control method and device of mixed energy storage system Download PDF

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CN109031946A
CN109031946A CN201810426334.3A CN201810426334A CN109031946A CN 109031946 A CN109031946 A CN 109031946A CN 201810426334 A CN201810426334 A CN 201810426334A CN 109031946 A CN109031946 A CN 109031946A
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loss
power
moment
power battery
storage system
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齐洪峰
王轶欧
于博轩
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CRRC Industry Institute Co Ltd
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

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  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The present invention discloses a kind of control method and device of mixed energy storage system.Wherein, which comprises establish the power battery power loss model and super capacitor power loss model of mixed energy storage system;The power loss Optimized model of the mixed energy storage system is established with the minimum target of power loss of mixed energy storage system under the conditions of full working scope based on the power battery power loss model and the super capacitor power loss model;The power loss Optimized model is solved based on dynamic programming algorithm, obtains the Optimal Control Strategy of the mixed energy storage system.Described device is for executing the above method.The control method and device of mixed energy storage system provided by the invention reduce the energy consumption of mixed energy storage system.

Description

A kind of control method and device of mixed energy storage system
Technical field
The present invention relates to rail traffic energy technology fields, and in particular to a kind of control method and dress of mixed energy storage system It sets.
Background technique
Due to the features such as tramcar passenger capacity is big, speed is high, frequently starting is braked in operational process, lead to it not only Having higher power demand, there are also biggish energy requirements.The energy-storage system mixed using power battery with super capacitor, not only It can satisfy the power energy demand of train, moreover it is possible to improve train operation efficiency and power performance, reduce cost.
For the energy-storage system that power battery is mixed with super capacitor, it is to improve to have that real vehicle operation control how is carried out to it The key point of rail electric car operational efficiency.The fuzzy logic power distribution plan based on stochastic prediction that prior art discloses a kind of Slightly, this method is focused on solving to power demand in future in real vehicle operational process based on the Markov stochastic prediction principle Forecasting problem, and using prediction power as one of input quantity of fuzzy control, to realize the power distribution of hybrid energy-storing and mention High train operation efficiency, but there is no optimize FUZZY ALGORITHMS FOR CONTROL;The prior art also discloses a kind of using population Algorithm is solved with the fuzzy controller relevant parameter of the minimum target of energy consumption of vehicles, and then completes the design of fuzzy controller, real Existing vehicle On-line Control, but since this method is to be realized based on certain fuzzy rule, thus acquired results are not optimal solution; The vehicle-mounted mixed energy storage system efficiency-optimization control of tramcar carries out the vehicle air-conditioning of train, root based on SUMT interior point method Train optimizing decision at this time is solved according to train current state, completes energy distribution, but according to principle of optimality it is found that train is instantaneous The optimal result of decision may not be exactly the result of decision of global optimum.
Therefore, the control method for how proposing a kind of mixed energy storage system can be realized mixed energy storage system entirety energy consumption Minimum becomes industry important topic urgently to be resolved to reduce the energy consumption of mixed energy storage system.
Summary of the invention
For the defects in the prior art, the present invention provides a kind of control method and device of mixed energy storage system.
On the one hand, the present invention proposes a kind of control method of mixed energy storage system, comprising:
Establish the power battery power loss model and super capacitor power loss model of mixed energy storage system;
Based on the power battery power loss model and the super capacitor power loss model, with the hybrid energy-storing The minimum target of power loss of system under the conditions of full working scope establishes the power loss optimization mould of the mixed energy storage system Type;
The power loss Optimized model is solved based on dynamic programming algorithm, obtains the mixed energy storage system Optimal Control Strategy.
On the other hand, the present invention provides a kind of control device of mixed energy storage system, comprising:
First establishing unit, for establishing the power battery power loss model and super capacitor power of mixed energy storage system Loss model;
Second establishes unit, for being based on the power battery power loss model and the super capacitor power loss mould Type establishes the mixed energy storage system with the minimum target of power loss of mixed energy storage system under the conditions of full working scope Power loss Optimized model;
Unit is solved, for solving based on dynamic programming algorithm to the power loss Optimized model, described in acquisition The Optimal Control Strategy of mixed energy storage system.
In another aspect, the present invention provides a kind of electronic equipment, comprising: processor, memory and communication bus, in which:
The processor and the memory complete mutual communication by the communication bus;
The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program to refer to Enable the control method that the mixed energy storage system provided such as the various embodiments described above is provided.
Another aspect, the present invention provide a kind of non-transient computer readable storage medium, and the non-transient computer is readable Storage medium stores computer instruction, and the computer instruction makes the computer execute the mixing provided such as the various embodiments described above The control method of energy-storage system.
The control method and device of mixed energy storage system provided by the invention, due to by establishing the dynamic of mixed energy storage system Power battery power consumption model and super capacitor power loss model, and it is based on power battery power loss model and super capacitor Power loss model establishes hybrid energy-storing system with the minimum target of power loss of mixed energy storage system under the conditions of full working scope The power loss Optimized model of system is then based on dynamic programming algorithm and solves to power loss Optimized model, mixed The Optimal Control Strategy of energy-storage system reduces the energy consumption of mixed energy storage system.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the structural schematic diagram of the mixed energy storage system of tramcar of the embodiment of the present invention;
Fig. 2 is the flow diagram of the control method of one embodiment of the invention mixed energy storage system;
Fig. 3 is solution flow chart of the one embodiment of the invention based on dynamic programming algorithm;
Fig. 4 is the structural schematic diagram of the control device of one embodiment of the invention mixed energy storage system;
Fig. 5 is the entity structure schematic diagram of one embodiment of the invention electronic equipment.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached in the embodiment of the present invention Figure, technical solution in the embodiment of the present invention are explicitly described, it is clear that described embodiment is a part of the invention Embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making wound Every other embodiment obtained under the premise of the property made labour, shall fall within the protection scope of the present invention.
Fig. 1 is the structural schematic diagram of the mixed energy storage system of tramcar of the embodiment of the present invention, as shown in Figure 1, described mixed Closing energy-storage system includes super capacitor, power battery and DC converter, the power battery by the DC converter with The super capacitor is connected in parallel on the DC bus of tramcar, is the vehicle traction system and auxiliary power supply of the tramcar System provides energy.Meanwhile the mixed energy storage system can also inhale the receipts feedback braking energy of the tramcar, complete institute State the interaction of power and energy of the tramcar under different operating conditions.The control method of mixed energy storage system provided by the invention, For above-mentioned mixed energy storage system, by the power battery power loss model and super capacitor power of establishing mixed energy storage system Loss model, and it is based on power battery power loss model and super capacitor power loss model, with mixed energy storage system complete The minimum target of power loss under working condition, establishes the power loss Optimized model of mixed energy storage system, is then based on dynamic State planning algorithm solves power loss Optimized model, carries out so as to the mixed energy storage system to the tramcar Efficient and accurate energy distribution, so that the power of the tramcar mixed energy storage system under the conditions of full working scope Loss is minimum, and can guarantee that each element works in safe and reliable range in the mixed energy storage system, is guaranteeing rail On the basis of the safe operation of electric car, the energy loss of the mixed energy storage system is efficiently and securely reduced.It is intelligible It is that the mixed energy storage system cannot only be applied on the tramcar, can also be used in automobile etc. certainly can use institute State industry or the field of mixed energy storage system.
Fig. 2 is the flow diagram of the control method of one embodiment of the invention mixed energy storage system, as shown in Fig. 2, this hair The control method of the mixed energy storage system of bright offer, comprising:
S201, the power battery power loss model for establishing mixed energy storage system and super capacitor power loss model;
Specifically, energy, the loss of energy are provided by power battery and super capacitor due to the mixed energy storage system The power battery and the super capacitor are mostly come from, therefore establishes the power battery power loss mould of mixed energy storage system Type calculates the power loss of the power battery, and establishes super capacitor power loss model to calculate the super capacitor Power loss.
S202, it is based on the power battery power loss model and the super capacitor power loss model, with described mixed Power loss minimum target of energy-storage system under the conditions of full working scope is closed, the power loss for establishing the mixed energy storage system is excellent Change model;
Specifically, after obtaining the power battery power loss model and the super capacitor power loss model, With the minimum target of power loss of mixed energy storage system under the conditions of full working scope, according to the power battery power loss Model and the super capacitor power loss model can establish the power loss Optimized model of the mixed energy storage system.It is described Power loss Optimized model may include optimization object function and constraint condition, the constraint condition include equality constraint and Inequality constraints condition.Wherein, the full working scope condition refers to one that the mixed energy storage system is run in practical applications Complete cycle, for example, the tramcar mixed energy storage system full working scope condition refer to the tramcar from starting point run To terminal.
S203, the power loss Optimized model is solved based on dynamic programming algorithm, obtains the hybrid energy-storing The Optimal Control Strategy of system.
It specifically, can be by dynamic programming algorithm to the power after obtaining the power loss Optimized model Loss optimizing model is solved, i.e., runing time of the mixed energy storage system under the conditions of full working scope is discrete for N A stage, with the state-of-charge (State of Charge, hereinafter referred to as SOC) of the power battery for state variable, with described The current-order of power battery passes through the power loss using ampere-hour integral formula as state transition equation for decision variable The Dynamic Programming Equation of Optimized model can obtain the mixed energy storage system in the case where meeting the constraint condition Optimal Control Strategy controls the mixed energy storage system according to the Optimal Control Strategy, can be realized described complete The minimum power loss of the mixed energy storage system under working condition.Wherein, the current-order is for being arranged the power electric The size of current in pond.
The control method of mixed energy storage system provided by the invention, due to the power battery by establishing mixed energy storage system Power loss model and super capacitor power loss model, and damaged based on power battery power loss model and super capacitor power It consumes model and the function of mixed energy storage system is established with the minimum target of power loss of mixed energy storage system under the conditions of full working scope Rate loss optimizing model is then based on dynamic programming algorithm and solves to power loss Optimized model, obtains hybrid energy-storing system The Optimal Control Strategy of system reduces the energy consumption of mixed energy storage system.
On the basis of the various embodiments described above, further, the power battery power loss model are as follows:
Wherein, Vp(k) the polarizing voltage value of the power battery described in the kth moment, V are indicatedp(k-1) it indicates at -1 moment of kth The polarizing voltage value of the power battery, k are positive integer, TsIndicate time step, e indicates natural constant, Ib(k) it indicates in kth The current value of power battery described in moment, Rp[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) pole under Change internal resistance value, SOC(k) state-of-charge of the power battery described in the kth moment, V are indicatedo(k) power described in the kth moment is indicated The terminal voltage value of battery, Vocv[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) open-circuit voltage values under, Ro[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) the ohmic internal resistance value under, Cp[SOC(k)] it indicates the Power battery described in the k moment is in current SOC(k) the polarization capacity value under, Pbat_loss(k) power electric described in the kth moment is indicated The loss power in pond;Vp(0)=0;
The super capacitor damage power consumes model are as follows:
Puc_loss(k)=Iuc(k)2Ruc
Wherein, Vuc(k) open-circuit voltage values in kth moment super capacitor, V are indicateduc(k-1) it indicates in -1 moment of kth institute State the open-circuit voltage values of super capacitor, Iuc(k) current value of the super capacitor described in the kth moment, C are indicateducIt indicates in kth Carve the capacitance of the super capacitor, Vc(k) terminal voltage value of the super capacitor described in the kth moment, R are indicateducIndicate described super The internal resistance value of grade capacitor, Puc_loss(k) loss power of the super capacitor described in the kth moment is indicated;Vuc(0)=0.
Specifically, the power battery is in the polarizing voltage value at the 0th moment, i.e. the polarizing voltage value V of initial timep(0) =0, the polarizing voltage value V at kth momentp(k), recurrence formula can be passed throughIt obtains ?.The time step Ts, can be set to 1s.State-of-charge S of the power battery at the 0th momentOC(0) be it is given, Pass through ampere-hour integral formulaThe power battery can be obtained at the kth moment State-of-charge SOC(k)。Ib(k) it is arranged to the decision variable.Rp[SOC(k)] the polarization resistance value measured using laboratory with The relationship of the state-of-charge is found out, Vocv[SOC(k)] pass of the open-circuit voltage values and the state-of-charge measured using laboratory System finds out, Cp[SOC(k)] relationship of the polarization capacity value and the state-of-charge that are measured using laboratory is found out, Ro[SOC(k)] The relationship of the ohmic internal resistance value and the state-of-charge that are measured using laboratory is found out.Wherein, the mixed energy storage system is in institute Runing time under the conditions of full working scope is stated by discrete as N number of stage, N number of stage correspond to N+1 a time points.
The power battery is in the open-circuit voltage values at the 0th moment, i.e. the open-circuit voltage values V of initial timeuc(0)=0, kth The polarizing voltage value V at momentuc(k), recurrence formula can be passed throughIt obtains.Wherein, What the loss power of the super capacitor considered is loss caused by ohmic internal resistance.
On the basis of the various embodiments described above, further, the power loss Optimized model includes optimization object function, The optimization object function are as follows:
Wherein, Ploss(i)=Pbat_loss(i)+Puc_loss(i)+Pdd_loss(i), Ploss(i) it indicates to mix described in the i-th moment Close the loss power of energy-storage system, Pbat_loss(i) loss power of the power battery described in the i moment, P are indicateduc_loss(i) it indicates The loss power of the super capacitor described in the i-th moment, Pdd_loss(i) loss power in the i-th moment DC converter, i are indicated More than or equal to 0 and i is less than or equal to N-1, and N is the mixed energy storage system discrete rank of runing time under the conditions of the full working scope Number of segment.
Specifically, when establishing the power loss Optimized model, in order to more accurately calculate the mixed energy storage system Loss power, introduce the loss power of DC converter, the loss power of the mixed energy storage system is equal to the power electric The sum of the loss power in pond, the loss power of the super capacitor and loss power of the DC converter.Described in foundation Power loss Optimized model is the minimum value in order to obtain the mixed energy storage system loss power under the conditions of full working scope. Loss power P of the DC converter at the i-th momentdd_loss(i)=(1- η) Pbat(i), wherein η is the DC converting The energy conversion efficiency of device, PbatIt (i) is the output power of the power battery described in the i-th moment.
On the basis of the various embodiments described above, further, the power loss Optimized model includes equality constraint With inequality constraints condition, in which:
The equality constraint are as follows:
Wherein, Puc(i) output power of the super capacitor described in the i-th moment, P are indicatedbd(i) it indicates in the i-th moment direct current The on high-tension side output power of converter, Preq(i) it indicates in the i-th moment load demand power, Pbat(i) it indicates in the i-th moment institute State the output power of power battery, PSIV(i) power in the i-th moment auxiliary power supply system, P are indicateddd_loss(i) it indicates i-th The loss power of DC converter described in moment, i is integer and i is more than or equal to 0.
The inequality constraints condition are as follows:
Wherein, Ib_minIndicate the minimum value of the charging and discharging currents of the power battery, Ib(i) it indicates described in the i-th moment The current value of power battery, Ib_maxIndicate the maximum value of the charging and discharging currents of the power battery, Iuc_minIndicate the super electricity The minimum value of the charging and discharging currents of appearance, Iuc(i) current value of the super capacitor described in the i-th moment, I are indicateduc_maxIndicate described super The maximum value of the charging and discharging currents of grade capacitor, SOC_minIndicate the minimum value of the state-of-charge of power battery, SOC(i) it indicates i-th The state-of-charge of power battery described in moment, SOC_maxIndicate the maximum value of the state-of-charge of power battery, Vuc_minDescribed in expression The minimum value of the open-circuit voltage of super capacitor, Vuc(i) open-circuit voltage values in the i-th moment super capacitor, V are indicateduc_maxIndicate institute The maximum value of the open-circuit voltage of super capacitor is stated, i is integer and i is more than or equal to 0.
It is further, described excellent to the power loss based on dynamic programming algorithm on the basis of the various embodiments described above Change model to be solved, the Optimal Control Strategy for obtaining the mixed energy storage system includes:
The state-of-charge that the power battery is arranged is state variable, and the current-order that the power battery is arranged is certainly Plan variable establishes following Dynamic Programming Equation:
Wherein, xi(k), i-th of state-of-charge in kth stage, u are indicatedj(k) j-th of current-order in kth stage is indicated, V(xi(k), k) it is multistep objective function from the 0th stage to the kth stage, V (xj(k-1), k-1) it is from the 0th stage to kth -1 The multistep objective function in stage, J (xi(k),uj(k)) indicate the state variable from xj(k-1) x is changed toi(k) single step when Objective function, M be the power battery state-of-charge from state-of-charge minimum value to state-of-charge maximum value it is discrete described in The quantity of state-of-charge;N is the discrete number of stages of runing time under the conditions of the full working scope of the mixed energy storage system.
Specifically, when solving using dynamic programming algorithm to the power loss Optimized model, need to be arranged institute The state-of-charge for stating power battery is state variable, and the state-of-charge of the power battery is from state-of-charge minimum value to charged Discrete state maximum value is M state-of-charge, such as with the 20% of the rated capacity of the power battery for the state-of-charge Minimum value, with the 80% of the rated capacity of the power battery for the state-of-charge maximum value, by the lotus of the power battery Electricity condition is divided into 12001 parts.Meanwhile the current-order that the power battery is arranged is decision variable, the current-order is used In the electric current that the power battery is arranged, the state-of-charge of the power battery is influenced.It can establish following Dynamic Programming Equation:
Wherein, the multistep objective function V (x in the 0th stage to kth stagei(k), k) i.e. described mixed energy storage system is from the 0th The sum of the loss power in stage to kth stage, the state variable is from xj(k-1) x is changed toi(k) single step objective function J when (xi(k),uj(k)) the i.e. described mixed energy storage system is x in state-of-chargei(k), decision uj(k) under, from -1 stage of kth to kth The loss power in stage.
Fig. 3 is solution flow chart of the one embodiment of the invention based on dynamic programming algorithm, as shown in figure 3, being advised based on dynamic The step of cost-effective method solves the power loss Optimized model is as follows:
(1) runing time under the conditions of full working scope of the mixed energy storage system is discrete for N number of stage, setting institute State power battery state-of-charge be state variable x, and by the state-of-charge of the power battery from state-of-charge minimum value to Discrete state-of-charge maximum value is the M state-of-charges, and the current-order that the power battery is arranged is decision variable u, with Ampere-hour integral formula is as state transition equation, using the optimization object function as single step objective function;
(2) initialize, and input solve the power loss Optimized model needed for primary data;
(3) the kth stage;
(4) kth stage, state x are calculatedi(k) decision region;
(5) kth stage, state x are calculatedi(k), decision uj(k) the state x in corresponding -1 stage of kth whenj(k-1);
(6) judge xj(k-1) whether meet constraint condition, if meeting constraint condition, carry out in next step;Otherwise j=j+ 1, return step (5);
(7) kth stage, state x are calculatedi(k), decision uj(k) single step objective function J (x wheni(k),uj(k));
(8) the multistep objective function V (x from the 0th stage to the kth stage is calculatedi(k), k)=J (xi(k),uj(k))+V(xj (k-1), k-1), and judge V (xi(k), k) it whether is minimum value, if it is minimum value, carry out in next step;Otherwise j=j+1 is returned It returns step (5);
(9) judge whether i is greater than M, if i is greater than M, illustrate to have traversed kth stage all state-of-charge, entrance is next A step;Otherwise i=i+1, return step (4);
(10) judge whether k is equal to N, if k is equal to N, calculating is finished, and exports calculated result;Otherwise k=k+1 returns to step Suddenly (3).
Fig. 4 is the structural schematic diagram of the control device of one embodiment of the invention mixed energy storage system, as shown in figure 4, this hair The control device of the mixed energy storage system of bright offer include first establishing unit 401, second establish unit 402 and solve unit 403, in which:
First establishing unit 401 is used to establish the power battery power loss model and super capacitor function of mixed energy storage system Rate loss model;Second establishes unit 402 for based on the power battery power loss model and the super capacitor power Loss model establishes the mixing storage with the minimum target of power loss of mixed energy storage system under the conditions of full working scope The power loss Optimized model of energy system;Unit 403 is solved to be used to optimize mould to the power loss based on dynamic programming algorithm Type is solved, and the Optimal Control Strategy of the mixed energy storage system is obtained.
Specifically, energy, the loss of energy are provided by power battery and super capacitor due to the mixed energy storage system The power battery and the super capacitor are mostly come from, therefore first establishing unit 401 establishes the dynamic of mixed energy storage system Power battery power consumption model calculates the power loss of the power battery, and establishes super capacitor power loss model to count Calculate the power loss of the super capacitor.
After obtaining the power battery power loss model and the super capacitor power loss model, second is established Unit 402 is with the minimum target of power loss of mixed energy storage system under the conditions of full working scope, according to the power battery Power loss model and the super capacitor power loss model can establish the power loss optimization of the mixed energy storage system Model.The power loss Optimized model may include optimization object function and constraint condition, and the constraint condition includes equation Constraint condition and inequality constraints condition.Wherein, the full working scope condition refers to the mixed energy storage system in practical applications One complete cycle of operation, such as the full working scope condition of mixed energy storage system of the tramcar refer to the tramcar Terminal is run to from starting point.
After obtaining the power loss Optimized model, solving unit 403 can be by dynamic programming algorithm to described Power loss Optimized model is solved, i.e., runing time of the mixed energy storage system under the conditions of full working scope is discrete Become using the state-of-charge of the power battery as state variable by decision of the current-order of the power battery for N number of stage Amount, using ampere-hour integral formula as state transition equation, by the Dynamic Programming Equation of the power loss Optimized model, full In the case where the foot constraint condition, the Optimal Control Strategy of the mixed energy storage system can be obtained, is controlled according to the optimization System strategy controls the mixed energy storage system, can be realized the mixed energy storage system under the conditions of full working scope Minimum power loss.Wherein, the current-order is used to be arranged the size of current of the power battery.
The control device of mixed energy storage system provided by the invention, due to the power battery by establishing mixed energy storage system Power loss model and super capacitor power loss model, and damaged based on power battery power loss model and super capacitor power It consumes model and the function of mixed energy storage system is established with the minimum target of power loss of mixed energy storage system under the conditions of full working scope Rate loss optimizing model is then based on dynamic programming algorithm and solves to power loss Optimized model, obtains hybrid energy-storing system The Optimal Control Strategy of system reduces the energy consumption of mixed energy storage system.
On the basis of the above embodiments, further, the power battery power loss model are as follows:
Wherein, Vp(k) the polarizing voltage value of the power battery described in the kth moment, V are indicatedp(k-1) it indicates at -1 moment of kth The polarizing voltage value of the power battery, k are positive integer, TsIndicate time step, e indicates natural constant, Ib(k) it indicates in kth The current value of power battery described in moment, Rp[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) pole under Change internal resistance value, SOC(k) state-of-charge of the power battery described in the kth moment, V are indicatedo(k) power described in the kth moment is indicated The terminal voltage value of battery, Vocv[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) open-circuit voltage values under, Ro[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) the ohmic internal resistance value under, Cp[SOC(k)] it indicates the Power battery described in the k moment is in current SOC(k) the polarization capacity value under, Pbat_loss(k) power electric described in the kth moment is indicated The loss power in pond;Vp(0)=0;
The super capacitor power loss model are as follows:
Puc_loss(k)=Iuc(k)2Ruc
Wherein, Vuc(k) open-circuit voltage values in kth moment super capacitor, V are indicateduc(k-1) it indicates in -1 moment of kth institute State the open-circuit voltage values of super capacitor, Iuc(k) current value of the super capacitor described in the kth moment, C are indicateducIt indicates in kth Carve the capacitance of the super capacitor, Vc(k) terminal voltage value of the super capacitor described in the kth moment, R are indicateducIndicate described super The internal resistance value of grade capacitor, Puc_loss(k) loss power of the super capacitor described in the kth moment is indicated;Vuc(0)=0.
Specifically, the power battery is in the polarizing voltage value at the 0th moment, i.e. the polarizing voltage value V of initial timep(0) =0, the polarizing voltage value V at kth momentp(k), recurrence formula can be passed throughIt obtains ?.The time step Ts, can be set to 1s.State-of-charge S of the power battery at the 0th momentOC(0) be it is given, Pass through ampere-hour integral formulaThe power battery can be obtained at the kth moment State-of-charge SOC(k)。Ib(k) it is arranged to the decision variable.Rp[SOC(k)] the polarization resistance value measured using laboratory with The relationship of the state-of-charge is found out, Vocv[SOC(k)] pass of the open-circuit voltage values and the state-of-charge measured using laboratory System finds out, Cp[SOC(k)] relationship of the polarization capacity value and the state-of-charge that are measured using laboratory is found out, Ro[SOC(k)] The relationship of the ohmic internal resistance value and the state-of-charge that are measured using laboratory is found out.Wherein, the mixed energy storage system is in institute Runing time under the conditions of full working scope is stated by discrete as N number of stage, N number of stage correspond to N+1 a time points.
The power battery is in the open-circuit voltage values at the 0th moment, i.e. the open-circuit voltage values V of initial timeuc(0)=0, kth The polarizing voltage value V at momentuc(k), recurrence formula can be passed throughIt obtains.Wherein, What the loss power of the super capacitor considered is loss caused by ohmic internal resistance.
On the basis of the above embodiments, further, the power loss Optimized model includes optimization object function, institute State optimization object function are as follows:
Wherein, Ploss(i)=Pbat_loss(i)+Puc_loss(i)+Pdd_loss(i), Ploss(i) it indicates to mix described in the i-th moment Close the loss power of energy-storage system, Pbat_loss(i) loss power of the power battery described in the i moment, P are indicateduc_loss(i) it indicates The loss power of the super capacitor described in the i-th moment, Pdd_loss(i) loss power in the i-th moment DC converter, i are indicated More than or equal to 0 and i is less than or equal to N-1, and N is the mixed energy storage system discrete rank of runing time under the conditions of the full working scope Number of segment.
Specifically, when establishing the power loss Optimized model, in order to more accurately calculate the mixed energy storage system Loss power, introduce the loss power of DC converter, the loss power of the mixed energy storage system is equal to the power electric The sum of the loss power in pond, the loss power of the super capacitor and loss power of the DC converter.Described in foundation Power loss Optimized model is the minimum value in order to obtain the mixed energy storage system loss power under the conditions of full working scope. Loss power P of the DC converter at the i-th momentdd_loss(i)=(1- η) Pbat(i), wherein η is the DC converting The energy conversion efficiency of device, PbatIt (i) is the output power of the power battery described in the i-th moment.
The embodiment of device provided by the invention specifically can be used for executing the process flow of above-mentioned each method embodiment, Details are not described herein for function, is referred to the detailed description of above method embodiment.
Fig. 5 is the entity structure schematic diagram of one embodiment of the invention electronic equipment, as shown in figure 5, the electronic equipment packet Include processor (processor) 501, memory (memory) 502 and communication bus 503;
Wherein, processor 501, memory 502 complete mutual communication by communication bus 503;
Processor 501 is used to call the program instruction in memory 502, to execute provided by above-mentioned each method embodiment Method, for example, establish the power battery power loss model and super capacitor power loss model of mixed energy storage system;Base In the power battery power loss model and the super capacitor power loss model, with the mixed energy storage system in full work The minimum target of power loss under the conditions of condition, establishes the power loss Optimized model of the mixed energy storage system;Based on dynamic Planning algorithm solves the power loss Optimized model, obtains the Optimal Control Strategy of the mixed energy storage system.
The present embodiment discloses a kind of computer program product, and the computer program product includes being stored in non-transient calculating Computer program on machine readable storage medium storing program for executing, the computer program include program instruction, when described program instruction is calculated When machine executes, computer is able to carry out method provided by above-mentioned each method embodiment, for example, establishes mixed energy storage system Power battery power loss model and super capacitor power loss model;Based on the power battery power loss model and institute Super capacitor power loss model is stated, with the minimum target of power loss of mixed energy storage system under the conditions of full working scope, Establish the power loss Optimized model of the mixed energy storage system;Based on dynamic programming algorithm to the power loss Optimized model It is solved, obtains the Optimal Control Strategy of the mixed energy storage system.
The present embodiment provides a kind of non-transient computer readable storage medium, the non-transient computer readable storage medium Computer instruction is stored, the computer instruction makes the computer execute method provided by above-mentioned each method embodiment, example It such as include: the power battery power loss model and super capacitor power loss model for establishing mixed energy storage system;Based on described Power battery power loss model and the super capacitor power loss model, with the mixed energy storage system in full working scope condition Under the minimum target of power loss, establish the power loss Optimized model of the mixed energy storage system;It is calculated based on Dynamic Programming Method solves the power loss Optimized model, obtains the Optimal Control Strategy of the mixed energy storage system.
In addition, the logical order in above-mentioned memory can be realized and as independence by way of SFU software functional unit Product when selling or using, can store in a computer readable storage medium.Based on this understanding, of the invention Technical solution substantially the part of the part that contributes to existing technology or the technical solution can be with software in other words The form of product embodies, which is stored in a storage medium, including some instructions use so that One computer equipment (can be personal computer, device or the network equipment etc.) executes described in each embodiment of the present invention The all or part of the steps of method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read- Only Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can be with Store the medium of program code.
The apparatus embodiments described above are merely exemplary, wherein described, unit can as illustrated by the separation member It is physically separated with being or may not be, component shown as a unit may or may not be physics list Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness Labour in the case where, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can It realizes by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on Stating technical solution, substantially the part that contributes to existing technology can be embodied in the form of software products in other words, should Computer software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation Method described in certain parts of example or embodiment.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations;Although Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features; And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and Range.

Claims (10)

1. a kind of control method of mixed energy storage system characterized by comprising
Establish the power battery power loss model and super capacitor power loss model of mixed energy storage system;
Based on the power battery power loss model and the super capacitor power loss model, with the mixed energy storage system The minimum target of power loss under the conditions of full working scope, establishes the power loss Optimized model of the mixed energy storage system;
The power loss Optimized model is solved based on dynamic programming algorithm, obtains the optimization of the mixed energy storage system Control strategy.
2. the method according to claim 1, wherein the power battery power loss model are as follows:
Wherein, Vp(k) the polarizing voltage value of the power battery described in the kth moment, V are indicatedp(k-1) it indicates described in -1 moment of kth The polarizing voltage value of power battery, k are positive integer, TsIndicate time step, e indicates natural constant, Ib(k) it indicates at the kth moment The current value of the power battery, Rp[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) in the polarization under Resistance value, SOC(k) state-of-charge of the power battery described in the kth moment, V are indicatedo(k) power battery described in the kth moment is indicated Terminal voltage value, Vocv[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) open-circuit voltage values under, Ro [SOC(k)] indicate the power battery described in the kth moment in current SOC(k) the ohmic internal resistance value under, Cp[SOC(k)] it indicates in kth Power battery described in moment is in current SOC(k) the polarization capacity value under, Pbat_loss(k) power battery described in the kth moment is indicated Loss power;Vp(0)=0;
The super capacitor power loss model are as follows:
Puc_loss(k)=Iuc(k)2Ruc
Wherein, Vuc(k) open-circuit voltage values in kth moment super capacitor, V are indicateduc(k-1) it indicates to surpass described in -1 moment of kth The open-circuit voltage values of grade capacitor, Iuc(k) current value of the super capacitor described in the kth moment, C are indicateducIt indicates in kth moment institute State the capacitance of super capacitor, Vc(k) terminal voltage value of the super capacitor described in the kth moment, R are indicateducIndicate the super electricity The internal resistance value of appearance, Puc_loss(k) loss power of the super capacitor described in the kth moment is indicated;Vuc(0)=0.
3. the method according to claim 1, wherein the power loss Optimized model includes optimization aim letter Number, the optimization object function are as follows:
Wherein, Ploss(i)=Pbat_loss(i)+Puc_loss(i)+Pdd_loss(i), Ploss(i) it indicates to mix storage described in the i-th moment The loss power of energy system, Pbat_loss(i) loss power of the power battery described in the i moment, P are indicateduc_loss(i) it indicates the The loss power of super capacitor described in the i moment, Pdd_loss(i) indicate that the loss power in the i-th moment DC converter, i are greater than Equal to 0 and i is less than or equal to N-1, and N is mixed energy storage system runing time discrete stage under the conditions of the full working scope Number.
4. the method according to claim 1, wherein the power loss Optimized model includes equality constraint With inequality constraints condition, in which:
The equality constraint are as follows:
Wherein, Puc(i) output power of the super capacitor described in the i-th moment, P are indicatedbd(i) it indicates in the i-th moment DC converting The on high-tension side output power of device, Preq(i) it indicates in the i-th moment load demand power, Pbat(i) it indicates to move described in the i-th moment The output power of power battery, PSIV(i) power in the i-th moment auxiliary power supply system, P are indicateddd_loss(i) it indicates at the i-th moment The loss power of the DC converter, i is integer and i is more than or equal to 0.
The inequality constraints condition are as follows:
Wherein, Ib_minIndicate the minimum value of the charging and discharging currents of the power battery, Ib(i) power described in the i-th moment is indicated The current value of battery, Ib_maxIndicate the maximum value of the charging and discharging currents of the power battery, Iuc_minIndicate the super capacitor The minimum value of charging and discharging currents, Iuc(i) current value of the super capacitor described in the i-th moment, I are indicateduc_maxIndicate the super electricity The maximum value of the charging and discharging currents of appearance, SOC_minIndicate the minimum value of the state-of-charge of power battery, SOC(i) it indicates at the i-th moment The state-of-charge of the power battery, SOC_maxIndicate the maximum value of the state-of-charge of power battery, Vuc_minIndicate described super The minimum value of the open-circuit voltage of capacitor, Vuc(i) open-circuit voltage values in the i-th moment super capacitor, V are indicateduc_maxIndicate described super The maximum value of the open-circuit voltage of grade capacitor, i is integer and i is more than or equal to 0.
5. the method according to claim 1, wherein described excellent to the power loss based on dynamic programming algorithm Change model to be solved, the Optimal Control Strategy for obtaining the mixed energy storage system includes:
The state-of-charge that the power battery is arranged is state variable, and the current-order of the power battery is arranged as decision change Amount, establishes following Dynamic Programming Equation:
Wherein, xi(k), i-th of state-of-charge in kth stage, u are indicatedj(k) j-th of current-order in kth stage, V (x are indicatedi (k), k) it is multistep objective function from the 0th stage to the kth stage, V (xj(k-1), k-1) it is from the 0th stage to -1 stage of kth Multistep objective function, J (xi(k), uj(k)) indicate the state variable from xj(k-1) x is changed toi(k) single step target when Function, M are the state-of-charge of the power battery from state-of-charge minimum value to discrete described charged of state-of-charge maximum value The quantity of state;N is the discrete number of stages of runing time under the conditions of the full working scope of the mixed energy storage system.
6. a kind of control device of mixed energy storage system characterized by comprising
First establishing unit, for establishing the power battery power loss model and super capacitor power loss of mixed energy storage system Model;
Second establishes unit, for being based on the power battery power loss model and the super capacitor power loss model, With the minimum target of power loss of mixed energy storage system under the conditions of full working scope, the function of the mixed energy storage system is established Rate loss optimizing model;
Unit is solved, for solving based on dynamic programming algorithm to the power loss Optimized model, obtains the mixing The Optimal Control Strategy of energy-storage system.
7. device according to claim 6, which is characterized in that the power battery power loss model are as follows:
Wherein, Vp(k) the polarizing voltage value of the power battery described in the kth moment, V are indicatedp(k-1) it indicates described in -1 moment of kth The polarizing voltage value of power battery, k are positive integer, TsIndicate time step, e indicates natural constant, Ib(k) it indicates at the kth moment The current value of the power battery, Rp[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) in the polarization under Resistance value, SOC(k) state-of-charge of the power battery described in the kth moment, V are indicatedo(k) power battery described in the kth moment is indicated Terminal voltage value, Vocv[SOC(k)] indicate the power battery described in the kth moment in current SOC(k) open-circuit voltage values under, Ro [SOC(k)] indicate the power battery described in the kth moment in current SOC(k) the ohmic internal resistance value under, Cp[SOC(k)] it indicates in kth Power battery described in moment is in current SOC(k) the polarization capacity value under, Pbat_loss(k) power battery described in the kth moment is indicated Loss power;Vp(0)=0;
The super capacitor power loss model are as follows:
Puc_loss(R)=Iuc(R)2Ruc
Wherein, Vuc(k) open-circuit voltage values in kth moment super capacitor, V are indicateduc(k-1) it indicates to surpass described in -1 moment of kth The open-circuit voltage values of grade capacitor, Iuc(k) current value of the super capacitor described in the kth moment, C are indicateducIt indicates in kth moment institute State the capacitance of super capacitor, Vc(k) terminal voltage value of the super capacitor described in the kth moment, R are indicateducIndicate the super electricity The internal resistance value of appearance, Puc_loss(k) loss power of the super capacitor described in the kth moment is indicated;Vuc(0)=0.
8. device according to claim 6, which is characterized in that the power loss Optimized model includes optimization aim letter Number, the optimization object function are as follows:
Wherein, Ploss(i)=Pbat_loss(i)+Puc_loss(i)+Pdd_loss(i), Ploss(i) it indicates to mix storage described in the i-th moment The loss power of energy system, Pbat_loss(i) loss power of the power battery described in the i moment, P are indicateduc_loss(f) it indicates the The loss power of super capacitor described in the i moment, Pdd_loss(i) indicate that the loss power in the i-th moment DC converter, i are greater than Equal to 0 and i is less than or equal to N-1, and N is mixed energy storage system runing time discrete stage under the conditions of the full working scope Number.
9. a kind of electronic equipment characterized by comprising processor, memory and communication bus, in which:
The processor and the memory complete mutual communication by the communication bus;
The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program to instruct energy It is enough to execute such as method described in any one of claim 1 to 5.
10. a kind of non-transient computer readable storage medium, which is characterized in that the non-transient computer readable storage medium is deposited Computer instruction is stored up, the computer instruction makes the computer execute such as method described in any one of claim 1 to 5.
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