CN110435631B - Energy supply control method and system - Google Patents
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- CN110435631B CN110435631B CN201910670777.1A CN201910670777A CN110435631B CN 110435631 B CN110435631 B CN 110435631B CN 201910670777 A CN201910670777 A CN 201910670777A CN 110435631 B CN110435631 B CN 110435631B
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- 230000007704 transition Effects 0.000 claims abstract description 17
- 238000005457 optimization Methods 0.000 claims description 10
- 230000000694 effects Effects 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 7
- 239000000446 fuel Substances 0.000 description 6
- 238000011217 control strategy Methods 0.000 description 4
- 239000003921 oil Substances 0.000 description 4
- 238000002485 combustion reaction Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 2
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/24—Conjoint control of vehicle sub-units of different type or different function including control of energy storage means
- B60W10/26—Conjoint control of vehicle sub-units of different type or different function including control of energy storage means for electrical energy, e.g. batteries or capacitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W20/00—Control systems specially adapted for hybrid vehicles
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Abstract
An energy supply control method and system comprises the following steps: acquiring energy supply working condition data, and dividing and processing the energy supply working condition data to obtain battery state change data; acquiring state transition path data, and processing battery state change data and state transition path data to obtain a path control variable; processing the path control variable to obtain stage energy consumption data; and acquiring the lowest total energy consumption according to the stage energy consumption data to obtain the optimized control data. The invention solves the technical problem of poor energy-saving effect in the prior art.
Description
Technical Field
The present invention relates to hybrid power control technologies, and in particular, to a method and a system for controlling energy supply.
Background
Hybrid vehicles have at least two power sources, typically one of which is an internal combustion engine and the other of which is a battery. To improve the economy of hybrid vehicles, various energy management strategies have emerged. The energy management strategy and the online optimization method in the prior art cannot obtain a global optimal solution, cannot fully exert the energy-saving potential of the hybrid electric vehicle, cannot obtain the optimal overall economy, do not consider the influence of the power loss of the motor, and cannot ensure the lowest comprehensive energy consumption of the power system at the selected engine working point.
In summary, the prior art has a technical problem of poor energy saving effect.
Disclosure of Invention
In view of the technical problems of the prior art, such as poor energy saving effect, the present invention provides an energy supply control method and system, to solve the technical problems of the prior art, such as poor energy saving effect, and the energy supply control method includes: acquiring energy supply working condition data, and dividing and processing the energy supply working condition data to obtain battery state change data; acquiring state transition path data, and processing battery state change data and state transition path data to obtain a path control variable; processing the path control variable to obtain stage energy consumption data; and acquiring the lowest total energy consumption according to the stage energy consumption data to obtain the optimized control data.
In one embodiment of the present invention, the step of calculating the path control variable includes: predetermined electrical lossesPower range data; calculating battery state change data according to the following formula to obtain battery power data PB:
Wherein, UOCIs the battery voltage, RiThe delta SOC is the battery change data for the power supply circuit resistance; according to the following formula and said battery power data PBElectric power loss range data, calculating an engine power range:
PENG+PB+Pout+Pacc+Ploss=0
wherein, PENGIs engine power, PoutPower, P, required for the whole vehicleaccTo power of electric accessory, PlossElectrical power loss; and calculating motor power data and battery power difference data according to the engine power range, and processing the data to obtain the path control variable.
In one embodiment of the present invention, the step of calculating the path control variable according to the motor power and the difference data includes: acquiring actual battery power and acquiring target battery power; calculating actual battery power and target battery power; the actual battery power is differed from the target battery power to obtain battery power difference data; acquiring a minimum difference value according to the battery power difference value data; and determining the path control variable corresponding to the minimum difference value as the path control variable.
In an embodiment of the present invention, the step of calculating the phase energy consumption data includes: and acquiring stage energy consumption data corresponding to the path control variable.
In one embodiment of the present invention, the step of calculating the optimized control data includes: calculating energy consumption data to obtain the lowest total energy consumption; and acquiring control data of the path corresponding to the lowest total energy consumption as an optimal control strategy.
In one embodiment of the present invention, a power supply control system includes: the variable processing device is used for acquiring energy supply working condition data and dividing and processing the energy supply working condition data to obtain battery state change data; the path processing unit is used for acquiring state transition path data, and processing the battery state change data and the state transition path data to obtain a path control variable; the energy consumption processing unit is used for processing the path control variable to obtain stage energy consumption data; and the optimization processor is used for acquiring the lowest total energy consumption according to the stage energy consumption data so as to obtain the optimized control data.
As described above, the present invention provides an energy supply control method and system to overcome the disadvantages of the prior art, and provides a method for determining an engine operating point, which considers the influence of the engine operating point on the motor loss, and in the dynamic programming method, for a certain transfer path of a State of Charge (SOC) in two adjacent stages, because the variation of the SOC is determined, a corresponding target battery power can be obtained.
In summary, the invention provides an energy supply control method and system, which solve the technical problem of poor energy saving effect in the prior art.
Drawings
Fig. 1 is a schematic diagram illustrating the steps of an energy supply control method according to the present invention.
FIG. 2 is a schematic diagram of the optimal fuel consumption line of the engine of the present invention.
Fig. 3 is a flowchart illustrating step S1 in fig. 1 in an embodiment.
Fig. 4 is a schematic diagram showing the SOC variation of the battery according to the present invention.
Fig. 5 is a flowchart illustrating step S24 in fig. 3 in an embodiment.
Fig. 6 is a flowchart illustrating step S4 in fig. 1 in an embodiment.
Fig. 7 is a schematic diagram showing the connection of the energy supply control system device of the invention.
Description of the element reference numerals
1 variable processing device
2-path processing unit
3 energy consumption processing unit
4 optimizing processor
Description of step designations
Method steps S1-S4
Method steps S21-S24
Method steps S241 to S245
Method steps S41-S42
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure.
Referring to fig. 1 to 7, it should be understood that the structures shown in the drawings are only used for understanding and reading the present disclosure, and are not used to limit the conditions of the present invention, which can be implemented, so that the present invention has no technical significance, and any structural modification, ratio change or size adjustment should still fall within the scope of the present invention without affecting the function and the achievable object of the present invention. In addition, the terms "upper", "lower", "left", "right", "middle" and "one" used in the present specification are for clarity of description, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not to be construed as a scope of the present invention.
Referring to fig. 1 and 2, there are shown schematic diagrams of steps of a power supply control method and an optimal fuel consumption line of an engine according to the present invention, as shown in fig. 1 and 2, a power supply control method includes:
and S1, acquiring energy supply working condition data, and dividing and processing the energy supply working condition data to obtain battery state change data. In one embodiment, the vehicle may have at least two power sources, typically one of which is an internal combustion engine and the other of which is a battery. Part of energy required by the running process of the vehicle comes from an internal combustion engine and converts chemical energy in fuel into mechanical energy; the other part is from a power battery, and the electric energy is converted into mechanical energy through a motor. In this embodiment, the State variable is a power battery SOC (State of Charge), the operating condition of the vehicle is divided into N stages according to time, an SOC value range and change data in two adjacent stages are determined according to constraint conditions such as a working interval and Charge/discharge capacity of the power battery, as shown in fig. 4;
and S2, acquiring the state transition path data, and processing the battery state change data and the state transition path data to obtain the path control variable. In the embodiment, a dynamic programming method is adopted for energy supply control strategy optimization. In the dynamic programming method, a plurality of transfer paths are arranged from the k stage to the k +1 stage of the state variable SOC, and for one transfer path, the corresponding target battery power P can be obtained according to the following formula because the variation of the SOC is determinedB:
In this embodiment, the battery is controlled to achieve the target power P according to the value of the control variableBAnd (4) running. The invention selects the working point (T) of the enginee,ne) For the control variable, the method for determining the value of the control variable is as follows:
presetting electric loss power range data;
obtaining the power range [ P ] of the engine through the power balance relation of the whole vehicleENG_min,PENG_max];
Selecting P on the optimal oil consumption line of the engineENG_min,PENG_max]Points within the range are taken as allowable values of the control variable;
calculating working points and respective powers of the two motors according to the relationship between system dynamics and kinematics;
calculating the battery power P of each pointB_cal(ii) And with the battery target power PBThe difference of (a):
ΔP(ii)=abs(PB_cal(ii)-PB)
selecting the engine working point which enables the minimum delta P (ii) to be used as a control variable value corresponding to the state transition path;
and S3, obtaining stage energy consumption data according to the path control variables.
And acquiring stage energy consumption data corresponding to the path control variables, and in one embodiment, calculating the whole vehicle energy consumption of the path from the SOC (i, k) to the SOC (j, k +1), namely the energy consumption of the k-th stage on the path. The cost function of each stage is mainly the comprehensive energy consumption of the whole vehicle, and in addition, in order to protect the battery, avoid the severe fluctuation of the SOC, the SOC penalty function is increased. L (k) ═ Lfuel(k)+Lelec(k)+LSOC(k) Wherein L isfuel(k)、Lelec(k)、LSOC(k) Respectively representing the engine oil consumption, the equivalent oil consumption by electric energy and a penalty function of SOC variation;
LSOC(k)=w1·ΔSOC(k)2
in the formula, s is an equivalent factor; qlhvIs the lower heating value of the engine fuel; w is a1And penalizing the function weight coefficient for the change of the SOC of the battery.
And S4, determining the lowest total energy consumption according to the stage energy consumption data to obtain the optimized control data. In this embodiment, after the values of the path control variables are determined, the cost function values corresponding to all the transfer paths between the kth stage and the (k +1) th stage and the overall objective function value from the nth stage to the kth stage may be calculated.
In this embodiment, the overall goal of the energy management strategy is to minimize the total energy consumption for the entire operating regime, i.e., the sum of the cost functions for each phase.
The total energy consumption of the whole working condition is the sum of the energy consumptions of all stages:
thus, the overall objective function is:
the calculation is performed from the Nth stage in the reverse order until the 1 st stage. And selecting the minimum value of the overall objective function in the stage k being 1, namely the minimum value of the total energy consumption, wherein the corresponding state transition path is the optimal control strategy, and the corresponding state variable value is the optimal track.
Referring to fig. 3 and 4, which are a detailed flowchart and a schematic diagram of the battery SOC variation in an embodiment of step S2 in fig. 1, as shown in fig. 3 and 4, the step S2 of calculating the path control variable includes:
s21, presetting electric loss power range data;
s22, calculating the battery state change data according to the following formula to obtain the battery power data PB:
Wherein, UOCIs the open circuit voltage of the battery, RiΔ SOC is the battery SOC variation, which is the battery resistance.
x(k+1)=f(x(k),u(k)) k=1,2,3,...,N
Wherein,
x(k)={SOC(k)},
u(k)={Te(k),ne(k) in one embodiment, since the power of the battery is determined by the operating points of the engine and the motor and cannot be directly controlled, the latter method is to control the engine and the motor to operate the battery at the target power;
s23, according to the following formula and the battery power data PBCalculating the power of the engine based on the power loss and power range dataRate range:
PENG+PB+Pout+Pacc+Ploss=0
wherein, PENGIs engine power, PoutPower, P, required for the whole vehicleaccTo power of electric accessory, PlossFor the electric power loss, in one embodiment, the target battery power P is calculated from the foregoing steps according to the power balance relationship of the hybrid electric vehicleBAnd the vehicle driving power P is knownoutAnd electric accessory power PaccAccording to the above formula, if the power P is electrically lostlossIf known, the engine power PENGAre also available. In one embodiment, for a hybrid powertrain, the operating point of the electric machine varies with the operating point of the engine, and different engine operating points will result in different electrical losses. Thus, the electrical power loss [0, P ] is presetloss_max]The power range [ P ] of the engine can be obtained according to the power balance relationENG_min,PENG_max];
S24, calculating the motor power data and the battery power difference data according to the engine power range, and processing the data to obtain the path control variable, wherein in one embodiment, the path control variable is used for each engine working point (n)e(ii),Te(ii) The operating point of the motor can be determined from the system dynamics and kinematics relationships, and the motor power can be calculated.
Referring to fig. 5, which is a detailed flowchart of step S24 in fig. 3 according to an embodiment, as shown in fig. 5, step S24 includes:
and S241, calculating the power of the motor, and taking the working point of the engine on the optimal oil consumption line of the engine according to the power range of the engine obtained in the step. In one embodiment, for each engine operating point (n)e(ii),Te(ii) The working point of the motor can be determined according to the system dynamics and the kinematic relation, and the motor power can be calculated;
s242, acquiring the actual battery power by taking the working point of the engine on the optimal oil consumption line of the engine;
s243, subtracting the actual battery power from the target battery power to obtain battery power difference data, in this embodiment, the working state of the entire power system is completely determined, and the actual battery power P corresponding to each engine working point can be calculatedB_cal(ii) And its difference from the target value: Δ P (ii) abs (P)B_cal(ii)-PB);
S244, acquiring a minimum difference value according to the battery power difference value data;
s245, determining the path control variable corresponding to the minimum difference as the path control variable, in this embodiment, selecting the engine operating point with the minimum Δ p (ii) as the state transition path, i.e. the control variable value corresponding to the SOC (i, k) to SOC (j, k + 1).
Referring to fig. 6, which is a detailed flowchart illustrating step S4 in fig. 1 according to an embodiment, as shown in fig. 6, the step S4 of calculating the optimized control data includes:
s41, calculating the energy consumption data to obtain the lowest total energy consumption, in this embodiment, calculating the cumulative energy consumption from the nth stage to the kth stage until k is 1. The overall goal of the energy management strategy is to minimize the total energy consumption of the whole working condition, i.e. the sum of the cost functions of each stage is minimum;
the total energy consumption of the whole working condition is the sum of the energy consumptions of all stages:
thus, the overall objective function is:
and S42, acquiring the control data of the path corresponding to the lowest total energy consumption as the optimized control data. In this embodiment, the SOC path with the lowest total energy consumption is the optimal trajectory, and the control variable value corresponding to the path is the optimal control strategy.
Referring to fig. 7, which is a schematic diagram showing a connection of the energy supply control system device of the present invention, as shown in fig. 7, an energy supply control system includes a variable processing device 1, a path processing unit 2, an energy consumption processing unit 3, and an optimization processor 4, where the variable processing device 1 is configured to obtain energy supply condition data, and divide and process the energy supply condition data to obtain battery state change data; the path processing unit 2 is used for acquiring state transition path data, processing the battery state change data and the state transition path data to obtain a path control variable, and the path processing unit 2 is connected with the variable processing device 1; the energy consumption processing unit 3 is used for processing the path control variable to obtain stage energy consumption data and is connected with the path processing unit 2; and the optimization processing unit 4 is used for acquiring the lowest total energy consumption according to the stage energy consumption data so as to obtain the optimization control data, and the optimization processing unit 4 is connected with the energy consumption processing unit 3.
In conclusion, the energy supply control method and the energy supply control system provided by the invention comprehensively consider the influence of the working point of the engine on the power loss of the motor, and the obtained energy management strategy can ensure that the comprehensive energy consumption of the whole vehicle is the lowest; when the allowable control set is determined, the method reduces the calculation amount of the selection of the working point of the engine and improves the calculation efficiency.
In summary, the invention provides an energy supply control method and system, which solve the technical problem of poor energy saving effect in the prior art.
Claims (4)
1. An energy supply control method, comprising:
acquiring energy supply working condition data, and dividing and processing the energy supply working condition data to obtain battery state change data;
acquiring state transition path data, and processing the battery state change data and the state transition path data to obtain a path control variable;
processing the path control variable to obtain stage energy consumption data;
acquiring the lowest total energy consumption according to the stage energy consumption data to obtain optimized control data;
the step of calculating the path control variables includes:
presetting electric loss power range data;
calculating the battery state change data according to the following formula to obtain battery power data PB:
Wherein, UOCIs the battery voltage, RiThe delta SOC is the battery change data for the power supply circuit resistance;
according to the following formula and said battery power data PBElectric power loss range data, calculating an engine power range:
PENG+PB+Pout+Pacc+Ploss=0
wherein, PENGIs engine power, PoutPower, P, required for the whole vehicleaccTo power of electric accessory, PlossElectrical power loss;
calculating motor power data and battery power difference data according to the engine power range, and processing the path control variable according to the motor power data and the battery power difference data to obtain the path control variable, wherein the path control variable comprises the following steps:
calculating the power of the motor according to the power range of the engine obtained in the previous step;
acquiring the actual battery power by taking the working point of the engine on the optimal oil consumption line of the engine;
the actual battery power is differed from the target battery power to obtain battery power difference data;
acquiring a minimum difference value according to the battery power difference value data;
and determining the path control variable corresponding to the minimum difference value as the path control variable.
2. The method of claim 1, wherein the step of calculating stage energy consumption data comprises:
and acquiring stage energy consumption data corresponding to the path control variable.
3. The method of claim 1, wherein the step of calculating the optimized control data comprises:
calculating the stage energy consumption data to obtain the lowest total energy consumption;
and acquiring path corresponding data according to the lowest total energy consumption to serve as optimization control data.
4. An energy supply control system, comprising:
the variable processing device is used for acquiring energy supply working condition data and dividing and processing the energy supply working condition data to obtain battery state change data;
the path processing unit is used for acquiring state transition path data and processing the battery state change data and the state transition path data to obtain a path control variable;
the energy consumption processing unit is used for processing the path control variable to obtain stage energy consumption data;
the optimization processor is used for obtaining the lowest total energy consumption according to the stage energy consumption data so as to obtain the optimization control data;
the step of calculating the path control variables includes:
presetting electric loss power range data;
calculating the battery state change data according to the following formula to obtain battery power data PB:
Wherein, UOCIs the battery voltage, RiThe delta SOC is the battery change data for the power supply circuit resistance;
according to the following formula and said battery power data PBElectric power loss range data, calculating an engine power range:
PENG+PB+Pout+Pacc+Ploss=0
wherein, PENGIs engine power, PoutPower, P, required for the whole vehicleaccTo power of electric accessory, PlossElectrical power loss;
calculating motor power data and battery power difference data according to the engine power range, and processing the path control variable according to the motor power data and the battery power difference data to obtain the path control variable, wherein the path control variable comprises the following steps:
calculating the power of the motor, and obtaining the power range of the engine according to the steps;
acquiring the actual battery power by taking the working point of the engine on the optimal oil consumption line of the engine;
the actual battery power is differed from the target battery power to obtain battery power difference data;
acquiring a minimum difference value according to the battery power difference value data;
and determining the path control variable corresponding to the minimum difference value as the path control variable.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101602364A (en) * | 2008-12-31 | 2009-12-16 | 宾洋 | Be applied to the quick DP control method of PHEV |
CN102069804A (en) * | 2010-12-25 | 2011-05-25 | 浙江吉利汽车研究院有限公司 | Predictive control method for running state of hybrid power automobile |
CN103600742A (en) * | 2013-12-03 | 2014-02-26 | 北京交通大学 | Energy management control device of hybrid electric vehicle and method for energy management control |
CN107878445A (en) * | 2017-11-06 | 2018-04-06 | 吉林大学 | A kind of energy-optimised management method of hybrid vehicle for considering cell performance decay |
WO2018209038A1 (en) * | 2017-05-12 | 2018-11-15 | Ohio State Innovation Foundation | Real-time energy management strategy for hybrid electric vehicles with reduced battery aging |
CN108909702A (en) * | 2018-08-23 | 2018-11-30 | 北京理工大学 | A kind of plug-in hybrid-power automobile energy management method and system |
CN109017809A (en) * | 2018-08-27 | 2018-12-18 | 北京理工大学 | A kind of energy distributing method based on the prediction of cross-country operating condition |
CN109031946A (en) * | 2018-05-07 | 2018-12-18 | 中车工业研究院有限公司 | A kind of control method and device of mixed energy storage system |
-
2019
- 2019-07-23 CN CN201910670777.1A patent/CN110435631B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101602364A (en) * | 2008-12-31 | 2009-12-16 | 宾洋 | Be applied to the quick DP control method of PHEV |
CN102069804A (en) * | 2010-12-25 | 2011-05-25 | 浙江吉利汽车研究院有限公司 | Predictive control method for running state of hybrid power automobile |
CN103600742A (en) * | 2013-12-03 | 2014-02-26 | 北京交通大学 | Energy management control device of hybrid electric vehicle and method for energy management control |
WO2018209038A1 (en) * | 2017-05-12 | 2018-11-15 | Ohio State Innovation Foundation | Real-time energy management strategy for hybrid electric vehicles with reduced battery aging |
CN107878445A (en) * | 2017-11-06 | 2018-04-06 | 吉林大学 | A kind of energy-optimised management method of hybrid vehicle for considering cell performance decay |
CN109031946A (en) * | 2018-05-07 | 2018-12-18 | 中车工业研究院有限公司 | A kind of control method and device of mixed energy storage system |
CN108909702A (en) * | 2018-08-23 | 2018-11-30 | 北京理工大学 | A kind of plug-in hybrid-power automobile energy management method and system |
CN109017809A (en) * | 2018-08-27 | 2018-12-18 | 北京理工大学 | A kind of energy distributing method based on the prediction of cross-country operating condition |
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