CN117375171A - Micro-energy operation algorithm - Google Patents
Micro-energy operation algorithm Download PDFInfo
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- CN117375171A CN117375171A CN202311378167.7A CN202311378167A CN117375171A CN 117375171 A CN117375171 A CN 117375171A CN 202311378167 A CN202311378167 A CN 202311378167A CN 117375171 A CN117375171 A CN 117375171A
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- 238000004146 energy storage Methods 0.000 claims abstract description 74
- 239000003990 capacitor Substances 0.000 claims abstract description 47
- 230000002093 peripheral effect Effects 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims abstract description 7
- 241000282577 Pan troglodytes Species 0.000 claims description 25
- 230000008602 contraction Effects 0.000 claims description 15
- 238000007599 discharging Methods 0.000 claims description 12
- 238000005457 optimization Methods 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 8
- 230000000739 chaotic effect Effects 0.000 claims description 6
- 230000006835 compression Effects 0.000 claims description 4
- 238000007906 compression Methods 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 4
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 230000003068 static effect Effects 0.000 claims description 4
- 230000005611 electricity Effects 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0068—Battery or charger load switching, e.g. concurrent charging and load supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
- H02J7/00036—Charger exchanging data with battery
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/007—Regulation of charging or discharging current or voltage
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/007—Regulation of charging or discharging current or voltage
- H02J7/00712—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters
- H02J7/007182—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters in response to battery voltage
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/345—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering using capacitors as storage or buffering devices
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2207/00—Indexing scheme relating to details of circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J2207/50—Charging of capacitors, supercapacitors, ultra-capacitors or double layer capacitors
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention relates to the technical field of electricity, in particular to a micro-energy operation algorithm, which comprises the following steps: s1: the MCU is in a non-electric state, the system charges the energy storage capacitor, and energy obtained in the charging stage is calculated; s2: initializing an MCU, reading discharge voltage in the initialization stage, and acquiring an optimal value of the discharge voltage according to the running time and the running power consumption of the MCU; s3: MCU operates, records each operation time through a low power consumption timer and calculates accumulated consumed energy; and switching states of the MCU and the peripheral circuit according to the accumulated consumption energy value. According to the invention, through the energy algorithm of the MCU, the rapid starting is realized under the condition of the minimum energy storage capacity without increasing extra hardware cost and consuming extra current, and the initialization and working state after the starting are combined with the charge and discharge characteristics to determine the awakening and working time. The method realizes faster starting speed and extremely low starting current of the industrial alternating current passive wireless sensor.
Description
Technical Field
The invention relates to the technical field of electricity, in particular to a micro-energy operation algorithm.
Background
In order to meet the requirements of system initialization and power consumption during operation, a conventional micro-energy collection system uses a larger energy storage capacitor or super capacitor, so that a long time is required to charge the energy storage system under the condition that the energy storage system is completely unpowered. When the charging of the energy storage system is completed, the energy storage capacitor has very small voltage fluctuation because of very large capacity when the system runs, and the MCU can be maintained to enter low power consumption after the initialization is completed. But a cold start time of several tens of minutes or even hours brings about a bad use experience and a lengthy cold start time.
When a smaller energy storage capacitor is used, although the voltage rises quickly at the time of starting, the voltage drops quickly once the MCU starts to operate and initialize, and the MCU is easily reset.
The low power consumption system also greatly limits the working current of each circuit of the system, and adding additional circuits to the system operation often brings about hundreds of uA of current, which is unacceptable power consumption for micro-energy sensors with average current to be controlled within 10 uA.
Disclosure of Invention
The present invention aims to solve the above-mentioned drawbacks of the background art by proposing a micro-energy operation algorithm.
The technical scheme adopted by the invention is as follows:
a micro-energy operation algorithm is provided, comprising the steps of:
s1: the MCU is in a non-electric state, the system charges the energy storage capacitor, and energy obtained in the charging stage is calculated;
s2: initializing an MCU, reading discharge voltage in the initialization stage, and acquiring an optimal value of the discharge voltage according to the running time and the running power consumption of the MCU;
s3: MCU operates, records each operation time through a low power consumption timer and calculates accumulated consumed energy; and switching states of the MCU and the peripheral circuit according to the accumulated consumption energy value.
As a preferred technical scheme of the invention: the charging process of the capacitor in S1 is calculated as follows:
F*U＝I*T
wherein F is the capacity of the energy storage capacitor, U is the charging or discharging variable voltage on the energy storage capacitor, I is the charging or discharging current of the energy storage capacitor, and T is the charging or discharging time;
as a preferred technical scheme of the invention: in the step S1, the voltage on the energy storage capacitor is judged through the voltage detection chip, and when the voltage of the energy storage capacitor rises to the starting voltageThen, the voltage detection chip starts a rear-end power supply circuit, and the power supply chip with low static power consumption supplies power to the MCU at the rear end; wherein the voltage of the energy storage capacitor rises to the starting voltage +.>The energy obtained by MCU in the charging phase of (2) is +.>
As a preferred technical scheme of the invention: in S2, after the MCU obtains the voltage for the first time and operates, the initialization code is operated, and the discharge voltage in the initialization stage is read to be changed intoObtaining an optimal value between the runtime and the MCU running power consumption based on an improved chimpanzee optimization algorithm such that +.>
As a preferred technical scheme of the invention: the improved chimpanzee optimization algorithm is specifically as follows:
D＝|WX o (t)-HX s (t)|
X s (t+1)＝X s (t)-Q·D
wherein D is the distance between the chimpanzee and the preyFrom W, Q is coefficient vector, H is chaos vector generated by chaos mapping, X o (t) is the t iteration prey position vector, X s (t) chimpanzee position vector, X, for the t-th iteration s (t+1) is the chimpanzee position vector for the t+1st iteration;
Q＝2f·r 1 -f
W＝2r 2
wherein f is a convergence constraint, r 1 、r 2 Are all [0,1 ]]A random number therebetween;
wherein τ is the maximum number of iterations;
obtaining the fitness values of all chimpanzee individuals in the population, and sequencing to obtain a corresponding optimal solution X A Suboptimal solution X B And the worst point X C Center point X S Set as the optimal solution X A And suboptimal solution X B Center position of the room:
for the worst point X C And (3) reflecting:
X K ＝X S +δ(X S -X C )
wherein X is K Is a reflection point, delta is a reflection coefficient;
if f (X) K )＜f(X C ) At the time of reflection point X K Instead of the worst point X C Expanding to obtain an expansion point X L ：
X L ＝X S +ε(X K -X S )
Wherein epsilon is the expansion coefficient;
if f (X) L )＜f(X K ) Expansion point X L Instead of the worst point X C Expanding otherwise using reflection point X K Instead of the worst point X C Generating a new simplex, and performing the next iteration;
if f (X) C )＜f(X K ) In this case, the outer shrinkage is performed to obtain an outer shrinkage point X G ：
Wherein,is the external contraction coefficient;
if f (X) A )＜f(X K )＜f(X C ) Performing internal contraction to obtain an internal contraction point X g ；
X g ＝X S +ρ(X C -X s )
Wherein ρ is the internal shrinkage factor;
if f (X) g )＜f(X C ) Or f (X) G )＜f(X C ) Then use compression point X G Or X g Instead of the worst point X C Otherwise using reflection point X K Instead of the worst point.
As a preferred technical scheme of the invention: the initialization code is used for setting all IO states and levels to be correct states and reading parameters.
As a preferred technical scheme of the invention: in the step S3, the fixed running time and running current of each task are obtained, and the running time of each task is recorded by using a low-power-consumption timer for the task with the running time changing along with the external condition.
As a preferred technical scheme of the invention: in the S3, the consumed energy of the xth task operation stage is recorded as follows The following are satisfied in each discharge period:
when n tasks accumulate and consume energyWhen the MCU suspends the operation of the following tasks, the MCU and the peripheral circuit are set to enter a sleep state, and the current consumed by the system is +.>The system enters an energy storage stage for energy storage.
As a preferred technical scheme of the invention: in the energy storage stage, the voltage value increased by the energy storage capacitor isThe energy storage time of the system is as follows:
wherein T is NP The energy storage time of the system;
time T of storing energy of system NP And setting the wake-up time of low-power wake-up, and enabling the MCU to wake up to continue running tasks after the energy storage stage is completed.
As a preferred technical scheme of the invention: when the system detects that the starting voltage is larger than the margin energy storage starting voltage, the MCU starts the margin energy charging circuit, and the system charges redundant energy of the energy storage capacitor to the super capacitor for secondary storage.
Compared with the prior art, the micro-energy operation algorithm provided by the invention has the beneficial effects that:
according to the invention, through the energy algorithm of the MCU, the rapid starting is realized under the condition of the minimum energy storage capacity without increasing extra hardware cost and consuming extra current, and the initialization and working state after the starting are combined with the charge and discharge characteristics to determine the awakening and working time. The method realizes faster starting speed and extremely low starting current of the industrial alternating current passive wireless sensor.
Drawings
FIG. 1 is a flowchart of an algorithm of a preferred embodiment of the present invention;
fig. 2 is a diagram showing a system operation voltage variation test in a preferred embodiment of the present invention.
Detailed Description
It should be noted that, under the condition of no conflict, the embodiments of the present embodiments and features in the embodiments may be combined with each other, and the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and obviously, the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a preferred embodiment of the present invention provides a micro-energy operation algorithm comprising the steps of:
s1: the MCU is in a non-electric state, the system charges the energy storage capacitor, and energy obtained in the charging stage is calculated;
s2: initializing an MCU, reading discharge voltage in the initialization stage, and acquiring an optimal value of the discharge voltage according to the running time and the running power consumption of the MCU;
s3: MCU operates, records each operation time through a low power consumption timer and calculates accumulated consumed energy; and switching states of the MCU and the peripheral circuit according to the accumulated consumption energy value.
The charging process of the capacitor in S1 is calculated as follows:
F*U＝I*T
wherein F is the capacity of the energy storage capacitor, U is the charging or discharging variable voltage on the energy storage capacitor, I is the charging or discharging current of the energy storage capacitor, and T is the charging or discharging time;
in the step S1, the voltage on the energy storage capacitor is judged through the voltage detection chip, and when the voltage of the energy storage capacitor rises to the starting voltageThen, the voltage detection chip starts a rear-end power supply circuit, and the power supply chip with low static power consumption supplies power to the MCU at the rear end; wherein the voltage of the energy storage capacitor rises to the starting voltage +.>The energy obtained by MCU in the charging phase of (2) is +.>
In S2, after the MCU obtains the voltage for the first time and operates, the initialization code is operated, and the discharge voltage in the initialization stage is read to be changed intoObtaining an optimal value between runtime and MCU operational power consumption based on an improved chimpanzee optimization algorithm such that
The improved chimpanzee optimization algorithm is specifically as follows:
D＝|WX o (t)-HX s (t)|
X s (t+1)＝X s (t)-Q·D
wherein D is the distance between the chimpanzee and the prey, W, Q is the coefficient vector, H is the chaotic vector generated by chaotic mapping, and X o (t) is the t iteration prey position vector, X s (t) chimpanzee position vector, X, for the t-th iteration s (t+1) is the chimpanzee position vector for the t+1st iteration;
Q＝2f·r 1 -f
W＝2r 2
wherein f is a convergence constraint, r 1 、r 2 Are all [0,1 ]]A random number therebetween;
wherein τ is the maximum number of iterations;
obtaining the fitness values of all chimpanzee individuals in the population, and sequencing to obtain a corresponding optimal solution X A Suboptimal solution X B And the worst point X C Center point X S Set as the optimal solution X A And suboptimal solution X B Center position of the room:
for the worst point X C And (3) reflecting:
X K ＝X S +δ(X S -X C )
wherein X is K Is a reflection point, delta is a reflection coefficient;
if f (X) K )＜f(X C ) At the time of reflection point X K Instead of the worst point X C Expanding to obtain an expansion point X L ：
X L ＝X S +ε(X K -X S )
Wherein epsilon is the expansion coefficient;
if f (X) L )＜f(X K ) Expansion point X L Instead of the worst point X C Expanding otherwise using reflection point X K Instead of the worst point X C Generating a new simplex, and performing the next iteration;
if f (X) C )＜f(X K ) In this case, the outer shrinkage is performed to obtain an outer shrinkage point X G ：
Wherein,is the external contraction coefficient;
if f (X) A )＜f(X K )＜f(X C ) Performing internal contraction to obtain an internal contraction point X g ；
X g ＝X S +ρ(X C -X S )
Wherein ρ is the internal shrinkage factor;
if f (X) g )＜f(X C ) Or f (X) G )＜f(X C ) Then use compression point X G Or X g Instead of the worst point X C Otherwise using reflection point X K Instead of the worst point.
The initialization code is used for setting all IO states and levels to be correct states and reading parameters.
In the step S3, the fixed running time and running current of each task are obtained, and the running time of each task is recorded by using a low-power-consumption timer for the task with the running time changing along with the external condition.
In the S3, the consumed energy of the xth task operation stage is recorded as followsThe following are satisfied in each discharge period:
when n tasks accumulate and consume energyWhen the MCU suspends the operation of the following tasks, the MCU and the peripheral circuit are set to enter a sleep state, and the current consumed by the system is +.>The system enters an energy storage stage for energy storage.
In the energy storage stage, the voltage value increased by the energy storage capacitor isThe energy storage time of the system is as follows:
wherein T is NP The energy storage time of the system;
time T of storing energy of system NP And setting the wake-up time of low-power wake-up, and enabling the MCU to wake up to continue running tasks after the energy storage stage is completed.
When the system detects that the starting voltage is larger than the margin energy storage starting voltage, the MCU starts the margin energy charging circuit, and the system charges redundant energy of the energy storage capacitor to the super capacitor for secondary storage.
In this embodiment, the start-up phase:
and starting the MCU, wherein the MCU is completely powered off, the system charges the energy storage capacitor, and the voltage on the energy storage capacitor is judged by the voltage detection chip. When the voltage of the energy storage capacitor rises to the starting voltageAnd then, the voltage detection chip starts a rear-end power supply circuit, and the power supply chip with low static power consumption supplies power to the MCU at the rear end.
Energy obtained during the charging phaseCalculation of
The charging process of the energy storage capacitor is calculated according to the following formula:
F*U＝I*T
wherein F is the capacity of the energy storage capacitor, U is the charging or discharging variable voltage on the energy storage capacitor, I is the charging or discharging current of the energy storage capacitor, and T is the charging or discharging time;
an initialization stage:
after the MCU obtains the voltage for the first time and operates, an initialized code must be operated, including setting all IO states and levels to be correct states and reading parameters. Discharge voltage at the read initialization stageIs changed intoThe chimpanzee optimization algorithm is improved to take an optimal value between the operation time and the MCU operation power consumption, so that the system has rich electricity after initialization is finished and can support the following operation state. Here, engineering experience values are taken: />
The improved chimpanzee optimization algorithm is as follows:
D＝|WX o (t)-HX s (t)|
X s (t+1)＝X s (t)-Q·D
wherein D is the distance between the chimpanzee and the prey, W, Q is the coefficient vector, H is the chaotic vector generated by chaotic mapping, and X o (t) is the t iteration prey position vector, X s (t) chimpanzee position vector, X, for the t-th iteration s (t+1) is the chimpanzee position vector for the t+1st iteration;
Q＝2f·r 1 -f
W＝2r 2
wherein f is a convergence constraint, r 1 、r 2 Are all [0,1 ]]A random number therebetween;
wherein τ is the maximum number of iterations;
obtaining the fitness values of all chimpanzee individuals in the population, and sequencing to obtain a corresponding optimal solution X A Suboptimal solution X B And the worst point X C Center point X S Set as centroid position of vertex except worst point, i.e. optimal solution X A And suboptimal solution X B Center position of the room:
for the worst point X C And (3) reflecting:
X K ＝X S +δ(X s -X C )
wherein X is K The delta is a reflection coefficient, and the value of delta is 1;
if f (X) K )＜f(X C ) At the time of reflection point X K Instead of the worst point X C Expanding to obtain an expansion point X L ：
X L ＝X s +ε(X K -X s )
Wherein epsilon is an expansion coefficient and can take a value of 2;
if f (X) L )＜f(X K ) Expansion point X L Instead of the worst point X C Expanding otherwise using reflection point X K Instead of the worst point X C Generating a new simplex, and performing the next iteration;
if f (X) C )＜f(X K ) In this case, the outer shrinkage is performed to obtain an outer shrinkage point X G ：
Wherein,the external contraction coefficient can be 0.5;
if f (X) A )＜f(X K )＜f(X C ) Performing internal contraction to obtain an internal contraction point X g ；
X g ＝X S +ρ(X C -X S )
Wherein ρ is an internal contraction coefficient, and the value is 0.5;
if f (X) g )＜f(X C ) Or f (X) G )＜f(X C ) Then use compression point X G Or X g Instead of the worst point X C Otherwise using reflection point X K Instead of the worst point.
The worst individual position is improved by carrying out reflection, expansion, external contraction and internal contraction operations on worst individuals in the population through simplex, the phenomenon of 'precocity' of the algorithm can be avoided by improving a chimpanzee optimization algorithm, the global searching capability and the local exploring capability of the algorithm are balanced, the optimal value between the running time and the running power consumption of the MCU is obtained, and the running control performance of the MCU is conveniently improved.
And (3) an operation stage:
a fixed run time and run current may be obtained for each task determined. The low power timer is used to record each run time for tasks whose run time varies with external conditions.
The energy consumed in the operation stage of the xth task is as follows
Requiring that in one charge-discharge cycle
When the accumulated consumed energy of n tasks reachesWhen the MCU suspends the operation of the following tasks, the MCU and the peripheral circuit are set to enter a sleep state, and the current consumed by the system is +.>The system enters an energy storage stage for energy storage.
Energy storage stage:
MCU calculates the voltage value required to be increased in the energy storage capacitorBy->The energy storage time required by the system is calculated as follows:
wherein T is NP The energy storage time of the system;
and setting the energy storage time as the wake-up time of low-power wake-up, and enabling the MCU to wake up to continue running tasks after the energy storage phase is completed.
When the system detects that the starting voltage is larger than the margin energy storage starting voltage, the MCU starts the margin energy charging circuit, and the system charges redundant energy of the energy storage capacitor to the super capacitor for secondary storage.
Referring to fig. 2, it can be seen that the voltage after the system is started does not operate in a conventional manner by keeping the input voltage fluctuation relatively smooth, but rather determines the time point of operation and the operation duration by an algorithm. Although the voltage at the front end has large fluctuation, the power chip can output stable voltage to the MCU after voltage stabilization, so that the MCU is ensured not to reset because the voltage is lower than the minimum working voltage due to overlarge energy consumption.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (10)
1. A micro-energy operation algorithm, characterized by: the method comprises the following steps:
s1: the MCU is in a non-electric state, the system charges the energy storage capacitor, and energy obtained in the charging stage is calculated;
s2: initializing an MCU, reading discharge voltage in the initialization stage, and acquiring an optimal value of the discharge voltage according to the running time and the running power consumption of the MCU;
s3: MCU operates, records each operation time through a low power consumption timer and calculates accumulated consumed energy; and switching states of the MCU and the peripheral circuit according to the accumulated consumption energy value.
2. The micro-energy operation algorithm of claim 1, wherein: the charging process of the capacitor in S1 is calculated as follows:
F*U＝I*T
wherein F is the capacity of the energy storage capacitor, U is the charging or discharging variable voltage on the energy storage capacitor, I is the charging or discharging current of the energy storage capacitor, and T is the charging or discharging time;
3. the micro-energy operation algorithm of claim 2, wherein: in the step S1, the voltage on the energy storage capacitor is judged through the voltage detection chip, and when the voltage of the energy storage capacitor rises to the starting voltageThen, the voltage detection chip starts a rear-end power supply circuit, and the power supply chip with low static power consumption supplies power to the MCU at the rear end; wherein the voltage of the energy storage capacitor rises to the starting voltage +.>The energy obtained by MCU in the charging phase of (2) is +.>
4. A micro-energy operation algorithm according to claim 3, characterized in that: in S2, after the MCU obtains the voltage for the first time and operates, the initialization code is operated, and the discharge voltage in the initialization stage is read to be changed intoObtaining an optimal value between the runtime and the MCU running power consumption based on an improved chimpanzee optimization algorithm such that +.>
5. The micro energy operation algorithm of claim 4, wherein: the improved chimpanzee optimization algorithm is specifically as follows:
D＝|WX o (t)-HX s (t)|
X s (t+1)＝X s (t)-Q·D
wherein D is the distance between the chimpanzee and the prey, W, Q is the coefficient vector, H is the chaotic vector generated by chaotic mapping, and X o (t) is the t iteration prey position vector, X s (t) chimpanzee position vector, X, for the t-th iteration s (t+1) is the chimpanzee position vector for the t+1st iteration;
Q＝2f·r 1 -f
W＝2r 2
wherein f is a convergence constraint, r 1 、r 2 Are all [0,1 ]]A random number therebetween;
wherein τ is the maximum number of iterations;
obtaining the fitness values of all chimpanzee individuals in the population, and sequencing to obtain a corresponding optimal solution X A Suboptimal solution X B And the worst point X C Center point X S Set as the optimal solution X A And suboptimal solution X B Center position of the room:
for the worst point X C And (3) reflecting:
X K ＝X S +δ(X S -X C )
wherein X is K Is a reflection point, delta is a reflection coefficient;
if f (X) K )＜f(X C ) At the time of reflection point X K Instead of the worst point X C Expanding to obtain an expansion point X L ：
X L ＝X S +ε(X K -X S )
Wherein epsilon is the expansion coefficient;
if f (X) L )＜f(X K ) Expansion point X L Instead of the worst point X C Expanding otherwise using reflection point X K Instead of the worst point X C Generating a new simplex, and performing the next iteration;
if f (X) C )＜f(X K ) In this case, the outer shrinkage is performed to obtain an outer shrinkage point X G ：
Wherein,is the external contraction coefficient;
if f (X) A )＜f(X K )＜f(X C ) Performing internal contraction to obtain an internal contraction point X g ；
X g ＝X S +ρ(X C -X S )
Wherein ρ is the internal shrinkage factor;
if f (X) g )＜f(X C ) Or f (X) G )＜f(X C ) Then use compression point X G Or X g Instead of the worst point X C Otherwise using reflection point X K Instead of the worst point.
6. The micro energy operation algorithm of claim 5, wherein: the initialization code is used for setting all IO states and levels to be correct states and reading parameters.
7. The micro energy operation algorithm of claim 6, wherein: in the step S3, the fixed running time and running current of each task are obtained, and the running time of each task is recorded by using a low-power-consumption timer for the task with the running time changing along with the external condition.
8. The micro energy operation algorithm of claim 7, wherein: in the S3, the consumed energy of the xth task operation stage is recorded as followsThe following are satisfied in each discharge period:
when n tasks accumulate and consume energyWhen the MCU suspends the operation of the following tasks, the MCU and the peripheral circuit are set to enter a sleep state, and the current consumed by the system is +.>The system enters an energy storage stage for energy storage.
9. The micro energy operation algorithm of claim 8, wherein: in the energy storage phase, the energy storage capacitance is increasedThe voltage value isThe energy storage time of the system is as follows:
wherein T is NP The energy storage time of the system;
time T of storing energy of system NP And setting the wake-up time of low-power wake-up, and enabling the MCU to wake up to continue running tasks after the energy storage stage is completed.
10. The micro energy operation algorithm of claim 9, wherein: when the system detects that the starting voltage is larger than the margin energy storage starting voltage, the MCU starts the margin energy charging circuit, and the system charges redundant energy of the energy storage capacitor to the super capacitor for secondary storage.
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