CN107958129B - Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor - Google Patents

Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor Download PDF

Info

Publication number
CN107958129B
CN107958129B CN201810001978.8A CN201810001978A CN107958129B CN 107958129 B CN107958129 B CN 107958129B CN 201810001978 A CN201810001978 A CN 201810001978A CN 107958129 B CN107958129 B CN 107958129B
Authority
CN
China
Prior art keywords
equation
equation set
voltage
current
value
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810001978.8A
Other languages
Chinese (zh)
Other versions
CN107958129A (en
Inventor
胡军
何金良
孟鹏飞
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tsinghua University
Original Assignee
Tsinghua University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tsinghua University filed Critical Tsinghua University
Priority to CN201810001978.8A priority Critical patent/CN107958129B/en
Publication of CN107958129A publication Critical patent/CN107958129A/en
Application granted granted Critical
Publication of CN107958129B publication Critical patent/CN107958129B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/30Circuit design
    • G06F30/36Circuit design at the analogue level
    • G06F30/367Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Medicines Containing Antibodies Or Antigens For Use As Internal Diagnostic Agents (AREA)
  • Thermistors And Varistors (AREA)

Abstract

An algorithm for simulating the microscopic current distribution of a zinc oxide piezoresistor comprises a formula establishing step, a sectional control step and an optimization step, wherein the formula establishing step, the sectional control step and the optimization step are sequentially carried out. The beneficial effects are as follows: the fast algorithm of the piecewise linearization enables the ZnO varistor calculation simulation model after the introduction of the grain boundary real conduction mechanism to be effectively solved, and the speed and efficiency of calculation simulation are greatly improved by fully optimizing the related algorithm.

Description

Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor
Technical Field
The invention relates to the field of research on novel high-performance ZnO piezoresistors with high voltage gradients, in particular to an algorithm for simulating the microcosmic current distribution of a zinc oxide piezoresistor.
Background
The most basic premise of material design is that the actual process of material experimental study and the various elements involved therein can be described by a suitable mathematical model; the most basic tool for material design is a calculation simulation model capable of truly reflecting the change rule of material characteristics.
Since the original optimization variables (raw material component formula and processing process conditions) and the final optimization target (macroscopic electrical performance parameters) in the optimization problem have a very complex correlation relationship, experimental research is almost the only tool and way for optimization solution for a long time. The important achievements in the aspect of optimizing the performance of the ZnO piezoresistor are basically established on the basis of a great amount of experimental research, and the important achievements are the main reasons that domestic manufacturers do not break through the novel high-performance ZnO valve plate in years of tracking research and related research achievements of domestic scientific research institutes and practical application requirements are different.
There is a very complex association between the optimization variables and the optimization objectives of the original optimization problem that is difficult to systematically generalize and describe. Compared with this, in each optimization problem divided into two steps, the original optimization variables and the intermediate optimization targets, and the association relationship between the intermediate optimization variables and the final optimization targets are definitely simpler and clearer. For the optimization variables and the optimization targets of each step in the optimization process divided into two steps, clear correlation relations between the optimization variables and the optimization targets can be established, and the correlation relations are basic conditions for further solving the original complete optimization problem.
For the calculation simulation model and algorithm of the ZnO varistor, some researchers have carried out related research and achieved certain results at present. However, the existing research results of calculating and simulating the ZnO piezoresistor still have certain problems and disadvantages, and it is difficult to obtain a direct correlation between the optimization variables and the target, that is, an intricate influence relationship and a correlation mechanism between the intrinsic microstructure and grain boundary characteristic parameters of the ZnO piezoresistor and macroscopic electrical performance parameters.
For solving a large-scale nonlinear equation system involved in a ZnO varistor calculation simulation model, the most common numerical calculation method which is also commonly adopted by researchers in the past is a traditional Newton iteration method. Because the resources and the solving time required by calculation are increased in geometric progression along with the increase of the equation and the unknown quantity in the equation set, researchers generally carry out numerical calculation simulation on the ZnO piezoresistor in the order of hundreds of grains, and each calculation usually takes more than ten hours.
Disclosure of Invention
The invention aims to solve the problems and designs an algorithm for simulating the microcosmic current distribution of the zinc oxide piezoresistor. The specific design scheme is as follows:
an algorithm for simulating the microcosmic current distribution of a zinc oxide piezoresistor comprises a formula establishing step, a sectional control step and an optimization step which are sequentially carried out,
in the formula establishing step, the effect of the added voltage increment on the equivalent circuit is solved, and the nonlinear circuit is subjected to approximate linearization processing;
in the step of sectional control, controlling the current increment of the external power supply and determining a control strategy that the external power supply gradually increases from zero voltage to the maximum value;
in the optimization step, the equation set established in the segmentation control step is evolved to simplify calculation.
In the formula establishing step, in the k and k +1 steps, the voltage and current data of each node and branch in the equivalent circuit need to satisfy a first nonlinear equation set and a second linear equation set,
the first nonlinear equation is:
Figure GDA0002604248070000021
the second linear equation set is:
Figure GDA0002604248070000031
defining the voltage and current data difference value of each node and branch in the k step and the k +1 step to obtain a third equation set of voltage and current:
Figure GDA0002604248070000032
and (3) substituting the linear equation set I and the linear equation set II into an equation set III to obtain a deformed equation set IV:
Figure GDA0002604248070000033
performing Taylor series expansion on the deformed equation set four to obtain an equation set five:
Figure GDA0002604248070000034
in the step of the sectional control, necessary changes are carried out on the constraint conditions of the external power supply branches in the equation group five to obtain an equation group six:
Figure GDA0002604248070000041
and for the increment of the current of the external power supply, controlling based on the current density value flowing through the whole ZnO piezoresistor to obtain a seventh equation set:
Figure GDA0002604248070000042
in the formula establishing step, voltage and current data of nodes and branches generated by the increment of the voltage of the external power supply are calculated, actual voltage and current data of each node and branch in the equivalent circuit under the action of the voltage of the current external power supply are obtained by three-step superposition of an equation set on the calculation result obtained in the previous step, various macroscopic electrical performance parameters of the ZnO piezoresistor are comprehensively analyzed, and the piecewise linearization algorithm of calculation simulation of the ZnO piezoresistor is realized.
In the optimization step, data corresponding to the relevant matrix in the equation set and the external power supply branch in the vector are segmented with other data to obtain the following equation:
A=[AGB,AS];
Figure GDA0002604248070000043
Figure GDA0002604248070000044
substituting the equation into equation set six to obtain equation set eight:
Figure GDA0002604248070000045
in the eighth equation set, the 2 nd equation in the equation set is substituted into the 4 th equation, the 4 th equation is substituted into the 1 st equation in sequence to obtain the voltage increment of each node in the direct solution equivalent circuit
Figure GDA0002604248070000051
Equation one of (1):
Figure GDA0002604248070000052
by
Figure GDA0002604248070000053
Obtaining the voltage and current increment delta U of each branch in the equivalent circuit through direct calculation(k+1)
Figure GDA0002604248070000054
The system of equations of (a) is:
Figure GDA0002604248070000055
in seven of the equation set, SBulkIn order to calculate the estimated value of the overall cross-sectional area of the simulated ZnO piezoresistor, J _ exp _ min is the minimum value of the current density actually flowing through the ZnO piezoresistor, the value is-9, J _ exp _ step is the incremental value of the corresponding current density, the value is 0.01, and the calculation is iterated until the current density reaches the maximum value J _ exp _ max, and the value is 5.
The algorithm for simulating the microscopic current distribution of the zinc oxide piezoresistor obtained by the technical scheme has the beneficial effects that:
the fast algorithm of the piecewise linearization enables the ZnO varistor calculation simulation model after the introduction of the grain boundary real conduction mechanism to be effectively solved, and the speed and efficiency of calculation simulation are greatly improved by fully optimizing the related algorithm.
Drawings
FIG. 1 is a graph of a piecewise linearization algorithm of a ZnO varistor calculation simulation according to the present invention;
fig. 2 is an error analysis diagram of the computational simulation algorithm of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
FIG. 1 is a sectional linearization algorithm chart of the ZnO varistor calculation simulation of the invention, as shown in FIG. 1, an algorithm for simulating the microscopic current distribution of the zinc oxide varistor comprises a formula establishing step, a sectional control step and an optimization step, wherein the formula establishing step, the sectional control step and the optimization step are sequentially carried out,
in the formula establishing step, the effect of the added voltage increment on the equivalent circuit is solved, and the nonlinear circuit is subjected to approximate linearization processing;
in the step of sectional control, controlling the current increment of the external power supply and determining a control strategy that the external power supply gradually increases from zero voltage to the maximum value;
in the optimization step, the equation set established in the segmentation control step is evolved to simplify calculation.
In the formula establishing step, in the k and k +1 steps, the voltage and current data of each node and branch in the equivalent circuit need to satisfy a first nonlinear equation set and a second linear equation set,
the first nonlinear equation is:
Figure GDA0002604248070000061
the second linear equation set is:
Figure GDA0002604248070000062
defining the voltage and current data difference value of each node and branch in the k step and the k +1 step to obtain a third equation set of voltage and current:
Figure GDA0002604248070000063
and (3) substituting the linear equation set I and the linear equation set II into an equation set III to obtain a deformed equation set IV:
Figure GDA0002604248070000071
performing Taylor series expansion on the deformed equation set four to obtain an equation set five:
Figure GDA0002604248070000072
in the step of the sectional control, necessary changes are carried out on the constraint conditions of the external power supply branches in the equation group five to obtain an equation group six:
Figure GDA0002604248070000073
and for the increment of the current of the external power supply, controlling based on the current density value flowing through the whole ZnO piezoresistor to obtain a seventh equation set:
Figure GDA0002604248070000074
in the formula establishing step, voltage and current data of nodes and branches generated by the increment of the voltage of the external power supply are calculated, actual voltage and current data of each node and branch in the equivalent circuit under the action of the voltage of the current external power supply are obtained by three-step superposition of an equation set on the calculation result obtained in the previous step, various macroscopic electrical performance parameters of the ZnO piezoresistor are comprehensively analyzed, and the piecewise linearization algorithm of calculation simulation of the ZnO piezoresistor is realized.
In the optimization step, data corresponding to the relevant matrix in the equation set and the external power supply branch in the vector are segmented with other data to obtain the following equation:
A=[AGB,AS];
Figure GDA0002604248070000081
Figure GDA0002604248070000082
substituting the equation into equation set six to obtain equation set eight:
Figure GDA0002604248070000083
in the eighth equation set, the 2 nd equation in the equation set is substituted into the 4 th equation, the 4 th equation is substituted into the 1 st equation in sequence to obtain the voltage increment of each node in the direct solution equivalent circuit
Figure GDA0002604248070000084
Equation one of (1):
Figure GDA0002604248070000085
by
Figure GDA0002604248070000086
Obtaining the voltage and current increment delta U of each branch in the equivalent circuit through direct calculation(k+1)
Figure GDA0002604248070000087
The system of equations of (a) is:
Figure GDA0002604248070000088
in seven of the equation set, SBulkIn order to calculate the estimated value of the overall cross-sectional area of the simulated ZnO piezoresistor, J _ exp _ min is the minimum value of the current density actually flowing through the ZnO piezoresistor, the value is-9, J _ exp _ step is the incremental value of the corresponding current density, the value is 0.01, and the calculation is iterated until the current density reaches the maximum value J _ exp _ max, and the value is 5.
Example 1
And according to the sixth equation set, voltage and current data of the nodes and the branches generated by the additional power supply increment in the step (k +1) can be obtained, and the voltage and current data of each node and branch in the equivalent circuit in the step (k +1) can be obtained by adding the voltage and current data to the calculation result obtained in the step (k) through the third equation set.
FIG. 2 is an error analysis diagram of the computational simulation algorithm of the present invention, as shown in FIG. 2, the data actually corresponds to a certain data point on the tangent extension of the kth step data point on the nonlinear curve, i.e., point A, rather than being directly located on the nonlinear curve; for the solving process of the (k + 2) th step, an equation is adopted, which is actually equivalent to a point B serving as a tangent extension line, so that the linearization of a nonlinear curve is realized.
Example 2
On the basis of embodiment 1, for the point B, the voltage data of each node branch in the equivalent circuit is completely the same as the point a, so that the kirchhoff-related law is still satisfied, and the current data of the branch is no longer the same as the point a, so that a certain deviation exists from the requirements of the kirchhoff-related law. And obtaining branch current data corresponding to the B point through a complete equation set:
Figure GDA0002604248070000091
wherein V is the voltage applied to two sides of the potential barrier;
Qiis the charge density of the surface state filling;
Ni(E) is a surface state energy distribution function;
fi(E) is a fermi distribution function;
kBboltzmann (Boltzmann) constants;
t is the absolute temperature;
a is the Richardson constant;
kBboltzmann constant;
t is the absolute temperature;
ξenergy level difference ξ between conduction band energy level Ec and Fermi level ξiIs a quasi-fermi level.
Example 3
On the basis of example 2, the following calculation errors are defined on this basis:
Figure GDA0002604248070000101
in the above definition of the calculation error Ierr, the essence of the numerator portion is the sum of all the currents flowing into and out of each node of the equivalent circuit, and the essence of the denominator portion is the total current value flowing through each node.
According to kirchhoff's correlation law, the numerical value of the sum of the currents flowing into and out of any node in the circuit is supposed to be zero, the requirement of the law can be met for branch current data I (k +1) at the point A, and the branch current data corresponding to the point B does not meet the requirement of the law, namely a certain calculation error is generated.
And dividing the error data of the sum of the currents of each node by the total current value flowing through each node to obtain error ratio data which can better reflect the severity of the calculated current error of each node. And accumulating and averaging the current error ratio data of all the nodes to serve as an error evaluation index of the whole calculation simulation algorithm.
For the practical calculation simulation example, the calculation result obtained by adopting the piecewise linearization fast algorithm proposed by the paper and various related optimization measures has the calculation error Ierr only in the order of magnitude of 10-3 according to the definition, and the error value is very small, thereby showing that the related calculation simulation algorithm is completely reasonable and reliable.
The technical solutions described above only represent the preferred technical solutions of the present invention, and some possible modifications to some parts of the technical solutions by those skilled in the art all represent the principles of the present invention, and fall within the protection scope of the present invention.

Claims (2)

1. An algorithm for simulating the microcosmic current distribution of a zinc oxide piezoresistor comprises a formula establishing step, a sectional control step and an optimization step, and is characterized in that the formula establishing step, the sectional control step and the optimization step are sequentially carried out,
in the formula establishing step, the effect of the added voltage increment on the equivalent circuit is solved, and the nonlinear circuit is subjected to approximate linearization processing;
in the step of sectional control, controlling the current increment of the external power supply and determining a control strategy that the external power supply gradually increases from zero voltage to the maximum value;
in the optimization step, the equation set established in the segmentation control step is evolved to simplify calculation,
in the formula establishing step, in the k and k +1 steps, the voltage and current data of each node and branch in the equivalent circuit need to satisfy a first nonlinear equation set and a second linear equation set,
the first nonlinear equation is:
Figure FDA0002606231190000011
the second linear equation set is:
Figure FDA0002606231190000012
defining the voltage and current data difference value of each node and branch in the k step and the k +1 step to obtain a third equation set of voltage and current:
Figure FDA0002606231190000013
and (3) substituting the linear equation set I and the linear equation set II into an equation set III to obtain a deformed equation set IV:
Figure FDA0002606231190000021
performing Taylor series expansion on the deformed equation set four to obtain an equation set five:
Figure FDA0002606231190000023
in the step of the sectional control, necessary changes are carried out on the constraint conditions of the external power supply branches in the equation group five to obtain an equation group six:
Figure FDA0002606231190000024
and for the increment of the current of the external power supply, controlling based on the current density value flowing through the whole ZnO piezoresistor to obtain a seventh equation set:
Figure FDA0002606231190000025
in the formula establishing step, voltage and current data of nodes and branches generated by the increment of the voltage of the external power supply are calculated, actual voltage and current data of each node and branch in the equivalent circuit under the action of the voltage of the current external power supply are obtained by three-step superposition on the calculation result obtained in the previous step according to an equation set, various macroscopic electrical performance parameters of the ZnO piezoresistor are comprehensively analyzed, and a piecewise linearization algorithm of calculation simulation of the ZnO piezoresistor is realized,
in the optimization step, data corresponding to the relevant matrix in the equation set and the external power supply branch in the vector are segmented with other data to obtain the following equation:
Figure FDA00026062311900000310
substituting the equation into equation set six to obtain equation set eight:
Figure FDA0002606231190000034
in the eighth equation set, the 2 nd equation in the equation set is substituted into the 4 th equation, the 4 th equation is substituted into the 1 st equation in sequence to obtain the voltage increment of each node in the direct solution equivalent circuit
Figure FDA0002606231190000035
Equation one of (1):
Figure FDA0002606231190000036
by
Figure FDA0002606231190000037
Obtaining the voltage and current increment delta U of each branch in the equivalent circuit through direct calculation(k+1)
Figure FDA0002606231190000038
The system of equations of (a) is:
Figure FDA0002606231190000039
2. the algorithm for modeling the micro-current distribution of a zinc oxide varistor as claimed in claim 1, wherein S in the seventh equation setBulkIn order to calculate the estimated value of the overall cross-sectional area of the simulated ZnO piezoresistor, J _ exp _ min is the minimum value of the current density actually flowing through the ZnO piezoresistor, the value is-9, J _ exp _ step is the incremental value of the corresponding current density, the value is 0.01, and the calculation is iterated until the current density reaches the maximum value J _ exp _ max, and the value is 5.
CN201810001978.8A 2018-01-02 2018-01-02 Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor Active CN107958129B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810001978.8A CN107958129B (en) 2018-01-02 2018-01-02 Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810001978.8A CN107958129B (en) 2018-01-02 2018-01-02 Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor

Publications (2)

Publication Number Publication Date
CN107958129A CN107958129A (en) 2018-04-24
CN107958129B true CN107958129B (en) 2020-10-02

Family

ID=61956114

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810001978.8A Active CN107958129B (en) 2018-01-02 2018-01-02 Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor

Country Status (1)

Country Link
CN (1) CN107958129B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113009226B (en) * 2021-02-03 2022-08-30 长江存储科技有限责任公司 Method and device for obtaining contact resistance
CN113406940B (en) * 2021-07-28 2024-05-17 金盛 Intelligent drainage grading real-time control method based on model predictive control

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060047370A1 (en) * 2004-08-26 2006-03-02 Chang Gung University Efficient look-ahead load margin and voltage profiles contingency analysis using a tangent vector index method
CN103353563A (en) * 2013-06-28 2013-10-16 清华大学 Method for testing current distribution uniformity inside monolithic piezoresistor valve plate
CN105510683B (en) * 2015-12-29 2018-12-07 清华大学 Wide temperature range varistor valve internal current distributing homogeneity test method

Also Published As

Publication number Publication date
CN107958129A (en) 2018-04-24

Similar Documents

Publication Publication Date Title
Kheldoun et al. A new Golden Section method-based maximum power point tracking algorithm for photovoltaic systems
US20190197203A1 (en) Simulation of Photovoltaic Systems
CN105205502B (en) A kind of Load time series classification method based on markov Monte Carlo
CN110889527B (en) Electric vehicle charging load prediction method based on LSTM neural network
CN113205207A (en) XGboost algorithm-based short-term power consumption load fluctuation prediction method and system
CN109088407B (en) Power distribution network state estimation method based on deep belief network pseudo-measurement modeling
CN110956312A (en) Photovoltaic power distribution network voltage prediction method based on EMD-CNN deep neural network
CN107958129B (en) Algorithm for simulating microcosmic current distribution of zinc oxide piezoresistor
CN116526473A (en) Particle swarm optimization LSTM-based electrothermal load prediction method
CN113537582B (en) Photovoltaic power ultra-short-term prediction method based on short-wave radiation correction
CN102856903A (en) Micro-grid probability load flow calculation method
CN111160772A (en) Large power grid risk rapid assessment method
CN113033136B (en) Simplified photovoltaic cell physical parameter extraction optimization method and system
CN115186923A (en) Photovoltaic power generation power prediction method and device and electronic equipment
CN111832839A (en) Energy consumption prediction method based on sufficient incremental learning
CN113991711B (en) Capacity configuration method for energy storage system of photovoltaic power station
Celsa et al. Matlab/Simulink model of photovoltaic modules/strings under uneven distribution of irradiance and temperature
CN108694475B (en) Short-time-scale photovoltaic cell power generation capacity prediction method based on hybrid model
Hashim et al. Optimal population size of particle swarm optimization for photovoltaic systems under partial shading condition
CN113591957A (en) Wind power output short-term rolling prediction and correction method based on LSTM and Markov chain
CN111177973B (en) Photovoltaic array online modeling method based on reinforcement learning
CN117592592A (en) VMD-SSA-LSTM-based power transmission line icing thickness prediction method
CN117200223A (en) Day-ahead power load prediction method and device
CN117077546A (en) Power system load modeling method and system based on data driving
Shi et al. Linear fitting Rule of I–V characteristics of thin-film cells based on Bezier function

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant