CN114865888B - Power feedforward inductance parameter identification method and system for energy storage converter - Google Patents
Power feedforward inductance parameter identification method and system for energy storage converter Download PDFInfo
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Abstract
The invention provides a power feedforward inductance parameter identification method and system for an isolated direct current energy storage converter, wherein the method provided by the invention comprises the steps of determining a first output current model under a corresponding modulation mode and a second output current model under a steady state condition based on power models of the isolated direct current energy storage converter under different modulation modes; then determining constraint conditions met by the isolation type direct current energy storage converter in the actual discrete sampling system and defining a first parameter related to a control period and a second parameter related to output current; and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter. The method can realize real-time on-line identification of the series inductance parameters of the isolated DC energy storage converter to improve the accuracy of an advanced control algorithm, and can eliminate identification errors caused by factors such as switch dead zones, parasitic parameters, device voltage drop and the like and improve the accuracy of identification of the inductance parameters.
Description
Technical Field
The invention belongs to the technical field of energy storage converters, and particularly relates to a power feedforward inductance parameter identification method and system for an isolated direct current energy storage converter.
Background
Due to the continuous progress of society, the demand of human beings for new energy is highly concerned among countries in the world. How to effectively develop, store and utilize energy is always a difficult problem which needs to be solved urgently. With the development of China in the aspects of energy consumption, energy conservation and emission reduction, strong driving force is injected for the rapid development of the smart grid. With the development of smart power grids, micro power grids are paid more and more attention as one of important achievements, and operation, maintenance, economic cost and stability of a power system are directly influenced by adjusting light storage charging and discharging of the micro power grid system under the condition of considering time-of-use electricity price.
At present, the battery energy storage technology is developed at a high speed, and a large number of battery energy storage systems are configured at a power plant and a user side for smoothing output fluctuation or reducing electricity consumption cost and the like. Accordingly, various advanced control algorithms are proposed: if students propose various micro power supply strategies of optimal operation, the annual cost expense of the micro power grid is minimized; scholars propose to optimize the micro-grid dispatching and improve the utilization efficiency of renewable energy sources; the scholars propose a V2G (vehicle to grid) scheme with multiple operation modes facing users, and the peak value of power utilization is reduced.
Although various advanced control algorithms have been proposed in succession for energy storage microgrid systems. However, in these advanced control methods, the isolated dc energy storage converter often needs accurate inductance parameters to realize precise control of the converter. The accuracy and control performance of these advanced control algorithms can be compromised if the inductance parameter is biased. Therefore, how to realize the online accurate identification of the series inductance parameters of the isolated DC energy storage converter is a key problem to be solved urgently.
Disclosure of Invention
In view of this, the present invention is directed to solve the problem that, in various advanced control methods for an energy storage microgrid system, the accuracy and the control performance of advanced control algorithms may be reduced due to the occurrence of offset in inductance parameters of an isolated dc energy storage converter.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, the present invention provides a method for identifying a power feedforward inductance parameter of an energy storage converter, which is suitable for an isolated dc energy storage converter, and includes the following steps:
determining a first output current model under a corresponding modulation mode based on power models of the isolated DC energy storage converter under different modulation modes;
determining a second output current model under a steady-state condition according to the first output current model;
determining constraint conditions met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, wherein the constraint conditions are used for determining constraint relations among a control period, output current and series inductance parameters;
defining a first parameter and a second parameter of the output current respectively, wherein the first parameter and the second parameter are in a direct proportion relation, and the first parameter and the second parameter are related to the control period based on the constraint condition;
and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.
Further, if the modulation mode is single phase shift modulation, the second output current model specifically includes:
in the formula,which is indicative of the output current of the power converter,the battery side voltage of the isolated dc energy storage converter is shown,indicating a control period,Which represents the ratio of the transformation of the converter,the series inductance of the isolated DC energy storage converter is shown,the amount of phase shift is indicated.
Further, the expression of the constraint condition is specifically:
in the formula,a steady state value representing the amount of phase shift during the kth sampling period,andrepresenting the steady state values of the output current and the battery voltage at the kth sampling period.
Further, a first parameter related to the control period and a second parameter related to the output current are respectively defined based on the constraint condition, specifically according to the following formula:
Further, still include:
and (3) carrying out adaptive filtering on the series inductance parameters by utilizing an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, wherein the adaptive filtering is carried out according to the following formula:
in the formula,indicating the error for the k-th sampling period,the inductance parameter of the recursive least square algorithm represents the inductance calculated quantity of the kth sampling period under the inductance parameter identification adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the representation calculation result depends more on the previous data, and when forgetting the factorWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
In a second aspect, the present invention provides a power feedforward inductance parameter identification system for an energy storage converter, which is suitable for an isolated dc energy storage converter, and includes:
the first output current model determining unit is used for determining a first output current model in a corresponding modulation mode based on power models of the isolated DC energy storage converter in different modulation modes;
a second output current model determination unit for determining a second output current model under a steady-state condition according to the first output current model;
the constraint condition determining unit is used for determining a constraint condition which is met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, and the constraint condition is used for determining a constraint relation among a control period, output current and series inductance parameters;
a parameter defining unit for defining a first parameter regarding the control period and a second parameter regarding the output current, respectively, based on a constraint condition, the first parameter and the second parameter being in a direct proportional relationship;
and the inductance parameter identification unit is used for taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.
Further, if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit specifically includes:
in the formula,which is representative of the output current of the power supply,the battery side voltage of the isolated dc energy storage converter is shown,it is indicated that the control period is,which represents the ratio of the transformation of the converter,the series inductance of the isolated DC energy storage converter is shown,the amount of phase shift is indicated.
Further, the expression of the constraint condition determined by the constraint condition determining unit is specifically:
in the formula,a steady state value representing the amount of phase shift for the kth sampling period,andrepresenting the steady state values of the output current and the battery voltage at the kth sampling period.
Further, the parameter definition unit defines a first parameter and a second parameter, specifically according to the following formula:
Further, still include:
the adaptive filtering unit is used for carrying out adaptive filtering on the series inductance parameters by utilizing an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, and the adaptive filtering is carried out according to the following formula:
in the formula,indicating the error for the k-th sampling period,inductance parameters representing the recursive least square algorithm identify the inductance calculation amount of the kth sampling period under the adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the calculation result is more dependent on the previous data, andwhen forgetting factorWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
In summary, the present invention provides a method and a system for identifying a power feedforward inductance parameter of an isolated dc energy storage converter, wherein the method provided by the present invention includes determining a first output current model in a corresponding modulation mode based on power models of the isolated dc energy storage converter in different modulation modes; determining a second output current model under a steady-state condition according to the first output current model; determining constraint conditions met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model; defining a first parameter and a second parameter of the output current respectively, wherein the first parameter and the second parameter are in a direct proportion relation, and the first parameter and the second parameter are related to the control period based on the constraint condition; and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter. The method can realize real-time on-line identification of the series inductance parameters of the isolated DC energy storage converter so as to improve the accuracy of an advanced control algorithm, and can eliminate identification errors caused by factors such as switch dead zones, parasitic parameters, device voltage drop and the like and improve the accuracy of inductance parameter identification.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a method for identifying a power feedforward inductance parameter for an isolated dc energy storage converter according to an embodiment of the present invention;
fig. 2 is a circuit structure diagram of an isolated dc energy storage converter according to an embodiment of the present invention;
fig. 3 is a control block diagram of a power feedforward inductance parameter identification method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Due to the continuous progress of society, the demand of human beings for new energy is highly concerned among countries in the world. How to effectively develop, store and utilize energy is a difficult problem which needs to be solved urgently. With the development of China in the aspects of energy consumption, energy conservation and emission reduction, strong driving force is injected for the rapid development of the smart grid. With the development of smart power grids, micro power grids are paid more and more attention as one of important achievements, and operation, maintenance, economic cost and stability of a power system are directly influenced by adjusting light storage charging and discharging of the micro power grid system under the condition of considering time-of-use electricity price.
At present, the battery energy storage technology is developed at a high speed, and a large number of battery energy storage systems are configured at a power plant and a user side and used for smoothing output fluctuation or reducing electricity consumption cost and the like. Accordingly, various advanced control algorithms are proposed: aiming at the problem that the flexibility and the economy are cooperated with each other in the energy optimization scheduling method of the micro-grid, students propose various micro-power supply strategies for optimal operation, so that the annual cost of the micro-grid is minimum. Meanwhile, the load response of the demand side is considered, an internal search algorithm is improved, and the micro-grid is optimized. In addition, scholars propose that optimizing the micro-grid dispatching is one of important ways for improving the utilization efficiency of renewable energy sources, and propose a particle swarm optimization algorithm based on which a micro-grid system including a photo-electricity, a wind power, a diesel engine and a battery is optimized. Meanwhile, the degree of power consumption requirements is getting larger and larger, and in order to reduce the high peak value of the power consumption, a scholars puts forward a V2G (vehicle-to-grid) scheme of multiple operation modes facing users, so that more EVs participate in V2G operation to carry out coordination charging, peak clipping and valley filling to reduce the peak value of the grid. In addition, wind power generation is considered, the optimal running state of the energy storage SOC (state of charge) is taken as a target in the face of variable power change, PSO (particle swarm optimization) is selected to optimize the capacity of the energy storage system, and solution calculation is carried out. Further, in the face of the economic dispatching problem of the power grid, the PSO optimization algorithm is improved for solving. And optimizing the particle swarm algorithm to optimize the capacity configuration by considering self-balancing constraint. And carrying out optimization solution by utilizing a wolf algorithm aiming at the time-of-use electricity price, and realizing the economic optimum.
Although various advanced control algorithms have been proposed in succession for energy storage microgrid systems. However, in these advanced control methods, the isolated dc energy storage converter often needs accurate inductance parameters to realize precise control of the converter. The accuracy and control performance of these advanced control algorithms can be compromised if the inductance parameter is biased. Therefore, how to realize the online accurate identification of the series inductance parameters of the isolated direct current energy storage converter is a key problem to be solved urgently.
Based on the method, the invention provides a method and a system for identifying the parameters of the power feedforward inductance of the isolated DC energy storage converter.
Firstly, for isolated DC energy-storage converterThe circuit structure will be briefly explained. As shown in fig. 2, in the circuit structure of the isolated dc energy storage converter,the output power of the isolated DC energy storage converter is shown,andrespectively representing the battery side voltage and the output voltage of the isolated DC energy storage converter,it is indicated that the control period is,which represents the transformation ratio of the transformer,the series inductance of the isolated DC energy storage converter is shown,indicating the amount of phase shift under single phase shift modulation.
The following describes an embodiment of a method for identifying a power feedforward inductance parameter for an isolated dc energy storage converter according to the present invention in detail.
Referring to fig. 1, the present embodiment provides a method for identifying a power feedforward inductance parameter of an isolated dc energy storage converter, including the following steps:
s100: and determining a first output current model under the corresponding modulation mode based on the power models of the isolated DC energy storage converter under different modulation modes.
For the isolated DC energy storage converter, the modulation modes comprise single phase shift modulation, double phase shift modulation and triple phase shift modulation. The converter has a different number of controllable degrees of freedom in different modulation modes. Under the condition of steady-state working, the isolated direct-current energy storage converter realizes the charging and discharging of the energy storage battery module by controlling the charging and discharging current of the energy storage battery. Taking single phase shift modulation as an example, the power model of the isolated dc storage converter can be expressed as,
wherein,the output power of the isolated DC energy storage converter is shown,andrespectively representing the battery side voltage and the output voltage of the isolated DC energy storage converter,it is indicated that the control period is,which represents the transformation ratio of the transformer,the series inductance of the isolated DC energy storage converter is shown,indicating the amount of phase shift under single phase shift modulation.
On the basis, the output current model of the isolated DC energy storage converter under the condition of single phase shift modulation can be expressed as,
wherein,and the output current of the isolated direct current energy storage converter under the condition of single phase shift modulation is shown.
From the above formula, under the steady-state operation condition, the load current of the isolated energy storage dc converter is independent of the output voltage, that is, the optimal phase shift amount of the converter can be further derived according to the load current of the converter. In the conventional output voltage closed-loop control method, the dynamic response speed of the converter is relatively slow because the phase shift amount 1 of the converter is mainly adjusted according to the error of the output voltage. When the load suddenly changes, the change of the output voltage is relatively small, so the phase shift amount of the converter cannot be quickly adjusted. However, when the load of the converter suddenly changes, the output current of the converter can suddenly change. The optimum amount of phase shift of the converter can thus be derived from the output current, i.e.,
wherein,the output current reference of the isolated DC energy storage converter under the condition of single phase shift modulation is shown to meet the requirement,
s200: a second output current model under steady state conditions is determined from the first output current model.
According to the output current model of the isolated DC energy storage converter under the condition of single phase shift modulation, under the steady state condition, the output current model can be further expressed as,
s300: and determining constraint conditions met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, wherein the constraint conditions are used for determining constraint relations among the control period, the output current and the series inductance parameters.
Based on the second output circuit model of step S200, further, the output current model can be expressed as,
considering that in an actual discrete sampling system, the output current of the isolated energy storage dc transformer, the battery side voltage and the phase shift amount should satisfy a constraint condition, that is,
wherein,a steady state value representing the amount of phase shift for the kth sampling period,andrepresenting the steady state values of the output current and the battery voltage at the kth sampling period.
S400: a first parameter and a second parameter of the output current with respect to the control period are respectively defined based on the constraint condition, and the first parameter and the second parameter are in a direct proportional relationship.
In order to facilitate the realization of the on-line parameter identification of the series inductance, the series inductance is respectively definedAndsatisfy the following requirementsAndproportional relation is formed, and the proportionality coefficient is the series inductance coefficient,
s500: and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.
In addition, sampling noise always exists in the practical implementation of the inductance parameter identification algorithm, so that the sampling noise also exists in the calculation of the inductance parameter. Therefore, in order to realize mutual decoupling of the dynamic response of the on-line identification of the inductance parameters and the dynamic response of the control loop, an inductance parameter identification adaptive filtering algorithm based on a recursion least square algorithm is provided so as to realize real-time identification of the series inductance parameters. Specifically, the inductance parameter identification adaptive filtering algorithm for realizing the recursive least square algorithm comprises the following steps,
in the formula,indicating the error for the k-th sampling period,the inductance parameter of the recursive least square algorithm represents the inductance calculated quantity of the kth sampling period under the inductance parameter identification adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the representation calculation result depends more on the previous data, and when forgetting the factorWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
Based on the steps, the control method for the isolated type direct current energy storage converter comprises the steps of firstly detecting input voltage, output voltage and output current of the isolated type energy storage direct current transformer; then, a proportional-integral controller of an output voltage closed loop is adopted to realize real-time control; simultaneously, combining the output voltage, the input voltage and the output current obtained by sampling, and identifying the inductance parameter of the converter in real time by adopting an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm; and finally, based on the obtained identification inductance parameter, combining the deduced current model of the isolated energy storage direct current transformer to complete the power feedforward control of the converter so as to improve the dynamic response speed of the energy storage direct current converter.
FIG. 3 is a control block diagram of the proposed inductance parameter identification method, in which the output voltage v of the converter is measured o And a reference voltage v ref Comparing, sending the voltage error to a proportional integral controller Gc(s), calculating a phase shift value phi for realizing the voltage control of the converter, and then sampling the output current of the converter to pass through a current feedforward controller in a formula (3) to output a feedforward phase shift value phi m The obtained final phase shift phi is superposed, the actual output current of the converter can be obtained through the phase shift phi-output voltage transfer function of the converter, and then the equivalent output impedance model Z is converted out (s) the actual output voltage is obtained.
The embodiment provides a power feedforward inductance parameter identification method for an isolated direct current energy storage converter, which takes a power feedforward control algorithm as an example, and firstly analyzes a power model of the isolated direct current energy storage converter under the traditional single-phase shift modulation, and further deduces a corresponding current model. On the basis, a feedforward phase shift amount calculation method of the converter under a power feedforward control algorithm is deduced; meanwhile, an identification model of the series inductor is deduced on the basis of a current model of the direct-current energy storage converter; in order to improve identification accuracy and suppress sampling noise, an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm is provided so as to realize real-time identification of series inductance parameters.
The method for identifying the power feedforward inductance parameter of the isolated DC energy storage converter can realize real-time online identification of the series inductance parameter of the isolated DC energy storage converter so as to improve the accuracy of an advanced control algorithm, and meanwhile, the method can eliminate identification errors caused by factors such as switch dead zones, parasitic parameters, device voltage drop and the like, and improve the accuracy of inductance parameter identification.
The above is a detailed description of an embodiment of the present invention of a power feedforward inductance parameter identification method for an isolated dc energy storage converter, and the following is a detailed description of an embodiment of the present invention of a power feedforward inductance parameter identification system for an isolated dc energy storage converter.
The embodiment provides a power feedforward inductance parameter identification system for an energy storage converter, which is suitable for an isolated direct current energy storage converter and comprises the following components:
and the first output current model determining unit is used for determining a first output current model in a corresponding modulation mode based on the power models of the isolated DC energy storage converter in different modulation modes.
And the second output current model determining unit is used for determining a second output current model under the steady-state condition according to the first output current model.
It should be noted that, if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit specifically includes:
in the formula,which is indicative of the output current of the power converter,the battery side voltage of the isolated DC energy storage converter is shown,it is indicated that the control period is,which represents the ratio of the transformation of the converter,the series inductance of the isolated DC energy storage converter is shown,the amount of phase shift is indicated.
And the constraint condition determining unit is used for determining a constraint condition which is met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, and the constraint condition is used for determining a constraint relation among the control period, the output current and the series inductance parameter.
It should be noted that the expression of the constraint condition determined by the constraint condition determining unit is specifically:
in the formula,a steady state value representing the amount of phase shift during the kth sampling period,andrepresenting the steady state values of the output current and the battery voltage at the kth sampling period.
And the parameter definition unit is used for respectively defining a first parameter and a second parameter of the output current relative to the control period based on the constraint condition, and the first parameter and the second parameter are in a direct proportional relation.
It should be noted that, the parameter defining unit defines the first parameter and the second parameter, and specifically performs according to the following formula:
And the inductance parameter identification unit is used for taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated direct current energy storage converter.
In addition, the system provided in this embodiment further includes an adaptive filtering unit, configured to perform adaptive filtering on the series inductance parameter by using an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, where the adaptive filtering is performed according to the following equation:
in the formula,indicating the error for the k-th sampling period,inductance parameters representing the recursive least square algorithm identify the inductance calculation amount of the kth sampling period under the adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the representation calculation result depends more on the previous data, and when the forgetting factor isWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
It should be noted that, the inductance parameter identification system provided in this embodiment is used to implement the inductance parameter identification method provided in the foregoing embodiment, and the specific configuration of each unit is subject to complete implementation of the method, which is not described herein again.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for identifying power feedforward inductance parameters of an energy storage converter is suitable for an isolated direct current energy storage converter and is characterized by comprising the following steps:
determining a first output current model under a corresponding modulation mode based on power models of the isolated DC energy storage converter under different modulation modes;
determining a second output current model under a steady-state condition according to the first output current model;
determining constraint conditions met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output current model, wherein the constraint conditions are used for determining constraint relations among a control period, output current and series inductance parameters;
defining a first parameter and a second parameter of the output current respectively with respect to the control period based on the constraint condition, the first parameter and the second parameter being in a direct proportional relationship;
and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated direct current energy storage converter.
2. A method as claimed in claim 1, wherein if the modulation scheme is single phase shift modulation, the second output current model is specifically:
in the formula,which is representative of the output current of the power supply,the battery side voltage of the isolated DC energy storage converter is shown,it is indicated that the control period is,which represents the ratio of the transformation of the converter,the series inductance of the isolated DC energy storage converter is shown,the amount of phase shift is indicated.
3. A method for identifying parameters of a power feed forward inductance for an energy storage converter as claimed in claim 2, wherein the constraint is expressed by the following expression:
4. A power feed forward inductance parameter identification method for an energy storage converter according to claim 3, characterized in that the first parameter related to the control period and the second parameter related to the output current are respectively defined based on the constraint conditions, and specifically according to the following formula:
5. A power feed forward inductance parameter identification method for a power storage converter as claimed in claim 4, further comprising:
and carrying out adaptive filtering on the series inductance parameters by using an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, wherein the adaptive filtering is carried out according to the following formula:
in the formula,indicating the error for the k-th sampling period,the inductance parameter of the recursive least square algorithm represents the inductance calculated quantity of the kth sampling period under the inductance parameter identification adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the representation calculation result depends more on the previous data, and when the forgetting factor isWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
6. A power feedforward inductance parameter identification system for an energy storage converter, suitable for an isolated DC energy storage converter, comprising:
the first output current model determining unit is used for determining a first output current model in a corresponding modulation mode based on power models of the isolated direct-current energy storage converter in different modulation modes;
a second output current model determination unit for determining a second output current model under a steady-state condition according to the first output current model;
the constraint condition determining unit is used for determining a constraint condition which is met by the isolated direct-current energy storage converter in the actual discrete sampling system based on the second output current model, and the constraint condition is used for determining a constraint relation among a control period, output current and series inductance parameters;
a parameter defining unit for defining a first parameter regarding a control period and a second parameter regarding an output current, respectively, based on the constraint condition, the first parameter and the second parameter being in a direct proportional relationship;
and the inductance parameter identification unit is used for taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.
7. A power feedforward inductance parameter identification system for an energy storage converter according to claim 6, wherein if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit is specifically:
in the formula,which is indicative of the output current of the power converter,the battery side voltage of the isolated DC energy storage converter is shown,it is indicated that the control period is,which represents the ratio of the transformation of the converter,the series inductance of the isolated DC energy storage converter is shown,the amount of phase shift is indicated.
8. A power feedforward inductance parameter identification system for an energy storage converter according to claim 7, wherein the constraint condition determined by the constraint condition determining unit is specifically expressed as:
9. A power feed forward inductance parameter identification system for a power storage converter as claimed in claim 8 wherein said parameter definition unit defines a first parameter and a second parameter in accordance with the following equation:
10. A power feed forward inductance parameter identification system for a power storage converter as claimed in claim 9 further comprising:
the adaptive filtering unit is used for carrying out adaptive filtering on the series inductance parameters by utilizing an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, and the adaptive filtering is carried out according to the following formula:
in the formula,represents the kth sampleThe error in the period of time of the cycle,inductance parameters representing the recursive least square algorithm identify the inductance calculation amount of the kth sampling period under the adaptive filtering algorithm,inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithmUsed for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factorWhen approaching 1, the representation calculation result depends more on the previous data, and when forgetting the factorWhen the value is close to 0, the calculation result is more dependent on the latest data;andrespectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,representing the first intermediate variable value for the (k-1) th sampling period.
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