CN-121663708-B - Modular battery control method and system based on LLC resonant converter

CN121663708BCN 121663708 BCN121663708 BCN 121663708BCN-121663708-B

Abstract

The invention relates to the technical field of power electronics and battery management, and discloses a modularized battery control method and system based on an LLC resonant converter, wherein the method comprises the steps of obtaining real-time state parameters such as voltage, current, temperature and the like of each battery module; the method comprises the steps of calculating spatial gradient parameters reflecting state difference distribution among modules, time differential parameters reflecting state change trend and cross coupling parameters reflecting mutual influence degree among different state parameters, carrying out multi-objective collaborative optimization decision, quantifying negative influence cost and dynamically judging priority when targets collide, searching global compromise which enables the whole system to steadily evolve to an equilibrium state in a state space as a collaborative power distribution instruction set, driving an LLC resonant converter to execute power management on each module, realizing normal form conversion from independent control of monomer states to intelligent collaborative regulation of dynamic coupling relation among modules, and effectively solving the problem of dynamic non-uniformity.

Inventors

CUI JIAFENG
LIU CAN
QIU SHIJUN
CAO JINFANG
Ye Yingran
Deng Qiuwen
TANG ZHIYANG

Assignees

湖南京能新能源科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260205

Claims (8)

1. A modular battery control method based on an LLC resonant converter, comprising: s1, acquiring real-time state parameters of each battery module in a plurality of battery modules, wherein the state parameters comprise voltage, current and temperature; s2, calculating a multi-element differential relation parameter of the interaction relation between the battery modules through the real-time state parameter of each battery module; Taking the multi-element differential relation parameter as input, and inputting the multi-element differential relation parameter into an optimization solver; the space gradient parameters are used for constructing an optimization target item about state consistency, the time differential parameters are used for constructing a constraint item about the dynamic response speed and stability of the system, and the cross coupling parameters are used for constructing a coupling cost item for describing the mutual constraint relation between different state variables; The optimization solver constructs a comprehensive cost function by using an optimization target item and a coupling cost item, takes a constraint item as a boundary condition, and solves an optimal prediction vector of the power requirements of each battery module in a future limited time window by minimizing the comprehensive cost function; Decoupling and decomposing the optimal prediction vector into a group of instantaneous power set values which are in one-to-one correspondence with each battery module, synchronous in time and coordinated in numerical value according to the real-time state of each battery module and the mutual correlation of the battery modules in the multi-element differential relation parameter to form a collaborative power distribution instruction set; the instruction set is used for ensuring that the electric connection and the thermal constraint are met, the power set value is used for the cooperative operation of the floor optimal prediction vector planning, and each module is driven to respond synchronously; s3, performing multi-objective collaborative optimization decision-making through the multi-element differential relation parameters, and generating collaborative power distribution instruction sets corresponding to a plurality of battery modules; When a conflict exists among a plurality of control targets, calculating negative influence cost of a single battery module on the associated targets through cross coupling parameters, and judging real-time priority of each control target through a spatial gradient parameter and a time differential parameter; S4, searching a global compromise solution capable of enabling the multi-element differential relation parameter to be integrally and stably evolved to an equilibrium state in a state space through the negative influence cost and the real-time priority, and taking the global compromise solution as the collaborative power allocation instruction set.
2. A modular battery control method based on an LLC resonant converter in accordance with claim 1, wherein: The multi-element differential relation parameters comprise a space gradient parameter reflecting state difference distribution among modules, a time differential parameter reflecting state change trend of each module and a cross coupling parameter reflecting mutual influence degree among state parameters of different dimensions.
3. A modular battery control method based on an LLC resonant converter in accordance with claim 2, wherein: constructing a multidimensional state space through real-time state parameters of all battery modules; the multidimensional state space obtains the space gradient parameter by calculating the ratio or statistical distribution characteristic of the variable quantity of any two different battery modules on the same state parameter, and the space gradient parameter is used for quantifying the space distribution mode of state inconsistency; The method comprises the steps of obtaining time differential parameters by carrying out differential operation on each state parameter of each battery module with respect to time, wherein the time differential parameters are used for quantifying the instantaneous change speed and trend of each module state; And obtaining the cross coupling parameters by calculating the association proportion between the state parameter variable quantities of at least two different dimensions of any battery module, and quantifying the dynamic interaction strength between different physical quantities.
4. A modular battery control method based on an LLC resonant converter in accordance with claim 1, wherein: The method for calculating the negative influence cost comprises the following steps: S3011 takes as input the cross-coupling parameter, the intended control for the target battery module, and the unit change in the first state parameter of the module caused by the control action; S3012, calculating the predicted variation of the second state parameter of the target battery module according to the mapping relation of the cross coupling parameters; S3013 outputs the predicted variation as the negative impact cost generated when the control action is performed to achieve the first objective The method for judging the real-time priority comprises the following steps: s3021, determining the reference priority of each control target according to the state difference reflected by the spatial gradient parameter; s3022, dynamically adjusting the reference priority in combination with the state change rate and the acceleration trend indicated by the time differential parameter.
5. A modular battery control method based on an LLC resonant converter in accordance with claim 1, wherein: constructing a Lyapunov function taking the multiple differential relation parameters as key variables; The space gradient parameter defines a potential energy surface of the Lyapunov function, the cross coupling parameter defines the curvature of the potential energy surface, and the time differential parameter is used for evaluating the instantaneous kinetic energy of a system state track; the global solution is that in an energy field described by the Lyapunov function, a state evolution direction which enables the sum of potential energy and kinetic energy of the system to attenuate fastest and the evolution path to be smoother is selected, and a control input corresponding to the direction is the global solution.
6. A modular battery control method based on an LLC resonant converter in accordance with claim 5, wherein: The Lyapunov function embeds the quantized cost into nonlinear constraint in a state space, and converts the dynamic priority into a differential requirement on convergence speed of different sections of the state track; And obtaining the global compromise solution by solving the constrained gradient flow optimization problem, wherein the global compromise solution is used for enabling the system state to bypass the obstacle formed by the high-cost area in a self-adaptive manner when moving along the negative gradient direction of the energy field, and preferentially meeting the convergence speed requirement corresponding to the high-priority target.
7. A modular battery control method based on an LLC resonant converter in accordance with claim 6, wherein: the global compromise is solved by a preset inverse system mapping model, and the global compromise is inversely solved into a power injection vector required by the current evolution direction under the current system constraint; the power injection vector is the coordinated power distribution instruction set, with each component corresponding to an instantaneous power setting of a battery module.
8. A modular battery control system through an LLC resonant converter for implementing a modular battery control method based on an LLC resonant converter as claimed in any of claims 1-7, comprising a state sensing module, a collaborative decision module and a control module; the state sensing module comprises a signal acquisition unit and a multi-element differential calculation unit; the multi-element differential calculation unit is connected with the signal acquisition unit and is used for calculating a space gradient parameter reflecting state difference distribution among modules, a time differential parameter reflecting state change trend of each module and a cross coupling parameter reflecting interaction degree among state parameters of different dimensions based on the real-time state parameters; When a conflict exists among a plurality of control targets, the module calculates negative influence cost of single control brake on the associated target through the cross coupling parameter, dynamically judges the real-time priority of each control target through the space gradient parameter and the time differential parameter, and searches a global compromise solution which can enable the multi-element differential relation parameter to be integrally and stably evolved to an equilibrium state in a state space; The control module is configured to demap and generate the global compromise as a set of real-time cooperative control parameters of the LLC resonant converter to drive the converter to perform differentiated and mutually cooperative power management operations on different battery modules simultaneously.

Description

Modular battery control method and system based on LLC resonant converter Technical Field The invention relates to the technical field of power electronics and battery management, and discloses a modularized battery control method and system based on an LLC resonant converter. Background With the rapid development of new energy storage and electric automobiles, a high-voltage battery system formed by connecting a plurality of battery modules in series or in parallel has become a mainstream, and an LLC resonant converter is widely used as an isolated charge-discharge interface of the modules due to high efficiency and soft switching characteristics. However, the existing control strategy has a plurality of defects, such as decision making is usually carried out only according to a single instantaneous state of a battery module, static feedback control is carried out, dynamic change trend of a state cannot be perceived and predicted, response is delayed, LLC frequency conversion control is adopted to realize voltage equalization among modules, but only voltage instantaneous value cannot be responded, SOC or temperature trend cannot be predicted, equalization speed is slow, and the equalization strategy of the SOC in the prior art does not consider the temperature rise problem caused by high current equalization. Therefore, the existing method is difficult to solve the problem of dynamic non-uniformity in the multi-state variable coupling scene. Disclosure of Invention In order to solve the above technical problems, a main object of the present invention is to provide a modular battery control method and system based on an LLC resonant converter, wherein the modular battery control method based on the LLC resonant converter includes: s1, acquiring real-time state parameters of each battery module in the plurality of battery modules, wherein the state parameters comprise voltage, current and temperature; s2, calculating a multi-element differential relation parameter of the interaction relation between the battery modules through the real-time state parameter of each battery module; S3, performing multi-objective collaborative optimization decision-making through the multi-element differential relation parameters, and generating collaborative power distribution instruction sets corresponding to the plurality of battery modules; When a conflict exists among a plurality of control targets, calculating negative influence cost of a single battery module on the associated targets through cross coupling parameters, and judging real-time priority of each control target through a spatial gradient parameter and a time differential parameter; S4, searching a global compromise solution capable of enabling the multi-element differential relation parameter to be integrally and stably evolved to an equilibrium state in a state space through the negative influence cost and the real-time priority, and taking the global compromise solution as the collaborative power allocation instruction set. As a preferred embodiment of the modular battery control method based on an LLC resonant converter of the present invention, wherein: The multi-element differential relation parameters comprise a space gradient parameter reflecting state difference distribution among modules, a time differential parameter reflecting state change trend of each module and a cross coupling parameter reflecting mutual influence degree among state parameters of different dimensions. As a preferred embodiment of the modular battery control method based on an LLC resonant converter of the present invention, wherein: constructing a multidimensional state space through real-time state parameters of all battery modules; the multidimensional state space obtains the space gradient parameter by calculating the ratio or statistical distribution characteristic of the variable quantity of any two different battery modules on the same state parameter, and the space gradient parameter is used for quantifying the space distribution mode of state inconsistency; The method comprises the steps of obtaining time differential parameters by carrying out differential operation on each state parameter of each battery module with respect to time, wherein the time differential parameters are used for quantifying the instantaneous change speed and trend of each module state; And obtaining the cross coupling parameters by calculating the association proportion between the state parameter variable quantities of at least two different dimensions of any battery module, and quantifying the dynamic interaction strength between different physical quantities. As a preferred embodiment of the modular battery control method based on an LLC resonant converter of the present invention, wherein: The method for calculating the negative influence cost comprises the following steps: S3011 takes as input the cross-coupling parameter, the intended control for the target battery module, and the unit cha