CN113866654A - BMS structure based on proprietary SOC estimation and proprietary equalization algorithm - Google Patents
BMS structure based on proprietary SOC estimation and proprietary equalization algorithm Download PDFInfo
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Abstract
The invention discloses a BMS structure based on proprietary SOC estimation and proprietary equalization algorithms, which comprises a plurality of SOC estimation modules, an equalization algorithm module and an equalization circuit, wherein the equalization circuit comprises a plurality of equalizers, and the SOC estimation modules are used for estimating the SOC values of each single battery and outputting the estimated results to an equalization control algorithm module. According to the BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm, the environmental temperature is considered, the initial value of the model parameter is determined according to the initial value of the battery measurable variable and the parameter lookup table, and the UKF algorithm and the RLS algorithm are combined to achieve high-accuracy SOC estimation.
Description
Technical Field
The invention relates to the technical field of battery equalization, in particular to a BMS structure based on a proprietary SOC estimation and proprietary equalization algorithm.
Background
With the continuous popularization of new energy automobiles, the research on power batteries is widely concerned. Due to the limited capacity of the power Battery, the maximization of energy utilization is realized in the limited Battery energy storage range, the service life of the Battery is prolonged, and meanwhile, the guarantee of the Battery safety is the target of Battery Management System (BMS) research. The current BMS has a problem that soc (state of charge) estimation accuracy is not high enough, and most of equalization methods use terminal voltage as an equalization evaluation index, however, the terminal voltage cannot provide accurate battery capacity information, which causes battery pack over-equalization and frequent start of an equalization system. This not only makes equalization inefficient but also shortens battery life. In addition, in the SOC-based equalization algorithm, if the SOC estimation accuracy is not high, effective battery equalization still cannot be achieved.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a BMS structure based on a proprietary SOC estimation and proprietary equalization algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme: a BMS structure based on a proprietary SOC estimation and a proprietary equalization algorithm comprises a plurality of SOC estimation modules, an equalization algorithm module and an equalization circuit, wherein the equalization circuit comprises a plurality of equalizers;
the SOC estimation modules are used for estimating the SOC values of the single batteries and outputting the estimation results to the balance control algorithm module;
the equalization algorithm module is responsible for calculating equalization signals required by each single-head battery, takes SOC value estimation results of each single battery in the battery pack as input, and then sends the calculated equalization signals to the plurality of equalization circuits.
As a further description of the above technical solution:
the system comprises a plurality of SOC estimation modules, and is characterized by further comprising an ambient temperature acquisition module, wherein the output end of the ambient temperature acquisition module is electrically connected with the input ends of the SOC estimation modules, and the ambient temperature acquisition module is used for acquiring ambient temperature information and transmitting the ambient temperature information to the SOC estimation modules.
As a further description of the above technical solution:
the output ends of the SOC estimation modules are electrically connected with the input end of the balance control algorithm module, the SOC estimation modules take the voltage and the current of the single battery corresponding to each SOC estimation module and the ambient temperature information acquired by the ambient temperature acquisition module as input, and the SOC estimation results of the single battery are output.
As a further description of the above technical solution:
a plurality of equalizers in the equalization circuit are respectively responsible for equalization of a plurality of single batteries, and the equalizers receive control signals sent by the equalization algorithm module to realize the equalization function of the battery pack.
As a further description of the above technical solution:
the SOC estimation module comprises a first-order RC battery equivalent circuit model module, an offline parameter identification and extraction module, a two-dimensional lookup table module, a UKF algorithm module, an RLS algorithm module and an SOC initial value module.
The off-line parameter identification and extraction module is used for acquiring a terminal voltage value and a discharge current value of the target battery and acquiring an off-line parameter identification and extraction result of the model parameter by utilizing parameter identification and extraction;
the two-dimensional lookup table module utilizes the parameters extracted by the offline parameter identification and extraction module to establish an R0 two-dimensional lookup table, an R1 two-dimensional lookup table, a C1 two-dimensional lookup table and an OCV two-dimensional lookup table;
the SOC initial value module obtains an initial value of the SOC through an SOC two-dimensional lookup table, the input of the SOC two-dimensional lookup table is an initial OCV value and environment temperature information collected by the environment temperature collecting module, the SOC two-dimensional lookup table is obtained by converting the OCV two-dimensional lookup table, and the initial OCV value is obtained from an initial end voltage value of the battery when the battery works.
As a further description of the above technical solution:
the UKF algorithm module establishes a state equation and a measurement equation of the UKF according to a first-order RC battery equivalent circuit model, an initial value of SOC is used as an input value to form a state vector of the UKF, a real-time terminal voltage value and a real-time current value are also input into the UKF algorithm module, an SOC value at a new moment is obtained according to the UKF algorithm, and the current value is determined by the current SOC value, environment temperature information acquired by the environment temperature acquisition module and an OCV two-dimensional lookup table and is given to the RLS algorithm module.
As a further description of the above technical solution:
the battery model parameter updating method comprises the steps that the RLS algorithm module determines a conversion relation between battery model parameters and RLS parameter vectors according to a first-order RC battery equivalent circuit model, the OCV value at a new moment obtained by the UKF algorithm is added with a real-time terminal voltage value and a real-time current value to update the state vector of the RLS algorithm, so that an online identification result of the model parameters is obtained, the battery model parameter values are updated, and then the online identification result is fed back to the UKF algorithm module, and a state equation and a measurement equation in the UKF algorithm module are updated.
As a further description of the above technical solution:
the first-order RC battery equivalent circuit model module comprises a voltage source, a resistor R0, a resistor R1 and a capacitor, wherein the positive electrode of the voltage source is connected with one end of the resistor R1 and one end of the capacitor, the negative electrode of the voltage source is grounded, and the other end of the resistor R1 is connected with the other end of the capacitor and one end of the resistor R0.
Advantageous effects
The invention provides a BMS structure based on a proprietary SOC estimation and proprietary equalization algorithm. The method has the following beneficial effects:
(1): according to the BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm, the environmental temperature is considered, the initial values of the model parameters are determined according to the initial values of the battery measurable variables and the parameter lookup table, and the UKF algorithm and the RLS algorithm are combined to realize the SOC estimation with high accuracy.
(2) According to the BMS structure based on the special SOC estimation and the special equalization algorithm, the inconsistency among the batteries can be essentially improved based on the special equalization control algorithm of the SOC, and therefore the utilization efficiency of the battery pack is improved.
Drawings
Fig. 1 is a block diagram of a BMS architecture based on a proprietary SOC estimation and proprietary equalization algorithm according to the present invention;
FIG. 2 is a block diagram of a SOC estimation module according to the present invention;
FIG. 3 is a diagram illustrating simulation results of a SOC estimation method;
FIG. 4 is a diagram illustrating the result of SOC estimation error.
Detailed Description
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 it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-2, a BMS structure based on a proprietary SOC estimation and a proprietary equalization algorithm includes a plurality of SOC estimation modules, an equalization algorithm module, and an equalization circuit including a plurality of equalizers;
the SOC estimation modules are used for estimating the SOC values of the single batteries and outputting the estimation results to the balance control algorithm module;
the equalization algorithm module is responsible for calculating equalization signals required by each single-head battery, takes SOC value estimation results of each single battery in the battery pack as input, and then sends the calculated equalization signals to the plurality of equalization circuits.
The system comprises a plurality of SOC estimation modules, and is characterized by further comprising an ambient temperature acquisition module, wherein the output end of the ambient temperature acquisition module is electrically connected with the input ends of the SOC estimation modules, and the ambient temperature acquisition module is used for acquiring ambient temperature information and transmitting the ambient temperature information to the SOC estimation modules.
The output ends of the SOC estimation modules are electrically connected with the input end of the balance control algorithm module, the SOC estimation modules take the voltage and the current of the single battery corresponding to each SOC estimation module and the ambient temperature information acquired by the ambient temperature acquisition module as input, and the SOC estimation results of the single battery are output.
A plurality of equalizers in the equalization circuit are respectively responsible for equalization of a plurality of single batteries, and the equalizers receive control signals sent by the equalization algorithm module to realize the equalization function of the battery pack.
The SOC estimation module comprises a first-order RC battery equivalent circuit model module, an offline parameter identification and extraction module, a two-dimensional lookup table module, a UKF algorithm module, an RLS algorithm module and an SOC initial value module.
The off-line parameter identification and extraction module is used for acquiring a terminal voltage value and a discharge current value of the target battery and acquiring an off-line parameter identification and extraction result of the model parameter by utilizing parameter identification and extraction;
the two-dimensional lookup table module utilizes the parameters extracted by the offline parameter identification and extraction module to establish an R0 two-dimensional lookup table, an R1 two-dimensional lookup table, a C1 two-dimensional lookup table and an OCV two-dimensional lookup table;
the SOC initial value module obtains an initial value of the SOC through an SOC two-dimensional lookup table, the input of the SOC two-dimensional lookup table is an initial OCV value and environment temperature information collected by the environment temperature collecting module, the SOC two-dimensional lookup table is obtained by converting the OCV two-dimensional lookup table, and the initial OCV value is obtained from an initial end voltage value of the battery when the battery works.
The UKF algorithm module establishes a state equation and a measurement equation of the UKF according to a first-order RC battery equivalent circuit model, an initial value of the SOC is used as an input value to form a state vector of the UKF, a real-time terminal voltage value and a real-time current value are also input into the UKF algorithm module, an SOC value at a new moment is obtained according to the UKF algorithm, and the current value is determined by the current SOC value, environment temperature information acquired by the environment temperature acquisition module and an OCV two-dimensional lookup table and is given to the RLS algorithm module.
The battery model parameter updating method comprises the steps that an RLS algorithm module determines a conversion relation between battery model parameters and RLS parameter vectors according to a first-order RC battery equivalent circuit model, the OCV value at a new moment obtained by a UKF algorithm is added with a real-time terminal voltage value and a real-time current value to update the state vector of the RLS algorithm, so that an online identification result of the model parameters is obtained, the battery model parameter values are updated, and then the online identification result is fed back to the UKF algorithm module, and a state equation and a measurement equation in the UKF algorithm module are updated.
The first-order RC battery equivalent circuit model module comprises a voltage source, a resistor R0, a resistor R1 and a capacitor, wherein the positive electrode of the voltage source is connected with one end of the resistor R1 and one end of the capacitor, the negative electrode of the voltage source is grounded, and the other end of the resistor R1 is connected with the other end of the capacitor and one end of the resistor R0.
The specific implementation steps are as follows:
s1, estimating the SOC of each single battery according to the voltage, the current and the ambient temperature of each single battery;
s2, determining whether balance operation is needed or not through a balance control algorithm according to the SOC estimation result of each single battery;
s3, when the balancing operation is not needed, returning to S1, otherwise, performing the step S4;
and S4, further calculating a signal of each single battery needing to be balanced through a balance control algorithm, sending a balance starting signal to the battery needing to be balanced, returning the charge to the whole battery pack for redistribution, and then returning to S1.
Firstly, a simulation model of a proprietary SOC estimation algorithm is established in Matlab, the simulation result of the SOC estimation algorithm is shown in FIG. 3, and FIG. 4 shows that the SOC estimation error is lower than 0.87%.
Table 1 equalization control algorithm test results
And then, respectively carrying out experiment comparison under the conditions of no equalization control algorithm and the conditions of equalization control algorithm, and recording the working time of the battery pack, wherein the experiment test results in table 1 show that after the equalization control algorithm is added, the working time of the battery pack is increased from 1 hour 42 minutes to 3 hours 34 minutes, which shows that the invention can effectively improve the effective capacity of the battery.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. A BMS structure based on a proprietary SOC estimation and a proprietary equalization algorithm is characterized by comprising a plurality of SOC estimation modules, an equalization algorithm module and an equalization circuit, wherein the equalization circuit comprises a plurality of equalizers;
the SOC estimation modules are used for estimating the SOC values of the single batteries and outputting the estimation results to the balance control algorithm module;
the equalization algorithm module is responsible for calculating equalization signals required by each single-head battery, takes SOC value estimation results of each single battery in the battery pack as input, and then sends the calculated equalization signals to the plurality of equalization circuits.
2. The BMS structure based on proprietary SOC estimation and proprietary equalization algorithm according to claim 1, further comprising an ambient temperature collection module, wherein an output of the ambient temperature collection module is electrically connected to inputs of the SOC estimation modules, and the ambient temperature collection module is used for collecting ambient temperature information and transmitting the ambient temperature information to the SOC estimation modules.
3. The BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm of claim 2, wherein output terminals of the SOC estimation modules are electrically connected to input terminals of the equalization control algorithm module, and the SOC estimation modules input the corresponding cell voltage, current and ambient temperature information collected by the ambient temperature collection module and output SOC estimation results of the cells.
4. The BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm of claim 1, wherein a plurality of equalizers of the equalization circuit are respectively responsible for equalization of a plurality of battery cells, and the plurality of equalizers receive control signals sent by the equalization algorithm module to realize equalization function of the battery pack.
5. The BMS structure based on proprietary SOC estimation and proprietary equalization algorithm of claim 1, wherein the SOC estimation module comprises a first order RC battery equivalent circuit model module, an offline parameter identification and extraction module, a two-dimensional lookup table module, a UKF algorithm module, a RLS algorithm module, and a SOC initial value module;
the off-line parameter identification and extraction module is used for acquiring a terminal voltage value and a discharge current value of the target battery and acquiring an off-line parameter identification and extraction result of the model parameter by utilizing parameter identification and extraction;
the two-dimensional lookup table module utilizes the parameters extracted by the offline parameter identification and extraction module to establish an R0 two-dimensional lookup table, an R1 two-dimensional lookup table, a C1 two-dimensional lookup table and an OCV two-dimensional lookup table;
the SOC initial value module obtains an initial value of the SOC through an SOC two-dimensional lookup table, the input of the SOC two-dimensional lookup table is an initial OCV value and environment temperature information collected by the environment temperature collecting module, the SOC two-dimensional lookup table is obtained by converting the OCV two-dimensional lookup table, and the initial OCV value is obtained from an initial end voltage value of the battery when the battery works.
6. The BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm according to claim 5, wherein the UKF algorithm module establishes a state equation and a measurement equation of the UKF according to a first-order RC battery equivalent circuit model, and uses an initial value of SOC as an input to form an initial value of a state vector of the UKF, real-time terminal voltage value and current value are also input into the UKF algorithm module, obtains an SOC value at a new moment according to the UKF algorithm, and determines an OCV value at the moment to be given to the RLS algorithm module by using the SOC value at the moment, the environmental temperature information collected by the environmental temperature collection module, and the OCV two-dimensional lookup table.
7. The BMS structure based on the proprietary SOC estimation and the proprietary equalization algorithm according to claim 5, wherein the RLS algorithm module determines a conversion relationship between battery model parameters and RLS parameter vectors according to a first-order RC battery equivalent circuit model, and the OCV value at a new moment obtained by the UKF algorithm plus the real-time terminal voltage value and current value are used for updating the state vectors of the RLS algorithm, so that online identification results of the model parameters are obtained, and battery model parameter values are updated and then fed back to the UKF algorithm module to update the state equations and the measurement equations in the UKF algorithm module.
8. The BMS structure based on proprietary SOC estimation and proprietary equalization algorithm of claim 5, wherein the first order RC battery equivalent circuit model module comprises a voltage source, a resistor R0, a resistor R1, and a capacitor, wherein the positive terminal of the voltage source is connected to one terminal of the resistor R1 and one terminal of the capacitor, the negative terminal of the voltage source is grounded, and the other terminal of the resistor R1 is connected to the other terminal of the capacitor and one terminal of the resistor R0.
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