CN110554319A - battery parameter detection method based on improved lithium ion battery mathematical model - Google Patents
battery parameter detection method based on improved lithium ion battery mathematical model Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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Abstract
the invention discloses a battery parameter detection method based on an improved lithium ion battery mathematical model, which comprises the following steps: s10, obtaining the hysteresis voltage coefficient of the lithium ion battery; s20, constructing an improved lithium ion battery mathematical model according to the hysteresis voltage coefficient; the improved lithium ion battery mathematical model represents a circuit structure of the lithium ion battery and a relation between a hysteresis voltage and a hysteresis voltage coefficient in the circuit structure; and S30, solving the improved lithium ion battery mathematical model to obtain the hysteresis voltage generated in the working process of the lithium ion battery. The method has the advantages that the acquired battery parameters have higher accuracy, and the acquisition efficiency of the battery parameters can be improved.
Description
Technical Field
the invention relates to the technical field of batteries, in particular to a battery parameter detection method based on an improved lithium ion battery mathematical model.
Background
With the increasing requirements of electric automobiles on power and energy density of power batteries, the realization of commercialization of novel lithium ion batteries with excellent performance is of great significance. However, under the actual vehicle condition, some types of batteries generate a severe voltage hysteresis phenomenon in the charging and discharging process, which greatly increases the management difficulty of the power battery state. Some traditional lithium ion battery mathematical models directly ignore the influence of voltage hysteresis, and some traditional lithium ion battery mathematical models do not consider the change characteristics of the voltage hysteresis of different types of lithium ion batteries, so that the practical situation cannot be reflected, and the limitation is large, thereby easily causing the low accuracy of battery parameters such as the battery SOC (State of Charge) determined according to the traditional lithium ion battery mathematical models.
Disclosure of Invention
Aiming at the problems, the invention provides a battery parameter detection method based on an improved lithium ion battery mathematical model.
In order to achieve the purpose of the invention, the invention provides a battery parameter detection method based on an improved lithium ion battery mathematical model, which comprises the following steps:
s10, obtaining the hysteresis voltage coefficient of the lithium ion battery;
S20, constructing an improved lithium ion battery mathematical model according to the hysteresis voltage coefficient; the improved lithium ion battery mathematical model represents a circuit structure of the lithium ion battery and a relation between a hysteresis voltage and a hysteresis voltage coefficient in the circuit structure;
And S30, solving the improved lithium ion battery mathematical model to obtain the hysteresis voltage generated in the working process of the lithium ion battery.
In one embodiment, the battery parameter detection method based on the improved mathematical model of the lithium ion battery further includes:
determining the average steady-state open-circuit voltage of the lithium ion battery according to the charge-discharge characteristic curve of the lithium ion battery and the hysteresis voltage generated by the lithium ion battery in the working process;
and determining the SOC of the lithium ion battery according to the average steady-state open-circuit voltage of the lithium ion battery.
As an embodiment, the determining an average steady-state open-circuit voltage of the lithium ion battery according to the charge-discharge characteristic curve of the lithium ion battery and a hysteresis voltage generated during the operation of the lithium ion battery includes:
fitting the hysteresis voltage generated in the working process of the lithium ion battery into a hysteresis voltage curve;
Determining the average steady-state open-circuit voltage curve according to the difference between the charge-discharge characteristic curve and the hysteresis voltage curve;
And identifying the average steady-state open-circuit voltage of the lithium ion battery at each working moment according to the average steady-state open-circuit voltage curve.
As one embodiment, the determining the SOC of the lithium ion battery according to the average steady-state open circuit voltage of the lithium ion battery comprises:
Acquiring a corresponding relation between the average steady-state open-circuit voltage and the SOC of the lithium ion battery;
and determining the SOC corresponding to the average steady-state open-circuit voltage at each working moment according to the corresponding relation.
In one embodiment, the improved mathematical model of the lithium ion battery comprises:
In the formula of UbRepresenting the voltage across a first capacitor in said circuit arrangement, UsRepresenting the voltage across a second capacitor, U, in said circuit arrangementhRepresenting the hysteresis voltage, UlRepresenting the load voltage, IlRepresenting the load current, CbDenotes a first capacitance, Csdenotes a second capacitance, Redenotes the polarization resistance, RsThe surface effect resistance is expressed in terms of,represents a pair of Ubfinding a first derivative，Represents a pair of Usa first derivative is obtained by calculating the first derivative,Represents a pair of UhA first derivative is obtained by calculating the first derivative,Represents a pair of UlCalculating a first derivative, kappa represents a hysteresis voltage coefficient, I represents the current of the lithium ion battery in the charging and discharging process, M represents half of the maximum hysteresis voltage of the lithium ion battery, sgn (I) represents the sign of calculating I, and R representstRepresenting the termination resistance.
In one embodiment, the obtaining the hysteresis voltage coefficient of the lithium ion battery includes:
And fitting the relation between the hysteresis voltage and the hysteresis voltage coefficient of the lithium ion battery into a hysteresis corresponding curve on a simulation platform, and determining the hysteresis voltage coefficient according to the hysteresis corresponding curve.
as an embodiment, the simulation platform is Matlab.
According to the battery parameter detection method based on the improved lithium ion battery mathematical model, the circuit structure representing the lithium ion battery and the improved lithium ion battery mathematical model representing the relation between the hysteresis voltage and the hysteresis voltage coefficient in the circuit structure are constructed, so that the battery parameters such as the hysteresis voltage generated in the working process of the lithium ion battery are obtained through solving, the obtained battery parameters have higher accuracy, and the obtaining efficiency of the battery parameters can be improved.
drawings
FIG. 1 is a flow chart of a battery parameter detection method based on an improved mathematical model of a lithium ion battery according to an embodiment;
FIG. 2 is a circuit schematic of an embodiment;
FIG. 3 is a schematic diagram of a fitted curve of an embodiment;
FIG. 4 is a simulation model diagram of a battery of an embodiment;
FIG. 5 is a diagram illustrating simulation results according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 is a flowchart of a battery parameter detection method based on an improved mathematical model of a lithium ion battery according to an embodiment, including the following steps:
S10, obtaining the hysteresis voltage coefficient of the lithium ion battery;
the lithium ion battery has a corresponding hysteresis voltage coefficient, and the hysteresis voltage coefficient can be obtained by performing corresponding curve fitting on a relevant simulation platform.
specifically, the step S10 can be implemented by the following processes:
And fitting the relation between the hysteresis voltage and the hysteresis voltage coefficient of the lithium ion battery into a hysteresis corresponding curve on a simulation platform, and determining the hysteresis voltage coefficient according to the hysteresis corresponding curve.
In one example, the simulation platform is Matlab.
s20, constructing an improved lithium ion battery mathematical model according to the hysteresis voltage coefficient; the improved lithium ion battery mathematical model represents a circuit structure of the lithium ion battery and a relation between a hysteresis voltage and a hysteresis voltage coefficient in the circuit structure;
The circuit structure can represent the direct connection relation of all components of the lithium ion battery. The improved lithium ion battery mathematical model can represent the relationship among device parameters (such as capacitance, resistance and the like), current parameters and voltage parameters among all components in the corresponding circuit structure, and can also represent the relationship between hysteresis voltage and hysteresis voltage coefficient of the whole circuit structure; the method can be used for modeling simulation of common lithium ions, can be more suitable for modeling simulation of special batteries with larger charge-discharge voltage hysteresis, and has wide applicability and high simulation precision.
And S30, solving the improved lithium ion battery mathematical model to obtain the hysteresis voltage generated in the working process of the lithium ion battery.
In the above steps, a relevant mathematical calculation method can be adopted to correspondingly solve the improved lithium ion battery mathematical model, so as to obtain values of each parameter included in the improved lithium ion battery mathematical model at each working moment of the lithium ion battery in the working process, thereby obtaining the hysteresis voltage generated in the working process of the lithium ion battery.
According to the battery parameter detection method based on the improved lithium ion battery mathematical model, the circuit structure representing the lithium ion battery and the improved lithium ion battery mathematical model representing the relation between the hysteresis voltage and the hysteresis voltage coefficient in the circuit structure are constructed, so that the battery parameters such as the hysteresis voltage generated in the working process of the lithium ion battery are obtained through solving, the obtained battery parameters have higher accuracy, and the obtaining efficiency of the battery parameters can be improved.
In an embodiment, the battery parameter detection method based on the improved mathematical model of the lithium ion battery may further include:
Determining the average steady-state open-circuit voltage of the lithium ion battery according to the charge-discharge characteristic curve of the lithium ion battery and the hysteresis voltage generated by the lithium ion battery in the working process;
And determining the SOC of the lithium ion battery according to the average steady-state open-circuit voltage of the lithium ion battery.
In this embodiment, the average steady-state open-circuit voltage of the lithium ion battery has a corresponding relationship with the SOC, the average steady-state open-circuit voltage is obtained, and the SOC can be accurately determined.
As an embodiment, the determining the average steady-state open-circuit voltage of the lithium ion battery according to the charge-discharge characteristic curve of the lithium ion battery and the hysteresis voltage generated during the operation of the lithium ion battery includes:
Fitting the hysteresis voltage generated in the working process of the lithium ion battery into a hysteresis voltage curve;
determining the average steady-state open-circuit voltage curve according to the difference between the charge-discharge characteristic curve and the hysteresis voltage curve;
And identifying the average steady-state open-circuit voltage of the lithium ion battery at each working moment according to the average steady-state open-circuit voltage curve.
the embodiment can accurately determine the average steady-state open-circuit voltage of the lithium ion battery at each working moment. Specifically, the average steady-state open-circuit voltage corresponding to the current moment is the current average steady-state open-circuit voltage, and the current SOC of the lithium ion battery can be accurately determined according to the current average steady-state open-circuit voltage.
As an embodiment, the determining the SOC of the lithium ion battery according to the average steady-state open circuit voltage of the lithium ion battery includes:
Acquiring a corresponding relation between the average steady-state open-circuit voltage and the SOC of the lithium ion battery;
and determining the SOC corresponding to the average steady-state open-circuit voltage at each working moment according to the corresponding relation.
The average steady-state open-circuit voltage of each lithium ion battery and the SOC have corresponding relations, and according to the corresponding relations, the SOC of each working moment of the lithium ion battery can be accurately determined according to the average steady-state open-circuit voltage of each working moment of the lithium ion battery.
In one embodiment, the improved mathematical model of the lithium ion battery comprises:
in the formula of UbRepresenting the voltage across a first capacitor in said circuit arrangement, Usrepresenting the voltage across a second capacitor, U, in said circuit arrangementhrepresenting the hysteresis voltage, UlRepresenting the load voltage, IlRepresenting the load current, CbDenotes a first capacitance, Csdenotes a second capacitance, Redenotes the polarization resistance, Rsthe surface effect resistance is expressed in terms of,Represents a pair of UbA first derivative is obtained by calculating the first derivative,Represents a pair of Usa first derivative is obtained by calculating the first derivative,represents a pair of UhA first derivative is obtained by calculating the first derivative,Represents a pair of UlCalculating a first derivative, kappa represents a hysteresis voltage coefficient, I represents the current of the lithium ion battery in the charging and discharging process, M represents half of the maximum hysteresis voltage of the lithium ion battery, sgn (I) represents the sign of calculating I, and R representstrepresenting the termination resistance.
Specifically, the circuit structure of the lithium ion battery can be referred to as shown in fig. 2, and the above improved mathematical model of the lithium ion battery can completely and accurately represent the circuit structure shown in fig. 2. Compared with the traditional lithium ion battery mathematical model, the voltage hysteresis influence is directly ignored, the change characteristics of the voltage hysteresis of the lithium ion batteries of different types are not considered, the actual situation cannot be reflected, and the limitation is large. The improved lithium ion battery mathematical model introduces a voltage hysteresis coefficient in a common battery RC model, the voltage hysteresis coefficient can be obtained through early-stage test calculation and is embedded into the battery mathematical model, and therefore accurate estimation of battery parameters such as battery SOC is achieved.
In one example, a corresponding modified lithium ion battery mathematical model is constructed for the circuit structure shown in fig. 2, and a voltage hysteresis coefficient κ in the modified lithium ion battery mathematical model is obtained by Matlab versus first order differential equation:and performing curve fitting to obtain. First order differential equationThe curve fitted to Matlab can be seen in fig. 3, where in fig. 3, the abscissa represents SOC and the ordinate represents Uh. According to fig. 3, half M of the maximum hysteresis voltage deviation is about 0.5/2 to 0.25, the charging and discharging curves of the battery (lithium ion battery) are subtracted to obtain hysteresis voltage data, and then the curve in fig. 3 is fitted in Matlab by using a regression algorithm to obtain a hysteresis voltage coefficient k with a value of 3.6e-4。
Referring to fig. 4, a simulation model of the battery can be built in Matlab/simlink by using the mathematical model (improved lithium ion battery mathematical model). In fig. 4, U and I are operating condition current and terminal voltage data collected by the charging and discharging machine, the input initial parameters include parameters such as open-circuit voltage, temperature, hysteresis voltage, etc. of the battery, and the initial SOC of the battery is found according to the relationship between the open-circuit voltage and the SOC. According to the charge-discharge characteristic curve of the battery, the hysteresis voltage U is removed from the charge-discharge curve of the batteryhThe value U obtainedocvand is in one-to-one correspondence with the battery SOC. Here, U is put inocvis defined as electricityaverage steady state open circuit of the cell. From the improved RC equivalent circuit model, UocvEqual to the capacitance C in the improved RC modelb(first capacitance), capacitance Csthe voltage across (second capacitance), i.e.: u shapeb＝Us＝Uocvnamely:Wherein Q is C before and after the battery is placed stillbAnd CsThe electric quantity between the two can be converted, and after Q is calculated, U can be calculatedocvhas a value ofFinally, the SOC and the average steady-state open-circuit voltage U are comparedocvAnd interpolating the relation curve to obtain the SOC value of the battery. The estimation model of the SOC can be expressed as: SOCv(t)＝f(Ub,Us)。
Fig. 5 shows the result of comparing the model-based SOC estimation with the set initial SOC value. As can be seen from fig. 5, under typical conditions, both models considering battery charge-discharge hysteresis can track the preset SOC reference value well; the root mean square error of the SOC estimation of the battery model multiplied by the hysteresis coefficient is in a range of +/-4 percent, while the root mean square error of the SOC estimation of the improved battery model based on the invention is in a range of +/-2 percent, so that the SOC (state of charge) of the target battery can be estimated more accurately than the SOC estimation of the target battery.
Through a simulation surface, the improved lithium ion battery mathematical model can be used for modeling simulation of common lithium ions and can be more suitable for modeling simulation of special batteries with large charging and discharging voltage hysteresis, and the voltage hysteresis coefficient can be obtained through experimental calculation, so that the applicability is wide and the simulation accuracy is high.
the technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It should be noted that the terms "first \ second \ third" referred to in the embodiments of the present application merely distinguish similar objects, and do not represent a specific ordering for the objects, and it should be understood that "first \ second \ third" may exchange a specific order or sequence when allowed. It should be understood that "first \ second \ third" distinct objects may be interchanged under appropriate circumstances such that the embodiments of the application described herein may be implemented in an order other than those illustrated or described herein.
The terms "comprising" and "having" and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device that comprises a list of steps or modules is not limited to the listed steps or modules but may alternatively include other steps or modules not listed or inherent to such process, method, product, or device.
the above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (7)
1. A battery parameter detection method based on an improved lithium ion battery mathematical model is characterized by comprising the following steps:
s10, obtaining the hysteresis voltage coefficient of the lithium ion battery;
S20, constructing an improved lithium ion battery mathematical model according to the hysteresis voltage coefficient; the improved lithium ion battery mathematical model represents a circuit structure of the lithium ion battery and a relation between a hysteresis voltage and a hysteresis voltage coefficient in the circuit structure;
And S30, solving the improved lithium ion battery mathematical model to obtain the hysteresis voltage generated in the working process of the lithium ion battery.
2. The battery parameter detection method based on the improved lithium ion battery mathematical model according to claim 1, characterized by further comprising:
determining the average steady-state open-circuit voltage of the lithium ion battery according to the charge-discharge characteristic curve of the lithium ion battery and the hysteresis voltage generated by the lithium ion battery in the working process;
And determining the SOC of the lithium ion battery according to the average steady-state open-circuit voltage of the lithium ion battery.
3. the method of claim 2, wherein the determining the average steady-state open-circuit voltage of the lithium ion battery according to the charging and discharging characteristic curve of the lithium ion battery and the hysteresis voltage generated by the lithium ion battery during operation comprises:
Fitting the hysteresis voltage generated in the working process of the lithium ion battery into a hysteresis voltage curve;
determining the average steady-state open-circuit voltage curve according to the difference between the charge-discharge characteristic curve and the hysteresis voltage curve;
And identifying the average steady-state open-circuit voltage of the lithium ion battery at each working moment according to the average steady-state open-circuit voltage curve.
4. The method of claim 3, wherein the determining the SOC of the Li-ion battery according to the average steady-state open-circuit voltage of the Li-ion battery comprises:
acquiring a corresponding relation between the average steady-state open-circuit voltage and the SOC of the lithium ion battery;
and determining the SOC corresponding to the average steady-state open-circuit voltage at each working moment according to the corresponding relation.
5. The battery parameter detection method based on the improved lithium ion battery mathematical model according to any one of claims 1 to 4, characterized in that the improved lithium ion battery mathematical model comprises:
In the formula of UbRepresenting the voltage across a first capacitor in said circuit arrangement, Usrepresenting the voltage across a second capacitor, U, in said circuit arrangementhrepresenting the hysteresis voltage, UlRepresenting the load voltage, Ilrepresenting the load current, CbDenotes a first capacitance, CsDenotes a second capacitance, ReDenotes the polarization resistance, Rsthe surface effect resistance is expressed in terms of,Represents a pair of UbA first derivative is obtained by calculating the first derivative,Represents a pair of UsA first derivative is obtained by calculating the first derivative,represents a pair of Uha first derivative is obtained by calculating the first derivative,represents a pair of UlTaking a first derivative, k denotes lateThe hysteresis voltage coefficient is represented by I, M, sgn (I), R and R, wherein I represents the current of the lithium ion battery in the charging and discharging processes, M represents half of the maximum hysteresis voltage of the lithium ion battery, sgn (I) represents the sign of I calculation, and R represents the sign of I calculationtRepresenting the termination resistance.
6. The method for detecting battery parameters based on the improved mathematical model of the lithium ion battery according to any one of claims 1 to 4, wherein the obtaining the hysteresis voltage coefficient of the lithium ion battery comprises:
And fitting the relation between the hysteresis voltage and the hysteresis voltage coefficient of the lithium ion battery into a hysteresis corresponding curve on a simulation platform, and determining the hysteresis voltage coefficient according to the hysteresis corresponding curve.
7. The improved lithium ion battery mathematical model-based battery parameter detection method of claim 6, wherein the simulation platform is Matlab.
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