An anti-interference direct identification method for characteristic parameters of super capacitor circuit

Abstract

The application discloses an anti-interference direct identification method for characteristic parameters of a super capacitor circuit, and comprises the following steps: initializing a to-be-detected super capacitor to a zero state, applying a direct current voltage source with a constant amplitude to the to-be-detected super capacitor, sampling and saving a super capacitor current, performing a sliding mean filtering process on samples, calculating a first characteristic coefficient, a second characteristic coefficient and a third characteristic coefficient, calculating a first identification parameter, a second identification parameter and an average identification parameter, calculating a decay factor and a homogenization factor, and analyzing an equivalent resistance and a capacitance of a characteristic parameter of the super capacitor circuit; the application takes the super capacitor as a detection object, performs real-time monitoring on circuit characteristic parameters of the super capacitor, constructs a simulation model of the super capacitor, verifies the identification method through experiments, and experiment results show that the method can accurately, effectively and reliably estimate the sizes of the characteristic parameters in an interference environment and has no physical damage to the super capacitor.

Description

Technical Field

[0001] This invention relates to the field of supercapacitor parameter identification technology, and in particular to an anti-interference direct identification method for supercapacitor circuit characteristic parameters. Background Technology

[0002] With the rapid development of new energy technologies and the electric vehicle industry, supercapacitors, as a novel energy storage device, are increasingly widely used in fields such as electric vehicle energy recovery, new energy power generation smoothing, rail transit braking energy recovery, and uninterruptible power supplies due to their advantages such as high power density, long cycle life, fast charge and discharge speed, and wide operating temperature range. Accurately identifying the equivalent circuit parameters of supercapacitors is of great practical significance for the design of battery management systems, state of charge estimation, and health status assessment.

[0003] like Figure 1 As shown, the equivalent circuit model of a supercapacitor mainly consists of the equivalent resistance R. eq and equivalent capacitance C eq It is connected in series, and its input voltage is u. in (t), capacitor voltage is u c Given i(t) and i(t), from circuit knowledge, we have:

[0004] (1.1)

[0005] (1.2)

[0006] Input voltage u in (t) represents the step signal, i.e.:

[0007] (1.3)

[0008] That is, before operation, there is no voltage input, and the supercapacitor is connected to the ground via grounding or other means. c Both (t) and i(t) are zero, meaning the supercapacitor is in a zero state. That is, after it starts working, the input voltage u of the supercapacitor in (t) is a constant value E S By combining equations (1.1) to (1.3), the voltage u in the time domain can be solved. c (t), current i(t). For packaged supercapacitor products, measure its internal capacitor voltage u. c Measuring the external current i(t) is relatively difficult, but measuring the external current i(t) is relatively easy.

[0009] Typically, nonlinear indirect methods are used to identify the characteristic parameter R of supercapacitor circuits. eq Ceq These methods require a good initial point; otherwise, convergence is slow, and they often get stuck in local optima instead of global optima. These methods generally suffer from high computational complexity and are sensitive to noise and interference. Most have complex processes, and some identification methods can only estimate capacitance parameters; the equivalent resistance also affects actual operation, changing with temperature and other factors, leading to inaccuracies in supercapacitor measurements. Some identification methods do not consider the influence of resistance, resulting in inaccurate capacitance measurements. Currently, a direct identification method with low computational cost has been developed, but its anti-interference capability is limited; when the noise / signal ratio is down to 3.9%, the identification error of circuit characteristic parameters approaches 10%. In many cases, the noise / signal ratio is higher than 3.9%. Therefore, this invention proposes an anti-interference direct identification method for supercapacitor circuit characteristic parameters to solve the problems existing in the prior art. Summary of the Invention

[0010] To address the aforementioned problems, the present invention aims to propose an anti-interference direct identification method for the characteristic parameters of supercapacitor circuits, thereby solving the problems that most existing supercapacitor parameter identification methods suffer from sensitivity to initial points, high computational complexity, and poor noise resistance.

[0011] To achieve the objectives of this invention, the invention is implemented through the following technical solution: a direct anti-interference identification method for characteristic parameters of a supercapacitor circuit, comprising the following steps:

[0012] Step 1: Initialize the supercapacitor under test to a zero state, and prepare a voltage amplitude of A constant DC voltage source and a current acquisition system;

[0013] Step 2: Connect the voltage source prepared in Step 1 to the input terminal of the supercapacitor under test. Simultaneously, use the current acquisition system prepared in Step 1 to sample and save the current i(t) of the supercapacitor under test. The sample is denoted as g(k) = i(kT). S ), representing the current sampled in the k-th sampling period, k = 1, 2, 3, ..., M, where M is the number of samples and the sampling period is . ;

[0014] Step 3: Perform moving mean filtering on the sample g(k) saved in Step 2 to obtain the processed sample h(k). ω is the width of the filter window, k = 1 + 0.5ω, 2 + 0.5ω, 3 + 0.5ω, ..., M ‒ 0.5ω;

[0015] Step 4: Using the sample h(k), calculate the first characteristic coefficient α(k), the second characteristic coefficient β(k), and the third characteristic coefficient γ(k), where k = 2 + 0.5ω, 3 + 0.5ω, 4 + 0.5ω, 5 + 0.5ω, ..., n, n < 0.5M ‒ 0.25ω;

[0016] Step 5: Calculate the first identification parameter P1, the second identification parameter P2, and the average identification parameter P. avg ;

[0017] Step 6: Calculate the attenuation factor λ(k) and the homogenization factor λ avg ;

[0018] Step 7: Analyze the characteristic parameters of the supercapacitor circuit, specifically the equivalent resistance R. eq With capacitor C eq .

[0019] A further improvement lies in the following: the calculation formulas for the first characteristic coefficient α(k), the second characteristic coefficient β(k), and the third characteristic coefficient γ(k) in step four are as follows:

[0020]

[0021]

[0022] .

[0023] The further improvement lies in: the first identification parameter P1, the second identification parameter P2, and the average identification parameter P in step five. avg The calculation formula is:

[0024]

[0025]

[0026] .

[0027] In the formula, E s The voltage amplitude of a constant DC voltage source.

[0028] A further improvement lies in: the attenuation factor λ(k) and the homogenization factor λ in step six. avg The calculation formula is:

[0029]

[0030] .

[0031] A further improvement lies in: the equivalent resistance R of the supercapacitor circuit characteristic parameter in step seven.eq and capacitor C eq The calculation formula is:

[0032] .

[0033] The beneficial effects of this invention are as follows: This invention uses a supercapacitor as the detection object, identifies the characteristic parameters of its equivalent circuit, constructs a simulation model of the supercapacitor based on the MATLAB / Simulink platform, and verifies the calculation method of the characteristic parameters within the equivalent circuit through experiments. Analysis of the experimental results confirms that the identification method of this invention can accurately estimate the magnitude of the supercapacitor circuit characteristic parameters by real-time monitoring of the supercapacitor's current without disassembling or damaging the supercapacitor. It has outstanding advantages such as strong anti-interference ability, high data acquisition timeliness, high accuracy, and no damage to the supercapacitor. Furthermore, it involves low computational load, high identification accuracy, and stable and reliable identification, laying the foundation for more timely and accurate dynamic monitoring of the supercapacitor's operating status. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a schematic diagram of the first-order RC equivalent circuit model of a supercapacitor in the background technology of this invention;

[0036] Figure 2 This is a flowchart illustrating the anti-interference direct identification method for supercapacitor circuit characteristic parameters of the present invention.

[0037] Figure 3 This is a schematic diagram of the supercapacitor circuit test system architecture in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0039] See Figure 1 , Figure 2 , Figure 3In this embodiment, a supercapacitor circuit model is established in the Simulink environment of MATLAB, and experiments are conducted on this circuit model to verify the method of the present invention. The specific steps are as follows:

[0040] Step 1: First, establish a circuit model for the supercapacitor, such as... Figure 3 As shown, the equivalent resistance R eq =1.008Ω, equivalent capacitance C eq =10.3125F, the gain after white noise is set to 0, that is, there is no noise interference input, and a step signal with an amplitude of 768 controls the controlled voltage source to generate E. S =768V step power supply u in (t) is used for the supercapacitor. The current sensor collects the supercapacitor current i(t). The voltage across the capacitor is initialized to 0V, that is, the supercapacitor is initialized to a zero state.

[0041] Step 2: Set the sampling period T S =0.001 seconds, simulation started, u in (t) is connected to the input terminal of the supercapacitor. At the same time, the current sensor collects i(t) and saves it, denoted as g(k) = i(kT). S ), representing the k-th sampled value, k = 1, 2, 3, ..., M. When M = 50000, the simulation duration reaches 50 seconds, which is approximately 5 times the time constant, and the experiment ends and sampling ends.

[0042] Step 3: Perform moving mean filtering on the sample g(k) saved in Step 2 to obtain the processed sample h(k). ω is the width of the filter window, taken as ω = 51, k = 27, 28, 29, ..., 49974:

[0043] Step 4: Using the sample h(k), calculate the first characteristic coefficient α(k), the second characteristic coefficient β(k), and the third characteristic coefficient γ(k), where k = 28, 29, 30, ..., 20000.

[0044]

[0045]

[0046] ;

[0047] Step 5: Calculate the first identification parameter P1, the second identification parameter P2, and the average identification parameter P. avg ,in,

[0048]

[0049]

[0050] ;

[0051] Step 6: Calculate the attenuation factor λ(k) and the homogenization factor λ. avg ,in,

[0052]

[0053] ;

[0054] Step 7: Calculate the equivalent resistance R of the supercapacitor. eq and capacitor C eq ,in,

[0055]

[0056]

[0057] The circuit characteristic parameters of the supercapacitor identified in step seven above are: R eq =1.0080000195802Ω, C eq =10.31250161F. Therefore, the supercapacitor circuit characteristic parameter identification method proposed in this invention, for the specific case in the experiment, has R... eq C eq The relative identification errors were 1.984 × 10⁻⁶. -6 %, 9.697×10 -3 As can be seen, the supercapacitor circuit characteristic parameter identification method proposed in this invention can effectively identify interference-free systems with high identification accuracy.

[0058] In practical applications, input signals, supercapacitors, and acquired signals are often affected by interference. This interference can be equivalently incorporated into the input signal, typically manifesting as white noise. To test the anti-interference performance of the identification method proposed in this invention, such as... Figure 3 As shown, in Figure 1 A white noise signal module was added to the model input to simulate the interference signals experienced by the system. The supercapacitor in the interference environment can be practically equivalent to... Figure 3 In the model shown, the actual input to the supercapacitor, besides the pure input signal u, is... in (t), and also the amplified white noise, i.e., the equivalent interference. Correspondingly, the supercapacitor current i(t) not only includes u inThe interference generated by (t) also includes the interference generated by equivalent interference. In the experiment, the white noise module was set with a power spectral density of 0.001 and a seed number of 5. The interference intensity in the actual working environment was simulated by changing the amplitude of the noise, which was achieved by setting the gain after the white noise. In the experiment, the gain was set to 153.6, 307.2, 460.8, and 614.4, which correspond to interference amplitudes of 153.6V, 307.2V, 460.8V, and 614.4V, respectively, and corresponding to noise / signal ratios of 20%, 40%, 60%, and 80%. Each time the gain was changed, that is, the interference amplitude or noise / signal ratio was changed, the above steps one to seven were repeated as in the experiment above, and an identification experiment was performed. The final experimental results are shown in Table 1. Table 1 records the identification experiments of the present invention with interference in five typical cases.

[0059] As shown in Table 1, the identification method proposed in this invention can effectively, accurately, and reliably identify the characteristic parameters of supercapacitor circuits. Under interference-free conditions, the method exhibits very high accuracy, with relative errors in estimating the equivalent resistance and capacitance less than 10%. -2 The level of error is approximately zero in engineering practice. Generally, the identification error of this method gradually increases with the increase of white noise amplitude or the increase of the noise-to-signal ratio. As the interference noise-to-signal ratio increases from 20% to 80%, the relative error of the equivalent resistance increases from 2.222% to 3.304%, while that of the equivalent capacitance increases from -1.395% to -8.494%. The increase in the relative estimation error of the equivalent capacitance is greater than that of the equivalent resistance. An 80% noise-to-signal ratio and a relative error of less than 10% indicate that the identification method proposed in this invention has high accuracy, strong anti-interference capability, and can meet most practical needs. These results demonstrate that the identification method proposed in this invention has strong anti-interference capability, high identification accuracy, and is stable and reliable.

[0060] Table 1. Identification of characteristic parameters of supercapacitor circuits with white noise interference signals.

[0061]

[0062] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for direct, interference-resistant identification of characteristic parameters of a supercapacitor circuit, characterized in that, Includes the following steps: Step 1: Initialize the supercapacitor under test to a zero state, and prepare a voltage amplitude of A constant DC voltage source and a current acquisition system; Step 2: Connect the voltage source prepared in Step 1 to the input terminal of the supercapacitor under test. Simultaneously, use the current acquisition system prepared in Step 1 to sample and save the current i(t) of the supercapacitor under test. The sample is denoted as g(k) = i(kT). S ), representing the current sampled in the k-th sampling period, k = 1, 2, 3, ..., M, where M is the number of samples and the sampling period is . ; Step 3: Perform moving mean filtering on the sample g(k) saved in Step 2 to obtain the processed sample h(k). ω is the width of the filter window, k = 1 + 0.5ω, 2 + 0.5ω, 3 + 0.5ω, ..., M ‒ 0.5ω; Step 4: Using the sample h(k), calculate the first characteristic coefficient α(k), the second characteristic coefficient β(k), and the third characteristic coefficient γ(k), where k = 2+0.5ω, 3+0.5ω, 4+0.5ω, 5+0.5ω, ..., n, n < 0.5M-0.25ω; Step 5: Calculate the first identification parameter P1, the second identification parameter P2, and the average identification parameter P. avg ; Step 6: Calculate the attenuation factor λ(k) and the homogenization factor λ. avg ; Step 7: Calculate the equivalent resistance R of the supercapacitor circuit characteristic parameters. eq and capacitor C eq .

2. The anti-interference direct identification method for characteristic parameters of a supercapacitor circuit according to claim 1, characterized in that: The formulas for calculating the first characteristic coefficient α(k), the second characteristic coefficient β(k), and the third characteristic coefficient γ(k) in step four are as follows: 。 3. The anti-interference direct identification method for characteristic parameters of a supercapacitor circuit according to claim 1, characterized in that: The first identification parameter P1, the second identification parameter P2, and the average identification parameter P in step five. avg The calculation formula is: In the formula, E s The voltage amplitude of a constant DC voltage source.

4. The anti-interference direct identification method for characteristic parameters of a supercapacitor circuit according to claim 1, characterized in that: The attenuation factor λ(k) and the homogenization factor λ in step six avg The calculation formula is: 。 5. The anti-interference direct identification method for characteristic parameters of a supercapacitor circuit according to claim 1, characterized in that: The supercapacitor circuit characteristic parameter, equivalent resistance R, in step seven is mentioned. eq and capacitor C eq The calculation formula is: 。

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