Multi-frequency small-signal discharge internal resistance on-line measurement method based on harmonic analysis

Abstract

This invention relates to the field of battery health status monitoring technology, and discloses an online measurement method for multi-frequency small-signal discharge internal resistance based on harmonic analysis, including the steps of: using a smart load module to measure the internal resistance of a multi-frequency small-signal discharge. i An alternating load is applied across the battery terminals at a specific frequency. The excitation generation module adjusts the switch duty cycle, and the intelligent load module adjusts the resistance value, ensuring that the amplitude of the 1kHz sinusoidal harmonic component in the current flowing through the battery is at a set value. The feedback adjustment module conditions the 1kHz sinusoidal harmonic component in the voltage and current across the battery terminals, sampling to obtain a discrete sequence. The intelligent computing unit obtains the amplitude and phase angle of the sequence through Fourier transform. Based on the phase angle, the ohmic internal resistance of the battery is calculated, and a linear regression algorithm is used to obtain the real-time internal resistance of the battery. This invention avoids damage to the battery during internal resistance measurement, reduces circuit design costs, increases operating speed, and improves measurement accuracy.

Description

Technical Field

[0001] This invention relates to the field of battery health status monitoring technology, and in particular to an online method for measuring the internal resistance of multi-frequency small-signal discharge based on harmonic analysis. Background Technology

[0002] Measuring the internal resistance of a battery can quickly assess its health status, determine its aging level and remaining lifespan, and prevent problems such as voltage drop, low charging and discharging efficiency, and unstable power supply caused by excessive internal resistance. In critical power systems (such as UPS, communication base stations, and rail transportation), regular internal resistance measurement helps prevent battery failures, ensures system reliability, and reduces the risk of sudden power outages. Simultaneously, internal resistance testing can help detect internal battery problems such as sulfation and plate corrosion, reducing the likelihood of safety accidents. Compared to battery capacity testing, internal resistance measurement is faster and more efficient, making it an important tool for battery maintenance and management.

[0003] In practice, the discharge method and AC injection method are commonly used to measure the ohmic internal resistance of a battery. The discharge method works because during discharge, the battery's internal resistance causes a drop in voltage across its terminals, especially noticeable under high load current. The basic idea of ​​the discharge method is to apply a known discharge current, record the voltage change, and then calculate the internal resistance from this voltage variation. This can be done using the following formula: To calculate, where R int V is the internal resistance of the battery. initial V is the battery voltage before current is applied (the voltage at the start of discharge). final I is the battery voltage after applying current (the voltage at the end of discharge), and I is the applied constant current (discharge current).

[0004] The AC injection method involves applying a small-amplitude sinusoidal current signal of known frequency to the battery port, then measuring the change in the battery voltage response to deduce the battery's internal resistance. Analyzing the ratio of the battery voltage and current signals allows for the calculation of the battery's impedance. The battery impedance is typically a complex number and can be expressed as... Among them, z (f) V is the complex impedance of the battery. (f) I is the voltage response after an AC signal is applied. (f) Let f be the current response of the battery, and f be the frequency of the AC signal. The internal resistance of the battery is usually expressed as the real part of the impedance at low frequencies. By analyzing the impedance spectrum of the battery in the low-frequency region, the ohmic internal resistance R of the battery can be obtained. int This is the resistance of the battery when it is working normally.

[0005] The discharge method requires the battery to discharge under certain load conditions. If the load current is too small, the battery voltage change may not be obvious, making it difficult to accurately measure the internal resistance. Conversely, if the load current is too large, the battery voltage may drop too quickly, potentially causing overheating or damage, posing a safety hazard. AC injection methods mostly require dedicated signal generation and conditioning circuits, which are complex, costly, and have weak anti-interference capabilities in the calculation results. Summary of the Invention

[0006] The purpose of this invention is to avoid damage to the battery during the measurement of its internal resistance, reduce circuit design costs, improve operating speed, and improve measurement accuracy, by providing an online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis.

[0007] To achieve the above-mentioned objectives, the embodiments of the present invention provide the following technical solutions:

[0008] The online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis includes the following steps:

[0009] Step 1, use the intelligent load balancing module to f i An alternating load is applied at the frequency of the battery terminals;

[0010] Step 2: The excitation generation module adjusts the switch duty cycle, and the intelligent load module adjusts the resistance value so that the amplitude of the 1kHz sinusoidal harmonic component in the current flowing through the battery is the set value.

[0011] Step 3: The feedback adjustment module conditions the 1kHz sinusoidal harmonic components in the voltage and current across the battery terminals and samples them to obtain a discrete sequence; the intelligent computing unit obtains the amplitude and phase angle of the sequence through Fourier transform.

[0012] Step 4: Calculate the ohmic internal resistance of the battery based on the phase angle, and use a linear regression algorithm to obtain the real-time internal resistance of the battery.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0014] This invention is based on multiple frequencies f i By applying an alternating load to both ends of the battery and taking the 1kHz sinusoidal harmonic component, the ohmic resistance of the battery is obtained. Then, by optimizing the weights and bias through linear regression, the real-time internal resistance of the battery can be measured online in a short calculation time. This calibration measurement method has low small-signal discharge energy (for batteries of different capacities, the small-signal current is only less than 0.1% of the battery's rated capacity, such as 25mA in this scheme), and the discharge process causes very little damage to the battery. It is suitable for long-term monitoring and repeated testing, has no safety hazards, and has high measurement accuracy, strong model training robustness, and strong anti-interference ability. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the method of the present invention;

[0017] Figure 2 This is a system block diagram of the present invention. Detailed Implementation

[0018] 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0019] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance, or suggesting any such actual relationship or order between these entities or operations. Additionally, the terms "connected," "linked," etc., can refer to a direct connection between elements or an indirect connection via other elements.

[0020] Example 1:

[0021] This invention is achieved through the following technical solutions, such as... Figure 1 As shown, the online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis includes the following steps:

[0022] Step 1, use the intelligent load balancing module to f i An alternating load is applied at the frequency of the battery terminals.

[0023] like Figure 2 As shown, the intelligent load module uses f iAn alternating load is applied at a frequency that causes a square wave voltage signal U of the same frequency to appear at both ends of the battery. io(t) and square wave current signal I io(t) Where i can take n values, i = 1, 2, ..., n, therefore the frequency f i Also in groups n, the same square wave voltage signal U io(t) and square wave current signal I io(t) There are also n groups.

[0024] Step 2: The excitation generation module adjusts the switch duty cycle, and the intelligent load module adjusts the resistance value so that the amplitude of the 1kHz sine wave harmonic component in the current flowing through the battery is 25mA.

[0025] The excitation generation module contains a switch. Adjusting the duty cycle P of the switch simultaneously adjusts the internal resistance R of the intelligent load module. This adjustment is achieved through the control of the duty cycle P, resistance R, and frequency f. i The three factors work together to generate the square wave current signal I at both ends of the battery. io(t) 1kHz sine wave harmonic component I i,1kHz The amplitude is 25mA. Specifically, typically n frequency groups f i It is predetermined, therefore when a frequency f is selected... i After the value of I, in order to i,1kHz If the amplitude is 25mA, it can be achieved by adjusting the duty cycle P and the resistance R.

[0026] Furthermore, a precision current sampling module connected between the smart load module and the battery is used to monitor the 1kHz sinusoidal harmonic component I in real time. i,1kHz The amplitude.

[0027] Step 3: The feedback adjustment module conditions the 1kHz sinusoidal harmonic components in the voltage and current across the battery terminals and samples them to obtain a discrete sequence; the intelligent computing unit obtains the amplitude and phase angle of the sequence through Fourier transform.

[0028] The feedback adjustment module includes a filtering module, a signal conditioning module, and a signal acquisition module. First, the filtering module processes the square wave voltage signal U across the battery terminals. io(t) and square wave current signal I io(o) Filtering is performed to remove unwanted signals, resulting in a voltage signal U with 1kHz sinusoidal harmonic components. i,1kHz The current signal I with 1kHz sinusoidal harmonic components i,1kHz Next, the signal conditioning module conditions the voltage signal U. i,1kHz and current signal I i,1kHz The signal is then conditioned and amplified. Finally, the signal acquisition module processes the conditioned and amplified voltage signal U. i,1kHzSampling yields a discrete voltage signal sequence U i,1kHz And the conditioned and amplified current signal I i,1kHz Sampling yields a discrete current signal sequence I i,1kHz .

[0029] The feedback adjustment module feeds back the current 1kHz sine wave harmonic component I to the excitation generation module and the intelligent load module. i,1kHz If the amplitude is not 25mA, the excitation module and the intelligent load module continue to adjust the duty cycle P and the resistance R.

[0030] The intelligent computing unit uses Fourier transform to calculate the discrete sequence U. i,1kHz and I i,1kHz The amplitude and the phase angle α between the two. i The Fourier transform algorithm for calculating amplitude and phase angle is a conventional technique, so it will not be elaborated here.

[0031] Step 4: Calculate the ohmic internal resistance of the battery based on the phase angle, and use a linear regression algorithm to obtain the real-time internal resistance of the battery.

[0032] Based on phase angle α i and discrete sequence U i,1kHz I i,1kHz The ohmic internal resistance r of the battery was calculated. i :

[0033]

[0034] Using the linear regression algorithm, we obtained:

[0035]

[0036] in, ω represents the real-time internal resistance of the battery. i Represents frequency f i The corresponding weights, where b represents the bias.

[0037] N sets of calibration data were obtained through experiments. in The frequency f in the k-th implementation represents i The corresponding ohmic resistances are i = 1, 2, ..., n; r k This represents the actual ohmic internal resistance of the battery measured by a high-precision internal resistance meter, k = 1, 2, ..., N. The model is trained using N sets of calibration data, and the optimization objective is to minimize the mean square error.

[0038]

[0039] After model training, the optimal weights ω are obtained. iAnd bias b. When actually measuring the real-time internal resistance of the battery, a certain frequency f is selected. i and the corresponding weight ω i Then, the real-time internal resistance of the battery can be obtained.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for online measurement of the internal resistance of multi-frequency small-signal discharge based on harmonic analysis, characterized in that, Includes the following steps: Step 1, use a smart load module at multiple frequencies Apply an alternating load across the battery terminals; Step 2: The excitation generation module adjusts the switch duty cycle, and the intelligent load module adjusts the resistance value so that the amplitude of the 1kHz sinusoidal harmonic component in the current flowing through the battery is the set value. Step 3: The feedback adjustment module conditions the 1kHz sinusoidal harmonic components in the voltage and current across the battery terminals and samples them to obtain a discrete sequence; the intelligent computing unit obtains the amplitude and phase angle of the sequence through Fourier transform. Step 4: Calculate the ohmic internal resistance of the battery based on the phase angle, and use a linear regression algorithm to obtain the real-time internal resistance of the battery. Step 4, which involves obtaining the real-time internal resistance of the battery using a linear regression algorithm, specifically includes: Using the linear regression algorithm, we obtained: in, This indicates the real-time internal resistance of the battery. Represents frequency The corresponding weights Indicates bias; N sets of calibration data were obtained through experiments. ,in Represents the frequency in the k-th group of experiments The corresponding ohmic resistance, i=1,2,...,n; This represents the actual ohmic internal resistance of the battery as measured by a high-precision internal resistance meter, k=1,2,...,N; The model is trained using N sets of calibration data, and the optimization objective is to minimize the mean squared error. After model training, the optimal weights are obtained. and bias ; When actually measuring the real-time internal resistance of a battery, a certain frequency is selected. and the corresponding weights Then, the real-time internal resistance of the battery can be obtained. .

2. The online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis according to claim 1, characterized in that, Step 1 specifically includes the following steps: Intelligent load module with An alternating load is applied at a frequency that causes square wave voltage signals of the same frequency to appear at both ends of the battery. and square wave current signal Here, i takes n values, i = 1, 2, ..., n, so n sets of square wave voltage signals can be obtained. and square wave current signal .

3. The online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis according to claim 2, characterized in that, Step 3 specifically includes the following steps: The feedback adjustment module includes a filtering module, a signal conditioning module, and a signal acquisition module; First, the filtering module processes the square wave voltage signal across the battery terminals. and square wave current signal After filtering, a voltage signal with 1kHz sinusoidal harmonic components is obtained. Current signal with 1kHz sine wave harmonic components ; Next, the signal conditioning module conditions the voltage signal. and current signal To adjust and amplify; Finally, the signal acquisition module processes the conditioned and amplified voltage signal. Sampling yields discrete voltage signal sequences. and the conditioned and amplified current signal Sampling yields discrete current signal sequences. .

4. The online measurement method for the internal resistance of multi-frequency small-signal discharge based on harmonic analysis according to claim 3, characterized in that, In step 4, the formula for calculating the ohmic internal resistance of the battery based on the phase angle is as follows: in, For phase angle; It is the internal resistance of the Ohm.

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