A method of extending the temperature range of a SOC prediction

Abstract

The application provides a method for extending the temperature range of SOC prediction, collects dynamic discharge data of a battery at different temperatures, establishes a regression equation of state of charge-terminal voltage at different temperatures, calculates voltage compensation factors at different temperatures based on room temperature, adds corresponding temperature compensation factors to the real-time measured voltage for underwater vehicles working at different ambient temperatures, and solves the influence of ambient temperature on the SOC evaluation algorithm. The temperature compensation factor introduced by the application is simple to operate and has small calculation amount, the proposed temperature range extension method can significantly improve the prediction accuracy of the SOC prediction algorithm in a low-temperature environment, only the voltage at different temperatures needs to be temperature compensated, so there is no excessive calculation burden, and the method can bring relatively practical application value in underwater vehicles.

Description

Technical Field

[0001] This invention relates to the field of underwater vehicles, and in particular to a method for predicting underwater temperature. Background Technology

[0002] Autonomous underwater vehicles (AUVs) are the primary tools for ocean exploration, possessing diverse civilian and military applications, and thus occupy an important position in national development and construction. Electric propulsion systems, with their advantages of low noise, no wake, immunity to pressure effects, suitability for deep-sea navigation, and ease of maintenance, are gradually becoming the most widely used propulsion method for underwater vehicles.

[0003] Batteries, by converting chemical energy into electrical energy, serve as excellent energy storage devices. Power lithium batteries, with their high safety, long cycle life, excellent power characteristics, and low operating costs, are currently the most ideal power source for industrial and scientific underwater vehicles. State of charge (SOC) is a parameter reflecting the remaining charge of a battery. Based on this parameter, the battery management system (BMS) performs a series of operations including charge / discharge control, equalization control, thermal management, and safety control. Therefore, accurate SOC prediction is crucial for the reliable operation of the entire battery system. However, the internal chemical reactions of a battery are closely related to temperature, making SOC prediction algorithms highly sensitive to external temperatures. Typical Kalman series SOC prediction algorithms exhibit significant errors under low-temperature conditions, thus limiting their practical application in engineering fields.

[0004] Therefore, it is extremely urgent to solve the problem of low prediction accuracy of existing SOC prediction algorithms under low temperature conditions. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a method for extending the predicted temperature range of SOC.

[0006] The specific steps of the technical solution adopted by the present invention to solve its technical problem are as follows:

[0007] Step 1: Collect dynamic discharge data of the battery at different temperatures. The dynamic discharge data includes the lower terminal voltage U at each sampling time. t and current i L And record dynamic discharge data;

[0008] Step 2: Establish State of Charge (SOC) - Terminal Voltage (U) at different temperatures t The regression equation for );

[0009] Step 3: Calculate the voltage compensation factor at each temperature based on room temperature;

[0010] SOC-U was obtained by fitting at room temperature. t Relation f 25 (SOC-Ut The slope a in ) 25 As the slope, SOC-U at other temperatures is successively fitted. t Relation f i (SOC-U t ), and then obtain the slope b corresponding to each temperature in sequence. i The temperature compensation factor at each temperature is obtained through the intercept b at 25°C. 25 Intercept b at the current temperature i The difference is used to obtain the temperature compensation factor, i.e., factor = b. 25 -b i ;

[0011] Step 4: For underwater vehicles operating under different ambient temperatures, add the corresponding temperature compensation factor to the real-time measured voltage to address the impact of ambient temperature on the SOC evaluation algorithm.

[0012] In step 2, the SOC calculation uses the ampere-hour integration method.

[0013] The SOC-U t The regression equation was established using the least squares linear regression method.

[0014] The temperature sampling points in step 3 include: -20℃, -10℃, 0℃, 10℃ and 25℃. The dynamic sampling data is the standard sampling data, the charging and discharging mode is the Urban Dynamometer Driving Schedule (UDDS), and the sampling frequency is 10Hz.

[0015] The beneficial effects of this invention are that the temperature compensation factor introduced by this invention is simple to operate and requires little computation. The proposed method for extending the temperature range can significantly improve the prediction accuracy of the SOC prediction algorithm in low-temperature environments. It only requires temperature compensation for the voltage at different temperatures, so there is no excessive computational burden. It can bring more practical application value to underwater vehicles. Attached Figure Description

[0016] Figure 1 This invention relates to SOC-U at different temperatures. t Fitted plot.

[0017] Figure 2 This invention compares the SOC predictions before and after adding a temperature compensation factor. Detailed Implementation

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] Step 1: Collect dynamic discharge data of the battery at different temperatures. The dynamic discharge data includes the lower terminal voltage U at each sampling time. t and current i L And record dynamic discharge data;

[0020] Step 2: Establish State of Charge (SOC) - Terminal Voltage (U) at different temperatures t The regression equation for );

[0021] Step 3: Calculate the voltage compensation factor at each temperature based on room temperature;

[0022] SOC-U was obtained by fitting at room temperature. t Relation f 25 (SOC-U t The slope a in ) 25 As the slope, SOC-U at other temperatures is successively fitted. t Relation f i (SOC-U t ), and then obtain the slope b corresponding to each temperature in sequence. i The temperature compensation factor at each temperature is obtained through the intercept b at 25°C. 25 Intercept b at the current temperature i The difference is used to obtain the temperature compensation factor, i.e., factor = b. 25 -b i ;

[0023] Step 4: For underwater vehicles operating under different ambient temperatures, add the corresponding temperature compensation factor to the real-time measured voltage to resolve the impact of ambient temperature on the SOC evaluation algorithm.

[0024] In step 2, the SOC calculation uses the ampere-hour integration method, SOC-U t The regression equation is established using the least squares linear regression method, such as... Figure 1 As shown.

[0025] The temperature sampling points in step 3 include: -20℃, -10℃, 0℃, 10℃ and 25℃. The dynamic sampling data is the standard sampling data, the charging and discharging mode is the Urban Dynamometer Driving Schedule (UDDS), and the sampling frequency is 10Hz.

[0026] The calculation method for the compensation factor at different temperatures in step 3 is as follows:

[0027] 3.1: Fitting SOC-U at 25℃ using least squares linear regression t Relation f 25 (SOC-U t Determine the slope a.25 and intercept b 25 ;

[0028] 3.2: The SOC and U values ​​of UDDS under operating conditions collected at -20℃, -10℃, 0℃, and 10℃ were analyzed respectively. t Least square fitting is performed to obtain the least square fitting curve, where the slope remains constant at 25℃. 25 Thus, the SOC-U at various temperatures can be obtained. t Relation f i (SOC-U t ), where the subscript i represents the various temperature values: -20, -10, 0, 10;

[0029] 3.3: Intercept b under 25℃ operating conditions 25 Using this as a baseline, calculate the intercept b at each temperature. i With b 25 The difference is used as a compensation factor (factor = b) at different temperatures. 25 -b i .

[0030] In step 4, the compensation factor for the underwater vehicle at various operating temperatures can be obtained by linearly interpolating the above five temperature nodes.

[0031] Based on the UKF-RBFFNN-based SOC evaluation algorithm, the results before and after introducing this temperature compensation strategy are presented, such as... Figure 2 As shown in the figure, the results demonstrate that the prediction performance of the UKF-RBFFNN-based SOC estimator is significantly improved after adding the compensation factor, with the improvement becoming more pronounced at lower temperatures. At -20℃, the SOC evaluation results after adding the temperature compensation factor remain well consistent with the reference value throughout the discharge process.

Claims

1. A method for extending the predicted temperature range of State of Charge (SOC), characterized in that... Includes the following steps: Step 1: Collect dynamic discharge data of the battery at different temperatures. The dynamic discharge data includes the lower terminal voltage U at each sampling time. t and current i L And record dynamic discharge data; Step 2: Establish the state of charge (SOC) terminal voltage U at different temperatures t The regression equation; Step 3: Calculate the voltage compensation factor at each temperature based on room temperature; SOC-U was obtained by fitting at room temperature. t Relation f 25 (SOC-U t The slope a in ) 25 As the slope, SOC-U at other temperatures is successively fitted. t Relation f i (SOC-U t The slope k corresponding to each temperature is obtained sequentially, and the intercept b of the temperature compensation factor at each temperature through 25℃ is obtained. 25 Intercept b at the current temperature i The difference is used to obtain the temperature compensation factor, i.e., factor = b. 25 -b i ; Step 4: For underwater vehicles operating under different ambient temperatures, add the corresponding temperature compensation factor to the real-time measured voltage to address the impact of ambient temperature on the SOC evaluation algorithm.

2. The method for extending the SOC prediction temperature range according to claim 1, characterized in that: In step 2, the SOC calculation uses the ampere-hour integration method.

3. The method for extending the SOC prediction temperature range according to claim 1, characterized in that: The SOC-U t The regression equation was established using the least squares linear regression method.

4. The method for extending the SOC prediction temperature range according to claim 1, characterized in that: The temperature sampling points in step 3 include: -20℃, -10℃, 0℃, 10℃ and 25℃. The dynamic sampling data is the standard sampling data, the charging and discharging mode is the urban road cycle UDDS, and the sampling frequency is 10Hz.

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