Multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system

Abstract

The invention relates to the field of power battery monitoring, in particular to a multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system, which has the technical scheme that when the system is applied to temperature monitoring of a new energy automobile power battery, a mathematical model for measuring current and temperature is constructed through a B spline curve; the predicted temperature of the monitored current is calculated to serve as a reference, a mathematical model of the monitored current and the predicted temperature is constructed through a Bezier curve, so that a relational expression between the current and the temperature is simplified, and the mathematical model of the monitored current and the monitored temperature is constructed through a rational Bezier curve; the control point weight serves as an evaluation index of the temperature change trend, the abnormity of the temperature change trend can be accurately detected before the temperature of the battery is obviously abnormal, the timeliness of problem discovery and solving is enhanced, the aging and damage degree of the battery is reduced, and the safety of vehicle driving is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of power battery monitoring, and in particular to a multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system. Background Art

[0002] With the popularization of new energy vehicles, safety issues have begun to emerge frequently, attracting widespread public attention. Among them, extreme environments, long-term high-speed driving, irregular charging, system failures, and battery aging or damage can cause abnormal power battery temperature. If the owner cannot understand the battery status in time, fails to effectively check the battery and solve the problem effectively, it will cause risks such as reduced cruising range, limited charging and discharging, accelerated aging, thermal runaway, short circuit, and electrolyte leakage.

[0003] There is a relationship of mutual restriction and mutual influence between the temperature and current of the power battery of the car. At present, the battery management system of electric vehicles will monitor the temperature and current and other parameters of the battery in real time. Once an abnormal situation is found, such as excessive temperature or excessive current, the battery management system will immediately take measures to protect it. However, before the battery temperature is obviously abnormal, the temperature will show an abnormal trend. If the abnormal temperature change trend can be detected in time, the timeliness of problem discovery and solution can be enhanced, thereby reducing the aging and damage of the battery and enhancing the safety of vehicle driving. At present, the technical means in this regard are relatively lacking and need to be improved.

[0004] In view of this, we propose a multifunctional integrated system for data acquisition, transmission and detection of power battery industrial equipment to solve the existing problems. Summary of the invention

[0005] The purpose of the present invention is to provide a multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system to solve the problems raised in the above background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system, applied to the temperature monitoring of power batteries of new energy vehicles, including: a data acquisition module, a data processing module, a battery evaluation module, and an early warning module;

[0007] The data acquisition module acquires the current and temperature of the vehicle power battery; the current of the vehicle power battery includes the measured current and the monitored current; the temperature of the vehicle power battery includes the measured temperature and the monitored temperature;

[0008] The data processing module constructs a mathematical model through the current and temperature of the automobile power battery; the mathematical model includes a B-spline curve, a Bezier curve and a rational Bezier curve; the mathematical model for measuring current and measuring temperature is constructed according to the B-spline curve; the mathematical model for monitoring current and predicting temperature is constructed according to the Bezier curve; the mathematical model for monitoring current and monitoring temperature is constructed according to the rational Bezier curve;

[0009] The battery evaluation module determines whether the battery temperature and its change trend are normal based on the monitored temperature and the control point weights of the rational Bezier curve;

[0010] The early warning module emits an indicator light of a corresponding color according to the evaluation result.

[0011] Furthermore, the specific working steps include:

[0012] S1: Set the normal range of battery temperature. In the experiment, change the battery current and measure the battery temperature. Set the measurement current range and measurement interval current. Starting from the lowest value of the measurement current range, each time the measurement interval current is increased, record the corresponding measurement temperature of the battery until the measurement current is increased to the highest value of the measurement current range.

[0013] S2: Using the measured current and the measured temperature corresponding to the battery as nodes, construct a B-spline curve and obtain the control points of the B-spline curve;

[0014] S3: In practice, a monitoring time range is set, and within the current monitoring time range, the current monitoring current and monitoring temperature of the battery are recorded;

[0015] S4: obtaining a monitoring current range, setting a monitoring interval current, and obtaining a predicted temperature corresponding to the battery through a B-spline curve each time the monitoring interval current is increased from the lowest value of the monitoring current range until the monitoring current is increased to the highest value of the monitoring current range;

[0016] S5: constructing a Bezier curve according to the monitored current and the predicted temperature corresponding to the battery, and obtaining the control point of the Bezier curve;

[0017] S6: constructing a rational Bezier curve according to the monitored current, the monitored temperature and the control points of the Bezier curve, and obtaining the weights of the control points of the rational Bezier curve;

[0018] S7: If the control point weights of the rational Bezier curve do not exceed the set threshold and the monitoring temperature range is within the normal range of the battery temperature, it is determined that the battery temperature is normal; if there is a control point weight of the rational Bezier curve that exceeds the threshold or the monitoring temperature range is not within the normal range of the battery temperature, it is determined that the battery temperature is abnormal;

[0019] S8: The battery temperature indicator light emits light of a corresponding color according to the monitoring result of the battery temperature.

[0020] Furthermore, S1 and S3 are completed by the data acquisition module, S2, S4, S5 and S6 are completed by the data processing module, S7 is completed by the battery evaluation module; and S8 is completed by the early warning module.

[0021] Further, in S1 , the measured temperature is within a normal range of battery temperature.

[0022] Further, in S2, the measured current is the input value of the B-spline curve, and the measured temperature is the output value of the B-spline curve.

[0023] Further, in S3, within the current monitoring time range, if there are multiple monitoring current values ​​of the same value, the temperature of the last value is set as the corresponding monitoring temperature.

[0024] Further, in S5, the monitored current is an input value of the Bezier curve, and the predicted temperature is an output value of the Bezier curve.

[0025] Further, in S6, the monitored current is an input value of the rational Bezier curve, and the monitored temperature is an output value of the rational Bezier curve.

[0026] Further, in S8, if the control point weights of the rational Bezier curve do not exceed the set threshold and the monitored temperature range is within the normal range of the battery temperature, the battery temperature indicator light emits green light; if there is a temperature lower than the minimum value of the normal range of the battery temperature, the battery temperature indicator light emits blue light; if there is a temperature higher than the maximum value of the normal range of the battery temperature, the battery temperature indicator light emits red light.

[0027] Further, in S8, a control point lower than 0.5 is set as a low control point, and a control point higher than 0.5 is set as a high control point. When the monitored temperature range is within the normal range of the battery temperature:

[0028] If the weight of the low control point is higher than the set threshold and the weight of the high control point is not higher than the set threshold, the battery temperature indicator light emits cyan light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is not higher than the set threshold, the battery temperature indicator light emits yellow light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is higher than the set threshold, the battery temperature indicator light emits purple light.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] When the present invention is applied to temperature monitoring of a power battery of a new energy vehicle, a mathematical model for measuring current and temperature is constructed by a B-spline curve, thereby calculating the predicted temperature of the monitored current as a reference, and a mathematical model for monitoring current and predicted temperature is constructed by a Bezier curve, thereby simplifying the relationship between current and temperature, and a mathematical model for monitoring current and temperature is constructed by a rational Bezier curve, and a control point weight is used as an evaluation index of the temperature change trend. The abnormality of the temperature change trend can be accurately detected before the battery temperature is obviously abnormal, thereby enhancing the timeliness of problem discovery and resolution, thereby reducing the degree of aging and damage of the battery and enhancing the safety of vehicle driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a workflow diagram of the multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system of the present invention when applied to temperature monitoring of power batteries of new energy vehicles. DETAILED DESCRIPTION

[0032] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0033] Embodiment 1

[0034] like Figure 1 As shown, the multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system is applied to the temperature monitoring of the power battery of new energy vehicles, including: data acquisition module, data processing module, battery evaluation module and early warning module.

[0035] The specific work steps include:

[0036] S1: Set the normal range of battery temperature. In the experiment, change the battery current and measure the battery temperature. Set the measurement current range and measurement interval current. Starting from the lowest value of the measurement current range, each time the measurement interval current is increased, record the corresponding measurement temperature of the battery until the measurement current is increased to the highest value of the measurement current range.

[0037] S2: Using the measured current and the measured temperature corresponding to the battery as nodes, construct a B-spline curve and obtain the control points of the B-spline curve;

[0038] S3: In practice, a monitoring time range is set, and within the current monitoring time range, the current monitoring current and monitoring temperature of the battery are recorded;

[0039] S4: obtaining a monitoring current range, setting a monitoring interval current, and obtaining a predicted temperature corresponding to the battery through a B-spline curve each time the monitoring interval current is increased from the lowest value of the monitoring current range until the monitoring current is increased to the highest value of the monitoring current range;

[0040] S5: constructing a Bezier curve according to the monitored current and the predicted temperature corresponding to the battery, and obtaining the control point of the Bezier curve;

[0041] S6: constructing a rational Bezier curve according to the monitored current, the monitored temperature and the control points of the Bezier curve, and obtaining the weights of the control points of the rational Bezier curve;

[0042] S7: If the control point weights of the rational Bezier curve do not exceed the set threshold and the monitoring temperature range is within the normal range of the battery temperature, it is determined that the battery temperature is normal; if there is a control point weight of the rational Bezier curve that exceeds the threshold or the monitoring temperature range is not within the normal range of the battery temperature, it is determined that the battery temperature is abnormal;

[0043] S8: The battery temperature indicator light emits light of a corresponding color according to the monitoring result of the battery temperature.

[0044] Among them, S1 and S3 are completed by the data acquisition module, S2, S4, S5 and S6 are completed by the data processing module, S7 is completed by the battery evaluation module; S8 is completed by the early warning module.

[0045] The working principle of the multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system based on the first embodiment is:

[0046] In S1, the set of measured currents is set to I S , the set of measured temperatures is set to T S .

[0047] The algorithm formula for the n-order m-segment B-spline curve is:

[0048]

[0049] Where: P i,n (t) is the value of the i-th segment after the n-th B-spline curve transformation, where i = 1, 2, 3, ..., m; t is the value before the B-spline curve transformation, and for each point of the curve segment, 0 ≤ t ≤ 1 is satisfied, t = 0 represents the beginning node of the i-th segment, and t = 1 represents the end node of the i-th segment; p i+k-1 is the control point of the i-th segment of the B-spline curve; F k,n (t) is a piecewise mixing function of an n-order B-spline curve, where 0≤t≤1, k=0,1,2,...,n.

[0050] The range of the measured current and the measured temperature is relatively wide, so the segmented correction method of the B-spline curve can more accurately reflect the relationship between the measured current and the measured temperature.

[0051] In S2, I S With T S The B-spline curve expression is set to F(IS )·p S =T S , where F(I S ) is I S The set of piecewise mixing functions, p S is the control point set of the B-spline curve, which can be obtained by I S With T S Find p S .

[0052] In S3, the set of monitored currents is set to I M , the set of monitored temperatures is set to T M .

[0053] In S4, the set of predicted temperatures is set to T P , T P =F(I M )·p S , can be obtained by I M With p S Find T P .

[0054] The algorithm formula for N-order Bezier surface:

[0055]

[0056] Where: is the Bessel basis function; p i is the control point of the Bezier curve; u is the value of the Bezier curve before transformation; P(u) is the value of the Bezier curve after transformation.

[0057] The monitoring current and the monitoring temperature reflect the status of the battery within the current monitoring time range. Therefore, the range of the monitoring current is relatively narrow, and the range of the predicted temperature is also narrow. The relationship between the monitoring current and the predicted temperature can be simplified into a Bezier curve to reduce the complexity of the evaluation.

[0058] In S5, I M With T P The Bezier curve expression is set to B(I M )·p M =T P , where B(I M ) is I M The Bessel basis function set, p M is the control point set of the Bezier curve, which can be obtained by I M With T P Find p M .

[0059] The algorithm formula for N-order rational Bezier surface is:

[0060]

[0061] Where: B i N (u) is the Bessel basis function; p i is the control point of the rational Bezier curve; w i is the control point weight of the rational Bezier curve; u is the value of the rational Bezier curve before transformation; P(u) is the value of the rational Bezier curve after transformation.

[0062] For control points above 0.5, the higher the weight, the higher the transformed value; for control points below 0.5, the higher the weight, the lower the transformed value. Therefore, if the weight of the control point is too high, the degree of numerical transformation will be too large.

[0063] In S6, I M With T M The rational Bezier curve expression is set to where w M is the set of control point weights, which can be represented by I M 、p M and T M Find w M .

[0064] In S7, according to T M With w M It can be determined whether the battery temperature and its change trend are normal.

[0065] The RGB color space includes the colors of three channels: red, green, and blue. These three colors are used as the indicator light colors that reflect the battery temperature evaluation results, so that the driver can understand the battery temperature more clearly and intuitively through the indicator light.

[0066] In S8, if the control point weights of the rational Bezier curve do not exceed the set threshold and the monitored temperature range is within the normal range of the battery temperature, the battery temperature indicator light emits green light; if there is a temperature lower than the minimum value of the normal range of the battery temperature, the battery temperature indicator light emits blue light; if there is a temperature higher than the maximum value of the normal range of the battery temperature, the battery temperature indicator light emits red light.

[0067] In the RGB color space, red and green are superimposed as yellow, blue and green are superimposed as cyan, and red and blue are superimposed as purple. These three colors are used as indicator light colors to reflect the evaluation results of the battery temperature change trend, so that the driver can understand the battery temperature change trend more clearly and intuitively through the indicator light.

[0068] In S8, the control point below 0.5 is set as the low control point, and the control point above 0.5 is set as the high control point. When the monitored temperature range is within the normal range of the battery temperature:

[0069] If the weight of the low control point is higher than the set threshold and the weight of the high control point is not higher than the set threshold, the battery temperature indicator light emits cyan light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is not higher than the set threshold, the battery temperature indicator light emits yellow light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is higher than the set threshold, the battery temperature indicator light emits purple light.

[0070] The above-mentioned specific embodiments are only several preferred embodiments of the present invention. Based on the technical solutions of the present invention and the relevant inspirations of the above-mentioned embodiments, those skilled in the art can make various alternative improvements and combinations to the above-mentioned specific embodiments.

Claims

1. Multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system, applied to the temperature monitoring of power batteries of new energy vehicles, characterized by: include: Data acquisition module, data processing module, battery evaluation module, early warning module; The data acquisition module acquires the current and temperature of the vehicle power battery; the current of the vehicle power battery includes the measured current and the monitored current; the temperature of the vehicle power battery includes the measured temperature and the monitored temperature; The data processing module constructs a mathematical model through the current and temperature of the automobile power battery; the mathematical model includes a B-spline curve, a Bezier curve and a rational Bezier curve; the mathematical model for measuring current and measuring temperature is constructed according to the B-spline curve; the mathematical model for monitoring current and predicting temperature is constructed according to the Bezier curve; the mathematical model for monitoring current and monitoring temperature is constructed according to the rational Bezier curve; The battery evaluation module determines whether the battery temperature and its change trend are normal based on the monitored temperature and the control point weights of the rational Bezier curve; The early warning module emits an indicator light of a corresponding color according to the evaluation result.

2. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 1 is characterized in that: The specific work steps include: S1: Set the normal range of battery temperature. In the experiment, change the battery current and measure the battery temperature. Set the measurement current range and measurement interval current. Starting from the lowest value of the measurement current range, each time the measurement interval current is increased, record the corresponding measurement temperature of the battery until the measurement current is increased to the highest value of the measurement current range. S2: Using the measured current and the measured temperature corresponding to the battery as nodes, construct a B-spline curve and obtain the control points of the B-spline curve; S3: In practice, a monitoring time range is set, and within the current monitoring time range, the current monitoring current and monitoring temperature of the battery are recorded; S4: obtaining a monitoring current range, setting a monitoring interval current, and obtaining a predicted temperature corresponding to the battery through a B-spline curve each time the monitoring interval current is increased from the lowest value of the monitoring current range until the monitoring current is increased to the highest value of the monitoring current range; S5: constructing a Bezier curve according to the monitored current and the predicted temperature corresponding to the battery, and obtaining the control point of the Bezier curve; S6: constructing a rational Bezier curve according to the monitored current, the monitored temperature and the control points of the Bezier curve, and obtaining the weights of the control points of the rational Bezier curve; S7: If the control point weights of the rational Bezier curve do not exceed the set threshold and the monitoring temperature range is within the normal range of the battery temperature, it is determined that the battery temperature is normal; if there is a control point weight of the rational Bezier curve that exceeds the threshold or the monitoring temperature range is not within the normal range of the battery temperature, it is determined that the battery temperature is abnormal; S8: The battery temperature indicator light emits light of a corresponding color according to the monitoring result of the battery temperature.

3. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: S1 and S3 are completed by the data acquisition module, S2, S4, S5 and S6 are completed by the data processing module, S7 is completed by the battery evaluation module; S8 is completed by the early warning module.

4. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: In S1 , the measured temperature is within the normal range of battery temperature.

5. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: In S2, the measured current is the input value of the B-spline curve, and the measured temperature is the output value of the B-spline curve.

6. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: In S3, within the current monitoring time range, if there are multiple monitoring current values ​​of the same value, the temperature of the last value is set as the corresponding monitoring temperature.

7. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: In S5 , the monitored current is the input value of the Bezier curve, and the predicted temperature is the output value of the Bezier curve.

8. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized by: In S6 , the monitored current is an input value of the rational Bezier curve, and the monitored temperature is an output value of the rational Bezier curve.

9. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized by: In S8, if the control point weights of the rational Bezier curve do not exceed the set threshold and the monitored temperature range is within the normal range of the battery temperature, the battery temperature indicator light emits green light; if there is a temperature lower than the minimum value of the normal range of the battery temperature, the battery temperature indicator light emits blue light; if there is a temperature higher than the maximum value of the normal range of the battery temperature, the battery temperature indicator light emits red light.

10. The multifunctional power battery industrial equipment data acquisition, transmission and detection integrated system according to claim 2 is characterized in that: In S8, the control point below 0.5 is set as the low control point, and the control point above 0.5 is set as the high control point. When the monitored temperature range is within the normal range of the battery temperature: If the weight of the low control point is higher than the set threshold and the weight of the high control point is not higher than the set threshold, the battery temperature indicator light emits cyan light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is not higher than the set threshold, the battery temperature indicator light emits yellow light; if the weight of the high control point is higher than the set threshold and the weight of the low control point is higher than the set threshold, the battery temperature indicator light emits purple light.

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